Circulating biomarkers and methods for detecting lung cancer

Abstract

Disclosed herein are biomarkers associated with lung cancer and methods for determining whether a subject has or is at risk of developing lung cancer, the methods comprising detecting the expression level of at least one or more miRNAs in a biological sample obtained from the subject.

Description

[Technical Field]

[0001] FIELD OF THE INVENTION The present invention relates generally to the field of molecular biology. In particular, the present invention relates to biomarkers associated with lung cancer and methods of using the biomarkers to determine whether a subject has or is at risk of developing lung cancer. [Background technology]

[0002] Background of the Invention According to global cancer statistics reported by the International Agency for Research on Cancer, lung cancer is the leading cause of cancer death worldwide, accounting for 18% of all cancer deaths in 2020 (Ferlay et al., 2020). The 5-year survival rate for lung cancer patients diagnosed at an early stage (stage I or II) is approximately 70%, but decreases to less than 20% when the cancer is diagnosed at a later stage (stage III and IV), and the high mortality rate can be attributed to the detection of cancer at an advanced stage.

[0003] Chest x-rays and sputum smears are the most common screening techniques for lung cancer, but their low sensitivity limits their usefulness in diagnosing early-stage cancer. When indicated, fiberoptic bronchoscopy or biopsy can be used to directly examine lesions and determine the nature of pathology. However, these approaches are invasive and difficult to apply to large-scale testing of at-risk populations. Low-dose spiral CT is currently considered the most effective technique for lung cancer screening. While noninvasive and highly sensitive, it has a false-positive rate of up to 96.4% and the cost of screening is relatively high. Therefore, there is an unmet need for effective methods for screening populations that will improve the rate of early diagnosis and treatment of lung cancer and reduce lung cancer deaths. There is a need to provide alternative methods for lung cancer diagnosis. Summary of the Invention

[0004] Summary of the Invention In one aspect, the present disclosure relates to a method for determining whether a subject has or is at risk of developing lung cancer, the method comprising detecting / determining the expression level of at least one miRNA from a biological sample obtained from the subject, wherein the at least one miRNA is selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p and hsa-miR-877-5p.

[0005] In certain embodiments, the method comprises detecting at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 miRNAs.

[0006] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting / determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p in a biological sample.

[0007] In certain embodiments, the expression level of at least one miRNA selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p is compared with the expression level of one or more miRNAs in a control, and a differential expression level of the one or more miRNAs in a biological sample obtained from the subject compared to the control is indicative of the subject having or being at risk of developing lung cancer.

[0008] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises: a. Obtaining a biological sample from a subject; b. contacting the biological sample with a set of isolated probes suitable for detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p; c. comparing the expression level of one or more miRNAs in a biological sample with the level of the same miRNA in a control; d. Determining whether the subject has or is at risk for developing lung cancer by differential expression of one or more miRNAs compared to a control; Includes.

[0009] In certain embodiments, the biological sample obtained from the subject is a non-cellular biological fluid.

[0010] In certain embodiments, the non-cellular biological fluid is plasma or serum.

[0011] In certain embodiments, the method further comprises detecting the presence of at least one additional biomarker. In certain embodiments, the method further comprises detecting the expression level of at least one additional biomarker from a biological sample obtained from the subject. In some embodiments, the additional biomarker is one or more selected from carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), or cytokeratin 19 fragment antigen (CYFRA21-1). In some other embodiments, the biomarker is CEA.

[0012] In certain embodiments, the method for determining whether a subject has lung cancer or is at risk of developing lung cancer further comprises additional clinical testing. In some embodiments, the additional clinical testing comprises one or more of an imaging test, a sputum cytology test, a biopsy, or a combination thereof. In certain embodiments, the imaging test comprises a CT scan, an X-ray, an MRI, or a PET scan.

[0013] Also provided is a method of treating a subject identified as having lung cancer, comprising: a. determining whether a subject has or is at risk of developing lung cancer by detecting the expression level of at least one miRNA from a biological sample obtained from the subject, wherein the at least one miRNA is selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p; b. comparing the expression level of one or more miRNAs in the biological sample with the expression level in a control; c. Treating a subject determined to have or be at risk for lung cancer with one or more therapies appropriate for treating lung cancer; Includes.

[0014] In some embodiments, the one or more therapies suitable for treating lung cancer include administration of an anti-cancer compound, surgery, and / or radiation therapy.

[0015] In some embodiments, the control may comprise one or more biological samples obtained from a healthy subject, a disease-free subject, a cancer-free subject, a lung cancer-free subject, and / or a subject not suffering from or at risk of developing lung cancer, hi some embodiments, the control may comprise the expression levels of one or more biomarkers for use in determining whether a subject has or is at risk for lung cancer, measured in one or more biological samples obtained from the subject.

[0016] In certain embodiments, the at least one miRNA is detectable by one or more methods such as, but not limited to, sequencing, nucleic acid hybridization, microarray nucleic acid amplification, and the like.

[0017] Also provided is a kit for determining whether a subject has or is at risk of developing lung cancer, the kit comprising a set of isolated probes capable of detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0018] In some embodiments, the kit comprises a set of isolated probes capable of detecting hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0019] In some embodiments, the probe is selected from the group consisting of an aptamer, an antibody, an affibody, a peptide, and a nucleic acid.

[0020] In some embodiments, the kit comprises a set of isolated probes suitable for determining the expression level of at least one miRNA selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p, detectable by one or more methods, such as, but not limited to, sequencing, nucleic acid hybridization, microarray, and nucleic acid amplification. In some examples, nucleic acid amplification may include, but is not limited to, quantitative reverse transcription polymerase chain reaction (qRT-PCR), reverse transcription polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), locked nucleic acid PCR, clustered regularly interspaced short palindromic repeat (CRISPR)-based assays, or isothermal amplification assays.

[0021] In certain embodiments, the kit further comprises probes and / or reagents for detecting at least one additional biomarker. In some embodiments, the additional biomarker is one or more selected from carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), or cytokeratin 19 fragment antigen (CYFRA21-1). In some embodiments, the additional biomarker is CEA.

