WO2024128987A2 - Biomarqueurs circulants pour la détection du cancer du poumon et procédés associés - Google Patents

Biomarqueurs circulants pour la détection du cancer du poumon et procédés associés Download PDF

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WO2024128987A2
WO2024128987A2 PCT/SG2023/050840 SG2023050840W WO2024128987A2 WO 2024128987 A2 WO2024128987 A2 WO 2024128987A2 SG 2023050840 W SG2023050840 W SG 2023050840W WO 2024128987 A2 WO2024128987 A2 WO 2024128987A2
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mir
hsa
lung cancer
subject
risk
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Ruiyang ZOU
He Cheng
Lihan ZHOU
Li Zhou
Jin Yu
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MiRXES Lab Pte. Ltd.
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention relates generally to the field of molecular biology.
  • the present invention relates to biomarkers associated with lung cancer and methods of using the biomarkers to determine whether a subject suffers from, or is at risk of developing, lung cancer.
  • Chest X-rays and sputum smears are the most common techniques for lung cancer screening, but such tests suffer from low sensitivity and hence has limited utility in diagnosing cancer at an early stage.
  • fibre optic bronchoscopy or biopsy may be used directly examine the lesion and determine the nature of the pathology, but such approaches are invasive, and are difficult to be applied for larger scale testing of the at-risk population.
  • Low- dose spiral CT is currently considered to be the most effective technique for lung cancer screening, which is non-invasive and highly sensitive, and however has a false -positive rate of up to 96.4%, and the cost for screening is relatively high. Therefore, there is an unmet need for an effective method for screening of the population to improve the rate of early diagnosis and treatment of lung cancer to reduce lung cancer mortality. There is a need to provide an alternative method of diagnosis of lung cancer.
  • the present disclosure relates to a method of determining whether a subject suffers from, or is at risk of developing lung cancer, wherein the method comprises 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.
  • the method comprises detecting 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.
  • the method for determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting/determining the expression level 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.
  • the method for determining whether a subject is suffering from, or is at risk of developing lung cancer comprises: a. obtaining a biological sample from a subject; b. contacting the biological sample 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; c.
  • the biological sample obtained from the subject is a non- cellular biological fluid.
  • the non-cellular biological fluid is plasma or serum.
  • 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 the biological sample obtained from the subject.
  • 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 (CYFRA 21-1). In some other embodiments, the biomarker is CEA.
  • the method for determining whether a subject is suffering from, or is at risk of developing lung cancer further comprises additional clinical tests.
  • the additional clinical test comprises one or more imaging test, sputum cytology, biopsy, or a combination thereof.
  • the imaging tests comprises a CT scan, an X-ray, an MRI or a PET scan.
  • Also provided are methods of treating a subject identified to be suffering from lung cancer comprising: a. determining whether a subject is suffering from, 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 the one or more miRNAs in the biological sample with
  • the one or more treatments suitable for treating lung cancer comprises the administration of an anti -cancer compound, surgery, and/or radiation therapy.
  • control may comprise one or more biological samples obtained from a healthy subject, a non-diseased 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.
  • control may comprise the expression level of the one or more biomarkers for use in determining whether a subject is suffering from, or is at risk of lung cancer measured in the one or more biological samples obtained from said subjects.
  • the at least one miRNA is detectable by one or more method, such as, but is not limited to, sequencing, nucleic acid hybridisation, microarray nucleic acid amplification, and the like.
  • kits for determining whether a subject suffers from, or is at risk of developing lung cancer comprising an isolated set of 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.
  • the kit comprises isolated set of 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.
  • the probe is selected from the group consisting of an aptamer, an antibody, an affibody, a peptide and a nucleic acid.
  • the kit comprises isolated sets of 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 method such as, but is not limited to, sequencing, nucleic acid hybridisation, microarray, and nucleic acid amplification, and the like.
  • hsa-miR-877-5p detectable by one or more method such as, but is not limited to, sequencing
  • nucleic acid amplification may include, but is not limited to, a quantitative reverse transcription - polymerase chain reaction (qRT-PCR), reverse transcription-polymerase chain reaction (RT- PCR), quantitative polymerase chain reaction (qPCR), a locked nucleic acid PCR, a clustered regularly interspaced short palindromic repeat (CRISPR)-based assay, or isothermal amplification assay.
  • qRT-PCR quantitative reverse transcription - polymerase chain reaction
  • RT-PCR reverse transcription-polymerase chain reaction
  • qPCR quantitative polymerase chain reaction
  • CRISPR clustered regularly interspaced short palindromic repeat
  • the kit further comprises probes and/or reagents for detecting at least one additional biomarker.
