Prognostic marker

Abstract

The present invention relates to a method for determining or predicting the prognosis and survival of a subject having prostate cancer comprising determining the levels of at least three lipid biomarkers in a biological sample obtained from said subject, and compositions and kits for use in said method, wherein the at least three lipid biomarkers are selected from the group consisting of ceramide (d18: 1 / 18: 0), ceramide (d18: 1 / 22: 0), ceramide (d18: 1 / 24: 0), ceramide (d18: 1 / 24: 1), ceramide (d20: 1 / 24: 0), ceramide (d20: 1 / 24: 1), phosphatidylcholine (16: 0 / 16: 0) and sphingomyelin (d18: 1 / 16: 0).

Description

Field of the Invention

[0001] The present invention generally relates to biomarkers for prostate cancer. More specifically, the present invention relates to lipid biomarkers and their use in kits, compositions, and methods for determining or predicting the prognosis and survival of subjects having prostate cancer, particularly metastatic castration-resistant prostate cancer. Background of the Invention

[0003] Prostate cancer is one of the most common cancers and is the fifth leading cause of cancer-related death in men globally. Although there have been recent advances in the treatment of prostate cancer, particularly metastatic castration-resistant prostate cancer, due to the development of androgen receptor signaling inhibitors and other therapies, the utility of these therapies is limited by the development of resistance. In this regard, intrinsic resistance affects approximately 20 - 30% of subjects, and all patients who receive these therapies will eventually develop acquired resistance. Thus, there is a need for new therapies to treat prostate cancer and for customized treatment regimens that can avoid the development of resistance.

[0004] It is known that sphingolipids such as ceramides regulate various biological processes including cell growth. Ceramides are known to promote tumor growth and metastasis through the ceramide - sphingosine - 1 - phosphate signaling axis in cancer cells and immune cells. Recently, it has been found that elevated circulating sphingolipid levels are associated with shorter metastasis - free survival in localized prostate cancer, early androgen deprivation therapy failure in metastatic hormone - sensitive prostate cancer, and shorter progression - free survival or overall survival after administration of docetaxel or androgen receptor signaling inhibitors in patients with metastatic castration - resistant prostate cancer. Thus, sphingolipids play an important role in the progression of prostate cancer and are viable targets for prostate cancer treatment. However, since not all patients will benefit from such treatment, there is a need for methods to identify subjects having prostate cancer who will benefit from therapies targeting lipids such as sphingolipids.

[0005] A circulating three - lipid signature (3LS) has been previously described that is associated with shorter overall survival in patients with metastatic castration - resistant prostate cancer. However, high - throughput LC - MS methods for detecting the lipids, ceramide (d18:1 / 24:1), sphingomyelin (d18:2 / 16:0), and phosphatidylcholine (16:0 / 16:0) have many drawbacks, including a lack of assay standardization and validation against regulatory or industry standards, and a lack of reproducibility of the LC - MS method between laboratories. In addition, assays for detecting the three - lipid signature can only be performed retrospectively and are not available for prospectively identifying men with prostate cancer who may benefit from therapies targeting lipids. There is a need for accurate and reproducible methods to determine the prognosis and survival of subjects having prostate cancer. SUMMARY OF THE INVENTION

[0007] The present invention is in part based on the discovery that abnormal lipid levels can be used to identify subjects with prostate cancer who are likely to be resistant to conventional therapies (e.g., therapies using chemotherapy or androgen receptor signaling inhibitors) and thus have a poor prognosis and reduced overall survival. Accordingly, the inventors have envisioned that levels of specific combinations of lipids (e.g., ceramides) can be used in kits, compositions, and methods for determining or predicting the prognosis and survival of subjects with prostate cancer, particularly metastatic castration-resistant prostate cancer.

[0008] In one aspect, there is provided a method for determining an indicator for determining the prognosis of a subject with prostate cancer, the method comprising the steps consisting essentially of the following steps:

[0009] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0010] b) using the biomarker levels to determine the indicator.

[0011] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0012] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In specific embodiments, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0013] In other embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein; particularly the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, step a) further comprises determining the levels of total cholesterol and triglycerides.

[0014] In a particular embodiment, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0015] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0016] In certain embodiments, poor prognosis includes disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In certain embodiments, good prognosis includes no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0017] In a specific embodiment, if the following situations occur, the indicator indicates the possibility of a poor prognosis: the level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes. In certain embodiments, step a) further includes determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, and if the following situations occur, the indicator indicates the possibility of a poor prognosis: the level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of high-density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0018] In certain embodiments, the method further includes applying a function to the biomarker levels to produce at least one functionalized biomarker level and using the at least one functionalized biomarker level to determine the indicator. In a particular embodiment, the function includes at least one of the following: (a) multiplying the biomarker level; (b) dividing the biomarker level; (c) adding the biomarker level; and (d) subtracting the biomarker level.

[0019] In certain embodiments, the method further includes combining the biomarker levels and / or the functionalized biomarker levels to provide a composite score and using the composite score to determine the indicator. In a particular embodiment, the biomarker levels and / or the functionalized biomarker levels are combined by adding, multiplying, subtracting, and / or dividing the biomarker levels and / or the functionalized biomarker levels.

[0020] In certain embodiments, the method further comprises analyzing the biomarker level, functionalized biomarker level, or composite score with reference to a corresponding reference biomarker level range or cut-off level, functionalized biomarker level range or cut-off level, or reference composite score range or cut-off score to determine the metric.

[0021] In a specific embodiment, the method for determining the metric comprises: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to the value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglycerides, or a functionalized level of any one of the foregoing levels. In certain embodiments, the method comprises determining the metric using Formula I:

[0022] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L]+[-0.2783 x the level of total cholesterol in mmol / L]+[-0.2240 x the level of triglycerides in mmol / L]+[-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

[0023] In a specific embodiment, a score calculated using Formula I that is greater than or equal to -1.1903 indicates a likelihood of poor prognosis, and a score calculated using Formula I that is less than -1.1903 indicates a likelihood of good prognosis.

[0024] In certain embodiments, the subject has undergone, is undergoing, or is initiating a treatment regimen for treating prostate cancer, such as chemotherapy and / or administration of an androgen receptor signaling inhibitor.

[0025] In certain embodiments, a prostate cancer treatment, such as a lipid-targeted therapy, including administration of evolocumab or opaganib, is administered to a subject determined to have a poor prognosis.

[0026] In certain embodiments, the level of the biomarker is a quantitative level. In certain embodiments, the level of the biomarker is determined using mass spectrometry; in particular, wherein the level of the biomarker is determined using absolute quantification.

[0027] In another aspect, provided is a method for determining or predicting the prognosis of a subject having prostate cancer, the method comprising the steps of, consisting of, or consisting essentially of the following steps:

[0028] a) Determine the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0);

[0029] b) Compare the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and

[0030] c) Determine or predict the prognosis of the subject based on the determined levels of the biomarkers and the comparison.

[0031] In certain embodiments, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0032] In certain embodiments, predicting the prognosis includes predicting subject survival.

[0033] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly wherein the prostate cancer is metastatic cancer.

[0034] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0035] In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; particularly wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides. In certain embodiments, step a) further comprises determining the levels of total cholesterol and triglycerides.

[0036] In a specific embodiment, step a) includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0037] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0038] In certain embodiments, poor prognosis includes disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In such embodiments, good prognosis includes no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0039] In a particular embodiment, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of poor prognosis if: the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample. In other embodiments, step a) further includes determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of poor prognosis if: the level of total cholesterol is lower than the level in the reference sample; the level of triglycerides is lower than the level in the reference sample; and / or the level of high density lipoprotein is lower than the level in the reference sample.

[0040] In certain embodiments, the method includes determining the prognosis of the subject as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglycerides, or a functionalized level of any of the foregoing levels.

[0041] In a specific embodiment, the method includes determining the prognosis of the subject using Formula I:

[0042] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglycerides in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

[0043] In such embodiments, a score calculated using Formula I that is greater than or equal to -1.1903 indicates a likelihood of poor prognosis, and a score calculated using Formula I that is less than -1.1903 indicates a likelihood of good prognosis.

[0044] In certain embodiments, the subject has undergone, is undergoing, or is initiating a treatment regimen for prostate cancer, such as chemotherapy and / or administration of an androgen receptor signaling inhibitor.

[0045] In certain embodiments, prostate cancer treatment, such as lipid-targeted therapy, e.g., evolocumab or opaganib, is administered to a subject determined to have a poor prognosis.

[0046] In certain embodiments, the level of the biomarker is a quantitative level.

[0047] In a particular embodiment, the level of the biomarker is determined using mass spectrometry; in particular, absolute quantification is used.

[0048] In another aspect, there is provided a method for determining or predicting the likelihood of survival of a subject having prostate cancer, the method comprising the steps consisting of or consisting essentially of the following steps:

[0049] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0050] b) comparing the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and

[0051] c) Determine or predict the likelihood of survival of the subject based on the determined biomarker levels and the comparison.

[0052] In certain embodiments, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0053] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0054] In certain embodiments, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0055] In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; particularly the levels of one or more biomarkers selected from total cholesterol and triglycerides. In certain embodiments, step a) further comprises determining the levels of total cholesterol and triglycerides.

[0056] In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0057] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0058] In certain embodiments, survival comprises no disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0059] In certain embodiments, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and a subject has a likelihood of non - survival if: the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample. In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein, and a subject has a likelihood of non - survival if: the level of total cholesterol is lower than the level in the reference sample; the level of triglycerides is lower than the level in the reference sample; and / or the level of high - density lipoprotein is lower than the level in the reference sample.

[0060] In some embodiments, the method comprises determining the likelihood of survival as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1) and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels. In certain embodiments, the method comprises determining the likelihood of survival using Equation I:

[0061] [10.0506x the level of ceramide (d18:1 / 18:0) in mg / L]+[-0.2783x the level of total cholesterol in mmol / L]+[-0.2240x the level of triglycerides in mmol / L]+[-0.2979x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Equation I.

[0062] In a specific embodiment, a score calculated using Equation I that is greater than or equal to - 1.1903 indicates a likelihood of non - survival, and a score calculated using Equation I that is less than - 1.1903 indicates a likelihood of survival.

[0063] In some embodiments, the subject has undergone, is undergoing, or is initiating a treatment regimen for prostate cancer, such as chemotherapy and / or administration of an androgen receptor signaling inhibitor.

[0064] In certain embodiments, a prostate cancer treatment, such as a lipid-targeted therapy, e.g., evolocumab or opaganib, is administered to a subject determined to have a likelihood of non-survival.

[0065] In certain embodiments, the level of the biomarker is a quantitative level. In a particular embodiment, the level of the biomarker is determined using mass spectrometry; in particular, using absolute quantification.

[0066] In yet another aspect, a method for determining an indicator for determining the likelihood of survival of a subject having prostate cancer is provided, the method comprising the steps of, consisting of, or consisting essentially of the following steps:

[0067] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0068] b) using the biomarker levels to determine the indicator.

[0069] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; in particular, metastatic cancer.

[0070] In a particular embodiment, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a specific embodiment, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0071] In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein; particularly the levels of one or more biomarkers selected from total cholesterol and triglycerides. In specific embodiments, step a) further comprises determining the levels of total cholesterol and triglycerides.

[0072] In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0073] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0074] In certain embodiments, survival comprises no disease - related death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0075] In certain embodiments, the metric indicates a likelihood of non - survival if: the level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes. In other embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein, and the metric indicates a likelihood of non - survival if: the level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of high - density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0076] In certain embodiments, the method further comprises applying a function to the biomarker levels to produce at least one functionalized biomarker level and using the at least one functionalized biomarker level to determine the metric; in particular, wherein the function comprises at least one of the following: (a) multiplying the biomarker level; (b) dividing the biomarker level; (c) adding the biomarker level; and (d) subtracting the biomarker level. In certain embodiments, the method further comprises combining the biomarker levels and / or the functionalized biomarker levels to provide a composite score and using the composite score to determine the metric; in particular, wherein the biomarker levels and / or the functionalized biomarker levels are combined by adding, multiplying, subtracting, and / or dividing the biomarker levels and / or the functionalized biomarker levels.

[0077] In certain embodiments, the method further comprises analyzing the biomarker level, functionalized biomarker level, or composite score with reference to a corresponding reference biomarker level range or cut-off level, functionalized biomarker level range or cut-off level, or reference composite score range or cut-off score to determine the metric.

[0078] In certain embodiments, the method comprises determining the metric as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to the value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any one of the foregoing levels.

[0079] In specific embodiments, the method comprises determining the metric using Equation I:

[0080] [10.0506 x level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x level of total cholesterol in mmol / L] + [-0.2240 x level of triglycerides in mmol / L] + [-0.2979 x (level of ceramide (d18:1 / 24:0) in mg / L / level of ceramide (d18:1 / 24:1) in mg / L)] Equation I.

[0081] In such embodiments, a score calculated using Equation I that is greater than or equal to -1.1903 indicates a likelihood of non-survival, and a score calculated using Equation I that is less than -1.1903 indicates a likelihood of survival.

[0082] In certain embodiments, the subject has undergone, is undergoing, or is initiating a treatment regimen for treating prostate cancer, such as chemotherapy and / or administration of an androgen receptor signaling inhibitor.

[0083] In certain embodiments, prostate cancer treatment is administered to a subject determined to have a likelihood of non-survival; in particular, wherein the treatment comprises administering a lipid-targeted therapy, such as evolocumab or opaganib.

[0084] In certain embodiments, the level of the biomarker is a quantitative level. In specific embodiments, the level of the biomarker is determined using mass spectrometry; particularly using absolute quantification.

[0085] In another aspect, the present invention provides a method for treating or inhibiting the progression of prostate cancer in a subject, the method comprising the steps consisting essentially of or consisting of the following steps:

[0086] a) Identify prostate cancer subjects with poor prognosis using the method of the present invention; and

[0087] b) Administer a prostate cancer treatment.

[0088] In certain embodiments, the treatment is a lipid-targeted therapy, such as evolocumab or opaganib.

[0089] In another aspect, further encompassed is a composition comprising a biological sample from a subject with prostate cancer and isotopically labeled lipids corresponding to each of at least three lipid biomarkers in the sample, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

[0090] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0091] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a specific embodiment, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0092] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0093] In another aspect, there is provided a kit for determining or predicting the prognosis of a subject having prostate cancer, which comprises one or more reagents for determining the levels of at least three lipid biomarkers in a biological sample from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

[0094] In a specific embodiment, the one or more reagents include isotopically labeled lipids corresponding to each of the at least three lipid biomarkers in the sample.

[0095] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0096] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0097] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0098] In another aspect, there is provided a device for determining an indicator used in evaluating the prognosis of a subject having prostate cancer, the device comprising at least one electronic processing device, the device:

[0099] a) Determine the biomarker levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0100] b) Use the obtained biomarker levels to determine the metric.

[0101] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0102] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a particular embodiment, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0103] In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; particularly the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, step a) further comprises determining the levels of total cholesterol and triglycerides.

[0104] In a particular embodiment, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0105] In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0106] In another aspect, there is provided a method for selecting a subject with prostate cancer for treatment with lipid-targeted therapy, the method comprising the steps of, consisting of, or consisting essentially of: identifying a subject with prostate cancer having a poor prognosis using the method of the present invention.

[0107] In certain embodiments, the treatment comprises evolocumab or opaganib.

[0108] There is further provided a method for monitoring the response of a subject with prostate cancer to a therapeutic treatment, the method comprising the steps of, consisting of, or consisting essentially of:

[0109] a) determining the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the first biological sample is obtained before or after initiation of treatment;

[0110] b) determining a first metric using the biomarker levels;

[0111] c) determining the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained at a time point after initiation of the therapeutic treatment and after the first biological sample;

[0112] d) determining a second metric using the biomarker levels; and

[0113] e) comparing the metrics in the first and second biological samples;

[0114] wherein a change in the metric between the first and second biological samples indicates whether the subject is responsive to the therapeutic treatment.

[0115] In another aspect, there is provided a method for monitoring the prognosis of a subject having prostate cancer, the method comprising, consisting essentially of, or consisting of the following steps:

[0116] a) determining the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0);

[0117] b) determining a first metric using the biomarker levels;

[0118] c) determining the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained at a time point after the first biological sample is obtained;

[0119] d) determining a second metric using the biomarker levels; and

[0120] e) comparing the metrics in the first and second biological samples;

[0121] wherein a change in the metric between the first and second biological samples indicates a change in the prognosis of the subject.

[0122] In certain embodiments, the prostate cancer is castration-resistant prostate cancer; particularly metastatic cancer.

[0123] In certain embodiments, the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarkers in steps a) and c) are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0124] In certain embodiments, steps a) and c) further comprise determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein; in particular, the levels of one or more biomarkers selected from total cholesterol and triglycerides. In certain embodiments, steps a) and c) further comprise determining the levels of total cholesterol and triglycerides.

[0125] In certain embodiments, steps a) and c) comprise determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0126] In certain embodiments, the biological sample is blood, serum, or plasma; in particular, plasma. Brief Description of the Drawings

[0128] Figure 1 is the LC-MS chromatogram of each lipid analyte of interest.

[0129] Figure 2 is a series of scatter plots and scatter plot matrices comparing targeted assays and high-throughput assays. Figure 2A is a series of scatter plots of the correlations between individual lipids in targeted assays and high-throughput assays. Figure 2B is a scatter plot matrix of lipid species pairs performed on targeted assays using Pearson's correlation coefficient. Abbreviations: Cer, ceramide; R, Pearson's correlation coefficient; and HDL, high density lipoprotein.

[0130] Figure 3A series of graphs showing the Kaplan Meier survival analysis of overall survival of PCPro in the following patients: (A) discovery cohort, (B) validation cohort, (C) those in the validation cohort treated with ARSI, (D) those in the validation cohort treated with taxane chemotherapy, (E) those in the validation cohort treated with first-line therapy, and (F) those in the validation cohort treated with second-line therapy. Abbreviations: ARSI, androgen receptor signaling inhibitor; HR, hazard ratio; mo, months; OS, overall survival; and NR, not reached.

[0131] Figure 4 A graph showing the correlation of PCPro with the tri-lipid prognostic signature in the discovery cohort.

[0132] Figure 5 A graph showing the correlation of PCPro with the tri-lipid prognostic signature in the validation cohort. DETAILED DESCRIPTION OF THE INVENTION

[0134] 1. Definitions

[0135] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are described. For the purposes of the present invention, the following terms are defined below.

[0136] The citation of any prior publication (or information obtained therefrom) or any known matter in this specification does not constitute and should not be regarded as an admission or acknowledgment or any form of implication that the prior publication (or information obtained therefrom) or known matter forms part of the common general knowledge in the field to which this specification pertains.

[0137] The articles "a" and "an" are used herein to denote one or more than one (i.e., at least one) of the grammatical object of the article. By way of example, "an element" refers to one element or more than one element.

[0138] "About" means a quantity, level, value, number, frequency, percentage, dimension, size, amount, weight or length that varies by at most 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or 1% from a reference quantity, level, value, number, frequency, percentage, dimension, size, amount, weight or length.

[0139] The term "agent" includes compounds that induce a desired pharmacological and / or physiological effect. The term also encompasses pharmaceutically acceptable and pharmacologically active ingredients of those compounds specifically mentioned herein, including, but not limited to, salts, esters, amides, prodrugs, active metabolites, analogs, etc. When the above terms are used, it should be understood that this includes the active agent itself as well as pharmaceutically acceptable, pharmacologically active salts, esters, amides, prodrugs, metabolites, analogs, etc. The term "agent" should not be construed narrowly, but extends to small molecules, proteinaceous molecules (such as peptides, polypeptides, and proteins), and compositions containing them and genetic molecules (such as RNA, DNA, their mimetics, and chemical analogs), as well as cell agents.

[0140] The term "and / or" as used herein means and encompasses any and all possible combinations of one or more of the related listed items, as well as the case where there is no combination when interpreted in the alternative (or).

[0141] The term "biomarker" as used herein refers to a naturally occurring biomolecule that is present at different concentrations in a subject and can be used to predict the prognosis or outcome of a disease or disorder (such as prostate cancer). For example, a biomarker can be a lipid that is present in higher or lower amounts in a biological sample (such as blood, serum, or plasma) of a subject with prostate cancer (especially metastatic castration-resistant prostate cancer). Suitable biomarkers include, for example, ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high-density lipoprotein.

[0142] The term "composite score" as used herein refers to a collection of biomarker levels measured in a subject sample, optionally combined with one or more patient clinical parameters or signs.

[0143] Throughout this specification and the following claims, unless the context otherwise requires, the word "comprise" and variations such as "comprises" and "comprising" are to be interpreted as implying the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps. Thus, the use of the term "comprise" etc. indicates that the listed integers are essential or mandatory, but that other integers are optional and may or may not be present. "Consisting of" is intended to include, but not be limited to, what follows the phrase "consisting of". Thus, the phrase "consisting of" indicates that the listed elements are essential or mandatory and that no other elements may be present. "Consisting essentially of" means including any elements listed after the phrase, and limited to other elements that do not interfere with or contribute to the activity or function specified for the listed elements. Thus, the phrase "consisting essentially of" indicates that the listed elements are essential or mandatory, but that other elements are optional and may or may not be present, depending on whether they affect the activity or function of the listed elements.

[0144] As used herein, the terms "associated" or "associated with" and like terms denote a statistical association between two or more things, such as events, characteristics, outcomes, numbers, data sets, etc., which may be referred to as "variables". It should be understood that the things may be of different types. Variables are typically represented as numbers (e.g., measurements, values, probabilities or risks), where a positive association means that as one variable increases, the other variable also increases, and a negative association (also referred to as an inverse association) means that as one variable increases, the other variable decreases. In various embodiments, associating a biomarker or biomarker signature with a prognosis (e.g., a favorable outcome or good prognosis such as no disease progression and / or no disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor, or an unfavorable outcome or poor prognosis such as disease progression and / or disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor) includes determining the level of at least one biomarker in a biological sample from a subject having a specified prognosis or known not to have that prognosis. In a specific embodiment, a receiver operating characteristic (ROC) curve is used to associate a profile of biomarker levels with an overall probability or a specific outcome.

