Method, composition, and system for detecting head and neck cancer in saliva samples

Abstract

Methods, compositions, and systems for detecting head and neck cancer using saliva samples are disclosed. For example, the method may measure the presence and / or amount of HNSCC-related biomarkers in an individual by obtaining a saliva sample from the individual and measuring the amount of expression product from at least one gene encoding a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in the saliva sample, the gene comprising at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10.

Description

[Technical Field]

[0001]

[0001] A method, composition, and system for detecting head and neck cancer using a saliva sample are disclosed. [Background technology]

[0002]

[0002] Head and neck cancers are common diseases. Based on information from the Surveillance, Epidemiology, and End Results (SEER) database maintained by the National Cancer Institute (NCI), the American Cancer Society has determined that early detection of oral and oropharyngeal cancers improves patient survival rates (https: / / www.cancer.org / cancer / oral-cavity-and-oropharyngeal-cancer / detection-diagnosis-staging / survival-rates.html). The American Dental Association has also approved saliva as a biofluid for diagnostic purposes, including the assessment of head and neck cancer risk (https: / / www.ada.org / resources / research / science-and-research-institute / oral-health-topics / salivary-diagnostics).

[0003]

[0003] The majority of head and neck cancers histologically belong to the squamous cell type and are therefore classified as head and neck squamous cell carcinoma (HNSCC). HNSCC is the sixth most common cancer in the world and the third most common cancer in developing countries. The biological mechanisms behind HNSCC are unknown, and there are few biomarkers, if any, that provide reliable indicators of this condition. Nevertheless, it would be useful for individuals susceptible to HNSCC to adjust their lifestyle to avoid triggering the onset of symptoms and / or accelerating the further progression of the disease. Therefore, there is a need to develop and evaluate improved biomarkers for HNSCC. [Overview of the Initiative] [Means for solving the problem]

[0004]

[0004] The terms “invention,” “the invention,” “this invention,” and “the present invention,” as used herein, as well as “disclosure,” “this disclosure,” and “the present disclosure,” are intended to broadly refer to the subject matter of this patent application and all of the following claims. Any statements containing these terms should be understood not to limit the subject matter described herein, nor to limit the meaning or scope of the following claims. The applicable embodiments of the invention are defined by the claims and specification, not by this summary. This summary is a high-level overview of various aspects of the invention and introduces some of the concepts described and illustrated herein and in the accompanying drawings. This summary is not intended to identify any important or essential features of the claimed subject matter, nor is it intended to be used alone to determine the scope of the claimed subject matter. The subject matter should be understood by referring to the entire specification, any or all of the drawings and the appropriate parts of each claim. Some exemplary embodiments of the invention are described below.

[0005]

[0005] Methods, compositions, and systems for detecting target head and neck cancer using saliva samples are disclosed. The disclosed methods, compositions, and systems can be embodied in various forms.

[0006]

[0006] For example, in certain embodiments, the method may include measuring the presence and / or amount of a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in an individual, and comprising the steps of (a) obtaining a saliva sample from the individual, and (b) measuring the amount of expression product from at least one gene encoding a biomarker associated with HNSCC in the saliva sample, wherein the gene includes at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured. In yet another embodiment, a composition for detecting a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in an individual is disclosed, comprising a reagent for detecting at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 in saliva. In addition, the composition may include a reagent for detecting at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. Systems for carrying out the method of the present invention and / or for using the composition of the present invention are also disclosed.

[0007]

[0007] The present invention can be better understood by referring to the following non-limiting figures. [Brief explanation of the drawing]

[0008] [Figure 1] An overview of one embodiment of the method of the present disclosure is provided, including a range of accepted sample volumes for use in conjunction with the method according to one embodiment of the present disclosure. [Figure 2] One embodiment of this disclosure shows sex, age, cancer stage, tumor location, and the number of saliva samples ("total"). [Figure 3] This paper presents a random forest analysis to identify and rank differentially expressed genes using an RNASeq dataset showing the top 10 candidate genes, in order to distinguish HNCs from non-cancer samples. [Figure 4]We present a random forest analysis to identify and rank additional differentially expressed genes to distinguish HNCs from non-cancer samples. [Figure 5] One embodiment of this disclosure shows a random forest analysis for identifying and ranking genes differentially expressed in saliva to distinguish HNCs from non-cancer samples. [Figure 6] This figure shows the gene expression levels in copies / μL (y-axis) for each saliva sample for 26 genes (upper panel) and RPL30 (housekeeping gene) (lower panel) according to one embodiment of the present disclosure. The x-axis identifies the genes measured in the saliva sample (upper panel) and their corresponding housekeeping controls. The dotted line crossing the bottom of both graphs, labeled "No Call," represents ddPCR results from saliva samples that yielded too few positive droplets to obtain copies / μL. [Figure 7] This embodiment of the present disclosure shows the median normalized expression of 26 genes in normal (i.e., non-cancerous) saliva compared to those reported in the TCGA HNC RNASeq dataset for normal (i.e., non-cancerous) tissue samples. [Figure 8] The graph on the right shows the median change in expression ratio for each of the 26 genes according to one embodiment of this disclosure, calculated separately for early oral cancer (early OC, stage I / II) and late oral cancer (late OC, stage III / IV) using saliva samples (left graph) and TCGA HNC RNASeq datasets (tissue) (right graph). [Figure 9] This embodiment of the present disclosure shows the effect of normalized ddPCR and low levels of normalized gene (RPL30) on a specific sample. [Figure 10]Shows the establishment of a cutoff for normalization (e.g., housekeeping gene) according to an embodiment of the present disclosure. The left panel shows the increase in the range between the upper 95% confidence interval (CI) value and the lower 95% confidence interval (CI) value at low values of the housekeeping gene (RPL30), and the right panel shows the percent coefficient of variation (%CV) of the housekeeping gene (RPL30) from samples taken from healthy volunteers or individuals with early oral cancer (OC) or advanced OC. [Figure 11] Shows the statistical differences between the normalized ddPCR expression levels from the saliva of healthy volunteers (HV) compared to the saliva from patients with early oral (early OC) cancer, evaluated using an unpaired t-test and Wilcox Rank Sum Test according to an embodiment of the present disclosure. [Figure 12] Shows the performance of gene expression levels for classifying saliva samples from healthy volunteers or patients with early oral cancer, evaluated by receiver operating characteristic (ROC) analysis according to an embodiment of the present disclosure. [Figure 13] Shows gene expression levels combined by logistic regression and performance, evaluated by ROC analysis according to an embodiment of the present disclosure. [Figure 14] Shows a system according to an embodiment of the present disclosure. [Figure 15] Illustrates a computing system according to an embodiment of the present disclosure.

Mode for Carrying Out the Invention

[0009]

[0023] Terms and Definitions To more easily understand the present disclosure, certain terms are first defined. Additional definitions of the following terms and other terms are described throughout this specification.

[0010]

[0024] Numerical ranges and parameters setting forth the broad scope of the present disclosure are approximations, and although the numerical values set forth in the specific examples are reported as accurately as possible, any numerical value inherently contains certain errors necessarily resulting from the standard deviation found in their respective test measurements. Further, all ranges disclosed herein are to be understood to encompass any and all subranges subsumed therein. For example, a range described as “1 to 10” includes any and all subranges between and including the minimum value of 1 and the maximum value of 10, that is, all subranges beginning with a minimum value of 1 or more, such as 1 to 6.1, and ending with a maximum value of 10 or less, such as 5.5 to 10. In addition, any reference cited as “incorporated herein” is to be understood as incorporated in its entirety.

[0011]

[0025] It should be further noted that, as used herein, the singular forms “a,” “an,” and “the” include plural referents unless expressly and specifically limited to one referent. The term “and / or” is generally used to indicate at least one of either or both. In some cases, the term “and / or” is used interchangeably with the term “or.” The term “comprising” is used herein to mean the phrase “comprising, but not limited to,” and is used interchangeably with it. The term “for example” is used herein to mean the phrase “for example, without limitation,” and is used interchangeably with it.

[0012]

[0026] As used herein, the term “biomarker” or “marker” refers to one or more nucleic acids (e.g., mRNA, DNA or other nucleic acids), polypeptides and / or other biomolecules (e.g., cholesterol, lipids) that can be used alone or in combination with other biomarkers to diagnose a disease or syndrome of interest, or to assist in its diagnosis or prognosis, monitor the progression of a disease or syndrome of interest, and / or monitor the effectiveness of treatment of a syndrome or disease of interest.

[0013]

[0027] As used herein, “digital PCR” or “dPCR” refers to a technique in which individual PCR reactants are compartmentalized into hundreds to millions of individual wells, or into small volumes of water-oil emulsion droplets, as in “droplet digital PCR” or “ddPCR.” After PCR amplification, each compartment is counted as either positive or negative. The ratio of positive compartments (k) to the total number of compartments (n) is used to calculate the initial concentration (C) by a Poisson distribution, where C = -ln(1-k / n).

[0014]

[0028] As used herein, the term “duplex digital drop PCR” or “duplex ddPCR” refers to the ability of a detection system to simultaneously detect two different colored dyes in a single ddPCR reaction. Also as used herein, the term “multiplex digital drop PCR” or “multiplex ddPCR” refers to the ability of a detection system to simultaneously use multiple different colored dyes in a single ddPCR reaction to detect multiple different PCR reactions.

[0015]

[0029] Where used herein, “head and neck squamous cell carcinoma” or “HNSCC” and “head and neck cancer” or “HNC” are used interchangeably to refer to head and neck cancer. Head and neck cancer is the name given to cancers that develop in the mouth, nose and sinuses, salivary glands, throat, and larynx. Most head and neck cancers are squamous cell carcinomas. They begin in the moist tissues that cover the head and neck. Cancer cells may spread to deeper tissues as the cancer grows. Other cancers that develop in the head and neck include brain cancer, eye cancer, and esophageal cancer. These other cancers are not usually considered head and neck cancers because of the different types of cancers and the different treatments they receive.

[0016]

[0030] As used herein, “Receiver Operating Characteristic” or “ROC” analysis. A Receiver Operating Characteristic (ROC) curve is defined as a plot of test sensitivity as the y-coordinate versus specificity or false positive rate (FPR) as the x-coordinate.

[0017]

[0031] overview Methods, compositions, and systems for saliva-based screening tests for oral and oropharyngeal cancers are disclosed. Saliva-based screening tests for oral and oropharyngeal cancers can be highly advantageous for early detection of HNSCC. Saliva is a convenient biological sample for diagnostic purposes and a biological source close to tissues that may exhibit HNSCC. In certain embodiments, saliva may be collected using a simple collection device during an annual physical examination by a primary care physician, a six-monthly preventive dental examination by a dentist, or for saliva collection at home. Relatively easy and non-invasive sampling makes saliva an ideal biological fluid. In HNSCC detection, saliva-based detection can improve detection sensitivity due to direct contact with oral and oropharyngeal tissues.

[0018]

[0032] Accordingly, methods, compositions, and systems (e.g., kits and / or computer software) for diagnosing the presence of HNSCC or an increased risk of developing HNSCC are provided in this disclosure. The methods, compositions, and systems of this disclosure may be used to obtain or provide genetic information from a subject to objectively diagnose the presence or increased risk of a subject or other subject developing HNSCC. The methods, compositions, and systems of this disclosure may be used to determine the presence or increased risk of a subject developing HNSCC. The methods, compositions, and systems may be embodied in a variety of forms.

[0019]

[0033] Diagnostic methods for HNSCC Embodiments of the present invention include a method for diagnosing the presence of HNSCC or an increased risk of developing HNSCC. The method can be embodied in various ways.

[0020]

[0034] For example, a method is disclosed for measuring the presence and / or amount of a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising the steps of (a) obtaining a saliva sample from the individual, and (b) measuring the amount of expression product from at least one gene encoding a biomarker associated with HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP3, or MMP10. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured.

[0021]

[0035] In another embodiment, a method is disclosed for identifying individuals at risk of head and neck squamous cell carcinoma (HNSCC), comprising (a) obtaining a saliva sample from the individual, and (b) measuring the amount of expression product in the saliva sample from at least one gene encoding a biomarker associated with HNSCC, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP3, or MMP10, and the presence of altered levels of expression product from the HNSCC-associated biomarker compared to a control identifies the individual as being at risk of HNSCC. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured and compared to a control.

[0022]

[0036] Further embodiments disclose a method for identifying and treating an individual having head and neck squamous cell carcinoma (HNSCC), comprising: (a) obtaining a saliva sample from the individual; (b) measuring the altered amount of expression product from at least one gene encoding an HNSCC-related biomarker in the saliva sample compared to a control, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP3, or MMP10; and (c) administering one or more HNSCC treatments to the individual. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured and compared to a control for altered expression.

[0023]

[0037] For example, depending on the location and extent of the primary tumor, as well as the lymph node status, some common considerations for the treatment of lip and oral cancer include surgery alone, radiotherapy alone, or a combination of both. See, for example, Harrison LB, Sessions RB, Hong WK, eds.: Head and Neck Cancer: A Multidisciplinary Approach. 3rd ed. Lippincott, William & Wilkins, 2009. Also, see the information available from the National Cancer Institute, found at https: / / www.cancer.gov / types / head-and-neck / hp. In certain embodiments, the optimal approach for treating oropharyngeal cancer cannot be easily defined, as a single regimen does not provide a clear, superior survival advantage. Treatment considerations should take into account functional and motor status, including speech and swallowing outcomes. Treatments include surgery, radiotherapy, chemotherapy, and immunotherapy.

