US20140329230A1 - Methods for detecting human papillomavirus and providing prognosis for head and neck squamous cell carcinoma - Google Patents

Methods for detecting human papillomavirus and providing prognosis for head and neck squamous cell carcinoma Download PDF

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US20140329230A1
US20140329230A1 US14/358,515 US201214358515A US2014329230A1 US 20140329230 A1 US20140329230 A1 US 20140329230A1 US 201214358515 A US201214358515 A US 201214358515A US 2014329230 A1 US2014329230 A1 US 2014329230A1
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hpv
hnscc
kit
subject
antibody
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Elizabeth Franzmann
Lutecia Pereira
Isildinha M. Reis
Robert C. Duncan
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University of Miami
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/5743—Specifically defined cancers of skin, e.g. melanoma
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G01N33/57488—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving compounds identifable in body fluids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/005—Assays involving biological materials from specific organisms or of a specific nature from viruses
    • G01N2333/01—DNA viruses
    • G01N2333/025—Papovaviridae, e.g. papillomavirus, polyomavirus, SV40, BK virus, JC virus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70585—CD44
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease

Definitions

  • the subject matter disclosed herein generally relates to methods and kits for the detection, treatment, and prognosis of head and neck squamous cell carcinoma.
  • HNSCC Head and neck squamous cell carcinoma
  • HPV human papillomavirus
  • the disclosed subject matter in one aspect, relates to methods and kits for detecting, treating, and providing a prognosis for head and neck squamous cell carcinoma.
  • FIGS. 1A to 1B are graphs showing progression free survival (PFS) ( FIG. 1A ) and overall survival (OS) ( FIG. 1B ) of patients in study.
  • FIG. 1C is a table showing median PFS, and rate of PFS and OS at 12, 24, and 36 months.
  • FIG. 1D is a table showing OS and PFS total, medial, minimum, maximum, mean, and standard deviation.
  • FIGS. 2 A to 2 RR are graphs showing PFS ( FIGS. 2A , 2 C, 2 E, 2 G, 2 I, 2 K, 2 M, 2 O, 2 Q, 2 S, 2 U, 2 W, 2 Y, 2 AA, 2 CC, 2 EE, 2 GG, 2 II, 2 KK, 2 MM, 2 OO, 2 QQ) and OS ( FIGS. 2B , 2 D, 2 F, 2 H, 2 J, 2 L, 2 N, 2 P, 2 R, 2 T, 2 V, 2 X, 2 Z, 2 BB, 2 DD, 2 FF, 2 HH, 2 JJ, 2 LL, 2 NN, 2 PP, 2 RR) in subjects characterized as p16 nuclear vs.
  • FIGS. 2A-2B cytoplasmic/no stain
  • FIGS. 2C-2D solCD44 ⁇ 10 ng/ml vs. ⁇ 10 ng/ml
  • FIGS. 2E-2F solCD44 ⁇ 10 ng/ml vs. ⁇ 10 ng/ml
  • FIGS. 2G-2H total protein ⁇ 1 mg/ml vs. ⁇ 1 mg/ml
  • FIGS. 2I-2J CD44 membrane only/universal staining vs. no staining/other
  • FIGS. 2K-2L EGFR membrane and cytoplasmic staining vs. no staining/other
  • FIGS. 2M-2N EGFR membrane and cytoplasmic vs. other vs. no stain
  • FIGS. 2O-2P EGFR membrane v. cytoplasmic/no stain
  • FIGS. 2Q-2R EGFR membrane vs. cytoplasmic only vs. no stain
  • FIGS. 2S-2T keratinizing vs. non-keratinizing
  • FIGS. 2W-2X current smoker vs. no/former smoker
  • FIGS. 2Y-2Z no alcohol vs. light/moderate alcohol v. heavy alcohol exposure
  • FIGS. 2Y-2Z heavy vs. slight/no alcohol exposure
  • FIGS. 3A-3C are graphs showing that CD44 overexpression increased proliferation ( FIG. 3A ), migration ( FIG. 3B ), and cisplatin resistance ( FIG. 3C ).
  • FIG. 4A is a Western blot from stable clones with down-regulated CD44.
  • FIG. 4B is a graph showing tumor growth inhibition in nude mice for two of the CD44siRNA clones compared to scramble or wild type CAL 27.
