Set of diagnostic markers for use in diagnosing breast cancer and method for in vitro diagnosis of breast cancer

Abstract

The invention relates to a set of diagnostic markers comprising glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, for use in diagnosing breast cancer, and to an in vitro method for diagnosing breast cancer.

Description

[0001] Set of diagnostic markers for use in diagnosing breast cancer and method for in vitro diagnosis of breast cancer

[0002] The present invention relates to a set of diagnostic markers for use in the diagnosis of breast cancer, and to an in vitro method for diagnosing breast cancer, in particular for identifying breast cancer, determining its molecular subtypes, and assessing the Ki-67 proliferation index. The invention belongs to the field of medicine, especially oncological diagnostics.

[0003] Breast cancer represents a major global health challenge. According to the Global Cancer Observatory, it is the most frequently diagnosed cancer in women, with an incidence rate of 58.5 per 100,000 and a mortality rate of 17.7 per 100,000. Breast cancer is associated with marked metabolic alterations and presents a complex profile that varies depending on the stage, subtype, and aggressiveness of the disease.

[0004] The Ki-67 index is widely used as a marker of cancer cell proliferation; however, its utility as an independent prognostic indicator is subject to several limitations. Differences in immunohistochemical methodology, such as the type of antibodies used, sample preparation and fixation procedures, and staining techniques, may lead to substantial inter-laboratory variability in results. The absence of uniform scoring criteria, for example whether manual or automated assessment should be applied and which tumor areas should be evaluated, results in inconsistencies in the interpretation of findings. Accordingly, assessment of the percentage of Ki-67-positive cells is often based on visual evaluation by pathologists, thereby introducing an element of subjectivity and variability that may affect the final result. In addition, marked intratumoral heterogeneity in Ki-67 expression may occur within a single tumor. Areas exhibiting high and low proliferation rates may be present side by side, making it difficult to obtain an assessment representative of the tumor as a whole. Furthermore, Ki-67 is expressed only during the active phases of the cell cycle, namely G1, S, G2, and M, and is absent in the GO phase. Consequently, the result depends on the timing of samplecollection and may not fully reflect the actual proliferative activity of the tumor. Different studies also apply different percentage cut-off values, such as 10%, 14%, or 20% Ki-67-positive cells, as criteria for distinguishing between tumors with low and high proliferative activity, which hinders comparison of results across studies and precludes unambiguous clinical interpretation.

[0005] Among the metabolites that have attracted particular attention in breast cancer research are amino acids, which are essential building blocks of cellular proteins [1], These molecules exhibit characteristic metabolic signatures in various body fluids, including serum, plasma, saliva, and urine [2-5], In addition to their classical role in biosynthetic processes, amino acids play a key role in immune cell activation and in meeting the energy demands required for the rapid growth of cancer cells [6], The complex interplay between amino acid metabolism and the initiation, progression, and modulation of breast cancer makes amino acids promising candidates for use in the diagnosis and prediction of this type of cancer [3,7,8], However, variability in the concentrations of individual amino acids in body fluids depends not only on the molecular phenotype of the breast cancer, but also on the age and ethnic background of the patients [9,10], As a consequence, the scientific literature contains numerous conflicting conclusions arising from differences in the patient cohorts investigated [11-13], Accordingly, the use of concentrations of individual amino acids as potential diagnostic parameters for breast cancer does not satisfy the requirements of clinical practice. There is therefore an urgent need to develop novel parameters based on plasma amino acid concentration ratios, which would enable the identification of breast cancer in patients with high accuracy and reliability, while also allowing determination of the tumor subtype and its proliferative status.

[0006] It is therefore an object of the present invention to provide sensitive and specific diagnostic parameters based on the determination of ratios of amino acid concentrations in plasma for use in the diagnosis of breast cancer. It is a further object of the present invention to provide a non-invasive method for the diagnosis of breast cancer, characterized by high specificity and sensitivity, particularly for diagnosing the presence of breast cancer, determining its molecular subtype, and assessing its proliferation index.The present invention further relates to a set of diagnostic markers comprising glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, for use in the diagnosis of breast cancer.