[0024]

[0038] Further embodiments of the present disclosure include a method for identifying and monitoring individuals at risk of head and neck squamous cell carcinoma (HNSCC), comprising: (a) obtaining a saliva sample from the individual; (b) measuring an altered amount of expression product from at least one gene encoding a biomarker associated with HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10; (c) determining that at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 shows altered expression compared to a healthy control; and (d) repeating steps (a) to (c) at a subsequent point in time to determine whether at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 shows increased altered expression compared to a healthy control. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured in step (b) and evaluated in steps (c) to (d).

[0025]

[0039] In some cases, increasing the number of biomarkers improves the statistical power of the method. In certain embodiments, the method may include measuring the expression products of at least two, three, four, five, or all of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In addition, the expression products of other genes, including at least one, at least two, at least three, at least four, at least five, or all of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured in combination with each other or in combination with at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In certain embodiments, the method may include measuring the expression of CDSN and AIM2, and / or CDSN, AIM2, and MMP1, and / or CDSN, AIM2, MMP1, and INHBA, and / or CDSN, AIM2, MMP1, INHBA, and / or MMP9. Alternatively, other gene combinations may be measured.

[0026]

[0040] Alternatively, other combinations of the disclosed markers may be used. In one embodiment, to determine a preferred combination of biomarkers, one method is to perform ROC analysis using each marker individually, as pairs, as groups of three, four, five, and all six (or more) together. For example, using this method with six genes, a total of 63 combinations are possible. Thus, there are 6+15+20+15+6+1=63 combinations in total, with the six genes (n=6) individually being (k=1)=6! / [1!x(6-1)!]=6 combinations, the six genes (n=6) as pairs being (k=2)=6! / [2!x(6-2)!]=15 combinations, and the six genes (n=6) as three groups being (k=3)=6! / [3!x The number of possible combinations is (6-3)! = 20. For 6 genes (n=6), the number of combinations in 4 groups is (k=4) = 6! / [4!x(6-4)!] = 15. For 6 genes (n=6), the number of combinations in 5 groups is (k=5) = 6! / [5!x(6-5)!] = 6. For all 6 genes (n=6) with k=6, the number of combinations is = 6! / [6!x(6-6)!] = 1. Under similar analysis, there are 127 possible combinations for 7 genes, 255 possible combinations for 8 genes, 511 possible combinations for 9 genes, and 1,023 possible combinations for 10 genes.

[0027]

[0041] For example, Figure 13 shows some combinations of AUC for some of the disclosed markers. A complete test with 100% sensitivity and 100% specificity has an AUC of 1. It can be seen that combinations with AUCs of 0.8611, 0.9664, 0.9412, and 0.9496 account for less than 15% of all four combinations, and three of the combinations account for less than 10% of the complete tests.

[0028]

[0042] In addition, in certain embodiments, other biomarkers may be measured. Thus, in certain embodiments, the method may further include measuring the expression product from any of the genes shown in Table 1, Table 2, Table 5, or Table 6. The biomarkers in Table 2 (as used herein) are from Table 6 of U.S. Patent Application No. 16 / 224,974, owned by common owner, filed on 19 December 2018 and published as U.S. Patent No. 2019 / 0187143 (which is incorporated herein by reference in its entirety).

[0029]

[0043] As disclosed in detail herein, in certain embodiments, the gene expression of a biomarker is normalized. For example, in certain embodiments, the method further includes measuring the expression product of a housekeeping gene and normalizing the results. The normalized gene or housekeeping gene may be RPL30. Or, the normalized gene or housekeeping gene may be KHDRBS1. Or, another housekeeping expression product or normalized expression product may be used.

[0030]

[0044] In various embodiments, the expression product is a protein or nucleic acid. In certain embodiments, the expression product is mRNA. In certain embodiments, the measurement includes measuring the amount of mRNA. Alternatively, the measurement may include an immunoassay.

[0031]

[0045] Various methods can be used to measure one or more expression products. In one embodiment, the method provides quantitative results. In a particular embodiment, the method used to measure expression includes real-time reverse transcriptase PCR (e.g., real-time RT-PCR), droplet digital PCR (ddPCR), duplex droplet digital PCR (duplex-ddPCR), or multiplex droplet digital PCR (multiplex-ddPCR).

[0032]

[0046] Duplex droplet digital PCR refers to the ability of a detection system to simultaneously detect two different colored dyes in a single ddPCR reaction. Therefore, in certain embodiments, the method may involve using a ddPCR probe labeled with a first dye (e.g., HEX) for a housekeeping gene or control gene (e.g., RPL30), and a second ddPCR probe labeled with a second dye (e.g., FAM) for the gene of interest (e.g., Figure 6). These two reactions may be carried out simultaneously in the same reaction tube and may be detected simultaneously using a commercially available droplet reader, such as, for example, the BioRad QX200 ddPCR droplet reader, but not limited to these. Additionally and / or alternatively, commercially available droplet readers capable of simultaneously detecting more than two dyes may be used. For example, the BioRad QX600 droplet digital reader allows for six-color multiplexing.

[0033]

[0047] Additionally and / or alternatively, the method may include the use of an array of expression products. Alternatively, other methods may be used, but are not limited to, Northern blotting, dot blotting, ribonuclease protection assay (RPA), sequential gene expression analysis (SAGE), differential or subtractive hybridization, reverse transcriptase PCR (RT-PCR), microarrays, next-generation sequencing (NGS), and / or RNA-Seq.

[0034]

[0048] Figure 1 outlines one embodiment of method 100 of the present disclosure. Thus, as shown in Figure 1, the method may include obtaining a saliva sample from a subject (102). Saliva may be collected using a simple collection device, such as a DNA Genotek CP-190, during an annual physical examination by a primary care physician, a six-monthly preventive dental examination by a dentist, or for home collection. Alternatively, other collection devices may be used. Relatively easy and non-invasive sampling makes saliva an ideal biological fluid.

[0035]

[0049] The method may further include the step of preparing a sample for analysis of the expression product. In certain embodiments, the measurement includes measuring mRNA. If the expression product is mRNA, the method may include adding an appropriate amount of RNA stabilizer (104). For example, in certain embodiments, equivolume (e.g., 2 mL) of stabilizer is added to a 2 mL aliquot of sample. The sample containing the added stabilizer may be stored at room temperature (RT) for up to 8 weeks or for longer periods at <20°C. The sampling device may be shipped at ambient temperature, handled according to the manufacturer's instructions, and stored at <70°C. The inset in Figure 1 shows the range of sample volumes that may be accepted in one embodiment of the method.

[0036]

[0050] Next, mRNA can be isolated (106). For example, aliquots of saliva / stabilizing fluid may be taken from a saliva collection device, and total RNA may be isolated using, for example, the MagMax mirVanna® Total RNA Isolation Kit of the KingFisher® Flex Purification System. Alternatively, other methods of RNA isolation may be used.

[0037]

[0051] Next, the amount of mRNA can be measured using quantitative techniques (108). For example, in certain embodiments, duplex-ddPCR may be used, as disclosed in detail herein. Thus, in certain embodiments, aliquots of eluate from the RNA isolation procedure may be used for the synthesis of first-strand cDNA using random hexamers. Next, an amplification reaction mixture may be prepared using target gene primers / probes (in some cases, the probe may be labeled with a detectable portion such as FAM) and housekeeping gene (e.g., RPL30) primers / probes (in some cases, the probe may be labeled with a detectable portion different from the gene-specific probe, such as HEX). Droplets may be prepared, for example, using a commercially available droplet generator, and the plate may be sealed with perforated foil. Next, thermal cycling (i.e., PCR amplification) may be performed. Then, the droplets may be detected and analyzed using analytical software capable of reporting units in copies / μL. In various embodiments, a control value of the gene of interest may be measured using one (or more) samples of normal (non-cancerous) tissue, saliva, or other bodily fluids, or may be obtained from a normal (non-cancerous) population. Additionally and / or alternatively, as described above, the method may include the measurement of at least one normalization (e.g., housekeeping) gene. The housekeeping gene may be measured using a patient sample to allow for the normalization of gene expression levels. In one embodiment, the normalization gene may be KHDRBS1. In other embodiments, RPL30 or other normalization genes may be used.

[0038]

[0052] At this point, the results may be reported to the subject or their healthcare provider (110).

[0039]

[0053] composition As described above, yet another embodiment of the present invention includes a composition for detecting HNSCC-related biomarkers in an individual. The composition can be embodied in various forms.

[0040]

[0054] Accordingly, other embodiments of the present disclosure include compositions for detecting or measuring biomarkers associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising a reagent for detecting at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 in saliva. In addition, expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured. Accordingly, in certain embodiments, the composition includes a reagent for detecting at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers may be measured. Accordingly, in certain embodiments, the composition and / or kit may include a reagent for measuring expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0041]

[0055] In some cases, increasing the number of biomarkers improves the statistical power of the method. In certain embodiments, the composition may include reagents for measuring expression products from at least two, three, four, five, or all of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. Additionally and / or alternatively, the composition may include reagents for measuring expression products of other genes, including at least one, at least two, at least three, at least four, at least five, or all of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, in combination with each other or in combination with at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In certain embodiments, the composition may include reagents for measuring the expression of CDSN and AIM2, and / or CDSN, AIM2 and MMP1, and / or CDSN, AIM2, MMP1 and INHBA, and / or CDSN, AIM2, MMP1, INHBA and / or MMP9. Alternatively, reagents for measuring other combinations of genes may be used.

[0042]

[0056] As disclosed in detail herein, in certain embodiments, the gene expression of a biomarker is normalized. For example, in certain embodiments, the composition further comprises a reagent for measuring the expression product of a housekeeping gene in saliva and normalizing the results. The normalized gene or housekeeping gene may be RPL30. Alternatively, the normalized gene or housekeeping gene may be KHDRBS1. Alternatively, another housekeeping expression product or normalized expression product may be used.

[0043]

[0057] In various embodiments, the expression product is a protein or nucleic acid. In certain embodiments, the expression product is mRNA. In certain embodiments, the composition includes reagents for measuring mRNA. Various methods may be used to measure one or more expression products. In certain embodiments, the composition and / or kit may include reagents for performing duplex-ddPCR and / or multiplex-ddPCR. Additionally and / or alternatively, the composition may constitute an array for measuring expression products. Or, other methods disclosed herein may be used. Or, the composition and / or kit may include reagents for measuring proteins using, for example, an immunoassay.

[0044]

[0058] Accordingly, in certain embodiments, the composition may comprise a primer (e.g., a primer pair) and / or probe for any one of these genes, the primer and / or probe being labeled by a detectable moiety as described herein. Additionally and / or alternatively, the primers and / or probes may also constitute an array on which the primers and / or probes are immobilized on a surface. In other embodiments, the reagents may comprise reagents for measuring peptides and / or proteins expressed from the disclosed genes. For example, the composition may comprise reagents for performing an immunoassay. These reagents may comprise an array as described in detail herein in some embodiments. As described in detail herein, the reagents may be labeled by a detectable moiety.

[0045]

[0059] In certain embodiments, the composition includes a reagent for quantifying at least one level of a disclosed biomarker in a biological sample. For example, as described in detail herein, the composition may include a reagent for quantitatively measuring mRNA. Various methods may be used to measure one or more expression products. In certain embodiments, the composition includes a reagent for measuring expression using one of the following: real-time reverse transcriptase PCR (e.g., real-time RT-PCR), droplet digital PCR (ddPCR), duplex-ddPCR, or multiplex-ddPCR.

[0046]

[0060] Therefore, in certain embodiments, the composition includes reagents for analyzing aliquots of elutes from an RNA isolation procedure by synthesis of first-strand cDNA using a random hexamer. The composition may further include reagents for preparing amplification reaction mixtures using target gene primers / probes and housekeeping gene (e.g., RPL30) primers / probes. For example, duplex ddPCR may be used to label the primer and / or probe of the gene of interest with a first detectable region (e.g., FAM), and the primer and / or probe of the housekeeping gene with a second detectable region (e.g., HEX). Alternatively, other detectable regions as described in detail herein may be used. The composition may further include reagents for forming droplets and carrying out PCR amplification. In various embodiments, the composition may include reagents (e.g., control nucleic acid templates) for measuring control values ​​from a single (or more) sample of normal (non-cancerous tissue) or control values ​​obtained from a normal (non-cancerous) population. Additionally and / or alternatively, as described above, the composition may include a reagent for measuring at least one normalization (e.g., housekeeping) gene. In one embodiment, the normalization gene may be KHDRBS1. In other embodiments, RPL30 or other normalization genes may be used.

[0047]

[0061] Alternatively, the composition may include reagents for measuring peptide biomarkers or polypeptide biomarkers. In one embodiment, the composition includes reagents for performing an immunoassay. In one embodiment, the composition includes reagents for performing a quantitative immunoassay (e.g., chemiluminescent immunoassay, ELISA, or similar quantitative method). Alternatively, the composition may include reagents for performing flow cytometry. Alternatively, as described in detail herein, the composition may include reagents for determining the presence and / or expression level of a specific sequence of nucleic acid. As described in detail herein, the reagents may be labeled with detectable moieties. system

[0048]

[0062] In certain embodiments, the present invention includes a system for carrying out any or all of the steps of the method disclosed herein and / or for using the compositions described herein. In certain embodiments, the system may comprise a kit; or the system may comprise computerized instructions and / or reagents for carrying out the method disclosed herein.