  • FIG. 5 contains histology slides showing CD44, EGFR, and pEGFR (Y1068) staining in CAL 27 xenografts after treatment with CD44 siRNA or a scrambled sequence.
  • CD44 downregulation inhibits EGFR expression and its phosphorylation (Y1068) in CAL 27 xenografts.
  • FIG. 6 shows immunohistochemistry (IHC) staining of p16, CD44, and EGFR in p16 ⁇ cancer where p16 staining is cytoplasmic and diffuse.
  • IHC immunohistochemistry
  • FIG. 7 shows IHC staining of p16, CD44, and EGFR in p16 + tumors where nuclei stain strongly for p16 and there is some cytoplasmic staining as well.
  • CD44 membrane staining is lost, only the invading lymphocytes retain CD44 expression.
  • EGFR expression is not seen at all.
  • Ranges can be expressed herein as from “about” one particular value, and/or to “about” another particular value. “About” can mean within 5% of the stated value. When such a range is expressed, another aspect includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another aspect. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. It is also understood that there are a number of values disclosed herein, and that each value is also herein disclosed as “about” that particular value in addition to the value itself.
  • references in the specification and concluding claims to parts by weight of a particular element or component in a composition denotes the weight relationship between the element or component and any other elements or components in the composition or article for which a part by weight is expressed.
  • X and Y are present at a weight ratio of 2:5, and are present in such ratio regardless of whether additional components are comprised in the composition.
  • a weight percent (wt. %) of a component is based on the total weight of the formulation or composition in which the component is included.
  • the term “individual,” “host,” “subject,” and “patient” are used interchangeably to refer to any individual who is the target of diagnosis, prognosis, administration, or treatment.
  • the subject can be a vertebrate, for example, a mammal.
  • the subject can be a human or veterinary patient.
  • a “biomarker” is any gene or protein whose level of expression in a tissue or cell is altered compared to that of a normal or healthy cell or tissue.
  • prognosis is recognized in the art and encompasses predictions about the likely course of disease or disease progression, particularly with respect to likelihood of disease remission, disease relapse, tumor recurrence, metastasis, and death.
  • Good prognosis refers to the likelihood that a patient afflicted with cancer, such as head and neck squamous cell carcinoma, will remain disease-free (i.e., cancer-free).
  • Proor prognosis is intended to mean the likelihood of a relapse or recurrence of the underlying cancer or tumor, metastasis, or death. Cancer patients classified as having a “good outcome” remain free of the underlying cancer or tumor.
  • the time frame for assessing prognosis and outcome is, for example, less than one year, one, two, three, four, five, six, seven, eight, nine, ten, fifteen, twenty or more years.
  • the relevant time for assessing prognosis or disease-free survival time begins with the surgical removal of the tumor or suppression, mitigation, or inhibition of tumor growth.
  • a “good prognosis” refers to the likelihood that a head and neck squamous cell carcinoma patient will remain free of the underlying cancer or tumor for a period of at least five, more particularly, a period of at least ten years.
  • a “bad prognosis” refers to the likelihood that a head and neck squamous cell carcinoma patient will experience disease relapse, tumor recurrence, metastasis, or death within less than five years, more particularly less than ten years. Time frames for assessing prognosis and outcome provided above are illustrative and are not intended to be limiting.
  • treatment refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder.
  • This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder.
  • this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder.
  • antibody refers to natural or synthetic antibodies that selectively bind a target antigen.
  • the term includes polyclonal and monoclonal antibodies.
  • fragments or polymers of those immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules that selectively bind the target antigen are fragments or polymers of those immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules that selectively bind the target antigen.
  • compositions, and components that can be used for, can be used in conjunction with, can be used in preparation for, or are products of the disclosed methods and compositions.
  • materials, compounds, compositions, and components that can be used for, can be used in conjunction with, can be used in preparation for, or are products of the disclosed methods and compositions.
  • These and other materials are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these materials are disclosed that while specific reference of each various individual and collective combinations and permutation of these compounds may not be explicitly disclosed, each is specifically contemplated and described herein. For example, if a composition is disclosed and a number of modifications that can be made to a number of components of the composition are discussed, each and every combination and permutation that are possible are specifically contemplated unless specifically indicated to the contrary.
