Xiaosong Wang, MD, PhD
Associate Professor of Pathology
University of Pittsburgh Cancer Institute
Hillman Cancer Center, Research Pavilion
5117 Centre Avenue
Pittsburgh, PA 15213
Office Telephone: 412-623-1587
- PhD - Peking University, Health Science Center, Beijing, China, 2003-2006
- BS, MD (equivalent) - China Medical University, Shenyang, China, 1994-2001
Research InterestsThe Cancer Genome Project Initiatives have generated a daunting amount of genomic and deep sequencing data for tens of thousands of human tumors. An overarching challenge of this post-genomic era is to identify and recognize the cancer drivers and targets from these daunting amount of big genomic data, especially those that can be therapeutically targeted to improve the clinical outcome. The mission of our lab is to apply a multiple disciplinary approach inclusive of integrative bioinformatics, cancer genetics, molecular cancer biology, and translational studies to identify driving genetic aberrations and appropriate cancer targets on the basis of deep sequencing and genomic profiling datasets. Our research projects are comprised of both computational and laboratory components. Our dry lab researches focus on developing innovative and integrative computational technologies and tools to discover causal genetic and epigenetic alternations, viable therapeutic targets, and predictive biomarkers in cancer, as well as understanding the tumorigenic process at systematic level. Our wet lab researches focus on experimentally characterizing individual genetic and epigenetic aberrations in breast cancer such as recurrent gene fusions, genomic amplifications, and epimutations, as well as qualifying viable cancer targets and predictive biomarkers for the development of precision therapeutics. Our current disease focus is clinically intractable breast cancers, such as luminal B or basal-like tumors. We expect that our new discoveries will yield novel insights into the recurring genetic abnormalities leading to breast cancer initiation, progression, and therapeutic resistance, and establish viable targets for effective intervention.
Selected PublicationsView Dr. Wang's complete bibliography on PubMed
- Veeraraghavan J, Tan Y, Cao XX, Kim JA, Wang X, Chamness GC, Maiti SN, Cooper LJN, Edwards DP, Contreras A, Hilsenbeck SG, Chang EC, Schiff R, Wang XS. Recurrent ESR1-CCDC170 rearrangements in an aggressive subset of estrogen-receptor positive breast cancers. Nature Communications. 2014 5:4577. PMID: 25099679.
- Fan Y*, Ge N*, Wang XS*, Sun W*, Mao R, Bu W, Creighton CJ, Zheng P, Vasudevan S, An L, Yang J, Zhao YJ, Zhang H, Li XN, Rao PH, Leung E, Lu YJ, Gray JW, Schiff R, Hilsenbeck SG, Osborne CK, Yang J, Zhang H. Amplification and overexpression of MAP3K3 gene in human breast cancer promotes formation and survival of breast cancer cells. The Journal of Pathology. 2014 232:75-86. PMID: 24122835.
- Xu QW, Zhao W, Wang Y, Sartor MA, Han DM, Deng JX, Ponnala R, Yang JY, Zhang QY, Liao GQ, Qu YM, Li L, Liu FF, Zhao HM, Yin YH, Chen WF, Zhang Y#, Wang XS. An integrated genome-wide approach to discover tumor specific antigens as potential immunological and clinical targets in cancer. Cancer Research. 2012 72:6351-61. PMID: 23135912.
- Wang XS*, Shankar S*, Dhanasekaran SM*, Ateeq B, Prensner JR, Yocum AK, Pflueger D, Jing X, Fries DF, Han B, Li Yong, Cao Q, Cao X, Maher CA, Kumar SC, Demichelis F, Tewari AK, Kuefer R, Omenn GS, Palanisamy S, Rubin MA, Varambally S, Chinnaiyan AM. Characterization of KRAS Rearrangements in Metastatic Prostate Cancer. Cancer Discovery. 2011 1:35-43. PMID: 22140652.
- Lai YQ, Ye JX, Chen J, Zhang LB, Wasi LJ, He ZS, Zhou LQ, Li H, Yan QX, Gui YT, Cai ZM, Wang XS, Guan ZC. UPK3A - A Promising Novel Urinary Marker for the Detection of Bladder Cancer. Urology. 2010 76:514. PMID: 20346489.
- Wang XS, Prensner JR, Chen G, Cao Q, Han B, Dhanasekaran SM, Ponnala R, Cao X, Varambally S, Thomas DG, Giordano TJ, Beer DG, Palanisamy N, Sartor MA, Omenn GS, Chinnaiyan AM. An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer. Nature Biotechnology. 2009 27:1005-1011. PMID: 19881495.