AUTHOR=Zhang Deyu , Wu Suna , Pan Shubo , Wang Meiqi , Wang Zhen , He Zixuan , Zhang Guanghao , Cui Fang , Song Yihang , Li Wanshun , Shi Xiaohua , Huang Haojie , Xu Huanhai TITLE=Single-cell sequencing reveals heterogeneity between pancreatic adenosquamous carcinoma and pancreatic ductal adenocarcinoma with prognostic value JOURNAL=Frontiers in Immunology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.972298 DOI=10.3389/fimmu.2022.972298 ISSN=1664-3224 ABSTRACT=

Pancreatic adenosquamous carcinoma (ASPC) is a rare subtype of pancreatic cancer with lethal malignancy, and few studies have focused on the heterogeneity of ASPC. Here, we performed a single-cell sequencing procedure on pancreatic tumor tissue from an ASPC patient and a patient with high-grade intraductal papillary mucinous neoplasm (IPMN). Through the combined analysis of single-cell sequencing data from five pancreatic ductal adenocarcinoma (PDAC) patients, one IPMN patient, and one ASPC patient in a public database, we identified 11 main types of cells, including macrophages, B cells, cancer stem cells, ductal cells, fibroblasts, endo/stellate cells, neutrophils, acinar cells, T cells, natural killer (NK) cells, dendritic cells, and mast cells. Then, the different characteristics and differentiation paths of the immune microenvironment among IPMN, ASPC, and PDAC in macrophages, T cells, and cancer-associated fibroblasts (CAFs) were identified through multiple bioinformatics analyses. Two novel special cancer-associated fibroblasts were identified as nCAFs and imCAFs. Then, cancer cells in duct cells were identified using the infercnv software. Two ASPC-specific subgroups of cancer cells with squamous cell features were identified. Finally, the identified specific CAFs and cancer cells were mapped to TCGA-PAAD cohort through the cibersoftx software. All of these identified subgroups were calculated to have a significant prognostic value in pancreatic cancer patients. These findings will promote the clinical application of single-cell sequencing data of pancreatic cancer and deepen our understanding of ASPC.