Pancreatic ductal adenocarcinoma (PDAC) remains one of the most challenging cancers to treat. Due to the asymptomatic nature of the disease and lack of curative treatment modalities, the 5-y survival rate of PDAC patients is one of the lowest of any cancer type. The recurrent genetic alterations in PDAC are yet to be targeted. Therefore, identification of effective drug combinations is desperately needed. Here, we performed an in vivo CRISPR screen in an orthotopic patient-derived xenograft (PDX) model to identify gene targets whose inhibition creates synergistic tumor growth inhibition with gemcitabine (Gem), a first- or second-line chemotherapeutic agent for PDAC treatment. The approach revealed protein arginine methyltransferase gene 5 (PRMT5) as an effective druggable candidate whose inhibition creates synergistic vulnerability of PDAC cells to Gem. Genetic depletion and pharmacological inhibition indicate that loss of PRMT5 activity synergistically enhances Gem cytotoxicity due to the accumulation of excessive DNA damage. At the molecular level, we show that inhibition of PRMT5 results in RPA depletion and impaired homology-directed DNA repair (HDR) activity. The combination (Gem + PRMT5 inhibition) creates conditional lethality and synergistic reduction of PDAC tumors in vivo. The findings demonstrate that unbiased genetic screenings combined with a clinically relevant model system is a practical approach in identifying synthetic lethal drug combinations for cancer treatment.
Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management.
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most challenging cancer to treat. Due to the asymptomatic nature of the disease and ineffective drug treatment modalities, the survival rate of PDAC patients remains one of the lowest. The recurrent genetic alterations in PDAC are yet to be targeted; therefore, identifying effective therapeutic combinations is desperately needed. Here, we performed an in vivo CRISPR screening in a clinically relevant patient-derived xenograft (PDX) model system to identify synergistic drug combinations for PDAC treatment. Our approach revealed protein arginine methyltransferase gene 5 (PRMT5) as a promising druggable candidate whose inhibition creates synergistic vulnerability of PDAC cells to gemcitabine. Genetic and pharmacological inhibition results indicate that of PRMT5 depletion results in synergistic cytotoxicity with Gem due to depleted replication protein A (RPA) levels and an impaired non-homology end joining (NHEJ) DNA repair.Thus, the novel combination creates conditional lethality through the accumulation of excessive DNA damage and cell death, both in vitro and in vivo. The findings demonstrate that unbiased genetic screenings combined with a clinically relevant model system is an effective approach in identifying synthetic lethal drug combinations for cancer treatment.
STATEMENT of SIGNIFICANCEIdentify synergistic drug combinations for PDAC is a significant unmet need. Through CRISPR screening, we discovered and validated that PRMT5 depletion creates synergistic vulnerability of PDAC cells to gemcitabine. Mechanistically, the combination impairs DNA repair, synergistic accumulation of DNA damage and cell death in vitro and in vivo.
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