Novel RNA-Affinity Proteogenomics Dissects Tumor Heterogeneity for Revealing Personalized Markers in Precision Prognosis of Cancer.

Cell Chem Biol 2018 05 1;25(5):619-633.e5. Epub 2018 Mar 1.

Department of Biochemistry & Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Chemistry & Institute of Biomedical Sciences, Fudan University, Shanghai 200032, China. Electronic address:

To discriminate the patient subpopulations with different clinical outcomes within each breast cancer (BC) subtype, we introduce a robust, clinical-practical, activity-based proteogenomic method that identifies, in their oncogenically active states, candidate biomarker genes bearing patient-specific transcriptomic/genomic alterations of prognostic value. First, we used the intronic splicing enhancer (ISE) probes to sort ISE-interacting trans-acting protein factors (trans-interactome) directly from a tumor tissue for subsequent mass spectrometry characterization. In the retrospective, proteogenomic analysis of patient datasets, we identified those ISE trans-factor-encoding genes showing interaction-correlated expression patterns (iCEPs) as new BC-subtypic genes. Further, patient-specific co-alterations in mRNA expression of select iCEP genes distinguished high-risk patient subsets/subpopulations from other patients within a single BC subtype. Function analysis further validated a tumor-phenotypic trans-interactome contained the drivers of oncogenic splicing switches, representing the predominant tumor cells in a tissue, from which novel personalized biomarkers were clinically characterized/validated for precise prognostic prediction and subsequent individualized alignment of optimal therapy.

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http://dx.doi.org/10.1016/j.chembiol.2018.01.016DOI Listing
May 2018
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