[0145] As used herein, the term "cut-off value" can be an absolute level, a relative level, or a level or amount (or concentration) of an amount (or concentration) that indicates whether a subject with prostate cancer has a specific prognosis (e.g., a good outcome or a good prognosis such as no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor, or a poor outcome or a poor prognosis such as disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor). Depending on the biomarker or combination of biomarkers, a subject with prostate cancer is considered to have a specific prognosis if the biomarker level, detected and determined separately, is below the cut-off value, or if the biomarker level, detected and determined separately, is above the cut-off value.

[0146] In the context of treating or inhibiting the development of a disorder, an "effective amount" means an amount of an agent, compound, or composition that, when administered to an individual in need of such treatment or prevention, either as a single dose or as part of a series of doses, is effective to prevent the occurrence of symptoms of the disorder, control such symptoms, and / or treat existing symptoms of the disorder. The effective amount will vary depending on the health and physical condition of the individual to be treated, the taxonomic group of the individual to be treated, the formulation of the composition, the assessment of the medical condition, and other relevant factors. It is contemplated that the amount will fall within a relatively wide range that can be determined by routine experimentation.

[0147] As used herein, the term "higher" with reference to a biomarker measurement means a statistically significant and measurable difference in the biomarker level as compared to another biomarker level or a control level, wherein the biomarker measurement is greater than the other biomarker level or the control level. The difference is suitably at least about 10%, at least about 20%, at least about 30%, at least about 40%, or at least about 50%.

[0148] As used herein, the terms "increase" or "augment" with reference to a biomarker level mean a statistically significant and measurable increase in the biomarker level as compared to another biomarker level or a control level. The increase is suitably an increase of at least about 10%, at least about 20%, at least about 30%, at least about 40%, or at least about 50%.

[0149] As used herein, the term "metric" refers to a result or manifestation of a result, including any information, number (such as biomarker levels, including functionalized biomarker levels and composite scores), ratio, signal, symbol, label, or annotation, based on which a person skilled in the art can estimate and / or determine the prognosis of a subject with a given disease or disorder, or the survival of a subject with a given disease or disorder. In the context of the present invention, the "metric" can optionally be used in combination with other clinical features to effect the determination of the prognosis or survival of a subject with prostate cancer. The fact that such a metric "is determined" does not imply that the metric is 100% accurate. A skilled clinician can use the metric in combination with other clinical parameters or signs to effect the prognosis or survival determination.

[0150] As used herein in a broad sense, the term "label" refers to a reagent that can provide a detectable signal either directly or by interacting with one or more additional members of a signal generation system, and that has been artificially added, linked, or attached to a molecule by chemical manipulation. A label can be visual, optical, photon, electronic, acoustic, photoacoustic, mass, electrochemistry, electro-optic, spectral, enzymatic, or otherwise chemically, biochemically, hydrodynamically, electrically, or physically detectable. In a specific embodiment, the molecules disclosed herein such as lipid biomarkers are detectable molecular labels selected from isotopes, radioisotopes, fluorescent compounds, bioluminescent compounds, chemiluminescent compounds, metal chelators, or enzymes. Examples of labels include, but are not limited to, isotopes (such as deuterium, 13 C, 15 N, etc.), radioisotopes (such as 3 H, 14 C, 35 S, 125 I, and 131 I), fluorescent labels (such as FITC, rhodamine, or lanthanide phosphors), luminescent labels such as luminol, enzyme labels (such as horseradish peroxidase, β-galactosidase, luciferase, alkaline phosphatase, and acetylcholinesterase), biotin groups (which can be detected by labeled avidin, e.g., streptavidin, which contains a fluorescent marker or enzyme activity detectable by optical or calorimetric methods), predetermined polypeptide epitopes recognized by a secondary reporter (such as leucine zipper pair sequences, binding sites for secondary antibodies, metal-binding domains, and epitope tags).

[0151] The "level" or "levels" of a biomarker used herein are the detectable biomarker levels in a sample. The levels can be measured by methods known to those of skill in the art as well as the methods disclosed herein (e.g., mass spectrometry). These terms encompass quantitative levels (e.g., weight or molar), semi - quantitative levels, relative levels (e.g., weight % or molar % within a certain category), concentrations, etc. Thus, these terms encompass the absolute or relative levels or concentrations of a biomarker in a sample. The levels may be raw levels or normalized levels, or may be mathematically transformed biomarker levels. Alternatively, a biomarker level can be a functionalized biomarker level, which is a level functionalized from one or more measured biomarker levels, e.g., by applying a function to one or more measured biomarker levels. The biomarker level can be in any suitable form, depending on the manner in which the level is determined. For example, high - throughput techniques (such as mass spectrometry, immunoassays, or any combination of such techniques, especially mass spectrometry) can be used to determine biomarker levels.

[0152] In this document, the nomenclature standards of the art are used to refer to lipids. For example, the common name of the lipid type and the side - chain structure in parentheses (format: (number of carbon atoms: number of double - bond equivalents)) are used herein to refer to a specific lipid. Two side - chains are defined where appropriate. The meaning of the "d" nomenclature in parentheses indicates 1,3 - dihydroxy. For example, ceramide (d18:1 / 24:0) is used herein to denote N - tetracosanoyl - D - erythro - sphingosine.

[0153] As used herein, the term "lower" with reference to a biomarker measurement value indicates a statistically significant and measurable difference in the biomarker level compared to another biomarker level or a control level, where the biomarker measurement value is less than the other biomarker level or the control level. The difference is suitably at least about 10%, at least about 20%, at least about 30%, at least about 40%, or at least about 50%.

[0154] The term "normalization" and its derivatives used herein, when used in conjunction with biomarker measurements across samples and time, refer to mathematical methods including, but not limited to, multiples of the median (MoM), standard - deviation normalization, sigmoid normalization, etc., the purpose of which is that these normalized values allow for the comparison of corresponding normalized values from different data sets in a way that eliminates or minimizes differences and overall effects.

[0155] As used herein, the term "prognosis" refers to a prediction of the likely course and outcome of a clinical condition or disease. Prognosis is typically made by assessing factors or symptoms of the disease that indicate a favorable or unfavorable course or outcome. One of skill in the art will understand that the term "prognosis" indicates an increased probability that a certain course or outcome (e.g., disease progression, no disease progression, death, survival, etc.) will occur; that is, a subject exhibiting the condition is more likely to experience a certain course or outcome than those individuals who do not exhibit the given condition. In certain embodiments, the prognosis also refers to the ability to exhibit a positive or negative response to a treatment or other treatment regimen for a subject's disease or condition. In certain embodiments, the prognosis refers to the ability to predict the presence or attenuation of disease / condition-related symptoms. The prediction method can include classifying a subject or a sample obtained from the subject into one of a plurality of categories, where the categories are associated with different probabilities that the subject will experience a particular outcome. For example, the categories can be low risk and high risk, where a subject in the low risk category has a lower likelihood of experiencing an adverse outcome (e.g., within a given time period such as 6 months, 1 year, 18 months, 2 years, or 3 years) than a subject in the high risk category. The adverse outcome can be, for example, disease progression or death due to the disease.

[0156] As used herein, the terms "reduced" or "decreased" in reference to a biomarker level mean a statistically significant and measurable decrease in the biomarker level as compared to another biomarker level or a control level. The reduction is suitably at least about 10%, at least about 20%, at least about 30%, at least about 40%, or at least about 50% reduction.

[0157] As used herein, the term "subject" refers to a mammalian subject having a prostate gland for which a prognosis or survival is to be evaluated, or which is in need of treatment or prophylaxis. Suitable subjects include, but are not limited to, primates; domestic animals such as sheep, cattle, horses, deer, donkeys, and pigs; laboratory test animals such as rabbits, mice, rats, guinea pigs, and hamsters; companion animals such as cats and dogs; and captive wild animals such as foxes, deer, and dingoes. Specifically, the subject is a human.

[0158] As used herein, the terms "treatment", "treating", etc. refer to obtaining a desired pharmacological and / or physiological effect. For the purposes of partially or completely curing a disease, disorder or condition and / or adverse effects attributable to a disease, disorder or condition, the effect can be therapeutic. These terms also encompass any treatment of a condition, disorder or disease in a subject, particularly a human, and include: (a) inhibiting a disease, disorder or condition, i.e., preventing its development; or (b) alleviating a disease, disorder or condition, i.e., causing regression of the disease, disorder or condition. In addition, the term includes palliative treatment, i.e., treatment aimed at alleviating symptoms rather than curing a disease, disorder or condition; prophylactic treatment, i.e., treatment aimed at minimizing or partially or completely inhibiting the development of a related disease, disorder or condition; and supportive treatment, i.e., treatment used to supplement another specific therapy aimed at improving a related disease, disorder or condition. It should be understood that although treatment is aimed at curing, improving, stabilizing or preventing a disease, pathological condition or disorder, it does not necessarily result in a cure, improvement, stabilization or prevention in practice.

[0159] As used herein, the term "treatment regimen" refers to prophylactic and / or therapeutic (i.e., after the onset of a particular condition) treatment, unless the context clearly indicates otherwise. The term "treatment regimen" encompasses natural substances and pharmaceutical agents (i.e., "drugs") as well as any other treatment regimen, including, but not limited to, dietary treatment, physical therapy or exercise regimens, surgical intervention, radiation therapy, chemotherapy, immunotherapy, lipid-targeted therapy, and combinations thereof. Desirable effects of treatment include reducing the rate of disease progression, improving or alleviating the disease state, and reducing or improving the prognosis. For example, an individual is successfully "treated" if one or more symptoms associated with prostate cancer are reduced or eliminated, including, but not limited to, reducing the proliferation of cancer cells (or destroying cancer cells), alleviating symptoms caused by the disease, increasing the quality of life of an individual suffering from the disease, reducing the dosage of other drugs required to treat the disease, and / or prolonging the survival of the individual.

[0160] Unless otherwise specifically stated, each embodiment described herein applies, with necessary modifications in detail, to each and every embodiment.

[0161] 2. Abbreviations

[0162] The following abbreviations are used throughout this application:

[0163] Ceramide (d18:1 / 18:0) = N-stearoyl-D-erythro-sphingosine

[0164] Ceramide (d18:1 / 22:0) = N-behenoyl-D-erythro-sphingosine

[0165] Ceramide (d18:1 / 24:0) = N-Tetracosanoyl-D-erythro-sphingosine

[0166] Ceramide (d18:1 / 24:1) = N-Tetracosenoyl-D-erythro-sphingosine

[0167] Ceramide (d20:1 / 24:0) = N-Tetracosanoyl-D-erythro-sphingosine (C20 base)

[0168] Ceramide (d20:1 / 24:1) = N-Tetracosenoyl-D-erythro-sphingosine (C20 base)

[0169] Phosphatidylcholine (16:0 / 16:0) = Dipalmitoyl phosphatidylcholine

[0170] Sphingomyelin (d18:1 / 16:0) = N-Palmitoyl-D-erythro-sphingosylphosphorylcholine

[0171] BuMe = Mixture of 1-butanol and methanol

[0172] Cer = Ceramide

[0173] HDL = High-density lipoprotein

[0174] HPLC = High performance liquid chromatography

[0175] HR = Hazard ratio

[0176] LASSO = Least absolute shrinkage and selection operator

[0177] LC-MS = Liquid chromatography - Mass spectrometry

[0178] NR = Not reached

[0179] OS = Overall survival

[0180] PC = Phosphatidylcholine

[0181] R = Pearson correlation coefficient

[0182] R 2 = Coefficient of determination

[0183] ROC = Receiver operating characteristic

[0184] SM = Sphingomyelin

[0185] 3. Biomarkers for determining the prognosis of subjects with prostate cancer

[0186] The present invention is based on the following discovery: Abnormal lipid levels can be used to identify subjects with prostate cancer who may be resistant to conventional therapies (e.g., therapies using chemotherapy or androgen receptor signaling inhibitors) and thus have a poor prognosis and reduced overall survival. The inventors have envisioned that the levels of specific lipids (e.g., ceramides, phosphatidylcholines, and / or sphingomyelins), optionally together with other markers such as total cholesterol, triglycerides, and high-density lipoprotein, can be used in kits, compositions, and methods for determining or predicting the prognosis and survival of subjects with prostate cancer (especially metastatic castration-resistant prostate cancer).

[0187] In one aspect, there is provided a method for determining an indicator for determining the prognosis of a subject with prostate cancer, the method comprising the steps consisting of or consisting essentially of the following steps:

[0188] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0189] b) using the biomarker levels to determine the indicator.

[0190] Although the method can be used to determine the prognosis of subjects with all types of prostate cancer, the method is particularly useful for determining the prognosis of subjects with castration-resistant prostate cancer. The prostate cancer can be metastatic cancer, such as metastatic castration-resistant prostate cancer. In certain embodiments, the subject has undergone, is undergoing, or is initiating a treatment regimen for prostate cancer, such as chemotherapy (e.g., docetaxel, cabazitaxel, mitoxantrone, estramustine, or carboplatin), administration of an androgen receptor signaling inhibitor (e.g., abiraterone, enzalutamide, apalutamide, or darolutamide), administration of a targeted radioisotope (e.g., lutetium-177 prostate-specific membrane antigen), and / or administration of a poly-ADP-ribose polymerase (PARP) inhibitor (e.g., olaparib, rucaparib, or niraparib).

[0191] In certain embodiments, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0). In particular embodiments, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In specific embodiments, the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0192] Although the method may only involve determining the levels of the lipids listed above, in certain embodiments, the method further comprises determining the level of total cholesterol (i.e., the total cholesterol level in the sample, including low-density lipoprotein cholesterol and high-density lipoprotein cholesterol), the level of triglycerides (i.e., the total triglyceride level in the sample), and / or the level of high-density lipoprotein. Thus, in certain embodiments, step a) further comprises determining the level of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; particularly the level of one or more biomarkers selected from total cholesterol and triglycerides. In specific embodiments, step a) further comprises determining the levels of total cholesterol and triglycerides. In particular embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0193] In an alternative aspect, step a) comprises determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers comprise at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0) and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides and high density lipoprotein. In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol and triglycerides.

[0194] In certain embodiments, the method includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0195] In certain embodiments, the method further includes applying a function to the biomarker levels to produce at least one functioned biomarker level and using the at least one functioned biomarker level to determine the metric. For example, the function can include multiplying, dividing, adding, and subtracting at least one of the biomarker levels.

[0196] The method can further include combining the biomarker levels and / or the functioned biomarker levels to provide a composite score and using the composite score to determine the metric. In certain embodiments, the biomarker levels and / or the functioned biomarker levels are combined by adding, multiplying, subtracting, and / or dividing the biomarker levels and / or the functioned biomarker levels.

[0197] The biomarker level, functionalized biomarker level, or composite score can be further analyzed with reference to the corresponding reference biomarker level range or cut-off level, functionalized biomarker level range or cut-off level, or reference composite score range or cut-off score to determine the indicator. For example, a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes (e.g., no disease progression and / or no disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor) or poor outcomes (e.g., disease progression and / or disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor), particularly good outcomes, can yield the reference level, score, or range or cut-off level or its score.

[0198] The method of the present invention can be used to determine whether a subject has a likelihood of poor prognosis or a likelihood of good prognosis. For example, poor prognosis may include poor outcomes such as disease progression and / or disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In contrast, good prognosis may include good outcomes such as no disease progression and / or no disease-caused death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0199] Suitably, if the biomarker level, functionalized biomarker level, or composite score indicates a biomarker level in a sample that is associated with an increased likelihood of poor prognosis relative to a predetermined reference biomarker level range or cut-off level, a predetermined reference functionalized biomarker level range or cut-off level, or a predetermined reference composite score range or cut-off value, then the indicator indicates the likelihood of poor prognosis.

[0200] Alternatively, if the biomarker level, functionalized biomarker level, or composite score indicates a biomarker level in a sample that is associated with an increased likelihood of good prognosis relative to a predetermined reference biomarker level range or cut-off level, a predetermined reference functionalized biomarker level range or cut-off level, or a predetermined reference composite score range or cut-off value, then the indicator indicates the likelihood of good prognosis.

[0201] In a specific embodiment, if the following occurs, the indicator indicates a likelihood of poor prognosis: the level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes. Additionally, when step a) further includes determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, if the following occurs, the indicator indicates a likelihood of poor prognosis: the level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of high-density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0202] In certain embodiments, when step a) further includes determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein, the metric indicates a likelihood of poor prognosis if: the level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of high density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0203] In a specific embodiment, the method includes determining the metric as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to that value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels.

[0204] For example, in certain embodiments, the method includes determining the metric using Equation II:

[0205] [A x the level of ceramide (d18:1 / 18:0) in mg / L] + [B x the level of total cholesterol in mmol / L] + [C x the level of triglycerides in mmol / L] + [D x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Equation II

[0206] Wherein:

[0207] A is a number in the range from about 9 to about 11 (and all ten-thousandths integers in between);

[0208] B is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between);

[0209] C is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between); and

[0210] D is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between).

[0211] In certain embodiments, A is a number in the range from about 9.5 to about 10.5; particularly about 10; more particularly about 10.0506.

[0212] In suitable embodiments, B is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.2 to about -0.3; more particularly about -0.28; most particularly about -0.2783.

[0213] In certain embodiments, C is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.2 to about -0.3; more particularly about -0.22; most particularly about -0.2240.

[0214] In specific embodiments, D is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.25 to about -0.35; more particularly about -0.3; most particularly about -0.2979.

[0215] In specific embodiments, the method includes determining the index using Formula I:

[0216] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglycerides in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

[0217] When a score calculated using Formula I or III is greater than or equal to approximately -0.5 to approximately -2 (and all ten-thousandths integers in between), it may indicate the likelihood of a poor prognosis; particularly a score greater than or equal to approximately -1.3 to approximately -1.16; more particularly a score equal to or greater than approximately -1.1903. A score less than this value indicates the likelihood of a good prognosis, particularly a score less than approximately -1.1903.

[0218] In certain embodiments, a score greater than or equal to approximately -1.1903 calculated using Formula I indicates the likelihood of a poor prognosis, and a score less than approximately -1.1903 calculated using Formula I indicates the likelihood of a good prognosis.

[0219] In an alternative embodiment, the method includes determining the metric as follows: subtracting the level of ceramide (d18:1 / 24:1) from the level of ceramide (d18:1 / 24:0) and adding to this value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels. In certain embodiments, the method includes determining the metric using Formula III:

[0220] [E x the level of ceramide (d18:1 / 18:0) in mg / L] + [F x the level of total cholesterol in mmol / L] + [G x the level of triglycerides in mmol / L] + {H x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Formula III

[0221] Where:

[0222] E is a number in the range from approximately 10 to approximately 12 (and all ten-thousandths integers in between);

[0223] F is a number in the range from approximately -0.1 to approximately -0.4 (and all ten-thousandths integers in between);

[0224] G is a number in the range from approximately -0.1 to approximately -0.4 (and all ten-thousandths integers in between); and

[0225] H is a number in the range from approximately -0.1 to approximately -0.4 (and all ten-thousandths integers in between).

[0226] In certain embodiments, E is a number in the range from approximately 10.5 to approximately 11.5; particularly approximately 11; more particularly approximately 10.9903.

[0227] In suitable embodiments, F is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.2 to about -0.3; more particularly about -0.28; most particularly about -0.2779.

[0228] In certain embodiments, G is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.2 to about -0.3; more particularly about -0.22; most particularly about -0.2243.

[0229] In specific embodiments, H is a number in the range from about -0.15 to about -0.35; particularly in the range from about -0.2 to about -0.3; more particularly about -0.24; most particularly about -0.2366.

[0230] In specific embodiments, the method includes determining the metric using Formula IV:

[0231] [10.9903 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2779 x the level of total cholesterol in mmol / L] + [-0.2243 x the level of triglycerides in mmol / L] + {-0.2366 x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Formula IV.

[0232] When a score greater than or equal to about -0.5 to about -1.5 (and all thousandths integers in between) is calculated using Formula III or IV, it may indicate the likelihood of a poor prognosis; particularly a score greater than or equal to about -0.9 to about -0.75; more particularly a score equal to or greater than about -0.817. A score less than this value indicates the likelihood of a good prognosis, particularly a score less than about -0.817.

[0233] In specific embodiments, a score greater than or equal to about -0.817 calculated using Formula IV indicates the likelihood of a poor prognosis, and a score less than about -0.817 calculated using Formula IV indicates the likelihood of a good prognosis.

