Skip to main content

Characterization of genomic alterations in HPV-negative and HPV-positive HNSCC cell lines with high throughput whole exome DNA and transcriptome RNA sequencing

Friday, September 18, 2015 — Poster Session IV

12:00 p.m. – 1:30 p.m.
FAES Terrace


  • H Cheng
  • X Yang
  • H Si
  • A Saleh
  • J Coupar
  • RL Ferris
  • WG Yarbrough
  • ME Prince
  • TE Carey
  • C Van Waes
  • Z Chen


Head and neck squamous cell carcinoma (HNSCC) is among the top cancer types with high frequencies of genomic alterations, including mutation and copy number variation (CNV). Recently the Cancer Genome Atlas (TCGA) has profiled over 279 HNSCC tumors and generated a comprehensive genomic characterization of HNSCC. This has led to an urgent need for a panel of HNSCC cell line models with genomic alterations representative of those found by TCGA. We performed whole exome-DNA and transcriptome RNA sequencing on 15 HPV-negative and 11 HPV-positive HNSCC lines. These sequencings were performed on the ABI SOLiD platform with an average depth of 87X and 44X respectively. We identified chromosome losses in 3p, 5q, 8p, 9p and 18q and gains in 3q, 7p and 11q in a significant portion of cell lines, which are consistent with previous karyotype and TCGA CNV studies. Integrative analysis between CNV by exome-seq and gene expression by RNAseq of these cell lines revealed a significant positive correlation in multiple oncogenes including PIK3CA, TP63, CCND1, FADD, BIRC2 and YAP1, which is in concordance with TCGA results. The significantly mutated genes identified by MutSig in TCGA are also frequently mutated in cell lines, including TP53, FAT1 and NOTCH1, etc. Many of the genomic alterations identified converge on the networks previously defined in HNSCC, including the PI3K/AKT/mTOR, NFκB, and RAS/MAPK pathways. Our findings suggest that these cell lines can serve as HNSCC models for mechanistic and therapeutic studies, and thereby provide a valuable resource for the wider biomedical research community.

Category: Genetics and Genomics