[0049]

[0063] Accordingly, in certain embodiments, a system is disclosed for measuring the presence and / or amount of a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in a salivary sample derived from an individual, comprising (a) a station and / or components for obtaining a salivary sample from an individual, and (b) a station and / or components for measuring the presence and / or amount of an expression product from at least one gene encoding a biomarker associated with HNSCC in the salivary sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In addition, the system can be used to measure the expression products of other genes in saliva, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. Accordingly, in certain embodiments, the system comprises a station and / or components for detecting the presence and / or amount of at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers can be measured. Therefore, in certain embodiments, the system may include stations and / or components for measuring expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0050]

[0064] In other embodiments, a system is disclosed for identifying individuals at risk of head and neck squamous cell carcinoma (HNSCC), comprising (a) a station and / or components for obtaining a saliva sample from the individual, and (b) a station and / or components for measuring the presence and / or amount of an expression product from at least one gene encoding an HNSCC-related biomarker in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10, and the system identifies individuals as being at risk of HNSCC based on the presence of altered levels of expression products from an HNSCC-related biomarker compared to a control. Alternatively, other gene expression products may be measured. In certain embodiments, the system comprises a station and / or components for detecting the presence and / or amount of at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers may be measured. Therefore, in certain embodiments, the system may include stations and / or components for measuring expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0051]

[0065] As described in detail herein, in certain embodiments, various combinations of genes can be measured using the disclosed system. In some cases, increasing the number of biomarkers improves the statistical power of the method. In certain embodiments, the system may comprise stations and / or components for measuring expression products from at least two, three, four, five, or all of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. Additionally and / or alternatively, the system may comprise stations and / or components for measuring expression products of other genes, including at least one, at least two, at least three, at least four, at least five, or all of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, in combination with each other or in combination with at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In certain embodiments, the system may include stations and / or components for measuring the expression of CDSN and AIM2, and / or CDSN, AIM2 and MMP1, and / or CDSN, AIM2, MMP1 and INHBA, and / or CDSN, AIM2, MMP1, INHBA and / or MMP9. Alternatively, stations and / or components may be used to measure other combinations of genes.

[0052]

[0066] Figure 14 outlines one embodiment of the system 200 of this disclosure. Thus, as shown in Figure 14, the system may comprise a station and / or components 202 for obtaining a saliva sample from a subject. Saliva may be collected using a simple collection device, such as a DNA Genotek CP-190, during an annual physical examination by a primary care physician, a six-monthly preventive dental checkup by a dentist, or for home collection. Alternatively, other collection devices may be used. Relatively easy and non-invasive sampling makes saliva an ideal biological fluid.

[0053]

[0067] The system may further include stations and / or components for preparing samples for analysis of expression products. In certain embodiments, the measurement includes measuring mRNA. If the expression product is mRNA, the system may include stations and / or components 204 for adding an appropriate amount of RNA stabilizer. For example, in certain embodiments, equivolume (e.g., 2 mL) of stabilizer is added to a 2 mL aliquot of sample. The sample containing the added stabilizer may be stored at room temperature (RT) for up to 8 weeks or for longer periods at <20°C. The sampling device may be shipped at ambient temperature, handled according to the manufacturer's instructions, and stored at <70°C.

[0054]

[0068] The system may further comprise stations and / or components 206 for isolating mRNA. For example, aliquots of saliva / stabilizing fluid may be taken from the saliva collection device, and total RNA may be isolated using, for example, the MagMax mirVanna® Total RNA Isolation Kit of the KingFisher® Flex Purification System. Alternatively, other methods of RNA isolation may be used.

[0055]

[0069] The system may further comprise a station and / or component 208 for measuring the amount of mRNA using quantitative techniques. For example, in certain embodiments, duplex-ddPCR and / or multiplex-ddPCR may be used, as disclosed in detail herein. Thus, in certain embodiments, aliquots of eluate from an RNA isolation procedure may be used for the synthesis of first-strand cDNA using a random hexamer. Next, an amplification reaction mixture may be prepared using a target gene primer / probe (and optionally, if the probe is labeled by a detectable portion such as FAM) and a housekeeping gene (e.g., RPL30) primer / probe (and optionally, if the probe is labeled by a detectable portion different from the gene-specific probe, e.g., HEX). Droplets may be prepared, for example, using a commercially available droplet generator, and the plate may be sealed with perforated foil. Next, a thermal cycle (i.e., PCR amplification) may be performed. The droplets may then be detected and analyzed using analytical software capable of reporting units in copies / μL. In various embodiments, the control value may be measured from a single (or multiple) sample of normal (non-cancerous tissue) or from a normal (non-cancerous) population. Additionally and / or alternatively, as described above, the system may include stations and / or components for measuring at least one normalization (e.g., housekeeping) gene. In one embodiment, the normalization gene may be KHDRBS1. In other embodiments, RPL30 or other normalization genes may be used.

[0056]

[0070] The system may further include stations and / or components 210 for reporting results to the subject or their healthcare provider.

[0057]

[0071] In certain embodiments, the system may include a computer 300. Accordingly, the Specified Provision discloses a computer (e.g., a data processor) and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium, which includes instructions configured to perform any of the stations / components of the system and / or perform one or more steps of any of the methods of any of the embodiments disclosed. In one embodiment, the system includes a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium, which includes instructions configured to measure the presence and / or amount of a biomarker associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising the steps of (a) obtaining a saliva sample from an individual and (b) measuring the presence and / or amount of an expression product from at least one gene encoding a biomarker associated with HNSCC in the saliva sample, wherein the gene includes at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. Alternatively, other gene expression products may be measured as described above. Accordingly, in certain embodiments, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure the presence and / or quantity of at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers may be measured. Accordingly, in certain embodiments, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure the presence and / or quantity of expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0058]

[0072] In other embodiments, the system comprises a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium, which includes instructions configured to identify individuals at risk of head and neck squamous cell carcinoma (HNSCC), comprising (a) obtaining a saliva sample from an individual and (b) measuring the amount of expression product from at least one gene encoding a biomarker associated with HNSCC in the saliva sample, wherein the gene includes at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10, and the presence of altered levels of expression product from an HNSCC-related biomarker compared to a control identifies the individual as being at risk of HNSCC. Alternatively, other gene expression products may be measured. Thus, in certain embodiments, the computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure the presence and / or amount of at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers may be measured. Therefore, in certain embodiments, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure the presence and / or quantity of expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0059]

[0073] In some cases, increasing the number of biomarkers improves the statistical power of the method. In certain embodiments, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure expression products from at least two, three, four, five, or all of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. Additionally and / or alternatively, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure expression products of other genes, including at least one, at least two, at least three, at least four, at least five, or all of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, in combination with each other or in combination with at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In certain embodiments, a computer and / or computer program product tangibly embodied in a non-temporary machine-readable storage medium includes instructions configured to measure the expression of CDSN and AIM2, and / or CDSN, AIM2 and MMP1, and / or CDSN, AIM2, MMP1 and INHBA, and / or CDSN, AIM2, MMP1, INHBA and / or MMP9. In addition, in certain embodiments, other biomarkers may be measured.

[0060]

[0074] Figure 15 shows a block diagram of an analytical system 300 used for detecting and / or quantifying an analyte from a dried sample. As illustrated in Figure 15, modules, engines, or components (e.g., programs, code, or instructions) executable by one or more processors may be used to implement various subsystems of the analytical instrument system according to various embodiments. The modules, engines, or components may be stored on non-temporary computer media. If necessary, one or more of the modules, engines, or components may be loaded into system memory (e.g., RAM) and executed by one or more processors of the analytical instrument system. The example shown in Figure 15 shows modules, engines, or components for implementing the method of the present disclosure or for running any of the systems of the present disclosure.

[0061]

[0075] Accordingly, Figure 15 illustrates an exemplary computing device 300 suitable for use with the systems and methods of the present disclosure. The exemplary computing device 300 includes a memory 310 and a processor 305 that communicates with other components of the computing device 300 using one or more communication buses 315. The processor 305 is configured to execute processor-executable instructions stored in the memory 310 to perform one or more methods or to operate one or more stations for detecting antibodies against SARS-CoV-2, according to various examples such as those in Figures 1 to 14 or disclosed elsewhere in this specification. In this example, the memory 310 may store processor-executable instructions 325 (320) that can analyze the results of a sample, as described herein.

[0062]

[0076] The computing device 300 in this example may also include one or more user input devices 330, such as a keyboard, mouse, touchscreen, or microphone, to accept user input. The computing device 300 may also include a display 335, e.g., a user interface, to provide visual output to the user. The computing device 300 may also include a communication interface 340. In some examples, the communication interface 340 may enable communication using one or more networks, including a local area network ("LAN"); a wide area network ("WAN" such as the Internet); a metropolitan area network ("MAN"); or point-to-point or peer-to-peer connections. Communication with other devices may be achieved using any preferred network protocol. For example, one preferred network protocol may include the Internet Protocol ("IP"), Transmission Control Protocol ("TCP"), User Datagram Protocol ("UDP"), or a combination thereof, e.g., TCP / IP or UDP / IP.

[0063]

[0077] As disclosed in detail herein, in certain embodiments, the gene expression of a biomarker is normalized. For example, in certain embodiments, the system further includes measuring the expression product of a housekeeping gene and normalizing the results. The normalized gene or housekeeping gene may be RPL30. Or, the normalized gene or housekeeping gene may be KHDRBS1. Or, another housekeeping expression product or normalized expression product may be used.

[0064]

[0078] In various embodiments, the expression product is a protein or nucleic acid. In certain embodiments, the expression product is mRNA. In certain embodiments, the measurement includes measuring the amount of mRNA. Alternatively, the measurement may include an immunoassay.

[0065]

[0079] Various methods may be used by the system to measure one or more expression products. In one embodiment, the method provides quantitative results. In a particular embodiment, the method used to measure expression includes real-time reverse transcriptase PCR (e.g., real-time RT-PCR), droplet digital PCR (ddPCR), or duplex-ddPCR. Additionally and / or alternatively, the method may include using an array of expression products.

[0066]

[0080] In certain embodiments, this disclosure provides kits for use according to the methods and compositions disclosed herein. Generally, a kit includes one or more reagents for detecting a biomarker of interest and optionally instructions for use. Preferred reagents may include nucleic acid probes and / or antibodies or fragments thereof. In some embodiments, preferred reagents are provided in the form of arrays, such as microarrays or mutation panels. The kit may further include reagents that serve as positive controls for the biomarker of interest (i.e., genes).

[0067]

[0081] Accordingly, embodiments of this disclosure include kits for detecting HNSCC-related biomarkers in individuals. In certain embodiments, the kit includes reagents for quantifying at least one level of the disclosed biomarkers in a biological sample. For example, as described in detail herein, the kit may include reagents for measuring mRNA; or the kit may include reagents for measuring peptide biomarkers or polypeptide biomarkers. In one embodiment, the kit includes reagents for performing an immunoassay; or the kit may include reagents for performing flow cytometry; or, as described in detail herein, the kit may include reagents for determining the presence and / or expression level of a particular sequence of nucleic acid. As described in detail herein, the reagents may be labeled with detectable moieties.

[0068]

[0082] Accordingly, other embodiments of the present disclosure include a kit for detecting or measuring biomarkers associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising a reagent for detecting at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 in saliva, or other gene expression products may be measured. Accordingly, in certain embodiments, the kit includes a reagent for measuring the presence and / or amount of at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15. In addition, in certain embodiments, other biomarkers may be measured. Accordingly, in certain embodiments, the kit includes a reagent for measuring the presence and / or amount of expression products from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

[0069]

[0083] In some cases, increasing the number of biomarkers improves statistical power. In certain embodiments, the kit may include reagents for measuring expression products from at least two, three, four, five, or all of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. Alternatively, other gene expression products may be measured. Thus, in certain embodiments, the kit includes reagents for measuring the presence and / or amount of at least two, three, four, five, or all of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, in combination with each other or in combination with at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. In addition, in certain embodiments, other biomarkers may be measured. Thus, in certain embodiments, the kit includes reagents for measuring the presence and / or amount of expression products from at least two, three, four, or more of any genes shown in Table 1, Table 2, Table 5, or Table 6. In certain embodiments, the kit may include reagents for measuring the expression of CDSN and AIM2, and / or CDSN, AIM2 and MMP1, and / or CDSN, AIM2, MMP1 and INHBA, and / or CDSN, AIM2, MMP1, INHBA and / or MMP9.

[0070]

[0084] In various embodiments, the expression product is a protein or nucleic acid. In certain embodiments, the expression product is mRNA. In certain embodiments, the kit includes reagents for measuring mRNA. Various methods may be used to measure one or more expression products. In certain embodiments, the kit may include reagents for performing duplex-ddPCR or multiplex-ddPCR. Additionally and / or alternatively, the kit may include an array of expression products. Or, other methods disclosed herein may be used. Or, the kit may include reagents for measuring proteins using, for example, an immunoassay.

[0071]

[0085] Additionally and / or alternatively, the kit may include reagents for detecting at least one normalization (e.g., housekeeping) gene. In one embodiment, the normalization gene may be KHDRBS1. In other embodiments, RPL30 or other normalization genes may be used. In some embodiments, the kit may include a positive control for any of the disclosed biomarkers and / or normalization genes, as well as a control derived from a normal (i.e., non-cancerous) sample.

[0072]

[0086] Accordingly, in certain embodiments, the kit may include a primer (e.g., a primer pair) and / or probe for any one of these genes, the primer and / or probe being labeled by a detectable moiety as described herein. Additionally and / or alternatively, the primers and / or probes may also constitute an array on which the primers and / or probes are immobilized on a surface. In other embodiments, the reagents may include reagents for measuring peptides and / or proteins expressed from the disclosed genes. For example, the kit may include reagents for performing an immunoassay. These reagents may, in some embodiments, constitute an array as described in detail herein. As described in detail herein, the reagents may be labeled by a detectable moiety.

[0073]

[0087] The kit may also include an instruction manual.

