Search

Invasive cervical cancer (ICC) with very low titer of high-risk human papillomavirus (HPV) has worse clinical outcome than cases with high titer, indicating a difference in molecular etiology. Fresh-frozen ICC tumors (n = 49) were classified into high- and low-HPV-titer cases using real-time PCR-based HPV genotyping. The mutation spectra were studied using the AmpliSeq Comprehensive Cancer Panel and the expression profiles using total RNA sequencing, and the results were validated using the AmpliSeq Transcriptome assay. HPV DNA genotyping and RNA sequencing showed that 16.6% of ICC tumors contained very low levels of HPV DNA and HPV transcripts. Tumors with low HPV levels had more mutations with a high allele frequency and fewer mutations with low allele frequency relative to tumors with high HPV titer. A number of genes showed significant expression differences between HPV titer groups, including genes with somatic mutations. Gene ontology and pathway analyses implicated the enrichment of genes involved in DNA replication, cell cycle control and extracellular matrix in tumors with low HPV titer. The results indicate that in low titer tumors, HPVs act as trigger of cancer development whereas somatic mutations are clonally selected and become drivers of the tumor development process. In contrast, in tumors with high HPV titer the expression of HPV oncoproteins plays a major role in tumor development and the many low frequency somatic mutations represent passengers. This putative subdivision of invasive cervical tumors may explain the higher radiosensitivity of ICC tumors with high HPV titer and thereby have consequences for clinical management. [ABSTRACT FROM AUTHOR]

We used a gene-based analysis in a GWAS of cervical cancer in the Swedish population to examine the association of 58 candidate gene/regions that have been reported in hypothesis-driven studies. Only TNF remained statistically significant after correcting for multiple testing.A large number of genetic associations with cervical cancer have been reported in hypothesis-driven candidate gene studies, but most studies have not included an independent replication or the results have been inconsistent between studies. In order to independently validate these associations, we reexamined 58 candidate gene/regions previously reported to be associated with cervical cancer using the gene-based Adaptive Rank Truncated Product test in a genome-wide association study (GWAS) of 1034 cervical cancer patients and 3948 controls from the Swedish population. Of the 58 gene/regions, 8 had a nominal P value < 0.05 [tumor necrosis factor (TNF), P = 5.0 × 10−4; DEAD (Asp-Glu-Ala-Asp) box helicase 1 [DDX1], P = 2.2 × 10−3; exonuclease 1 [EXO1], P = 4.7 × 10−3; excision repair cross-complementing rodent repair deficiency, complementation group 1 [ERCC1], P = 0.020; transmembrane channel-like 6 and 8 genes [TMC6-TMC8], P = 0.023; secreted phosphoprotein 1 [SPP1], P = 0.028; v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2 [ERBB2], P = 0.033 and chloride channel, voltage-sensitive 7 [CLCN7], P = 0.047). After correction for multiple testing, only TNF remained statistically significant (P = 0.028). Two single-nucleotide polymorphisms that are in nearly perfect linkage disequilibrium (rs2857602 and rs2844484) contributed most to the association with TNF. However, they are not independent from the previously reported associations within the MHC region. The very low number of previously reported associations with cervical cancer that replicate in the Swedish population underscore the need to apply more stringent criteria when reporting associations, including the prerequisite of replicating the association as part of the original study. [ABSTRACT FROM AUTHOR]

CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome- (WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server. [ABSTRACT FROM AUTHOR]