TY - JOUR
T1 - Personalized Integrated Network Modeling of the Cancer Proteome Atlas
AU - Ha, Min Jin
AU - Banerjee, Sayantan
AU - Akbani, Rehan
AU - Liang, Han
AU - Mills, Gordon B.
AU - Do, Kim Anh
AU - Baladandayuthapani, Veerabhadran
N1 - Funding Information:
This work was supported by the National Institutes of Health [R01-CA194391, P50-CA070907-18 to M.J.H. and V.B., R21CA220299-01A1 to M.J.H., V.B. and R.A., R01-160736 to V.B., P30-CA016672 to V.B. and K.A.D., 2P50 CA140388-06A1 to M.J.H. and K.A.D.., EDRN CA086368, CCTS TR000371, MD Anderson institutional Moonshot funding to K-A. D., CA168394, CA098258,1U24CA210950, U24CA210949, 1U24CA209851, U54HG008100, U01CA168394 to G.B.M., R01-CA175486 to H.L., U24CA209851 to G.B.M. and H.L., NIH/ NCI: 5U24 CA210950 and 5U24 CA209851 and DoD/CDMRP: W81XWH-16-1-0237 to R.A.; National Science Foundation [grant DMS1463233 to V.B.]; Mary K. Chapman Foundation, and the Michael & Susan Dell Foundation to R.A. and H.L.]; and Cancer Prevention Research Institute of Texas to R.A. and H.L.; DST INSPIRE Faculty fellowship [002165 to S.B.].
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Personalized (patient-specific) approaches have recently emerged with a precision medicine paradigm that acknowledges the fact that molecular pathway structures and activity might be considerably different within and across tumors. The functional cancer genome and proteome provide rich sources of information to identify patient-specific variations in signaling pathways and activities within and across tumors; however, current analytic methods lack the ability to exploit the diverse and multi-layered architecture of these complex biological networks. We assessed pan-cancer pathway activities for >7700 patients across 32 tumor types from The Cancer Proteome Atlas by developing a personalized cancer-specific integrated network estimation (PRECISE) model. PRECISE is a general Bayesian framework for integrating existing interaction databases, data-driven de novo causal structures, and upstream molecular profiling data to estimate cancer-specific integrated networks, infer patient-specific networks and elicit interpretable pathway-level signatures. PRECISE-based pathway signatures, can delineate pan-cancer commonalities and differences in proteomic network biology within and across tumors, demonstrates robust tumor stratification that is both biologically and clinically informative and superior prognostic power compared to existing approaches. Towards establishing the translational relevance of the functional proteome in research and clinical settings, we provide an online, publicly available, comprehensive database and visualization repository of our findings (https://mjha.shinyapps.io/PRECISE/).
AB - Personalized (patient-specific) approaches have recently emerged with a precision medicine paradigm that acknowledges the fact that molecular pathway structures and activity might be considerably different within and across tumors. The functional cancer genome and proteome provide rich sources of information to identify patient-specific variations in signaling pathways and activities within and across tumors; however, current analytic methods lack the ability to exploit the diverse and multi-layered architecture of these complex biological networks. We assessed pan-cancer pathway activities for >7700 patients across 32 tumor types from The Cancer Proteome Atlas by developing a personalized cancer-specific integrated network estimation (PRECISE) model. PRECISE is a general Bayesian framework for integrating existing interaction databases, data-driven de novo causal structures, and upstream molecular profiling data to estimate cancer-specific integrated networks, infer patient-specific networks and elicit interpretable pathway-level signatures. PRECISE-based pathway signatures, can delineate pan-cancer commonalities and differences in proteomic network biology within and across tumors, demonstrates robust tumor stratification that is both biologically and clinically informative and superior prognostic power compared to existing approaches. Towards establishing the translational relevance of the functional proteome in research and clinical settings, we provide an online, publicly available, comprehensive database and visualization repository of our findings (https://mjha.shinyapps.io/PRECISE/).
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U2 - 10.1038/s41598-018-32682-x
DO - 10.1038/s41598-018-32682-x
M3 - Article
C2 - 30297783
AN - SCOPUS:85054559014
VL - 8
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
IS - 1
M1 - 14924
ER -