[0022] In another aspect, the present invention relates to a combination of biomarkers suitable for determining whether a subject has or is at risk of developing lung cancer, the combination comprising at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 biomarkers selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p. In some embodiments, the combination of biomarkers comprises hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p. In some embodiments, the combination of biomarkers further comprises CEA. In some embodiments, the combination of biomarkers is suitable for use in detecting biomarkers in a biological sample obtained from a subject, wherein the biological sample is a non-cellular biological fluid, such as a plasma and / or serum sample.

[0023] In another aspect, the present invention also relates to the use of at least one reagent suitable for detecting one or more biomarkers in the manufacture or preparation of a diagnostic agent / kit for use in any of the above methods for determining whether a subject has or is at risk of developing lung cancer. In some embodiments, at least one reagent is used to measure / determine the expression level of at least one, two, three, four, five, six, seven, eight, nine, ten, eleven, or twelve biomarkers selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p in a biological sample obtained from a subject. In some embodiments, the reagents are used to measure / determine the expression levels of biomarkers including hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p. In some embodiments, the reagents are used to measure / determine the expression levels of at least one additional biomarker. In some embodiments, the additional biomarkers are one or more selected from carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), or cytokeratin 19 fragment antigen (CYFRA21-1).

[0024] definition As used herein, the term "miRNA" refers to microRNAs, small non-coding RNAs that, in some instances, contain approximately 19-25 nucleotides and are found in plants, animals, and some viruses. miRNAs are known to function in RNA silencing and post-transcriptional regulation of gene expression. These highly conserved RNAs regulate gene expression by binding to the 3'-untranslated region (3'-UTR) of specific mRNAs. For example, each miRNA is thought to regulate multiple genes, and hundreds of miRNA genes are expected to exist in higher eukaryotes; therefore, miRNAs are likely to be transcribed from several different loci within the genome. These genes encode long RNAs with hairpin structures that, when processed by a series of RNase III enzymes (including Drosha and Dicer), form miRNA duplexes, typically approximately 19-25 nucleotides long, with a 2-nt overhang at the 3' end. As will be understood by those skilled in the art, miRNAs are a type of polynucleotide with sequences containing letters such as "AUGC." Nucleotides will be understood to be ordered from left to right in 5'>3' order, unless otherwise noted, with "A" representing adenosine, "U" representing uracil, "G" representing guanosine, and "C" representing cytosine. The letters A, U, G, and C can be used to represent the bases themselves.

[0025] As used herein, "lung cancer" (abbreviated in some instances as "LC") refers to a disease in which malignant (cancer) cells form in the tissues of the lung. The main subtypes of lung cancer are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), but also include adenoid cystic carcinoma, lymphoma, and sarcoma. The main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These subtypes may originate from different types of lung cells, but are classified together as NSCLC because treatment and prognosis are often similar.

[0026] As used herein, "biomarker" or "marker" can refer to a gene, protein, or miRNA whose expression level or concentration is altered in a sample compared to a control. As used herein, a control refers to an expression level or concentration of a biomarker that indicates or correlates with a different outcome compared to the outcome of interest. For example, a biomarker can be an miRNA whose expression level or concentration is altered (e.g., increased or decreased) in a sample from a subject with a condition (e.g., lung cancer) compared to a control. Those skilled in the art will understand that comparing expression levels in a control does not necessarily involve obtaining a sample from a subject without lung cancer and testing the sample simultaneously with the test subject. In some embodiments, the control can be a control sample included in the kit, or a threshold set representing a range of biomarker expression within which a subject is identified as having or at risk of having lung cancer.

[0027] As used herein, "biological sample" or "sample" is intended to include any sampling of cells, tissues, or bodily fluids in which biomarker expression can be detected. Examples of such biological samples include, but are not limited to, biopsies, smears, blood, lymph, urine, saliva, or any other bodily secretion or derivative thereof. Blood may include, for example, whole blood, plasma, serum, or any derivative of blood. In some embodiments, the biological sample is a liquid biological sample. In some embodiments, the biological sample is a non-cellular biological fluid. In some embodiments, the non-cellular biological fluid may include serum and / or plasma. Samples may be obtained from a subject by a variety of techniques known to those skilled in the art.

[0028] As used herein, the term "expression level" or "level" of a biomarker refers to the presence / absence, amount, or concentration of a biomarker in a biological sample, and is expressed in any appropriate format or units as determined by one skilled in the art. For example, nucleic acid expression can be expressed as, but not limited to, copy number (copy / mL), Ct (cycle threshold), Cq (quantification cycle), Ct / Cq, or log2 scale expression level. In addition, expression levels can be expressed as a score constructed using any form of mathematical model or algorithm.

[0029] As used herein, the term "differential expression" refers to the measurement of a cellular component in comparison with a control or another sample, thereby determining, for example, a difference in the concentration, presence, or intensity of said cellular component. The results of such a comparison can be given absolutely, i.e., the component is present in the sample but not in the control, or relatively, i.e., the expression or concentration of the component is increased or decreased compared to the control. The terms "increased" and "decreased" in this context can be interchangeable with the terms "upregulated" and "downregulated," which are also used in this disclosure.

[0030] When described in some embodiments, the present disclosure may disclose a method as a specific sequence of steps. However, it will be understood that unless specifically necessary, the method should not be limited to the specific sequence of steps disclosed. Other sequences of steps may be possible. The specific order of steps disclosed herein should not be construed as undue limitation. Unless specifically necessary, the method disclosed herein should not be limited to steps performed in the order described. The sequence of steps may be varied and still remain within the scope of the present disclosure.

[0031] As used herein, "probe" refers to any molecule or agent capable of selectively detecting an intended target biomolecule, for example, by directly or indirectly binding to the target biomolecule. The target molecule may be a biomarker, for example, a nucleotide transcript or protein encoding or corresponding to the biomarker. In light of the present disclosure, a probe may be synthesized by one skilled in the art or generated by appropriate biological preparations. The probe may be designed to be labeled. Examples of molecules that can be used as probes include, but are not limited to, oligonucleotides, RNA, DNA (e.g., primers), proteins, peptides, antibodies, aptamers, affibodies, and organic molecules. In the case of probes designed for the detection of nucleic acid biomarkers, such probes may target the target region, a complementary nucleic acid on the opposite strand, or a copy of the same generated via an amplification process.

