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GenoScape - example of HPV genotype profiling report and visualization. Number, characteristics and percentage of reads that map to thirteen (13) HPV types, human, bacteria and unknown genomes after profiling reads of the clinical sample TrDNA-456 by tiered read mapping.

Scatter plots of HPV 16-L1 methylation in cervical brush (S7a) and urine ccfDNA (S7b). HPV16-L1 qMSP methylation can discriminate bisulfite treated cervical epithelium DNA and urine ccfDNA from patients with normal cytology, from women with dysplastic cytology, and premalignant cervical lesions with high Sensitivity and Specificity.

GenoScape - HPV genotype profiling from high-throughput sequencing samples consists of four analytic steps: (1) High-throughput sequencing (454, MiSeq) of HPV TrDNA; (2) Profiling by comparing sequences against several databases such as Human genome (bowtie), HPV databases -GenBank, PaVE, Enterix-HPV Hi-lo risk (sim4db) and RefSeq bacterial genomes (blast); (3) Assembly into contigs, for AlignScape visualization (newbler,minimus, trinity); and SNP discovery (samtools + filter).

Circulating cell free DNA isolation results.

Primer and probe list of genes used for quantitative Methylation Specific PCR in urine ccfDNA.

Mapping efficiency of cervical cancer cell lines, head and neck squamous cell carcinoma cell lines and clinical samples to HPV16-L1.

Dual Sequence capture of high risk HPV in TrDNA aligned to all high risk HPV types and low risk HPV types from PaVE database.

AlignScape - Pairwise alignment of the HPV16 genome with reads obtained from urine ccfDNA from seven clinical samples: TrDNA-445, TrDNA-455, TrDNA-456, TrDNA-481, TrDNA-504, TrDNA-513, and TrDNA-571. The large-scale HPV DNA server can produce a graphical 'large-scale' view of the pairwise alignments of up to twenty HPV genomes against a reference genome (HPV16 in this demo), together with annotations of genome rearrangement events.

Patient characteristics.

Reads of the HPV positive cervical cancer, head and neck cancer squamous cell carcinoma (HNSCC) cell lines and clinical samples that mapped uniquely to the reference genomes in the PAVE database.

Supplementary Methods.

Phase 1 Biomarker Development Trial to identify genes or clusters of genes that appear to be differentially methylated in cervical cancer biopsy tissues relative to control cervical brush epithelium tissue taken from women seen in the same hospital. The search for cervical cancer screening methylation biomarkers began with preclinical exploratory studies to identify characteristics unique to tumor tissue that might lead to methylated biomarkers for clinical tests that can discriminate cancer from pre-malignant and normal lesions. We used Methylated DNA Immunoprecipitation (MeDIP) and oligonucleotide sequencing arrays (Nimblegen 385K CpG Island Plus Promoter Arrays) to unveil the cervical cancer promoter region methylome (MeDIP-chip). We then used bisulfite sequencing and quantitative Methylation Specific Polymerase Chain Reaction (qMSP) to identify potential biomarkers of progression from normal cervical mucosa epithelium in cervical brush samples from women with abnormal cytology. MeDIP-chip Discovery identified 2,044 differentially methylated probes associated to total of 444 gene loci differentially methylated when comparing tumor and normal samples. Gene loci were subdivided according to two cutoffs defined for the maximal distance between a methylation peak and the TSS: -1000 to +1000, called the standard cut-off; -500 to +500, called the narrow cut-off. We found 255 unique gene loci that are cancer specific methylated according to the standard cutoff and 189 according to the narrow cutoff. More than half of the methylated gene promoters identified with MeDIP-chip (60%) were hypermethylated in all cancer samples and not in normal samples. One hundred and sixty two (162) genes were jointly identified by the intersection between both lists. These stringent criteria ensured that all 10 genes selected for biomarker validation had methylated peaks within a CPG island located in the promoter region, 500 base pairs upstream from the TSS in all the hybridized tumor samples and none in the normal samples hybridized to the arrays. The top three genes in the list that contained CpG islands in their promoter regions FKBP6, ZNF516 and INTS1) were selected for further analysis with MSP and qMSP in Validation and Prevalence cohorts. Samples were tsted for HPV presence using the reverse line blot assay.

Goals and Primary Aims of the five phases of the National Cancer Institue Early Detection Research Network biomarker development trials.

Amplification curves for the HPV TrDNA-qPCR assay on TrDNA from women with Cervical Intraepithelial Neoplasia 1 (CIN1), Cervical Intraepithelial Neoplasia 2-3 (CIN2-3) and women with no Intraepithelial Lesions or Neoplasia (NILM). TrDNA samples were analyzed for high risk HPV DNA using our HPV TrDNA SYBR green qPCR assay. HeLa genomic DNA was included as a positive control. Ct ranges are variable, but are in a similar range as the genomic control. NILM samples did not amplify.

