Songjian Lu, PhD Assistant Professor

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Presentation transcript:

Study cancer disease mechanisms by searching for cancer signaling pathways Songjian Lu, PhD Assistant Professor Department of Biomedical Informatics School of Medicine University of Pittsburgh

The major goal of my current research Goal & Method The major goal of my current research Pathway regulates the proliferation Pathway regulates the cell cycle Pathway regulates the cell death Genes related to the cell cycle Genes related to the proliferation Genes related to the cell death Re-construct the signaling pathways related to cancer development. Understand the cancer disease mechanism. Provide the potential candidates for targeted therapy. The basic method Apply the reverse engineering technology: Formulate the pathway reconstruction problem into the graph problems. Design efficient exact algorithms to solve the NP-hard graph problems in our models, which guarantees the optimal solutions of the models.

Examples of research results Computational results: The mutation of TP53, the amplifications of MED1, YWHAZ, and PTK2 affect the cell DNA repair, mitosis, cell cycle etc. Wet-lab verification: The knockdown of TP53, MED1, PTK2 and YWHAX disturb cell cycle.

Examples of research results Computational results: Tumors with or without mutation of TP53, the amplifications of MED1, YWHAZ, and PTK2 have distinguished expressions of EMT genes. Wet-lab verification: The knockdown of TP53, MED1, PTK2 and YWHAX suppress tumor metastasis. Hence, they are the potential candidates for targeted therapy.

Publications & funding Recent publications 1. G. Yan, V. Chen, X. Lu, S. Lu*. A signal-based method for finding driver modules of breast cancer metastasis to the lung. Scientific Reports; 2017 2. S. Lu, C. Cai, G. Yan, Z. Zhou, Y. Wan, L. Chen, V. Chen, G. Cooper, L. Obeid, Y. Hannun, A. Lee and X. Lu. Signal-oriented pathway analyses reveal a signaling complex as a synthetic lethal target for p53 mutations. Cancer Research; 2016, DOI: 10.1158/0008-5472.CAN-16-1740. 3. T. Huang, A. Alvarez, R. Pangeni, C. Horbinski, S. Lu, S. Kim, D. James, J. Raizer, J. Kessler, C. Brenann, E. Sulman, G. Finocchiaro, M. Tan, R. Nishikawa, X. Lu, I. Nakano, B. Hu, and S. Cheng. A Regulatory Circuit of miR-125b/miR-20b and Wnt Signaling Controls GBM Phenotypes through FZD6-Mediated Pathways. Nature Communications; 2016, DOI: 10.1038/ncomms12885. 4. S. Lu*, G. Mandava, G. Yan, X. Lu. An exact algorithm for finding cancer driver somatic genome alterations: the weighed mutually exclusive maximum set cover problem. Algorithms for Molecular Biology; 2016 11(11); DOI: 10.1186/s13015-016-0073-9. 5. S. Lu*, K. Lu, S. Cheng, B. Hu, X. Ma, N. Nystrom, X. Lu. Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets. PLOS Computational Biology; 2015 Aug; 11 (8):e1004257. PMCID: PMC4552843. PMID: 26317392. DOI: 10.1371/journal.pcbi.1004257 6. S. Lu, B. Jin, L. Cowart, X. Lu. From data towards knowledge: Revealing the architecture of signaling systems by unifying knowledge mining and data mining of systematic perturbation data. PLOS One; 2013; 8(4). Research funding Developing graph models and efficient algorithms for the study of cancer disease mechanisms (PI, NIH K99/R00, 02/2014--10/2018).