[0074]

[0088] In some embodiments, the provided kit further comprises reagents for performing various detection methods described herein (e.g., RT-PCR, sequencing, hybridization, primer extension, multiplex ASPE, immunoassay, etc.). For example, the kit may optionally contain buffers, enzymes, and / or reagents for use in the methods described herein, such as for amplifying nucleic acids via duplex ddPCR or multiplex ddPCR, RT-PCR (i.e., real-time RT-PCR), primer-directed amplification, or for performing ELISA experiments. In certain embodiments, the kit may comprise a primer and / or probe for any one of these genes, the primer and / or probe being labeled with a detectable portion described herein.

[0075]

[0089] In some embodiments, the provided kit further includes a control representing a healthy individual, e.g., a nucleic acid and / or protein sample from an individual that does not have the disease and / or syndrome of interest. Alternatively, the kit may include a positive control containing one (or more) of the measured biomarker genes in known amounts. The kit may also include instructions on how to determine whether an individual has the disease and / or syndrome of interest or is at risk of developing the disease and / or syndrome of interest.

[0076]

[0090] In some embodiments, a computer-readable medium is provided that encodes information corresponding to a biomarker of interest. Such a computer-readable medium may be included in the kit of the present invention. Peptide, polypeptide, and protein assays

[0077]

[0091] In certain embodiments, the biomarker of interest is detected at the protein level (or peptide or polypeptide level), i.e., the gene product is analyzed. For example, the protein or a fragment thereof may be analyzed by amino acid sequencing or by an immunoassay using one or more antibodies that specifically recognize one or more epitopes present on or, in some cases, specific to the mutation of interest. The protein may also be analyzed by protease digestion (e.g., trypsin digestion), and in some embodiments, the digested protein product may be further analyzed by 2D gel electrophoresis.

[0078]

[0092] Antibody-based detection methods In any of the various methods known in the art, a specific antibody that recognizes a biomarker of interest can be used. Antibodies against specific epitopes, polypeptides, and / or proteins can be produced using any of the various methods known in the art. For example, an antibody that produces the desired epitope, polypeptide, or protein can be injected into an animal, typically a mammal (e.g., a donkey, mouse, rabbit, horse, chicken, etc.), and the antibody produced by the animal can be collected from the animal. Monoclonal antibodies can also be produced by generating hybridomas that express the antibody of interest using immortal cell lines.

[0079]

[0093] In some embodiments, the antibody is labeled with a detectable moiety as described herein.

[0080]

[0094] Antibody detection methods, including enzyme-linked immunosorbent assays (ELISA) and Western blotting, are well known in the art, though not limited to these. Some such methods are suitable for array-based implementation.

[0081]

[0095] For example, in some embodiments, a biomarker of interest is detected using a first antibody (or antibody fragment) that specifically recognizes the biomarker. The antibody may be labeled with a detectable portion (e.g., a chemiluminescent molecule), an enzyme, or a second binder (e.g., streptavidin). Alternatively, the first antibody may be detected using a second antibody, as is known in the art.

[0082]

[0096] In certain embodiments, the method may further include adding a capture support, the capture support comprising at least one capture support binder that recognizes and binds to a biomarker so as to immobilize the biomarker on the capture support. In certain embodiments, the method may further include adding a second binder that can specifically recognize and bind to at least some of a plurality of binder molecules and / or biomarkers on the capture support. In one embodiment, the binder that can specifically recognize and bind to at least some of a plurality of binder molecules and / or biomarkers on the capture support is a soluble binder (e.g., a secondary antibody). The second binder may be labeled (e.g., by an enzyme) so that the binding of the biomarker of interest is measured by adding an enzyme substrate and quantifying the amount of the formed product.

[0083]

[0097] In one embodiment, the capture solid support may be an assay well (i.e., a microtiter plate, etc.). Alternatively, the capture solid support may be at some position on the array, or it may be a movable support such as a bead. Alternatively, the capture support may be a filter.

[0084]

[0098] In some cases, a biomarker may be complexed with a first binder (e.g., a primary antibody specific to the biomarker and labeled by a detectable moiety) and a second binder (e.g., a secondary antibody that recognizes the primary antibody or the second primary antibody), the second binder being complexed with a third binder (e.g., biotin), which can then interact with a capture support (e.g., magnetic beads) linked to the capture support and containing a reagent that recognizes the third binder (e.g., streptavidin). The complex (labeled primary antibody:biomarker:second primary antibody-biotin:streptavidin-beads) can then be captured using a magnet (e.g., a magnetic probe) to measure the amount of the complex.

[0085]

[0099] Various binders may be used in the methods of this disclosure. For example, the binder attached to the capture support, or the second antibody, may be either an antibody or antibody fragment that recognizes a biomarker. Alternatively, the binder may include a protein that binds to a non-protein target (i.e., a protein that specifically binds to a small molecule biomarker, or a receptor that binds to a protein).

[0086]

[0100] In certain embodiments, the solid support may be treated with a passivation agent. For example, in certain embodiments, the biomarker of interest may be captured on a passivated surface (i.e., a surface treated to reduce nonspecific binding). One such passivation agent is BSA. Additionally and / or alternatively, if the binder used is an antibody, the solid support may be coated with protein A, protein G, protein A / G, protein L, or another active agent (e.g., an antibody) that binds with high affinity to the binder. These proteins bind to the Fc domain of the antibody, thereby directing the binding of the antibody that recognizes one or more proteins of interest.

[0087]

[0101] nucleic acid assay In certain embodiments, the biomarkers disclosed herein are detected at the nucleic acid level. In one embodiment, the disclosure includes a method for diagnosing the presence of a syndrome or disease of interest (e.g., HNSCC) in a subject, or an increased risk of developing a syndrome or disease of interest (e.g., HNSCC) in a subject.

[0088]

[0102] The method may include the steps of obtaining nucleic acids from a tissue or bodily fluid sample derived from the target and performing an assay to identify whether or not there is overexpression of the gene of interest. For example, overexpression of a specific gene product can be quantified using reverse transcriptase PCR (RT-PCR). Alternatively, droplet digital PCR (ddPCR), duplex ddPCR, or multiplex ddPCR may be used.

[0089]

[0103] Alternatively, the method may include the steps of obtaining nucleic acids from a tissue or bodily fluid sample derived from the subject and performing an assay to identify whether the nucleic acid of the subject contains a variant sequence (i.e., a mutation). In certain embodiments, the method may include comparing the variant to known variants associated with the syndrome or disease of interest and determining whether the variant is a variant previously identified as associated with the syndrome or disease of interest. Alternatively, the method may include identifying the variant as a new, previously uncharacterized variant. If the variant is a new variant, the method may further include performing an analysis to determine whether the mutation is predicted to be detrimental to gene expression and / or to the function of the protein encoded by the gene. The method may further include using a variant profile (i.e., an aggregate of variants identified in the subject) to diagnose the presence of the syndrome or disease of interest, or an increased risk of developing the syndrome or disease of interest.

[0090]

[0104] Nucleic acid analysis may be performed on genomic DNA, messenger RNA, and / or cDNA. In various embodiments, nucleic acids may include genes, RNA, exons, introns, gene regulatory elements, expressed RNA, siRNA, or epigenetic elements. Regulatory elements, including splice sites, transcription factor binding sites, AI editing sites, microRNA binding sites, and functional RNA structure sites, may also be evaluated for mutations (i.e., variants). Thus, for each of the methods and compositions of this disclosure, a variant may include a nucleic acid sequence comprising at least one of the following: (1) A-to-I editing sites; (2) splice sites; (3) conserved functional RNA structures; (4) effective transcription factor binding sites (TFBS); (5) microRNA (miRNA) binding sites; (6) polyadenylation sites; (7) known regulatory elements; (8) miRNA genes; (9) nucleolar small RNA genes encoded in ROIs; and / or (10) hyperconserved elements across placental mammals.

[0091]

[0105] In many embodiments, nucleic acids are extracted from biological samples. In some embodiments, nucleic acids are analyzed without amplification. In some embodiments, nucleic acids are amplified using techniques known in the art (such as generating cDNA amplified using polymerase chain reaction (PCR)), and the amplified nucleic acids are used for subsequent analysis. Multiplex PCR may be used to amplify several amplicons at once using multiple sets of primer pairs (e.g., from different genomic regions). For example, nucleic acids may be analyzed by sequencing, hybridization, PCR amplification, restriction enzyme digestion, primer extension, e.g., single-nucleotide primer extension or multiplex allele-specific primer extension (ASPE), or DNA sequencing. In some embodiments, nucleic acids are amplified such that the size of the amplified product of the wild-type allele differs from the size of the mutant allele. Thus, the presence or absence of a particular mutant allele can be determined, for example, by detecting the size difference of the amplified products on an electrophoretic gel. For example, deletions or insertions of gene regions may be particularly suitable for the use of size-based methods.

[0092]

[0106] Specific exemplary nucleic acid analysis methods are described in detail below.

[0093]

[0107] Https analysis In certain embodiments, mRNA is analyzed using droplet digital PCR, such as duplex ddPCR or multiplex ddPCR. In digital PCR, individual PCR reactants are partitioned into hundreds to millions of individual wells, or into small volumes of water-oil emulsion droplets, as in droplet digital PCR (ddPCR). After PCR amplification, each partition is counted as either positive or negative. The ratio of positive partitions (k) to the total number of partitions (n) is used to calculate the initial concentration (C) by the Poisson distribution, where C = -ln(1-k / n).

[0094]

[0108] In certain embodiments, mRNA is analyzed using real-time and / or reverse transcriptase PCR, using methods known in the art, as well as / or commercially available reagents and / or kits. “Real-time PCR” or rPCR is a method for detecting and measuring products generated during each cycle of PCR, proportional to the amount of template nucleic acid before the start of PCR. The resulting information, such as amplification curves, can be used to determine the presence of a target nucleic acid and / or quantify the initial amount of a target nucleic acid sequence. The term “real-time PCR” is used to describe certain PCR techniques that enable the detection of PCR products throughout the entire PCR reaction or in real time. In some embodiments, rPCR is real-time reverse transcriptase (RT) real-time PCR (rRT-PCR).

[0095]

[0109] Reverse transcriptase PCR is used when the starting material is RNA and / or mRNA. RNA is first transcribed into complementary DNA (cDNA) by reverse transcriptase. In rRT-PCR, the cDNA is then used as a template for the qPCR reaction. rRT-PCR can be performed in a one-step method combining reverse transcription and PCR in a single tube and buffer using reverse transcriptase along with DNA polymerase. In one-step rRT-PCR, both RNA and DNA targets are amplified using sequence-specific targets. The term "quantitative PCR" encompasses any PCR-based technique that enables quantitative or semi-quantitative determination of the initially present target nucleic acid sequence.

[0096]

[0110] The principle of real-time PCR (rPCR) is generally described, for example, in Held et al., "Real Time Quantitative PCR," Genome Research 6:986-994 (1996). Generally, rPCR measures the signal at each amplification cycle. Some rPCR techniques rely on fluorophores that emit a signal at the completion of each amplification cycle. An example of such fluorophores is a fluorescent dye that emits fluorescence at a given wavelength when bound to double-stranded DNA, e.g., SYBR green. Thus, the increase in double-stranded DNA during each amplification cycle results in an increase in fluorescence intensity due to the accumulation of PCR products. Another example of fluorophores used for detection in rPCR is sequence-specific fluorescent reporter probes. An example of such probes is the TAQMAN® probe. The use of sequence-specific reporter probes results in the detection of highly specific target sequences and enables quantification even in the presence of non-specific DNA amplification. Fluorescent probes can also be used in multiplex assays to detect several genes in the same reaction, based on specific probes with different color labels. For example, a multiplex assay can use several sequence-specific probes labeled with various fluorophores, including but not limited to FAM, JA270, CY5.5, and / or HEX, in the same PCR reaction mixture.

[0097]

[0111] rPCR relies on the detection of measurable parameters such as fluorescence during the PCR reaction. The amount of the measurable parameter is proportional to the amount of the PCR product, thereby enabling the "real-time" observation of the increase in the PCR product. Some rPCR methods enable the quantification of the input DNA template based on the observable progress of the PCR reaction. The "growth curve" or "amplification curve" associated with a nucleic acid amplification assay is a graph of a function, where the independent variable is the number of amplification cycles and the dependent variable is the amplification-dependent measurable parameter measured at each cycle of amplification, for example, the fluorescence emitted by a fluorophore. As described above, the amount of the amplified target nucleic acid can be detected using a fluorophore-labeled probe. Typically, the amplification-dependent measurable parameter is the amount of fluorescence emitted by the probe during hybridization or upon hydrolysis of the probe by the nuclease activity of the nucleic acid polymerase. The increase in fluorescence emission is measured in real time and is directly related to the increase in target nucleic acid amplification. In some examples, the change in fluorescence (dR t ) is calculated using the formula dR n = R n+ - R n- , where R n+ is the fluorescence emission of the product at each time point and R n- is the baseline fluorescence emission. The dR n values are plotted against the number of cycles to obtain an amplification plot. In a typical polymerase chain reaction, the growth curve includes a segment of exponential growth followed by a plateau, and an S-shaped amplification plot is obtained when using a linear scale. The growth curve is characterized by a "crossing point" value or "C t " value, also referred to as the "threshold" or "cycle threshold" (C p ), which is the number of PCR cycles at which a predetermined magnitude of the measurable parameter is achieved. For example, when a fluorophore-labeled probe is used, the threshold (C t ) is the number of PCR cycles at which the fluorescence emission (dR n [[ID=A lower value indicates that the amplification is completed faster. t A higher value indicates that the amplification process takes longer. If the amplification efficiency is similar, C t A lower value reflects a higher starting dose of the target nucleic acid. t A higher value reflects a lower starting dose of the target nucleic acid. A "standard curve," or "control" curve, is created using a known concentration of control nucleic acid for various known concentrations of control nucleic acid. t When generating a set of values, the C of the target nucleic acid t Value and control nucleic acid C t By comparing it with the value, it becomes possible to determine the absolute amount of the target nucleic acid in the sample.

