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Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome
Qi Dong1, Mingyue Liu1, Bo Chen1
1Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Abstract:
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.
Insights
Poly (ADP-ribose) polymerase inhibitors (PARPis) offer cancer treatment through synthetic lethality. This study identifies genetic interactions to discover new biomarkers for predicting PARPi drug response and resistance, enabling precision therapeutics.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Poly (ADP-ribose) polymerase inhibitors (PARPis) are vital cancer drugs based on synthetic lethality (SL).
- Expanding patient eligibility and overcoming drug resistance are critical challenges for PARPi therapy.
- Genetic interactions (GIs), including SL and synthetic viability (SV), influence cancer cell drug responses.
Purpose of the Study:
- To develop a computational method for identifying genes with SL or SV interactions with PARP1/2/3.
- To use these identified genes as potential biomarkers for PARPi sensitivity or resistance.
- To provide new insights for precision therapeutics in cancer treatment.
Main Methods:
- Analyzed cell line fitness variations using CRISPR/Cas9 and RNA interference screens to identify PARP1/2/3-related GIs.
- Utilized pharmacogenomic datasets to identify potential resistant and sensitive mutated genes.
- Integrated computational analysis with functional genomic screening data.
Main Results:
- Identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes.
- Found that gain-of-function mutations in EGFR confer PARPi resistance, suggesting a veliparib and erlotinib combination therapy for lung cancer.
- Revealed prognostic gene sets associated with PARPi response in lower grade glioma (resistant) and ovarian cancer (sensitive).
Conclusions:
- Cancer genome-derived GIs offer a novel approach for identifying PARPi biomarkers.
- The findings pave the way for developing new precision therapeutic strategies.
- This study enhances our understanding of genetic determinants of PARPi efficacy and resistance.
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