Methods and compositions for oral cancer risk

Abstract

The present disclosure relates to methods and compositions for quantitative risk assessment of lesions in the oral cavity. The risk assessment tool may be used at a point-of-care facility. The present disclosure provides methods and compositions for effective risk assessment of life-threatening or irreversible decline human diseases or conditions, including oral cancer.

Description

[0001] Cross-reference to Related Applications

[0002] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 416,804, filed on October 17, 2022, titled "SYSTEM AND METHOD FOR SUSPICIOUS ORAL LESIONS RISK ASSESSMENT" (Attorney Docket No. 015225-005PV1), and U.S. Provisional Patent Application No. 63 / 466,802, filed on May 16, 2023, titled "METHODS AND COMPOSITIONS FOR ORAL CANCER RISK" (Attorney Docket No. 015225-008PV1), both of which are hereby incorporated by reference in their entirety as if fully set forth herein. TECHNICAL FIELD

[0003] The present invention relates to methods and compositions for quantitative, pre-diagnostic, point-of-care oral cancer risk assessment. Oral cancer risk is assessed using the biomarkers p16 and EGFR in whole saliva. A point-of-care device determines biomarker levels and determines risk assessments as well as clinical factors. BACKGROUND OF THE INVENTION

[0004] Oral potentially malignant disorders (OPMDs) are a heterogeneous group of oral mucosal lesions associated with an increased risk of malignant transformation into cancer. These conditions can progress to oral cancer and life-threatening or irreversible debilitating diseases.

[0005] Currently, visual oral examination (VOE) is the conventional method used to identify oral mucosal abnormalities and / or lesions.

[0006] Disadvantages of visual oral examination include a high dependence on the experience of healthcare providers. For example, several OPMD conditions, such as white or red lesions and persistent ulcers, are often indistinguishable by VOE in their clinical manifestations.

[0007] In addition, current adjunctive tools such as toluidine staining and light-based autofluorescence have the disadvantage of lacking the necessary accuracy for disease detection.

[0008] What is needed are methods for detecting and early detecting or assessing the risk of oral potentially malignant disorders.

[0009] There is an urgent need for methods for healthcare providers to assess the risk of OPMD or to diagnose, prognose, and / or monitor oral abnormalities and lesions. There is a need for methods to improve the detection, treatment, and survival rate of oral cancer. There is a need for early diagnosis of the risk of oral cancer to improve treatment and minimize the negative impact of invasive surgical interventions on quality of life. Summary of the Invention

[0010] The present invention provides methods and compositions for quantitatively assessing the risk of lesions in the oral cavity. The risk assessment tool can be used at the point-of-care facility.

[0011] The present disclosure provides methods and compositions for effectively assessing the risk of life-threatening or irreversible debilitating human diseases or conditions, including oral cancer.

[0012] The methods of the present invention can be used with or without a conventional oral visual examination.

[0013] The methods of the present invention can use patient saliva and provide an effective risk assessment of oral cancer.

[0014] In some embodiments, the present invention can utilize a lateral flow-based multiplex biomarker sensor device. Multiple independent biomarkers can be used for testing purposes.

[0015] In certain embodiments, the methods of the present invention can utilize the p16 and EGFR biomarkers.

[0016] Embodiments of the present invention can provide a multi-biomarker, non-invasive, inexpensive, and easy-to-perform point-of-care test method with improved sensitivity and specificity, which represents a breakthrough in the early detection of the risk of oral cancer.

[0017] Embodiments of the present invention include the following:

[0018] A method for assessing the risk level, diagnosing, prognosticating, or treating oral cancer in a subject, the method comprising detecting the level of a biomarker in a saliva sample from the subject; and using the biomarker level in combination with the subject's clinical factors to assess the risk level of oral cancer. Treatment of oral cancer can be based on the assessed risk level, diagnosis, or prognosis. The biomarker can include p16 and EGFR. The oral mucosal abnormality can be an oral lesion, oral cancer, dysplasia, early cancer, or pre-malignant disorder. The oral cancer can be located in any of the lip tissue, gum tissue, jaw tissue, tongue tissue, or oropharyngeal tissue. The above method can be a point-of-care risk assessment test. A sample can be obtained and the method is performed in a point-of-care environment. The method can be performed in a point-of-care environment with a test duration of 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes. The saliva sample can be prepared from filtered whole saliva in a buffer solution. The saliva sample can be stored in a refrigerator for less than 24 hours, or frozen and thawed no more than once. The method can provide early detection of oral cancer or the risk of oral cancer in the subject. Treatment can include any one or more of surgery, therapeutic radiation, chemotherapy, and pharmacotherapy. The method can reduce the need for invasive or debilitating cancer treatments.

[0019] The above method, wherein assessing the risk level, diagnosing, prognosticating, or treating comprises a logical combination of a sensor fusion function and a risk factor function to provide an output.

[0020] The above method, wherein the method is performed after a trained healthcare provider visualizes an oral mucosal abnormality in the subject.

[0021] The above method, wherein the clinical factors include age, gender, alcohol consumption, smoking, and the presence of non-oral diagnosed cancer.

[0022] The above method, wherein assessing the risk level, diagnosing, prognosticating, or treating results in a higher sensitivity, specificity, or predictive value compared to a visual oral examination alone.

[0023] The above method, wherein assessing the risk level, diagnosing, prognosticating, or treating provides a specificity of at least 70%, or at least 80%, or at least 85%.

[0024] The above method, wherein assessing the risk level, diagnosing, prognosticating, or treating provides a sensitivity of at least 70%, or at least 80%, or at least 85%.

[0025] The above method, wherein assessing the risk level, diagnosing, prognosticating, or treating provides a negative or positive predictive value of at least 70%, or at least 80%, or at least 85%, or at least 90%.

[0026] The above method, wherein p16 is detected within a biologically relevant range of 0 to 160 ng / mL, or within the C5 to C95 percentile range of 18.37 to 64.20 ng / mL.

[0027] The above method, wherein EGFR is detected within a biologically relevant range of 0 to 25 ng / mL, or within the C5 to C95 percentile range of 2.43 to 16.50 ng / mL.

[0028] The above method, wherein bilirubin, α-amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses do not cause significant interference.

[0029] The above method, wherein the level of p16 is detected as low when less than 10.5 ng / mL, medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and high when greater than 27.5 ng / mL.

[0030] The above method, wherein the level of EGFR is detected as low when less than 0.75 ng / mL, medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and high when greater than 1.4 ng / mL. The sensor fusion function can be based on the low, medium, or high levels of two lateral flow biomarkers, p16 and EGFR. The risk factor function can be based on the following risk factors: subject age, gender, alcohol consumption, smoking, and the presence of non-oral diagnosed cancer, wherein the risk factor function is determined by logistic regression to provide three risk ranges of low, medium, and high risk. When clinical data is not available, the regression can take the highest value of the risk factors. The output can be a treatment referral based on the logical combination of the sensor fusion function and the risk factor function, wherein the output is one of the following: no treatment referral due to low combined risk; treatment referral decided by the clinician due to medium combined risk; or treatment referral due to medium or high combined risk. The subject can be immediately referred for cancer treatment based on medium or high combined risk.

[0031] The present invention further contemplates a method for diagnosing, prognosticating, or monitoring oral cancer in a subject, the method comprising: measuring the level of a biomarker in a saliva sample from the subject; comparing the level of the biomarker to a reference level based on a control group of the subject; detecting a difference in the level of the biomarker between the subject and the control group; and diagnosing, prognosticating, or monitoring oral cancer in the subject based on the difference. The biomarker may include p16 and EGFR. The oral mucosal abnormality may be an oral lesion, oral cancer, dysplasia, early cancer, or pre-malignant disorder. The oral cancer may be located in any one of the lip tissue, gum tissue, jaw tissue, tongue tissue, or oropharyngeal tissue. The method may be performed in a point-of-care setting, with a test duration of 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes. The saliva sample may be prepared from filtered whole saliva in a buffer solution. The sample may be stored in a refrigerator for less than 24 hours, or frozen and thawed no more than once. The method may provide early detection of oral cancer or the risk of oral cancer in the subject. The method may reduce the need for invasive or debilitating cancer treatments. The control group may include subjects with oral mucosal abnormalities or oral cancer. The level of the biomarker may be determined by steps including: detecting a test line and a control line on a lateral flow substrate; determining the area of each of the test line and the control line and eliminating non-line areas; and measuring the light intensity of the test line and the control line.

[0032] The above method, wherein the diagnosis or prognosis may include a logical combination of a sensor fusion function and a risk factor function to provide an output.

[0033] The above method, wherein the method is performed after a trained healthcare provider visualizes the oral mucosal abnormality of the subject.