  • HNSCC head and neck squamous cell carcinoma
  • biomarkers such as CD44 (e.g., soluble CD44 (solCD44)
  • ISD44 soluble CD44
  • U.S. Pat. No. 8,088,591 by Franzmann et al. is incorporated by reference in its entirety for its description of biomarkers that can be used to diagnose and monitor HNSCC in a subject. Elevated levels of these biomarkers are able to distinguish cancer patients from controls with high accuracy and specificity. However, these biomarkers are reduced in certain subject populations despite the presence of HNSCC.
  • solCD44 and total protein levels are more effective at distinguishing HNSCC from controls than either marker alone.
  • solCD44 levels can be lower in subjects with human papillomavirus (HPV) infection.
  • HPV infection is less common. Therefore, inclusion of HPV status in a multivariate analysis can improve sensitivity and accuracy of the assay and allow for detection of HPV + HNSCC.
  • HNSCC risk factors and demographic factors that may be used in the multivariate analysis include tobacco exposure, alcohol exposure, race, ethnicity, dental health, gender, level of education, age, general health, family history of cancer, sexual history and socioeconomic status and using the one or more risk factors or demographic factors in the multivariate analysis to determine the combined score.
  • assays, and methods of using the assays for diagnosis and prognosis involve multivariate analysis of the disclosed biomarkers and risk factors to determine a combined score for an individual subject.
  • the combined score can then be used to determine the presence of HNSCC, or the risk of reoccurrence of HNSCC in a subject.
  • cut-off combined score values can be determined empirically by comparing positive and negative control values.
  • biomarkers described herein include genes and proteins. Such biomarkers include DNA comprising the entire or partial sequence of the nucleic acid sequence encoding the biomarker, or the complement of such a sequence.
  • the biomarker nucleic acids also include RNA comprising the entire or partial sequence of any of the nucleic acid sequences of interest.
  • a biomarker protein is a protein encoded by or corresponding to a DNA biomarker of the invention.
  • a biomarker protein comprises the entire or partial amino acid sequence of any of the biomarker proteins or polypeptides. Fragments and variants of biomarker genes and proteins are also encompassed by the present invention.
  • fragment is intended a portion of the polynucleotide or a portion of the amino acid sequence and hence protein encoded thereby.
  • Polynucleotides that are fragments of a biomarker nucleotide sequence generally comprise at least 10, 15, 20, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 800, 900, 1,000, 1,100, 1,200, 1,300, or 1,400 contiguous nucleotides, or up to the number of nucleotides present in a full-length biomarker polynucleotide disclosed herein.
  • a fragment of a biomarker polynucleotide will generally encode at least 15, 25, 30, 50, 100, 150, 200, or 250 contiguous amino acids, or up to the total number of amino acids present in a full-length biomarker protein of the invention.
  • “Variant” is intended to mean substantially similar sequences. Generally, variants of a particular biomarker of the invention will have at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more sequence identity to that biomarker as determined by sequence alignment programs.
  • biomarkers described herein are genes and proteins whose overexpression correlates with cancer, particularly HNSCC, prognosis.
  • selective overexpression of a biomarker or combination of biomarkers of interest in a patient sample is indicative of a poor cancer prognosis.
  • indicator of a poor prognosis is intended that overexpression of the particular biomarker or combination of biomarkers is associated with an increased likelihood of relapse or recurrence of the underlying cancer or tumor, metastasis, or death, as defined herein above.
  • “indicative of a poor prognosis” may refer to an increased likelihood of relapse or recurrence of the underlying cancer or tumor, metastasis, or death within five years, more particularly ten years. Biomarkers that are indicative of a poor prognosis may be referred to herein as “bad outcome biomarkers.” In other embodiments, the absence of overexpression of a biomarker or combination of biomarkers of interest is indicative of a good prognosis. As used herein, “indicative of a good prognosis” refers to an increased likelihood that the patient will remain cancer-free, as defined herein above. In some embodiments, “indicative of a good prognosis” refers to an increased likelihood that the patient will remain cancer-free for at least five, more particularly at least ten years. Such biomarkers may be referred to as “good outcome biomarkers.”
  • the disclosed biomarkers include genes and/or proteins whose overexpression (compared to a control) correlates with HNSCC prognosis.
  • a gene or protein can be overexpressed by 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 200%, 300%, 400%, 500%, or greater as compared to a control.
  • Biomarkers include genes and proteins that are indicative of a poor HNSCC prognosis (i.e., bad outcome biomarkers) as well as those that are indicative of a good prognosis (i.e., good outcome biomarkers).