[0234] A prostate cancer treatment can be administered to a subject determined to have a likelihood of a poor prognosis. The subject may have received or initiated a treatment regimen for treating prostate cancer, such as chemotherapy (e.g., docetaxel, cabazitaxel, mitoxantrone, estramustine, or carboplatin), administration of an androgen receptor signaling inhibitor (e.g., abiraterone or enzalutamide), and / or administration of a poly-ADP-ribose polymerase (PARP) inhibitor (e.g., olaparib, rucaparib, or niraparib). In such an embodiment, another treatment for prostate cancer or an alternative treatment for cancer can be administered to the subject. For example, the treatment may be more aggressive than the standard treatment for cancer (e.g., chemotherapy or administration of an androgen receptor signaling inhibitor and / or a PARP inhibitor). In a particular embodiment, the treatment is a lipid-targeted therapy (i.e., a treatment that directly or indirectly targets one or more lipids, such as lipid activity, lipid metabolism, or lipid synthesis), such as a ceramide inhibitor. Suitable lipid-targeted therapies include, but are not limited to, statins (e.g., atorvastatin, fluvastatin, lovastatin, mevastatin, pitavastatin, pravastatin, rosuvastatin, or simvastatin), proprotein convertase subtilisin / kexin type 9 (PCSK9) inhibitors (e.g., evolocumab or alirocumab), sphingosine kinase 1 and / or 2 inhibitors (e.g., opaganib, PF-543 (1-[[4-[[3-methyl-5-[(phenylsulfonyl)methyl]phenoxy]methyl]phenyl]methyl]-2R-pyrrolidinemethanol), SKI-349 (4-amino-2-((4-methoxyphenyl)amino)thiazol-5-yl)(3,4-dimethoxyphenyl)methanone), BML-258 (SKI-I;N'-[(2-Hydroxy-1-naphthyl)methylene]-3-(2-naphthyl)-1H-pyrazole-5-carbohydrazide), LCL351 (L-erythro-2-N-(1'-formamidine)-sphingosine hydrochloride), LCL146 (D-erythro-2-N-(1'-formamidine)-sphingosine hydrochloride), VPC96091 ((S)-1-(4-Dodecylbenzoyl)pyrrolidine-2-carboxamidine hydrochloride), SLP7111228 ((S)-2-((3-(4-Octylphenyl)-1,2,4-oxadiazol-5-yl)methyl)pyrrolidine-1-carboxamidine hydrochloride), RB-005 (1-(4-Octylphenethyl)piperidin-4-amine), (2S,3S)-N-((S)-1-(4-(5-(2-Cyclopentylethyl)-1,2,4-oxadiazol-3-yl)phenyl)ethyl)-3-hydroxypyrrolidine-2-carboxamide, SKI-II (2-(p-Hydroxyanilino)-4-(p-chlorophenyl)thiazole), MP-A08 (4-Methyl-N-[2-[[2-[(4-Methylphenyl)sulfonylamino]phenyl]iminomethyl]phenyl]benzenesulfonamide), safingol ((2S,3S)-2-Aminooctadecane-1,3-diol), balanocarpol, SLR080811 ((S)-2-[3-(4-Octylphenyl)-1,2,4-oxadiazol-5-yl]pyrrolidine-1-carboxamidine), trans-12a[(1r,4r)-N,N,N-Trimethyl-4(4-octylphenyl)cyclohexanammonium iodide], K145 (3-(2-Amino-ethyl)-5-[3-(4-Butoxyphenyl)-propylidene]-thiazolidine-2,4-dione), (R)-FTY720-OMe [(2R)-2-Amino-3-(O-methyl)-(2-(4'-n-octylphenyl)ethyl)propanol], SG-12 [(2S,3R)-2-Amino-4-(4-octylphenyl)butane-1,3-diol), etc.), dihydroceramide desaturase (Des1) inhibitors (such as XM462 (N-((2S,3S)-1,3-Dihydroxy-4-(tridecanethio)butan-2-yl)octanamide), SKI-II, fenretinide, resveratrol, etc.) and / or sterol regulatory element-binding protein (SREBP) inhibitors (such as fatostatin and betulin). In certain embodiments, a PCSK9 inhibitor such as evolocumab or a sphingosine kinase 1 and / or 2 inhibitor such as opaganib is administered to the subject.;

[0235] A biological sample from a subject can be any sample containing one or more lipid biomarkers. For example, in certain embodiments, the biological sample is blood, serum or plasma; particularly plasma. A suitable biological sample can be obtained by any method known in the art, such as drawing a subject's blood into a collection tube using a syringe. The serum or plasma can then be separated from the remaining blood components using a suitable method (e.g., by coagulation and / or centrifugation).

[0236] The lipid fraction can then be enriched from the biological sample, or the lipid fraction can be extracted from the sample. For example, the sample can be mixed with a suitable organic solvent such as an alcohol (e.g., 1-butanol, methanol, ethanol, isopropanol, etc. and combinations thereof), which can optionally contain a protein precipitant such as ammonium formate or ammonium sulfate, followed by sonication and centrifugation. Those skilled in the art will be fully aware of suitable lipid extraction and / or sample enrichment methods.

[0237] Any suitable technique or method known to those skilled in the art can be used to measure or evaluate biomarker levels. For example, antibody-based techniques can be used to evaluate biomarker levels, non-limiting examples of which include immunoassays such as enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay (RIA) or mass spectrometry (MS) methods, including liquid chromatography-mass spectrometry (LC-MS), direct analysis in real time mass spectrometry (DART MS), surface-enhanced laser desorption / ionization time-of-flight (SELDI-TOF) and matrix-assisted laser desorption / ionization time-of-flight (MALDI-TOF), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography-mass spectrometry (HPLC-MS), capillary electrophoresis-mass spectrometry, nuclear magnetic resonance spectroscopy or tandem mass spectrometry (e.g., MS / MS, MS / MS / MS, ESI-MS / MS, etc.). In certain embodiments, the mass spectrometry may include multiple reaction monitoring. Alternatively, enzyme techniques (such as enzyme reactions) can be used to determine the levels of specific biomarkers such as cholesterol, triglycerides, and high density lipoprotein. For example, total cholesterol can be measured as follows: esterified cholesterol is converted to cholesterol using cholesterol esterase, and then cholest-4-en-3-one and hydrogen peroxide are produced through the action of cholesterol oxidase. Then, in the presence of peroxidase, hydrogen peroxide reacts with 4-aminoantipyrine to produce a colored product (e.g., a red quinone-imine dye), which is measured at 505 nm (e.g., as described in Barbosa et al. (2019) Molecules, 24(16):2890). Commercially available assays can be used to measure total cholesterol, such as CHOL2, Cholesterol Gen.2 (reference numbers 05168538 190* or 05168538 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland), which is used with a COBAS analyzer. The level of triglycerides can be determined, for example, using a reaction with lipase and detecting the glycerol produced by this reaction. For example, the amount of triglycerides can be measured as follows: triglycerides are converted to glycerol using lipoprotein lipase and subsequently oxidized to dihydroxyacetone phosphate and hydrogen peroxide. Then hydrogen peroxide reacts with 4-aminoantipyrine and 4-chlorophenol in the catalytic action of peroxidase to form a red dye. The color intensity of the formed red dye can be measured photometrically and is proportional to the triglyceride concentration. A suitable commercially available assay is, for example, TRIGL, Triglyceride (reference numbers 05171407 190* or 05171407 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland), which is used with a COBAS analyzer.The levels of high density lipoproteins can be evaluated using, for example, PEG-cholesterol esterase and PEG-cholesterol oxidase or the protocol described in Moshides (1988) Scandinavian Journal of Clinical and Laboratory Investigation, 48(1):59-64. For example, non-HDL lipoproteins are combined with a polyanion and a detergent that forms a water-soluble complex, which blocks the enzymatic reaction of non-HDL lipoproteins. HDL-cholesterol esters are broken down by cholesterol esterase into free HDL-cholesterol and fatty acids. In the presence of oxygen, HDL-cholesterol is oxidized by cholesterol oxidase to Δ. 4 -cholestenone and hydrogen peroxide. In the presence of peroxidase, hydrogen peroxide then reacts with 4-amino-antipyrine and N-ethyl-N-(3-methylphenyl)-N'-succinylethylenediamine to form a dye. The color intensity of the dye can be measured photometrically and is proportional to the HDL-cholesterol concentration. A suitable commercially available assay is, for example, HDLC4, HDL-Cholesterol Gen.4 (reference numbers 07528582 190* or 07528582 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland), which is used with a COBAS analyzer. Such reactions can be carried out in a high-throughput manner, such as by using an analyzer (e.g., COBAS 8000 analyzer; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland). In certain embodiments, the biomarker level is a quantitative level.

[0238] In a specific embodiment, the level of the biomarker is determined using mass spectrometry, preferably using absolute quantification. For example, the sample can include labeled internal standards for each biomarker of interest, such as stable isotope-labeled internal standards, representative examples of which include D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 22:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 7 -ceramide (d20:1 / 24:0), D 7 -ceramide (d20:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D31 - Sphingomyelin (d18:1 / 16:0); especially D 7 - Ceramide (d18:1 / 18:0), D 7 - Ceramide (d18:1 / 24:0), D 7 - Ceramide (d18:1 / 24:1), D 9 - Phosphatidylcholine (16:0 / 16:0), D 9 - Sphingomyelin (d18:1 / 16:0) or D 31 - Sphingomyelin (d18:1 / 16:0).

[0239] In certain embodiments, mass spectrometry is used to determine the levels of one or more of ceramide, phosphatidylcholine, and / or sphingomyelin, and an enzymatic reaction is used to determine the levels of total cholesterol, triglycerides, and / or high density lipoprotein.

[0240] In another aspect, there is provided a method for determining or predicting the prognosis of a subject having prostate cancer, the method comprising, consisting essentially of, or consisting of the following steps:

[0241] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0);

[0242] b) comparing the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and

[0243] c) determining or predicting the prognosis of the subject based on the determined levels of the biomarkers and the comparison.

[0244] Suitable embodiments of the method are discussed above, including exemplary combinations of suitable biological samples and biomarkers.

[0245] In certain embodiments, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects having a good outcome (e.g., no disease progression and / or no death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor).

[0246] In certain embodiments, predicting prognosis includes predicting survival of a subject, such as survival for more than about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0247] In some embodiments, the prostate cancer is castration-resistant prostate cancer. In certain embodiments, the prostate cancer is metastatic cancer, particularly metastatic castration-resistant prostate cancer.

[0248] In some embodiments, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In specific embodiments, the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0249] In some embodiments, the method further comprises determining the levels of total cholesterol, triglycerides, and / or high density lipoprotein. In such embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein; particularly wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides. In specific embodiments, step a) further comprises determining the levels of total cholesterol and triglycerides. In specific embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0250] Alternatively, step a) may include determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers include at least one biomarker selected from the group consisting of ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from the group consisting of ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high density lipoprotein. In certain embodiments, step a) includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0251] In certain embodiments, the method comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0252] Suitable biological samples were discussed above. In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma.

[0253] The methods of the invention can be used to determine whether a subject has a likelihood of poor prognosis or a likelihood of good prognosis. For example, poor prognosis can include adverse outcomes such as disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In contrast, good prognosis can include favorable outcomes such as no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0254] In the case where the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, the subject may have a likelihood of poor prognosis if any of the following occur: the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample. When step a) further includes determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, the subject may have a likelihood of poor prognosis if any of the following occur: the level of total cholesterol is lower than the level in the reference sample; the level of triglycerides is lower than the level in the reference sample; and / or the level of high-density lipoprotein is lower than the level in the reference sample. In a particular embodiment, the subject may have a likelihood of poor prognosis if any of the following occur: the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample; the level of total cholesterol is lower than the level in the reference sample; the level of triglycerides is lower than the level in the reference sample; and / or the level of high-density lipoprotein is lower than the level in the reference sample.

[0255] The method can include applying a function to the biomarker levels, and / or combining the biomarker levels and / or the functionalized biomarker levels to provide a composite score as discussed above, which can then be compared to the levels or scores of a reference sample. For example, in certain embodiments, the method includes determining the prognosis of the subject by dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to that value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglycerides, or the functionalized level of any one of the foregoing levels. In such embodiments, the levels of the ceramides can appropriately be in mg / L, and the levels of total cholesterol and triglycerides can be in mmol / L. It can then be compared to a score obtained for a reference sample such as a group of prostate cancer subjects having a favorable outcome (e.g., no disease progression and / or no death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor).

[0256] For example, in certain embodiments, the method includes determining the metric using Formula II:

[0257] [A x the level of ceramide (d18:1 / 18:0) in mg / L]+[B x the level of total cholesterol in mmol / L]+[C x the level of triglycerides in mmol / L]+[D x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula II

[0258] Where:

[0259] A is a number in the range from about 9 to about 11 (and all integer ten-thousandths in between);

[0260] B is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between);

[0261] C is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between); and

[0262] D is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between).

[0263] Suitable embodiments of A, B, C, and D were discussed above.

[0264] In a specific embodiment, the method includes determining the prognosis of the subject using Formula I:

[0265] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglyceride in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

[0266] When a score greater than or equal to about -0.5 to about -2 (and all ten-thousandths integers in between) is calculated using Formula I or II, it may indicate the likelihood of a poor prognosis; in particular, a score greater than or equal to about -1.3 to about -1.16; more particularly, a score equal to or greater than about -1.1903. A score less than this value indicates the likelihood of a good prognosis, particularly a score less than about -1.1903.

[0267] In certain embodiments, a score greater than or equal to about -1.1903 calculated using Formula I indicates the likelihood of a poor prognosis, and a score less than about -1.1903 calculated using Formula I indicates the likelihood of a good prognosis.

[0268] In an alternative embodiment, the method includes determining the prognosis of the subject as follows: subtracting the level of ceramide (d18:1 / 24:1) from the level of ceramide (d18:1 / 24:0), and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglyceride, or a functionalized level of any of the foregoing levels. In certain embodiments, the method includes using Formula III to determine the indicator:

[0269] [E x the level of ceramide (d18:1 / 18:0) in mg / L] + [F x the level of total cholesterol in mmol / L] + [G x the level of triglyceride in mmol / L] + {H x [the level of ceramide (d18:1 / 24:0) in mg / L - the level of ceramide (d18:1 / 24:1) in mg / L]} Formula III

[0270] Wherein:

[0271] E is a number in the range from about 10 to about 12 (and all ten-thousandths integers in between);

[0272] F is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between);

[0273] G is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between); and

[0274] H is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between).

[0275] Suitable embodiments of E, F, G, and H were discussed above.

[0276] In certain embodiments, the method includes determining the prognosis of the subject using Formula IV:

[0277] [10.9903 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2779 x the level of total cholesterol in mmol / L] + [-0.2243 x the level of triglycerides in mmol / L] + {-0.2366 x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Formula IV.

[0278] When a score greater than or equal to about -0.5 to about -1.5 (and all one-thousandths integers in between) is calculated using Formula III or IV, it may indicate the likelihood of a poor prognosis; particularly a score greater than or equal to about -0.9 to about -0.75; more particularly a score equal to or greater than about -0.817. A score less than this value indicates the likelihood of a good prognosis, particularly a score less than about -0.817.

[0279] In certain embodiments, a score greater than or equal to about -0.817 calculated using Formula IV indicates the likelihood of a poor prognosis, and a score less than about -0.817 calculated using Formula IV indicates the likelihood of a good prognosis.

[0280] Suitable subjects are as discussed above. For example, in certain embodiments, the subject has undergone, is undergoing, or is beginning a treatment regimen for prostate cancer, such as chemotherapy (e.g., docetaxel, cabazitaxel, mitoxantrone, estramustine, or carboplatin), administration of an androgen receptor signaling inhibitor (e.g., abiraterone or enzalutamide), and / or administration of a poly-ADP-ribose polymerase (PARP) inhibitor (e.g., olaparib, rucaparib, or niraparib).

[0281] The method can further include administering a prostate cancer treatment to a subject determined to have a poor prognosis. Suitable treatments were discussed above, such as lipid-targeted therapies (e.g., statins, PCSK9 inhibitors, sphingosine kinase 1 and / or 2 inhibitors, Des1 inhibitors, and / or SREBP inhibitors), e.g., evolocumab or opaganib.

[0282] Suitable techniques for measuring or assessing biomarker levels were discussed above. In certain embodiments, the level of the biomarker is a quantitative level. In particular embodiments, mass spectrometry is used to determine the level of the biomarker; specifically, absolute quantification as discussed above is used.

[0283] The present invention also provides the use of the biomarker for determining or predicting the likelihood of survival of a subject with prostate cancer. Further provided herein is a method for determining or predicting the likelihood of survival of a subject with prostate cancer, the method comprising the steps of, consisting of, or consisting essentially of the following steps:

[0284] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0285] b) comparing the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and

[0286] c) determining or predicting the likelihood of survival of the subject based on the determined biomarker levels and the comparison.

[0287] Suitable reference samples include, for example, control biological samples obtained from a reference population of prostate cancer subjects with good outcomes (e.g., no disease progression and / or no death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor).

[0288] Suitable types of prostate cancer and subjects were discussed above. In particular embodiments, the prostate cancer is castration-resistant prostate cancer. In certain embodiments, the cancer is metastatic cancer, such as metastatic castration-resistant prostate cancer.

[0289] In an exemplary embodiment, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a specific embodiment, the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0290] Step a) may further include determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; in particular, the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, step a) further includes determining the levels of total cholesterol and triglycerides. In a preferred embodiment, step a) includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0291] In an alternative aspect, step a) includes determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers include at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high-density lipoprotein. In a specific embodiment, step a) includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0292] In certain embodiments, the method includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0293] The biological sample can be any sample containing biomarkers discussed in detail elsewhere herein, such as blood, serum, or plasma; particularly plasma.

[0294] Survival includes no death due to prostate cancer within a specific time period, such as from about 6 to about 36 months (and all integer months therebetween), including about 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, or 36 months; particularly about 18 months. In certain embodiments, survival includes no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In such embodiments, non - survival includes death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0295] In certain embodiments, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of non - survival if: the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample. In certain embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein, and the subject has a likelihood of non - survival if: the level of total cholesterol is lower than the level in the reference sample; the level of triglycerides is lower than the level in the reference sample; and / or the level of high - density lipoprotein is lower than the level in the reference sample.

[0296] In certain embodiments, the method comprises determining the likelihood of survival as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels. For example, in certain embodiments, the method comprises determining the metric using Equation II:

[0297] [A x the level of ceramide (d18:1 / 18:0) in mg / L]+[B x the level of total cholesterol in mmol / L]+[C x the level of triglycerides in mmol / L]+[D x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Equation II

[0298] Where:

[0299] A is a number in the range from about 9 to about 11 (and all integers to the ten - thousandth between);

[0300] B is a number in the range from about - 0.1 to about - 0.4 (and all integers to the ten - thousandth between);

[0301] C is a number in the range from about - 0.1 to about - 0.4 (and all integers to the ten - thousandth between); and

[0302] D is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between).

[0303] Suitable embodiments of A, B, C, and D were discussed above.

[0304] In certain embodiments, the method comprises determining the likelihood of survival using Equation I:

[0305] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglycerides in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Equation I.

[0306] When a score greater than or equal to about -0.5 to about -2 (and all ten-thousandths integers in between) is calculated using Equation I or II, it may indicate a likelihood of non-survival; particularly a score greater than or equal to about -1.3 to about -1.16; more particularly a score equal to or greater than about -1.1903. A score less than this value indicates a likelihood of survival, particularly a score less than about -1.1903.

[0307] In a specific embodiment, a score greater than or equal to about -1.1903 calculated using Equation I indicates a likelihood of non-survival, and a score less than about -1.1903 calculated using Equation I indicates a likelihood of survival.

[0308] In an alternative embodiment, the method comprises determining the likelihood of survival as follows: subtracting the level of ceramide (d18:1 / 24:1) from the level of ceramide (d18:1 / 24:0) and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels. In certain embodiments, the method comprises determining the metric using Equation III:

[0309] [E x the level of ceramide (d18:1 / 18:0) in mg / L] + [F x the level of total cholesterol in mmol / L] + [G x the level of triglycerides in mmol / L] + {H x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Equation III

[0310] Wherein:

[0311] E is a number in the range from about 10 to about 12 (and all ten-thousandths integers in between);

[0312] F is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between);

[0313] G is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between); and

[0314] H is a number in the range from about -0.1 to about -0.4 (and all ten-thousandths integers in between).

[0315] Suitable embodiments of E, F, G, and H are discussed above.

[0316] In a particular embodiment, the method includes determining the likelihood of survival using Equation IV:

[0317] [10.9903 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2779 x the level of total cholesterol in mmol / L] + [-0.2243 x the level of triglycerides in mmol / L] + {-0.2366 x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Equation IV.

[0318] When a score greater than or equal to about -0.5 to about -1.5 (and all thousandths integers in between) is calculated using Equation III or IV, it may indicate a likelihood of non-survival; particularly a score greater than or equal to about -0.9 to about -0.75; more particularly a score equal to or greater than about -0.817. A score less than this value indicates a likelihood of survival, particularly a score less than about -0.817.

[0319] In a particular embodiment, a score greater than or equal to about -0.817 calculated using Equation IV indicates a likelihood of non-survival, and a score less than about -0.817 calculated using Equation IV indicates a likelihood of survival.

[0320] As discussed in detail above, the subject may have undergone, be undergoing, or be starting a treatment regimen for treating prostate cancer, such as chemotherapy (e.g., docetaxel, cabazitaxel, mitoxantrone, estramustine, or carboplatin), administration of an androgen receptor signaling inhibitor (e.g., abiraterone or enzalutamide), and / or administration of a poly-ADP-ribose polymerase (PARP) inhibitor (e.g., olaparib, rucaparib, or niraparib). Prostate cancer treatment can be administered to a subject determined to have a likelihood of non-survival (e.g., death within about 18 months). Suitable treatments were discussed above, such as lipid-targeted therapies (e.g., statins, PCSK9 inhibitors, sphingosine kinase 1 and / or 2 inhibitors, Des1 inhibitors, and / or SREBP inhibitors), e.g., evolocumab or opaganib.

[0321] Suitable methods for determining biomarker levels are discussed elsewhere herein. In certain embodiments, mass spectrometry is used to determine the levels of the biomarkers; particularly, absolute quantification is used.

[0322] The present invention also contemplates methods for determining an indicator for determining the likelihood of survival of a subject having prostate cancer. Such methods comprise, consist of, or consist essentially of the following steps:

[0323] a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0324] b) using the biomarker levels to determine the indicator.

[0325] Suitable types of prostate cancer and biological samples are discussed above.