[0034] The above method, wherein the diagnosis or prognosis may be based on additional clinical factors including age, gender, alcohol consumption, smoking, and the presence of non-oral diagnosed cancer.

[0035] The above method, wherein the level of the biomarker may be determined by steps including: detecting a test line and a control line on a lateral flow substrate; determining the area of each of the test line and the control line and eliminating non-line areas; and measuring the light intensity of the test line and the control line.

[0036] The above method, wherein the diagnosis or prognosis may result in a higher sensitivity, specificity, or predictive value compared to a visual oral examination alone.

[0037] The above method, wherein the diagnosis or prognosis may provide a specificity of at least 70%, or at least 80%, or at least 85%.

[0038] The above method, wherein the diagnosis or prognosis may provide a sensitivity of at least 70%, or at least 80%, or at least 85%.

[0039] The above method, wherein the diagnosis or prognosis can provide a negative or positive predictive value of at least 70%, or at least 80%, or at least 85%, or at least 90%.

[0040] The above method, wherein p16 can be detected in a biologically relevant range of 0 to 160 ng / mL, or in the C5 to C95 percentile range of 18.37 to 64.20 ng / mL, respectively.

[0041] The above method, wherein EGFR can be detected in a biologically relevant range of 0 to 25 ng / mL, or in the C5 to C95 percentile range of 2.43 to 16.50 ng / mL, respectively.

[0042] The above method, wherein bilirubin, α-amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses do not cause significant interference.

[0043] The above method, wherein the level of p16 can be detected as low when it is less than 10.5 ng / mL, medium when it is greater than 10.5 ng / mL and less than 27.5 ng / mL, and high when it is greater than 27.5 ng / mL.

[0044] The above method, wherein the level of EGFR can be detected as low when it is less than 0.75 ng / mL, medium when it is greater than 0.75 ng / mL and less than 1.4 ng / mL, and high when it is greater than 1.4 ng / mL. The sensor fusion function can be based on two lateral flow biomarker levels: low, medium, or high levels of p16 and low, medium, or high levels of EGFR. The risk factor function can be based on the following risk factors: subject age, gender, alcohol consumption, smoking, and the presence of non-oral diagnosed cancer, wherein the risk factor function is determined by logistic regression to provide three risk ranges of low, medium, and high risk. When clinical data is not available, the regression can take the highest value of the risk factors. The output can be a treatment referral based on the logical combination of the sensor fusion function and the risk factor function, wherein the output is one of the following: no treatment referral due to low combined risk; clinician decides on treatment referral due to medium combined risk; or treatment referral due to medium or high combined risk. The subject can be immediately referred for cancer treatment based on medium or high combined risk.

[0045] The present invention further provides a method for data collection, the method comprising: obtaining a saliva sample from a subject; filtering the saliva sample; adding the filtered saliva to a buffer solution; and measuring the level of a biomarker in the filtered saliva sample. The biomarker may include the proteome p16 and EGFR. The biomarker level may be measured using an optical reader on a lateral flow test strip. The filtration may remove particles in a size range of 1 to 100 microns, or 1 to 10 microns, or 0.1 to 10 microns, or 0.1 to 5 microns, or 0.1 to 2 microns, or 0.1 to 1 micron. The filtration may remove particles having a size greater than about 0.05 microns, or about 0.1 microns, or about 0.2 microns, or about 0.45 microns, or about 1 micron, or about 2 microns, or about 5 microns.

[0046] The above method, wherein the saliva sample is stored in a refrigerator for less than 24 hours, or is frozen and thawed no more than once.

[0047] The above method, wherein the buffer solution is filtered after adding the saliva.

[0048] The above method, wherein the method is carried out in a point-of-care environment, and the test duration is 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes.

[0049] The above method, wherein the biomarker p16 is detected in a biologically relevant range of 0 to 160 ng / mL, or in the C5 to C95 percentile range of 18.37 to 64.20 ng / mL.

[0050] The above method, wherein the biomarker EGFR is detected in a biologically relevant range of 0 to 25 ng / mL, or in the C5 to C95 percentile range of 2.43 to 16.50 ng / mL.

[0051] The above method, wherein the measured biomarker level is accurate even in the presence of any one or more of bilirubin, α - amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses.

[0052] The above method, wherein the level of the biomarker p16 is detected as low when less than 10.5 ng / mL, as medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and as high when greater than 27.5 ng / mL.

[0053] The above method, wherein the level of the biomarker EGFR is detected as low when less than 0.75 ng / mL, as medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and as high when greater than 1.4 ng / mL.

[0054] The above method, wherein the subject presents oral mucosal abnormalities observed by a healthcare provider.

[0055] The above method, wherein the oral mucosal abnormalities are oral lesions, oral cancer, dysplasia, early cancer, or pre-malignant disorders.

[0056] The above method, wherein the oral mucosal abnormalities are located in any one of lip tissue, gingival tissue, jaw tissue, tongue tissue, or oropharyngeal tissue. Description of the Drawings

[0057] Figure 1 Shows the HPLC chromatogram of p16INK4a / CKD2a.

[0058] Figure 2 Shows the HPLC chromatogram of sEGFR.

[0059] Figure 3 Shows the ES-MS of p16INK4a / CKD2a.

[0060] Figure 4 Shows the SDS-PAGE analysis of rhEGFR detection antibody and capture antibody.

[0061] Figure 5 Shows the SDS-PAGE analysis of p16INK4a detection antibody and capture antibody.

[0062] Figure 6 Shows the SDS-PAGE gel of commercial p16INK4A.

[0063] Figure 7 Shows an ELISA sandwich assay demonstrating the binding characteristics (measured at OD450 nm) of EGFR and p16 antigens to matching antibodies. The upper curve shows the result where EGFRAb-1 is bound to the surface of the microtiter plate well and EGFRAb-2 is free in solution to bind to different epitopes of the sEGFR antigen. The lower curve shows that EGFRAb-2 is bound to the surface of the microtiter plate well and EGFRAb-1 is free in solution.

[0064] Figure 8 Shows an ELISA assay of p16 antigen when Abcam-2 is attached to the microtiter plate and Abcam-1 is used as the detection antibody.

[0065] Figure 9 Shows a sensorgram of anti-EGFR mAb (cetuximab) immobilized on the surface of a CM5 chip.

[0066] Figure 10 shows a sensorgram of the sequential binding of rhEGFR to anti-EGFR mAb (cetuximab) conjugated to a CM5 chip, followed by the binding of anti-EGFR mAb (EGFR.l) to a second epitope on rhEGFR, thereby forming a triple-stranded complex (sandwich assay) of two antibodies binding to separate epitopes on the antigen.

[0067] Figure 11 Shows a sensorgram of p16mAb695 immobilized on the surface of a CM5 chip.

[0068] Figure 12 Shows a sensorgram of the sequential binding of p16INK4a to p16mAb695 conjugated to a CM5 chip, followed by the binding of p16mAb961 to a second epitope on p16INK4a, thereby forming a triple-stranded complex (sandwich assay) of two antibodies binding to separate epitopes on the antigen.

[0069] Figure 13 Shows a dose-response curve of different concentrations of p16 incorporated into synthetic saliva.

[0070] Figure 14 Shows a dose-response curve of different concentrations of EGFR incorporated into synthetic saliva.

[0071] Figure 15 Shows a dose-response curve of p16 incorporated into pooled whole human saliva.

[0072] Figure 16 Shows a dose-response curve of EGFR incorporated into pooled whole human saliva.

[0073] Figure 17 Shows a dose-response curve of p16 incorporated into pooled whole human saliva.

[0074] Figure 18 Shows a dose-response curve of EGFR incorporated into pooled whole human saliva.

[0075] Figure 19 Shows the estimated intermediate range of p16 measured when positive and negative pathology-confirmed results overlap.

[0076] Figure 20 Shows the estimated intermediate range of EGFR measured when positive and negative pathology-confirmed results overlap.

[0077] Figure 21 Shows a logic table for combined clinical risk factor (CRF) assessment and sensor fusion assessment.

[0078] Figure 22 Shows the steps of a method for assessing the risk level or diagnosing or prognosticating oral cancer.

[0079] Figure 23 Show steps of a method for evaluating the risk level or diagnosing or prognosing oral cancer.

[0080] Figure 24 Show steps of a method for evaluating the risk level or diagnosing or prognosing oral cancer with early detection.

[0081] Figure 25 Show steps of a method for evaluating the risk level or diagnosing or prognosing and / or treating oral cancer.

[0082] Figure 26 Show steps of a method for diagnosing, prognosing or monitoring oral cancer.

[0083] Figure 27 Show optical detection of the p16 dose of an optical unit using a reader of the present disclosure.

[0084] Figure 28 Show optical detection of the EGFR dose of an optical unit using a reader of the present disclosure.