  • Biomarkers of particular interest include genes and proteins that are involved in regulation of cell growth and proliferation, cell cycle control, DNA replication and transcription, apoptosis, signal transduction, angiogenesis/lymphogenesis, or metastasis.
  • the biomarkers regulate protease systems involved in tissue remodeling, extracellular matrix degradation, and adjacent tissue invasion.
  • Other biomarkers include regulators of gene expression such as hypermethylation or microRNA.
  • biomarkers are selected from the group consisting of HPV, total protein, and CD44.
  • the CD44 biomarker is solCD44.
  • HPV infection can be determined by measuring HPV directly or indirectly.
  • Three categories of molecular assays are currently available for detection of HPV infection in tissue and exfoliated cell samples. All are based on detection of HPV DNA and include: (1) non-amplified hybridization assays (Southern transfer hybridization, (STH), dot blot hybridization (DB) and in situ hybridization (ISH)); (2) Signal amplified hybridization assays such as hybrid capture assays; and (3) Target amplification assays, such as PCR and in situ PCR.
  • STH Southern blot hybridization
  • DB dot blot hybridization
  • ISH in situ hybridization
  • Signal amplified hybridization assays such as hybrid capture assays
  • Target amplification assays such as PCR and in situ PCR.
  • the viral DNA is amplified in vitro by DNA polymerase to generate adequate amount of target, which is then either directly visualized on gels, or (the more specific approach) detected by specific probe using traditional hybridization methods.
  • the sensitivity of PCR based method is about 10-100 HPV viral genomes in a background of 100 ng cellular DNA. Since PCR can be performed on very small amounts of DNA (10-100 ng), it is ideal for use on specimens with low DNA content.
  • Hybrid capture II assay (Qiagen, Valencia, Calif.).
  • HPV DNAs are hybridized to RNA probes, and RNA-DNA hybrids are captured and detected by a chemiluminescent system.
  • the sensitivity of this assay is similar to that of PCR based assays, with high sensitivity being achieved by signal, rather than target amplification.
  • the current HC II assay has the sensitivity to detect 1 pg HPV (about 50,000 copies) per ml sample. Proper sample collection is essential to achieve maximal sensitivity, and a brush-sampling device has been shown to be optimal.
  • the HC II assay contains synthetic RNA probes complementary to the genomic sequence of 13 high-risk (types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68) and 5 low-risk (6, 11, 42, 43, 44) HPV types.
  • HPV infection may be determined be detecting viral mRNA transcripts or through detection of the cellular protein p16.
  • HPV to cause cancer, persistent infection and a cellular environment that allows for high level expression of viral oncogenes E6 and E7 (initially in the basal cell layer and then throughout the epithelium) is necessary. Therefore, detection of E6/E7 mRNA may identify more clinically significant infection than a DNA approach.
  • Cyclin-dependent kinase inhibitor 2A (CDKN2A, p16 Ink4A , p16) is a cellular correlate of the increased expression of oncogenic E6/E7 mRNA.
  • the main actions of the HPV oncogenes are the degradation of p53 by E6 and thereby the abrogation of apoptosis as well as the release of E2F from pRb that leads to continuous activation of the cell cycle.
  • E2F activation is mediated by phosphorylation of the Rb protein. This pathway is strictly regulated by a set of cyclin dependent kinase inhibitors, among them p16, that block enzymes phosphorylating pRB (cyclin dependent kinases).
  • Epigenetic effects of HPV infection may also be used to detect HPV. Differentially methylated loci between HPV + and HPV ⁇ HNSCC cell lines are described in Sartor M A, et al. Epigenetics 6(6):777-87 (2011), which is incorporated by reference for these epigenetic profiles.
  • HPV infection can be detected using antibodies that specifically bind p16 INK4a .
  • HPV infection can be determined by detecting HPV DNA, RNA, or protein.
  • HPV infection can be determined by detecting viral oncogenes (e.g., E6/E7) or epigenetic changes.
  • These methods each comprise assaying a body sample from the subject for the presence of total protein, solCD44, and HPV.
  • the combination of total protein, HPV, and CD44 levels may be used in a multivariate analysis to determine a combined score.
  • the method may further comprise assaying the body sample for the presence of hyaluronic acid (HA), hyaluronidase (HAase), IL-8, or a combination thereof HNSCC risk factors and/or demographic factors may also be used in combination with total protein, solCD44, and HPV detection to improve sensitivity and/or accuracy of the disclosed method.