[0032] As used herein, the term "imaging" relates to various non-invasive methods of visualizing the inside of a subject's body to diagnose disease or determine the extent / progression of disease, and may include computed tomography (CT) (including low-dose CT scans such as low-dose spiral CT or low-dose helical CT), magnetic resonance imaging (MRI), positron emission tomography (PET), or X-ray.

[0033] As used herein, the term "biopsy" relates to the removal of cells or tissues for examination, for example by a pathologist, to determine the presence or extent of disease.

[0034] As used herein, the term "sputum cytology" relates to the examination of cells found in sputum to detect abnormal cells, such as lung cancer cells.

[0035] As used herein, the term "(statistical) classification" refers to the problem of identifying a set of categories (subpopulations) to which a new observation belongs based on a training dataset containing observations (or examples) known to be members of the categories. An example is assigning a diagnosis to a particular patient as described by observed patient characteristics (gender, blood pressure, presence or absence of specific symptoms, etc.). In machine learning terminology, classification is considered supervised learning, i.e., learning examples where a training set of precisely identified observations is available. The corresponding unsupervised procedure is known as clustering and involves grouping data into categories based on some measure of intrinsic similarity or distance. Individual observations are often analyzed into a set of quantifiable characteristics, variously known as explanatory constants or features. These characteristics can vary in categorical (e.g., blood type "A," "B," "AB," or "O"), ordinal ("large," "medium," or "small"), integer value (e.g., the number of occurrences of a certain word in an email), or real value (e.g., blood pressure readings). Other classifiers work by comparing an observation to a previous observation using a similarity or distance function. In particular, an algorithm that implements classification in a specific implementation is known as a classifier. The term "classifier" sometimes refers to the mathematical function implemented by a classification algorithm that maps input data to categories.

[0036] As used herein, the terms "pre-trained" or "supervised (machine) learning" refer to the machine learning task of inferring a function from labeled training data. The training data may consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called a supervisory signal). A supervised learning algorithm, i.e., the algorithm being trained, analyzes the training data and generates an inference function that can be used to map new examples. In an optimal scenario, the algorithm will be able to correctly determine the class level of unseen examples. This requires the learning algorithm to generalize from the training data to unseen examples in a "rational" way.

[0037] As used herein, the term "score" refers to an integer or number and can be determined mathematically using computer models known in the art, for example, but not limited to, SVM, and calculated using any one of many mathematical equations and / or algorithms known in the art for statistical classification. Such scores are used to list an outcome within a range of possible outcomes. The relevance and statistical significance of such scores depend on the size and quality of the underlying data set used to establish the outcome spectrum. For example, blinded samples can be input into an algorithm, and a score is then calculated based on information provided by analysis of the blinded samples, thereby producing a score for the blinded sample. This score can be used to determine, for example, how likely a patient from whom the blinded sample was obtained is to have or not have cancer. The ends of the spectrum can be defined logically based on the data provided or arbitrarily according to the needs of the experimenter. In either case, it is necessary to define the spectrum before the blinded samples are tested. As a result, a score produced by such a blinded sample, for example a number "45," based on a spectrum defined as a scale of 1 to 50, with "1" defined as no cancer and "50" defined as cancer, may indicate that the corresponding patient has cancer. [Brief explanation of the drawings]

[0038] [Figure 1] 1 shows a receiver operating characteristic curve ("ROC curve") validating the performance of an exemplary embodiment of an miRNA assay for detecting subjects with or at risk of lung cancer. The x-axis shows the specificity of the assay, and the y-axis shows the sensitivity of the assay. [Figure 2] 1 shows ROC curves validating the performance of an exemplary embodiment of a miRNA assay in combination with CEA for detecting subjects with or at risk of lung cancer, where the x-axis indicates the specificity of the assay and the y-axis indicates the sensitivity of the assay. [Figure 3] 1 shows the performance of an exemplary panel of miRNAs provided in Table 4 for detecting subjects with or at risk for lung cancer. [Figure 4] 1 shows the performance of CEA in combination with an exemplary panel of miRNAs provided in Table 11 for detecting subjects with or at risk for lung cancer.

[0039] Detailed Description of the Invention miRNAs are evolutionarily conserved, single-stranded, non-coding RNAs (miRNAs) of 19 to 25 nucleotides whose primary function is to mediate degradation or translational repression of mRNA targets. Under normal physiological conditions, miRNAs are critical components of feedback mechanisms in a wide range of biological pathways, including cell proliferation, differentiation, and apoptosis. Conversely, dysregulated miRNAs have been implicated in hallmarks of cancer, including supporting tumor growth by inhibiting growth suppression, maintaining proliferative signaling to resist cell death, activating invasion and metastasis, and promoting angiogenesis. While miRNAs regulate carcinogenesis through tumor suppressive or oncogenic activity, increasing evidence of aberrant miRNA expression in various malignant lesions is now known.

[0040] Lung cancer diagnosis is commonly performed via sputum cytology, biopsy testing, or radiological imaging such as computed tomography (CT) scans, magnetic resonance imaging (MRI) scans, or positron emission tomography (PET) scans. Sputum cytology is rapid and inexpensive, but suffers from a high false-negative rate. The use of radiological imaging is costly and exposes subjects to radiation, making it unsuitable for use in screening for lung cancer in the general population. Blood tests for protein biomarkers, such as carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), or cytokeratin 19 fragment antigen (CYFRA21-1), do not provide sufficient accuracy for diagnostic use in clinical settings.

[0041] miRNAs are considered suitable biomarkers because changes in miRNA expression profiles in cancer reflect disease progression, and because miRNAs are stable and accessible in numerous bodily fluids, including blood, urine, and saliva. Minimally invasive methods, such as miRNA-based liquid biopsies, have the potential to overcome these drawbacks and improve overall detection accuracy.