[0326] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In specific embodiments, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0327] In an exemplary embodiment, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high density lipoprotein; in particular, the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, step a) further comprises determining the levels of total cholesterol and triglycerides. In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0328] Alternatively, step a) may comprise determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers comprise at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high density lipoprotein. In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0329] The method can include determining the levels of a specific combination of biomarkers. For example, in certain embodiments, the method includes determining ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0330] Survival includes no death due to prostate cancer within a specific predetermined time period, such as from about 6 to about 36 months (and all integer months therebetween), including about 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, or 36 months; particularly about 18 months. In certain embodiments, survival includes no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor. In such an embodiment, non - survival includes death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0331] In an exemplary embodiment, the metric indicates the likelihood of non - survival (e.g., death due to disease within about 18 months) if any of the following occur: the level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes. In other embodiments, step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein, and the metric indicates the likelihood of non - survival if any of the following occur: the level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; the level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or the level of high - density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

[0332] The reference population of prostate cancer subjects with good outcomes can be, for example, a group of subjects who have not died within about 6 to about 36 months (and all integer months therebetween) from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor, including about 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, or 36 months; particularly about 18 months. In a particular embodiment, the reference population of subjects with good outcomes has not died from disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

[0333] The method can include applying a function to biomarker levels, and / or combining the biomarker levels and / or the functionalized biomarker levels to provide a composite score as discussed above, which can then be compared to a reference level or score to determine the metric.

[0334] In certain embodiments, the method includes determining the metric as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to that value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels. For example, in some embodiments, the method includes determining the metric using Equation II:

[0335] [A x the level of ceramide (d18:1 / 18:0) in mg / L] + [B x the level of total cholesterol in mmol / L] + [C x the level of triglycerides in mmol / L] + [D x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Equation II

[0336] Where:

[0337] A is a number in the range from about 9 to about 11 (and all integer ten-thousandths in between);

[0338] B is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between);

[0339] C is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between); and

[0340] D is a number in the range from about -0.1 to about -0.4 (and all integer ten-thousandths in between).

[0341] Suitable embodiments of A, B, C, and D were discussed above.

[0342] In a specific embodiment, the method includes determining the metric using Equation I:

[0343] [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglyceride in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

[0344] When a score greater than or equal to about -0.5 to about -2 (and all integer ten-thousandths in between) is calculated using Formula I or II, it may indicate the likelihood of non-survival (e.g., death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor); in particular, a score greater than or equal to about -1.3 to about -1.16; more particularly, a score equal to or greater than about -1.1903. A score less than this value indicates the likelihood of survival (e.g., no death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor), in particular a score less than about -1.1903.

[0345] In certain embodiments, a score greater than or equal to about -1.1903 calculated using Formula I indicates the likelihood of non-survival (e.g., death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor), and a score less than about -1.1903 calculated using Formula I indicates the likelihood of survival (e.g., no death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor).

[0346] In an alternative embodiment, the method includes determining the metric as follows: subtracting the level of ceramide (d18:1 / 24:1) from the level of ceramide (d18:1 / 24:0) and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglyceride, or a functionalized level of any of the foregoing levels. In certain embodiments, the method includes determining the metric using Formula III:

[0347] [E x the level of ceramide (d18:1 / 18:0) in mg / L] + [F x the level of total cholesterol in mmol / L] + [G x the level of triglyceride in mmol / L] + {H x [the level of ceramide (d18:1 / 24:0) in mg / L - the level of ceramide (d18:1 / 24:1) in mg / L]} Formula III

[0348] Wherein:

[0349] E is a number in the range from about 10 to about 12 (and all integers in between to the ten-thousandths place);

[0350] F is a number in the range from about -0.1 to about -0.4 (and all integers in between to the ten-thousandths place);

[0351] G is a number in the range from about -0.1 to about -0.4 (and all integers in between to the ten-thousandths place); and

[0352] H is a number in the range from about -0.1 to about -0.4 (and all integers in between to the ten-thousandths place).

[0353] Suitable embodiments of E, F, G, and H were discussed above.

[0354] In a particular embodiment, the method includes determining the metric using Equation IV:

[0355] [10.9903 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2779 x the level of total cholesterol in mmol / L] + [-0.2243 x the level of triglycerides in mmol / L] + {-0.2366 x [the level of ceramide (d18:1 / 24:0) in mg / L] - [the level of ceramide (d18:1 / 24:1) in mg / L]} Equation IV.

[0356] When a score greater than or equal to about -0.5 to about -1.5 (and all integers in between to the thousandths place) is calculated using Equation III or IV, it may indicate the likelihood of non - survival; particularly a score greater than or equal to about -0.9 to about -0.75; more particularly a score equal to or greater than about -0.817. A score less than this value indicates the likelihood of survival, particularly a score less than about -0.817.

[0357] In a particular embodiment, a score greater than or equal to about -0.817 calculated using Equation IV indicates the likelihood of non - survival, and a score less than about -0.817 calculated using Equation IV indicates the likelihood of survival.

[0358] When the subject may have undergone, be undergoing, or be starting a treatment regimen for prostate cancer such as chemotherapy, administration of an androgen receptor signaling inhibitor, and / or administration of a PARP inhibitor, prostate cancer treatment can be administered to a subject determined to have a likelihood of non - survival. Suitable treatments were discussed above. In a particular embodiment, the treatment includes administering a lipid - targeting therapy, such as evolocumab or olaparib.

[0359] Suitable methods for determining biomarker levels are discussed elsewhere in this document. In a specific embodiment, mass spectrometry is used to determine the level of the biomarker; specifically, absolute quantification is used.

[0360] The methods of the present invention can also be used to monitor the prognosis of a subject over a specific period of time (such as one week, one month, or several years). This may involve determining the levels of the biomarkers disclosed herein in biological samples collected from a single subject at two different time points [e.g., from one week to three years (and all integer weeks and months in between)], and comparing the levels between the two samples. A change in the biomarker level between the samples indicates a change in the prognosis of the subject.

[0361] Thus, in another aspect, there is provided a method for monitoring the prognosis of a subject with prostate cancer, the method comprising the steps of, consisting essentially of, or consisting of the following steps:

[0362] a) determining the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0);

[0363] b) using the biomarker levels to determine a first metric;

[0364] c) determining the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained at a time point after the first biological sample;

[0365] d) using the biomarker levels to determine a second metric; and

[0366] e) comparing the metrics in the first and second biological samples;

[0367] wherein a change in the metrics between the first and second biological samples indicates a change in the prognosis of the subject.

[0368] Suitable embodiments of the method are as discussed above and include prostate cancer types, biological samples, and methods for determining the levels of the biomarkers, the metrics, and the prognosis of the subject.

[0369] In certain embodiments, the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarkers in steps a) and c) are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0370] The method may include, as discussed in detail elsewhere herein, determining the levels of one or more additional biomarkers in steps a) and c), such as the levels of total cholesterol, triglycerides, and / or high-density lipoprotein; in particular, the levels of one or more biomarkers selected from total cholesterol and triglycerides. In certain embodiments, steps a) and c) further include determining the levels of total cholesterol and triglycerides. In certain embodiments, steps a) and c) include determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0371] Alternatively, steps a) and c) may comprise determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers comprise at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high density lipoprotein. In certain embodiments, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0372] The method can include determining the levels of a specific combination of biomarkers. For example, in certain embodiments, the method includes determining ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0373] If the prognosis of the subject has become a likelihood of poor prognosis, a prostate cancer treatment, such as a lipid-targeted therapy, can be administered to the subject. Suitable treatments were discussed above. Alternatively, if the prognosis of the subject has become a good prognosis, the current treatment regimen of the subject can be re-evaluated and / or discontinued (e.g., if a lipid-targeted therapy is being administered to the subject).

[0374] In any of the above aspects, biomarker data can be analyzed by a variety of methods to identify biomarkers and determine the statistical significance of differences in biomarker levels observed between test and reference samples and / or populations, in order to evaluate whether a subject has a likelihood of good prognosis, poor prognosis, survival, and non-survival as discussed herein. For any particular biomarker, the distributions of biomarker levels or abundances in patients with poor outcomes and patients with good outcomes may overlap. In such cases, the test will not absolutely distinguish different outcomes with 100% accuracy, and the overlapping region indicates that the test cannot distinguish poor outcomes from good outcomes. A threshold is selected such that above the threshold (or below the threshold, depending on how the biomarker changes with the specified prognosis) the test is considered "positive", and below the threshold the test is considered "negative". "The area under the ROC curve (AUC) provides the C-statistic, which is a measure of the probability that a perceived measurement will correctly identify a certain condition (see, e.g., Hanley et al. (1982) Radiology, 143:29-36).

[0375] Alternatively, or in addition, a threshold can be established as follows: obtain early biomarker results from the same subject, and then subsequent results can be compared thereto. In these embodiments, the individual effectively serves as their own "control group". For biomarkers that decline inversely with prognostic risk, a decline over time in the same subject can indicate cancer progression, treatment regimen failure, or a poor outcome, while an increase over time can indicate cancer remission, treatment regimen success, or a good outcome.

[0376] In certain embodiments, the positive likelihood ratio, negative likelihood ratio, odds ratio, and / or the AUC or receiver operating characteristic (ROC) value are used as a measure of the ability of a method to predict a subject's outcome. As used herein, the term "likelihood ratio" is the probability of observing a given test result in a subject with a particular prognostic outcome divided by the probability of observing the same result in a patient without that prognostic outcome. Thus, the positive likelihood ratio is the probability of observing a positive result in a subject with a specified prognostic outcome divided by the probability of observing a positive result in a subject without the specified prognostic outcome. The negative likelihood ratio is the probability of a negative result in a subject without the specified prognostic outcome divided by the probability of a negative result in a subject with the specified prognostic outcome. As used herein, the term "odds ratio" represents the ratio of the odds of an event occurring in one group (e.g., one of the prognostic outcomes disclosed herein) to the odds of the event occurring in another group (e.g., another disclosed prognostic outcome), or a data-based estimate of that ratio. The term "area under the curve" or "AUC" represents the area under the receiver operating characteristic (ROC) curve, both of which are well known in the art. The AUC measurement is useful for comparing the accuracy of a classifier across the entire range of data. A classifier with a larger AUC has a greater ability to correctly classify two groups of unknowns of interest (e.g., the first disclosed prognostic outcome such as a poor prognosis, and the second disclosed prognostic outcome such as a good prognosis). The ROC curve can be used to plot the performance of a particular feature (e.g., any biomarker and / or any item of clinical parameter or symptom information disclosed herein) in distinguishing or discriminating between two populations (e.g., the first disclosed prognostic outcome and the second disclosed prognostic outcome). Generally, the feature data of the entire population (e.g., subjects with the first disclosed prognostic outcome and subjects with the second disclosed prognostic outcome) are sorted in ascending order according to the value of a single feature. Then, for each value of that feature, the true positive rate and false positive rate of the data are calculated. Sensitivity is determined by counting the number of cases above that feature value and then dividing by the total number of cases. Specificity is determined by counting the number of controls below that feature value and then dividing by the total number of controls. Alternatively, specificity can be calculated via the ROC curve and a threshold. While this definition represents the situation where a particular feature is elevated in one group of subjects relative to another, this definition also applies to the situation where a particular feature is decreased in one group of subjects relative to another (in such a case, samples below that feature value would be counted). The ROC curve can be generated for a single feature as well as other single outputs. For example, combinations of two or more features (e.g., combinations of two or more biomarker levels) can be mathematically combined (e.g., added, subtracted, multiplied, etc.) to produce a single value, and that single value can be plotted in the ROC curve.In addition, any combination of multiple features (e.g., a combination of multiple biomarker levels) can be plotted in an ROC curve, where the combination results in a single output value. These combinations of features may constitute a test. An ROC curve is a plot of the sensitivity of a test versus the specificity of the test, where sensitivity is typically plotted on the vertical axis and specificity is typically plotted on the horizontal axis. Thus, the "AUCROC value" is equal to the probability that the classifier ranks a randomly chosen positive instance higher than a randomly chosen negative instance. The AUC ROC value can be considered equivalent to the Mann-Whitney U test (which is used to test for a median difference between scores obtained in two groups under consideration, if the groups are continuous data) or the Wilcoxon rank test.

[0377] In certain embodiments, a biomarker or a set of biomarkers is selected to distinguish between subjects having a first disclosed prognostic outcome and subjects having a second disclosed prognostic outcome with an accuracy of at least about 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95%, or having a C statistic of at least about 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90 or 0.95.

[0378] For the positive likelihood ratio, a value of 1 indicates that the likelihood of a positive result is equal in the "first condition" and "second condition" groups of subjects, a value greater than 1 indicates that the likelihood of a positive result is greater in the first condition group, and a value less than 1 indicates that the likelihood of a positive result is greater in the second condition group. In this context, the "first condition" group is intended to represent the group with one characteristic (e.g., the first disclosed prognostic outcome), and the "second condition" group (e.g., the second disclosed prognostic outcome) is intended to represent the group lacking the same characteristic. For the negative likelihood ratio, a value of 1 indicates that the likelihood of a negative result is equal in the "first condition" and "second condition" groups of subjects, a value greater than 1 indicates that the likelihood of a negative result is greater in the first condition group, and a value less than 1 indicates that the likelihood of a negative result is greater in the second condition group. For the odds ratio, a value of 1 indicates that the likelihood of a positive result is equal in the "first condition" and "second condition" groups of subjects, a value greater than 1 indicates that the likelihood of a positive result is greater in the first condition group, and a value less than 1 indicates that the likelihood of a positive result is greater in the second condition group. For the AUC ROC value, this is calculated by numerical integration of the ROC curve. The value can range from 0.5 to 1.0. A value of 0.5 indicates that the probability that the classifier (e.g., biomarker characteristic) correctly classifies unknowns between two groups of interest (e.g., the first disclosed prognostic outcome and the second disclosed prognostic outcome disclosed herein) is no more than 50%, while 1.0 indicates relatively optimal diagnostic accuracy. In certain embodiments, a single biomarker and / or group of biomarkers is selected to exhibit a positive or negative likelihood ratio of at least about 1.5 or more or about 0.67 or less, at least about 2 or more or about 0.5 or less, at least about 5 or more or about 0.2 or less, at least about 10 or more or about 0.1 or less, or at least about 20 or more or about 0.05 or less.

[0379] In certain embodiments, a single biomarker and / or group of biomarkers is selected to exhibit an odds ratio of at least about 2 or more or about 0.5 or less, at least about 3 or more or about 0.33 or less, at least about 4 or more or about 0.25 or less, at least about 5 or more or about 0.2 or less, or at least about 10 or more or about 0.1 or less.

[0380] In certain embodiments, a single biomarker and / or group of biomarkers is selected to exhibit an AUC ROC value greater than 0.5, preferably at least 0.6, more preferably 0.7, more preferably at least 0.8, even more preferably at least 0.9, and most preferably at least 0.95.

[0381] In some cases, multiple thresholds can be determined in so-called "tercile", "quartile", or "quintile" analyses. In these methods, the "affected" group and the "control" group (or "high-risk" and "low-risk" groups) are considered together as a single population and divided into 3, 4, or 5 (or more) "bins" with the same number of individuals. The boundary between two of these "bins" can be considered a "threshold". Risk (e.g., the risk of a particular prognosis) can be assigned based on which "bin" the test subject belongs to.

[0382] In other embodiments, a specific threshold of a measured protein biomarker is not relied upon to determine whether a biomarker level obtained from a subject is associated with a particular prognosis. For example, the temporal variation of a biomarker can be used to determine or rule out one or more particular prognoses. Alternatively, a biomarker can be associated with a prognosis based on the presence or absence of one or more biomarkers in a particular assay format. For biomarker panels, the detection methods disclosed herein can utilize the evaluation of the entire biomarker population or subsets disclosed herein to provide a single result value (e.g., a "panel response" value expressed as a numerical score or percentage risk).

[0383] In certain embodiments, a panel of biomarkers is selected to assist in differentiating a pair of groups (i.e., to assist in assessing whether a subject has an increased likelihood of being in one or the other of the pair), the pair of groups being selected from a "good outcome group" (e.g., a good prognosis, such as no disease progression and / or death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor) and a "bad outcome group" (e.g., a bad prognosis, such as disease progression and / or death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor), or "low risk" and "high risk", having at least about 70%, 80%, 85%, 90%, or 95% sensitivity, suitably combined with at least about 70%, 80%, 85%, 90%, or 95% specificity. In some embodiments, both the sensitivity and the specificity are at least about 75%, 80%, 85%, 90%, or 95%.

[0384] As used herein, the phrases "assessing likelihood" and "determining likelihood" refer to methods by which a person skilled in the art can predict good and bad outcomes (such as good prognosis, poor prognosis, survival or non - survival) of a subject. A person skilled in the art will understand that the phrase includes within its scope an increased probability that a patient has one of the disclosed prognoses; that is, the patient is more likely to have that prognosis. For example, the probability that an individual predicted to have a specified prognosis (such as good prognosis or poor prognosis) actually has that prognosis can be expressed as "positive predictive value" or "PPV". The positive predictive value can be calculated as the number of true positives divided by the sum of true positives and false positives. The PPV is determined by the characteristics of the prediction method disclosed herein and the prevalence of the disease in the analyzed population. Statistical algorithms can be selected such that the positive predictive value in a population with disease prevalence is in the range of about 70% to about 99%, and can be, for example, at least about 70%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99%.

[0385] In other embodiments, the probability that an individual predicted not to have a specified prognosis actually does not have that prognosis can be expressed as "negative predictive value" or "NPV". The negative predictive value can be calculated as the number of true negatives divided by the sum of true negatives and false negatives. The negative predictive value is determined by the characteristics of the prediction method and the prevalence of the disease in the analyzed population. Statistical methods and models can be selected such that the negative predictive value in a population with disease prevalence is in the range of about 70% to about 99%, and can be, for example, at least about 70%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99%.

[0386] In certain embodiments, a subject is determined to have a significant likelihood of having or not having a specified prognosis (such as, for example, good prognosis or poor prognosis as disclosed herein). "Significant likelihood" means that the subject has a reasonable probability (such as about 0.6, 0.7, 0.8, 0.9 or more) of having or not having the specified prognosis.

[0387] The protein biomarker analysis disclosed herein allows for the generation of high-density data sets that can be evaluated using informatics methods. High-data density informatics analysis methods are known, and software is available to those of skill in the art, e.g., cluster analysis (Pirouette, Informetrix), class prediction (SIMCA-P, Umetrics), principal component analysis of computational model data sets (SIMCA-P, Umetrics), 2D cluster analysis (GeneLinker Platinum, Improved Outcomes Software), and metabolic pathway analysis (biotech.icmb.utexas.edu). The choice of software package provides specific tools for the questions of interest (Kennedy et al. (1997) Solving Data Mining Problems Through Pattern Recognition. Indianapolis: Prentice Hall PTR; Golub et al., (1999) Science 286:531-537; Eriksson et al. (2001) Multi and Megavariate Analysis Principles and Applications: Umetrics, Umea). In general, any suitable mathematical analysis can be used to evaluate the correlation of at least one biomarker in the populations disclosed herein with the disclosed prognosis. For example, methods such as multivariate analysis of variance, multivariate regression, and / or multiple regression can be used to determine the relationship between a dependent variable (e.g., a clinical measurement) and an independent variable (e.g., a biomarker level). Clustering (including hierarchical and non-hierarchical methods) and non-metric dimensional scaling can be used to determine the associations or relationships between variables and the variations of those variables.

[0388] In addition, principal component analysis is a commonly used method for reducing the dimensionality of a study and can be used to explain the variance-covariance structure of a data set. Principal components can be used in applications such as multiple regression and cluster analysis. Factor analysis describes covariance by constructing "hidden" variables from the observed variables. Factor analysis can be viewed as an extension of principal component analysis, where principal component analysis is used with maximum likelihood methods for parameter estimation. In addition, Hotelling's T-squared statistic can be used to test simple hypotheses such as the equality of two mean vectors.

[0389] In certain embodiments, a data set corresponding to the biomarker sets disclosed herein is used to create predictive rules or models for applications based on statistical and machine learning algorithms. Such algorithms use the relationships (sometimes referred to as training data) between the biomarker sets observed in control subjects or a representative population of control subjects and the disclosed prognoses (e.g., the good or poor prognoses disclosed herein), which provide a combined control or reference biomarker set for comparison with the biomarker set of a subject. The data is used to infer relationships, which are then used to predict the prognosis or survival of a subject.

[0390] Those skilled in the art of data analysis will recognize that many different forms of inferring relationships can be used in the training data without substantially changing the detection methods disclosed herein. The data shown in the tables, examples, and figures herein have been used to generate exemplary minimal combinations (models) of biomarkers that distinguish the disclosed prognoses (i.e., the good or poor prognoses and survival and non-survival disclosed herein). Exemplary models containing at least three biomarkers are capable of developing classifiers or generating algorithms (e.g., Formula I) for distinguishing between the two control groups as defined above, with a significantly increased positive predictive value compared to conventional methods. The algorithm can be advantageously used to determine the probability of one of the prognoses disclosed herein in a subject and thereby predict the subject as having a reduced or poor survival prognosis or an increased or good survival prognosis.

[0391] In certain embodiments, the evaluation of a biomarker includes determining the level of an individual protein biomarker associated with a prognosis, as defined above. In certain embodiments, the techniques used to detect protein biomarkers can include internal or external standards to allow for quantitative or semi-quantitative determination of those biomarkers, thereby enabling effective comparison of the biomarker levels in a biological sample with the corresponding biomarker levels in one or more reference samples. Such standards can be determined by those skilled in the art using standard protocols. In a specific example, the absolute value of the level or functional activity of an individual expression product is determined. Exemplary internal standards are discussed in further detail above.

[0392] In a semi-quantitative method, a threshold or cut-off value is appropriately determined and is optionally a predetermined value. In a particular embodiment, the threshold is predetermined, i.e., it is fixed, e.g., based on prior assay experience and / or the population of affected and / or unaffected subjects. Alternatively, a predetermined value can also indicate that the method of reaching the threshold is predetermined or fixed even if the specific value varies between individual assays or can even be determined for each assay run.