  • 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 (CYFRA 21-1).
  • CEA carcinoembryonic antigen
  • NSE neuron-specific enolase
  • CA-125 cancer antigen 125
  • CYFRA 21-1 cytokeratin 19 fragment antigen
  • the additional biomarker is CEA.
  • the invention relates to a biomarker combination suitable for determining whether a subject suffers from, or is at risk of developing lung cancer, wherein the combination comprises at least 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.
  • the biomarker combination 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.
  • the biomarker combination further comprises CEA.
  • the biomarker combination is suitable for use in detecting the 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 a serum sample.
  • the invention also relates to 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 method of determining whether a subject suffers from, or is at risk of developing lung cancer.
  • the at least one reagent is for use in measuring/determining in a biological sample obtained from a subject 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.
  • the reagent is for use in measuring/determining the expression level of biomarkers comprising 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.
  • the reagent is for use in measuring/determining the expression level of at least one additional biomarker.
  • 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 (CYFRA 21-1).
  • miRNA refers to microRNA, small non-coding RNA molecules, which in some examples contain about 19 to 25 nucleotides, and are found in plants, animals, and some viruses. miRNAs are known to have functions in RNA silencing and post- transcriptional regulation of gene expression. These highly conserved RNAs regulate the expression of genes by binding to the 3 ’-untranslated regions (3’-UTR) of specific mRNAs. For example, each miRNA is thought to regulate multiple genes, and since hundreds of miRNA genes are predicted to be present in higher eukaryotes, miRNAs tend to be transcribed from several different loci in the genome.
  • miRNA is a type of polynucleotide that has sequences comprising letters such as “AUGC.” It will be understood that the nucleotides are in 5’ > 3’ order from left to right and that “A” denotes adenosine, “U” denotes uracil, “G” denotes guanosine, and “C” denotes cytosine, unless otherwise noted.
  • the letters A, U, G, and C can be used to refer to the base themselves.
  • lung cancer refers to a disease in which malignant (cancer) cells form in the tissues of the lung.
  • the main subtypes of lung cancer are the non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) but further includes adenoid cystic carcinomas, lymphomas, and sarcomas.
  • NSCLC non-small cell lung cancer
  • SCLC small cell lung cancer
  • the main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These subtypes, which may originate from different types of lung cells are classified collectively as NSCLC because their treatment and prognoses are often similar.
  • biomarker can refer to a gene, protein, or miRNA whose level of expression or concentration in a sample is altered compared to that of a control.
  • a control refers to a level of expression or concentration of a biomarker that is indicative or correlated with a different outcome compared to the outcome of interest.
  • a biomarker can be a miRNA whose level of expression or concentration is altered (e.g., increased or decreased) compared to that of a control in a sample of a subject with a condition (i.e., lung cancer).
  • comparing the level of expression in the control does not necessarily entail obtaining a sample from a subject without lung cancer and testing said sample at the same time as the test subject.
  • said control could be a control sample incorporated in the kit or a threshold set to represent the range of expression of the biomarker where expression levels falling into this range would identify a subject as suffering from, or is at risk of suffering from, lung cancer.
  • biological sample or “sample” is intended to include any sampling of cells, tissues, or bodily fluids in which expression of a biomarker can be detected.
  • biological samples include, but are not limited to, biopsies, smears, blood, lymph, urine, saliva, or any other bodily secretion or derivative thereof.
  • Blood can, for example, include whole blood, plasma, serum, or any derivative of blood.
  • the biological sample is a liquid biological sample.
  • the biological sample is a non- cellular biological fluid.
  • the non-cellular bodily fluid may comprise serum and/or plasma. Samples can be obtained from a subject by a variety of techniques, which are known to those skilled in the art.
  • the term “expression level” or “level” of a biomarker refers to the presence/absence, amount or concentration of the biomarker in a biological sample, and may be represented in any suitable forms or units as determined by a person skilled in the art.
  • the expression level of nucleic acid e.g. DNA or RNA
  • the expression level of nucleic acid may be represented as, but not limited to, copy number (copy/mL), Ct (cycle threshold), Cq (quantification cycle), Ct/Cq or log2 scale expression levels.
  • the expression level may be expressed as a score constructed using any form of mathematical model or algorithm.
  • the term “differential expression” refers to the measurement of a cellular component in comparison to a control or another sample, and thereby determining the difference in, for example concentration, presence or intensity of said cellular component.