[0042] The present invention relates to a method for determining whether a subject has or is at risk of developing lung cancer, comprising detecting and / or measuring and / or determining the expression levels of one or more biomarkers, particularly the miRNAs listed in Table 1, present in a biological sample obtained from the subject.

[0043] [Table 1]

[0044] In certain embodiments of the present invention, a method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression level of one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0045] In certain embodiments, a method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, or at least twelve miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0046] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-1280 and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0047] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-23b-3p, and hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0048] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-320a-3p, and hsa-miR-23b-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0049] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-877-5p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0050] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-181c-5p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0051] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-487b-3p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0052] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-199b-5p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0053] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-205-5p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0054] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-210-3p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0055] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-16-5p and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-92a-3p, and hsa-miR-342-3p.

[0056] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-92a-3p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, and hsa-miR-342-3p.

[0057] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or at least eleven miRNAs selected from hsa-miR-342-3p, and hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, and hsa-miR-92a-3p.

[0058] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of hsa-miR-1280 and hsa-miR-487b-3p.

[0059] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, and hsa-miR-199b-5p.

[0060] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, and hsa-miR-205-5p.

[0061] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, and hsa-miR-16-5p.

[0062] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer comprises detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, and hsa-miR-320a-3p.

[0063] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, and hsa-miR-23b-3p.

[0064] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, and hsa-miR-181c-5p.

[0065] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, and hsa-miR-92a-3p.

[0066] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, and hsa-miR-210-3p.

[0067] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, and hsa-miR-342-3p.

[0068] In certain embodiments, methods for determining whether a subject has or is at risk of developing lung cancer comprise detecting and / or measuring and / or determining the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0069] In certain embodiments, the method for determining whether a subject has or is at risk for developing lung cancer comprises: The method includes detecting, measuring, and / or determining the expression level of one or more miRNAs selected from hsa-miR-23b-3p, hsa-miR-320a-3p, hsa-miR-877-5p, hsa-miR-181c-5p, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-1280, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-16-5p, hsa-miR-92a-3p, and hsa-miR-342-3p in a biological sample obtained from the subject, and comparing the expression of the one or more miRNAs with that in a control, wherein a differential expression level of the one or more miRNAs compared to the control indicates that the subject has or is at risk of developing lung cancer.

[0070] In some embodiments, the control may include one or more biological samples obtained from a healthy subject, a disease-free subject, a cancer-free subject, a lung cancer-free subject, and / or a subject not suffering from or at risk of developing lung cancer. In some embodiments, the control may include the expression level of one or more biomarkers measured in one or more biological samples obtained from a subject for use in determining whether the subject has or is at risk of developing lung cancer. In some embodiments, the control sample may not be obtained at the same time as the biological sample from the subject to be tested, but may be represented by a control sample provided with the kit, or, in some sense, by a threshold value for miRNA expression in a control population determined in an initial clinical study.

[0071] In some embodiments, the expression level of one or more of miR-23b-3p, miR-320a-3p, miR-877-5p, miR-181c-5p, miR-487b-3p, miR-199b-5p, miR-205-5p, miR-210-3p, miR-16-5p, and / or miR-92a-3p is increased in the biological sample compared to that of a control. In some embodiments, the expression level of miR-1280 and / or miR-342-3p is decreased in the biological sample compared to that of a control.

[0072] In some embodiments, the differential expression level of one or more of miR-23b-3p, miR-320a-3p, miR-877-5p, miR-181c-5p, miR-487b-3p, miR-199b-5p, miR-205-5p, miR-210-3p, miR-16-5p, and / or miR-92a-3p is increased in a biological sample in a subject having or at risk of developing lung cancer compared to a control. In some embodiments, the differential expression level of miR-1280 and / or miR-342-3p is decreased in a biological sample in a subject having or at risk of developing lung cancer compared to a control.

[0073] In certain embodiments, the method of determining whether a subject has or is at risk for developing lung cancer comprises: a. contacting a biological sample obtained from a subject with a set of isolated probes suitable for detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p; b. comparing the expression level of one or more miRNAs in the biological sample with the miRNA level of a control; c. Determining whether the subject has or is at risk for developing lung cancer based on the differential expression level of one or more miRNAs compared to a control. Includes.

[0074] In certain embodiments, the biological sample comprises a non-cellular biological fluid, hi some embodiments, the non-cellular biological fluid may be plasma or serum.

[0075] In certain embodiments, the method for determining whether a subject has or is at risk of developing lung cancer further comprises detecting the expression level of at least one additional biomarker, such as, but not limited to, carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), or cytokeratin 19 fragment antigen (CYFRA21-1).

[0076] In certain embodiments, the method of determining whether a subject has or is at risk of developing lung cancer further comprises one or more tests, such as, but not limited to, an imaging test, a sputum cytology, a biopsy, or a combination thereof.

[0077] In certain embodiments, subjects suffering from or at risk of developing lung cancer may be further examined using diagnostic imaging tests, including, but not limited to, sputum cytology, biopsy, fine-needle aspiration, or X-ray, computed tomography (CT), low-dose CT scan, magnetic resonance imaging (MRI) scan, or positron emission tomography. Lung cancer screening methods are known in the art, including the latest edition of the NCCN Oncology Clinical Diagnostic Guidelines for Lung Cancer Screening, the entire contents of which are incorporated herein by reference. Also provided are methods of treating a subject determined to have lung cancer using the methods disclosed herein. In some examples, the methods disclosed herein may further include administering treatment to a subject determined to have lung cancer. Such subjects will be referred to a physician and, if deemed appropriate, will be treated with an appropriate treatment, such as, but not limited to, an anti-cancer compound, surgery, immunotherapy, or radiation therapy, or a combination thereof. If a subject is diagnosed with lung cancer, treatment options include surgery, radiation therapy (including but not limited to external beam radiation therapy, intensity-modulated radiation therapy, proton therapy, stereotactic radiotherapy, or brachytherapy), chemotherapy (including but not limited to cisplatin, carboplatin, paclitaxel, docetaxel, gemcitabine, vinorelbine, etoposide, or pemetrexed, alone or in combination), targeted therapy (agents directed against specific aspects of angiogenesis, EGFR, KRAS, ALK, NTRK, BRAF, ROS1, etc.), or chemotherapy (including but not limited to chemotherapy, chemotherapy, or combinations of chemotherapy). or monoclonal antibodies, and the like, and may include, but are not limited to, osimertinib, erlotinib, gefitinib, afatinib, dacotinib, crizotinib, ceritinib, dabrafenib, trametinib, bevacizumab, amivantamab, cetuximab), immunotherapy (e.g., PD-1 and PDL-1 inhibitors such as pembrolizumab or nivolumab), or cell therapy (including chimeric antigen receptor T cells).Methods for treating lung cancer are known in the art, including the most recent edition of the NCCN Clinical Diagnostic Guidelines in Oncology for Non-Small Cell Lung Cancer and the NCCN Clinical Diagnostic Guidelines in Oncology for Small Cell Lung Cancer, which are incorporated by reference herein in their entireties.

