Molecular Landscape and Prognostic Biomarker Analysis of Advanced Pancreatic Cancer and Predictors of Treatment Efficacy of AG Chemotherapy - Du, Juan; Qiu, Xin; Lu, Changchang; Zhu, Yahui; Kong, Weiwei; Xu, Mian; Zhang, Xin; Tang, Min; Chen, Jun; Li, Qi; Li, Aimei; He, Jian; et al. (Frontiers in Oncology, 2022)
Purpose: Although mutational analysis of pancreatic cancer has provided valuable clinical information, it has not significantly changed treatment prospects. The purpose of this study is to further investigate molecular alterations in advanced pancreatic cancer and identify predictors of the efficacy of nab-paclitaxel plus gemcitabine (AG) chemotherapy. Experimental design: Tumor samples from 118 pancreatic cancer patients who received AG chemotherapy as first-line treatment were sequenced and genomic profile was generated. Molecular alterations and the involved signaling pathways were analyzed. Genes with a significant difference in mutation frequency between primary and metastatic tumors were identified, and prognostic-related mutant genes were screened using SPSS version 22.0. Results: The most common altered genes in the patients were KRAS (94.9%), TP53 (81.4%), CDKN2A (36.4%), and SMAD4 (22.9%). The mutational frequencies of CDKN2B (14.8% vs. 0%, p = 0.001), FAT3 (7.4% vs. 0%, p = 0.041), MTAP (13% vs. 1.6%, p = 0.023), and SMAD4 (31.4% vs. 15.6%, p = 0.049) in metastatic tumors were significantly higher than that in primary tumors. TP35 and KRAS mutations were significantly correlated with objective response rate, while EPHA7, RNF43, and HMGA2 mutations were significantly correlated with disease control rate. Additionally, patients with TGFR2B, FGF23, EPHA7, SMARCA4, CARD11, ADGRA2, CCNE1, and ACVR2A alterations had a worse overall survival. Further, EPHA7, CARD11, NOTCH1, GATA6, ACVR2A, and HMGA2 mutations indicated undesirable progression-free survival. Conclusions: CDKN2B, FAT3, MTAP, and SMAD4 may be biomarkers that distinguish primary tumors from metastases. EPHA7 mutation may serve as a prognostic biomarker to predict the treatment efficacy of AG chemotherapy.