  • the result of such a comparison can be given in the absolute, that is a component is present in the samples and not in the control, or in the relative, that is the expression or concentration of component is increased or decreased compared to the control.
  • the terms “increased” and “decreased” in this case can be interchanged with the terms “upregulated” and “downregulated” which are also used in the present disclosure.
  • probe refers to any molecule or agent that is capable of selectively detecting an intended target biomolecule, for example, by binding directly or indirectly to the target biomolecule.
  • the target molecule can be a biomarker, for example, a nucleotide transcript or a protein encoded by or corresponding to a biomarker.
  • Probes can be synthesized by one of skill in the art, or derived from appropriate biological preparations, in view of the present disclosure. Probes can be specifically designed to be labelled. Examples of molecules that can be utilized as probes include, but are not limited to, oligonucleotides, RNA, DNA (e.g., primers), proteins, peptides, antibodies, aptamers, affibodies, and organic molecules.
  • a probe designed for the detection of a nucleic acid biomarker such a probe may be directed to the target region, the complementary nucleic acid sequence on the reverse strand, or copies of the same generated via an amplification process.
  • imaging test relates to various non-invasive methods for visualising the inside of a subject’s body to diagnose a disease or determine the extent/progression of a disease and may include computerised 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.
  • CT computerised tomography
  • MRI magnetic resonance imaging
  • PET positron emission tomography
  • X-ray X-ray
  • biopsy relates to the removal of a sample of cells or tissues for examination, for example by a pathologist, to determine the presence or extent of a disease.
  • sputum cytology relates to the examination of cells found in sputum to detect abnormal cells, such as lung cancer cells.
  • (statistical) classification refers to the problem of identifying to which of a set of categories (sub -populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
  • An example is assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.).
  • classification is considered an instance of supervised learning, i.e., learning where a training set of correctly identified observations is available.
  • the corresponding unsupervised procedure is known as clustering and involves grouping data into categories based on some measure of inherent similarity or distance.
  • the individual observations are analysed into a set of quantifiable properties, known variously as explanatory variables or features. These properties may variously be categorical (e.g., "A”, “B”, “AB” or “O”, for blood type), ordinal (e.g., “large”, “medium” or “small”), integer-valued (e.g., the number of occurrences of a part word in an email) or real-valued (e.g. a measurement of blood pressure). Other classifiers work by comparing observations to previous observations by means of a similarity or distance function. An algorithm that implements classification, especially in a concrete implementation, is known as a classifier. The term “classifier” sometimes also refers to the mathematical function, implemented by a classification algorithm, which maps input data to a category.
  • the term “pre-trained” or “supervised (machine) learning” refers to a machine learning task of inferring a function from labelled training data.
  • the training data can consist of a set of training examples.
  • each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal).
  • a supervised learning algorithm that is the algorithm to be trained, analyses the training data and produces an inferred function, which can be used for mapping new examples.
  • An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way.
  • the term “score” refers to an integer or number, that can be determined mathematically, for example by using computational models a known in the art, which can include but are not limited to, SVM, as an example, and that is calculated using any one of a multitude of mathematical equations and/or algorithms known in the art for the purpose of statistical classification. Such a score is used to enumerate one outcome on a spectrum of possible outcomes. The relevance and statistical significance of such a score depends on the size and the quality of the underlying data set used to establish the results spectrum. For example, a blind sample may be input into an algorithm, which in turn calculates a score based on the information provided by the analysis of the blind sample. This results in the generation of a score for said blind sample.
  • a decision can be made, for example, how likely the patient, from which the blind sample was obtained, has cancer or not.
  • the ends of the spectrum may be defined logically based on the data provided, or arbitrarily according to the requirement of the experimenter. In both cases the spectrum needs to be defined before a blind sample is tested.
  • the score generated by such a blind sample for example the number “45” may indicate that the corresponding patient has cancer, based on a spectrum defined as a scale from 1 to 50, with “1” being defined as being cancer-free and “50” being defined as having cancer.
  • FIG 1. shows the Receiver Operating Characteristic curve (“ROC curve”) demonstrating the performance of an exemplary embodiment of the miRNA assay for the detection of a subject suffering from or is at risk of lung cancer.
  • the x-axis shows the specificity of the assay while the y-axis shows the sensitivity of the assay.
  • FIG 2. shows the ROC curve demonstrating the performance of an exemplary embodiment of the miRNA assay in combination with CEA for the detection of a subject suffering from or is at risk of lung cancer.