[0393] In certain embodiments, the levels of biomarkers are normalized. There is no intentional limitation on the method for the value of the biomarker used for normalization measurement, provided that the method used for testing human subject samples is the same as the method used for generating the risk classification table or threshold. There are many data normalization methods and they are familiar to those skilled in the art. These include methods such as background subtraction, scaling, MoM analysis, linear transformation, least squares fitting, etc. The purpose of normalization is to equalize the different measurement scales of different biomarkers so that the resulting values can be combined according to a weighted scale determined and designed by the user or machine learning system and are not affected by the absolute or relative values of the biomarkers found in nature.

[0394] A composite score can be calculated using standard statistical analyses well known to those skilled in the art, where the measured values of each biomarker in the group are combined, optionally together with clinical parameters, to provide a probability value. For example, generalized or multivariate logistic regression analysis can be used to derive a mathematical function having a set of variables corresponding to each biomarker and optionally clinical parameters, which provides a weighting factor for each variable. The weighting factors are derived by the agency that optimizes the function to predict the dependent variable, which is the dichotomy of the first prognostic outcome (e.g., poor prognosis) disclosed herein relative to the second prognostic outcome (e.g., good prognosis). The weighting factors are specific to a particular combination of variables (e.g., the group of biomarkers analyzed). The function can then be applied to the original sample to predict the probability of the disclosed prognosis or survival. In this way, a retrospective data set can be used to provide weighting factors for a particular group of biomarkers, optionally in combination with clinical parameters, which are then used to calculate the probability of the disclosed prognosis in a patient.

[0395] A composite score can be calculated, for example, using the statistical methods for processing and interpreting multiplex assay data disclosed in U.S. Publication No. 2008 / 013314. In this method, the amount of any one biomarker is compared to a predetermined cut-off value that differentiates between positive and negative for that biomarker, the cut-off value being determined from a control population study of patients having a prognostic outcome (e.g., poor prognosis) and appropriately matched controls (e.g., subjects having a poor outcome), to generate a score for each biomarker based on the comparison; and then the scores for each biomarker are combined to obtain a composite score of the biomarkers in the sample.

[0396] The predetermined cut-off value can be based on an ROC curve and a score for each biomarker can be calculated based on the specificity of the biomarker. Then, the total score can be compared to a predetermined total score to convert the total score into a qualitative determination of the likelihood or risk of having a particular prognosis disclosed herein.

[0397] In certain embodiments, the detection method utilizes a risk classification table to generate a risk score for a subject based on a composite score by comparing the composite score to a reference set from a cohort of subjects having one of the prognostic outcomes disclosed herein. The detection method can further include quantifying the increased risk of a subject developing a disclosed prognostic outcome as a risk score, wherein the composite score (the combined obtained biomarker levels or values and optionally obtained clinical parameter values) is matched to a risk category that classifies a cohort of subjects, and wherein each risk category includes a multiplier (or percentage) that indicates an increased likelihood of having a prognostic outcome associated with a range of composite scores. This quantification is based on a predefined grouping of a cohort of subjects. In certain embodiments, the grouping of the cohort of subjects or the classification of the prognostic cohort takes the form of a risk classification table. The selection of the prognostic cohort (i.e., the cohort of subjects having risk factors for the disclosed prognostic outcome) is well known to those skilled in the art of cancer research. However, those skilled in the art also recognize that the resulting classification may be more multi-dimensional and take into account further environmental, occupational, genetic, or biological factors (such as epidemiological factors).

[0398] After quantifying the increased risk of the presence of a disclosed prognostic outcome (such as a poor prognosis such as disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor, or a good prognosis such as no disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor) in the form of a risk score, the score can be provided in a form that is easily understandable by a physician. In certain embodiments, the risk score is provided in a report. For example, the report can include one or more of the following: subject information, risk classification table, risk score relative to a cohort population, one or more biomarker test scores, biomarker composite score, primary composite score, identification of the subject's risk category, interpretation of the risk classification table and obtained test scores, list of biomarkers tested, description of the disease cohort, environmental and / or occupational factors, cohort size, biomarker kinetics, gene mutations, family history, margin of error, etc.

[0399] 4. Kits and Compositions

[0400] The present invention further provides compositions that can be used to determine or predict the prognosis and survival of a subject having prostate cancer. Such compositions can include a biological sample that contains a lipid biomarker and a reagent for identifying the presence and / or level of the lipid biomarker.

[0401] The composition can include one or more reagents that permit quantification of at least one biomarker or each biomarker disclosed herein. Suitable reagents include, but are not limited to, antibodies or labeled biomarkers such as isotope-labeled biomarkers (e.g., for quantification by mass spectrometry). In certain embodiments, the reagent is one or more isotope-labeled internal standards for each biomarker of interest, such as D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 22:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 7 -ceramide (d20:1 / 24:0), D 7 -ceramide (d20:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0); particularly D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0).

[0402] Accordingly, the present invention further provides a composition comprising a biological sample from a subject having prostate cancer and isotope-labeled lipids corresponding to each of at least three lipid biomarkers in the sample, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

[0403] In certain embodiments, the subject has castration-resistant prostate cancer, particularly metastatic castration-resistant prostate cancer.

[0404] In certain embodiments, the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); in particular, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a specific embodiment, the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0405] The lipid can be labeled with any isotope (such as deuterium, 13 C, 15 N, etc.) suitable for detection by a quantitative detection technique (such as mass spectrometry). In a particular embodiment, the isotope is deuterium. Suitable isotope-labeled lipids corresponding to the biomarkers of the present invention include, but are not limited to, D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 22:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 7 -ceramide (d20:1 / 24:0), D 7 -ceramide (d20:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0); in particular, D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0).

[0406] Suitable biological samples are discussed in detail elsewhere herein. In a particular embodiment, the biological sample is blood, serum, or plasma; in particular, plasma.

[0407] The reagents and samples required for detecting the biomarkers disclosed herein can be assembled together in a kit. For example, the kit can contain one or more reagents that allow quantification of at least one biomarker or each biomarker disclosed herein. Suitable reagents are as discussed above. In certain embodiments, the one or more reagents are labeled biomarkers, such as isotope-labeled biomarkers, particularly one or more isotope-labeled internal standards of each biomarker of interest, such as D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 22:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 7 -ceramide (d20:1 / 24:0), D 7 -ceramide (d20:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0); particularly D 7 -ceramide (d18:1 / 18:0), D 7 -ceramide (d18:1 / 24:0), D 7 -ceramide (d18:1 / 24:1), D 9 -phosphatidylcholine (16:0 / 16:0), D 9 -sphingomyelin (d18:1 / 16:0) or D 31 -sphingomyelin (d18:1 / 16:0).

[0408] Thus, in another aspect, there is provided a kit for determining or predicting the prognosis or survival of a subject having prostate cancer, which kit contains one or more reagents for determining the levels of at least three lipid biomarkers in a biological sample from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

[0409] In the context of the present invention, a "kit" is understood to mean a product containing the different reagents required to carry out the methods of the present invention, said reagents being packaged for ease of transport and storage. Optionally, the kit may contain instructions regarding the simultaneous, sequential or separate use of the different components contained in the kit. The instructions may be in the form of printed material or in the form of an electronic support capable of storing the instructions such that a subject can read them, such as an electronic storage medium (e.g., disk, tape, etc.), an optical medium (e.g., CD-ROM or DVD), etc. Alternatively or additionally, the medium may contain the Internet address or a link thereto providing the instructions. The kit may contain software for interpreting assay data to determine the prognosis and / or survival of a subject. In certain embodiments, the kit may provide a way to access a machine learning system provided, for example, in the form of a software as a service (SaaS) deployment.

[0410] In a specific embodiment, the one or more reagents include labeled lipids, such as isotope-labeled lipids, each corresponding to at least three lipid biomarkers in a sample. Exemplary isotope-labeled lipids were discussed above. The reagent may be in liquid form or may be lyophilized under low pressure or dried otherwise. Suitable containers for the reagent include, for example, bottles, flasks, syringes and test tubes, which may be formed of a variety of materials, including glass or plastic. The kit may also include a package insert containing written instructions for the methods described herein (e.g., methods for determining the prognosis or survival of a subject).

[0411] In certain embodiments, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1) and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1) and ceramide (d20:1 / 24:1). In certain embodiments, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0) and ceramide (d18:1 / 24:1).

[0412] In certain embodiments, the kit may further comprise one or more reagents for determining the levels of total cholesterol, triglycerides and / or high density lipoprotein in a biological sample. For example, the one or more reagents may include enzymes, such as cholesterol esterase or a derivative thereof, cholesterol oxidase or a derivative thereof and / or lipase.

[0413] In an alternative aspect, the kit comprises one or more reagents for determining the levels of at least three biomarkers in a biological sample from a subject, wherein the biomarkers comprise at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high density lipoprotein. In certain embodiments, the biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0414] Suitable biological samples are discussed in detail herein. In certain embodiments, the biological sample is blood, serum, or plasma; particularly plasma. The kit may optionally include a container and / or device (such as a syringe) for collecting the biological sample from the subject.

[0415] The kit may further comprise appropriate reagents (where appropriate) for detecting labels, positive and negative controls, wash solutions, blotting membranes, microtiter plates, dilution buffers, etc. The kit may also include reagents for enriching and / or extracting lipid components, representative examples of which include alcohols (such as 1-butanol, methanol, ethanol, isopropanol, etc.) and optionally a protein precipitant such as ammonium formate or ammonium sulfate.

[0416] 5. Method of treatment

[0417] A method for determining the prognosis and / or survival of a subject can also be used to manage treatment decisions for a subject with prostate cancer, particularly metastatic castration-resistant prostate cancer, including treating or inhibiting or delaying the progression of the cancer. For example, in the case where a subject is identified by the method of the present invention as having a poor prognosis (e.g., disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor) or a likelihood of non-survival, an alternative therapy can be administered to the subject, including combination therapy, an increased dose of cancer therapy, an alternative cancer therapy, or palliative therapy can be received. In certain embodiments, an alternative cancer therapy can be administered to a subject identified as having a poor prognosis either alone or in combination with a standard or existing therapy such as lipid-targeted therapy.

[0418] Accordingly, in another aspect, there is provided a method for treating or inhibiting the progression of prostate cancer in a subject, the method comprising the steps consisting essentially of or consisting of the following steps:

[0419] a) identifying a subject with prostate cancer having a poor prognosis using the method of the present invention; and

[0420] b) administering a prostate cancer treatment.

[0421] Suitable treatments include, but are not limited to, lipid-targeted therapies (i.e., therapies that directly or indirectly target one or more lipids such as lipid activity, lipid metabolism, or lipid synthesis), such as ceramide inhibitors. Suitable lipid-targeted therapies include, but are not limited to, statins, PCSK9 inhibitors, sphingosine kinase 1 and / or 2 inhibitors, Des1 inhibitors, and / or SREBP inhibitors. Suitable statins, PCSK9 inhibitors, sphingosine kinase 1 and / or 2 inhibitors, Des1 inhibitors, and / or SREBP inhibitors are discussed in Part 3 above. In a particular embodiment, a PCSK9 inhibitor such as evolocumab or a sphingosine kinase 1 and / or 2 inhibitor such as opaganib is administered to the subject.

[0422] Alternatively or additionally, the treatment can include surgery, radiotherapy, chemotherapy, and other cancer therapies.

[0423] Radiation therapy includes radiation and waves that induce DNA damage, such as, for example, γ-irradiation, X-rays, ultraviolet light irradiation, microwaves, electron emission, radioisotopes, etc. Treatment can be achieved by irradiating a local tumor site with radiation in the above forms. Most likely, all of these agents cause extensive damage to DNA, DNA precursors, DNA replication and repair, and chromosome assembly and maintenance. The dose of X-rays ranges from a daily dose of 50 to 200 roentgens over a long period of time (3 to 4 weeks) to a single dose of 2000 to 6000 roentgens. The dose of radioisotopes varies widely and depends on the half-life of the isotope, the intensity and type of the emitted radiation, and the uptake by neoplastic cells. Non-limiting examples of radiation therapy include conformal external beam radiation therapy (50-100 gray, fractionated over 4-8 weeks), single or fractionated emission, high-dose rate brachytherapy, permanent interstitial brachytherapy, or systemic radioisotopes (such as strontium 89 or lutetium-177 prostate-specific membrane antigen). In certain embodiments, the radiation therapy can be administered in combination with a radiosensitizer, representative examples of which include etanidazole, etanidazole, fluosol, misonidazole, nimorazole, temoporfin, and tirapazamine.

[0424] There are numerous cancer therapeutics, including chemotherapeutic agents, which can be cytostatic or cytotoxic, such as anti-proliferative / anti-tumor drugs and their combinations, as used in medical oncology (e.g., alkylating agents such as cisplatin, carboplatin, cyclophosphamide, mechlorethamine, melphalan, chlorambucil, busulfan, and nitrosoureas; antimetabolites such as antifolates, including fluoropyrimidines such as 5-fluorouracil and tegafur, raltitrexed, methotrexate, cytarabine, and hydroxyurea; anti-tumor antibiotics such as anthracyclines like doxorubicin, bleomycin, epirubicin, daunorubicin, idarubicin, mitomycin-C, dactinomycin, and mithramycin; anti-mitotic agents such as vinca alkaloids like vincristine, vinblastine, vindesine, and vinorelbine, and taxanes such as paclitaxel and docetaxel; and topoisomerase inhibitors such as epipodophyllotoxins like etoposide and teniposide, amsacrine, topotecan, and camptothecin); cytostatic agents (e.g., anti-estrogens such as tamoxifen, toremifene, raloxifene, droloxifene, and idoxifene; estrogen receptor downregulators such as fulvestrant; anti-androgens such as bicalutamide, flutamide, nilutamide, and cyproterone acetate; UH antagonists or LHRH agonists such as goserelin, leuprolide, and buserelin; progesterones such as medroxyprogesterone acetate; aromatase inhibitors, including anastrozole, letrozole, vorozole, and exemestane; and inhibitors of 5α-reductase such as finasteride); agents that inhibit cancer cell invasion (e.g., metalloproteinase inhibitors such as marimastat and inhibitors of urokinase plasminogen activator receptor function); inhibitors of growth factor function (e.g., growth factor antibodies, growth factor receptor antibodies such as the anti-erbb2 antibody trastuzumab and the anti-erbb1 antibody cetuximab; farnesyl transferase inhibitors, MEK inhibitors, tyrosine kinase inhibitors, and serine / threonine kinase inhibitors, other inhibitors of the epidermal growth factor family such as other EGFR family tyrosine kinase inhibitors, including N-(3-chloro-4-fluorophenyl)-7-methoxy-6-(3-morpholinopropoxy)quinazolin-4-amine (gefitinib, AZD1839), N-(3-ethynylphenyl)-6,7-bis(2-methoxyethoxy)quinazolin-4-amine (erlotinib, OSI-774), and 6-acrylamido-N-(3-chloro-4-fluorophenyl)-7-(3-morpholinopropoxy)quinazolin-4-amine (CI 1033), inhibitors of the platelet-derived growth factor family, and inhibitors of the hepatocyte growth factor family); anti-angiogenic agents (e.g., those that inhibit the action of vascular endothelial growth factor, such as the anti-vascular endothelial growth factor antibody bevacizumab; compounds such as those disclosed in WO 97 / 22596, WO 97 / 30035, WO 97 / 32856, and WO 98 / 13354; and compounds that act by other mechanisms, such as linomide, inhibitors of integrin αvβ3 function, and angiostatin).Vascular disrupting agents (such as combretastatin A4 and the compounds disclosed in WO 99 / 02166, WO00 / 40529, WO 00 / 41669, WO01 / 92224, WO02 / 04434 and WO02 / 08213); antisense therapies (such as therapies targeting the above-mentioned targets, such as ISIS2503, an antisense inhibitor of H-ras); gene therapy methods (such as methods for replacing abnormal genes, such as abnormal p53 or abnormal GDEPT (gene-directed enzyme prodrug therapy) methods, such as methods using cytosine deaminase, thymidine kinase or bacterial nitroreductase, and methods for increasing the tolerance of patients to chemotherapy or radiotherapy, such as multidrug resistance gene therapy); immunotherapy methods (such as immune checkpoint inhibitors such as inhibitors that target CTLA-4 and thus block or inhibit the interaction between CTLA-4 and CD80 / CD86, such as CTLA-4 inhibitors, such as ipilimumab or tremelimumab; inhibitors that target PD-1 and thus block or inhibit the interaction between PD-1 and PD-L1, such as PD-1 inhibitors, representative examples of which include pembrolizumab, pidilizumab, nivolumab, REGN2810, CT-001, AMP-224, BMS-936558, MK-3475, MEDI0680 and PDR001; and inhibitors that target PD-L1 and thus block or inhibit the interaction between PD-1 and PD-L1, such as PD-L1 inhibitors such as atezolizumab, durvalumab, avelumab, BMS-936559 and MEDI4736; and methods for increasing the immunogenicity of a patient's tumor cells ex vivo and in vivo, such as transfection with cytokines (such as interleukin 2, interleukin 4 or granulocyte-macrophage colony-stimulating factor), methods for reducing T-cell anergy, methods using transfected immune cells (such as cytokine-transfected dendritic cells), methods using cytokine-transfected tumor cell lines and methods using anti-idiotypic antibodies).;

[0425] Generally, cancer treatments and therapies (such as lipid-targeted therapies) are administered in a pharmaceutical composition together with a pharmaceutically acceptable carrier and in an effective amount to achieve their intended purpose. The dose of the active compound administered to a subject should be sufficient to achieve a beneficial response in the subject over time, such as a reduction in tumor burden, improved prognosis, etc. The amount of the pharmaceutically active compound to be administered may depend on the subject to be treated, including its age, sex, weight and general health. A person skilled in the art will be able to easily determine the appropriate amount and / or dose of the active compound to be administered and the appropriate treatment regimen without undue experimentation.

[0426] The treatment can be administered in combination with adjuvant cancer therapies or treatments, representative examples of which include agents for alleviating pain, hair loss, vomiting, immunosuppression, nausea, diarrhea, rash, sensory disorders, anemia, and fatigue.

[0427] If a subject is identified as having a good prognosis (e.g., no disease progression and / or no disease-caused death within about 18 months), for example, after administering cancer treatment, cancer treatment can be continued or discontinued for the patient.

[0428] The methods of the present invention can also be used to select subjects with prostate cancer, particularly metastatic castration-resistant prostate cancer, for lipid-targeted therapy. For such uses, the methods involve identifying prostate cancer subjects with a poor prognosis using the methods of the present invention.

[0429] Suitable lipid-targeted therapies are as described above. In certain embodiments, the treatment includes administering a PCSK9 inhibitor such as evolocumab or a sphingosine kinase 1 and / or 2 inhibitor such as opaganib.

[0430] The methods of the present invention can be used to monitor the response of subjects with prostate cancer, particularly metastatic castration-resistant prostate cancer, to therapeutic treatment. Such methods comprise, consist of, or consist essentially of the following steps:

[0431] a) Determining the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the first biological sample is obtained before or after starting treatment;

[0432] b) Determining a first metric using the biomarker levels;

[0433] c) Determine the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained at a time point after initiation of the therapeutic treatment and after obtaining the first biological sample;

[0434] d) Use the biomarker levels to determine a second metric; and

[0435] e) Compare the metrics in the first and second biological samples;

[0436] wherein a change in the metric between the first and second biological samples indicates whether the subject is responsive to the therapeutic treatment.

[0437] Suitable embodiments of the method are as discussed above and include biological samples and methods for determining biomarker levels and the metric.

[0438] In certain embodiments, the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly, wherein the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In specific embodiments, the lipid biomarkers in steps a) and c) are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0439] The method can include, as discussed in detail elsewhere herein, determining the levels of one or more additional biomarkers in steps a) and c), such as the levels of total cholesterol, triglycerides, and / or high density lipoprotein; in particular, the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, steps a) and c) further include determining the levels of total cholesterol and triglycerides. In a particular embodiment, steps a) and c) include determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0440] Alternatively, steps a) and c) can include determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers include at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high density lipoprotein. In a particular embodiment, step a) includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0441] The method can include determining the levels of a specific combination of biomarkers. For example, in certain embodiments, the method includes determining ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0442] In certain embodiments, the first metric can be determined before administering a therapeutic treatment to a subject, and the second metric can be determined after administering the therapeutic treatment to the subject. A change in the metric from a poor prognosis (e.g., the first metric) to a good prognosis (e.g., the second metric) indicates the likelihood that the therapeutic treatment effectively treats the cancer and the cancer is not progressing. For example, if the metric does not change and the prognosis remains poor, this indicates the likelihood that the therapeutic treatment is ineffective in treating the cancer and the cancer is progressing.

[0443] In certain embodiments, the time difference between the first sample (i.e., early time point) and the second sample (i.e., late time point) is from at least about 1 week to at least about 3 years (and all integer weeks and months therebetween), including at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 weeks or at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months, or at least about 1, 2, or 3 years. The time difference can also be determined by the number of treatment cycles. In certain embodiments, the time difference between the early time point and the late time point is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 treatment cycles.

[0444] If the metric has become indicative of a likelihood of poor prognosis, another or more aggressive prostate cancer treatment, such as lipid-targeted therapy, can be administered to the subject. Suitable treatments were discussed above. Alternatively, if the metric has become indicative of a likelihood of good prognosis, the subject's current treatment regimen can be maintained and / or discontinued (e.g., if lipid-targeted therapy is being administered to the subject).

[0445] 6. Apparatus

[0446] Also encompassed are devices and equipment for practicing the methods of the invention, such as processing devices. Thus, in another aspect, provided is a device for determining a metric used in assessing the prognosis of a subject having prostate cancer, the device comprising at least one electronic processing device, the device:

[0447] a) determines biomarker levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and

[0448] b) determines the metric using the derived biomarker levels.

[0449] Suitable embodiments of the prediction method were discussed in Part 3 above, including the type of prostate cancer, biological sample, preferred biomarkers and combinations thereof, and methods for determining biomarker levels and metrics.

