Genetic variation within the human papillomavirus type 16 genome is associated with oropharyngeal cancer prognosis.

PURPOSE: A significant barrier to adoption of de-escalated treatment protocols for human papillomavirus-driven oropharyngeal cancer (HPV-OPC) is that few predictors of poor prognosis exist. We conducted the first large whole-genome sequencing (WGS) study to characterize the genetic variation of the HPV type 16 (HPV16) genome and to evaluate its association with HPV-OPC patient survival. PATIENTS AND METHODS: A total of 460 OPC tumor specimens from two large United States medical centers (1980-2017) underwent HPV16 whole-genome sequencing. Site-specific variable positions [single nucleotide polymorphisms (SNPs)] across the HPV16 genome were identified. Cox proportional hazards model estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival by HPV16 SNPs. Harrell C-index and time-dependent positive predictive value (PPV) curves and areas under the PPV curves were used to evaluate the predictive accuracy of HPV16 SNPs for overall survival. RESULTS: A total of 384 OPC tumor specimens (83.48%) passed quality control filters with sufficient depth and coverage of HPV16 genome sequencing to be analyzed. Some 284 HPV16 SNPs with a minor allele frequency ≥1% were identified. Eight HPV16 SNPs were significantly associated with worse survival after false discovery rate correction (individual prevalence: 1.0%-5.5%; combined prevalence: 15.10%); E1 gene position 1053 [HR for overall survival (HRos): 3.75, 95% CI 1.77-7.95; Pfdr = 0.0099]; L2 gene positions 4410 (HRos: 5.32, 95% CI 1.91-14.81; Pfdr = 0.0120), 4539 (HRos: 6.54, 95% CI 2.03-21.08; Pfdr = 0.0117); 5050 (HRos: 6.53, 95% CI 2.34-18.24; Pfdr = 0.0030), and 5254 (HRos: 7.76, 95% CI 2.41-24.98; Pfdr = 0.0030); and L1 gene positions 5962 (HRos: 4.40, 95% CI 1.88-10.31; Pfdr = 0.0110) and 6025 (HRos: 5.71, 95% CI 2.43-13.41; Pfdr = 0.0008) and position 7173 within the upstream regulatory region (HRos: 9.90, 95% CI 3.05-32.12; Pfdr = 0.0007). Median survival time for patients with ≥1 high-risk HPV16 SNPs was 3.96 years compared with 18.67 years for patients without a high-risk SNP; log-rank test P < 0.001. HPV16 SNPs significantly improved the predictive accuracy for overall survival above traditional factors (age, smoking, stage, treatment); increase in C-index was 0.069 (95% CI 0.019-0.119, P < 0.001); increase in area under the PPV curve for predicting 5-year survival was 0.068 (95% CI 0.015-0.111, P = 0.008). CONCLUSIONS: HPV16 genetic variation is associated with HPV-OPC prognosis and can improve prognostic accuracy.

The primacy of NF1 loss as the driver of tumorigenesis in neurofibromatosis type 1-associated plexiform neurofibromas.

Neurofibromatosis type 1 (NF1) is a common tumor-predisposition disorder due to germline mutations in the tumor suppressor gene NF1. A virtually pathognomonic finding of NF1 is the plexiform neurofibroma (PN), a benign, likely congenital tumor that arises from bi-allelic inactivation of NF1. PN can undergo transformation to a malignant peripheral nerve sheath tumor, an aggressive soft-tissue sarcoma. To better understand the non-NF1 genetic contributions to PN pathogenesis, we performed whole-exome sequencing, RNASeq profiling and genome-wide copy-number determination for 23 low-passage Schwann cell cultures established from surgical PN material with matching germline DNA. All resected tumors were derived from routine debulking surgeries. None of the tumors were considered at risk for malignant transformation at the time; for example, there was no pain or rapid growth. Deep (~500X) NF1 exon sequencing was also conducted on tumor DNA. Non-NF1 somatic mutation verification was performed using the Ampliseq/IonTorrent platform. We identified 100% of the germline NF1 mutations and found somatic NF1 inactivation in 74% of the PN. One individual with three PNs had different NF1 somatic mutations in each tumor. The median number of somatic mutations per sample, including NF1, was one (range 0-8). NF1 was the only gene that was recurrently somatically inactivated in multiple tumors. Gene Set Enrichment Analysis of transcriptome-wide tumor RNA sequencing identified five significant (FDR<0.01) and seven trending (0.01⩽FDR<0.02) gene sets related to DNA replication, telomere maintenance and elongation, cell cycle progression, signal transduction and cell proliferation. We found no recurrent non-NF1 locus copy-number variation in PN. This is the first multi-sample whole-exome and whole-transcriptome sequencing study of NF1-associated PN. Taken together with concurrent copy-number data, our comprehensive genetic analysis reveals the primacy of NF1 loss as the driver of PN tumorigenesis.

Identification of differentially expressed genes in hepatocellular carcinoma and metastatic liver tumors by oligonucleotide expression profiling.

BACKGROUND: The characterization of differentially expressed genes between cancerous and normal tissues is an important step in the understanding of tumorigenesis. Global gene expression profiling with microarrays has now offered a powerful tool to measure the changes of thousands of genes in any carcinoma tissues in an effort to identify these key disease-related genes. To compare the gene expression of a primary liver carcinoma, metastatic carcinoma to the liver, and normal liver, the authors analyzed tissue from six primary hepatocellular carcinomas (HCCs), five colorectal adenocarcinoma metastases to the liver, and eight normal livers. METHODS: Samples were processed from total RNA to fragmented cRNA and hybridized onto Affymetrix GeneChip(R) expression arrays. Analyses were performed to determine the consensus pattern of gene expression for primary liver carcinoma, metastatic liver carcinoma, and normal liver tissue and their changes in expression level. RESULTS: In hepatocellular carcinoma, 842 genes were overexpressed, and 393 genes were underexpressed in comparison with genes of normal liver tissue. Of note, 7 of the 20 most increased identified known genes previously have been associated with liver carcinoma or other types of cancers. The 13 additional identified genes until now have not previously shown strong association with cancers. Furthermore, the authors identified 42 genes and 24 expressed sequence tags that are expressed at a significant level in both HCC and metastastic tumors, presenting a list of marker genes indicative of cancerous liver tissue. CONCLUSIONS: In this study, genes that can be involved in the production of and maintenance of hepatic carcinomas were identified. These data offer new insight into genes that are potentially important in the pathogenesis of liver carcinoma, as well as additional targets for new strategies for cancer therapy and treatment.