  • the x-axis shows the specificity of the assay while the y-axis shows the sensitivity of the assay.
  • FIG 3. shows the performance of the exemplary panel of miRNAs provided in Table 4 for the detection of a subject suffering from or is at risk of lung cancer.
  • FIG 4. shows the performance of CEA in combination with the exemplary panel of miRNAs provided in Table 11 for the detection of a subject suffering from or is at risk of lung cancer.
  • miRNAs are evolutionary conserved, single -stranded non -coding RNAs of 19 to 25 nucleotides which primarily function in mediating the degradation or translational repression of mRNA targets.
  • miRNAs are key components of feedback mechanisms for a wide range of biological pathways such as cell proliferation, differentiation, and apoptosis.
  • dysregulated miRNAs have been implicated in the hallmarks of cancer including supporting tumour growth by inhibiting growth suppression, sustaining proliferative signalling and resisting cell death, activating invasion and metastasis, and promoting angiogenesis. It is now known that miRNAs regulate oncogenesis through their tumour suppressor or oncogenic activities, with increasing evidence of aberrant miRNA expression in a variety of malignancies.
  • the diagnosis of lung cancer is commonly performed via sputum cytology, biopsy examination or radiological imaging procedures such as computed tomography (CT) scan, magnetic resonance imaging (MRI) scan or positron emission tomography (PET) scan.
  • CT computed tomography
  • MRI magnetic resonance imaging
  • PET positron emission tomography
  • Sputum cytology is quick and inexpensive but suffer from a high rate of false negatives.
  • the use of radiological imaging procedures is both costly and exposes the subject to radiation and hence are not suitable 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 (CYFRA 21-1) do not provide sufficient accuracy for diagnostic use in the clinical setting.
  • CEA carcinoembryonic antigen
  • NSE neuron-specific enolase
  • CYFRA 21-1 cytokeratin 19 fragment antigen
  • miRNAs are deemed suitable as biomarkers because of altered miRNA expression profdes in cancer that reflect disease development, as well as the stability and the accessibility of circulating miRNAs in a myriad of body fluids including blood, urine, and saliva.
  • Minimally invasive methods, such as miRNA-based liquid biopsies, can potentially overcome these disadvantages and improve overall detection accuracy.
  • the present invention relates to methods of determining whether a subject suffers from, or is at risk of developing lung cancer, comprising the detection and/or measurement and/or determination of the expression level of one or more biomarkers present in a biological sample obtained from the subject, specifically the miRNAs listed in Table 1.
  • Table 1 Sequences of the miRNA biomarkers as described herein. The level of expression of the miRNAs are indicated as downregulated or upregulated with respect to the control.
  • the methods of determining whether a subject suffers from, 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.
  • miRNAs selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-1280 and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-23b-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-320a-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-877-5p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-181c-5p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-487b-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-199b-5p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-205-5p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level ofhsa-miR-210-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-16-5p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-92a-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-342-3p and 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, 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-1280, and hsa-miR-487b-3p.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-1280, hsa-miR-487b-3p, and hsa-miR-199b-5p.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, and hsa-miR-205- 5p.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level of hsa-miR-1280, hsa-miR-487b-3p, hsa-miR-199b-5p, hsa-miR-205-5p, and hsa-miR-16-5p.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, or is at risk of developing lung cancer comprises detecting and/or measuring and/or determining the expression level 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.
  • the methods of determining whether a subject suffers from, 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-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 these one or more miRNAs with that in a control, wherein differential expression levels of the one or more miRNA, as compared
  • the control may comprise one or more biological samples obtained from a healthy subject, a non-diseased 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.
  • the control may comprise the expression level of the one or more biomarkers for use in determining whether a subject suffers from, or is at risk of developing lung cancer measured in the one or more biological samples obtained from said subjects.
  • the control sample may not be obtained at same time as the biological sample from the subject to be tested and may be represented by a control sample provided with the kit or in some respect, a threshold for the expression of a miRNA in a control population determined in an earlier clinical study.
  • the expression level of one or more of 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, and/or hsa-miR-92a-3p is up-regulated in the biological sample as compared to that of the control.
  • the expression level of hsa-miR-1280 and/or hsa-miR-342-3p is down-regulated in the biological sample as compared to that of the control.
  • the differential expression level of one or more of 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, and/or hsa-miR-92a-3p in the subject having or is at risk of developing lung cancer is up-regulated in the biological sample as compared to that of the control.
  • the differential expression level of hsa- miR-1280 and/or hsa-miR-342-3p in the subject having or is at risk of developing lung cancer is down-regulated in the biological sample as compared to that of the control.