[0450] In a preferred embodiment, the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0); particularly selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1). In a specific embodiment, the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

[0451] Step a) may further comprise determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein; particularly the levels of one or more biomarkers selected from total cholesterol and triglycerides. In a specific embodiment, step a) further comprises determining the levels of total cholesterol and triglycerides. In a particular embodiment, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0452] Alternatively, step a) may comprise determining the levels of at least three biomarkers in a biological sample obtained from the subject, wherein the biomarkers include at least one biomarker selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and at least two biomarkers selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), sphingomyelin (d18:1 / 16:0), total cholesterol, triglycerides, and high-density lipoprotein. In a particular embodiment, step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

[0453] In certain embodiments, the method includes determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), ceramide (d18:1 / 22:0), total cholesterol, and triglycerides; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), and ceramide (d20:1 / 24:1); ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and total cholesterol; or ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and total cholesterol.

[0454] The method may further include retrieving a previously determined metric reference from a database, the metric reference being determined based on metrics determined from a reference population; comparing the metrics to the metric reference to determine the probability that the subject has or does not have the disclosed prognosis; and generating a representation of the probability, the representation being displayed to a user to allow the user to evaluate the likelihood that the subject has the disclosed prognosis.

[0455] The device may further include any one or more of the following devices: a sampling device that obtains a biological sample from a subject, the sample including at least three biomarkers as disclosed herein; a measuring device that quantifies the level of each biomarker; and at least one processing device that receives the biomarker levels from the measuring device, determines an indicator indicative of the disclosed prognosis using the biomarker levels (optionally in combination with one or more clinical parameters or signs of the subject), compares the indicator with at least one indicator reference, uses the result of the comparison to determine the likelihood that the subject has or does not have the disclosed prognosis, and generates a representation of the indicator and the likelihood for display to a user.

[0456] In certain embodiments, the device includes a processor configured to execute computer-readable medium instructions, such as a computer program or software application (e.g., a machine learning system), to receive biomarker levels from an assessment of biomarkers in a biological sample and, in combination with other risk factors (e.g., the patient's medical history, publicly available information sources related to poor prognosis in prostate cancer), can determine a primary composite score and compare it with groupings of a graded population that includes multiple risk categories (e.g., a risk classification table) and provide a risk score. Methods and techniques for determining the primary composite score and the risk score are known in the art.

[0457] The device may take any of a variety of forms, e.g., a handheld device, a tablet computer, or any other type of computer or electronic device. The device may also include a processor configured to execute instructions (e.g., a computer software product), an application for a handheld device, a handheld device configured to execute the method, a World Wide Web (WWW) page or other cloud or network accessible location, or any computing device. In other embodiments, the device may include a handheld device, a tablet computer, or any other type of computer or electronic device for accessing a machine learning system provided as a software as a service (SaaS) deployment. Thus, the correlation may be displayed as a graphical representation, which in certain embodiments is stored in a database or memory such as random access memory, read only memory, disk, virtual memory, etc. Other suitable representations or illustrations known in the art may also be used.

[0458] The device may further comprise storage means for storing the correlations, an input device, and a display device for displaying the status of a subject in accordance with a specific prognosis disclosed herein (e.g., a poor prognosis such as disease progression and / or death due to disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor). The storage means may be, for example, a random access memory, a read only memory, a cache, a buffer, a disk, a virtual memory, or a database. The input device may be, for example, a keypad, a keyboard, stored data, a touch screen, a voice activation system, a downloadable program, downloadable data, a digital interface, a portable device, or an infrared signal device. The display device may be, for example, a computer monitor, a cathode ray tube (CRT), a digital screen, a light emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digital image, a video image, or a portable device. The device may further comprise a database or communicate with a database, wherein the database stores the correlations of the factors and is accessible to a user.

[0459] In certain embodiments, the device is a computing device, e.g., in the form of a computer or a portable device that includes a processing unit, a memory, and storage means. The computing device may include or access a computing environment that includes various computer-readable media, such as volatile memory and non-volatile memory, removable memory and / or non-removable memory. Computer memory includes, for example, RAM, ROM, EPROM, and EEPROM, flash memory or other memory technologies, CDROM, digital versatile disc (DVD) or other optical disc storage, magnetic tape cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other media known in the art that can store computer-readable instructions. The computing device may also include or access a computing environment that includes input, output, and / or communication connections. The input may be one or several devices, such as a keyboard, a mouse, a touch screen, or a stylus. The output may also be one or several devices, such as a video display, a printer, an audio output device, a touch stimulation output device, or a screen reading output device. If desired, the computing device may be configured to operate in a network environment, using a communication connection to connect to one or more remote computers. The communication connection may be, for example, a local area network (LAN), a wide area network (WAN), or other network, and may operate through the cloud, a wired network, a radio frequency wireless network, and / or an infrared network.

[0460] In order to enable the present invention to be easily understood and put into practice, specific preferred embodiments will now be described by the following non-limiting examples. Examples

[0461] Materials and Methods

[0462] Chemicals and reagents

[0463] In addition to D obtained from BOC sciences (Shirley, NY, USA) 31 -SM (d18:1 / 16:0), ceramide, phosphatidylcholine and sphingomyelin standards and deuterated standards were purchased from Cayman Chemicals (Ann Arbor, MI, USA). Quality control standards (independent source required) of Cer (d18:1 / 18:0), Cer (d18:1 / 22:0), Cer (d18:1 / 24:0) and Cer (d18:1 / 24:1) were purchased from Toronto Research Chemicals (TRC) (Toronto, ON, Canada), and quality control standards of PC (16:0 / 16:0) were purchased from AvantiLipids (Birmingham, AL, USA). There was no quality control standard for SM (d18:1 / 16:0).

[0464] All high performance liquid chromatography (HPLC) solvents were LC-MS grade. Acetonitrile, isopropanol, methanol and 1-butanol were from LiChrosolv, Merck (Darmstadt, Germany). Ammonium formate was from Sigma-Aldrich (St Louis, MO, USA). Ultrapure water was produced using a Puris-esse water purification system (model: Esse-Up Analy-TOC-M, Rotek Australia, Bayswater, Australia).

[0465] Cer(d20:1 / 24:0) and Cer(d20:1 / 24:1) were synthesized in-house via an amide coupling reaction between long chain acids and sphingosine using hydroxybenzotriazole activated esters. All chemicals used to synthesize Cer(d20:1 / 24:0) and Cer(d20:1 / 24:1) were purchased from Cayman Chemicals, except for 1-hydroxybenzotriazole hydrate purchased from Toronto Research Chemicals, and triethylamine and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide purchased from Sigma-Aldrich.

[0466] Ceramide (d20:1 / 24:0) was prepared by dropwise adding a solution of triethylamine (15 μmol) and d(20:1) sphingosine (3.3 mg, 10 μmol) in anhydrous dichloromethane (10 mL) over 2 minutes to a solution of nervonic acid (3.6 mg, 10 μmol), 1-hydroxybenzotriazole hydrate (2.0 mg, 15 μmol) and triethylamine (15 μmol) in anhydrous dichloromethane / acetonitrile (9:1). The mixture was stirred for 3 h and then quenched with NaHCO 3 aqueous solution (5%, 20 mL). The aqueous layer was discarded and the organic layer was washed with HCl aqueous solution (0.1 M, 20 mL) and water (20 mL), then evaporated to dryness. The crude mixture was then redissolved in methanol and purified by HPLC to yield 1.42 mg of pure ceramide (d20:1 / 24:0). The selected M / z MRM pairs were 678.6 / 292.2, 678.6 / 292.2 and 678.6 / 280.35, and the HPLC retention time was 7.3 min.

[0467] Ceramide (d20:1 / 24:1) was synthesized by dropwise adding a solution of triethylamine (15 μmol) and d(20:1) sphingosine (3.3 mg, 10 μmol) in anhydrous dichloromethane (10 mL) over 2 minutes to a solution of nervonic acid (3.6 mg, 10 μmol), 1-hydroxybenzotriazole hydrate (2.0 mg, 15 μmol) and triethylamine (15 μmol) in anhydrous dichloromethane / acetonitrile (9:1). The mixture was stirred for 3 h and then quenched with NaHCO 3 aqueous solution (5%, 20 mL). The aqueous layer was discarded and the organic layer was washed with HCl aqueous solution (0.1 M, 20 mL) and water (20 mL), then evaporated to dryness. The crude mixture was then redissolved in methanol and purified by HPLC to yield 4.90 mg of pure ceramide (d20:1 / 24:1). The selected M / z MRM pairs were 676.6 / 292.35, 676.6 / 280.3 and 676.6 / 310.2, and the HPLC retention time was 6.7 min.

[0468] Plasma samples

[0469] A single source of thawed fresh frozen plasma (FFP) (FFP-1) was obtained from the Royal Prince Alfred Blood Bank. This was used for method optimization, standard curve creation and quality control (QC) samples.

[0470] According to a standardized blood collection protocol (Data Supplement), clinical plasma samples were collected from two cohorts (Discovery and Validation) before the start of treatment. The Discovery cohort consisted of 105 men with metastatic castration-resistant prostate cancer (mCRPC) who initiated docetaxel chemotherapy at seven sites in New South Wales, Australia. The Validation cohort consisted of 183 men with mCRPC who initiated docetaxel chemotherapy (docetaxel or cabazitaxel) or ARSI (abiraterone or enzalutamide) as first-line or second-line treatment at seven sites in New South Wales and Victoria, Australia.

[0471] All participants provided written informed consent (Monash Health Institutional Review Board (15571X), Royal Prince Alfred Hospital Human Research Ethics Committee (X14-0406, X19-0320), Australia-New Zealand Clinical Trials Registry ACTRN12607000077460, ACTRN12611000540910).

[0472] For blood collection in the Discovery cohort, non-fasting blood samples were obtained from patients. Briefly, peripheral blood samples were collected in BD Vacutainer tubes containing K 2 EDTA, centrifuged at 3000 x g for 5 minutes at room temperature, and the plasma was aliquoted into cryovials and stored at -80°C freezer until needed. For the Validation cohort, non-fasting blood samples were obtained from patients. Peripheral blood samples from patients were collected and lipid extraction was performed as previously described (see Lin et al. (2017) International Journal of Cancer, 141:2112-2120; Lin et al. (2021) Prostate Cancer and Prostatic Diseases, 24:860-870; and Lin et al. (2021) EBioMedicine, 72:103625). Whole blood was collected into tubes containing 10 mL EDTA and subjected to two-step centrifugation to separate plasma and buffy coat. First, the blood was centrifuged at 1600 x g for 15 minutes and the supernatant was transferred to a new tube, which was then centrifuged at 5000 x g for 10 minutes. Aliquots of the plasma after the second centrifugation were stored at -80°C until needed.

[0473] Preparation of stock solutions and working solutions

[0474] Prepare a stock solution (1 mg / mL) of the standards in isopropanol. Prepare the working solutions by diluting the stock solution with 1-butanol / methanol (v / v 1:1) (BuMe) to concentrations of 0.25 mg / L Cer(d18:1 / 18:0), 3.75 mg / L Cer(d18:1 / 22:0), 6.5 mg / L Cer(d18:1 / 24:0), 5.25 mg / L Cer(d18:1 / 24:1), 0.1 mg / L Cer(d20:1 / 24:0, 0.1 mg / L Cer(d20:1 / 24:1), 20 mg / L PC(16:0 / 16:0), and 50 mg / L SM(d18:1 / 16:0).

[0475] Combine the mixed solution of internal standards (IS) with the protein precipitation solution (PPS) consisting of 10 mM ammonium formate solution in BuMe. The concentrations of the internal standards in PPS are 0.5 mg / L D 7 -Cer(d18:1 / 18:0), 0.65 mg / L D 7 -Cer(d18:1 / 24:0), 0.52 mg / L D 7 -Cer(d18:1 / 24:1), 2.5 mg / L D 9 -PC(16:0 / 16:0) and 2.5 mg / LD 9 -SM(d18:1 / 16:0) or D 31 -SM(d18:1 / 16:0)).

[0476] Obtain a single-source thawed fresh frozen plasma (FFP) (FFP-1) from the Royal Prince Alfred Blood Bank. This is used for method optimization, creation of the standard curve, and quality control (QC) samples.

[0477] Lipid extraction from plasma samples

[0478] Combine 800 μL of IS-PPS with 100 μL of plasma and 100 μL of BuME, vortex for 10 seconds, then sonicate in a water bath at 20 °C for 60 minutes, and finally centrifuge at 16,000 g for 10 minutes. Transfer 750 μL of the supernatant to a glass vial for LC-MS analysis.

[0479] LC-MS analysis

[0480] Lipid extracts were analyzed on a Shimadzu LCMS-8050 using multiple reaction monitoring (MRM). Optimal mass spectrometry conditions for the analytes were determined by injecting individual lipid standards at 1 μg / mL.

[0481] Determination of plasma lipid concentrations

[0482] The lipid concentrations in clinical plasma samples were normalized to an internal standard (IS) and calculated from calibration standards consisting of freshly prepared and spiked FFP-1 included in each analytical run (see Table 1). Spiked FFP-1 was prepared by mixing 100 μL of FFP-1 with 100 μL of lipid standards and extracted in the same manner as clinical plasma samples (replacing BuMe and plasma with 200 μL of spiked FFP-1). The highest spiked concentration was the same as the working solution of lipids in pure BuMe. Subsequent spiked concentrations were 80%, 60%, 40%, 20%, and 0% of the working solution, respectively. The concentrations of analytes in the calibration standards were pre-determined by the standard addition method, which was performed on eight replicates of the calibration standards. For each replicate group, a calibration curve was obtained by simple linear regression of the standards, and the analyte concentration in blank FFP-1 (blank spike) was extrapolated from the regression line. The average concentration in eight replicates of blank FFP-1 was used to calculate the analyte concentration at each point on the calibration curve.

[0483] Discovery cohort samples were extracted and analyzed in two runs. Validation cohort samples were extracted and analyzed in seven runs over 6 days. Each run included FFP-1 calibration standards and QCs. All patients in the discovery and validation cohorts had been previously assayed to determine the presence of previously reported poor prognostic features (see Lin et al. (2017) International Journal of Cancer, 141:2112 - 2120; and Lin et al. (2021) EBioMedicine, 72:103625).

[0484] Quality control (QC)

[0485] Include a QC consisting of spiked FFP-1 at three concentrations for each analyte in each analytical run to monitor LC-MS method performance. To minimize errors, base materials from independent sources should be used as QCs and calibration standards, so the analytes in the QCs are from a different company than the lipids used in our calibration curves (if available). The QC concentrations are based on the concentration distributions detected in plasma samples in our previously published studies (see Lin et al. (2017) International Journal of Cancer, 141:2112-2120; Lin et al. (2021) Prostate Cancer and Prostatic Diseases, 24:860-870; and Lin et al. (2021) EBioMedicine, 72:103625).

[0486] Recovery and matrix effects of lipids

[0487] FFP and aqueous calibration standards were analyzed in eight replicate runs to determine the linearity of analyte response. The recovery of the analyte was calculated as the slope of the calibration curve in FFP divided by the slope of the curve in water in the same analytical run. A recovery reduction of <10% was considered insignificant. Matrix effect was determined by comparing the analyte concentrations between spikings added before and after lipid extraction of three different thawed FFP samples, and a difference of <10% was considered insignificant. The highest calibration spike concentration was used. For pre-extraction spiking, the spike was added to the FFP before lipid extraction. For post-extraction spiking, the spike was added after the sonication step and before the centrifugation step during lipid extraction.

[0488] Optimal LC-MS conditions

[0489] The optimal LC-MS conditions were as follows: interface temperature, 300 °C; nebulizing gas flow rate, 1.6 L / min; drying gas flow rate, 10 L / min; heating gas flow rate, 10 L / min; column oven temperature, 60 °C; ion spray voltage, 4.0 kV. Chromatographic separation was performed on an ACE Excel2 C18, 50 mm column (Advanced Chromatography Technologies, Ltd, Reading, UK). The mobile phase consisted of (A) 50% water, 30% acetonitrile, 20% isopropanol (containing 10 mM ammonium formate) and (B) 1% water, 9% acetonitrile, 90% isopropanol (containing 10 mM ammonium formate). The injection volume was 5 μL, and the flow rate was set at 0.8 mL / min. The gradient was as follows: starting from 10% B, increasing to 45% B over 1.9 minutes, then increasing to 53% over 0.01 minutes, increasing to 65% over 4.39 minutes, increasing to 89% over 0.1 minutes, increasing to 92% over 1.3 minutes, and increasing to 100% over 0.1 minutes. The solvent was then held at 100% B for 0.5 minutes. The solvent was decreased from 100% B to 10% B over 0.1 minutes and held for an additional 2.1 minutes (total cycle time was 10.5 minutes). The dwell time for each signal transition was set at 24 ms, except for the transitions belonging to PC(16:0 / 16:0), SM(d18:1 / 16:0) and their corresponding internal standards, for which the dwell time was set at 3 ms.

[0490] The m / z MRM pairs and internal standards are provided in Table 1.

[0491] Table 1 m / z MRM pairs and internal standards

[0492]

[0493]

[0494] Abbreviations: m / z, mass-to-charge ratio; MRM, multiple reaction monitoring; Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin.

[0495] Since the concentrations of PC(16:0 / 16:0) and SM(d18:1 / 16:0) in endogenous plasma were several times higher, the m / z MRM pairs of PC(16:0 / 16:0) and SM(d18:1 / 16:0) were adjusted to attenuate the signals. This involved increasing the m / z of the product ion of PC(16:0 / 16:0) by 0.2 and increasing the m / z of the parent and product ions of SM(d18:1 / 16:0) by 1.0 to yield the final m / z MRM pairs described above. The optimized collision energy was also adjusted by +10. The corresponding IS was adjusted accordingly.

[0496] No signal of the corresponding IS was observed in the extracted blank FFP (when extracted in the absence of IS), indicating no interference from the IS. The retention times of the endogenous substances matched those of the IS. D 7 -cer(d18:1 / 24:1) was used as the IS for Cer(d18:1 / 22:0) and Cer(d18:1 / 24:1), and D 7 -Cer(d18:1 / 24:0) was used as the IS for Cer(d18:1 / 24:0), Cer(d20:1 / 24:0) and Cer(d20:1 / 24:1) because their retention times were similar and the deuterated standards of Cer(d18:1 / 22:0), Cer(d20:1 / 24:0) and Cer(d20:1 / 24:1) could not be used.

[0497] The LC-MS protocol provided baseline separation of all lipid species (see Figure 1 ).

[0498] Linearity of calibration curves, analyte recovery and matrix effects

[0499] The calibration curves of the lipid standards prepared in plasma showed linearity for all candidate lipids, with an average determination coefficient of 0.938 - 0.998 (see Table 2). The recoveries of the spiked lipid standards from plasma for all lipids were in the range of 93 - 102%, except for 44% for SM(d18:1 / 16:0) and 72% for cer(d20:1 / 24:0) (see Table 3). These two low recovery values were considered acceptable in order to include multiple analytes in a single assay. The plasma matrix effect was minimal, with the pre-extraction peak areas for all lipid species being 97 - 115% of the post-extraction peak areas (see Table 3).

[0500] Table 2

[0501] Results of the linearity assessment of each lipid in FFP in each run repeat for determining the concentration on the calibration curve

[0502]

[0503]

[0504] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin.

[0505] Table 3 Assay recoveries and plasma matrix effects

[0506]

[0507] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0508] Quality control (QC) samples and stability assessment

[0509] Based on the spike concentration in Table 4, prepare QC fresh for each analytical run. The spike concentrations for low-quality control (LQC), medium-quality control (MQC), and high-quality control (HQC) are the 20th percentile, 50th percentile, and 80th percentile of the endogenous plasma concentrations measured by previous studies, respectively (see Lin et al. (2017) International Journal of Cancer, 141:2112 - 2120; Lin et al. (2021) Prostate Cancer and Prostatic Diseases, 24:860 - 870; and Lin et al. (2021) EBioMedicine, 72:103625). The spike concentration for the upper limit of quantification quality control (ULOQ) is twice the 20th percentile value. Prepare the lower limit of quantification quality control (LLOQ) using a stock solution of standard 2 spiked at a concentration of 10%. Extract samples according to the usual sample preparation method; however, use an aqueous solution of 1% bovine serum albumin instead of FFP-1.

[0510] Table 4 Concentrations of analytes spiked in quality control

[0511]

[0512]

[0513] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin.

[0514] Determine on-board and freezer stability by analyzing freshly extracted QC samples and comparing them with the same samples re-analyzed after being stored in the autosampler for 96 hours and in a -20°C freezer for 7 days. The average recoveries for on-board stability testing of all substances except Cer(d20:1 / 24:0) (which is 80%) are 95 - 104% (see Table 5), and the average recoveries for freezer stability testing of all substances are 93 - 120% (see Table 6).

[0515] Table 5 On-board stability - average recoveries of analytes from LQC, MQC, HQC, and ULOQ

[0516]

[0517] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0518] Table 6

[0519] Stability in freezer - Mean recoveries of analytes from LQC, MQC, HQC, and ULOQ

[0520]

[0521]

[0522] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0523] Stability over three freeze / thaw (F / T) cycles was determined in five human plasma samples. The plasma had been stored in an -80 °C freezer for at least five years and was collected as part of the same study protocol as the discovery cohort. The plasma was thawed, 100 μL of plasma was extracted according to the standard protocol, and analyzed on LC-MS. The remaining plasma was refrozen at -80 °C. The process was repeated twice over the following two weeks. The recovery was calculated as the percentage of the concentration of each lipid species in the first freeze / thaw sample in each plasma sample. The mean recovery for each analyte was >97% (see Table 7).