[0098]

[0112] Allele-specific amplification In some embodiments, for example, if the biomarker for the disease and / or syndrome of interest is a mutation, the biomarker is detected using an allele-specific amplification assay. This technique is variously referred to as PCR amplification of specific alleles (PASA) (Sarkar, et al., 1990 Anal. Biochem. 186:64-68), allele-specific amplification (ASA) (Okayama, et al., 1989 J. Lab. Clin. Med. 114:105-113), allele-specific PCR (ASPCR) (Wu, et al. 1989 Proc. Natl. Acad. Sci. USA. 86:2757-2760), and amplification-refractory mutation system (ARMS) (Newton, et al., 1989 Nucleic Acids Res. 17:2503-2516). This method is applicable to single base substitutions and microdeletions / insertions.

[0099]

[0113] For example, in a PCR-based amplification method, amplification primers can be designed to distinguish between different alleles (e.g., wild-type alleles and mutant alleles). Therefore, the presence or absence of an amplification product can be used to determine whether a gene mutation is present in a given nucleic acid sample. In some embodiments, allele-specific primers can be designed so that the presence of an amplification product indicates a gene mutation. In some embodiments, allele-specific primers can be designed so that the absence of an amplification product indicates a gene mutation.

[0100]

[0114] In some embodiments, two complementary reactions are used. One reaction uses a primer specific to the wild-type allele ("wild-type specific reaction"), and the other reaction uses a primer for the mutant allele ("mutation specific reaction"). The two reactions may use a common second primer. PCR primers specific to a particular allele (e.g., wild-type allele or mutant allele) generally perfectly match one allele variant of the target, but mismatch other allele variants (e.g., mutant allele or wild-type allele). The mismatch may be located at / near the 3' end of the primer and result in preferential amplification of the perfectly matched allele. Whether the amplification product can be detected from one reaction or both reactions indicates the absence or presence of the mutant allele. Detection of the amplification product from the wild-type specific reaction only indicates the presence of the wild-type allele only (e.g., homozygosity of the wild-type allele). Detection of the amplification product in the mutation specific reaction indicates the presence of the mutant allele only (e.g., homozygosity of the mutant allele). The detection of amplification products from both reactions indicates (e.g., heterozygotes). As used herein, this technique is called "allelicity-specific amplification (ASA)".

[0101]

[0115] Allele-specific amplification can also be used to detect duplication, insertion, or inversion by using primers that partially hybridize across the junction. The degree of junctional duplication can be varied to allow for specific amplification.

[0102]

[0116] For example, the amplified product can be examined by methods known in the art, such as visualizing the bands of nucleic acids that have moved through a gel (e.g., by electrophoresis) to separate nucleic acids by size (e.g., using one or more dyes).

[0103]

[0117] Allele-specific primer elongation In some embodiments, allele-specific primer elongation (ASPE) techniques are used to detect gene mutations. ASPE uses allele-specific primers that can distinguish between alleles (e.g., the mutant allele and the wild-type allele) in the elongation reaction, so that the elongation product is obtained only in the presence of a specific allele (e.g., the mutant allele or the wild-type allele). The elongation product may or may be detectable by, for example, using labeled deoxyribonucleotides in the elongation reaction. A variety of labels, including, but not limited to, radioactive, fluorescent, chemiluminescent, and enzymatic labels, are suitable for use in these methods. In some embodiments, the nucleotides are labeled with detectable labels, for example, entities that can be conjugated (directly or indirectly) by biotin molecules that can be conjugated by streptavidin conjugate fluorescent dyes. In some embodiments, the reaction is carried out in multiplex, for example, using many allele-specific primers in the same elongation reaction.

[0104]

[0118] In some embodiments, the elongation product is hybridized to a solid or semi-solid support, such as beads, a matrix, or a gel. For example, the elongation product may be tagged with a specific nucleic acid sequence (e.g., included as part of an allele-specific primer), and the solid support may be attached to an "anti-tag" (e.g., a nucleic acid sequence complementary to the tag in the elongation product). The elongation product can be captured and detected on the solid support. For example, beads can be sorted and detected.

[0105]

[0119] Single-chain nucleotide primer extension In some embodiments, single-chain nucleotide primer elongation (SNuPE) assays are used, in which the primer is designed to be elongated by only one nucleotide. In such methods, the identity of the nucleotide immediately downstream of the 3' end of the primer is known and differs in terms of the mutant allele compared to the wild-type allele. SNuPE can be carried out using an elongation reaction in which only one specific type of deoxyribonucleotide is labeled (e.g., labeled dATP, labeled dCTP, labeled dGTP, or labeled dTTP). Thus, the presence of a detectable elongation product can be used as an indicator of nucleotide identity at the site of interest (e.g., immediately downstream of the 3' end of the primer), and therefore as an indicator of the presence or absence of a mutation at that site. SNuPE can be implemented as described in U.S. Patent Nos. 5,888,819; 5,846,710; 6,280,947; 6,482,595; 6,503,718; 6,919,174; Piggee, C. et al. Journal of Chromatography A 781 (1997), pp. 367-375 ("Capillary Electrophoresis for the Detection of Known Point Mutations by Single-Nucleotide Primer Extension and Laser-Induced Fluorescence Detection"); Hoogendoorn, B. et al., Human Genetics (1999) 104:89-93 ("Genotyping Single Nucleotide Polymorphism by Primer Extension and High Performance Liquid Chromatography").

[0106]

[0120] In some embodiments, primer extension may be combined with mass spectrometry for accurate and rapid detection of the presence or absence of mutations. See U.S. Patent No. 5,885,775 by Haff et al. (analysis of single nucleotide polymorphism analysis by mass spectrometry); and U.S. Patent No. 7,501,251 by Koster (DNA diagnosis based on mass spectrometry). Suitable mass spectrometry formats include, but are not limited to, matrix-assisted laser desorption / ionization, time-of-flight (MALDI-TOF), electrospray (ES), IR-MALDI, ion cyclotron resonance (ICR), Fourier transform, and combinations thereof.

[0107]

[0121] Oligonucleotide ligation assay In some embodiments, oligonucleotide ligation assays ("OLA" or "OL") are used. OLA uses two oligonucleotides designed to hybridize to a single-stranded adjacent sequence of a target molecule. Typically, one oligonucleotide is biotinylated, and the other is labeled detectably by, for example, a streptavidin conjugate fluorescent moiety. If the exact complementary sequence is found within the target molecule, the oligonucleotides hybridize so that their ends are adjacent, creating a ligation substrate that can be captured and detected. See, for example, Nickerson et al. (1990) Proc. Natl. Acad. Sci. USA 87:8923-8927, Landegren, U. et al. (1988) Science 241:1077-1080, and U.S. Patent No. 4,998,617.

[0108]

[0122] Hybridization techniques In some embodiments, nucleic acids are analyzed under sufficiently stringent conditions to avoid single-chain nucleotide mismatches by hybridization using one or more oligonucleotide probes specific to the biomarker of interest. In certain embodiments, suitable nucleic acid probes can distinguish between normal and mutant genes. Thus, for example, those skilled in the art can use the probes of the present invention to determine whether an individual is homozygous or heterozygous for a particular allele.

[0109]

[0123] Nucleic acid hybridization techniques are well known in the art. Those skilled in the art will understand how to estimate and adjust the stringency of hybridization conditions so that sequences with at least a desired level of complementarity stably hybridize, while sequences with lower levels of complementarity do not. For examples of hybridization conditions and parameters, see, for example, Sambrook, et al., 1989, Molecular Cloning: A Laboratory Manual, Second Edition, Cold Spring Harbor Press, Plainview, NY; Ausubel, FM et al., 1994, Current Protocols in Molecular Biology, John Wiley & Sons, Secaucus, NJ.

[0110]

[0124] In some embodiments, probe molecules that hybridize to a mutant or wild-type sequence can be used to detect such sequences in the amplification product by solution-phase hybridization or, more preferably, solid-phase hybridization. Solid-phase hybridization can be achieved, for example, by mounting the probe on a microchip.

[0111]

[0125] Nucleic acid probes may include ribonucleic acid and / or deoxyribonucleic acid. In some embodiments, the nucleic acid probe provided is an oligonucleotide (i.e., “oligonucleotide probe”). Generally, oligonucleotide probes are long enough to specifically bind to homologous regions of the gene of interest, but short enough so that a one-nucleotide difference between the probe and the nucleic acid sample being tested disrupts hybridization. Typically, the size of oligonucleotide probes varies from about 10 to 100 nucleotides. In some embodiments, oligonucleotide probes vary in length from 15 to 90, 15 to 80, 15 to 70, 15 to 60, 15 to 50, 15 to 40, 15 to 35, 15 to 30, 18 to 30, or 18 to 26 nucleotides. As will be recognized by those skilled in the art, the optimal length of an oligonucleotide probe may depend on the specific methods and / or conditions under which the oligonucleotide probe may be used.

[0112]

[0126] In some embodiments, nucleic acid probes are useful, for example, as primers for nucleic acid amplification and / or extension reactions. For example, in certain embodiments, the gene sequence evaluated for a mutant includes an exon sequence. In certain embodiments, the exon sequence and additional flanking sequences (e.g., about 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 or more nucleotides of the UTR and / or intron sequence) are analyzed in the assay. Alternatively, an intron sequence or other non-coding region may be evaluated for a potentially harmful mutation. Or, a portion of these sequences may be used. Such mutant gene sequences may include sequences having at least one of the mutations described herein.

[0113]

[0127] Other embodiments of this disclosure provide isolated gene sequences containing mutations associated with syndromes and / or diseases of interest. Such gene sequences may be used to objectively diagnose the presence or increased risk of a subject developing HNSCC. In certain embodiments, the isolated nucleic acids may contain non-mutant sequences, or one or a combination thereof. For example, in certain embodiments, the gene sequence includes an exon sequence. In certain embodiments, the exon sequence and additional flanking sequences (e.g., about 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 or more nucleotides of the UTR and / or intron sequences) are analyzed in an assay. Alternatively, intron sequences or other non-coding regions may be used. Alternatively, portions of these sequences may be used. In certain embodiments, the gene sequence includes an exon sequence from at least one of the biomarker genes disclosed herein.

[0114]

[0128] In some embodiments, the nucleic acid probe is labeled with a detectable portion described herein.

[0115]

[0129] array The various methods described herein can be adapted for use as arrays, enabling the analysis and / or detection of a set of biomarkers in a single experiment. For example, multiple mutations containing biomarkers can be analyzed simultaneously. Methods involving the use of nucleic acid reagents (e.g., probes, primers, oligonucleotides, etc.) are particularly well-suited for adaptation to array-based platforms (e.g., microarrays). In some embodiments, the array contains one or more probes specific for detecting mutations of the biomarker of interest.

[0116]

[0130] In one embodiment, a panel of multiple disclosed biomarkers is used. In one embodiment, the disclosure includes a composition for detecting biomarkers associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising a reagent for quantifying the expression level of at least one of the genes in Tables 1, 2, 5, and / or 6, and / or at least one of AIM2, CDSN, INHBA, MMP1, MMP3, or MMP10. In addition, the expression products of other genes, including at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15, may be measured. Alternatively, combinations of these genes (disclosed herein) may be measured. Additionally and / or alternatively, the composition may include at least one normalization (e.g., housekeeping) gene. In one embodiment, the normalization gene may be KHDRBS1 and / or RPL30, or other normalization genes. In certain embodiments, the composition may comprise a primer and / or probe for any one of these genes, the primer and / or probe being labeled with a detectable portion as described herein.

[0117]

[0131] DNA sequencing In certain embodiments, the diagnosis of a biomarker of interest is performed by detecting variations in the sequence, genomic location or arrangement, and / or genomic copy number of nucleic acids or panels of nucleic acids by nucleic acid sequencing.

[0118]

[0132] In some embodiments, the method may include obtaining nucleic acids from a tissue or bodily fluid sample derived from the subject and sequencing at least a portion of the nucleic acids to obtain a sample nucleic acid sequence of at least one gene. In certain embodiments, the method may include comparing the variant to known variants associated with HNSCC and determining whether the variant is a variant previously identified as associated with HNSCC. Alternatively, the method may include identifying the variant as a new, previously uncharacterized variant. If the variant is a new variant, or possibly a previously characterized (i.e., identified) variant, the method may further include performing an analysis to determine whether the mutation is predicted to be detrimental to gene expression and / or to the function of the protein encoded by the gene. The method may further include using a variant profile (i.e., an aggregate of variants identified in the subject) to diagnose the presence of HNSCC or an increased risk of developing HNSCC.

[0119]

[0133] For example, in certain embodiments, next-generation (ultra-parallel sequencing) may be used. Alternatively, Sanger sequencing may be used. Alternatively, a combination of next-generation (ultra-parallel sequencing) and Sanger sequencing may be used. Additionally and / or alternatively, the sequencing includes at least one of single-molecule sequencing-by-synthesis. Thus, in certain embodiments, multiple DNA samples are analyzed in a pool to identify samples exhibiting mutations. Additionally and / or alternatively, in certain embodiments, multiple DNA samples are analyzed in multiple pools to identify individual samples exhibiting the same mutation in at least two pools.

[0120]

[0134] One conventional method of sequencing involves chain arrest and gel separation, as described in Sanger et al., 1977, Proc. Natl. Acad. Sci. USA, 74:5463-67. Another conventional sequencing method involves the chemical degradation of nucleic acid fragments. See Maxam et al., 1977, Proc. Natl. Acad. Sci., 74:560-564. Several methods have also been developed based on hybridization sequencing. See, for example, U.S. Patent Application Publication No. 20090156412 by Harris et al.