[0078] In certain embodiments, the method of treating a subject suffering from lung cancer comprises: a. contacting a biological sample obtained from a subject with a set of isolated probes suitable for detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p; b. comparing the expression level of one or more miRNAs in the biological sample with the miRNA level of a control; c. Determining whether the subject has or is at risk for developing lung cancer based on the differential expression level of one or more miRNAs compared to a control. d. Treating a subject determined to have or be at risk for lung cancer with one or more therapies selected from the group consisting of administration of an anti-cancer compound, surgery, and / or radiation therapy. Includes.

[0079] In certain embodiments, the method of treating a subject afflicted with lung cancer further comprises measuring the level of at least one additional biomarker in the subject.

[0080] In certain embodiments, the additional biomarker is one or more selected from carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), and cytokeratin 19 fragment antigen (CYFRA21-1). In some examples, the additional biomarker is carcinoembryonic antigen (CEA).

[0081] In certain embodiments, the method further comprises imaging, sputum cytology, or biopsy.

[0082] Further provided herein are compositions / agents / reagents for use in the methods disclosed herein. In some embodiments, such compositions / agents / reagents may include, but are not limited to, probes, antibodies, affibodies, nucleic acids, and / or aptamers. In some embodiments, the compositions are capable of (or detect) the level of expression of a panel of biomarkers (e.g., miRNAs) from a biological sample.

[0083] Any composition can be provided in the form of a kit or reagent mixture. For example, labeled probes can be provided in a kit for detecting a panel of biomarkers. The kit can contain all components necessary or sufficient for the assay, including target enrichment reagents, detection reagents (e.g., probes and / or fluorescent dyes), buffers, control reagents (e.g., positive and negative controls), amplification reagents, solid supports, labels, instructions, standards, and reference samples. In certain embodiments, the kit includes a set of probes for the panel of biomarkers and a solid support for immobilizing the set of probes. In certain embodiments, the kit includes a set of probes for the panel of biomarkers, a solid support, and reagents for processing the sample to be tested (e.g., reagents for isolating proteins or nucleic acids from the sample). In certain embodiments, the invention includes the use of detection reagents suitable for detecting a panel of biomarkers in the manufacture or preparation of a kit for use (or when used) in determining whether a subject has or is at risk of having lung cancer.

[0084] In certain embodiments, detection reagents (e.g., probes) suitable for use in the kits include, but are not limited to, oligonucleotides, RNA, DNA (e.g., primers), proteins, peptides, antibodies, aptamers, affibodies, and organic molecules. In the case of probes designed for the detection of nucleic acid biomarkers, such probes may be directed to the target region, a complementary nucleic acid on the opposite strand, or a copy of the same generated via an amplification process.

[0085] In some embodiments, provided herein are DNA-, RNA-, and protein-based detection methods that directly or indirectly detect the biomarkers disclosed herein. The present invention also provides components, reagents, and kits for such diagnostic purposes. The diagnostic methods described herein can be qualitative or quantitative. Quantitative diagnostic methods can be used, for example, to compare detected biomarker levels with cutoff or threshold levels. Where applicable, qualitative or quantitative diagnostic methods can also include amplification of targets, signals, or intermediate steps.

[0086] In some embodiments, biomarkers are detected at the nucleic acid (e.g., DNA or RNA) level. For example, the amount of biomarker RNA (e.g., miRNA) present in a sample is determined (e.g., to determine the expression level of the biomarker). Biomarker nucleic acids (e.g., miRNA, amplified cDNA, etc.) can be detected / quantified using various nucleic acid techniques known to those skilled in the art, including, but not limited to, sequencing, nucleic acid hybridization (e.g., Northern blot), microarray, and nucleic acid amplification (e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR), reverse transcription polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), locked nucleic acid (LNA) real-time PCR, CRISPR-based assays, or isothermal amplification assays. Isothermal amplification assays include, for example, nicking endonuclease amplification reaction (NEAR) assays, transcription-mediated amplification (TMA) assays, loop-mediated isothermal amplification (LAMP) assays, helicase-dependent amplification (HDA) assays, clustered regularly interspaced short palindromic The miRNA biomarkers may include, but are not limited to, a CRISPR assay, or a strand displacement amplification (SDA) assay. In some embodiments, the method used to detect the miRNA biomarkers may include the use of the assay methodology disclosed in WO2011159256A1, and the kit for detecting miRNAs may include a stem-loop oligonucleotide designed based on the teachings of WO2011159256A1, the disclosure of which is incorporated herein by reference.

[0087] Further provided herein is a kit for determining whether a subject has or is at risk of developing lung cancer, the kit comprising a set of isolated probes capable of detecting one or more miRNA biomarkers selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0088] In certain embodiments, the kit comprises a set of isolated probes capable of detecting hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

[0089] In certain embodiments, the kit further comprises reagents for detecting at least one additional biomarker in a biological sample obtained from the subject.

[0090] In certain embodiments, the additional biomarker is carcinoembryonic antigen (CEA).