  • HA hyaluronic acid
  • HAase hyaluronidase
  • IL-8 IL-8
  • HNSCC risk factors and/or demographic factors may also be used in combination with total protein, solCD44, and HPV detection to improve sensitivity and/or accuracy of the disclosed method.
  • Multivariate analysis is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical outcome variable at a time.
  • regression methods including, but not limited to generalized linear and nonlinear regressions, logistic and Poisson regressions, supervised machine learning algorithms, neural networks, support vector machines, response surface modeling, and multivariate adaptive regression splines.
  • logisitic regression is used.
  • the multivariate analysis can first involve determining how total protein, solCD44, and p16 levels change based on risk variables such as race, gender, smoking and alcohol use.
  • Mathematical models may then be developed whose terms include biomarker levels and the risk variables to predict the probability of cancer. The statistical significance associated with the terms reflect their importance for prediction.
  • a mathematical model may then be used to estimate a predictive score, which allows one to develop an overall probability score of cancer. For example, after having investigated how the marker levels and risk variables (e.g., race, gender, smoking and alcohol use) are associated with the outcome, including interactions, a fitted model can be obtained relating the log-odds of biomarkers and covariates. Based on this model, a score or a predictive probability for having cancer can be estimate at specified values of all variable included in the model.
  • an increase in combined (predictive) score above a cut-off point distinguishes subjects with HNSCC from those without HNSCC or at low risk of future occurrence thereof.
  • an increase in combined score above a cut-off point identifies HNSCC tumor stage, predicts effectiveness of an HNSCC treatment, predicts prognosis of a subject diagnosed with HNSCC, or predicts the risk of HNSCC recurrence.
  • an increase in score above a cut-off point may be associated with a poor prognosis or likelihood of recurrence.
  • the disclosed assays and methods may be used to guide therapeutic treatment of a subject with HNSCC or at risk of developing HNSCC.
  • a subject with a low combined score may be given a single modality treatment such as surgery or radiation alone rather than combined therapy. This would result in decreased treatment-related morbidity.
  • a subject with a high combined score may be offered more aggressive treatments, such as surgery, radiation and chemotherapy, since higher treatment-related morbidity would be warranted given the higher risk of death from the disease. Therefore, the disclosed methods may further comprise treating a subject diagnosed with HNSCC or determined to have a poor HNSCC prognosis, with surgery, radiation therapy, chemotherapy, photodynamic therapy, targeted therapy, or any combination thereof.
  • body sample any sampling of cells, tissues, or bodily fluids in which expression of a biomarker can be detected.
  • body samples include but are not limited to blood, lymph, urine, gynecological fluids, biopsies, and smears.
  • Bodily fluids useful in the present invention include blood, urine, saliva, nipple aspirates, lavages or any other bodily secretion or derivative thereof.
  • Blood can include whole blood, plasma, serum, or any derivative of blood.
  • the body sample comprises oral rinses. Methods for collecting various body samples are well known in the art.
  • the methods are useful in detecting individuals at risk for head and neck cancer, including, for example, smokers, alcohol abusers, and subjects exposed to HPV virus.
  • the methods described herein also permit the enhanced assessment of HNSCC prognosis in comparison to analysis of other known prognostic indicators.
  • the sensitivity and specificity is equal to or greater than that of known cancer prognostic evaluation methods.
  • the endpoint for assessing specificity and sensitivity is comparison of the prognosis or outcome predicted using the methods of the invention (i.e., at or near the time of diagnosis) with the actual clinical outcome (i.e., whether the patient remained cancer-free or suffered a recurrence within a specified time period).
  • sensitivity refers to the level at which a method of the invention can accurately identify samples that are true positives. Sensitivity is calculated in a clinical study by dividing the number of true positives by the sum of true positives and false negatives.
  • the sensitivity of the disclosed methods for the evaluation of HNSCC is at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more.
  • the specificity of the present methods is preferably at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more.
  • the combined sensitivity and specificity value for the prognostic methods of the invention is assessed.
  • combined sensitivity and specificity value is intended the sum of the individual specificity and sensitivity values, as defined herein above.
  • the combined sensitivity and specificity value of the present methods is preferably at least about 105%, 110%, 115%, 120%, 130%, 140%, 150%, 160% or more.
