BackgroundActivin A, an important member of transforming growth factor-β superfamily, is reported to inhibit proliferation of mature hepatocyte. However, the effect of activin A on growth of hepatic progenitor cells is not fully understood. To that end, we attempted to evaluate the potential role of activin A in the regulation of hepatic progenitor cell proliferation.ResultsUsing the 2-acetaminofluorene/partial hepatectomy model, activin A expression decreased immediately after partial hepatectomy and then increased from the 9th to 15th day post surgery, which is associated with the attenuation of oval cell proliferation. Activin A inhibited oval cell line LE6 growth via activating the SMAD signaling pathway, which manifested as the phosphorylation of SMAD2/3, the inhibition of Rb phosphorylation, the suppression of cyclinD1 and cyclinE, and the promotion of p21WAF1/Cip1 and p15INK4B expression. Treatment with activin A antagonist follistatin or blocking SMAD signaling could diminish the anti-proliferative effect of activin A. By contrast, inhibition of the MAPK pathway did not contribute to this effect. Antagonizing activin A activity by follistatin administration enhanced oval cell proliferation in the 2-acetylaminofluorene/partial hepatectomy model.ConclusionActivin A, acting through the SMAD pathway, negatively regulates the proliferation of hepatic progenitor cells.

Background Chemoresistance is the main reason for the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Thus, there is an urgent need to screen out new targets and compounds to reverse chemotherapeutic resistance. Methods We established a bio-bank of human PDAC organoid models, covering a representative range of PDAC tumor subtypes. We screened a library of 1304 FDA-approved compounds to identify candidates efficiently overcoming chemotherapy resistance. The effects of the compounds were evaluated with a CellTiter-Glo-3D assay, organoid apoptosis assay and in vivo patient-derived xenograft (PDX), patient-derived organoid (PDO) and LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) genetically engineered mouse models. RNA-sequencing, genome editing, sphere formation assays, iron assays and luciferase assays were conducted to elucidate the mechanism. Results High-throughput drug screening of chemotherapy-resistant PDOs identified irbesartan, an angiotensin ‖ type 1 (AT1) receptor antagonist, which could synergistically enhance the ability of chemotherapy to kill PDAC cells. In vitro and in vivo validation using PDO, PDX and KPC mouse models showed that irbesartan efficiently sensitized PDAC tumors to chemotherapy. Mechanistically, we found that irbesartan decreased c-Jun expression by inhibiting the Hippo/YAP1 pathway and further overcame chemotherapy resistance in PDAC. We also explored c-Jun, a potential target of irbesartan, which can transcriptionally upregulate the expression of key genes involved in stemness maintenance (SOX9/SOX2/OCT4) and iron metabolism (FTH1/FTL/TFRC). More importantly, we observed that PDAC patients with high levels of c-Jun expression demonstrated poor responses to the current standard chemotherapy regimen (gemcitabine plus nab-paclitaxel). Moreover, patients with PDAC had significant survival benefits from treatment with irbesartan plus a standard chemotherapy regimen in two-center retrospective clinical cohorts and patients with high c-Jun expression exhibited a better response to combination chemotherapy. Conclusions Irbesartan could be used in combination with chemotherapy to improve the therapeutic efficacy in PDAC patients with high levels of c-Jun expression. Irbesartan effectively inhibited chemotherapy resistance by suppressing the Hippo/YAP1/c-Jun/stemness/iron metabolism axis. Based on our findings, we are designing an investigator-initiated phase II clinical trial on the efficacy and safety of irbesartan plus a standard gemcitabine/nab-paclitaxel regimen in the treatment of patients with advanced III/IV staged PDAC and are hopeful that we will observe patient benefits.

Objective: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy. CD8+ T cells, cancer stem cells (CSCs), and tumor budding (TB) have been significantly correlated with the outcome of patients with PDAC, but the correlations have been independently reported. In addition, no integrated immune-CSC-TB profile for predicting survival in patients with PDAC has been established. Methods: Multiplexed immunofluorescence and artificial intelligence (AI)-based comprehensive analyses were used for quantification and spatial distribution analysis of CD8+ T cells, CD133+ CSCs, and TB. In vivo humanized patient-derived xenograft (PDX) models were established. Nomogram analysis, calibration curve, time-dependent receiver operating characteristic curve, and decision curve analyses were performed using R software. Results: The established ‘anti-/pro-tumor’ models showed that the CD8+ T cell/TB, CD8+ T cell/CD133+ CSC, TB-adjacent CD8+ T cell, and CD133+ CSC-adjacent CD8+ T cell indices were positively associated with survival of patients with PDAC. These findings were validated using PDX-transplanted humanized mouse models. An integrated nomogram-based immune-CSC-TB profile that included the CD8+ T cell/TB and CD8+ T cell/CD133+ CSC indices was established and shown to be superior to the tumor-node-metastasis stage model in predicting survival of patients with PDAC. Conclusions: ‘Anti-/pro-tumor’ models and the spatial relationship among CD8+ T cells, CSCs, and TB within the tumor microenvironment were investigated. Novel strategies to predict the prognosis of patients with PDAC were established using AI-based comprehensive analysis and machine learning workflow. The nomogram-based immune-CSC-TB profile can provide accurate prognosis prediction for patients with PDAC.

