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Title: Integrative omics analyses broaden treatment targets in human cancer

Abstract

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:
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Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1463657
Report Number(s):
PNNL-SA-138193
Journal ID: ISSN 1756-994X; PII: 564
Grant/Contract Number:  
AC05-76RL01830; R01CA178383; R01CA180006; R01DK087960; U01HG006517
Resource 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)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; cancer genomics; mult-omics; proteogenomics; precision medicine; cancer and druggability

Citation Formats

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., Fenyö, 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., 2018. Web. doi:10.1186/S13073-018-0564-Z.
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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., Fenyö, David, Townsend, Reid R., Dipersio, John F., Chen, Feng, & Ding, Li. Integrative omics analyses broaden treatment targets in human cancer. United States. https://doi.org/10.1186/S13073-018-0564-Z
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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., Fenyö, David, Townsend, Reid R., Dipersio, John F., Chen, Feng, and Ding, Li. Fri . "Integrative omics analyses broaden treatment targets in human cancer". United States. https://doi.org/10.1186/S13073-018-0564-Z. https://www.osti.gov/servlets/purl/1463657.
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@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 Fenyö, 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 = {Fri Jul 27 00:00:00 EDT 2018},
month = {Fri Jul 27 00:00:00 EDT 2018}
}
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Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1186/S13073-018-0564-Z
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Figures / Tables:

Fig. 1 Fig. 1: DEPO database. a The methodology supporting curation of the drug-variant depository, which we refer to as DEPO, or Database of Evidence for Precision Oncology, and its use in determining the “druggable” landscape of TCGA tumors. b The composition of sensitive variants in DEPO by variant type. For eachmore » variant type, only unique variants were counted even if a given variant is associated with multiple levels of evidence, multiple drugs, and/or multiple cancer types. “CNV” (copy number variation) corresponds to “CNA” (copy number amplification) and “CNL” (copy number loss) entries in DEPO; this includes genes for which CNA or CNL is associated with drug response, respectively. “Expression” refers to genes whose elevated and reduced expression is associated with drug response. “Mutations” refers to missense, nonsense, in-frame indels, and frameshift mutations. c Number of uniquely drug-associated mutations in DEPO by gene, sorted by evidence level: FDA approved, clinical trials, case reports, and preclinical« less
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