[0085] Figure 29 Show optical detection of the p16 dose of an optical unit using a reader of the present disclosure.

[0086] Figure 30 Show optical detection of the EGFR dose of an optical unit using a reader of the present disclosure. Detailed Description

[0087] The present invention provides methods and compositions for performing a quantitative risk assessment on a suspicious lesion of the oral cavity. The risk assessment tool can be operated by a healthcare provider at a point-of-care facility, which includes dentists, orthodontists, endodontists, periodontists, and oral healthcare providers such as oral surgeons and oral radiologists, as well as any hospital or radiology department.

[0088] The present disclosure provides methods and compositions for effectively assessing the risk of life-threatening or irreversible debilitating human diseases or conditions, including oral cancer.

[0089] In some embodiments, the methods and compositions of the present invention can be combined with a conventional oral visual examination in a point-of-care facility or clinic of a healthcare provider.

[0090] The subject of the present disclosure can be anyone, or an adult, or an adult with symptoms of oral abnormalities or oral cancer, or an adult with oral abnormalities or oral cancer but without symptoms.

[0091] In additional embodiments, the methods and compositions of the present invention can be used in symptomatic adult patients who may present oral mucosal abnormalities visible to a healthcare provider.

[0092] In certain embodiments, the methods and compositions of the present invention can advantageously provide an effective risk assessment for oral cancer as compared to conventional visual examinations performed by a healthcare provider.

[0093] The methods of the present disclosure can provide simplified and miniaturized point-of-care measurements. The methods disclosed herein can use patient saliva, which allows a healthcare provider to perform an in-chair examination. The methods of the present invention can provide significantly improved pre-diagnostic and diagnostic capabilities.

[0094] In some embodiments, the present invention can utilize a lateral flow-based multiplex biomarker sensor device. The methods of the present invention can use multiple biomarkers for testing purposes. For oral disease detection, the biomarkers can be highly independent of each other.

[0095] In certain embodiments, the methods of the present invention can utilize the p16 and EGFR biomarkers.

[0096] In some aspects, the methods of the present invention can utilize a reader-integrated quantitative risk assessment evaluation device. These methods can be applied to assess the risk due to oral abnormalities or lesions, as well as for the detection of oral diseases. Additionally, these methods can provide a rapid and timely integrated quantitative cancer risk assessment profile during a visit to a healthcare provider.

[0097] In additional aspects, the present invention can generate a multi-parameter biomarker cancer risk assessment signature that is rapidly obtained after the saliva content is dispensed onto a lateral flow device. The time effect of the biomarker antibody and saliva reaction can contain a multi-parameter information vector, which can enable a higher predictability of oral disease risk.

[0098] Embodiments of the present invention can provide a multi-biomarker, non-invasive, inexpensive, and easy-to-perform point-of-care test method with improved sensitivity and specificity, which represents a breakthrough in the early detection of oral cancer risk.

[0099] Evaluating the Risk of Oral Cancer

[0100] In some embodiments, oral cancer risk assessment can include clinical risk factor (CRF) assessment and sensor fusion assessment.

[0101] Clinical risk factor (CRF) assessment can include a multi-parameter regression of several clinical risk factors.

[0102] In some embodiments, the clinical risk factors include age, gender, alcohol consumption, smoking, and the presence of other cancers.

[0103] Oral cancer clinical risk factor assessment can be performed using whole saliva samples from patients with pathologically confirmed positive and negative results. Multiple parameter regression can be used to determine the coefficient of each clinical risk factor. The training and validation steps of the regression can be performed using patient data.

[0104] In some embodiments, the clinical risk factor assessment can provide low, medium, and high oral cancer risk ranges.

[0105] Sensor fusion assessment can include quantitative lateral flow results based on biomarker measurements.

[0106] In some embodiments, the sensor fusion assessment can include measurements of P16 and EGFR biomarkers. The sensor fusion assessment can provide low, medium, or high status of the p16 biomarker. The sensor fusion assessment can provide low, medium, or high status of the EGFR biomarker.

[0107] The biomarkers used in the methods of the present invention can be proteomic biomarkers.

[0108] In a further aspect, oral cancer risk assessment can include a combination of clinical risk factor (CRF) assessment and sensor fusion assessment.

[0109] In certain embodiments, oral cancer risk assessment can include a combination of clinical risk factor (CRF) assessment and sensor fusion assessment, as Figure 21 shown. As Figure 21 shown, a logic table can be used to combine the clinical risk factor (CRF) assessment and sensor fusion assessment to provide a healthcare referral decision.

[0110] In additional embodiments, oral cancer risk assessment can include a combination of clinical risk factor assessment and sensor fusion assessment, where the clinical risk factors each provide a value and the sensor fusion biomarker levels each provide a value for multivariate statistical analysis based on Cox proportional hazards, machine learning, cluster analysis, classification and regression trees, random forests, principal component analysis, curd and whey analysis, discriminant analysis, stepwise regression, logistic regression, neural network analysis, support vector machine analysis, and combinations thereof.

[0111] The present invention contemplates a method as Figure 22 shown. In step S104, risk factors input into a non - transitory storage medium can be obtained and evaluated. In step S106, biomarker levels can be measured and input into the non - transitory storage medium. In step S108, the risk of oral cancer can be determined from the stored risk factors and biomarker levels.

[0112] The present invention further contemplates a method as Figure 23The method shown. In step S202, oral abnormalities of a patient can be observed by a healthcare provider solely through visual examination of the patient. In step S204, risk factors input into a non-transitory storage medium can be obtained and evaluated. In step S206, biomarker levels can be measured and input into the non-transitory storage medium. In step S208, the risk of oral cancer can be determined from the stored risk factors and biomarker levels.

[0113] The present invention also contemplates a method as Figure 24 shown. In step S304, risk factors input into a non-transitory storage medium can be obtained and evaluated. In step S306, biomarker levels can be measured and input into the non-transitory storage medium. In step S308, the risk of oral cancer can be determined from the stored risk factors and biomarker levels, wherein the risk assessment provides early detection of oral cancer either alone or in combination with additional clinical work.

[0114] In addition, the present invention contemplates a method as Figure 25 shown. In step S404, risk factors input into a non-transitory storage medium can be obtained and evaluated. In step S406, the patient's biomarker levels can be measured and input into the non-transitory storage medium. In step S408, the risk of the patient developing oral cancer can be determined from the stored risk factors and biomarker levels. In step S410, the patient's oral cancer or abnormality can be treated. The treatment can include any one or more of surgery, therapeutic radiation, chemotherapy, and drug therapy.

[0115] In additional embodiments, the present invention contemplates a method as Figure 26 shown. In step S506, biomarker levels can be measured and input into the non-transitory storage medium. In step S507, the stored biomarker levels can be compared with a control group for evaluation. In step S509, the difference between the stored biomarker levels and the control group levels can be detected. In step S511, a diagnosis, prognosis, or monitoring of the subject's oral cancer or abnormality can be performed based on the difference.

[0116] In certain embodiments, the present invention additionally includes a method for data collection. The method for data collection can include the patient's biomarker levels. To obtain the patient's biomarker levels, a saliva sample can be collected from the patient. The saliva sample can be added to a buffer solution. Before or after being added to the buffer solution, the saliva sample can be filtered to remove particles of a certain size from the saliva. The patient's biomarker levels can be measured in the filtered saliva sample or the filtered saliva buffer solution.

[0117] In another aspect, filtering saliva or a buffer solution can remove particles in the size range of 1 to 100 microns, or 1 to 10 microns, or 0.1 to 10 microns, or 0.1 to 5 microns, or 0.1 to 2 microns, or 0.1 to 1 micron.

[0118] In an additional aspect, filtering saliva or a buffer solution can remove particles larger than about 0.05 microns, or about 0.1 microns, or about 0.2 microns, or about 0.45 microns, or about 1 micron, or about 2 microns, or about 5 microns.

[0119] Data Collection

[0120] Embodiments of the invention include data collection via an optical reader system (BEVIGILANT Rapid Reader) for lateral flow test strips. The reader can detect the p16 and EGFR biomarkers in the test cassette. The reader can detect biomarkers in low, medium, and high concentration ranges.

[0121] Figure 27 Shows optical detection of the p16 dose in the optical unit using the reader of the present disclosure.

[0122] Figure 28 Shows optical detection of the EGFR dose in the optical unit using the reader of the present disclosure.

[0123] The reader of the present disclosure can provide a p16 test line R of 0.981 2 and an EGFR test line R of 0.98 2 . These values exceed those of known readers.

[0124] Figure 29 Shows optical detection of the p16 dose in the optical unit using the reader of the present disclosure.

[0125] Figure 30 Shows optical detection of the EGFR dose in the optical unit using the reader of the present disclosure.