[0007] Preferably, the set is for use in diagnosing breast cancer having a molecular subtype selected from the group consisting of the triple-negative subtype, the HER2-positive subtype, and the luminal B subtype.

[0008] Preferably, the set is for use in assessing the proliferative activity of breast cancer.

[0009] A further aspect of the invention relates to an in vitro method for diagnosing breast cancer, characterized in that the method comprises the following steps:

[0010] (A) determining, in a biological sample, the concentrations of amino acids selected from the group consisting of glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, and then

[0011] (B) determining the following diagnostic indicators:

[0012] (i) (glutamic acid + glutamine) / (glycine + tryptophan + proline), or

[0013] (ii) tryptophan + threonine, or

[0014] (iii) glutamic acid + citrulline + threonine, or

[0015] (iv) glutamic acid + glutamine + aspartic acid, or

[0016] (v) glutamic acid - (asparagine + proline),

[0017] and subsequently

[0018] (C) comparing the diagnostic indicators determined in step (B) with reference diagnostic indicators determined in a subject not having breast cancer, wherein:

[0019] (I) if the amino acid ratio in the diagnostic indicator of step (B) (i) is > 0.9, the subject is diagnosed as having breast cancer;

[0020] (II) if the amino acid concentration in the diagnostic indicator of step (B) (ii) is > 99.9 pmol / L, the subject is diagnosed as having luminal B subtype breast cancer;(III) if the amino acid concentration in the diagnostic indicator of step (B) (iii) is < 81.55 pmol / L, the subject is diagnosed as having HER2-positive subtype breast cancer;

[0021] (IV) if the amino acid concentration in the diagnostic indicator of step (B) (iv) is > 430.9 pmol / L, the subject is diagnosed as having triple-negative breast cancer; and (V) if the absolute value of the diagnostic indicator of step (B) (v) is < 45.14 pmol / L, the subject is diagnosed as having breast cancer with Ki-67 levels above 30%.

[0022] Preferably, in the method according to the invention, the biological sample is blood plasma. The set of diagnostic markers according to the invention may significantly improve early disease detection and the individualization of therapy, since early detection of breast cancer enables treatment to be initiated at an earlier stage, which is critical for increasing therapeutic efficacy and improving prognosis. The metabolite set comprising amino acids belonging to different groups, such as glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, and in particular changes in the concentrations of these metabolites, reflect specific metabolic processes associated with the development of breast cancer. Detection and analysis of diagnostic indicators comprising ratios and / or sums of the aforementioned metabolites allow not only earlier diagnosis of the disease, but also more precise adjustment of therapy to the individual needs of the patient and effective monitoring of the course of treatment. Accordingly, they may constitute a valuable complement to currently available diagnostic methods.

[0023] The method according to the invention provides a tool for the evaluation of breast cancer that allows identification of the presence of breast cancer, determination of the molecular subtype of the tumor, and prediction of its aggressiveness, and thus of the likely course of the disease. In view of the heterogeneity of breast cancer, the diagnostic indicators according to the invention may support improved classification of tumor subtypes, which in turn enables treatment to be tailored to the specific molecular profile of the tumor. A further advantage of the indicators according to the invention is their potential to increase diagnostic sensitivity and specificity, thereby compensating for limitations of existingmethods, such as mammography or traditional tumor markers. Importantly, plasma-based tests are also more economical and easier to perform on a large scale, which supports their use in screening programs.

[0024] The method according to the invention enables detection of breast cancer owing to the high AUROC value (0.92) obtained for the parameter based on the concentration of combined amino acids, and may therefore constitute an effective tool for early diagnosis, which is crucial for improving patient prognosis. By offering the possibility of identifying a specific tumor subtype, namely luminal B, HER2-positive, or triple-negative, the solution may assist in tailoring therapy to the individual needs of patients. By enabling assessment of the proliferative status of the tumor, as determined by the Ki-67 index, the method may contribute to improved selection of therapeutic strategies, which in turn may improve treatment effectiveness. In addition, plasma testing is non-invasive, thereby allowing more frequent and less burdensome monitoring of patients.