  • the method for determining if a subject suffers from, or is at risk of developing lung cancer comprises: a. 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.
  • the biological sample comprises a non-cellular biological fluid.
  • the non-cellular biological fluid may be plasma or serum.
  • the method for determining if a subject suffers from, or is at risk of developing lung cancer further comprises detecting the expression level of at least one additional biomarker.
  • the additional biomarker may include, but is not limited to carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cancer antigen 125 (CA-125), cytokeratin 19 fragment antigen (CYFRA 21-1), and the like.
  • the method for determining if a subject suffers from or is at risk of developing lung cancer further includes one or more test, such as, but is not limited to, an imaging test, sputum cytology, biopsy, or a combination thereof.
  • a subject determined to be suffering from, or is at risk of developing lung cancer may be further tested using sputum cytology, biopsy, fine needle aspiration or diagnostic imaging tests including but not limited to X-ray, computed tomography (CT) scan, low dose CT scans, magnetic resonance imaging (MRI) scan or positron emission tomography (PET) scan.
  • CT computed tomography
  • MRI magnetic resonance imaging
  • PET positron emission tomography
  • the methods as disclosed herein may further comprise a step of administering a treatment to the subject determined to be suffering from lung cancer.
  • a treatment such as, but is not limited to, anti-cancer compound, surgery, immunotherapy, or radiation therapy or combinations of these.
  • treatment options may include surgery, radiation therapy (including but not limited to external radiation therapy, intensity-modulated radiation therapy, proton therapy, stereotactic radiosurgery or brachytherapy), or administering one or more anti-cancer compound that may include but is not limited to chemotherapy (including but not limited to cisplatin, carboplatin, paclitaxel, docetaxel, gemcitabine, vinorelbine, etoposide or pemetrexed whether alone or in combination), targeted therapy (such as drugs or monoclonal antibodies directed against specific aspects such as angiogenesis, EGFR, KRAS, ALK, NTRK, BRAF, ROS1, etc and may include but is not limited to osimertinib, erlotinib, gefitinib, afatinib, dacotinib, crizotinib, ceritinib, dabrafenib, trametinib, bevacizumab, bevacizumab, bevacizumab,
  • the method for treating a subject suffering from lung cancer comprises: a.
  • the method for treating a subject suffering from lung cancer further comprises measuring the level of at least one additional biomarker in the subject.
  • 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 (CYFRA 21-1).
  • CEA carcinoembryonic antigen
  • NSE neuron-specific enolase
  • CA-125 cancer antigen 125
  • CYFRA 21-1 cytokeratin 19 fragment antigen
  • the additional biomarker is carcinoembryonic antigen (CEA).
  • the method further includes an imaging test, sputum cytology or biopsy.
  • compositions/agents/reagents for use in the methods disclosed herein.
  • such compositions/agents/reagents may include, but are not limited to, probes, antibodies, affibodies, nucleic acids, and/or aptamers.
  • the compositions can detect (or detects) the level of expression (e.g., miRNA) of a panel of biomarkers from a biological sample.
  • kits can include all components necessary or sufficient for assays, which can include, but is not limited to, 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, instruction manuals, calibrators, and reference materials, etc.
  • the kit comprises a set of probes for the panel of biomarkers and a solid support to immobilize the set of probes.
  • the kit comprises a set of probes for the panel of biomarkers, a solid support, and reagents for processing the sample to be tested (e.g., reagents to isolate the protein or nucleic acids from the sample).
  • the invention may comprise the use of a detection reagent suitable for detecting the panel of biomarker in the manufacturing or preparation of a kit for use (or when used) in determining whether a subject is suffering from, or is at risk of suffering from, lung cancer.
  • detection reagents suitable for use in the kit include, but are not limited to, oligonucleotides, RNA, DNA (e.g., primers), proteins, peptides, antibodies, aptamers, affibodies, and organic molecules.
  • a probe designed for the detection of a nucleic acid biomarker such a probe may be directed to the target region, the complementary nucleic acid sequence on the reverse strand, or copies of the same generated via an amplification process.
  • DNA-, RNA-, and protein-based detection methods that either directly or indirectly detect the biomarkers described herein.
  • the present invention also provides compositions, reagents, and kits for such diagnostic purposes.
  • the diagnostic methods described herein may be qualitative or quantitative . Quantitative diagnostic methods may be used, for example, to compare a detected biomarker level to a cut-off or threshold level. Where applicable, qualitative or quantitative diagnostic methods can also include amplification of target, signal, or intermediary.