[0126] In some embodiments, the invention includes a method for data collection, wherein a saliva sample can be obtained from a subject. The saliva sample can be filtered before or after adding it to a buffer solution. The biomarker level can be measured in the filtered saliva sample. In certain embodiments, the biomarker level can be measured on a lateral flow test strip using an optical reader.

[0127] In additional embodiments, the method for data collection can include the following steps:

[0128] Obtaining a saliva sample from a subject;

[0129] Filtering the saliva sample;

[0130] Add the filtered saliva to a buffer solution; and

[0131] Measure the biomarker levels in the filtered saliva sample.

[0132] The saliva sample can be stored in a refrigerator for less than 24 hours, or can be frozen and thawed, preferably no more than once.

[0133] The method for data collection of the present disclosure can be performed in a point-of-care setting. The duration of a complete run of data collection or testing can be 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes.

[0134] In certain embodiments, the biomarker p16 can be detected in a biologically relevant range of 0 to 160 ng / mL, or in the C5 to C95 percentile range of 18.37 to 64.20 ng / mL, respectively.

[0135] In additional embodiments, the biomarker EGFR can be detected in a biologically relevant range of 0 to 25 ng / mL, or in the C5 to C95 percentile range of 2.43 to 16.50 ng / mL, respectively.

[0136] The data collection method of the present disclosure can provide accurate biomarker levels even in the presence of any one or more of bilirubin, α - amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses.

[0137] In some aspects, the biomarker p16 can be detected as low when less than 10.5 ng / mL, as medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and as high when greater than 27.5 ng / mL.

[0138] In additional aspects, the biomarker EGFR can be detected as low when less than 0.75 ng / mL, as medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and as high when greater than 1.4 ng / mL.

[0139] Embodiments of the present invention can utilize subjects presenting oral mucosal abnormalities observed by a healthcare provider. The oral mucosal abnormalities can be oral lesions, oral cancer, dysplasia, early cancer, or pre - malignant disorders. In some embodiments, the oral mucosal abnormalities can be located in any one of lip tissue, gingival tissue, jaw tissue, tongue tissue, or oropharyngeal tissue.

[0140] Ligand Binding Assay

[0141] In some embodiments, a ligand binding assay for the validation of lateral flow reagents is used to ensure consistently robust and consistent assay performance. The ligand binding assay can be enhanced by physicochemical and biophysical characterization of the reagents related to assay performance.

[0142] Analytical techniques such as high performance liquid chromatography - electrospray mass spectrometry (HPLC - ESMS), surface plasmon resonance (SPR), enzyme - linked immunosorbent assay (ELISA), and sodium dodecyl sulfate - polyacrylamide gel electrophoresis (SDS - PAGE) assays can be used to validate and confirm assay reagents.

[0143] In some embodiments, the present invention provides reliable and accurate inter - batch variability for reagents used in lateral flow devices. In such embodiments, the analytical results of antigens and antibodies meet the highest standards of the lateral flow system.

[0144] Device

[0145] Device embodiments useful in the methods of the present invention can be lateral flow devices with a collection device. Examples of collection devices include the SALETTO oral fluid collection device (Porex Life Sciences Institute). The collection device can collect, filter a saliva sample, and deliver it into the lateral flow device.

[0146] Examples of lateral flow devices can be based on the utilization of colorimetric biomarker antibody pairs for each of P16, EGFR, and the control line. The lateral flow device can include a lateral flow immunoassay cartridge and a reader device.

[0147] Devices for the methods of the present invention can provide point - of - care quantitative oral cancer risk assessment. The device can provide pre - diagnostic or diagnostic information.

[0148] The methods of the present invention can be used for symptomatic or asymptomatic adult patients. In some embodiments, the methods of the present invention can be used for symptomatic adult patients with oral mucosal abnormalities. Oral mucosal abnormalities can be visible to a healthcare provider through visual inspection.

[0149] In operation, a device for the methods of the present invention can receive patient data and clinical risk factors. A sample can be collected from the patient using a collection device. The sample can be filtered and combined with a buffer. The sample can be applied to a well on a test cartridge. The test cartridge can be placed in a positioning tray of a reader device. Device operation can be initiated to analyze the sample and provide a test result.

[0150] All publications, including patents, patent application publications, and non - patent publications, mentioned in this specification are hereby expressly incorporated by reference in their entirety for all purposes.

[0151] Although, for purposes of clarity of understanding, the foregoing disclosure has been described in detail by way of example, it will be apparent to those skilled in the art that certain changes and modifications are comprehended by the present disclosure and can be practiced within the scope of the appended claims without undue experimentation, which claims are presented by way of illustration and not limitation. The present invention includes all such additional embodiments, equivalents, and modifications. The present invention includes any combination or mixture of the various illustrative components, examples, and features, materials, elements, or limitations of the claimed embodiments.

[0152] By convention, it is emphasized that the features of the figures have any scale and are intended to cover similar features that can be enlarged or reduced arbitrarily.

[0153] Example

[0154] Example 1: The assessment of the risk of oral cancer by the method of the present invention is significantly superior to conventional oral visual examination.

[0155] Healthcare providers use oral visual examination to detect and characterize suspicious oral lesions. The assessment of the risk of oral cancer by this method does not provide high accuracy.

[0156] A blinded study was performed in multiple dental clinics to evaluate the ability of dentists to determine the risk of patients by oral visual examination of suspicious lesions only.

[0157] The cumulative results of four participating dental clinics based only on visual examination are shown in Table 1.

[0158] Table 1: Cumulative results of dental clinics based only on visual examination

[0159] Presence of the Disease Absence of the Disease Positive 143 71 Negative 63 127

[0160] The study shows that the confidence in risk assessment by visual examination alone is relatively poor. As shown in Table 2, a sensitivity of only up to 69% is achieved by visual examination alone.

[0161] Table 2: Assessment of the risk of oral cancer based only on visual examination

[0162] Visual Inspection Sensitivity 69％ Specificity 64％ Negative Predictive Value 67％ Positive Predictive Value 67％

[0163] In addition, as shown in Table 2, the specificity and predictive value do not exceed 67%.

[0164] In comparison, the compositions and examples of the present invention provide surprisingly improved sensitivity and specificity using the ORAFUSION assay method. As shown in Table 3, the method of the present invention provides surprisingly higher sensitivity, specificity, and predictive value than the conventional assessment based only on visual examination. As shown in Table 3, the method of the present invention achieves a sensitivity of 91%.

[0165] Table 3: Assessment of Oral Cancer Risk by Healthcare Providers Using ORAFUSION

[0166] ORAFUSION Sensitivity 91％ Specificity 88％ Negative Predictive Value 90％ Positive Predictive Value 90％

[0167] In addition, as shown in Table 3, the specificity is 88% and the predictive value is 90%. These results establish the unexpected advantages of the ORAFUSION method of the present invention. In addition, these results validate the designation of the breakthrough status of the method claimed herein by the FDA under the US FD&C Act.

[0168] Example 2: Ligand Binding Assay for Validation of Lateral Flow Reagents.

[0169] Antigens and antibodies were characterized by the following methods: SDS-PAGE, LC-ESMS, ELISA, and SPR (Biacore). SDS-PAGE and LC-MS were used to characterize the molecular weight and purity of the reagents. ELISA and SPR were used to characterize the binding of antigen-antibody complexes. LC and ESMS techniques showed that the purity of the key reagents was sufficient to develop the lateral flow assay. SDS-PAGE showed that these antibodies and reagents for lateral flow development were pure enough to develop the lateral flow immunoassay. The ELISA sandwich assay was used as a screening tool to select the best antibody pair for the lateral flow immunoassay. ELISA tests showed that two antibodies could pair with the same antigen. SPR demonstrated that the antibodies bound to different epitopes on the antigen and that the antibodies were good binding pairs for the antigen.

[0170] High Performance Liquid Chromatography and Electrospray Mass Spectrometry

[0171] High performance liquid chromatography (HPLC) and electrospray mass spectrometry (ESMS) were used for p16INK4a and sEGFR.

[0172] p16INK4a and sEGFR were analyzed by LC-ESMS. As Figure 1As shown, the HPLC analysis of p16INK4a / CDK2a (Peprotech) has three peaks. The first peak is 11.9 %, with a molecular weight (MW) of 16,548 g / mol, the second peak is 87.1 %, with a MW of 16,532 g / mol, and the third peak is 1.0 %, which is too small to be measured by ESMS. The difference between native p16INKA / CDKN2a and the second peak is 16 g / mol. Thus, the LC of p16INK4a shows two peaks of 87.1 % and 11.9 %, which differ only by 16 Da in molecular weight. Such a small change in molecular weight (0.1 %) is not expected to affect the total binding strength of the two antibodies to different epitopes on the antigen. The purity of this commercial antigen can be used for ELISA assays, SPR measurements, and LFIA strip development.

