The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) will generate a complete compendium of all cancer-associated genomic alterations with the goal of identifying and prioritizing the most promising therapeutic targets and diagnostic biomarkers. The output from these large-scale efforts in the last 2 years is radically transforming the way cancer science is conducted. At the same time, these efforts are uncovering a staggering level of genome complexity in cancer, making it clear that the effective translation of our new-found genomic knowledge into cancer therapeutics and diagnostics will require not only sophisticated computational analyses but, importantly, experimental systems to inform the functional activity of targets in the relevant biological context. The collective experience in cancer gene discovery and drug development has taught the field that an annotation of functionality alone is not sufficient to make informed decisions in cancer drug development. Rather, a productive drug development effort requires mechanistic understanding of a target's cancer-relevant activity, the specific biological and genotypic context in which it operates, and the clinical context in which to test the ultimate hypothesis, i.e. rational design of clinical trials. Given the hundreds and thousands of potential candidates from obtained by genomic efforts, it is imperative that an efficient prioritization pipeline is in place to filter and prioritize for downstream studies. Here we propose a CTD2 Center that will bring to the CTD2 Network multi-level functional and pharmacological assessments of biological importance, in both cell-based and in vivo settings, for somatic mutations identified by TCGA. Such """"""""ground-truth"""""""" will be incorporated iteratively into computational models developed and refined to identify """"""""driver mutations"""""""" with increasing specificity and sensitivity. In addition to these functional and pharmacological data and prediction algorithms, this Center has also developed novel approaches to rapidly and efficiently engineer somatic mutations in diverse vector systems which will support the activities of other centers in the Network and in the general cancer research community. Specific, we will pursue the following Aims: (1) Develop an algorithmic framework for identification of driver events through integrative and iterative analyses of genomic, functional and pharmacological response data;(2) Implement a high throughput platform for engineering somatic mutations in candidate genes identified by TCGA data for downstream functional studies;(3) Pharmacologically assess the therapeutic consequences conferred by candidate driver events in cell- based viability assays;(4) Functionally identify oncogenic driver events through in vivo Context-Specific screen for tumorigenicity.
A central challenge we face in implementing next generation sequencing into cancer patient care involves determining which aberrations in a given tumor are """"""""drivers"""""""" that determine tumor behavior versus """"""""passengers"""""""" that result from the inherently unstable nature of cancer genomes. This proposal aims to address the need for algorithms and practical high-throughput platforms to help prioritize the vast genomic data being generated by TCGA, ICGC and other similar efforts, and will enable the identification and selection of optimal therapies targeting driver aberrations.
|Grzeskowiak, Caitlin L; Kundu, Samrat T; Mo, Xiulei et al. (2018) In vivo screening identifies GATAD2B as a metastasis driver in KRAS-driven lung cancer. Nat Commun 9:2732|
|Peng, Xinxin; Xu, Xiaoyan; Wang, Yumeng et al. (2018) A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer. Cancer Cell 33:817-828.e7|
|Ng, Patrick Kwok-Shing; Li, Jun; Jeong, Kang Jin et al. (2018) Systematic Functional Annotation of Somatic Mutations in Cancer. Cancer Cell 33:450-462.e10|
|Wang, Jue; Zhao, Wei; Guo, Huifang et al. (2018) AKT isoform-specific expression and activation across cancer lineages. BMC Cancer 18:742|
|Berger, Ashton C; Korkut, Anil; Kanchi, Rupa S et al. (2018) A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers. Cancer Cell 33:690-705.e9|
|Kundu, Samrat T; Grzeskowiak, Caitlin L; Fradette, Jared J et al. (2018) TMEM106B drives lung cancer metastasis by inducing TFEB-dependent lysosome synthesis and secretion of cathepsins. Nat Commun 9:2731|
|Sun, Chaoyang; Yin, Jun; Fang, Yong et al. (2018) BRD4 Inhibition Is Synthetic Lethal with PARP Inhibitors through the Induction of Homologous Recombination Deficiency. Cancer Cell 33:401-416.e8|
|Sun, Chaoyang; Fang, Yong; Yin, Jun et al. (2017) Rational combination therapy with PARP and MEK inhibitors capitalizes on therapeutic liabilities in RAS mutant cancers. Sci Transl Med 9:|
|Xu, Xiaowei; De Angelis, Carmine; Burke, Kathleen A et al. (2017) HER2 Reactivation through Acquisition of the HER2 L755S Mutation as a Mechanism of Acquired Resistance to HER2-targeted Therapy in HER2+ Breast Cancer. Clin Cancer Res 23:5123-5134|
|Wang, Chao; Gu, Chao; Jeong, Kang Jin et al. (2017) YAP/TAZ-Mediated Upregulation of GAB2 Leads to Increased Sensitivity to Growth Factor-Induced Activation of the PI3K Pathway. Cancer Res 77:1637-1648|
Showing the most recent 10 out of 52 publications