[0524] Table 7 Mean recoveries of analytes from plasma samples over three freeze - thaw cycles

[0525]

[0526]

[0527] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0528] Inter-assay and intra-assay variations

[0529] Inter-assay variability was determined by analytical precision, expressed as the percent coefficient of variation (%CV) of each analyte at LQC, MQC, and HQC in eight run replicates (see Table 8). Intra-assay variability was determined by analyzing seven replicates of LQC, MQC, and HQC in the same analytical run (see Table 9). The target %CV was below 10%. The CV was below 10% for all lipids except Cer(d20:1 / 24:0) and Cer(d20:1 / 24:1), for which CV < 13%. The higher CVs for these two lipids reflect their lower endogenous concentrations and are still acceptable because the variables are continuous and are used for prediction.

[0530] Table 8 Inter-assay variability of analytes in QC samples

[0531]

[0532]

[0533] Abbreviations: QC, quality control; CV, coefficient of variation; Cer, ceramide; LQC, low quality control; MQC, medium quality control; HQC, high quality control; PC, phosphatidylcholine; SM, sphingomyelin.

[0534] Table 9 Intra-assay variability of analytes

[0535]

[0536]

[0537] Abbreviations: QC, quality control; CV, coefficient of variation; Cer, ceramide; LQC, low quality control; MQC, medium quality control; HQC, high quality control; PC, phosphatidylcholine; SM, sphingomyelin.

[0538] Limit of quantification

[0539] The signal-to-noise ratio of the analyte in the LLOQ was greater than 20 for all lipids, except for Cer(d20:1 / 24:1), for which the signal-to-noise ratio was greater than 10. This was considered acceptable (see Table 10). The %CV of the signal-to-noise ratio for the LLOQ of PC(16:0 / 16:0) and SM(d18:1 / 16:0) > 10%. The average LLOQ value for SM(d18:1 / 16:0) was below zero due to the value inferred from the calibration curve. Since the LLOQ concentrations of these analytes are much lower than the target concentration (and much lower than any measured clinical sample), this was considered acceptable.

[0540] Table 10 Signal-to-noise ratio, mean, and coefficient of variation for eight run replicates at LLOQ

[0541]

[0542]

[0543] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0544] Endogenous lipid concentrations in FFP-1

[0545] Table 11 shows the endogenous lipid concentrations in FFP-1 determined by the standard addition method through the calibration curve.

[0546] Table 11 Endogenous concentration (mg / L) of each lipid species in blank FFP-1 for each of the eight analytical replicates

[0547]

[0548]

[0549] Abbreviations: Cer, ceramide; PC, phosphatidylcholine; SM, sphingomyelin; %CV, coefficient of variation.

[0550] Measurement of standard lipids

[0551] Total cholesterol, high-density lipoprotein (HDL), and triglycerides were measured by enzyme reactions using a COBAS 8000 analyzer (module C702; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland) with CHOL2, Cholesterol Gen.2 (reference number 05168538 190* or 05168538 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland); TRIGL, triglyceride (reference number 05171407 190* or 05171407 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland); and HDLC4, HDL-Cholesterol Gen.4 (reference number 07528582 190* or 07528582 214*; Roche Diagnostics, F. Hoffmann-La Roche AG, Basel, Switzerland).

[0552] High-throughput plasma lipidomics analysis method

[0553] Lipids were extracted from 10 μL of plasma mixed with internal standards using the butanol / methanol extraction method described above. Pooled human plasma from healthy individuals and NIST SRM 1950 human reference plasma were extracted and analyzed together with the study plasma samples as quality controls.

[0554] Lipid extracts of the discovery cohort were analyzed using an Agilent 1200 liquid chromatography system coupled with an Applied Biosystems API 4000 Q / TRAP mass spectrometer as described by Lin et al. (2017) International Journal of Cancer, 141:2112 - 2120. Lipid extracts of the validation cohort were analyzed using an Agilent 6490 QQQ mass spectrometer and an Agilent 1290 series HPLC system as previously described (see Lin et al. (2021) Prostate Cancer and Prostatic Diseases, 24:860 - 870; and Lin et al. (2021) EBioMedicine, 72:103625).

[0555] The concentrations of lipid species were calculated by comparison with relevant internal standards and adjusted with response factors [lipid concentration = (area of analyte / area of corresponding internal standard) x concentration of internal standard x response factor].

[0556] For the discovery cohort, 323 lipid species from 22 lipid classes / subclasses were quantified, while for the validation cohort, 824 lipid species from 47 lipid classes were quantified.

[0557] Dataset normalization, alignment and calculation of 3-lipid signatures (3LS)

[0558] To determine the presence of circulating 3LS, the two cohorts were independently normalized first according to the probability - based quotient (PBQ) normalization method described previously (Lin et al. (2017) International Journal of Cancer, 141:2112 - 2120). The reference samples used in the PBQ normalization were created based on the average levels of each lipid species in all plasma samples of each cohort, respectively. The final lipid levels were transformed to log - 2 of pmol / mL for statistical analysis.

[0559] Normalization is a data pre - processing step that is crucial for large - scale analysis of multivariate data. This normalization step adjusts for biases that can arise from sample preparation (e.g., sample loss, evaporation, irregular extraction efficiency, pipetting errors), biological effects (e.g., differences in water content), or biological variations (e.g., individual differences unrelated to disease pathology).

[0560] To account for LC-MS platform and batch differences, the normalized lipidomics datasets needed to be aligned. Therefore, the lipidomics datasets were aligned with the original cohort in Lin et al. (2017) International Journal of Cancer, 141:2112-2120 using the ComBat algorithm (R package sva, v3.34.0), from which 3LS was derived.

[0561] Finally, 3LS of the two cohorts was calculated according to the following formula:

[0562]

[0563] Statistical analysis

[0564] Statistical analysis was performed using R software version 4.1.1 or IBM SPSS version 27. The overall survival (OS) was calculated from the treatment start date to death and censored at the last follow-up date if the event did not occur.

[0565] Pearson's correlation coefficient was used to evaluate the linear relationship between the lipid concentrations measured in targeted lipid assays and those measured by high-throughput lipidomics, or the linear relationship between lipid species pairs (R packages 'ggplot2' version 3.3.5, 'ggpubr' version 0.4.0). Univariate cox regression was used to determine the relationship between lipids and OS (R package'survival' version 3.2-13).

[0566] Various Cox regression prognostic models of OS were constructed using the discovery cohort. The least absolute shrinkage and selection operator (LASSO) method was used to select predictors from different lipid combinations (R packages'survival' version 3.2-13, 'glmnet' version 4.1-2). The minimum value of λ was used to determine unnecessary covariates. The model with the highest concordance index (C-statistic) was regarded as the best model.

[0567] The sum of the variables in the cox regression formula (i.e., the logarithm of the lipid concentration multiplied by the hazard ratio (HR) of each variable) was used as the risk score. A high score indicates high risk (poor prognosis), while a low score indicates low risk (good prognosis). To determine the optimal cut-off point of the risk score indicating whether a person is at high risk or low risk, the scores between the median and the worst 30th percentile of the discovery cohort were evaluated as potential cut-off points. The worst 30th percentile was selected because this is the proportion of patients with 3LS in the discovery cohort.

[0568] The clinical outcomes of risk groups generated at different cut - points were compared by univariate cox regression and Weibull regression (R package 'Survival' version 3.2 - 13). The cut - point that gave the highest C - statistic and the log - likelihood of the Weibull regression model was selected, and the performance of the model was evaluated within the validation cohort.

[0569] Example 1 - LC - MS Assay Development

[0570] Cer(d18:1 / 18:0), cer(d18:1 / 22:0), cer(d18:1 / 24:0), cer(d18:1 / 24:1), cer(d20:1 / 24:0), cer(d20:1 / 24;1), PC(16:0 / 16:0), and SM(d18:1 / 16:0) were selected as candidates for lipid biomarker assays. As discussed above, a targeted LC - MS assay was developed to measure these lipids in a single run. Total cholesterol, HDL, and triglycerides were measured separately by enzymatic reactions. The LC - MS method provided baseline separation of all lipid species (see Figure 1 ). The assay development met and exceeded the requirements of the National Association of Trial Organizations.

[0571] Example 2 - Prognostic Ability of Targeted Lipid Biomarker Assays

[0572] The prognostic ability of the targeted lipid biomarker assay was evaluated using plasma samples from two groups of mCPRC men. These cohorts (referred to as the discovery and validation cohorts) consisted of 105 men and 183 men, respectively. The plasma lipid profiles of these men had previously been evaluated by high - throughput lipidomics analysis (see Lin et al. (2017) International Journal of Cancer, 141:2112 - 2120; and Lin et al. (2021) EBioMedicine, 72:103625). Table 12 provides the patient characteristics of the cohorts. All patients in the discovery cohort started treatment with taxane chemotherapy (docetaxel / cabazitaxel), while all patients in the validation cohort started treatment with taxane chemotherapy or androgen receptor signaling inhibitors (enzalutamide / abiraterone).

[0573] Table 12 Patient Characteristics of the Discovery and Validation Cohorts

[0574]

[0575]

[0576]

[0577] Where: Q1 = the first quartile, Q3 = the third quartile.

[0578] For all lipids in the discovery cohort except SM(d18:1 / 16:0) (Pearson's R = 0.13), the lipid concentrations measured in plasma by LC-MS targeted assays were highly correlated with the measurements by high-throughput assays (Pearson's R > 0.6) (Figure 2). SM(d18:1 / 16:0) was excluded from subsequent analyses.

[0579] Except for Cer(d18:1 / 24:0) and Cer(d18:1 / 22:0) with Pearson's R = 0.76 (S5), no other lipids showed collinearity with each other (Pearson's R > 0.75), so these two lipids were not included in any model.

[0580] In the discovery cohort, four lipids measured by high-throughput assays were associated with OS (p < 0.05) (Cerd18:1 / 24:0), Cer(d18:1 / 24:1), total cholesterol, and triglycerides). Similar associations were observed in targeted assays, where Cer(d18:1 / 24:0), Cer(d18:1 / 24:1), and Cer(d20:1 / 24:1) were associated with OS (p < 0.05) (see Table 13).

[0581] In the validation cohort, four lipids measured by high-throughput assays were associated with OS (p < 0.05) (Cerd18:1 / 18:0), Cer(d18:1 / 24:1), Cer(d20:1 / 24:1), and total cholesterol). Similar associations were observed for the lipids measured in targeted assays, where Cer(d18:1 / 18:0), Cer(d18:1 / 24:0), Cer(d20:1 / 24:1), total cholesterol, and HDL were associated with OS (p < 0.05) (see Table 13).

[0582] Table 13

[0583] Univariate COX regression of LOG2-transformed lipid species concentrations measured by targeted and high-throughput assays in the discovery and validation cohorts

[0584]

[0585]

[0586] Where: Cer, ceramide; PC, phosphatidylcholine; HDL, high-density lipoprotein; and CI, confidence interval.

[0587] Empty cells containing "-" indicate lipids not measured in the high-throughput lipidomics assay.

[0588] Example 3 - Model Development Using the Discovery Cohort and Performance in the Validation Cohort

[0589] Twelve models consisting of different combinations of candidate lipids were derived (see Table 14).

[0590] Details of each prognostic model studied

[0591]

[0592]

[0593]

[0594]

[0595]

[0596]

[0597]

[0598] Where: HR, hazard ratio; C-statistic, concordance; Cer, ceramide; PC, phosphatidylcholine; and HDL, high-density lipoprotein.

[0599] + Values of lipids measured by LC-MS are in mg / L. Values of lipids measured by enzymatic colorimetric assay are in mmol / L.

[0600] ** Total ceramide = Cer(d18:1 / 18:0) + Cer(d18:1 / 22:0) + Cer(d18:1 / 24:0) + Cer(d18:1 / 24:1) + Cer(d20:1 / 24:0) + Cer(d20:1 / 24:1).

[0601] The formula for each model after LASSO shrinkage is as follows:

[0602] Model 1: Σβx = (-0.241 x Cer(d18:1 / 24:0)) + (12.07 x Cer(d18:1 / 18:0)) + (-0.2657 x total cholesterol) + (-0.2164 x triglycerides)

[0603] Model 2: Σβx = (-0.6597 x Cer(d18:1 / 24:0)) + (9.2732 x Cer(d18:1 / 18:0)) + (10.5265 x Cer(d20:1 / 24:1))

[0604] Model 3: Σβx = (0.4434 x Cer(d18:1 / 24:1)) + (-0.8446 x Cer(d18:1 / 22:0) + (12.2 x Cer(d18:1 / 18:0)) + (-0.2957 x total cholesterol) + (-0.2128 x triglyceride)

[0605] Model 4: Σβx = (-0.1209 x total cholesterol) + (-0.2398 x HDL) + (-0.3013 x triglyceride)

[0606] Model 5: Σβx = (10.0506 x Cer(d18:1 / 18:0)) + (-0.2783 x total cholesterol) + (-0.2240 x triglyceride) + (-0.2979 x (Cer(d18:1 / 24:0) / Cer(d18:1 / 24:1)))

[0607] Model 6: Σβx = (10.9903 x Cer(d18:1 / 18:0)) + (-0.2779 x total cholesterol) + (-0.2243 x triglyceride) + (-0.2366 x (Cer(d18:1 / 24:0) - Cer(d18:1 / 24:1)))

[0608] Model 7: Σβx = (10.0506 x Cer(d18:1 / 18:0)) + (-0.2783 x total cholesterol) + (-0.2240 x triglyceride) + (-0.2979 x (Cer(d18:1 / 24:0) / Cer(d18:1 / 24:1)))

[0609] Model 8: Σβx = (9.6096 x Cer(d18:1 / 18:0)) + (-0.2863 x total cholesterol) + (-0.3543 x (Cer(d18:1 / 24:0) / Cer(d18:1 / 24:1)))

[0610] Model 9: Σβx = (-0.1579 x total cholesterol) + (-1.949 x Cer(d18:1 / 24:0) / total ceramide) + (43.74 x Cer(d18:1 / 18:0) / total ceramide)

[0611] Model 10: Σβx = (42.01 x Cer(d18:1 / 18:0) / total ceramide) + (-0.3235 x (Cer(d18:1 / 24:0) / Cer(d18:1 / 24:1)))

[0612] Model 11: Σβx = (33.84 x (Cer(d18:1 / 18:0) / total cholesterol) + (1.59 x (Cer(d18:1 / 24:1) / total cholesterol) + (0.3304 x (PC(16:0 / 16:0) / total cholesterol))

[0613] Model 12: Σβx = (-0.1495 x total cholesterol) + (49.98 x (Cer(d18:1 / 18:0) / total ceramide)) + (-8.275 x (Cer(d18:1 / 18:0) / total cholesterol) + (0.1557 x (PC(16:0 / 16:0) / total cholesterol) + (-0.2464 x (Cer(d18:1 / 24:0) / Cer(d18:1 / 24:1)))

[0614] Models 5 and 6 (models starting from all lipids plus the ratio or difference between Cer(d18:1 / 24:0) and Cer(d18:1 / 24:1)) had the highest C-statistic (0.660) and were selected for further evaluation. For Models 5 and 6, the optimal cut-off points for defining whether a person is at low risk or high risk for the risk score were -1.1903 and -0.817, respectively (see Tables 15 and 16).

[0615] Table 15

[0616] Results of univariate cox regression and Weibull regression models for the group formed by Model 5 scores between the median and the worst 30%

[0617]

[0618]

[0619] **Optimal cut-off.

[0620] Table 16

[0621] Results of univariate cox regression and Weibull regression models for the group formed by Model 6 scores between the median and the worst 30%

[0622]

[0623]

[0624] **Optimal cut-off.

[0625] Using two models, the OS of the poor-risk group was significantly shorter than that of the low-risk group (Model 5: median OS of 12.0 months vs. 24.2 months, HR 3.75 [95% confidence interval (CI) 2.29 - 6.15], p < 0.001; Model 6: median OS of 12.2 months vs. 26.4 months, HR 3.62 [2.21 - 5.94], p < 0.001) (see Figure 3 ). Model 5 was selected as the best model.

[0626] Then, the performance of Model 5 (hereinafter referred to as "PCPro") was evaluated in the validation cohort. In the validation cohort, the median OS of PCPro-positive patients was significantly shorter than that of the PCPro-negative group (13.0 months vs. 25.7 months, HR = 2.13 [95% CI 1.46 - 3.12], log-rank p < 0.001) (see Figure 3 ).

[0627] For patients treated with ARSI, the median OS of the PCPro-positive group was significantly shorter than that of the PCPro-negative group (12.3 months vs. 31.5 months, HR = 2.36 [1.47 - 3.80], log-rank p < 0.001). Although the OS of PCPro-positive patients treated with taxanes was shorter than that of PCPro-negative patients, it did not reach statistical significance (median OS 16.6 months vs. 20.3 months, HR = 1.67 [0.88 - 3.18], log-rank p = 0.12) (see Figure 3 ).

[0628] Among men in the PCPro-positive group, those receiving first-line or second-line treatment had a shorter OS (first-line: median OS 19.0 months vs. 27.2 months, HR = 1.89 [1.18 - 3.02], log-rank p = 0.008; second-line: median OS 9.66 months vs. 21.81 months, HR = 2.60 [1.33 - 5.07], log-rank p = 0.005) (see Figure 3 ).

[0629] PCPro was well correlated with the previously described tri-lipid signature (3LS), with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.869 in the discovery cohort and 0.751 in the validation cohort (see Figure 4 and 5 and Tables 17 and 18).

[0630] Table 17 Cox regression and survival analysis of 3LS and PCPro in the discovery cohort

[0631]

[0632] Table 18 Cox regression and survival analysis of 3LS and PCPro in the validation cohort

[0633]

[0634]

[0635] When PCPro was modeled with clinicopathological factors in multivariable cox regression, PCPro and hemoglobin were independent predictors of OS in both the discovery and validation cohorts (p < 0.05), while alkaline phosphatase (ALP) was an independent predictor in the discovery cohort alone (see Tables 19 - 23). Diabetes was not significantly correlated with PCPro and was not a predictor of OS in the discovery cohort (see Tables 24 and 25). Data on diabetes status were not available for the validation cohort.

[0636] Table 19 Cox regression analysis

[0637]

[0638]

[0639] * Analyzed as continuous variables unless otherwise specified

[0640] ** In the discovery cohort, visceral metastases and lymph node metastases were not distinguished in our database

[0641] *** P - value is statistically significant (p ≤ 0.05)

[0642] Abbreviations: CI = confidence interval, PSA = prostate - specific antigen.

[0643] The Halabi nomogram is available at: https: / / www.cancer.duke.edu / Nomogram / firstlinechemotherapy.html. Some of the clinical variables of the Halabi nomogram were not available (discovery cohort: lactate dehydrogenase levels were not available for all patients; ECOG performance status, albumin levels, and opioid use were available for only some patients; validation cohort: data on opioid use were not available for all patients; lactate dehydrogenase levels, ECOG performance status, and albumin levels were available for only some patients). Missing values were estimated as described in the table footnotes below. To facilitate further comparison using complete clinicopathological data, another clinicopathological model was derived from the multivariable Cox regression of the available data, also as described in the table footnotes below.

[0644] Table 20 Survival analysis of risk groups in the discovery cohort using the Halabi nomogram

[0645]

[0646] *The lactate dehydrogenase value was not available, and it was thus assumed that the lactate dehydrogenase values of all patients were below the normal limit. Using the module "ImputeMissingValuesKNN" in GenePattern version 3.2.3, the missing values of ECOG performance status, albumin level, and opioid use were estimated by the k-nearest neighbor method with Euclidean metric. The number of neighbors used for imputation was 10.

[0647] **The clinicopathological model is a prognostic index (B 1 X 1 +B 2 X 2 +B 3 X 3 +....+B n X n )(see below). The size of the risk groups was based on the same proportion as in PCPro.

[0648] Table 21

[0649] Regression coefficients of the multivariate cox regression of clinicopathological factors in the discovery cohort (103 cases), applicable to the clinicopathological model

[0650]

[0651]

[0652] *Lymph node metastasis and visceral metastasis were not distinguished in the database.

[0653] Survival analysis of risk groups in the validation cohort using the Halabi nomogram

[0654]

[0655] *Opioid use data were not available and were assumed to be "not used". Lactate dehydrogenase values were available for only some patients, and it was assumed that the lactate dehydrogenase values of all other patients were below the normal limit. Using the module "ImputeMissingValuesKNN" in GenePattern version 3.2.3, the missing values of ECOG performance status and albumin level were estimated by the k-nearest neighbor method with Euclidean metric. The number of neighbors used in the imputation process was 10.

[0656] **The clinicopathological model is a prognostic index (B) of multivariable Cox regression of alkaline phosphatase (ALP), hemoglobin (Hb), PSA, and metastatic site (mets) 1 X 1 +B 2 X 2 +B 3 X 3 +....+B n X n )(see below). The size of the risk groups is based on the same proportions as PCPro.

[0657] Table 23

[0658] Regression coefficients of multivariable cox regression of clinicopathological factors in the validation cohort, applicable to the clinicopathological model

[0659]

[0660] Table 24 Relationship between PCPro and diabetes status in the discovery cohort

[0661]

[0662] *4 patients did not have diabetes status (all PCPro negative)

[0663] Table 25 Cox regression analysis of diabetes

[0664]

[0665] *Only includes patients with diabetes status

[0666] The disclosures of each patent, patent application, and publication cited herein are hereby incorporated by reference in their entirety.

[0667] The citation of any reference in this application should not be construed as an admission that such reference is available as "prior art" for this application.

[0668] In this specification, the aim has been to describe the preferred embodiments of the invention and not to limit the invention to any one embodiment or specific collection of features. Thus, those skilled in the art will recognize that, given the disclosure of the invention, various modifications and variations can be made in the specific embodiments of the examples without departing from the scope of the invention. All such modifications and variations are intended to be included within the scope of the appended claims.

[0669] This application claims priority to Australian Provisional Application No. 2022902527, the entire content of which is incorporated herein by reference.

