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Title: Integrative omics analyses broaden treatment targets in human cancer

Although large-scale, next-generation sequencing (NGS) studies of cancers hold promise for enabling precision oncology, challenges remain in integrating NGS with clinically validated biomarkers. To overcome such challenges, we utilized the Database of Evidence for Precision Oncology (DEPO) to link druggability to genomic, transcriptomic, and proteomic biomarkers. Using a pan-cancer cohort of 6570 tumors, we identified tumors with potentially druggable biomarkers consisting of drug-associated mutations, mRNA expression outliers, and protein/phosphoprotein expression outliers identified by DEPO. As a result, within the pan-cancer cohort of 6570 tumors, we found that 3% are druggable based on FDA-approved drug-mutation interactions in specific cancer types. However, mRNA/phosphoprotein/protein expression outliers and drug repurposing across cancer types suggest potential druggability in up to 16% of tumors. The percentage of potential drug-associated tumors can increase to 48% if we consider preclinical evidence. Further, our analyses showed co-occurring potentially druggable multi-omics alterations in 32% of tumors, indicating a role for individualized combinational therapy, with evidence supporting mTOR/PI3K/ESR1 co-inhibition and BRAF/AKT co-inhibition in 1.6 and 0.8% of tumors, respectively. We experimentally validated a subset of putative druggable mutations in BRAF identified by a protein structure-based computational tool. Finally, analysis of a large-scale drug screening dataset lent further evidence supporting repurposing ofmore » drugs across cancer types and the use of expression outliers for inferring druggability. Finally, our results suggest that an integrated analysis platform can nominate multi-omics alterations as biomarkers of druggability and aid ongoing efforts to bring precision oncology to patients.« less
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [3] ;  [4] ;  [1] ;  [1] ;  [1] more »; ORCiD logo [1] « less
  1. Washington Univ., St. Louis, MO (United States)
  2. Memorial Sloan Kettering Cancer Center, New York, NY (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. New York Univ. Langone School of Medicine, New York, NY (United States)
Publication Date:
Grant/Contract Number:
AC05-76RL01830; R01CA178383; R01CA180006; R01DK087960; U01HG006517
Type:
Accepted Manuscript
Journal Name:
Genome Medicine
Additional Journal Information:
Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 1756-994X
Publisher:
BioMed Central (BMC)
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; cancer genomics; mult-omics; proteogenomics; precision medicine; cancer and druggability
OSTI Identifier:
1463657

Sengupta, Sohini, Sun, Sam Q., Huang, Kuan-lin, Oh, Clara, Bailey, Matthew H., Varghese, Rajees, Wyczalkowski, Matthew A., Ning, Jie, Tripathi, Piyush, McMichael, Joshua F., Johnson, Kimberly J., Kandoth, Cyriac, Welch, John, Ma, Cynthia, Wendl, Michael C., Payne, Samuel H., Fenyo, David, Townsend, Reid R., Dipersio, John F., Chen, Feng, and Ding, Li. Integrative omics analyses broaden treatment targets in human cancer. United States: N. p., Web. doi:10.1186/S13073-018-0564-Z.
Sengupta, Sohini, Sun, Sam Q., Huang, Kuan-lin, Oh, Clara, Bailey, Matthew H., Varghese, Rajees, Wyczalkowski, Matthew A., Ning, Jie, Tripathi, Piyush, McMichael, Joshua F., Johnson, Kimberly J., Kandoth, Cyriac, Welch, John, Ma, Cynthia, Wendl, Michael C., Payne, Samuel H., Fenyo, David, Townsend, Reid R., Dipersio, John F., Chen, Feng, & Ding, Li. Integrative omics analyses broaden treatment targets in human cancer. United States. doi:10.1186/S13073-018-0564-Z.
Sengupta, Sohini, Sun, Sam Q., Huang, Kuan-lin, Oh, Clara, Bailey, Matthew H., Varghese, Rajees, Wyczalkowski, Matthew A., Ning, Jie, Tripathi, Piyush, McMichael, Joshua F., Johnson, Kimberly J., Kandoth, Cyriac, Welch, John, Ma, Cynthia, Wendl, Michael C., Payne, Samuel H., Fenyo, David, Townsend, Reid R., Dipersio, John F., Chen, Feng, and Ding, Li. 2018. "Integrative omics analyses broaden treatment targets in human cancer". United States. doi:10.1186/S13073-018-0564-Z. https://www.osti.gov/servlets/purl/1463657.
@article{osti_1463657,
title = {Integrative omics analyses broaden treatment targets in human cancer},
author = {Sengupta, Sohini and Sun, Sam Q. and Huang, Kuan-lin and Oh, Clara and Bailey, Matthew H. and Varghese, Rajees and Wyczalkowski, Matthew A. and Ning, Jie and Tripathi, Piyush and McMichael, Joshua F. and Johnson, Kimberly J. and Kandoth, Cyriac and Welch, John and Ma, Cynthia and Wendl, Michael C. and Payne, Samuel H. and Fenyo, David and Townsend, Reid R. and Dipersio, John F. and Chen, Feng and Ding, Li},
abstractNote = {Although large-scale, next-generation sequencing (NGS) studies of cancers hold promise for enabling precision oncology, challenges remain in integrating NGS with clinically validated biomarkers. To overcome such challenges, we utilized the Database of Evidence for Precision Oncology (DEPO) to link druggability to genomic, transcriptomic, and proteomic biomarkers. Using a pan-cancer cohort of 6570 tumors, we identified tumors with potentially druggable biomarkers consisting of drug-associated mutations, mRNA expression outliers, and protein/phosphoprotein expression outliers identified by DEPO. As a result, within the pan-cancer cohort of 6570 tumors, we found that 3% are druggable based on FDA-approved drug-mutation interactions in specific cancer types. However, mRNA/phosphoprotein/protein expression outliers and drug repurposing across cancer types suggest potential druggability in up to 16% of tumors. The percentage of potential drug-associated tumors can increase to 48% if we consider preclinical evidence. Further, our analyses showed co-occurring potentially druggable multi-omics alterations in 32% of tumors, indicating a role for individualized combinational therapy, with evidence supporting mTOR/PI3K/ESR1 co-inhibition and BRAF/AKT co-inhibition in 1.6 and 0.8% of tumors, respectively. We experimentally validated a subset of putative druggable mutations in BRAF identified by a protein structure-based computational tool. Finally, analysis of a large-scale drug screening dataset lent further evidence supporting repurposing of drugs across cancer types and the use of expression outliers for inferring druggability. Finally, our results suggest that an integrated analysis platform can nominate multi-omics alterations as biomarkers of druggability and aid ongoing efforts to bring precision oncology to patients.},
doi = {10.1186/S13073-018-0564-Z},
journal = {Genome Medicine},
number = 1,
volume = 10,
place = {United States},
year = {2018},
month = {7}
}

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