[0121]

[0135] In other embodiments, nucleic acid sequencing is achieved by massively parallel sequencing (also known as "next-generation sequencing") of single molecules or groups of largely identical molecules derived from a single molecule, through amplification via methods such as PCR. Massively parallel sequencing is demonstrated, for example, in U.S. Patent No. 7,169,560 by Lapidus et al., U.S. Patent No. 6,818,395 by Quake et al., U.S. Patent No. 7,282,337 by Harris, and Braslavsky, et al., PNAS (USA), 100:3960-3964 (2003).

[0122]

[0136] In next-generation sequencing, PCR or whole-genome amplification can be performed on nucleic acids to obtain a sufficient amount of nucleic acid for analysis. In some forms of next-generation sequencing, amplification is not required because this method can evaluate DNA sequences from unamplified DNA. The nucleic acid sequences and / or genome sequences and / or genome copy numbers from the test samples, once determined, are compared to a standard reference from one or more individuals not known to have HNSCC at the time the samples were collected. Any differences between the nucleic acid sequences and / or genome sequences and / or genome sequences and / or copy numbers from the test samples and the standard reference are considered variants.

[0123]

[0137] In next-generation (ultra-parallel sequencing), all regions of interest are sequenced together, and the origin of each sequence read is determined by comparison (alignment) with a reference sequence. The regions of interest may be enriched together in a single reaction, or they may be enriched separately and then combined before sequencing. In certain embodiments, as further detailed in the examples herein, DNA sequences derived from coding exons of genes included in the assay are enriched by bulk hybridization of randomly fragmented genomic DNA to a specific RNA probe. The same adapter sequence is attached to the ends of all fragments, allowing enrichment of any hybridization-captured fragment by PCR using one primer pair in a single reaction. Regions that are not captured very efficiently by hybridization are amplified by PCR using specific primers. In addition, PCR using specific primers may be used to amplify exons where similar sequences ("pseudoexons") exist elsewhere in the genome.

[0124]

[0138] In certain embodiments where ultra-parallel sequencing is used, PCR products are ligated to form a long stretch of DNA, which is then sheared into shorter fragments (e.g., by acoustic energy). This step ensures that the fragment ends are distributed throughout the region of interest. Subsequently, a stretch of dA nucleotides is added to the 3' end of each fragment, allowing it to be bound to a plane ("flow cell") coated with oligo(dT) primers. Each fragment can then be sequenced by extending the oligo(dT) primers with fluorescently labeled nucleotides. Only one type of nucleotide (A, G, T, or C) is added during each sequencing cycle, and only one nucleotide can be incorporated by using a chain-stopping nucleotide. For example, a fluorescently labeled dCTP may be added during the first sequencing cycle. This nucleotide is incorporated only into the growing complementary DNA strand that requires C as the next nucleotide. After each sequencing cycle, an image of the flow cell is taken to determine which fragments were extended. DNA strands incorporating 1C fluoresce, while those without 1C fluoresce appear dimmer. The strand arrest is reversed, allowing the growing DNA strand to be extended again, and this process is repeated for a total of 120 cycles. The images are converted into strings of bases, commonly called "reads," which reproduce the 25–60 bases at the 3' end of each fragment. The reads are then compared to a reference sequence of the analyzed DNA. Since any given 25-base string typically occurs only once in the human genome, most reads can be "aligned" to one specific location within the human genome. Finally, a consensus sequence for each genomic region may be constructed from the available reads and compared to the exact sequence of the reference at that location. Any difference between the consensus sequence and the reference is called a sequence variant.

[0125]

[0139] Detectable portion In certain embodiments, certain molecules used in accordance with the present invention and / or provided by the present invention (e.g., nucleic acid probes, antibodies, etc.) comprise one or more detectable entities or parts, i.e., such molecules are "labeled" by such entities or parts.

[0126]

[0140] A wide variety of detectable active substances can be used in the implementation of this disclosure. Suitable detectable active substances include, but are not limited to, various ligands; radioactive nucleotides; fluorescent dyes; chemiluminescent agents (e.g., acridinium esters, stabilized dioxetanes, etc.); bioluminescent agents; spectrally decomposable inorganic fluorescent semiconductor nanocrystals (e.g., quantum dots); microparticles; metal nanoparticles (e.g., gold, silver, copper, platinum); nanoclusters; paramagnetic metal ions; enzymes; colorimetric labels (e.g., dyes, gold colloids, etc.); biotin; dioxygenin; haptens; and proteins for which antiserum or monoclonal antibodies are available.

[0127]

[0141] In some embodiments, the detectable portion is biotin. Biotin can bind to avidin (such as streptavidin), and avidin is typically conjugated (directly or indirectly) to another detectable portion (e.g., a fluorescent portion).

[0128]

[0142] Some non-exclusive examples of some detectable parts that may be used are listed below.

[0129]

[0143] fluorescent dyes In certain embodiments, the detectable portion is a fluorescent dye. A large number of known fluorescent dyes with diverse chemical structures and physical properties are suitable for use in the implementation of this disclosure. The fluorescent detectable portion can be stimulated by a laser using light emitted by a detector. The detector may be a charge-coupled device (CCD) or a confocal microscope that records its intensity.

[0130]

[0144] Suitable fluorescent dyes include, but are not limited to, fluorescein and fluorescein dyes (e.g., fluorescein isothiocyanine or FITC, naphthofluorescein, 4',5'-dichloro-2',7'-dimethoxyfluorescein, 6-carboxyfluorescein or FAM), hexachlorofluorescein (HEX), carbocyanine, merocyanine, styryl dyes, oxonol dyes, phycoerythrin, erythrosine, eosin, rhodamine dyes (e.g., carboxytetramethylrhodamine or TAMRA, carboxyrhodamine 6G, carboxy-X-rhodamine (ROX), lysaminerhodamine B, rhodamine 6G, rhodamine Green, rhodamine Red, tetramethylrhodamine (TMR)), coumarin and coumarin dyes (e.g., methoxycoumarin, dialkylaminocoumarin, hydroxycoumarin, aminomethylcoumarin (AMCA)), Q-DOTS, Oregon Green pigments (e.g., Oregon Green 488, Oregon Green 500, Oregon Green 514), Texas Red, Texas Red-X, Spectrum Red, Spectrum Green, Cyanine pigments (e.g., CY-3, CY-5, CY-3.5, CY5.5), Alexa Fluorine pigments (e.g., Alexa Fluorine 350, Alexa Fluorine 488, Alexa Fluorine 532, Alexa Fluorine 546, Alexa Fluorine 568, Alexa Fluorine 594, Alexa Fluorine 633, Alexa Fluorine 660, Alexa Fluorine 680), Bodipy pigments (e.g., Bodipy FL, Bodipy R6G, Bodipy TMR, Bodipy TR, Bodipy This includes 530 / 550, BODIPY 558 / 568, BODIPY 564 / 570, BODIPY 576 / 589, BODIPY 581 / 591, BODIPY 630 / 650, BODIPY 650 / 665), IRDyes (e.g., IRD40, IRD700, IRD800), etc.For further examples of suitable fluorescent dyes and methods for conjugating them to other chemical entities such as proteins and peptides, see, for example, "The Handbook of Fluorescent Probes and Research Products," 9th Ed., Molecular Probes, Inc., Eugene, OR. Preferred properties of fluorescent labels include high molar absorption coefficients, high fluorescence quantum yield, and photostability. In some embodiments, the labeled fluorophores exhibit absorption and emission wavelengths in the visible region (i.e., 400–750 nm) rather than the ultraviolet region of the spectrum (i.e., below 400 nm).

[0131]

[0145] The detectable portion may include multiple chemical entities, for example, in fluorescence resonance energy transfer (FRET). Resonance transfer results in an overall enhancement of emission intensity. See, for example, Ju et al. (1995) Proc. Nat'l Acad. Sci. (USA) 92:4347, whose entire content is incorporated herein by reference. To achieve resonance energy transfer, a first fluorescent molecule ("donor" phosphor) absorbs light and transfers it to a second fluorescent molecule ("acceptor" phosphor) through resonance of excited electrons. In one method, both the donor and acceptor dyes can be ligated together and attached to an oligo primer. A method for ligating donor and acceptor dyes to nucleic acids is described, for example, in U.S. Patent No. 5,945,526 by Lee et al. Possible donor / acceptor pairs of dyes include, for example, fluorescein / tetramethylrhodamine, IAEDANS / fluorescein, EDANS / DABCYL, fluorescein / fluorescein, BODIPY FL / BODIPY FL, and fluorescein / QSY 7 dyes. See, for example, U.S. Patent No. 5,945,526 by Lee et al. Many of these dyes are commercially available, for example, from Molecular Probes Inc. (Eugene, Oreg.). Suitable donor fluorophores include 6-carboxyfluorescein (FAM), tetrachloro-6-carboxyfluorescein (TET), and 2'-chloro-7'-phenyl-1,4-dichloro-6-carboxyfluorescein (VIC).

[0132]

[0146] enzyme In certain embodiments, the detectable portion is an enzyme. Suitable enzymes include, but are not limited to, those used in ELISA, such as horseradish peroxidase, beta-galactosidase, luciferase, and alkaline phosphatase. Other examples include beta-glucuronidase, beta-D-glucosidase, urease, and glucose oxidase. Enzymes can be conjugated to molecules using linker groups such as carbodiimide, diisocyanate, and glutaraldehyde.

[0133]

[0147] radioactive isotope In certain embodiments, the detectable portion is a radioactive isotope. For example, the molecule may be isotope-labeled (i.e., it may contain one or more atoms that have different atomic masses or mass numbers than those commonly found in nature), or the isotope may be attached to the molecule. Non-limiting examples of isotopes that can be incorporated into molecules include isotopes of hydrogen, carbon, fluorine, phosphorus, copper, gallium, yttrium, technetium, indium, iodine, rhenium, thallium, bismuth, astatine, samarium, and lutetium (e.g., 3H, 13C, 14C, 18F, 19F, 32P, 35S, 64Cu, 67Cu, 67Ga, 90Y, 99mTc, 111In, 125I, 123I, 129I, 131I, 135I, 186Re, 187Re, 201T1, 212Bi, 213Bi, 21lAt, 153Sm, 177Lu).

[0134]

[0148] Dendrimer In some embodiments, signal amplification is achieved using labeled dendrimers as detectable portions (see, e.g., Physiol Genomics 3:93-99, 2000). Fluorescently labeled dendrimers are available from Genisphere (Montvale, NJ). These may be chemically conjugated to oligonucleotide primers by methods known in the art.

[0135]

[0149] Method for identifying HNSCC markers Data mining In certain embodiments of this disclosure, biomarkers are identified using data mining techniques. For example, public databases, such as PubMed and The Cancer Genome Atlas (TCGA), may be searched for genes that have been shown to be (directly or indirectly) associated with a particular disease and / or to be differentially expressed in cancer compared to normal tissue. Such genes may then be evaluated as biomarkers.

[0136]

[0150] molecule In certain embodiments, the disclosure includes a method for identifying biomarkers (i.e., variants in nucleic acid sequences associated with HNSCC in a statistically significant manner) of a syndrome or disease of interest. For example, the gene of interest, and potential normalization genes, may be identified by evaluating gene expression in tissue samples isolated from patients with head and neck cancer using random forest analysis (see, e.g., L. Breiman, "Random Forests," Machine Learning, 2001, 45:5-32), as described in detail herein. In this method, a random forest is a combination of tree predictors such that each tree depends on the values ​​of random vectors sampled independently of all trees in the forest in the same distribution.

[0137]

[0151] For example, as shown in U.S. Patent Application No. 16 / 224,974, filed December 19, 2018, published as U.S. Patent No. 2019 / 0187143, which is incorporated herein by reference in its entirety, RNASeq datasets from head and neck cancer (HNC) and normal tissue samples in the Cancer Genome Atlas (TCGA) may be matched by random forest (RF) analysis to identify and rank differentially expressed genes that can be used as diagnostic markers to distinguish HNC from non-cancer samples. The RNASeq data may be filtered to include only genes with reported values ​​for more than 50% of the samples and expression fold change greater than 2, with a Wilcox-adjusted p-value less than 0.001. In one embodiment, 75% of the samples may be used for a training set and 25% for a test set. The results may be cross-validated in 10 parts and optimized for Cohen's kappa and the top 20 ranked genes. The entire process may be repeated multiple times (e.g., four times) to determine the list of genes and the ranking of each RF (see, for example, Table 3 of U.S. Patent No. 2019 / 0187143) (in this table, rank 20 was the highest and rank 1 was the lowest). As shown in Table 4 of U.S. Patent No. 2019 / 0187143, the rank sum of genes from four RF runs results in a list of 36 unique genes. The column titled "Number of RFs" represents the number of times a particular gene appeared in the RF list. Genes appearing in all four RF repeats suggest that this could be a top candidate marker for distinguishing HNCs from non-cancer samples and may appear at the top of the list with the largest rank sum.

[0138]

[0152] As a complementary technique to RF analysis for identifying differentially expressed genes, the TCGA HNC RNASeq dataset may be used to compare the percentage of overlapping expression versus the fold change in expression (HNC / normal).

[0139]

[0153] For genes where HNC expression is increased (upregulated) compared to normal tissue, the percentage of expression overlap can be defined as the percentage of the sample between the 95th percentile of the normal distribution and the 5th percentile of the HNC distribution (see, for example, Figure 6 of U.S. Patent No. 2019 / 0187143, with GRIN2D as an example). For genes where HNC expression is decreased (downregulated) compared to normal tissue, the percentage of expression overlap can be defined as the percentage of the sample between the 95th percentile of the HNC distribution and the 5th percentile of the normal distribution. In certain embodiments, genes with a small percentage of expression overlap may be more suitable for use as a diagnostic marker to distinguish HNC from non-cancer samples.