[0025] Potential end users of the solution according to the invention include hospitals and oncology clinics, in which the method may be implemented as part of standard diagnostic procedures for evaluating patients suspected of having breast cancer across different age groups, with particular benefit in the diagnosis of breast cancer in younger patients, as well as diagnostic laboratories and clinical research centers.

[0026] The invention is illustrated by the accompanying figures, in which:

[0027] Fig- 1 shows the diagnostic utility of the combined ratio of plasma amino acid concentrations [(glutamic acid + glutamine) / (glycine + tryptophan + proline)] for differentiating patients with breast cancer (BC) from healthy subjects. (A) Values of the ratio [(glutamic acid + glutamine) / (glycine + tryptophan + proline)] in plasma samples from patients with breast cancer and healthy subjects. Results are presented as mean ± SEM; control group, n = 50; BC, n = 213; *** indicates statistical significance at p < 0.001. (B) ROC curve for the plasma ratio [(glutamic acid + glutamine) / (glycine + tryptophan + proline)] (BC, n = 213; control group, n = 50; statistical significance p < 0.0001). The AUROC (area under the curve) value for this parameter was 0.92.Fig. 2 shows the values of selected sums of plasma amino acid concentrations in different molecular subtypes of breast cancer, namely luminal B, HER2-positive, and triple-negative subtypes, as well as their diagnostic value. (A) Levels of the sum of plasma tryptophan and threonine concentrations in patients with luminal B subtype breast cancer as compared with patients with other breast cancer subtypes. *** indicates statistical significance at p < 0.001. (B) ROC curve for the sum of plasma tryptophan and threonine concentrations in patients with luminal B subtype breast cancer as compared with patients with other breast cancer subtypes. Statistical significance was p < 0.0001. AUROC = 0.74. (C) Levels of the sum of plasma glutamic acid, citrulline, and threonine concentrations in patients with HER2-positive subtype breast cancer as compared with patients with other breast cancer subtypes. *** indicates statistical significance at p < 0.001. (D) ROC curve for the sum of plasma glutamic acid, citrulline, and threonine concentrations in patients with HER2-positive breast cancer as compared with patients with other breast cancer subtypes. Statistical significance was p < 0.0001. The AUROC value for this parameter was 0.89. (E) Levels of the sum of plasma glutamic acid, glutamine, and aspartic acid concentrations in patients with triple-negative subtype breast cancer as compared with patients with other breast cancer subtypes. *** indicates statistical significance at p < 0.001. (F) ROC curve for the sum of plasma glutamic acid, glutamine, and aspartic acid concentrations in patients with triple-negative subtype breast cancer as compared with patients with other breast cancer subtypes. Statistical significance was p < 0.0001. The AUROC value for this parameter was 0.88. Results in panels (A), (C), and (E) are presented as mean ± SEM. The numbers of patients in the respective groups were as follows: luminal B subtype, n = 23; non-luminal B subtype (remaining breast cancer types), n = 190; HER2-positive subtype, n = 13; non-HER2-positive subtype (remaining breast cancer types), n = 200; triple-negative subtype, n = 22; non-triple-negative subtype (remaining breast cancer types), n = 191.

[0028] Fig- 3 shows the diagnostic utility of a parameter expressed as the absolute value of the equation [plasma glutamic acid concentration] - [plasma asparagine concentration + plasma proline concentration] for differentiating patients according to the value of the tumor proliferation marker Ki-67. (A) Absolute value of the equation [plasma glutamic acidconcentration] - [plasma asparagine concentration + plasma proline concentration] in patients with breast cancer classified according to different Ki-67 levels (<30% and >30%). Results are presented as mean ± SEM; *** indicates statistical significance at p < 0.001. (B) ROC curve for the absolute value of the equation [glutamic acid] - [asparagine + proline] in plasma samples from patients with breast cancer classified according to Ki-67 levels above 30%, as compared with patients having Ki-67 levels below 30%. Statistical significance was p < 0.0001. ROC analysis showed an AUROC value of 0.89 for discriminating patients with breast cancer having Ki-67 levels above 30%. The number of patients with breast cancer characterized by a Ki-67 index <30% was n = 170, and the number of patients with breast cancer characterized by a Ki-67 index >30% was n = 40.