Clinically useful molecular tools to triage women for a biopsy upon referral to colposcopy are not available. We aimed to develop a molecular panel to detect cervical intraepithelial neoplasia (CIN) grade 2 or higher lesions (CIN2+) in women with abnormal cervical cytology and high-risk HPV (HPV+). We tested a biomarker panel in cervical epithelium DNA obtained from 211 women evaluated in a cervical cancer clinic in Chile from 2006 to 2008. Results were verified in a prospective cohort of 107 women evaluated in a high-risk clinic in Puerto Rico from 2013 to 2015. Promoter methylation of ZNF516, FKBP6, and INTS1 discriminated cervical brush samples with CIN2+ lesions from samples with no intraepithelial lesions or malignancy (NILM) with 90% sensitivity, 88.9% specificity, 0.94 area under the curve (AUC), 93.1% positive predictive value (PPV), and 84.2% negative predictive value (NPV). The panel results were verified in liquid-based cervical cytology samples from an independent cohort with 90.9% sensitivity, 60.9% specificity, 0.90 AUC, 52.6% PPV, and 93.3% NPV, after adding HPV16-L1 methylation to the panel. Next-generation sequencing results in HPV+ cultured cells, and urine circulating cell-free DNA (ccfDNA) were used to design assays that show clinical feasibility in a subset (n = 40) of paired plasma (AUC = 0.81) and urine (AUC = 0.86) ccfDNA samples obtained from the prospective cohort. Viral and host DNA methylation panels can be tested in liquid cytology and urine ccfDNA from women referred to colposcopy, to triage CIN2+ lesions for biopsy and inform personalized screening algorithms. Cancer Prev Res; 9(12); 915–24. ©2016 AACR.

Primer and probe list of genes used for quantitative Methylation Specific PCR.

Background HPV-positive oropharyngeal squamous cell carcinomas (OPSCCs) are sensitive to chemo-radiation therapy and have favorable survival outcomes compared with HPV-negative cancers. These tumors are usually not related to tobacco and alcohol exposure. Therefore, it is crucial to diagnose HPV-positive OPSCCs for the appropriate management of the disease, and no suitable markers are available for HPV-positive tumors. In this study, we attempt to find HPV-specific epigenetic biomarkers for OPSCCs. Methods A total of 127 surgical samples were analyzed for HPV positivity and promoter methylation of a panel of genes. HPV detection was performed by PCR detection of HPV E6 and E7 viral oncoproteins. In addition, promoter methylation of a total of 8 genes (DAPK, FHIT, RASSF1A, TIMP3 AGTR1, CSGALNACT2, GULP1 and VGF) was analyzed by quantitative-methylation specific PCR (QMSP), and their associations with HPV positivity or RB/p16 expressions were evaluated. Results AGTR1and FHIT were frequently methylated in HPV positive OPSCC samples with a good area under the curve (AUC over 0.70). In addition, these genes promoter methylation significantly associated with p16 positive and RB negative cases, which were the characteristics of OPSCC cases with favorable survival outcomes. Either of AGTR1and FHIT methylated cases were significantly associated with HPV-positive cancers with 92.0% sensitivity (P AGTR1 and FHIT methylation demonstrated a suitable detection marker of OPSCCs derived from the HPV-infected field, which were familiar with p16-positive and RB-negative phenotypes.

Purpose: To elucidate the role of biological and clinical impact of aberrant promoter hypermethylation (PH) in ovarian cancer (OC).Experimental Design: PH of PGP9.5, HIC1, AIM1, APC, PAK3, MGMT, KIF1A, CCNA1, ESR1, SSBP2, GSTP1, FKBP4 and VGF were assessed by quantitative methylation specific PCR (QMSP) in a training set. We selected two genes (VGF and PGP9.5) for further QMSP analysis in a larger independent validation (IV) set with available clinical data. Biologic relevance of VGF gene was also evaluated.Results: PH frequency for PGP9.5 and VGF were 85% (316/372) and 43% (158/366) respectively in the IV set of samples while no PH was observed in controls. In 372 OC cases with available follow up, PGP9.5 and VGF PH were correlated with better patient survival [Hazard Ratios (HR) for overall survival (OS) were 0.59 (95% Confidence Intervals (CI) = 0.42-0.84, p = 0.004), and 0.73 (95% CI = 0.55-0.97, p = 0.028) respectively, and for disease specific survival (DSS) were 0.57 (95% CI 0.39-0.82, p = 0.003) and 0.72 (95% CI 0.54-0.96, p = 0.027). In multivariate analysis, VGF PH remained an independent prognostic factor for OS (HR 0.61, 95% CI 0.43-0.86, p Conclusions: Our results indicate that VGF and PGP9.5 PH are potential biomarkers for ovarian carcinoma. Confirmatory cohorts with longitudinal follow-up are required in future studies to define the clinical impact of VGF and PGP9.5 PH before clinical application.