The HPV Induced Cancer Resource (THInCR): a Suite of Tools for Investigating HPV-Dependent Human Carcinogenesis

Abstract

Human papillomaviruses (HPVs) are highly infectious and cause the most common sexually transmitted viral infections. They induce hyperproliferation of squamous epithelial tissue, often forming warts. Virally encoded proteins reprogram gene expression and cell growth to create an optimal environment for viral replication. In addition to their normal roles in infection, functional alterations induced by viral proteins establish conditions that frequently contribute to human carcinogenesis. In fact, ~5% of human cancers are caused by HPVs, with virtually all cervical squamous cell carcinomas (CESC) and an increasing number of head and neck squamous cell carcinomas (HNSC) attributed to HPV infection. The Cancer Genome Atlas (TCGA) molecularly characterized thousands of primary human cancer samples in many cancer types, including CESC and HNSC, and created a comprehensive atlas of genomic, epigenomic, and transcriptomic data. This publicly available genome-wide information provides an unprecedented opportunity to expand the knowledge of the role that HPV plays in human carcinogenesis. While many tools exist to mine these data, few, if any, focus on the comparison of HPV-positive cancers with their HPV-negative counterparts or adjacent normal control tissue. We have constructed a suite of web-based tools, The HPV Induced Cancer Resource (THInCR), to utilize TCGA data for research related to HPV-induced CESC and HNSC. These tools allow investigators to gain greater biological and medical insights by exploring the impacts of HPV on cellular gene expression (mRNA and microRNA), altered gene methylation, and associations with patient survival and immune landscape features. These tools are accessible at https://thincr.ca/. IMPORTANCE The suite of analytical tools of THInCR provides the opportunity to investigate the roles that candidate target genes identified in cell lines or other model systems contribute to in actual HPV-dependent human cancers and is based on large-scale TCGA data sets. Expression of target genes, including both mRNA and microRNA, can be correlated with HPV gene expression, epigenetic changes in DNA methylation, patient survival, and numerous immune features, like leukocyte infiltration, interferon gamma response, T cell response, etc. Data from these analyses may immediately provide evidence to validate in vitro observations, reveal insights into mechanisms of virus-mediated alterations in cell growth, behavior, gene expression, and innate and adaptive immunity and may help hypothesis generation for further investigations.

Keywords: DNA methylation; HPV; TCGA; analysis resource; cancer; cervical cancer; correlation; database; gene expression; head and neck cancer; human papillomavirus; methylation; oncogene; survival.

FIG 1

Volcano plots of differentially expressed genes (DEGs) between HPV⁺ and HPV⁻ patients for CESC mRNA (A), HNSC mRNA (B), CESC miRNA (C), and HNSC miRNA (D) TCGA data sets. Each dot represents an individual gene. Genes shaded in blue exhibited a statistically decreased level of expression in HPV16/33/35⁺ cancers. Genes shaded in red exhibited a statistically increased level of expression in HPV⁺ cancers, whereas expression of those indicated in black was not significantly different. Calculations were performed with a false discovery rate (FDR) of 10%.

FIG 2

Spearman correlation coefficient versus negative log of significance for CESC cellular mRNA versus E6 (A) or E7 (B) mRNA levels and for HNSC cellular mRNA versus E6 (C) or E7 (D) mRNA. Only HPV16/33/35⁺ samples were included in these analyses. Genes shaded in red exhibited a statistically increased level of expression in HPV⁺ cancers, whereas expression of those indicated in black was not significantly different. Calculations were performed with an FDR of 10%.

FIG 3

Volcano plots of differentially methylated sites between HPV⁺ and HPV⁻ patients for the CESC (A) and HNSC (B) TCGA data sets. Each dot represents an individual methylation probe from the Infinium HumanMethylation450 BeadChip array. Probes shaded in blue exhibited a statistically decreased level of expression in HPV16/33/35⁺ cancers. Probes shaded in red exhibited a statistically increased level of expression in HPV⁺ cancers, whereas expression of those indicated in black was not significantly different. Calculations were performed with an FDR of 10%.

FIG 4

Example survival curve with 3 comparison groups. Analysis was based on mRNA expression levels of BRCA1-associated RING domain 1 mRNA (BARD1; Gene ID 580), with the gene being differentially regulated between HPV⁺ and HPV⁻ samples for HNSC. This figure was generated natively as part of the THInCR suite, as an example of data output. The HPV16/33/35⁺ samples from the TCGA HNSC cohort were divided into high-, middle-, and low-expressing subsets for Kaplan-Meier survival analysis.

FIG 5

Example of a correlation plot between NSD2/WHSC1 mRNA expression levels and the leukocyte fraction immune landscape feature for the HNSC data set. The figure was generated natively as part of the THInCR suite. Red dots represent HPV16/33/35⁺ HNSC samples, while blue dots represent HPV⁻ HNSC samples. For HPV⁺, R = −0.39, P = 9.3e−4; for HPV⁻, R = −0.078, P = 0.1.