[0091] The invention illustratively described herein can suitably be practiced without any element(s), limitation(ies), not specifically disclosed herein. Thus, for example, terms such as "comprising," "including," and "containing" are to be interpreted expansively and without limitation. Furthermore, the terms and expressions used herein are used for purposes of description and not limitation, and the use of such terms and expressions is not intended to exclude equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention as claimed. Thus, while the invention has been specifically disclosed by preferred embodiments and optional features, it should be understood that modifications and variations of the invention disclosed and embodied herein may be practiced by those skilled in the art, and that such modifications and variations are considered to be within the scope of the invention.

[0092] The inventions are described broadly and generically herein. Each of the narrower species and subgeneric groupings falling within the generic disclosure also form part of the invention. This includes a generic description of the invention with a provisos or negative limitation excluding any subject matter from the genus, regardless of whether the excluded content is specifically set forth herein.

[0093] Throughout this disclosure, certain embodiments may be disclosed in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosed ranges. Thus, the description of a range should be considered to have specifically disclosed not only each individual numerical value within that range, but also all possible subranges. For example, a description of a range of 1 to 6 should be considered to have specifically disclosed subranges such as 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, 3 to 6, etc., as well as each individual numerical value within that range, such as 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0094] Other embodiments are within the scope of the following claims and non-limiting examples. Additionally, where features or aspects of the invention are described in terms of a Markush group, those skilled in the art will recognize that the invention also can be described in terms of any individual member or subgroup of Markush group members.

[0095] Illustrative embodiments of the present invention are provided in the following examples. While the illustrative embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, it should be understood that the invention is not limited to these examples.

[0096] Sample Calculation of Prediction or Risk Score for Lung Cancer Risk It is known in the art that biomarkers (e.g., miRNAs) can be combined to form a biomarker panel, for example, using a linear model to calculate a disease risk score. Examples include calculating a risk score using logistic regression, forming a linear model, etc. Prediction scores can also be calculated using a classification algorithm selected from the group comprising: support vector machine (SVM) algorithm, logistic regression algorithm, multinomial logistic regression algorithm, Fisher's linear discriminant algorithm, quadratic classifier algorithm, perceptron algorithm, k-nearest neighbor algorithm, artificial neural network algorithm, random forest algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method that combines multiple learning algorithms.

[0097] A challenge in this area concerns the identification of relevant biomarkers, such as circulating miRNAs, that can be applied to identify individuals at risk for diseases such as lung cancer. If relevant miRNAs could be identified through thorough and well-designed studies, it would be within the skill of those familiar with the state of the art to apply the measured relevant miRNAs in such statistical models to generate a score for predicting the risk of a subject having lung cancer.

[0098] Examples of such mathematical methods used to perform the calculations disclosed herein, such as the calculation of prediction scores, may include, but are not limited to, support vector machine algorithms, logistic regression algorithms, multinomial logistic regression algorithms, Fisher's linear discriminant algorithms, quadratic classifier algorithms, perceptron algorithms, k-nearest neighbor algorithms, artificial neural network algorithms, random forest algorithms, decision tree algorithms, naive Bayes algorithms, adaptive Bayes network algorithms, and ensemble learning methods that combine multiple learning algorithms.In one example, the calculation of prediction scores is performed using a linear model and a support vector machine algorithm.

[0099] As an example to aid in understanding, different disease risk scores are calculated for controls and subjects with lung cancer. A suitable probability distribution of the disease risk scores for controls and subjects with lung cancer indicates that there is a separation between the two groups. Based on this prior probability and the previously determined suitable probability distribution, the probability (risk) of subjects who are not sure whether they have lung cancer can be calculated based on their disease risk score values. The higher the score, the higher the risk the subject has of having lung cancer. Furthermore, for example, the disease risk score can refer to the fold change in the probability (risk) of subjects who are not sure whether they have lung cancer, compared to, for example, the lung cancer rate in a high-risk population.

[0100] A prerequisite for the success of such a process is the availability of high-quality data: quantitative data of all detected miRNAs in a large number of well-defined clinical samples, including appropriate controls from symptomatic non-lung cancer patients (disease controls), will not only improve the accuracy and precision of the results, but also ensure the consistency of the identified biomarker panel for further clinical application, for example, using quantitative polymerase chain reaction (qPCR).

[0101] As an example, Equation 1 below illustrates the use of a linear model for lung cancer risk prediction, where a disease risk score (unique to each subject) indicates the likelihood that the subject has lung cancer, calculated by summing weighted measurements of, for example, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, or 19 miRNAs.

[0102]

number

[0103] where log2copy_miRNA i where K is the logarithmically transformed copy number of n individual miRNAs in the test sample amount (e.g., in the example of 12 miRNAs, n=12). From this, the coefficient Ki and constant C used to weight multiple miRNA targets can be derived by applying a linear model. Subjects with a disease risk score lower than 0 will be considered to be 0, and subjects with a disease risk score higher than 100 will be considered to be 100. Deriving the relevant disease risk score and cutoff for identifying subjects at risk of having lung cancer will be within the understanding of one of ordinary skill in the art who knows the identity of the relevant miRNA biomarkers.

[0104] A further example of such an algorithm for calculating a risk score is the use of a logistic regression model:

[0105]

number

[0106] where n is the number of individual miRNAs (e.g., n = 12 for the 12 miRNA example), Ki is a coefficient used to weight multiple miRNA targets, Ct is the cycle threshold (usually defined as the number of cycles of the real-time PCR reaction required for the fluorescent signal to exceed the threshold), and the constant can be derived by applying a linear model.

[0107] Further examples of such algorithms further incorporate the use of reference samples containing known levels of the assayed miRNA to normalize the scores of each assay run to account for run-to-run variations (which may be referred to as quantitative references (QRs)), and in some embodiments, the average QR score may be used to calculate an expected QR score. Using the example provided above, an example of how such normalization may be performed is provided below. Deriving relevant disease risk scores and cutoffs to identify subjects at risk of having lung cancer would be within the understanding of one skilled in the art, knowing the identity of the relevant miRNA biomarkers.

