Background Solid tumors such as pancreatic ductal adenocarcinoma (PDAC) comprise not just tumor cells but also a microenvironment with which the tumor cells constantly interact. Detailed characterization of the cellular composition of the tumor microenvironment is critical to the understanding of the disease and treatment of the patient. Single-cell transcriptomics has been used to study the cellular composition of different solid tumor types including PDAC. However, almost all of those studies used primary tumor tissues. Methods In this study, we employed a single-cell RNA sequencing technology to profile the transcriptomes of individual cells from dissociated primary tumors or metastatic biopsies obtained from patients with PDAC. Unsupervised clustering analysis as well as a new supervised classification algorithm, SuperCT, was used to identify the different cell types within the tumor tissues. The expression signatures of the different cell types were then compared between primary tumors and metastatic biopsies. The expressions of the cell type-specific signature genes were also correlated with patient survival using public datasets. Results Our single-cell RNA sequencing analysis revealed distinct cell types in primary and metastatic PDAC tissues including tumor cells, endothelial cells, cancer-associated fibroblasts (CAFs), and immune cells. The cancer cells showed high inter-patient heterogeneity, whereas the stromal cells were more homogenous across patients. Immune infiltration varies significantly from patient to patient with majority of the immune cells being macrophages and exhausted lymphocytes. We found that the tumor cellular composition was an important factor in defining the PDAC subtypes. Furthermore, the expression levels of cell type-specific markers for EMT+ cancer cells, activated CAFs, and endothelial cells significantly associated with patient survival. Conclusions Taken together, our work identifies significant heterogeneity in cellular compositions of PDAC tumors and between primary tumors and metastatic lesions. Furthermore, the cellular composition was an important factor in defining PDAC subtypes and significantly correlated with patient outcome. These findings provide valuable insights on the PDAC microenvironment and could potentially inform the management of PDAC patients.

About half of all patients can expect recovery from pancreatectomy after 6 months, but those with risk factors need more careful follow-up and supportive management.

Pros and cons were well balanced between the two groups. Decisions on the timing of cholecystectomy after PTGBD should be made based on considerations of patient condition, hospital facilities, and surgical experience.

PurposeThe 8th edition of the American Joint Committee on Cancer (AJCC) staging system for pancreatic neuroendocrine tumor (PNET) included several significant changes. We aim to evaluate this staging system compared to the 7th edition AJCC staging system and European Neuroendocrine Tumors Society (ENETS) system.Materials and MethodsWe used Korean nationwide surgery database (2000-2014). Of 972 patients who had undergone surgery for PNET, excluding patients diagnosed with ENETS/World Health Organization 2010 grade 3 (G3), only 472 patients with accurate stage were included.ResultsPoor discrimination in overall survival rate (OSR) was noted between AJCC 8th stage III and IV (p=0.180). The disease-free survival (DFS) curves of 8th AJCC classification were well separated between all stages. Compared with stage I, the hazard ratio of II, III, and IV was 3.808, 13.928, and 30.618, respectively (p=0.007, p < 0.001, and p < 0.001). The curves of OSR and DFS of certain prognostic group in AJCC 7th and ENETS overlapped. In ENETS staging system, no significant difference in DFS between stage IIB versus IIIA (p=0.909) and IIIA versus IIIB (p=0.291). In multivariable analysis, lymphovascular invasion (p=0.002), perineural invasion (p=0.003), and grade (p < 0.001) were identified as independent prognostic factors for DFS.ConclusionThis is the first large-scale validation of the AJCC 8th edition staging system for PNET. The revised 8th system provides better discrimination compared to that of the 7th edition and ENETS TNM system. This supports the clinical use of the system.