[0173] Figure 2 ES-MS of p16INK4a / CKD2a (Peprotech) is shown.

[0174] Figure 3 The HPLC chromatogram of sEGFR (R&D Systems) is shown and exhibits three peaks. The main peak (C) is 82.5 %, the second peak (B) is 12.4 %, followed by the third peak (A) at 5.1 %.

[0175] The sEGFR protein is too large to be measured by ES-MS. Enzymatic digestion of the sEGFR protein is used to identify representative portions of fragments that align with the EGFR sequence.

[0176] SDS-PAGE Analysis of Antigens and Antibodies

[0177] As used herein, the extracellular domain of the epidermal growth factor receptor is abbreviated as sEGFR. The cetuximab antibody is designated sEGFRmAb-1. The EGFR.1 antibody is designated sEGFRmAb-2. Antibodies against p16INK2a / CDK2a are designated p16mAb-1 and p16 mAb-2.

[0178] According to the manufacturer's instructions, precast gels were used and inserted into a Mini-PROTEAN Tetra electrophoresis cell. All running buffers and sample buffers were made according to the manufacturer's instructions. Proteins were run on two different types of gels: 1. denaturing gels; 2. reducing gels.

[0179] SDS-PAGE analysis of the p16INK4a detection antibody and capture antibody, and the rhEGFR detection antibody and capture antibody was performed using the following added proteins: 1. empty; 2. P16mAb961 (lane 2); 3. P16mAb695 (lane 3); 4. empty; 5. rhEGFR antigen (lane 5); 6. EGFRAb1 (lane 6); and 7. EGFRAb2 (lane). A Peacock molecular weight ladder was used.

[0180] Figure 4 The results of Gel II are shown. The proteins run on the denaturing gel (II) passed through the gel intact. Thus, the molecular weight of the bands indicates the intact molecular weight of the proteins.

[0181] Figure 5 The results of Gel I are shown. The proteins run on the reducing gel passed through the gel (I) as fragments of the intact proteins. The fragments are the portions of the proteins that are joined by disulfide bonds to form the intact proteins.

[0182] Figure 6 The SDS-PAGE gel of p16INK4A is shown. p16INK4A is pure, as shown compared to the faint line on the left (which is the Peacock molecular weight standard marker). The Peacock molecular weight standard marker was placed near the p16INK4a column for comparison (leaked from the ladder well). Only the molecular weights of the bottom three markers were added to the picture, but the ladder molecular weights are the same as the Figure 4 and 5 ladder in.

[0183] Enzyme-Linked Immunosorbent Assay

[0184] A sandwich ELISA was performed to determine the binding of the sEGFR protein to the antibody pairs, namely C225 / Cetuximab (or EGFRAbl) and EGFR.1 (or EGFRAb2). In the first ELISA test, C225 was coated onto the bottom surface of the wells, then the sEGFR protein was added, followed by the monoclonal antibody EGFR.1. The binding curve of this ternary molecule is shown in Figure 7 (upper curve).

[0185] In the second ELISA test, the monoclonal antibody pair was added to the wells in the reverse order. EGFR.1 was first coated onto the bottom of the wells of the microtiter plate, followed by the addition of the sEGFR protein. Once the sEGFR protein had bound to the EGFR.l monoclonal antibody, then the second antibody C225 was added to the wells. The results of this binding curve are shown in Figure 7 (lower curve).

[0186] A sandwich ELISA was performed on the p16 protein, with the Abcam-2 antibody (capture - ab244695) coated on the ELISA plate and Abcam-1 (detection - Ab244961) used as the detection antibody. The results of this binding curve are shown in Figure 8 as follows.

[0187] Surface Plasmon Resonance (SPR) sEGFR Sandwich Assay

[0188] In this study, a sandwich assay was developed using a Biacore SPR instrument to demonstrate the binding of two anti-sEGFR mAbs to a single molecule of sEGFR. The developed sandwich assay demonstrated that the mAbs bind to different epitopes on the antigen surface.

[0189] Figure 9 A sensorgram showing the anti-EGFR mAb (Cetuximab) immobilized on the surface of a CM5 chip is shown.

[0190] Figure 10 shows a sensorgram of the sequential binding of rhEGFR to the anti-EGFR mAb (Cetuximab) immobilized on a CM5 chip, followed by the binding of the anti-EGFR mAb (EGFR.l) to a second epitope on rhEGFR, thus forming a triple-strand of two antibodies binding to separate epitopes on the antigen (standard sandwich assay configuration). This quantitatively shows the combined binding of the antibody to the antigen (rising line) to the equilibrium state (flat line), and finally the binding of the secondary antibody (second rising line) to the equilibrium state. After equilibrium, dissociation of the antigen and secondary antibody from the primary antibody occurs during the regeneration step.

[0191] p16INK4a / mAb SPR Sandwich Assay

[0192] In this study, the measurement of a single molecule of p16INK4a by a pair of anti-p16INK4a / CDK2a mAbs was demonstrated by developing a sandwich assay on the surface of a CM5 chip.

[0193] Figure 11 A sensorgram showing the immobilization of p16mAb695 on the activated surface of a CM5 chip is shown. This sensorgram shows the activation, attraction, and covalent coupling of p16mAb695 to the chip surface, and then the deactivation of the surface. The final height difference between the starting resonance units (RU) and the final RU indicates the degree of immobilization. The binding capacity of the surface depends on the concentration of the immobilized ligand.

[0194] Figure 12 A sensorgram showing the sequential binding of p16INK4a to the antibody p16mAb695 immobilized on a CM5 chip, followed by the sequential binding of the p16mAb961 antibody to a second epitope on the bound p16INK4a antigen, thus forming a triple-strand of a sandwich assay is shown.

[0195] Figure 11 and Figure 12 The sensing maps of Figure 12 demonstrate that a pair of antibodies bind to different molecular surfaces on the antigen. The different surfaces are typically classified as epitopes.

[0196] Example 3: Materials and reagents for lateral flow biomarker strips.

[0197] The components of an embodiment of a lateral flow immunoassay device are shown in Table 4.

[0198] Table 4: Materials and reagents for lateral flow biomarker strips

[0199]

[0200]

[0201] Example 4: Measuring accurate P16 and EGFR biomarker concentrations with synthetic saliva samples.

[0202] The results of this experimental study show that the lateral flow strips for p16 and EGFR are surprisingly reliable when used with synthetic oral fluid.

[0203] This experiment was conducted using synthetic oral fluid (UTAK) as a matrix to determine the limit of detection (LoD) of the biomarkers EGFR and p16. In this process, the biomarkers p16 and EGFR were added to the strips at a concentration 2 times the LoD in synthetic oral fluid.

[0204] Curves were generated by measuring different concentrations of p16 and EGFR added to the lateral flow immunoassay strips. These strips were read on a LUMOS LEELU reader.

[0205] Figure 13 The dose - response curve of p16 incorporated into synthetic saliva is shown. The dose - response curve of p16 was generated using filtered (POREX SALETTO oral fluid collection device) incorporated pooled whole human saliva (n = 3). The biomarker p16 was incorporated into synthetic oral fluid (UTAK), and its measurement range was 0 - 96 ng / mL. The LoD of p16 was determined to be 1.5 ng / mL. In Figure 13 , the solid circles are the data points measured by the reader, and the curve - fitting line was calculated by a four (4) - parameter logistic equation.

[0206] Figure 14Shows the dose - response curve of EGFR incorporated into synthetic saliva. The dose - response curve of EGFR uses filtered (POREX SALETTO oral fluid collection device) (n = 3) incorporated pooled whole human saliva. The antigen EGFR is incorporated into synthetic oral fluid (UTAK), and its measurement range is 0 - 16 ng / mL. The LoD of EGFR was determined to be 1.0 ng / mL. In Figure 14 the solid circles are the data points measured by the reader, and the curve - fitting line is calculated by the four (4) - parameter (a, b, c, d) logistic equation. The %CV (not shown) varies between 10 - 25%.

[0207] The dose - response parameters of the biomarkers p16 and EGFR in synthetic oral fluid obtained by curve - fitting are shown in Table 5.

[0208] Table 5: Dose - response parameters of biomarkers p16 and EGFR

[0209] Antigen a (ng / mL) d (ng / mL) c (ng / mL) b R Square P16 0.01±0.01 0.76±0.13 41.33±13.96 1.11±0.20 0.9959 EGFR 0.0 0.56±0.23 6.56±0.43 1.35±0.04 0.9999

[0210] The regression curves fit the data surprisingly closely, as shown by the R - squared values of 0.9959 and 0.9999 for p16 and EGFR respectively.