Background and ObjectivesPretreatment immunological indicators and nutritional factors are associated with survival of many malignancies. This study aims to develop a prognostic nutritional score based on a combination of pretreatment lymphocyte, platelet, and prealbumin (Co‐LPPa) in patients with pancreatic cancer (PC) and to investigate the prognostic significance of this score.MethodsPatients who underwent pancreatectomy with a curative intent for PC were retrospectively enrolled. A pretreatment prognostic score was established by immunological indicators and nutritional factors that were independently associated with survival.ResultsPretreatment lymphocyte (<1.6 × 109/L), platelet (<160 × 109/L) and prealbumin (<0.23 g/L) were independently associated with poorer overall survival (OS) and recurrence‐free survival (RFS), and were used to create the Co‐LPPa score. The Co‐LPPa scores were inversely related to OS and RFS, and were able to stratify survival into four groups. The survival differences among the four groups were all significant. Besides, the Co‐LPPa scores could stratify survival independently of pathological prognostic factors. The Co‐LPPa score was superior to prognostic nutritional index and carbohydrate antigen 19‐9 in predicting OS and RFS.ConclusionThe Co‐LPPa score could accurately predict the prognosis of PC patients who underwent curative resection. The score may be helpful for preoperative therapeutic strategies.

The CeO2/CuO catalysts were synthesized by the hydrothermal method. The study shows that the particle-like CeO2 can self-assemble into the rod-like CeO2 during the hydrothermal procedure and the rods of CeO2 become shorter with the decrease of Ce/Cu molar ratio. The highly dispersed CuO is favorable for CO oxidation at lower temperature, and the bulk CuO can help CO oxidation at higher temperature due to the limitation of reduction.

Preoperative serum CA19-9 and histology grade could show the biological characteristics of pancreatic ductal adenocarcinoma (PDAC). This study aims to explore the combined effect of preoperative CA19-9 and histology grade on the prognosis of patients with PDAC. A total of 612 patients with PDAC undergoing curative pancreatectomy were retrospectively enrolled. 360 (58.8%) patients had preoperative CA19-9 > 112 U/ml and 348 (56.9%) patients had high histology grade. A biological risk model was established based on preoperative CA19-9 and histology grade. Prognostic analysis showed that biological risk based on preoperative CA19-9 and histology grade was independently associated with survival of PDAC patients. Then the biological risk was incorporated into the eighth edition of the TNM staging system and a modified TNM (mTNM) staging system was developed. The ROC curves showed that the area under curve(AUC) of the mTNM staging system was significantly greater than that of the TNM staging system. Biological risk based on preoperative CA19-9 and histology grade was an independent prognostic factor for patients with PDAC. Incorporating the biological risk into the TNM staging system could improve the the accuracy of the TNM staging system in predicting prognosis of patients with PDAC.

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Background: Preoperative serum CA19-9 and histology grade could reflect the biological characteristics of pancreatic ductal adenocarcinoma (PDAC). This study aims to explore the combined effect of preoperative CA19-9 and histology grade on the prognosis of patients with PDAC. Methods: A total of 612 patients with PDAC undergoing curative pancreatectomy were retrospectively enrolled. A biological risk model was established based on preoperative CA19-9 and histology grade. Prognostic significance of the biological risk was evaluated. Results: 360 (58.8%) patients had preoperative CA19-9>112 U/ml and 348 (56.9%) patients had high histology grade. Biological risk based on preoperative CA19-9 and histology grade was independently associated with survival of PDAC patients. The biological risk was incorporated into the eighth edition of the TNM staging system and a modified TNM (mTNM) staging system was developed. The ROC curves showed that the area under curve(AUC) of the mTNM staging system was significantly greater than that of the TNM staging system. Conclusion: Biological risk based on preoperative CA19-9 and histology grade was an independent prognostic factors for patients with PDAC. Incorporating the biological risk into the TNM staging system could improve the the accuracy of the TNM staging system in predicting prognosis of PDAC.