  • biomarkers are detected at the nucleic acid (e.g., DNA or RNA) level.
  • the amount of biomarker RNA (e.g., miRNA) present in a sample is determined (e.g., to determine the level of biomarker expression).
  • Biomarker nucleic acid e.g., miRNA, amplified cDNA, etc.
  • Biomarker nucleic acid can be detected/quantified using a variety of nucleic acid techniques known to those of ordinary skill in the art, including but not limited to, sequencing, nucleic acid hybridisation (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), a locked nucleic acid (LNA) real-time PCR, a CRISPR-based assay, or isothermal amplification assay.
  • qRT-PCR quantitative reverse transcription polymerase chain reaction
  • RT-PCR reverse transcription polymerase chain reaction
  • qPCR quantitative polymerase chain reaction
  • LNA locked nucleic acid
  • An isothermal amplification assay can, for example, include, but is not limited to, a nicking endonuclease amplification reaction (NEAR) assay, a transcription mediated amplification (TMA) assay, a loop-mediated isothermal amplification (LAMP) assay, a helicase-dependent amplification (HDA) assay, a clustered regularly interspaced short palindromic repeat (CRISPR) assay, or a strand displacement amplification (SDA) assay.
  • NEAR nicking endonuclease amplification reaction
  • TMA transcription mediated amplification
  • LAMP loop-mediated isothermal amplification
  • HDA helicase-dependent amplification
  • CRISPR clustered regularly interspaced short palindromic repeat
  • SDA strand displacement amplification
  • the method used to detect miRNA biomarkers may comprise the use of the assay methodologies disclosed in WO2011159256A1 and a kit for the detection of miRNAs may comprise the stemloop oligonucleotides designed based on the teachings of WO2011159256A1, the disclosure of which is incorporated herein by reference.
  • kits for determining whether a subject suffers from, or is at risk of developing lung cancer comprising an isolated set of probes capable of detecting one or more miRNAs 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.
  • miRNAs biomarkers selected from hsa-miR-1280, hsa-miR-487b-3p, hsa-miR- 199b-5p
  • the kit comprises an isolated set of 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.
  • the kit further comprises reagents for detecting at least one additional biomarker in a biological sample obtained from the subject.
  • the additional biomarker is carcinoembryonic antigen (CEA).
  • range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosed ranges. Accordingly, the description of a range should be considered to have specifically disclosed all the possible sub-ranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed sub-ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.
  • biomarkers e.g., miRNAs
  • a biomarker panel can be combined to calculate the disease risk score, for example using a linear model.
  • An example would be to calculate such a risk score using logistic regression, a form of linear model.
  • the prediction score may 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 neighbours algorithm, artificial neural network algorithm, random forests algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method combining multiple learning algorithms.
  • SVM support vector machine
  • the challenge in the field pertains to identifying relevant biomarkers, such as circulatory miRNAs, that could be applied to identify an individual at risk of a disease such as lung cancer.
  • relevant miRNAs could be identified via exhaustive and well -designed studies, it would be within the skill of someone aware of the state of the art to apply the measured level of the relevant miRNAs in such statistical models to generate a score for the prediction of the risk of a subject having lung cancer.
  • Examples of such mathematical methods used to perform the calculations disclosed herein, for example, the calculation of a prediction score can be, but are not limited to, support vector machine algorithm, logistic regression algorithm, multinomial logistic regression algorithm, Fisher’s linear discriminant algorithm, quadratic classifier algorithm, perceptron algorithm, k-nearest neighbours algorithm, artificial neural network algorithm, random forests algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method combining multiple learning algorithms.
  • the calculation of the prediction score is calculated using linear models and support vector machine algorithms.
  • the control and subjects with lung cancer have different disease risk score values calculated. Fitted probability distributions of the disease risk scores for the control and subjects with lung cancer show a separation between the two groups can be found. Based on this prior probability and the fitted probability distributions previously determined, the probability (risk) of an unknown subject having lung cancer can be calculated based on their disease risk score values. With higher score, the subject has higher risk of having lung cancer. Furthermore, the disease risk score can, for example, tell the fold change of the probability (risk) of an unknown subject having lung cancer compared to, for example, the lung cancer rate in high-risk population.
  • Formula 1 below exemplifies the use of a linear model for lung cancer risk prediction, where the disease risk score (unique for each subject) indicates the likelihood of a subject having lung cancer. This is calculated by the summing the weighted measurements for, for example, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, or 19 miRNAs.
