Lung cancer is the world's leading cause of cancer death with strong ancestry disparities. By sequencing and assembling the largest genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n = 305) to date, we found that East Asian LUADs had more stable genomes characterized by fewer mutations and less copy number alteration than LUADs from individuals of European ancestry (EUR). This difference is much stronger in smokers as compared to non-smokers. Transcriptomic clustering identified a novel EAS-specific LUAD subgroup with a less complex genomic profile and up-regulated immune-related genes, allowing the possibility of immunotherapybased approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to the less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts.

Extensive and multi-dimensional data sets generated from recent cancer omics profiling projects have presented new challenges and opportunities for unraveling the complexity of cancer genome landscapes. In particular, distinguishing the unique complement of genes that drive tumorigenesis in each patient from a sea of passenger mutations is necessary for translating the full benefit of cancer genome sequencing into the clinic. We address this need by presenting a data integration framework (OncoIMPACT) to nominate patient-specific driver genes based on their phenotypic impact. Extensive in silico and in vitro validation helped establish OncoIMPACT's robustness, improved precision over competing approaches and verifiable patient and cell line specific predictions (2/2 and 6/7 true positives and negatives, respectively). In particular, we computationally predicted and experimentally validated the gene TRIM24 as a putative novel amplified driver in a melanoma patient. Applying OncoIMPACT to more than 1000 tumor samples, we generated patient-specific driver gene lists in five different cancer types to identify modes of synergistic action. We also provide the first demonstration that computationally derived driver mutation signatures can be overall superior to single gene and gene expression based signatures in enabling patient stratification and prognostication. Source code and executables for OncoIMPACT are freely available from http://sourceforge.net/projects/oncoimpact.

In our group, we have extensively sequenced various cancer genomes (breast cancer, ovarian cancer and melanoma) using a range of genome-wide sequencing approaches, including DNA-PET, RNA-SEQ and exome-capture sequencing. Taking each tumor as a system of its own, we aim to integrate the different outputs of these technologies to explore the composite of hard-wired changes that drive tumorgenesis in different cancers. One type of hard-wired changes is copy number alterations, where the cancer genome tends to gain oncogenes and lose tumor suppressors by DNA amplifications and deletions respectively. While copy number variation data are now a standard output of the DNA-PET pipeline, the accurate prediction of copy number gains and losses is further complicated by several issues, including normal tissue contamination, tumor heterogeneity and aneuploidy. I will present my current work to deconvolute the contribution of these factors to the copy number profile. I will also discuss the classification of our sequenced cancer genomes into various chromotypes based on their unique copy number signatures. I will show how different chromotypes are enriched in specific types of structural variations, which may underlay alternative mechanisms of genomic instability promoting cancer evolution. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4947. doi:1538-7445.AM2012-4947

Melanoma is one of the most aggressive human cancers. The worldwide incidence rate of melanoma has increased during the last decade but with few FDA approved therapeutic options. Patients with lymph node metastasis can show highly variable clinical outcomes, from several years disease free survival after excision of the primary lesion to extremely aggressive metastatic disease; while patients with distant metastasis show poor clinical outcome. Outstanding outcomes using target therapies such as B-RAF V600E inhibitor (Vemurafenib) bring hope for possibility of melanoma cure. Alternatively, since melanoma acquires resistance to Vemurafenib, the necessity of searching for other candidates and simultaneously targeting several pathways for long-term survival is inevitable. Better understanding of the genomic signatures of melanoma progression and maintenance provides new opportunities for developing novel therapeutic targets for successful management of this fatal disease. In this study, we aim to reveal the complex patterns of distinct molecular aberrations and mechanisms underlying the progression and maintenance of melanoma using high-throughput sequencing approaches. Our hypothesis is that there are genetic changes in melanoma which suggest the survival of the distant metastasis; these genetic changes include activated oncogenes and suppressed tumor suppressor genes correlated with melanoma progression and maintenance. As a proof of principal we initiated this study with a poor prognosis melanoma patient; a 46 year old man diagnosed with lymph node metastasis and treated with T-cell vaccination (TCV), who showed the tumor distant metastasis to lung, 14.8 months after complete lymph node dissection. The availability of primary cell lines established from both lymph node and lung metastatic tissues represents a major advantage for the functional validation of individual candidate genes which may serve as novel targets for cancer therapy. Integration of copy number with structural variation data showed a great selection for cell lines generation (derived from lymph node and lung tumors) and we observed that this selection was for a similar clone embedded in lymph node and lung metastatic tumors. With this data, we hypothesized that common sets of events which cut across all samples in this case identify the core sets of putative oncogenes and tumor suppressor genes which drive this patient's cancer cells. The correlation of these genes with the cancer phenotype will be addressed. Citation Format: Faranak Ghazi Sherbaf, Charlie LEE Wah Heng, Xing Yi Woo, Denis Bertrand, Koichiro Inaki, Kelly Chong Chong, Donald Morton, Sharon Huang, Dave Hoon, Edison Liu. Genomic signatures of melanoma progression and maintenance. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2001. doi:10.1158/1538-7445.AM2013-2001