  • true and false positives and negatives will be dependent upon whether the biomarker or combination of biomarkers under consideration are good outcome or bad outcome biomarkers. That is, in the case of good outcome biomarkers (i.e., those indicative of a good prognosis), “true positive” refers to those samples exhibiting overexpression of the biomarker of interest, as determined by a physical exam followed by biopsy. A positive biopsy on pathology can indicate whether a sample is positive or negative.
  • two or more biomarkers are used, more preferably, two or more complementary biomarkers.
  • complementary is intended that detection of the combination of biomarkers in a body sample results in the accurate determination of cancer prognosis in a greater percentage of cases than would be identified if only one of the biomarkers was used.
  • a more accurate determination of cancer prognosis can be made by using at least two of the disclosed biomarkers.
  • detecting expression of biomarkers can be detected on a nucleic acid level or a protein level.
  • detecting expression is intended determining the quantity or presence of a biomarker gene or protein.
  • detecting expression encompasses instances where a biomarker is determined not to be expressed, not to be detectably expressed, expressed at a low level, expressed at a normal level, or overexpressed.
  • the body sample to be examined can be compared with a corresponding sample. For example, a corresponding body sample that originates from a healthy person.
  • the “normal” level of expression is the level of expression of the biomarker in, for example, a sample from a human subject or patient not afflicted with HNSCC.
  • the body sample can also be compared with a corresponding body sample from a subject treated for HNSCC.
  • Such a sample can be present in standardized form.
  • determination of biomarker overexpression requires no comparison between the body sample and a corresponding body sample that originates from a healthy person.
  • detection of overexpression of a biomarker indicative of a poor prognosis in a tumor sample may preclude the need for comparison to a corresponding sample that originates from a healthy person.
  • no expression, underexpression, or normal expression (i.e., the absence of overexpression) of a biomarker or combination of biomarkers of interest provides useful information regarding the prognosis of a patient.
  • Methods for detecting expression of the biomarkers of the invention comprise any methods that determine the quantity or the presence of the biomarkers either at the nucleic acid or protein level. Such methods are well known in the art and include, but are not limited to, lateral flow “test strips,” western blots, northern blots, southern blots, ELISA, immunoprecipitation, immunofluorescence, flow cytometry, immunohistochemistry, nucleic acid hybridization techniques, nucleic acid reverse transcription methods, and nucleic acid amplification methods, for example, PCR.
  • expression of a biomarker is detected on a protein level using, for example, antibodies that are directed against specific biomarker proteins.
  • antibodies can be used in various methods such as Western blot, ELISA, immunoprecipitation, or immunohistochemistry techniques.
  • immunostaining of tissue can be combined with assessment of clinical information, conventional prognostic methods, and expression of molecular markers (e.g., p16 INK4a and solCD44) known in the art. In this manner, the disclosed methods can permit the more accurate determination of HNSCC prognosis.
  • kits for diagnosing a subject with HNSCC or determining the prognosis of a subject with HNSCC can include means for measuring p16 INK4a , solCD44, and/or total protein.
  • the kit can include a plurality of antibodies that specifically bind p16 INK4a .
  • the antibody comprises the idiotype of the E6H4 antibody clone.
  • the kit can further include a detection agent (e.g., secondary antibodies and/or colorimetric agent) for detecting the contained antibodies.
  • the kit can further include a plurality of antibodies that specifically bind CD44 (e.g., solCD44).
  • the kit can further include a reagent for determining total protein concentration in a sample.
  • the kit can also include a reference sample of p16 INK4a and/or solCD44.
  • the kit can additionally include directions for use of the kit (e.g., instructions for diagnosing a subject), a container, and/or a carrier.
  • the kit can contain a computer readable medium or a hyperlink that uses algorithms and reference tables to convert detection values into a combined score.
  • the kit is a lateral flow immunoassay.
  • the kit can comprise a multi-well plate, optionally coated with the antibody that specifically binds p16 INK4a , the antibody that specifically binds CD44, or a combination thereof.
  • the relationship between the test described herein and HPV-related HNSCC was studied by looking at how the markers described herein improve in patients whose tumors are positive for p16 INK4a .
  • Fourteen oropharyngeal cancer subjects were evaluated.
  • the p16 INK4a immunohistochemistry results from their tumor tissue and solCD44 and protein results from their oral rinses were obtained.