  • Kj - the coefficients used to weight multiple miRNA targets and C - constant, can be derived through the application of a linear model. Subjects with disease risk score lower than 0 will be considered as 0 and subjects with disease risk score higher than 100 will be considered as 100. It would be within the understanding of someone skilled in the art, knowing the identity of the relevant miRNA biomarkers, to derive the relevant disease risk scores and cut-offs to identify a subject at risk of having lung cancer.
  • a further example of such an algorithm for risk score calculation includes the use of logistic regression models:
  • a further example of such an algorithm further incorporates the use of a reference sample with known levels of assayed miRNAs to normalize the score for each assay run to account for run-to-run variations (which may be referred to as the Quantitative Reference (QR)), and in some embodiments, the mean value for the QR scores may be used to calculate the expected QR scores.
  • QR Quantitative Reference
  • the test may be used to stratify the patient into low-risk or high-risk categories based on the results derived from Ct of the target miRNAs.
  • a low-risk result indicated that the patient is at low risk of suffering from or developing lung cancer.
  • a high-risk result indicated the presence of miRNAs associated with high risk of lung cancer, and these patients are at risk of suffering from lung cancer and hence should be considered for further diagnostic workup in accordance with clinical guidelines.
  • a Reverse Transcription-quantitative Polymerase Chain Reaction approach 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 samples
  • Step 2 cDNA synthesis
  • Step 3 Pre -amplification
  • Step 4 Detection of miRNAs by quantitative PCR (qPCR)
  • Step 5 Conversion of miRNA Ct (threshold cycle) values (also may be known as Cq or quantification cycle) into risk score
  • RNA extraction of RNA is performed using a semi -automated system. Pre-processing 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 pre-processed sample was added into the extraction cartridges, which were later loaded onto a Maxwell® CSC 48, Maxwell® CSC 16, Maxwell® RSC 48, or Maxwell® RSC 16 instrument. The automated part of the extraction took place in the instrument using paramagnetic particles, which provided a mobile solid phase to optimize sample capture, washing and purification of nucleic acid.
  • PPP platelet-poor plasma
  • the miRNA targets from each sample were converted into cDNAs using the miRNA specific stem-loop-based reverse transcription primers in a single reaction.
  • the stem -loop structure improved primer hybridisation to target miRNAs as compared to linear primers, which resulted in higher analytical sensitivity. It also minimized primer hybridisation to the precursor form of the miRNAs, and, thus, improved assay analytical specificity.
  • the cDNAs were amplified using pairs of sequence specific PCR primers in a single reaction.
  • the pre -amplification increased the number of copies of miRNA targets prior to qPCR step while maintaining target amplification specificity.
  • each miRNA target was amplified by a sequence-specific forward PCR primer and a hemi-nested sequence specific reverse PCR primer. Such combination enabled enhanced discrimination of a wide range of highly homologous family members.
  • the amplicons were then detected using SYBR Green I dye in single-plex reactions under accelerated cycling conditions.
  • the primary purpose of this study was to identify and develop circulating biomarker signatures identified in plasma and/or serum samples for the purpose of identifying subjects that are at risk of or are suffering from lung cancer.
  • Blood samples from 623 subjects were collected, of which 525 were finally used for the development and validation.
  • Reasons for the exclusion of samples include lack of clinical information, failure to meet inclusion criteria or significant haemolysis in samples.
  • Table 2 The details of the cohort of subjects recruited is detailed in Table 2.
  • the level of carcinoembryonic antigen (CEA) was further combined with the miRNA classifiers obtained in the previous step.
  • Table 10 details the performance of CEA when combined with the miRNA biomarkers, either singularly or in combinations with other miRNA biomarkers, with an exemplary embodiment of such miRNA biomarker provided in Table 11 (and depicted graphically in Fig 3).
  • the combination of miRNAs with CEA improves the performance of the test and therefore there may be value to test the level of CEA in addition to measuring the levels of miRNA biomarkers in a subject.
  • the combinations of miRNAs of the current 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 gives the desired or sufficiently high AUC.
  • Table 3 Mean and highest AUC values for the use of miRNA biomarkers alone or in combinations of up to 12 miRNAs for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 4 Exemplary panel of miRNA biomarkers (with hsa-miR-1280) for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 5 Exemplary panel of miRNA biomarkers (with hsa-miR-199b-5p) for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 6 Exemplary panel of miRNA biomarkers (hsa-miR-181c-5p) with for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 7 Exemplary panel of miRNA biomarkers (with hsa-miR-210-3p) for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 8 Exemplary panel of miRNA biomarkers (with hsa-miR-16-5p) for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 9 Exemplary panel of selected 3-miRNA combinations for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 10 Mean and highest AUC values for the use of miRNA biomarkers in combination with CEA (in panels of up to 12 miRNAs) for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer.