[0211] The 5th, 50th, and 95th percentiles of each biomarker were calculated and are shown in Table 6. No hook effect was observed at the concentrations examined. The lateral low bars of EGFR and p16 are within the biologically relevant range. The range of p16 for the C5 to C95 percentile interval is 18.37 to 64.29 ng / mL, which is within the biologically relevant range (0 - 160 ng / mL based on ELISA testing). The concentration of the EGFR biomarker for the C5 to C95 percentile interval is 5.85 to 7.27 ng / mL, which is within the biologically relevant range of EGFR in whole human saliva (0 - 25 ng / mL based on ELISA testing).

[0212] Table 6: Dose - response results of p16 and EGFR in pooled saliva

[0213]

[0214] In another study, the performance characteristics of biomarker measurements based on artificial saliva (synthetic oral fluid, UTAK) are shown in Table 7.

[0215] Table 7: Performance characteristics of biomarker analysis using artificial saliva

[0216]

[0217]

[0218] Example 5: Advantageously eliminates interference and cross-reactivity for the measurement of biomarkers EGFR and P16.

[0219] This example shows the identification and elimination of interference and cross-reactivity of various endogenous and exogenous substances in lateral flow assays for the measurement of biomarkers EGFR and P16.

[0220] Perform interference and cross-reactivity studies to determine biomarker assay specificity in the presence of other substances / reagents in saliva.

[0221] Interference tests are used to observe any attenuation of test line intensity in the presence of interfering substances, which are first mixed with biomarkers p16 and EGFR and then added to oral synthetic fluid (UTAK).

[0222] Cross-reactivity tests are used to observe any reduction in the appearance of test lines when p16 or EGFR is incorporated into synthetic oral fluid (UTAK). Interfering substances are mixed in the synthetic oral fluid.

[0223] Interfering and cross-reacting substances or reagents are any of the following: (a) endogenous substances present in the patient's oral cavity, such as proteins and cellular components, (b) exogenous substances ingested or used by the patient, such as alcohol, toothpaste, and mouthwash, and (c) pathogens that can infect tissues in the patient's oral cavity.

[0224] Arrange lateral immunoassay strips according to the NCX protocol. Cross-reacting substances are diluted in synthetic oral fluid. Interfering substances are diluted in synthetic oral fluid together with antigen P16 or EGFR. Then, the incorporated samples are filtered through a POREX SALETTO oral fluid collection device. Aliquots are mixed with lateral flow running buffer and applied to the strips, and the test line signals are compared with control test lines. The control test lines contain only the biomarker without cross-reacting and interfering substances.

[0225] The tested protein and cellular component substances are: bilirubin, 0.15 mg / mL, α-amylase, 250 μg / mL, human serum albumin (HSA), 15 mg / mL, IgA, 1 mg / mL, lactoferrin, 0.1 mg / mL, and whole blood, 4% v / v. No significant cross-reactivity of any of these substances was observed except for HSA used for EGFR.

[0226] The tested ingested substances are: alcohol, coffee, mouthwash, and toothpaste, all at 6% v / v. No significant interference or cross-reactivity of any of these substances was observed except for coffee interfering with EGFR, mouthwash cross-reacting with P16, and toothpaste interfering with EGFR.

[0227] The test pathogens were: combined bacteria, 10^6 cfu, Candida albicans, 10^6 cfu, and combined virus, 10^5 cfu. No significant interference or cross-reactivity of any of these substances was observed, except that Candida albicans interfered with P16. The combined bacteria were Pseudomonas aeruginosa, Streptococcus mutans, and Eikenella corrodens Z22 (Zeptometrix, Buffalo, NY). The combined virus was cytomegalovirus (CMV) (AD-169), herpes simplex virus (type 1), and Epstein-Barr virus (B95-8).

[0228] For this study, a change in the intensity of the test line of less than 30% compared to the control test line was considered not significant in terms of cross-reactivity and interference. Additionally, if the intensity of the sample test line and the control test line was less than 0.03 arbitrary units (LoD), then these substances were considered not significant in terms of cross-reactivity and interference.

[0229] According to this study, patients should fast for approximately one hour before the test. Patients should not have oral bleeding. There should be no Candida albicans in the patient's mouth during visual inspection.

[0230] Example 6: Measure accurate P16 and EGFR biomarker concentrations using combined frozen-thawed whole human saliva samples.

[0231] This example shows that combined whole human saliva samples can be used to improve the precision of biomarker measurements.

[0232] Collect thawed whole human saliva, combine and spiked with the biomarkers EGFR and p16 to create a dose-response curve. Combining saliva reduces the variability of individual saliva samples. The combined saliva is used as the sample buffer and running buffer for developing the EGFR and p16 lateral flow strips.

[0233] Combine thirty (30) negative whole human saliva samples and spiked with different concentrations of antigen. Combine thirty (30) negative thawed whole human saliva samples and then spiked with different concentration ranges of antigen, p16, and EGFR. Then filter the samples and dilute 1:1 in sample buffer. After dilution, add 100 μL aliquots to the device of the present invention and develop the samples for 20 minutes before reading on a Lumos Leelu reader. The results of absorbance (arbitrary units) are plotted against the spiked concentration of antigen.

[0234] Figure 15 Shows the dose-response curve of p16 spiked into combined whole human saliva and filtered (POREX SALETTO oral fluid collection device) (n = 3).

[0235] Figure 16 The dose - response curves of EGFR incorporated into pooled human saliva and filtered (POREX SALETTO oral fluid collection device) (n = 3) are shown.

[0236] The logistic regression parameters of the non - linear dose - response curves of p16 and EGFR in pooled saliva are given in Table 8. The regression curves fit the data surprisingly closely, as shown by the R - squared values of 0.9977 and 0.9988 for p16 and EGFR, respectively.

[0237] The dose - response parameters of the biomarkers p16 and EGFR incorporated into pooled human saliva obtained by curve fitting are shown in Table 8.

[0238] Table 8: Dose - response of the biomarkers p16 and EGFR incorporated into pooled human saliva

[0239] Antigen a (ng / mL) d (ng / mL) c (ng / mL) b R Square P16 0.001±0.02 0.72±0.14 46.84±18.27 1.14±0.23 0.9977 EGFR 0.007±0.02 1.20±0.20 30.74±13.112 0.90±0.17 0.9988

[0240] The regression curves fit the data surprisingly closely, as shown by the R - squared values of 0.9977 and 0.9988 for p16 and EGFR, respectively. This shows that the measurement of biomarkers in frozen and thawed oral fluid is surprisingly reliable, resulting in unexpectedly high precision. Due to the high precision, even the potential effects of cross - reactivity or interference in lateral flow immunoassays can be determined. Additionally, the shape of the curve shows an accurate relationship between the concentration of the biomarker and its absorbance value.

[0241] The 5th, 50th, and 95th percentiles of each biomarker are calculated and shown in Table 9. The lateral low bars of EGFR and p16 are within the biologically relevant range. The range of p16 in the C5 to C95 percentile interval is 16.82 to 76.86 ng / mL, which is within the biologically relevant range (0 - 160 ng / mL based on ELISA test). The concentration of the EGFR biomarker in the C5 to C95 percentile interval is 9.167 to 52.31 ng / mL, which is within the biologically relevant range of EGFR in pooled human saliva (0 - 25 ng / mL based on ELISA test).

[0242] Table 9: Dose - response results of p16 and EGFR in thawed pooled human saliva

[0243]

[0244] Example 7: Measuring accurate P16 and EGFR biomarker concentrations using pooled fresh saliva samples.

[0245] Fresh human saliva samples were pooled and then spiked with different concentrations of the biomarkers p16 and EGFR. The samples were then filtered and diluted 1:1 in sample buffer. After dilution, 100 μL aliquots were added to the wells of a 96-well plate and the samples were developed for 20 minutes before reading on a Lumos Labs reader. The results of absorbance (arbitrary units) were plotted against the spiked concentration of the antigen.

[0246] Figure 17 Shows the dose-response curve of p16 incorporated into pooled human saliva that was filtered (POREX SALETTO oral fluid collection device) (n = 2).

[0247] Figure 18 Shows the dose-response curve of EGFR incorporated into pooled human saliva that was filtered (POREX SALETTO oral fluid collection device) (n = 2).

[0248] Figure 17 The curve fits of the data in are shown in Table 10.

[0249] Table 10: Dose responses of p16 and EGFR incorporated into fresh pooled human saliva

[0250] Antigen a (ng / mL) d (ng / mL) c (ng / mL) b R Square P16 45.1±43.1 3500±271 46.7±4.78 1.81±0.20 0.9989 EGFR 39.8±117 7210±1960 9.46±4.25 1.28±0.32 0.9988

[0251] The regression curves fit the data surprisingly well, as shown by the R-squared values of 0.9989 and 0.9988 for p16 and EGFR, respectively. This shows that biomarker measurements in fresh oral fluid are surprisingly reliable, resulting in unexpectedly high precision. Due to the high precision, even the potential effects of cross-reactivity or interference in lateral flow immunoassays can be determined. Additionally, the shape of the curve shows an accurate relationship between the concentration of the biomarker and its absorbance value.

