Abstract 4801: Integrated genomic analysis of chromosome 11 in squamous tumors
Authors: Walter Vonn , Du Ying , Yin Xiaoying , Sun Wei , Wilkerson Matthew D. , Hayward Michele C. , Salazar Ashley H. , Perou Charles M. , Hayes David N. 
Published: August 2015

Background: Studies by The Cancer Genome Atlas (TCGA) and others have identified regions of somatic copy number alteration (SCNA) in cervical squamous cell carcinoma (CESC), head and neck squamous cell carcinoma (HNSC), and lung squamous cell carcinoma (LUSC). These three tumor types exhibit frequent SCNAs in chromosome 11, including focal gains in 11q13 and 11q22, as well as broad losses in 11p and 11q22-qter. Because expression levels are affected by underlying genomic events, we hypothesized that an integrated analysis of multiple genomic data types would provide increased ability to identify target genes in SCNA regions when compared to methods based on copy number alone while providing insight into mechanisms regulating expression. Examination of multiple tumor types provides a method to validate findings.

Techniques: Gene expression (GE), DNA copy number (CN), DNA methylation (ME), and microRNA expression (miR) data were obtained from the TCGA studies of CESC, HNSC, and LUSC. For each tumor type, univariate and multivariate linear models were constructed on a gene-by-gene basis to investigate the effect of changes in CN, ME, and miR on GE. Analysis of model output provided an approach to identify target genes in SCNA regions and assess the effect of genomic alterations on expression.

Results: Genome-wide GE, CN, ME, and miR data were available for n = 191 (CESC), n = 453 (HNSC), and n = 326 (LUSC) tumor samples. Univariate modeling detected a strong overall association between GE and CN, as measured by the coefficient of determination (model R2). Underlying CN events produced high model R2 for widely recognized genes, e.g. FADD in HNSC and LUSC, and less well-known genes. For example, DCUN1D5 (11q22) exhibits high model R2 in all three tumor types. Univariate analyses suggest that ALDH3B1 (11q13), a predicted target of the tumor suppressor miR-205, is epigenetically regulated. Most samples exhibit high expression of miR-205 and moderate expression of ALDH3B1, but increased ALDH3B1 levels are seen when miR-205 levels are low. This is notable in light of the striking negative association between miR-205 expression and methylation levels, particularly in CESC and LUSC. Fanconi anemia family member FANCF lies in a broad region of CN loss in 11p that contains no clear driver gene. Whereas univariate associations between FANCF GE and CN were moderate, multivariate analyses highlighted this gene because of the additional effect of ME on GE, which was pronounced in CESC and LUSC.

Conclusion: Linear modeling techniques provide a flexible and powerful basis for performing integrated analysis of genomic data. Our approach produces predicted results when analyzing known cancer genes, highlights lesser known genes for future study, provides insight into gene regulation, and draws attention to genes relevant in multiple tumor types.

Citation Format: Vonn Walter, Ying Du, Xiaoying Yin, Wei Sun, Matthew D. Wilkerson, Michele C. Hayward, Ashley H. Salazar, Charles M. Perou, David N. Hayes. Integrated genomic analysis of chromosome 11 in squamous tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4801. doi:10.1158/1538-7445.AM2015-4801