[0140]

[0154] In some embodiments, the pluripotency change in expression may be determined by dividing the median expression from the HNC sample by the median expression of each gene in a normal sample. In certain embodiments, genes with large pluripotency changes in expression may be more suitable as diagnostic markers for distinguishing HNCs from non-cancer samples.

[0141]

[0155] In certain embodiments, the top (e.g., about 10) genes identified from RF analysis may have less than 20% overlap in expression, further supporting the idea that genes with a smaller percentage of overlap may be more suitable as diagnostic markers for distinguishing HNCs from non-cancer samples, and also highlighting the similarities between these two complementary methods for identifying differentially expressed genes.

[0142]

[0156] Alternatively, genes and / or genomic regions assayed for novel markers may be selected based on their importance in biochemical pathways demonstrating genetic linkage and / or biological causal relationship with the syndrome and / or disease of interest. Alternatively, genes and / or genomic regions assayed for markers may be selected based on genetic linkage with DNA regions genetically associated with the inheritance of HNSCC in the family. Alternatively, genes and / or genomic regions assayed for markers may be systematically evaluated to cover specific chromosomal regions that have not yet been assessed.

[0143]

[0157] In other embodiments, the gene or genomic region being evaluated for a novel marker may be part of a biochemical pathway that could be associated with the development of the syndrome and / or disease of interest (e.g., HNSCC). Variants and / or combinations of variants may be evaluated for their clinical significance based on one or more of the following methods: If a variant or combination of variants is reported or known to occur more frequently in nucleic acids from subjects with the syndrome and / or disease of interest than in subjects without the syndrome and / or disease of interest, it is considered at least a potential predisposition to the syndrome and / or disease of interest. If a variant or combination of variants is reported or known to be transmitted exclusively or preferentially to individuals with the syndrome and / or disease of interest, it is considered at least a potential predisposition to the syndrome and / or disease of interest. Conversely, if a variant is found at similar frequencies in both populations, it is less likely to be associated with the development of the syndrome and / or disease of interest.

[0144]

[0158] If a variant or combination of variants has been reported or is known to have an overall detrimental effect on the function of a protein or biological system in an experimental model system suitable for measuring the function of that protein or biological system, and if this variant or combination of variants affects one or more genes known to be associated with the syndrome and / or disease of interest, then it is considered to be at least a potential predisposition to the syndrome and / or disease of interest. For example, if a variant or combination of variants is predicted to have an overall detrimental effect on protein or gene expression (i.e., resulting in a nonsense variant, frameshift variant or splice site variant, or even a missense variant) based on the predicted effects on the sequence and / or structure of a protein or nucleic acid, and if this variant or combination of variants affects one or more genes known to be associated with the syndrome and / or disease of interest, then it is considered to be at least a potential predisposition to the syndrome and / or disease of interest.

[0145]

[0159] Furthermore, in certain embodiments, the total number of variants may be important. If one or more variants are detected in a test sample, individually or in combination, that are assessed to be at least likely to be associated with the syndrome and / or disease of interest, then individuals possessing this variant or the genetic material in which these variants were detected may be diagnosed as having the syndrome and / or disease of interest, or being at high risk of developing the syndrome and / or disease of interest.

[0146]

[0160] For example, the disclosure herein provides a method for diagnosing the presence of HNSCC development or an increased risk of HNSCC development in a subject. Such a method may include obtaining nucleic acids from a saliva sample derived from the subject. The method may include determining the expression of at least one gene in normal and cancerous tissues to identify potential biomarkers in the subject of interest. The method may further include sequencing the nucleic acid or determining the genomic sequence or copy number of the nucleic acid to detect whether one or more variants are present in the nucleic acid sequence or genomic sequence or copy number. The method may further include a step of evaluating the clinical significance of one or more variants. Such analysis may include an assessment of the degree of relevance of the variant sequence in an affected population (i.e., a subject having the disease). Such analysis may also include an analysis of the extent to which the mutation may have an effect on gene expression and / or protein function. The method may also include diagnosing the presence of HNSCC development or an increased risk of HNSCC development based on the assessment. [Examples]

[0147]

[0161] The following non-limiting examples may help illustrate certain aspects of the present invention.

[0148]

[0162] Example 1 - Overview The goal of this project was to develop a saliva-based screening test for oral and oropharyngeal cancers. Saliva may be collected using a simple collection device, such as a DNA Genotek CP-190, during annual physical examinations by primary care physicians, during 6-month preventive dental checkups by dentists, or for home collection. Relatively easy and non-invasive sampling makes saliva an ideal biological fluid. For screening head and neck cancers, saliva can be a preferred sample and may offer increased sensitivity due to direct contact with oral and oropharyngeal tissues. Figure 1 shows a diagram of the overall method according to one embodiment of the present disclosure.

[0149]

[0163] Example 2 - Saliva collection, and RNA isolation and quantification Two milliliters (mL) of saliva were collected from HNC patients and healthy volunteers using a DNA Genotek CP-190 collection device and mixed with two mL of RNA stabilizer. Samples can be stored at room temperature (RT) for up to eight weeks, or for longer periods at <20°C. The collection device was shipped at ambient temperature, processed according to the manufacturer's instructions, and stored at <70°C. The inset in Figure 1 shows the range of sample volumes accepted for this study.

[0150]

[0164] 235 μL aliquots were taken from the saliva collection device, and total RNA was isolated using the MagMax mirVanna® Total RNA Isolation Kit (ThermoFisher catalog number A27828) in the KingFisher® Flex Purification System. The MagMax mirVanna® Total RNA Isolation Kit contains GTC buffer and "silica-like" magnetic beads (Dynabeads® MyOne® Silane). The KingFisher® Flex Purification System uses PK+DNase with approximately 50 μL of eluate.

[0151]

[0165] Using 8 μL of eluate from 50 μL of KingFisher Flex, first-strand cDNA was synthesized using a random hexamer with the SuperScript IV First-Strand Synthesis System Kit (ThermoFisher catalog number 18091050) according to the manufacturer's recommended procedure. 23 μL of ddPCR reaction mixture was prepared using Bio-Rad 2X ddPCR Supermix for Probes (without dUTP, Bio-Rad catalog number 1863024), 900 nM / 250 nM target gene primers / probes (Bio-Rad ddPCR GEX FAM Assay, catalog number 10031252), and 900 nM / 250 nM RPL30 (housekeeping gene) primers / probes (Bio-Rad ddPCR GEX HEX Assay, catalog number 10031255). Droplets were generated in a Bio-Rad Automated Droplet Generator, and the plates were sealed with perforated foil using a Bio-Rad PCR Plate Sealer. Thermal cycling was performed in an Applied Biosystems Veriti 96-well Fast Thermal Cycler under the following conditions: 40 cycles of 10 minutes at 95°C (enzyme activation), 30 seconds at 94°C and 1 minute at 55°C (annealing / extension), 10 minutes at 98°C (enzyme inactivation), followed by holding at 4°C. Droplets were detected using a Bio-Rad QX200 Droplet Reader and analyzed using Bio-Rad QuantaSoft Analysis Pro Software, version 1.0, reporting units in copies / μL. Figure 2 shows the sex, age, cancer stage, tumor location, and number of saliva samples used in this study.

[0152]

[0166] Example 3 - General gene selection Candidate genes of interest were identified using the random forest method described in U.S. Patent Application No. 16 / 224,974, owned by the same owner, filed on 19 December 2018 and published as U.S. Patent No. 2019 / 0187143 (which is incorporated herein by reference in its entirety). For example, as shown in U.S. Patent No. 2019 / 0187143, owned by the same owner, RNASeq datasets from head and neck cancer (HNC) and normal tissue samples in the Cancer Genome Atlas (TCGA) were matched by random forest (RF) analysis to identify and rank differentially expressed genes that could be used as diagnostic markers to distinguish HNC from non-cancer samples. RNASeq data were filtered to include only genes with a multiplier change of more than 2, with reported values ​​for more than 50% of the samples and a Wilcox-adjusted p-value of less than 0.001. Next, 75% of the samples were used as a training set and 25% as a test set. The results were cross-validated in 10 parts and optimized for Cohen's kappa and the top 20 ranked genes. The entire process was repeated four times to determine the list of genes and the ranking of each RF (see Table 3 in shared U.S. Patent Publication 2019 / 0187143, e.g., showing gene rankings from 20 to 1). As shown in Figure 3, the sum of gene ranks from the four RF runs resulted in a list of 36 unique genes (from U.S. Patent Application 16 / 224,974, filed December 19, 2018, and published as U.S. Patent 2019 / 0187143). The improved rankings developed under this analysis are shown in Table 1 below. The column titled “Number of RFs” represents the number of times a particular gene appeared in the RF list. Genes appearing in all four RF repeats suggested that this could be a top candidate marker for distinguishing HNCs from non-cancer samples. Such genes appear at the top of the list with the largest sum of ranks. [Table 1] JPEG2026523253000003.jpg186170

[0153]

[0167] As a complementary technique to RF analysis for identifying differentially expressed genes, the TCGA HNC RNASeq dataset may be used to compare the percentage of overlapping expression versus the fold change in expression (HNC / normal).

[0154]

[0168] For genes with increased HNC expression (upregulated) compared to normal tissue, the percentage of expression overlap can be defined as the percentage of the sample between the 95th percentile of the normal distribution and the 5th percentile of the HNC distribution (see, for example, Figure 6 in U.S. Patent Publication 2019 / 0187143, owned by a common entity). For genes with decreased HNC expression (downregulated) compared to normal tissue, the percentage of expression overlap can be defined as the percentage of the sample between the 95th percentile of the HNC distribution and the 5th percentile of the normal distribution. In certain embodiments, genes with a small percentage of expression overlap may be more suitable for use as a diagnostic marker to distinguish HNCs from non-cancer samples.

[0155]

[0169] In some cases, the median expression level from HNC samples was divided by the median expression level of normal samples for each gene to determine the multiplicative change in expression. Genes with large multiplicative changes in expression may be more suitable as diagnostic markers to distinguish HNCs from non-cancer samples.

[0156]

[0170] The top (e.g., about 10) genes identified from RF analysis, indicated as white circles in Figure 3 and Table 1—SH3BGRL2, CAB39L, HSD17B6, NRG2, GRIN2D, MMP11, GPD1L, DLG2, ADAM12, and IL11—were found to have less than 20% overlap in expression. This further supports the idea that genes with smaller percentages of overlap may be more suitable as diagnostic markers for distinguishing HNCs from non-cancer samples, and also highlights the similarities between these two complementary methods for identifying differentially expressed genes.

[0157]

[0171] The remaining genes (#11-36) identified by RF analysis are shown as white squares in the data representation in Figure 4 (from U.S. Patent Application No. 16 / 224,974, filed December 19, 2018, and published as U.S. Patent No. 2019 / 0187143). In total, 23 of the 36 genes identified by RF analysis (64%) have less than 20% overlap in expression.

[0158]

[0172] A potential benefit of the graphical representation was the identification of additional genes not selected by RF analysis, particularly 45 genes with less than 20% overlap in expression. These 45 genes are listed in Table 2 (also shown as Table 6 in U.S. Patent Publication 2019 / 0187143). They are shown as black circles below the 20% overlap line in Figures 3 and 4. Similar to the genes identified by RF analysis, the expression of these additional genes with less than 20% overlap may be useful as diagnostic markers to distinguish HNCs from non-cancer samples. [Table 2] JPEG2026523253000005.jpg156170

[0159]

[0173] Example 4 - Gene selection in saliva We identified genes whose expression levels were measured from saliva samples from HNC volunteers and healthy volunteers. Twenty-six genes were found whose expression levels were measured by ddPCR in the saliva samples of HNC and healthy volunteers.

[0160]

[0174] We initiated our initial search for salivary biomarkers from genes exhibiting >10-fold changes in expression in the TCGA HNC RNASeq dataset. Therefore, we used the TCGA HNC RNASeq dataset, derived from either HNC or normal tissue, as a predictive model system for saliva. Here, to improve the likelihood of discovering genes with altered expression in saliva, saliva from HNC patients is a mixture of RNA transcripts from both cancerous and normal tissues present in the oral cavity, starting with genes exhibiting relatively high expression and >10-fold changes in the TCGA HNC RNASeq dataset.

[0161]

[0175] As shown in Figure 5, in the TCGA HNC RNASeq dataset, 22 out of 26 genes identified using the TCGA HNC RNASeq dataset were upregulated (positive HNC / normal index), and 4 out of 26 were downregulated (negative HNC / normal index).

[0162]

[0176] Example 5 - Saliva-duplex ddPCR The platform used to measure gene expression from saliva was Bio-Rad droplet digital PCR (ddPCR). Because the Bio-Rad QX200 Droplet Reader can distinguish between two colors, a duplex ddPCR reaction was performed to measure both the gene of interest (i.e., candidate biomarker) labeled with FAM and the housekeeping gene (RPL30) labeled with HEX in a single ddPCR reaction. The results are shown in Figure 6.

[0163]

[0177] The graph at the top of Figure 6 shows the gene expression levels (copies / μL, y-axis) for each saliva sample for the 26 genes measured (x-axis). The dotted line crossing the bottom of both graphs, labeled "No Call," represents ddPCR results from saliva samples that did not produce enough positive droplets to obtain copies / μL. The genes were sorted from those with low to high median expression levels. Expression levels ranged from >18,000 times, 0.12 to 2,279 copies / μL, with median expression levels approximately 300 times, 0.35 to 102 copies / μL.

[0164]

[0178] The graph at the bottom of Figure 6 shows the level of RPL30 (housekeeping gene) expression for each saliva sample from the 26 genes analyzed (x axis), expressed in copies / μL (y axis). In contrast to the distribution from the expression of the individual genes mentioned above, the distribution of RPL30 expression was not significantly different (Kruskal-Wallis p=0.2451).