[0252] The 5th, 50th, and 95th percentiles were calculated for each biomarker and are shown in Table 11. The lateral low bars for EGFR and p16 are within the biologically relevant range. The range of p16 for the C5 to C95 percentile interval is 38.81 to 54.53 ng / mL, which is within the biologically relevant range (0 - 160 ng / mL based on ELISA testing). The concentration of the EGFR biomarker for the C5 to C95 percentile interval is 2.26 to 16.49 ng / mL, which is within the biologically relevant range of EGFR in human saliva (0 - 25 ng / mL based on ELISA testing).

[0253] Table 11: Dose response results of p16 and EGFR in fresh pooled human saliva

[0254]

[0255] The fitting constant c is used to determine the C95, C50, and C5 percentiles. According to the Clinical and Laboratory Standards Institute (CLSI) EP17-A12 instructions, the fitting constant a is used to determine the limit of blank (LOB) and limit of detection (LOD).

[0256] At the concentrations examined, no hook effect was observed.

[0257] By comparison, the C50 values of p16 in frozen and fresh pooled human saliva were nearly identical, 46.8 and 46.7, respectively.

[0258] By comparison, the C50 values of EGFR in frozen and fresh pooled human saliva were significantly different, 30.7 and 9.5, respectively.

[0259] Example 8: The clinical performance characteristics for assessing oral cancer risk using the method of the present invention are highly accurate.

[0260] In another study, the likelihood ratios of tests based on the method of the present invention were surprisingly high, indicating a high degree of accuracy in the assessment of oral cancer risk.

[0261] For this study, the likelihood ratio was determined based on sensitivity / (1 - specificity). The clinical performance characteristics of the salivary biomarker measurements are shown in Table 12. As shown in Table 12, the likelihood ratios are very high, indicating a high degree of accuracy in the assessment of oral cancer risk.

[0262] Table 12: Clinical performance characteristics of biomarker measurements

[0263] Clinical Manifestation Characteristics P16 EGFR Threshold 8 - 15 ng / ml 0.7 - 1.0 ng / ml Sensitivity 88％ 92％ Specificity 92％ 100％ Positive Predictive Value 90％ 100％ Negative Predictive Value 91％ 94％ Likelihood Ratio 12 >100 Expected Value of the Normal Population 7.7 ng / ml 0.2 ng / ml Expected Value of the Affected Population 60.9 ng / ml 3.6 ng / ml

[0264] Example 9: Using the freeze-thawed pooled human saliva, the lateral flow immunoassay method of the present invention for assessing oral cancer risk achieves high sensitivity and specificity.

[0265] This example shows that the lateral flow immunoassay (LFIA) uses the concentrations of biomarkers P16 and EGFR to accurately provide positive and negative oral cancer risk readings. The stratification of oral cancer risk biomarker values was confirmed by comparing the measured values of pooled human saliva samples with ELISA measurements and ANOVA analysis.

[0266] In a blinded study, the biomarker concentration cut-off values for determining moderate oral cancer risk stratification and the estimated clinical sensitivity and specificity results of biomarkers p16 and EGFR in pooled human saliva were determined. The blinded study provided 50 positive results and 67 negative results. For values above the upper cut-off, high risk will be indicated, meaning a positive reading, and for values below the lower cut-off, low risk will be indicated, meaning a negative reading.

[0267] As Figure 19 shown, for biomarker P16, the cut-off levels for intermediate risk are 10.5 ng / ml and 27.5 ng / ml. The estimated sensitivity is 94%, and the estimated specificity is 100%. The estimated specificity meets the acceptance criteria of more than 90%.

[0268] As Figure 20 shown, for biomarker EGFR, the cut-off levels for intermediate risk are 0.75 ng / ml and 1.4 ng / ml. The estimated sensitivity is 92%, and the estimated specificity is 100%. The estimated specificity meets the acceptance criteria of more than 90%.

[0269] Compared with any conventional parameters, these results are unexpectedly favorable for determining the risk of oral cancer.

[0270] In Figure 19 and Figure 20 , the low region only contains negative results that match the pathological findings. The intermediate region includes the range of individual ELISA results where positive and negative pathological confirmation results overlap. The high range only contains positive results that match the pathological findings.

[0271] Example 10: Freeze-thaw and refrigerated stability of saliva samples.

[0272] Saliva sample degradation and stability studies were performed, and the effects of freeze-thaw and refrigeration cycles on the measured concentrations of biomarkers p16 and EGFR were demonstrated. Slight degradation was observed in samples stored in the refrigerator for more than 24 hours or samples that underwent more than one freeze-thaw cycle. Based on the concentrations of p16, EGFR, α-amylase, and lysozyme, slight sample degradation was observed.

[0273] For one freeze-thaw cycle, P16 was found to retain 85% strength (41.8 / 48.9, in ng / mL).

[0274] For one freeze-thaw cycle, EGFR was found to retain 88% of its strength (2.2 / 2.5, in ng / mL).

Claims

1. A method for assessing the risk level, diagnosing, prognosticating or treating oral cancer in a subject, the method comprising: detecting a biomarker level in a saliva sample from the subject; and using the biomarker level, in combination with the subject's clinical factors, to assess the risk level of the oral cancer.

2. The method according to claim 1, comprising treating the oral cancer based on the assessed risk level, diagnosis or prognosis.

3. The method according to claim 1, wherein the biomarker comprises p16 and EGFR.

4. The method according to any one of claims 1, wherein the oral mucosal abnormality is an oral lesion, oral cancer, dysplasia, early cancer or pre-malignant disorder.

5. The method according to claim 1, wherein the oral cancer is located in any one of lip tissue, gingival tissue, jaw tissue, tongue tissue or oropharyngeal tissue.

6. The method according to claim 1, wherein the method is a point-of-care risk assessment test.

7. The method according to claim 1, wherein the sample is obtained and the method is performed in a point-of-care setting.

8. The method according to claim 1, wherein the method is performed in a point-of-care setting, with a test duration of 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes.

9. The method according to claim 1, wherein the saliva sample is prepared from filtered whole saliva in a buffer solution.

10. The method according to claim 1, wherein the saliva sample is stored in a refrigerator for less than 24 hours, or is frozen and thawed no more than once.

11. The method according to claim 1, wherein the method provides early detection of oral cancer or the risk of oral cancer in a subject.

12. The method according to claim 1, wherein the treatment is any one or more of surgery, therapeutic radiation, chemotherapy and pharmacotherapy.

13. The method according to claim 1, wherein the method reduces the need for invasive or debilitating cancer treatments.

14. The method according to any one of claims 1 - 13, wherein the assessing the risk level, diagnosing, prognosticating or treating comprises a logical combination of a sensor fusion function and a risk factor function to provide an output.

15. The method according to any one of claims 1 - 13, wherein the method is performed after a trained healthcare provider visualizes an oral mucosal abnormality of the subject.

16. The method according to any one of claims 1 - 13, wherein the clinical factors include age, gender, alcohol consumption, smoking and the presence of non-oral diagnosed cancer.

17. The method according to any one of claims 1 - 13, wherein the assessing the risk level, diagnosing, prognosticating or treating results in a higher sensitivity, specificity or predictive value compared to a visual oral examination alone.

18. The method according to any one of claims 1 - 13, wherein the assessing the risk level, diagnosing, prognosticating or treating provides a specificity of at least 70%, or at least 80%, or at least 85%.

19. The method according to any one of claims 1 - 13, wherein the assessing of the risk level, diagnosis, prognosis or treatment provides a sensitivity of at least 70%, or at least 80%, or at least 85%.

20. The method according to any one of claims 1 - 13, wherein the assessing of the risk level, diagnosis, prognosis or treatment provides a negative or positive predictive value of at least 70%, or at least 80%, or at least 85%, or at least 90%.

21. The method according to any one of claims 1 - 13, wherein p16 is detected in a biologically relevant range from 0 to 160 ng / mL, or in a range from the 5th to the 95th percentile from 18.37 to 64.20 ng / mL.

22. The method according to any one of claims 1 - 13, wherein EGFR is detected in a biologically relevant range from 0 to 25 ng / mL, or in a range from the 5th to the 95th percentile from 2.43 to 16.50 ng / mL.

23. The method according to any one of claims 1 - 13, wherein bilirubin, α - amylase, IgA, lactoferrin, whole blood, mixed common bacteria or mixed common viruses do not cause significant interference.