Claims

1. A method for determining an index, which is used in determining the prognosis of a subject with prostate cancer, the method comprising the following steps, consisting of the following steps, or consisting essentially of the following steps consisting of: a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and b) determining the index using the biomarker levels.

2. The method according to claim 1, wherein the prostate cancer is castration-resistant prostate cancer.

3. The method according to claim 1 or claim 2, wherein the prostate cancer is metastatic cancer.

4. The method according to any one of claims 1-3, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

5. The method according to claim 4, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

6. The method according to claim 5, wherein the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

7. The method according to any one of claims 1-6, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglyceride, and high-density lipoprotein.

8. The method according to claim 7, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglyceride.

9. The method according to claim 8, wherein step a) further comprises determining the levels of total cholesterol and triglyceride.

10. The method according to any one of claims 1-9, wherein step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglyceride.

11. The method according to any one of claims 1-10, wherein the biological sample is blood, serum, or plasma.

12. The method according to claim 11, wherein the biological sample is plasma.

13. The method according to any one of claims 1-12, wherein the poor prognosis includes disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

14. The method according to any one of claims 1-12, wherein the good prognosis includes no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

15. The method according to claim 13, wherein the indicator indicates a likelihood of poor prognosis if any of the following occurs: i. The level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; ii. The level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; iii. The level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; iv. The level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; v. The level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; vi. The level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or vii. The level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

16. The method according to claim 15, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, and the indicator indicates a likelihood of poor prognosis if any of the following occurs: i. The level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; ii. The level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or iii. The level of high-density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

17. The method according to any one of claims 1-16, the method further comprising applying a function to the biomarker levels to produce at least one functionalized biomarker level and determining the indicator using the at least one functionalized biomarker level.

18. The method according to claim 17, wherein the function comprises at least one of the following: (a) multiplying the biomarker level; (b) dividing by the biomarker level; (c) adding the biomarker level; and (d) subtracting the biomarker level.

19. The method according to any one of claims 1-18, the method further comprising combining the biomarker level and / or the functionalized biomarker level to provide a composite score and using the composite score to determine the metric.

20. The method according to claim 19, wherein the biomarker level and / or the functionalized biomarker level are combined by adding, multiplying, subtracting, and / or dividing the biomarker level and / or the functionalized biomarker level.

21. The method according to any one of claims 1-20, the method further comprising analyzing the biomarker level, the functionalized biomarker level, or the composite score with reference to a corresponding reference biomarker level range or cut-off level, a functionalized biomarker level range or cut-off level, or a reference composite score range or cut-off score to determine the metric.

22. The method according to any one of claims 7-20, wherein the method comprises determining the metric as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1) and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any one of the foregoing levels.

23. The method according to any one of claims 7-20, wherein the method comprises determining the metric using Formula I: [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783 x the level of total cholesterol in mmol / L] + [-0.2240 x the level of triglycerides in mmol / L] + [-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

24. The method according to claim 23, wherein a score calculated using Formula I that is greater than or equal to -1.1903 indicates the likelihood of a poor prognosis, and a score calculated using Formula I that is less than -1.1903 indicates the likelihood of a good prognosis.

25. The method according to any one of claims 1-24, wherein the subject has undergone, is undergoing, or is about to initiate a treatment regimen for prostate cancer.

26. The method according to claim 25, wherein the treatment regimen comprises chemotherapy and / or administration of an androgen receptor signaling inhibitor.

27. The method according to any one of claims 1-26, wherein prostate cancer treatment is administered to a subject determined to have a poor prognosis.

28. The method according to claim 27, wherein the treatment comprises administration of a lipid-targeted therapy.

29. The method according to claim 27 or claim 28, wherein the treatment comprises administering evolocumab or olaparib.

30. The method according to any one of claims 1-29, wherein the level of the biomarker is a quantitative level.

31. The method according to any one of claims 1-30, wherein the level of the biomarker is determined using mass spectrometry.

32. The method according to claim 31, wherein the level of the biomarker is determined using absolute quantification.

33. A method for determining or predicting the prognosis of a subject having prostate cancer, the method comprising the steps of, consisting of, or consisting essentially of the following steps consisting of: a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); b) comparing the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and c) determining or predicting the prognosis of the subject based on the determined levels of the biomarkers and the comparison.

34. The method according to claim 33, wherein the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

35. The method according to claim 33 or claim 34, wherein predicting the prognosis includes predicting subject survival.

36. The method according to any one of claims 33-35, wherein the prostate cancer is castration-resistant prostate cancer.

37. The method according to any one of claims 33-36, wherein the prostate cancer is metastatic cancer.

38. The method according to any one of claims 33-37, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

39. The method according to claim 38, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

40. The method according to claim 39, wherein the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

41. The method according to any one of claims 33 - 40, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein.

42. The method according to claim 41, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides.

43. The method according to claim 42, wherein step a) further comprises determining the levels of total cholesterol and triglycerides.

44. The method according to any one of claims 33 - 43, wherein step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

45. The method according to any one of claims 33 - 44, wherein the biological sample is blood, serum, or plasma.

46. The method according to claim 45, wherein the biological sample is plasma.

47. The method according to any one of claims 33 - 46, wherein poor prognosis includes disease progression and / or death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

48. The method according to any one of claims 33 - 46, wherein good prognosis includes no disease progression and / or no death due to the disease within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

49. The method according to claim 47, wherein the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of poor prognosis if: i. The level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; ii. The level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; iii. The level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; iv. The level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; v. The level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; vi. The level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or vii. The level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample.

50. The method according to claim 47 or claim 49, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of poor prognosis if any of the following occurs: i. The level of total cholesterol is lower than the level in the reference sample; ii. The level of triglycerides is lower than the level in the reference sample; and / or iii. The level of high-density lipoprotein is lower than the level in the reference sample.

51. The method according to any one of claims 41-50, wherein the method comprises determining the prognosis of the subject as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, and the level of triglycerides, or a functionalized level of any of the foregoing levels.

52. The method according to any one of claims 41-51, wherein the method comprises determining the prognosis of the subject using Formula I: [10.0506 x the level of ceramide (d18:1 / 18:0) in mg / L]+[-0.2783 x the level of total cholesterol in mmol / L]+[-0.2240 x the level of triglycerides in mmol / L]+[-0.2979 x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

53. The method according to claim 52, wherein a score calculated using Formula I that is greater than or equal to -1.1903 indicates a likelihood of poor prognosis, and a score calculated using Formula I that is less than -1.1903 indicates a likelihood of good prognosis.

54. The method according to any one of claims 33-53, wherein the subject has undergone, is undergoing, or is starting a treatment regimen for prostate cancer.

55. The method according to claim 54, wherein the treatment regimen comprises chemotherapy and / or administration of an androgen receptor signaling inhibitor.

56. The method according to any one of claims 33-55, wherein prostate cancer treatment is administered to a subject determined to have a poor prognosis.

57. The method according to claim 56, wherein the treatment comprises administration of a lipid-targeted therapy.

58. The method according to claim 56 or claim 57, wherein the treatment comprises administration of evolocumab or opaganib.

59. The method according to any one of claims 33-58, wherein the level of the biomarker is a quantitative level.

60. The method according to any one of claims 33-59, wherein the level of the biomarker is determined using mass spectrometry.

61. The method according to claim 60, wherein the level of the biomarker is determined using absolute quantification.

62. A method for determining or predicting the likelihood of survival of a subject having prostate cancer, the method comprising the steps of, consisting of, or consisting essentially of the following steps consisting of: a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and b) comparing the levels of the biomarkers with the respective levels of the corresponding biomarkers in a reference sample; and c) determining or predicting the likelihood of survival of the subject based on the determined biomarker levels and the comparison.

63. The method according to claim 62, wherein the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

64. The method according to claim 62 or claim 63, wherein the prostate cancer is castration-resistant prostate cancer.

65. The method according to any one of claims 62-64, wherein the prostate cancer is metastatic cancer.

66. The method according to any one of claims 62-65, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

67. The method according to claim 66, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

68. The method according to claim 67, wherein the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

69. The method according to any one of claims 62-68, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein.

70. The method according to claim 69, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides.

71. The method according to claim 70, wherein step a) further comprises determining the levels of total cholesterol and triglycerides.

72. The method according to any one of claims 62 - 71, wherein step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

73. The method according to any one of claims 62 - 72, wherein the biological sample is blood, serum, or plasma.

74. The method according to claim 73, wherein the biological sample is plasma.

75. The method according to any one of claims 62 - 74, wherein survival comprises no disease - related death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

76. The method according to claim 75, wherein the reference sample is a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes, and the subject has a likelihood of non - survival if: i. the level of ceramide (d18:1 / 18:0) is higher than the level in the reference sample; ii. the level of ceramide (d18:1 / 22:0) is lower than the level in the reference sample; iii. the level of ceramide (d18:1 / 24:0) is lower than the level in the reference sample; iv. the level of ceramide (d18:1 / 24:1) is higher than the level in the reference sample; v. the level of ceramide (d20:1 / 24:0) is lower than the level in the reference sample; vi. the level of ceramide (d20:1 / 24:1) is higher than the level in the reference sample; and / or vii. the level of phosphatidylcholine (16:0 / 16:0) is higher than the level in the reference sample.

77. The method according to claim 76, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein, and the subject has a likelihood of non - survival if: i. the level of total cholesterol is lower than the level in the reference sample; ii. the level of triglycerides is lower than the level in the reference sample; and / or iii. the level of high - density lipoprotein is lower than the level in the reference sample.

78. The method according to any one of claims 69 - 77, wherein the method comprises determining the likelihood of survival as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding this value to the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglycerides, or a functionalized level of any one of the foregoing levels.

79. The method according to any one of claims 69 - 78, wherein the method comprises determining the likelihood of survival using formula I: [10.0506x the level of ceramide (d18:1 / 18:0) in mg / L] + [-0.2783x the level of total cholesterol in mmol / L] + [-0.2240x the level of triglycerides in mmol / L] + [-0.2979x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

80. The method according to claim 79, wherein a score calculated using Formula I that is greater than or equal to -1.1903 indicates a likelihood of non-survival, and a score calculated using Formula I that is less than -1.1903 indicates a likelihood of survival.

81. The method according to any one of claims 62 - 80, wherein the subject has undergone, is undergoing, or is initiating a treatment regimen for treating prostate cancer.

82. The method according to claim 81, wherein the treatment regimen comprises chemotherapy and / or administration of an androgen receptor signaling inhibitor.

83. The method according to any one of claims 62 - 82, wherein prostate cancer treatment is administered to a subject determined to have a likelihood of non-survival.

84. The method according to claim 83, wherein the treatment comprises administration of a lipid-targeted therapy.

85. The method according to claim 83 or claim 84, wherein the treatment comprises administration of evolocumab or opaganib.

86. The method according to any one of claims 62 - 85, wherein the level of the biomarker is a quantitative level.

87. The method according to any one of claims 62 - 86, wherein the level of the biomarker is determined using mass spectrometry.

88. The method according to claim 87, wherein the level of the biomarker is determined using absolute quantification.

89. A method for determining an index used in determining the likelihood of survival of a subject having prostate cancer, the method comprising the following steps, consisting of the following steps, or consisting essentially of the following steps consisting of: a) determining the levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and b) determining the index using the biomarker levels.

90. The method according to claim 89, wherein the prostate cancer is castration-resistant prostate cancer.

91. The method according to claim 89 or claim 90, wherein the prostate cancer is metastatic cancer.

92. The method according to any one of claims 89 - 91, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

93. The method according to claim 92, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

94. The method according to claim 93, wherein the lipid biomarker is ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

95. The method according to any one of claims 89 - 94, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein.

96. The method according to claim 95, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides.

97. The method according to claim 96, wherein step a) further comprises determining the levels of total cholesterol and triglycerides.

98. The method according to any one of claims 89 - 97, wherein step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

99. The method according to any one of claims 89 - 98, wherein the biological sample is blood, serum, or plasma.

100. The method according to claim 99, wherein the biological sample is plasma.

101. The method according to any one of claims 89 - 100, wherein survival comprises no disease - related death within about 18 months from the start of chemotherapy or treatment with an androgen receptor signaling inhibitor.

102. The method according to claim 101, wherein the metric indicates a likelihood of non - survival if any of the following occurs: i. The level of ceramide (d18:1 / 18:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; ii. The level of ceramide (d18:1 / 22:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; iii. The level of ceramide (d18:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; iv. The level of ceramide (d18:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; v. The level of ceramide (d20:1 / 24:0) is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; vi. The level of ceramide (d20:1 / 24:1) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or vii. The level of phosphatidylcholine (16:0 / 16:0) is higher than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

103. The method according to claim 102, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein, and the metric indicates a likelihood of non-survival if any of the following occur: i. The level of total cholesterol is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; ii. The level of triglycerides is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes; and / or iii. The level of high-density lipoprotein is lower than the level in a control biological sample obtained from a reference population of prostate cancer subjects with good outcomes.

104. The method according to any one of claims 89 - 103, the method further comprising applying a function to the biomarker levels to produce at least one functionalized biomarker level and using the at least one functionalized biomarker level to determine the metric.

105. The method according to claim 104, wherein the function comprises at least one of the following: (a) multiplying the biomarker level; (b) dividing the biomarker level; (c) adding the biomarker level; and (d) subtracting the biomarker level.

106. The method according to any one of claims 89 - 105, the method further comprising combining the biomarker levels and / or functionalized biomarker levels to provide a composite score and using the composite score to determine the metric.

107. The method according to claim 106, wherein the biomarker levels and / or functionalized biomarker levels are combined by adding, multiplying, subtracting, and / or dividing the biomarker levels and / or functionalized biomarker levels.

108. The method according to any one of claims 89 - 107, the method further comprising analyzing the biomarker levels, functionalized biomarker levels, or composite score with reference to a corresponding reference biomarker level range or cut-off level, functionalized biomarker level range or cut-off level, or reference composite score range or cut-off score to determine the metric.

109. The method according to any one of claims 95 - 108, wherein the method comprises determining the index as follows: dividing the level of ceramide (d18:1 / 24:0) by the level of ceramide (d18:1 / 24:1), and adding to this value the level of ceramide (d18:1 / 18:0), the level of total cholesterol, the level of triglycerides, or a functionalized level of any of the foregoing levels.

110. The method according to any one of claims 95 - 109, wherein the method comprises determining the index using Formula I: [10.0506x the level of ceramide (d18:1 / 18:0) in mg / L]+[-0.2783x the level of total cholesterol in mmol / L]+[-0.2240x the level of triglycerides in mmol / L]+[-0.2979x (the level of ceramide (d18:1 / 24:0) in mg / L / the level of ceramide (d18:1 / 24:1) in mg / L)] Formula I.

111. The method according to claim 110, wherein a score calculated using Formula I that is greater than or equal to -1.1903 indicates the likelihood of non - survival, and a score calculated using Formula I that is less than -1.1903 indicates the likelihood of survival.

112. The method according to any one of claims 89 - 111, wherein the subject has undergone, is undergoing, or is about to initiate a treatment regimen for prostate cancer.

113. The method according to claim 112, wherein the treatment regimen comprises chemotherapy and / or administration of an androgen receptor signaling inhibitor.

114. The method according to any one of claims 89 - 113, wherein prostate cancer treatment is administered to a subject determined to have a likelihood of non - survival.

115. The method according to claim 114, wherein the treatment comprises administration of a lipid - targeting therapy.

116. The method according to claim 114 or claim 115, wherein the treatment comprises administration of evolocumab or opaganib.

117. The method according to any one of claims 89 - 116, wherein the level of the biomarker is a quantitative level.

118. The method according to any one of claims 89 - 117, wherein the level of the biomarker is determined using mass spectrometry.

119. The method according to claim 118, wherein the level of the biomarker is determined using absolute quantification.

120. A method for treating or inhibiting the progression of prostate cancer in a subject, the method comprising the steps of, consisting of, or consisting essentially of the following steps consisting of: a) identifying a subject with prostate cancer having a poor prognosis using the method according to any one of claims 1 - 61; and b) administering a prostate cancer treatment.

121. The method according to claim 120, wherein the treatment is a lipid - targeting therapy.

122. The method according to claim 120 or claim 121, wherein the treatment comprises evolocumab or opaganib.

123. A composition comprising a biological sample from a subject having prostate cancer and isotopically labeled lipids corresponding to each of at least three lipid biomarkers in the sample, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

124. The composition according to claim 123, wherein the prostate cancer is castration-resistant prostate cancer.

125. The composition according to claim 123 or claim 124, wherein the prostate cancer is metastatic cancer.

126. The composition according to any one of claims 123-125, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

127. The composition according to claim 126, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

128. The composition according to claim 127, wherein the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

129. The composition according to any one of claims 123-128, wherein the biological sample is blood, serum, or plasma.

130. The composition according to claim 129, wherein the biological sample is plasma.

131. A kit for determining or predicting the prognosis of a subject with prostate cancer, comprising one or more reagents for determining the levels of at least three lipid biomarkers in a biological sample from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0).

132. The kit according to claim 131, wherein the one or more reagents comprise isotopically labeled lipids corresponding to each of the at least three lipid biomarkers in the sample.

133. The kit according to claim 131 or claim 132, wherein the prostate cancer is castration-resistant prostate cancer.

134. The kit according to any one of claims 131-133, wherein the prostate cancer is metastatic cancer.

135. The kit according to any one of claims 131-134, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

136. The kit according to claim 135, wherein the lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

137. The kit according to claim 136, wherein the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

138. The kit according to any one of claims 132-137, wherein the biological sample is blood, serum, or plasma.

139. The kit according to claim 138, wherein the biological sample is plasma.

140. A device for determining an index used in assessing the prognosis of a subject with prostate cancer, the device comprising at least one electronic processing means, the means: a) Determine the biomarker levels of at least three lipid biomarkers in a biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); and b) Determine the index using the derived biomarker levels.

141. The device according to claim 140, wherein the prostate cancer is castration-resistant prostate cancer.

142. The device according to claim 140 or claim 141, wherein the prostate cancer is metastatic cancer.

143. The device according to any one of claims 140-142, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

144. The device according to claim 143, wherein the lipid biomarker is selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

145. The device according to claim 144, wherein the lipid biomarkers are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

146. The device according to any one of claims 140-145, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high-density lipoprotein.

147. The device according to claim 146, wherein step a) further comprises determining the levels of one or more biomarkers selected from total cholesterol and triglycerides.

148. The device according to claim 147, wherein step a) further comprises determining the levels of total cholesterol and triglycerides.

149. The device according to any one of claims 140-148, wherein step a) comprises determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

150. The device according to any one of claims 140-149, wherein the biological sample is blood, serum, or plasma.

151. The device according to claim 150, wherein the biological sample is plasma.

152. A method for selecting a subject with prostate cancer for treatment with lipid-targeted therapy, the method comprising the following steps, consisting of the following steps, or consisting essentially of the following steps Consisting of: Identifying a subject with prostate cancer having a poor prognosis using the method according to any one of claims 1-61.

153. The method according to claim 152, wherein the treatment comprises evolocumab or opaganib.

154. A method for monitoring the response of a subject with prostate cancer to a therapeutic treatment, the method comprising the following steps, consisting of the following steps, or consisting essentially of the following steps Consisting of: a) Determining the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the first biological sample is obtained before or after the start of treatment; b) Determining a first metric using the biomarker levels; c) Determining the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained after the start of therapeutic treatment and at a time point after the first biological sample is obtained; d) Determining a second metric using the biomarker levels; and e) Comparing the metrics in the first and second biological samples; wherein a change in the metric between the first and second biological samples indicates whether the subject is responsive to the therapeutic treatment.

155. A method for monitoring the prognosis of a subject with prostate cancer, the method comprising the following steps, consisting of the following steps, or consisting essentially of the following steps Consisting of: a) Determine the levels of at least three lipid biomarkers in a first biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0); b) Determine a first metric using the biomarker levels; c) Determine the levels of at least three lipid biomarkers in a second biological sample obtained from the subject, wherein the at least three lipid biomarkers are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:0), ceramide (d20:1 / 24:1), phosphatidylcholine (16:0 / 16:0), and sphingomyelin (d18:1 / 16:0), and the second biological sample is obtained at a time point after the first biological sample is obtained; d) Determine a second metric using the biomarker levels; and e) Compare the metrics in the first and second biological samples; wherein a change in the metric between the first and second biological samples indicates a change in the prognosis of the subject.

156. The method according to claim 154 or claim 155, wherein the prostate cancer is castration-resistant prostate cancer.

157. The method according to any one of claims 154 - 156, wherein the prostate cancer is metastatic cancer.

158. The method according to any one of claims 154 - 157, wherein the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), ceramide (d20:1 / 24:1), and phosphatidylcholine (16:0 / 16:0).

159. The method according to claim 158, wherein the lipid biomarkers in steps a) and c) are selected from ceramide (d18:1 / 18:0), ceramide (d18:1 / 22:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), and ceramide (d20:1 / 24:1).

160. The method according to claim 159, wherein the lipid biomarkers in steps a) and c) are ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), and ceramide (d18:1 / 24:1).

161. The method according to any one of claims 154 - 160, wherein steps a) and c) further comprise determining the levels of one or more biomarkers selected from total cholesterol, triglycerides, and high - density lipoprotein.

162. The method according to claim 161, wherein steps a) and c) further comprise determining the levels of one or more biomarkers selected from total cholesterol and triglycerides.

163. The method according to claim 162, wherein steps a) and c) further comprise determining the levels of total cholesterol and triglycerides.

164. The method according to any one of claims 154 - 163, wherein steps a) and c) comprise determining the levels of ceramide (d18:1 / 18:0), ceramide (d18:1 / 24:0), ceramide (d18:1 / 24:1), total cholesterol, and triglycerides.

165. The method according to any one of claims 154 - 164, wherein the biological sample is blood, serum, or plasma.

166. The method according to claim 165, wherein the biological sample is plasma.

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