[0165]

[0179] Normalized ddPCR was the quotient obtained by dividing the gene copies / μL by RPL30 copies / μL for each sample: Normalized ddPCR = (gene - FAM copies / μL) / (RPL20 - HEX copies / μL)

[0166]

[0180] Example 6 - Median of normal expression The median normal expression levels of 26 genes obtained from normalized ddPCR results of saliva from healthy volunteers were compared with those reported in the TCGA HNC RNASeq dataset from normal tissue samples. As shown in Figure 7, a weak positive relationship (R) was observed between gene expression measured from saliva by ddPCR and gene expression measured from oral tissue by RNASeq. 2 It appeared that there was a value of =0.5572.

[0167]

[0181] However, as shown in Table 3, there was a significant difference in expression range (equal to maximum / minimum expression) between the two measurements. The expression range from oral tissue reported in the TCGA HNC RNASeq dataset was 32,734-fold, while the expression range from the same gene measured in saliva by ddPCR was 758-fold, a decrease of >43-fold. These large differences in expression may be due to the fact that the TCGA HNC RNASeq dataset was derived from either HNC tissue or normal tissue, whereas saliva from HNC patients consists of a mixture of RNA transcripts from both cancerous and normal tissues present in the oral cavity. Despite these limitations, the use of the TCGA HNC RNASeq dataset offers utility for predicting gene expression levels in saliva. [Table 3]

[0168]

[0182] Example 7 - Median of the change in expression ratio Figure 8 shows the median change in gene expression levels for each of the 26 genes, calculated separately for early oral cancer (early OC, stage I / II) and late oral cancer (late OC, stage III / IV) using measured saliva samples (left graph) and the TCGA HNC RNASeq dataset (tissue) (right graph).

[0169]

[0183] Many of the genes measured in saliva showed changes in expression of only a small + / - 2-fold or less. Interestingly, the median multiplicative change in expression from a small number of genes (e.g., MMP1, COL1A1, MMP3, GRIN2D, and KRT4) was much larger in late OC compared to early OC. The increased multiplicative change in expression may not be surprising, as late OC samples come from more advanced stages of cancer and likely represent relatively large tumors or multiple sites with cancerous tissue. More importantly, the increased gene expression observed in the saliva of late-stage cancer patients compared to early-stage cancer patients supports a link between these genes and oral cancer.

[0170]

[0184] In contrast to the fold changes observed from saliva, the fold changes in expression from the TCGA HNC RNASeq dataset in tissue samples were far greater, ranging from up to 149-fold for upregulated genes to -1,006-fold for downregulated genes. Notably, the four genes at the far right of the graph (CRISP3, KRT4, MUCH, and MAL), all of which are downregulated in the TCGA HNC RNASeq dataset, showed only one downregulation (MAL) in early OC from saliva. While the TCGA HNC RNASeq dataset suggests a relatively large decrease in expression (-139 to -1,006-fold) for these four genes, a decrease in expression from the same genes in saliva was not readily detected. Again, these differences may be due to the fact that the TCGA HNC RNASeq dataset originated from either HNC tissue or normal tissue, whereas saliva from HNC patients consists of a mixture of RNA transcripts from both cancerous and normal tissues present in the oral cavity.

[0171]

[0185] Example 8 - Normalized ddPCR at low RPL30. One purpose of normalizing gene expression data is to reduce technical variation while preserving biological variation, and plotting normalized ddPCR versus RPL 30 copies / μL was an attempt to evaluate data normalization. The results are shown in Figure 9.

[0172]

[0186] As shown in Figure 9, the solid shaded line represents the calculated copies / μL from one positive droplet out of 20,000 total droplets (intended total number of droplets), the dashed shaded line represents the calculated copies / μL from one positive droplet out of 10,000 total droplets (minimum total number of droplets allowed for copy / μL calculation by QantaSoft software), and the black dots represent the calculated copies / μL from one positive droplet out of the actual number of droplets in the assay well. Assay wells with a total number of droplets close to 20,000 were preferred because increasing the total number of droplets in the assay well improved or decreased the low detection limit.

[0173]

[0187] Of the 26 genes shown, three represent low (MMP3), medium (CDSN), and high (MMP9) gene expression levels in saliva. Many samples from a wide range of RPL30 copies / μL resulted in low expression levels of "No Call" for many genes, e.g., MMP3, GRIN2D, HMGA2, COL5A1, and MMP12 (see Figure 6). A weak positive relationship was observed between the median normal gene expression from the TCGA HNC RNASeq dataset and gene expression measured from saliva by ddPCR (Figure 7), but the detection limit of gene expression from saliva was empirically assessed by ddPCR.

[0174]

[0188] The normalized ddPCR values ​​shown in Figure 9 were the quotient obtained by dividing gene copies / μL by RPL30 copies / μL. Normalized ddPCR results from genes with medium (CDSN) and high (MMP9) expression levels were highest at low RPL30 copies / μL, suggesting overnormalization after division at low RPL30 copies / μL. To minimize overnormalization, normalized ddPCR values ​​obtained at RPL30 copies / μL or less were removed (see Example 8).

[0175]

[0189] Example 9 - RPL30 Cutoff An RPL30 cutoff of <2 copies / μL was established to minimize overnormalization due to low RPL30 copies / μL. The results are shown in Figure 10.

[0176]

[0190] Therefore, as shown in Figure 10, the graph on the left represents the upper and lower 95% confidence intervals (CI) for each RPL30 copy / μL from the entire sample. As seen in the graph and Table 4 below, the range between the upper and lower 95% CIs increased as the RPL30 copy / μL decreased. To help detect small changes in gene expression, accurate measurements are preferred, so an RPL30 cutoff with a range of twice the CI, corresponding to 2 copies / μL, was selected. For RPL30 > 2 copies / μL, the 95% confidence interval range is < 2 times. [Table 4]

[0177]

[0191] In Figure 10, the graph on the right compares the percentage coefficient of variation (%CV) of RPL30 copies / μL from all samples. As the mean RPL30 copies / μL decreased, the variability of the measurements increased dramatically, reaching a maximum of 130%CV at 0.3 copies / μL. In contrast, for samples with RPL30 greater than 2 copies / μL (dashed vertical line), the median CV was 28%, and the CV ranged from 11 to 56%. Based on the wide CI and increasing %CV, samples with RPL30 less than 2 copies / μL were excluded from further analysis. In summary, for RPL30 > 2 copies / μL, the 95% confidence interval range is <2x, and the median %CV is 28% (range 11–56%).

[0178]

[0192] Example 10 - Differences between healthy volunteers and early OC (Oral Consumption). We evaluated the statistical differences between normalized ddPCR expression levels from healthy volunteer saliva compared to saliva from early oral (OC) cancer patients for all genes, using unpaired t-tests and the Wilcox Rank Sum Test. The results are shown in Figure 11 and Table 5. Table 5 lists the genes from the minimum to the maximum p-value from the t-test. We also adjusted the p-values ​​for multiple tests using false detection rate and Bonferroni correction. A p-value less than 0.05 was considered statistically significant. Not applied (NA) indicates genes for which there was insufficient sample size for comparison. [Table 5]

[0179]

[0193] The distribution of normalized ddPCR results for five genes from healthy volunteers (HV) and early oral cancer (OC) patients is also shown (Figure 11). Compared to saliva from healthy volunteers, saliva from early OC patients showed significantly higher levels of expression (t-test p<0.05) for AIM2, CDSN, INHBA, MMP1, and MMP10.

[0180]

[0194] Example 11 - ROC Analysis Receiver operating characteristic (ROC) analysis was used to evaluate the performance of gene expression levels for classifying saliva samples from healthy volunteers or patients with early-stage oral cancer. The results are shown in Figure 12 and Table 6. Table 6 lists genes from maximum to minimum area under the curve (AUC), along with the relevant performance metrics at the optimal cutoff. AUCs with significant p-values ​​(p<0.05) are shown in bold. NA = Genes for which the sample size was insufficient for evaluation. [Table 6]

[0181]

[0195] The ROC curves from genes with significant AUCs are listed in Table 6 and the top six genes are shown in Figure 12. In particular, five genes with statistically different means (t-tests) (i.e., AIM2, CDSN, INHBA, MMP1, and MMP10) were also found to have statistically significant AUCs by ROC analysis. ROC analysis identified one additional gene, MMP9, which had a small but significant AUC (0.6786) but was not identified by the t-test.

[0182]

[0196] Example 12 - ROC analysis - Gene combination. Based on the performance of individual genes, gene expression levels were combined using logistic regression and performance-based analysis, evaluated by ROC analysis. The results are shown in Figure 13 and Table 7. Combined gene expression showed improved performance in classification at larger AUCs than individual genes, particularly in combinations of 3, 4, and 5 genes (Table 6). Relevant performance metrics (sensitivity, specificity, and precision) at the optimal cutoff are listed along with each AUC. [Table 7]

[0183]

[0197] As shown in Figure 13, the ROC curves for combinations of two, three, four, and five genes exhibit the highest AUC from each combination, with each of these gene combinations having a larger AUC than any of the single genes. The gene combination that performed best when determined by the Youden index was observed to be the three-gene combination CDSN+AIM2+MMP1 (Youden index = 0.8750), which yielded an AUC of 0.9412 with a sensitivity of 0.8750 and a specificity of 1.000.

Claims

1. A method for measuring the presence and / or amount of biomarkers associated with head and neck squamous cell carcinoma (HNSCC) in an individual, (a) A step of obtaining a saliva sample from the individual, (b) A method comprising the step of measuring the amount of expression product from at least one gene encoding the biomarker related to HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10.

2. The method according to claim 1, further comprising measuring the expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15.

3. The method according to claim 1, further comprising measuring the expression product from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

4. The method according to claim 1, further comprising measuring the expression product of a housekeeping gene and normalizing the result.

5. A method for identifying individuals at risk of head and neck squamous cell carcinoma (HNSCC), (a) A step of obtaining a saliva sample from the individual, (b) A method comprising the step of measuring the amount of expression product from at least one gene encoding a biomarker related to HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10, and identifying the individual as being at risk of HNSCC due to the presence of altered levels of the expression product compared to a healthy control for the biomarker related to HNSCC.

6. The method according to claim 5, further comprising measuring an expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15.

7. The method according to claim 5, further comprising measuring the expression product from any of the genes shown in Table 1, Table 2, Table 5, or Table 6.

8. The method according to claim 5, further comprising measuring the expression of housekeeping genes and normalizing the results.

9. A method for identifying individuals with head and neck squamous cell carcinoma (HNSCC) and treating such individuals, (a) A step of obtaining a saliva sample from the individual, (b) A step of measuring the altered amount of expression product from at least one gene encoding a biomarker related to HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. (c) A method comprising the step of administering one or more HNSCC treatments to the individual.

10. The method according to claim 9, further comprising measuring an expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15.

11. The method according to claim 9, further comprising measuring the expression product from at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6.

12. The method according to claim 9, further comprising measuring the expression of housekeeping genes and normalizing the results.

13. A method for identifying individuals at risk of head and neck squamous cell carcinoma (HNSCC) and monitoring such individuals, (a) A step of obtaining a saliva sample from the individual, (b) A step of measuring the increased amount of expression product from at least one gene encoding a biomarker related to HNSCC in the saliva sample, wherein the gene comprises at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10. (c) A step of determining that at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 shows altered expression compared to a healthy control, (d) A method comprising the step of repeating steps (a) to (c) at a later point in time to determine whether at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 shows an increased expression of a change compared to a healthy control.

14. The method according to claim 13, further comprising: step (b) measuring the expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15; step (c) determining that at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15 shows altered expression; and step (d) determining whether steps (a) to (c) are repeated at a later point in time to determine whether at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15 shows altered increased expression compared to a healthy control.

15. The method according to claim 13, further comprising: step (b) measuring the expression product from at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6; step (c) determining that at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6 shows altered expression; and step (d) repeating steps (a) to (c) at a later point in time to determine whether at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6 shows altered increased expression compared to a healthy control.

16. The method according to claim 13, further comprising measuring the expression of housekeeping genes and normalizing the results.

17. The method according to any one of claims 1 to 16, wherein the expression product is a protein or mRNA.

18. The method according to claims 1 to 17, wherein the measurement step comprises duplex ddPCR or multiplex ddPCR.

19. The method according to any one of claims 1 to 17, wherein the detection step includes an array of expression products.

20. A kit comprising a reagent for detecting at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10 in saliva, and instructions for use.

21. The kit according to claim 20, further comprising a reagent for detecting an expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15.

22. The kit according to claim 20, further comprising a reagent for detecting an expression product from at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6.

23. The kit according to claim 20, further comprising a reagent for detecting expression products of housekeeping genes for normalizing the results.

24. A composition for detecting or measuring biomarkers associated with head and neck squamous cell carcinoma (HNSCC) in an individual, comprising a reagent for detecting at least one of AIM2, CDSN, INHBA, MMP1, MMP9, or MMP10.

25. The composition according to claim 24, further comprising a reagent for detecting an expression product from at least one of MMP13, CRISP3, MUC21, ADAM12, MMP3, or ISG15.

26. The composition according to claim 24, further comprising a reagent for detecting an expression product from at least one of the genes shown in Table 1, Table 2, Table 5, or Table 6.

27. The composition according to claim 24, further comprising a reagent for detecting expression products of housekeeping genes for normalizing the results.

28. A system for carrying out any or all of the steps of the method according to claims 1 to 19, and / or for using the composition according to any one of claims 24 to 27.

29. A computer program product tangibly embodied in a non-temporary machine-readable storage medium, comprising instructions configured to operate the system described in claim 28 and / or to perform one or more steps of the methods described in claims 1 to 19.

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