24. The method according to any one of claims 1 - 13, wherein the level of p16 is detected as low when less than 10.5 ng / mL, medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and high when greater than 27.5 ng / mL.

25. The method according to any one of claims 1 - 13, wherein the level of EGFR is detected as low when less than 0.75 ng / mL, medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and high when greater than 1.4 ng / mL.

26. The method according to claim 14, wherein the sensor fusion function is based on two lateral flow biomarker levels, the low, medium or high level of p16 and the low, medium or high level of EGFR.

27. The method according to claim 14, wherein the risk factor function is based on the following risk factors: subject age, gender, alcohol consumption, smoking and the presence of non - oral diagnosed cancer, wherein the risk factor function is determined by logistic regression to provide three risk ranges of low, medium and high risk.

28. The method according to claim 27, wherein when the clinical data is not available, the regression takes the highest value of the risk factors.

29. The method according to claim 14, wherein the output is a treatment referral based on the logical combination of the sensor fusion function and the risk factor function, and the output is one of the following: No treatment referral due to low combined risk; Treatment referral is decided by the clinician due to medium combined risk; or Treatment referral due to medium or high combined risk.

30. The method according to claim 29, wherein the subject is immediately referred for cancer treatment based on medium or high combined risk.

31. A method for diagnosing, prognosing or monitoring oral cancer in a subject, the method comprising: Measuring the level of a biomarker in a saliva sample from the subject; Comparing the level of the biomarker with a reference level of a control group based on the subject; Detecting a difference in the level of the biomarker between the subject and the control group; Diagnosing, prognosing or monitoring the oral cancer of the subject based on the difference.

32. The method according to claim 31, wherein the biomarker comprises p16 and EGFR.

33. The method according to claim 31, wherein the oral mucosal abnormality is an oral lesion, oral cancer, dysplasia, early cancer or pre-malignant disorder.

34. The method according to claim 31, wherein the oral cancer is located in any one of lip tissue, gingival tissue, jaw tissue, tongue tissue or oropharyngeal tissue.

35. The method according to claim 31, wherein the method is performed in a point-of-care setting, and the test duration is 3 - 5 minutes, or 5 - 50 minutes, or about 20 minutes.

36. The method according to claim 31, wherein the saliva sample is prepared from filtered whole saliva in a buffer solution.

37. The method according to claim 31, wherein the sample is stored in a refrigerator for less than 24 hours, or frozen and thawed no more than once.

38. The method according to claim 31, wherein the method provides early detection of oral cancer or the risk of oral cancer in a subject.

39. The method according to claim 31, wherein the method reduces the need for invasive or debilitating cancer treatment.

40. The method according to claim 31, wherein the control group comprises subjects with oral mucosal abnormalities or oral cancer.

41. The method according to claim 31, wherein the biomarker level is determined by the steps comprising: Detecting a test line and a control line on a lateral flow substrate; Determining the area of each of the test line and the control line and eliminating non-line areas; and Measuring the light intensity of the test line and the control line.

42. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis comprises a logical combination of a sensor fusion function and a risk factor function to provide an output.

43. The method according to any one of claims 31 - 41, wherein the method is performed after a trained healthcare provider visualizes an oral mucosal abnormality of the subject.

44. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis is based on additional clinical factors including age, gender, alcohol consumption, smoking and the presence of non-oral diagnosed cancer.

45. The method according to any one of claims 31 - 41, wherein the biomarker level is determined by the steps comprising: Detecting a test line and a control line on a lateral flow substrate; Determining the area of each of the test line and the control line and eliminating non-line areas; and Measuring the light intensity of the test line and the control line.

46. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis results in a higher sensitivity, specificity, or predictive value compared to a visual oral examination alone.

47. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis provides a specificity of at least 70%, or at least 80%, or at least 85%.

48. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis provides a sensitivity of at least 70%, or at least 80%, or at least 85%.

49. The method according to any one of claims 31 - 41, wherein the diagnosis or prognosis provides a negative or positive predictive value of at least 70%, or at least 80%, or at least 85%, or at least 90%.

50. The method according to any one of claims 31 - 41, wherein p16 is detected within a biologically relevant range of 0 to 160 ng / mL, or within the C5 to C95 percentile range of 18.37 to 64.20 ng / mL.

51. The method according to any one of claims 31 - 41, wherein EGFR is detected within a biologically relevant range of 0 to 25 ng / mL, or within the C5 to C95 percentile range of 2.43 to 16.50 ng / mL.

52. The method according to any one of claims 31 - 41, wherein bilirubin, α - amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses do not cause significant interference.

53. The method according to any one of claims 31 - 41, wherein the level of p16 is detected as low when less than 10.5 ng / mL, medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and high when greater than 27.5 ng / mL.

54. The method according to any one of claims 31 - 41, wherein the level of EGFR is detected as low when less than 0.75 ng / mL, medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and high when greater than 1.4 ng / mL.

55. The method according to claim 42, wherein the sensor fusion function is based on two lateral flow biomarker levels, the low, medium, or high level of p16, and the low, medium, or high level of EGFR.

56. The method according to claim 42, wherein the risk factor function is based on the following risk factors: subject age, gender, alcohol consumption, smoking, and the presence of non - oral diagnosed cancer, wherein the risk factor function is determined by logistic regression to provide three risk ranges of low, medium, and high risk.

57. The method according to claim 56, wherein when the clinical data is not available, the regression takes the highest value of the risk factors.

58. The method according to claim 42, wherein the output is a treatment referral based on the logical combination of the sensor fusion function and the risk factor function, wherein the output is one of the following: No treatment referral due to low combined risk; Due to moderate combined risk, the clinician decides on a treatment referral; or Treatment referral due to moderate or high combined risk.

59. The method according to claim 58, wherein the subject is immediately referred for cancer treatment based on moderate or high combined risk.

60. A method for data collection, the method comprising: Obtaining a saliva sample from a subject; Filtering the saliva sample; Adding the filtered saliva to a buffer solution; And Measuring the biomarker levels in the filtered saliva sample.

61. The method according to claim 60, wherein the biomarker comprises the proteome p16 and EGFR.

62. The method according to any one of claims 60-61, wherein the biomarker levels are measured on a lateral flow test strip using an optical reader.

63. The method according to any one of claims 60-62, wherein the filtration removes particles in the size range of 1 to 100 microns, or 1 to 10 microns, or 0.1 to 10 microns, or 0.1 to 5 microns, or 0.1 to 2 microns, or 0.1 to 1 micron.

64. The method according to any one of claims 60-62, wherein the filtration removes particles larger than about 0.05 microns, or about 0.1 microns, or about 0.2 microns, or about 0.45 microns, or about 1 micron, or about 2 microns, or about 5 microns.

65. The method according to any one of claims 60-64, wherein the saliva sample is stored in a refrigerator for less than 24 hours, or is frozen and thawed no more than once.

66. The method according to any one of claims 60-65, wherein the buffer solution is filtered after adding the saliva.

67. The method according to any one of claims 60-66, wherein the method is performed in a point-of-care setting for a duration of 3-5 minutes, or 5-50 minutes, or about 20 minutes.

68. The method according to any one of claims 60-67, wherein the biomarker p16 is detected in a biologically relevant range of 0 to 160 ng / mL, or in the C5 to C95 percentile range of 18.37 to 64.20 ng / mL.

69. The method according to any one of claims 60-67, wherein the biomarker EGFR is detected in a biologically relevant range of 0 to 25 ng / mL, or in the C5 to C95 percentile range of 2.43 to 16.50 ng / mL.

70. The method according to any one of claims 60-67, wherein the measured biomarker levels are accurate even in the presence of any one or more of bilirubin, α-amylase, IgA, lactoferrin, whole blood, mixed common bacteria, or mixed common viruses.

71. The method according to any one of claims 60-67, wherein the level of biomarker p16 is detected as low when less than 10.5 ng / mL, detected as medium when greater than 10.5 ng / mL and less than 27.5 ng / mL, and detected as high when greater than 27.5 ng / mL.

72. The method according to any one of claims 60-67, wherein the level of biomarker EGFR is detected as low when less than 0.75 ng / mL, detected as medium when greater than 0.75 ng / mL and less than 1.4 ng / mL, and detected as high when greater than 1.4 ng / mL.

73. The method according to any one of claims 60-72, wherein the subject presents oral mucosal abnormalities observed by a healthcare provider.

74. The method according to claim 73, wherein the oral mucosal abnormalities are oral lesions, oral cancer, dysplasia, early cancer or pre-malignant disorders.

75. The method according to claim 73, wherein the oral mucosal abnormalities are located in any one of lip tissue, gum tissue, jaw tissue, tongue tissue or oropharyngeal tissue.

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