Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome

Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (G...

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Main Authors: Qi Dong, Mingyue Liu, Bo Chen, Zhangxiang Zhao, Tingting Chen, Chengyu Wang, Shuping Zhuang, Yawei Li, Yuquan Wang, Liqiang Ai, Yaoyao Liu, Haihai Liang, Lishuang Qi, Yunyan Gu
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S200103702100338X
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spelling doaj-cf34724db82342edadb3c5f7ca37ed932021-08-20T04:34:24ZengElsevierComputational and Structural Biotechnology Journal2001-03702021-01-011944354446Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genomeQi Dong0Mingyue Liu1Bo Chen2Zhangxiang Zhao3Tingting Chen4Chengyu Wang5Shuping Zhuang6Yawei Li7Yuquan Wang8Liqiang Ai9Yaoyao Liu10Haihai Liang11Lishuang Qi12Yunyan Gu13Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Pharmacology, College of Pharmacy, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China; Corresponding author at: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (GIs) include SL and synthetic viability (SV) that participate in drug response in cancer cells. Based on the hypothesis that mutated genes with SL or SV interactions with PARP1/2/3 are potential sensitive or resistant PARPis biomarkers, respectively, we developed a novel computational method to identify them. We analyzed fitness variation of cell lines to identify PARP1/2/3-related GIs according to CRISPR/Cas9 and RNA interference functional screens. Potential resistant/sensitive mutated genes were identified using pharmacogenomic datasets. We identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes, and observed that EGFR with gain-of-function mutation induced PARPi resistance, and predicted a combination therapy with PARP inhibitor (veliparib) and EGFR inhibitor (erlotinib) for lung cancer. We also revealed that a resistant gene set (TNN, PLEC, and TRIP12) in lower grade glioma and a sensitive gene set (BRCA2, TOP3A, and ASCC3) in ovarian cancer, which were associated with prognosis. Thus, cancer genome-derived GIs provide new insights for identifying PARPi biomarkers and a new avenue for precision therapeutics.http://www.sciencedirect.com/science/article/pii/S200103702100338XPARP inhibitorsGenetic interactionsMutationResistant biomarkersSensitive biomarkers
collection DOAJ
language English
format Article
sources DOAJ
author Qi Dong
Mingyue Liu
Bo Chen
Zhangxiang Zhao
Tingting Chen
Chengyu Wang
Shuping Zhuang
Yawei Li
Yuquan Wang
Liqiang Ai
Yaoyao Liu
Haihai Liang
Lishuang Qi
Yunyan Gu
spellingShingle Qi Dong
Mingyue Liu
Bo Chen
Zhangxiang Zhao
Tingting Chen
Chengyu Wang
Shuping Zhuang
Yawei Li
Yuquan Wang
Liqiang Ai
Yaoyao Liu
Haihai Liang
Lishuang Qi
Yunyan Gu
Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
Computational and Structural Biotechnology Journal
PARP inhibitors
Genetic interactions
Mutation
Resistant biomarkers
Sensitive biomarkers
author_facet Qi Dong
Mingyue Liu
Bo Chen
Zhangxiang Zhao
Tingting Chen
Chengyu Wang
Shuping Zhuang
Yawei Li
Yuquan Wang
Liqiang Ai
Yaoyao Liu
Haihai Liang
Lishuang Qi
Yunyan Gu
author_sort Qi Dong
title Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
title_short Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
title_full Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
title_fullStr Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
title_full_unstemmed Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
title_sort revealing biomarkers associated with parp inhibitors based on genetic interactions in cancer genome
publisher Elsevier
series Computational and Structural Biotechnology Journal
issn 2001-0370
publishDate 2021-01-01
description Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (GIs) include SL and synthetic viability (SV) that participate in drug response in cancer cells. Based on the hypothesis that mutated genes with SL or SV interactions with PARP1/2/3 are potential sensitive or resistant PARPis biomarkers, respectively, we developed a novel computational method to identify them. We analyzed fitness variation of cell lines to identify PARP1/2/3-related GIs according to CRISPR/Cas9 and RNA interference functional screens. Potential resistant/sensitive mutated genes were identified using pharmacogenomic datasets. We identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes, and observed that EGFR with gain-of-function mutation induced PARPi resistance, and predicted a combination therapy with PARP inhibitor (veliparib) and EGFR inhibitor (erlotinib) for lung cancer. We also revealed that a resistant gene set (TNN, PLEC, and TRIP12) in lower grade glioma and a sensitive gene set (BRCA2, TOP3A, and ASCC3) in ovarian cancer, which were associated with prognosis. Thus, cancer genome-derived GIs provide new insights for identifying PARPi biomarkers and a new avenue for precision therapeutics.
topic PARP inhibitors
Genetic interactions
Mutation
Resistant biomarkers
Sensitive biomarkers
url http://www.sciencedirect.com/science/article/pii/S200103702100338X
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