[0029] The invention is further illustrated by the following examples.

[0030] Examples

[0031] The study was conducted in accordance with the principles of the Declaration of Helsinki. The study was approved by the local bioethics committee. Informed consent was obtained from all participants. Demographic and clinical data were collected from the participants, including age and family history. In the case of patients with breast cancer, specific clinicopathological features were also taken into account, including the molecular subtype of breast cancer and the Ki-67 index value.

[0032] The inclusion criteria required that patients with breast cancer be between 18 and 79 years of age, have histopathologically confirmed breast cancer, and have no other malignant disease. In addition, the patients with breast cancer must not have undergone surgery, chemotherapy, or radiotherapy prior to plasma sample collection.

[0033] The inclusion criteria for healthy participants required an age of between 18 and 79 years and no history of cancer or other breast disease. The exclusion criteria included participants with chronic systemic diseases, such as cardiovascular disease, hypertension, or diabetes, metabolic disorders such as phenylketonuria or hepatic encephalopathy, and mental disorders, as well as women who were menstruating, pregnant, or breastfeeding.Based on these criteria, 50 healthy women were enrolled as a control group (mean age: 57 ± 10, mean ± SEM; median age: 56), and 213 patients with breast cancer were enrolled (mean age: 59 ± 12, mean ± SEM; median age: 61).

[0034] Plasma was obtained from fasting peripheral blood collected into EDTA tubes, followed by centrifugation at 1200 x g for 5 minutes at 21 °C.

[0035] A set of diagnostic markers comprising glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, for use in the diagnosis of breast cancer, and the respective plasma concentrations thereof, were determined using a modified procedure based on an established protocol

[0014] , A 25 pl plasma sample was mixed with 5 pl of an isotopomer mixture for each amino acid, followed by deproteinization of the sample with acetonitrile at a ratio of 1:2.4, and centrifugation at 20,800 x g for 10 minutes at 4°C. The supernatant was collected and lyophilized. The residue was then dissolved in 25 pl of water. The concentrations of amino acids and their derivatives were determined by liquid chromatography coupled with mass spectrometry (LC / MS) according to a previously described methodology

[0014] , The identity of each amino acid was confirmed on the basis of molecular mass similarity, fragmentation pattern, and chromatographic retention time, in accordance with the results obtained in the earlier study

[0014] ,

[0036] After obtaining concentration values for the individual amino acids listed above, the following diagnostic indicators were determined therefrom:

[0037] • (glutamic acid + glutamine) / (glycine + tryptophan + proline), or

[0038] • tryptophan + threonine, or

[0039] • glutamic acid + citrulline + threonine, or

[0040] • glutamic acid + glutamine + aspartic acid, or

[0041] • the absolute value of the equation: glutamic acid - (asparagine + proline),

[0042] after which the determined diagnostic indicators were compared with reference diagnostic indicators determined in a subject not having breast cancer.A first stage of the method according to the invention concerned determination of a parameter differentiating the group of patients with breast cancer from women not affected by the disease. Subsequently, taking into account the molecular heterogeneity of breast cancer, which constitutes one of the greatest diagnostic challenges, and based on the clinical characteristics of the group of patients with breast cancer, indicators were determined that enable differentiation of the molecular subtypes of breast cancer associated with higher malignancy and poorer clinical prognosis, namely the triple-negative subtype, the HER.2-positive subtype, and the luminal B subtype. Finally, a diagnostic indicator associated with plasma amino acid concentrations was determined, suggesting a risk of increased tumor progression, reflected by altered levels in patients with an elevated tumor proliferation index Ki-67 (above 30%).