[0108]

number

[0109] where n is the number of individual miRNAs (e.g., n=12 for the example of 12 miRNAs), Ki is a coefficient used to weight multiple miRNA targets, Ct is the cycle threshold (usually defined as the number of cycles in a real-time PCR reaction required for the fluorescent signal to cross the threshold, sometimes also known as Cq), and the constant can be derived by applying a linear model, QR run is the QR score obtained from a specific run, and QR expected is the average QR score from multiple validation runs.

[0110] In some embodiments, test can be used to classify patients into low-risk or high-risk category based on the result derived from the Ct of target miRNA.Low-risk result indicates that patient has low risk of suffering from or developing lung cancer.High-risk result indicates the presence of miRNA associated with high risk of lung cancer, and these patients are at risk of suffering from lung cancer, and therefore should be considered for further diagnostic workup according to clinical guidelines. [Example]

[0111] Methods and Materials A reverse transcription-quantitative polymerase chain reaction (RT-PCR) method was used to detect multiple miRNA biomarkers associated with lung cancer and non-lung cancer groups. The assay involved five steps: Step 1: RNA isolation from platelet-poor plasma Step 2: cDNA synthesis Step 3: Preamplification Step 4: Detecting miRNAs by quantitative PCR (qPCR) Step 5: Conversion of miRNA Ct (threshold cycle) values ​​(also known as Cq or quantification cycle) into risk scores

[0112] RNA extraction was performed using a semi-automated system. Pretreatment was performed by manually adding lysis buffer C and proteinase K to platelet-poor plasma (PPP), followed by incubation at 37°C for 15 minutes. The pretreated sample was added to an extraction cartridge and later loaded into a Maxwell® CSC 48, Maxwell® CSC 16, Maxwell® RSC 48, or Maxwell® RSC 16 instrument. The automated portion of the extraction was performed on the instrument using paramagnetic particles to provide a mobile solid phase for optimized sample capture, washing, and nucleic acid purification.

[0113] In the cDNA synthesis step, miRNA targets from each sample were converted to cDNA in a single reaction using miRNA-specific stem-loop-based reverse transcription primers. The stem-loop structure improved primer hybridization to the target miRNA compared to linear primers, resulting in higher analytical sensitivity. It also minimized primer hybridization to miRNA precursors, thereby improving the analytical specificity of the assay.

[0114] In the preamplification step, cDNA was amplified in a single reaction using a pair of sequence-specific PCR primers. The preamplification reaction increased the copy number of miRNA targets before the qPCR step while maintaining target amplification specificity. In the qPCR step, each miRNA target was amplified with a sequence-specific forward PCR primer and a hemi-nested sequence-specific reverse PCR primer. This combination enhanced the discrimination of a broad range of highly homologous family members. The amplification products were then detected using SYBR Green I dye in a singleplex reaction under accelerated cycling conditions.

[0115] Development and validation of miRNA biomarkers for lung cancer diagnosis Study design The primary objective of this study was to identify and develop a circulating biomarker signature identified in plasma and / or serum samples with the goal of identifying subjects at risk for or affected by lung cancer. Blood samples were collected from 623 subjects, of which 525 were ultimately used for development and validation. Reasons for sample exclusion included lack of clinical information, failure to meet inclusion criteria, or significant hemolysis in the sample. Details of the cohort of subjects recruited are detailed in Table 2.

[0116] [Table 2]

[0117] miRNA biomarker development and validation A total of 525 clinical samples were used to develop and validate the miRNA classifier, including 261 lung cancer (LC) samples and 264 non-LC samples. Tests were performed 57 times at three different sites using three manufactured kit lots. All samples were run in random order and operators were blinded. Run data were collected and normalized, and a risk score was calculated using a logistic regression model (the exemplary approach presented herein) to classify LC and non-LC patients.

[0118] Table 3 details the performance of miRNA biomarkers when used alone or in combination with other miRNA biomarkers, and exemplary embodiments of such miRNA biomarkers are provided in Tables 4-8 (and graphically illustrated in Figure 1). Panel performance generally peaks with combinations of five or more miRNA biomarkers, and the addition of additional miRNA biomarkers does not significantly change the AUC. Additionally, an exemplary panel of selected three-miRNA combinations is shown in Table 9.

[0119] The use of miRNA biomarkers alone achieved a performance of 80.5% overall area under the curve (AUC), 75.5% sensitivity, and 70.1% specificity (Figure 2).

[0120] The levels of carcinoembryonic antigen (CEA) were further combined with the miRNA classifier obtained in the previous step. Table 10 details the performance of CEA as a miRNA biomarker alone or in combination with other miRNA biomarkers, with exemplary embodiments of such miRNA biomarkers provided in Table 11 (shown graphically in Figure 3). The combination of CEA and miRNA improves the performance of the test, and therefore it may be worthwhile to test the levels of CEA in addition to measuring the levels of miRNA biomarkers in a subject.

[0121] A logistic regression model was used to calculate a new risk score based on both miRNA and CEA levels. The new model combining miRNA with CEA achieved an AUC of 86.4%, a sensitivity of 84.3%, and a specificity of 71.6% (Figure 4).

[0122] For the avoidance of doubt, the miRNA combinations of the present invention are not limited to the exemplary panels as listed in Tables 4-9 and 11. Any suitable combination or number of miRNAs may be selected from the 12 miRNAs to form a panel that provides a desired or sufficiently high AUC.

[0123] [Table 3]

[0124] [Table 4]

[0125] [Table 5]

[0126] [Table 6]

[0127] [Table 7]

[0128] [Table 8]

[0129] [Table 9]

[0130] [Table 10]

[0131] [Table 11]

[0132] Consideration There is an unmet clinical need for noninvasive methods for the early detection of lung cancer. Provided herein are circulating biomarkers suitable for identifying subjects with or at risk of developing lung cancer. Circulating biomarkers have been identified that, when used alone or in combination as a biomarker expression signature, are suitable for distinguishing subjects with or at risk of developing lung cancer from non-lung cancer controls. The use of circulating biomarkers suggests that panels may serve as tools for the early detection of the condition, as such tests are readily available for general laboratory use and minimally invasive. The biomarkers identified in this study were also shown to be useful in combination with other cancer biomarkers, such as carcinoembryonic antigen (CEA). In this study, biomarker development and validation were performed at three different sites to account for inter-site variability, including the use of three different kit lots to account for manufacturing variability. Running the tests in random order with operators blinded to sample type further reduces potential bias and ensures the robustness and reliability of the biomarker panel in determining whether a subject has or is at risk for lung cancer.

