Speaker
Bing Zhang, Ph.D.
Date
Location
University of Houston
Abstract
Precision oncology has largely been driven by genomic profiling, but success so far has been
limited. By combining next generation-based genomics and transcriptomics and mass
spectrometry-based proteomics, proteogenomic profiling of human tumors holds promise in
providing deeper mechanistic insights and generating therapeutic hypotheses to better match
patients to targeted treatments than analyzing each ‘ome in isolation. Using data generated
by the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) on
HPV-negative head and neck squamous cell carcinoma (HNSCC) as an example, I will present a
few strategies on using proteogenomics data to drive therapeutic hypothesis generation for
precision oncology. Predictive biomarkers identified through integrated proteogenomic
characterization of the target proteins and pathways of existing drugs enable matching
tumors to the most effective drugs. Meanwhile, new targets identified through unbiased
exploratory analysis of proteogenomic data provide rationale for new drug development.
limited. By combining next generation-based genomics and transcriptomics and mass
spectrometry-based proteomics, proteogenomic profiling of human tumors holds promise in
providing deeper mechanistic insights and generating therapeutic hypotheses to better match
patients to targeted treatments than analyzing each ‘ome in isolation. Using data generated
by the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) on
HPV-negative head and neck squamous cell carcinoma (HNSCC) as an example, I will present a
few strategies on using proteogenomics data to drive therapeutic hypothesis generation for
precision oncology. Predictive biomarkers identified through integrated proteogenomic
characterization of the target proteins and pathways of existing drugs enable matching
tumors to the most effective drugs. Meanwhile, new targets identified through unbiased
exploratory analysis of proteogenomic data provide rationale for new drug development.