  • Table 11 Exemplary panel of CEA with miRNA biomarkers for the purpose of identifying a subject suffering from or is at risk suffering from lung cancer. Discussion
  • circulating biomarkers suitable for identifying a subject suffering from or is at risk of suffering from lung cancer is disclosed. Circulating biomarkers were identified that were suitable, whether used individually or in combination as a biomarker expression signature, to distinguish subjects suffering from or are at risk of suffering from lung cancer from non -lung cancer controls. The use of circulating biomarkers raises the possibility that the panel might provide a tool for early detection of the condition as such tests would be more easily made available for general testing use and is minimally invasive.
  • the biomarkers identified herein were also shown to be useful in combination with other cancer biomarkers such as carcinoembryonic antigen (CEA).
  • CEA carcinoembryonic antigen
  • the present study involves the development and validation of biomarkers is performed on the 3 different sites to account for variability across different sites and using 3 different lots of kits to account for manufacturing variations.
  • potential biases are further reduced to ensure the robustness and reliability of the biomarker panel in determining whether a subject is suffering from or are at risk of suffering from lung cancer.
  • the biomarkers were intended for use as an aid in the diagnosis of lung cancer in a subject, at times in conjunction with other clinical factors or symptoms. Therefore, the biomarkers are intended to distinguish a subject suffering from or is at risk of suffering from lung cancer from subject not suffering from lung cancer.
  • a possible embodiment of a test employing such biomarkers may be reagents for research use, a laboratory developed test, or an in vitro detection kit for the early detection or aiding in the diagnosis of lung cancer using the biomarker panels disclosed herein.
  • a patient classified to be at risk of or suffering from lung cancer may be treated with one or more therapeutic agents or therapies suitable for use in treating the disease.
  • Such a test may be used alone, or in combination with other methods including sputum cytology, biopsy or imaging tests (which includes CT scans, MRI, X-Ray or PET scans), tests for cancer biomarkers (such as CEA) or any other methods for diagnosing lung cancer as recognized by a medical practitioner or someone of similar skill in the art.

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Abstract

L'invention concerne des biomarqueurs associés au cancer du poumon et des procédés permettant de déterminer si un sujet souffre d'un cancer du poumon ou présente un risque de développer un cancer du poumon, le procédé comprenant la détection du niveau d'expression d'au moins un ou plusieurs miARN dans un échantillon biologique issu d'un sujet.
PCT/SG2023/050840 2022-12-15 2023-12-15 Biomarqueurs circulants pour la détection du cancer du poumon et procédés associés WO2024128987A2 (fr)

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WO2011159256A1 (fr) 2010-06-14 2011-12-22 National University Of Singapore Transcription inverse à médiation par un oligonucléotide à tige-boucle modifié et pcr quantitative restreinte à espacement de bases

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011159256A1 (fr) 2010-06-14 2011-12-22 National University Of Singapore Transcription inverse à médiation par un oligonucléotide à tige-boucle modifié et pcr quantitative restreinte à espacement de bases

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
FERLAY J, ERVIK M, LAM F, COLOMBET M, MERY L, PINEROS M, ZNAOR A.SOERJOMATARAM I, BRAY F: " Global Cancer Observatory: Cancer Today. Lyon, France:", INTERNATIONAL AGENCY FOR RESEARCH ON CANCER, 2020, Retrieved from the Internet <URL:https://gco.iarc.fr/today>
NCCN CLINICAL PRACTICE GUIDELINES IN ONCOLOGY FOR LUNG CANCER SCREENING VERSION 1.2023 © NATIONAL COMPREHENSIVE CANCER NETWORK, 12 December 2022 (2022-12-12)
NCCN CLINICAL PRACTICE GUIDELINES IN ONCOLOGY FOR NON-SMALL CELL LUNG CANCER VERSION 6.2022 © NATIONAL COMPREHENSIVE CANCER NETWORK, 12 December 2022 (2022-12-12)
NCCN CLINICAL PRACTICE GUIDELINES IN ONCOLOGY FOR SMALL CELL LUNG CANCER VERSION 2.2023 (Ç) NATIONAL COMPREHENSIVE CANCER NETWORK, 12 December 2022 (2022-12-12)

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