[0133] The examples provided herein relate to exemplary embodiments of the intended uses of the present invention. In some embodiments, the biomarkers are intended to be used, possibly in conjunction with other clinical factors or symptoms, to aid in the diagnosis of lung cancer in a subject. Thus, the biomarkers are intended to distinguish subjects who have or are at risk of having lung cancer from subjects who do not have lung cancer.

[0134] Possible embodiments of such biomarker-based tests can be research reagents, laboratory-developed tests, or in vitro detection kits to aid in the early detection or diagnosis of lung cancer using the biomarker panels disclosed herein. In other examples, patients classified as at risk for or suffering from lung cancer can be treated with one or more therapeutic agents or therapies suitable for use in treating the disease. It is envisioned that such tests can be used alone or in combination with other methods, including sputum cytology, biopsy, or imaging tests (including CT scans, MRIs, X-rays, or PET scans), cancer biomarker tests (such as CEA), or any other method for diagnosing lung cancer recognized by a physician or equivalent skilled in the art.

[0135] References 1. Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Pineros M, Znaor A, Soerjomataram I, Bray F (2020). Global Cancer Observatory: Cancer Today. Lyon, France: International Agency for Research on Cancer. Available from: https: / / gco.iarc.fr / today, accessed 12 Dec 2022. 2. Too HP and Azlinda BA. Modified stem-loop oligonucleotide mediated reverse transcription and base-spacing constrained quantitative PCR. 2011 Dec 22. (WO2011159256A1). 3. NCCN Clinical Practice Guidelines in Oncology for Non-Small Cell Lung Cancer version 6.2022 (c) National Comprehensive Cancer Network, Inc. 2022. All rights reserved. Accessed Dec 12, 2022. To view the most recent and complete version of the guideline, go online to NCCN.org. 4. NCCN Clinical Practice Guidelines in Oncology for Small Cell Lung Cancer version 2.2023 (c) National Comprehensive Cancer Network, Inc. 2022. All rights reserved. Accessed Dec 12, 2022. To view the most recent and complete version of the guideline, go online to NCCN.org. 5. NCCN Clinical Practice Guidelines in Oncology for Lung Cancer Screening version 1.2023 (c) National Comprehensive Cancer Network, Inc. 2022. All rights reserved. Accessed Dec 12, 2022. To view the most recent and complete version of the guideline, go online to NCCN.org.

Claims

1. 1. A method for determining whether a subject is suffering from or at risk of developing lung cancer, comprising detecting the expression level of at least one miRNA from a biological sample obtained from the subject, wherein the at least one miRNA is selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

2. 10. The method of claim 1, comprising detecting at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 miRNAs.

3. The method of claim 1 or claim 2, comprising detecting the expression levels of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

4. 10. The method of any one of the preceding claims, wherein a differential expression level of the one or more miRNAs compared to a control indicates that the subject has or is at risk of developing lung cancer.

5. contacting a biological sample obtained from the subject with an isolated set of probes suitable for detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p; b. comparing the expression level of said one or more miRNAs in said biological sample with the level of the same miRNAs in a control; c. Determining whether the subject has or is at risk for developing lung cancer based on the differential expression of the one or more miRNAs compared to the control.

10. The method of any one of the preceding claims, comprising:

6. 10. The method of any preceding claim, further comprising detecting the expression level of at least one additional biomarker from a biological sample obtained from said subject.

7. 7. The method of claim 6, wherein the additional biomarkers are one or more biomarkers selected from the group consisting of carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), and cytokeratin 19 fragment antigen (CYFRA21-1).

8. 10. The method of any one of the preceding claims, wherein the biological sample is a non-cellular biological fluid.

9. The method of claim 8, wherein the non-cellular biological fluid is plasma and / or serum.

10. 10. The method of any one of the preceding claims, wherein the control comprises one or more biological samples obtained from a healthy subject, a disease-free subject, a cancer-free subject, a lung cancer-free subject, and / or a subject not suffering from or not at risk of developing lung cancer.

11. 10. The method of any preceding claim, further comprising imaging, sputum cytology, biopsy, or a combination thereof.

12. 1. A method of treating a subject suffering from lung cancer, comprising: a. Determining whether a subject has or is at risk of developing lung cancer using the method of any one of claims 1 to 11; and b. Treating the subject determined to be suffering from or at risk of lung cancer with one or more therapies selected from the group consisting of administration of an anti-cancer compound, surgery, and / or radiation therapy. A method comprising:

13. 10. The method of any preceding claim, wherein the at least one miRNA is detected by one or more methods selected from the group consisting of sequencing, nucleic acid hybridization, microarray, and nucleic acid amplification.

14. A kit for determining whether a subject is suffering from or at risk of developing lung cancer, comprising a set of isolated probes and / or reagents capable of detecting one or more miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

15. The kit according to claim 14, wherein the set of isolated probes and / or reagents is capable of detecting hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, hsa-miR-16-5p, hsa-miR-320a-3p, hsa-miR-23b-3p, hsa-miR-181c-5p, hsa-miR-92a-3p, hsa-miR-210-3p, hsa-miR-342-3p, and hsa-miR-877-5p.

16. 16. The kit of claim 14 or 15, wherein the probe is selected from the group consisting of an aptamer, an antibody, an affibody, a peptide, and a nucleic acid.

17. The kit of any one of claims 14 to 16, wherein the at least one miRNA is detected by one or more methods selected from the group consisting of sequencing, nucleic acid hybridization, microarray, and nucleic acid amplification.

18. The kit of any one of claims 14 to 17, further comprising probes and / or reagents for detecting at least one additional biomarker.

19. The kit of claim 18, wherein the biomarker is one or more selected from carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), and cytokeratin 19 fragment antigen (CYFRA21-1).

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