  • the solCD44 and protein tests that were measured using the supernatants from oral rinses were combined with p16 INK4a levels detected using the pellets from the same oral rinses.
  • the p16 INK4a protein was quantified using a colorimetric ELISA sandwich technique using microtiter strips coated with the p16 INK4a -specific, monoclonal antibody E6H4TM (Roche mtm laboratories AG) and a second p16 INK4a -specific, monoclonal antibody labeled with HRP. Quantitation was performed by generating a standard curve based on known p16 INK4a levels (Standards 1-6). The levels in test samples were determined by interpolation based on the standard curve. A microtiter plate reader was used to measure absorbance in each well at a wavelength of 450 nm (reference wavelength: 620 nm).
  • p16 INK4a in combination with CD44 and protein was tested in 14 HNSCC patients including patients with oral cavity or oropharyngeal squamous cell carcinoma (CA) or unknown primary carcinomas (UK1 CA).
  • Three healthy volunteers (HV) were also tested (see Table 1).
  • Two patients with low levels of CD44 (cut-off set at 2.7 ng/ml) and protein (cut-off set at 1.0 mg/ml) had p16 INK4a levels above the cut-off of 15 U/ml.
  • CD44 and protein also each identified tumors that were not detected by the other tests.
  • the 3 healthy volunteers that were tested all had levels for each marker below the cut-offs.
  • CD44 and EGFR markers which are associated with poor prognosis were evaluated.
  • p16 the surrogate marker for HPV
  • Nuclear staining with p16 is an effective indicator of HPV infection.
  • SolCD44 levels are higher in HPV ⁇ than HPV + .
  • CD44 interacts has been shown to interact with key tyrosine kinases such as EGFR (the target for cetuximab therapy) to induce growth and migration.
  • EGFR the target for cetuximab therapy
  • the disclosed data in FIG. 5 shows that total EGFR and its phosphorylated form (Y1068) are reduced on CD44-siRNA xenografts indicating that the two molecules are functionally related.
  • solCD44 was evaluated in oral rinses from cancer patients and controls.
  • solCD44 could be detected in oral rinses and could distinguish patients with invasive disease from normal volunteers with a sensitivity of 79% and 100% specificity.
  • a control cohort with a history of tobacco and/or alcohol use and benign disease of the head and neck was developed.
  • the solCD44 ELISA test was shown to have a sensitivity of 62% and specificity of 88% and benign disease was shown not to significantly impact results. Levels of the markers were determined to be lower in subjects with laryngeal/hypopharyngeal tumors which are less frequent and located more distally in the upper aerodigestive tract (UADT).
  • This study used a case-control design to evaluate soluble markers for HNSCC in 150 oropharyngeal and oral cavity HNSCC patients and 150 controls frequency matched for important variables.
  • Table 7 shows an interim analysis of solCD44, log 2 SolCD44 and total protein levels in 132 cases and 124 controls. Cases and controls were successfully frequency matched for age, gender, race and ethnicity (p>0.5). Both solCD44 and total protein levels are significantly elevated.
  • the logistic models in Table 8 are all adjusted for age. The test detected oral cancer best in black males. For black females, the sample size was smaller. There was no significant effect of markers either individually or together, however the corresponding odds ratios were in the same direction as black males.
  • This cohort had the following demographics: mean age was 60.4 years, 16.2% were female, 59.5% were Hispanic, 21.6% were black, 64.9% were current smokers, 50% were heavy drinkers, 57.1% had income less than $10,000 per year.
  • the group's disease characteristics were as follows: 35.1% were oral cavity (OC) and the remainder were oropharyngeal cancers (OP); only 32.4% of subjects were stage III or lower; patients were treated with chemoradiotherapy (43.2%), surgery and chemoradiotherapy (24.3%), surgery alone (13.5%), surgery plus radiation (5.4%), surgery and chemotherapy (2.7%), chemotherapy alone (2.7%) and nothing or the data was missing (5.4%). Nearly 57% recurred or progressed and 43.2% died.
  • tumors Forty-four percent of tumors were p16 + as defined by 50% or more of the tumor cells staining positive for p16.
  • FIG. 6 shows typical p16-IHC staining where staining is cytoplasmic and diffuse.
  • CD44 stains in the membrane and universally throughout the tumor.
  • CD44 and EGFR colocalize on the cell membrane and there is some cytoplasmic staining of EGFR as well.

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