[0043] The study demonstrated that the parameter based on the combined plasma amino acid concentration, calculated as the amino acid ratio (glutamic acid + glutamine) / (glycine + tryptophan + proline), was significantly increased in patients with breast cancer as compared with healthy subjects (Fig. 1A). This parameter achieved a satisfactory AUROC value of 0.92 (Fig. 1B). The AUROC value (Area Under the Receiver Operating Characteristic curve) is a statistical parameter used to assess the ability of a diagnostic test to discriminate between two groups. The ROC curve represents the relationship between sensitivity and specificity of the diagnostic test for different threshold values. The higher the AUROC value, the better the ability of the test to correctly distinguish between the groups under investigation. The optimal cut-off range for the above indicator extends from greater than 0.9 to 1.02 and above, at a sensitivity of ^80% and a specificity of ^90%. An AUROC value of 0.92 indicates that the proposed diagnostic indicator discriminates very effectively between patients with breast cancer and healthy subjects, with a sensitivity of 87.3% and a specificity of 91.7%. Moreover, it was demonstrated that the plasma amino acid profile is strongly dependent on the molecular subtype of breast cancer. Statistical analyses as well as ROC analyses showed:

[0044] • an increased sum of plasma tryptophan and threonine concentrations in patients with luminal B subtype breast cancer (Fig. 2A), as compared with patients having other molecular subtypes, namely luminal A, HER2-positive,and triple-negative. The AUROC value for the sum of plasma tryptophan and threonine concentrations in patients with luminal B subtype breast cancer, as compared with patients having other breast cancer subtypes, was 0.74 (Fig.

[0045] 2B). The optimal cut-off range for the above indicator extends from greater than 99.9 pmol / L, with a specificity of 70.21% and a sensitivity of 74.07%, to greater than 101.3 pmol / L, with a specificity of 73.94% and a sensitivity of 70.37%;

[0046] • a decreased sum of plasma glutamic acid, citrulline, and threonine concentrations in patients with HER2-positive subtype breast cancer (Fig.

[0047] 2C), as compared with patients having other molecular subtypes, namely luminal A, luminal B, and triple-negative. The AUROC value for the sum of plasma glutamic acid, citrulline, and threonine concentrations in patients with HER2-positive subtype breast cancer, as compared with patients having other molecular subtypes, namely luminal A, luminal B, and triple-negative, was 0.89 (Fig. 2D). The optimal cut-off range for the above indicator extends from less than 81.55 pmol / L, with a specificity of 87.18% and a sensitivity of 84.62%, to less than 98.19 pmol / L, with a specificity of 82.56% and a sensitivity of 92.31%;

[0048] • an increased sum of plasma glutamic acid, glutamine, and aspartic acid concentrations in patients with triple-negative subtype breast cancer (Fig. 2E), as compared with patients having other molecular subtypes, namely luminal A, luminal B, and HER2-positive. The AUROC value for the sum of plasma glutamic acid, glutamine, and aspartic acid concentrations in patients with triple-negative subtype breast cancer, as compared with patients having other molecular subtypes, namely luminal A, luminal B, and HER2-positive, was 0.88 (Fig. 2F). The optimal cut-off range for the above indicator extends from greater than 430.9 pmol / L, with a specificity of 80.21% and a sensitivity of 86.36%, to greater than 432.3 pmol / L, with a specificity of 81.25% and a sensitivity of 81.82%.In addition, a parameter expressed as the absolute value of the equation [plasma glutamic acid concentration] - [plasma asparagine concentration + plasma proline concentration] was calculated, and this parameter was decreased in patients with breast cancer classified as having Ki-67 levels above 30%, as compared with patients having Ki-67 levels below 30% (Fig.

[0049] 3A). ROC analysis showed an AUROC value of 0.89 for discriminating patients with breast cancer having Ki-67 levels above 30% (Fig. 3B). The optimal cut-off range for the above indicator extends from less than 45.14 pmol / L, with a specificity of 83.64% and a sensitivity of 80.82%, to less than 49.12 pmol / L, with a specificity of 80.00% and a sensitivity of 83.56%.

[0050] References:

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[0055] [5] Zhou, J.; Wang, Y.; Zhang, X. Metabonomics Studies on Serum and Urine of Patients with Breast Cancer Using 1H-NMR Spectroscopy. Oncotarget 2017, 0 (0). https: / / doi.org / 10.18632 / oncotarget.16210.

