Single-cell RNA sequencing revealed subclonal heterogeneity and gene signatures of gemcitabine sensitivity in pancreatic cancer - Hou, Zelin; Lin, Jiajing; Ma, Yuan; Fang, Haizhong; Wu, Yuwei; Chen, Zhijiang; Lin, Xianchao; Lu, Fengchun; Wen, Shi; Yu, Xunbin; Huang, Heguang; Pan, Yu (Frontiers in Pharmacology, 2023)
Resistance to gemcitabine is common and critically limits its therapeutic efficacy in pancreatic ductal adenocarcinoma (PDAC). We constructed 17 patient-derived xenograft (PDX) models from PDAC patient samples and identified the most notable responder to gemcitabine by screening the PDX sets in vivo. Gemcitabine showed a dramatic antitumor effect in the notable responder, but this patient was unable to achieve a complete response. To analyze tumor evolution and microenvironmental changes pre- and postchemotherapy, single-cell RNA sequencing (scRNA-seq) was performed. ScRNA-seq revealed that gemcitabine promoted the expansion of subclones associated with drug resistance and recruited macrophages related to tumor progression and metastasis. We further investigated the particular drug-resistant subclone and established a gemcitabine-sensitivity gene panel (GSGP) (SLC46A1, PCSK1N, KRT7, CAV2, and LDHA) dividing PDAC patients into two groups to predict the overall survival (OS) in The Cancer Genome Atlas (TCGA) training dataset. The signature was successfully validated in 3 independent datasets. We also found that 5-GSGP predicted the sensitivity to gemcitabine in PDAC patients in TCGA training dataset who were treated with gemcitabine. Our study provides new insight into the natural selection of tumor cell subclones and remodeling of tumor microenvironment (TME) cells induced by gemcitabine. We revealed a specific drug resistance subclone, and based on the characteristics of this subclone, we constructed a GSGP that can robustly predict gemcitabine sensitivity and prognosis in pancreatic cancer, which provides a theoretical basis for individualized clinical treatment.