Objective: The aim of the study was to analyze the outcomes of patients who have undergone laparoscopic pancreaticoduodenectomy (LPD) in China. Summary Background Data: LPD is being increasingly used worldwide, but an extensive, detailed, systematic, multicenter analysis of the procedure has not been performed. Methods: We retrospectively reviewed 1029 consecutive patients who had undergone LPD between January 2010 and August 2016 in China. Univariate and multivariate analyses of patient demographics, changes in outcome over time, technical learning curves, and the relationship between hospital or surgeon volume and patient outcomes were performed. Results: Among the 1029 patients, 61 (5.93%) required conversion to laparotomy. The median operation time (OT) was 441.34 minutes, and the major complications occurred in 511 patients (49.66%). There were 21 deaths (2.43%) within 30 days, and a total of 61 (5.93%) within 90 days. Discounting the effects of the early learning phase, critical parameters improved significantly with surgeons’ experience with the procedure. Univariate and multivariate analyses revealed that the pancreatic anastomosis technique, preoperative biliary drainage method, and total bilirubin were linked to several outcome measures, including OT, estimated intraoperative blood loss, and mortality. Multicenter analyses of the learning curve revealed 3 phases, with proficiency thresholds at 40 and 104 cases. Higher hospital, department, and surgeon volume, as well as surgeon experience with minimally invasive surgery, were associated with a lower risk of surgical failure. Conclusions: LPD is technically safe and feasible, with acceptable rates of morbidity and mortality. Nonetheless, long learning curves, low-volume hospitals, and surgical inexperience are associated with higher rates of complications and mortality.
Background: Human pancreatic ductal adenocarcinoma (PDAC) responds poorly to immune checkpoint inhibitor (ICPi). While the mechanism is not completely clear, it has been recognized that tumor microenvironment (TME) plays key roles. We investigated if targeting CD47 with a monoclonal antibody could enhance the response of PDAC to ICPi by altering the TME. Methods: Using immunohistochemistry, we examined tumor-infiltrating CD68 + pan-macrophages (CD68 + M) and CD163 + M2 macrophages (CD163 + M2) and tumor expression of CD47 and PD-L1 proteins in 106 cases of PDAC. The efficacy of CD47 blockade was examined in xenograft models. CD45 + immune cells from syngeneic tumor models were subjected to single-cell RNA-sequencing (scRNA-seq) by using the 10x Genomics pipeline. Results: We found that CD47 expression correlated with the level of CD68 + M but not CD163 + M2. High levels of tumor-infiltrating CD68 + M, CD163 + M2, and CD47 expression were significantly associated with worse survival. CD47 high /CD68 + M high and CD47 high /CD163 + M2 high correlated significantly with shorter survival, whereas CD47 low / CD68 + M low and CD47 low /CD163 + M2 low correlated with longer survival. Intriguingly, CD47 blockade decreased the tumor burden in the Panc02 but not in the MPC-83 syngeneic mouse model. Using scRNA-seq, we showed that anti-CD47 treatment significantly remodeled the intratumoral lymphocyte and macrophage compartments in Panc02 tumor-bearing mice by increasing the pro-inflammatory macrophages that exhibit anti-tumor function, while reducing the anti-inflammatory macrophages. Moreover, CD47 blockade not only increased the number of intratumoral CD8 + T cells, but also remodeled the T cell cluster toward a more activated one. Further, combination therapy targeting both CD47 and PD-L1 resulted in synergistic inhibition of PDAC growth in the MPC-83 but not in Panc02 model. MPC-83 but not Panc02 mice treated with both anti-CD47 and anti-PD-L1 showed increased number of PD-1 + CD8 + T cells and enhanced expression of key immune activating genes. Conclusion: Our data indicate that CD47 targeting induces compartmental remodeling of tumor-infiltrating immune cells of the TME in PDAC. Different PDAC mouse models exhibited differential response to the anti-CD47 and anti-PD-L1 blockade due to the differential effect of this combination treatment on the infiltrating immune cells and key immune activating genes in the TME established by the different PDAC cell lines.
Pancreatic cancer is a malignant tumor with the worst prognosis among all cancers. At the time of diagnosis, surgical cure is no longer a feasible option for most patients, thus early detection of pancreatic cancer is crucial for its treatment. Metabolomics is a powerful new analytical approach to detect the metabolome of cells, tissue, or biofluids. Here, we report the application of (1)H nuclear magnetic resonance (NMR) combined with principal components analysis to discriminate pancreatic cancer patients from healthy controls based on metabolomic profiling of the serum. The metabolic analysis revealed significant lower of 3-hydroxybutyrate, 3-hydroxyisovalerate, lactate, and trimethylamine-N-oxide as well as significant higher level of isoleucine, triglyceride, leucine, and creatinine in the serum from pancreatic cancer patients compared to that of healthy controls. Our data demonstrate that the subtle differences in metabolite profiles in serum of pancreatic cancer patients and that of healthy subjects as a result of physiological and pathological variations could be identified by NMR-based metabolomics and exploited as metabolic markers for the early detection of pancreatic cancer.
Human pancreatic ductal adenocarcinoma (PDAC) exhibits marginal responses to anti-PD-1/PD-L1 immunotherapy and its mechanism remains poorly understood. We have investigated the effect of anti-PD-L1 and c-Myc inhibition in PDAC. Using 87 patients with PDAC from our hospital database we found a significant correlation between the expression of PD-L1 and c-Myc. Moreover, the expression of both PD-L1 and c-Myc was associated with poor overall survival. In addition, we confirmed this finding with the PDAC patients in the TCGA database. Using several PDAC cell lines we demonstrated a significant correlation between the expression of PD-L1 and c-Myc. We also found that expression of PD-L1 correlated with high-grade histology. JQ1, an inhibitor of c-Myc inhibited PD-L1 expression and tumor growth. Using xenograft models, we demonstrated that the combination of JQ1 and anti-PD-L1 antibody exerted synergistic inhibition of PDAC growth. Our data demonstrated that the expression of PD-L1 and c-Myc may be helpful prognostic biomarkers, and their inhibition may potentially serve as an effective treatment for PDAC.
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