[0056] [6] Wang, Z.; Wu, X.; Chen, H. N.; Wang, K. Amino Acid Metabolic Reprogramming in Tumor Metastatic Colonization. Frontiers in Oncology. 2023. https: / / doi.org / 10.3389 / fonc.2023.1123192.

[0057] [7] Wang, X.; Zhao, X.; Chou, J.; Yu, J.; Yang, T.; Liu, L.; Zhang, F. Taurine, Glutamic Acid and Ethylmalonic Acid as Important Metabolites for Detecting Human Breast Cancer Basedon the Targeted Metabolomics. Cancer Biomarkers 2018, 23 (2). https: / / doi.org / 10.3233 / CBM-181500.

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[0059] [9] Shen, J.; Yan, L.; Liu, S.; Ambrosone, C. B.; Zhao, H. Plasma Metabolomic Profiles in Breast Cancer Patients and Healthy Controls: By Race and Tumor Receptor Subtypes. Transl. Oncol. 2013, 6 (6). https: / / doi.org / 10.1593 / tlo.13619.

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[0010] Tayyari, F.; Gowda, G. A. N.; Olopade, O. F.; Berg, R.; Yang, H. H.; Lee, M. P.; Ngwa, W. F.; Mittal, S. K.; Raftery, D.; Mohammed, S. I. Metabolic Profiles of Triple-Negative and Luminal A Breast Cancer Subtypes in African-American Identify Key Metabolic Differences. Oncotarget 2018, 9 (14). https: / / doi.org / 10.18632 / oncotarget.24433.

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[0011] Bel’skaya, L. V.; Gundyrev, I. A.; Solomatin, D. V. The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review. Current Issues in Molecular Biology. 2023. https: / / doi.org / 10.3390 / cimb45090474.

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[0012] Baranovicova, E.; Racay, P.; Zubor, P.; Smolar, M.; Kudelova, E.; Halasova, E.; Dvorska, D.; Dankova, Z. Circulating Metabolites in the Early Stage of Breast Cancer Were Not Related to Cancer Stage or Subtypes but Associated with Ki67 Level. Promising Statistical Discrimination from Controls. Mol. Cell. Probes 2022, 66. https: / / doi.Org / 10.1016 / j.mcp.2022.101862.

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Claims

Claims1. A set of diagnostic markers comprising glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, for use in diagnosing breast cancer.

2. The set according to claim 1, for use in diagnosing breast cancer having a molecular subtype selected from the group consisting of triple-negative, HER2-positive, and luminal B.

3. The set according to claim 1, for use in assessing proliferation of breast cancer using the Ki-67 index.

4. An in vitro method for diagnosing breast cancer, characterized in that it comprises the following steps:a) determining, in a biological sample, the concentrations of amino acids selected from the group consisting of glutamic acid, glutamine, glycine, tryptophan, proline, threonine, citrulline, aspartic acid, and asparagine, and thenb) determining the following diagnostic indicators:i. (glutamic acid + glutamine) / (glycine + tryptophan + proline), or ii. tryptophan + threonine, oriii. glutamic acid + citrulline + threonine, oriv. glutamic acid + glutamine + aspartic acid, orv. glutamic acid - (asparagine + proline), and thenc) comparing the diagnostic indicators determined in step b) with reference diagnostic indicators determined in a subject not having breast cancer, wherein:I. if the amino acid ratio in the diagnostic indicator of step b) i. is >0.9, the subject is diagnosed as having breast cancer;II. if the amino acid concentration in the diagnostic indicator of step b) ii. is >99.9 pmol / L, the subject is diagnosed as having luminal B subtype breast cancer;III. if the amino acid concentration in the diagnostic indicator of step b) iii. is <81.55 pmol / L, the subject is diagnosed as having HER2-positive subtype breast cancer;IV. if the amino acid concentration in the diagnostic indicator of step b) iv. is >430.9 pmol / L, the subject is diagnosed as having triple-negative breast cancer; andV. if the absolute value of the diagnostic indicator of step b) v. is <45.14 pmol / L, the subject is diagnosed as having breast cancer with a Ki-67 index above 30%.

5. The method according to claim 4, characterized it that the biological sample is blood plasma.

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