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Abstract Background This study aimed to predict metastasis risk and identify prognostic factors of gastrointestinal signet ring cell carcinoma (SRCC) using data from the SEER database, the largest cancer dataset in North America. Methods Data were obtained from the SEER database, covering 17 cancer registries from 2004 to 2020. Demographic and clinical data included sex, age, race, tumor location, size, pathological grade, stage, overall survival time, and treatment modalities. Statistical analyses were conducted using SPSS and R software. Propensity Score Matching (PSM) ensured comparable baseline characteristics between gastric cancer (GC) and colorectal cancer (CRC) groups. LASSO regression analysis identified predictors of metastasis, leading to the construction of predictive models using the lrm function in R. Nomograms were visualized with the “rms” package and assessed via ROC curves, calibration curves, and decision curve analysis (DCA). Cox regression analyses identified prognostic indicators for overall survival (OS), and Kaplan–Meier curves compared OS between high-risk and low-risk groups. Results From 2004 to 2020, 7680 SRCC patients were identified, including 4980 GC and 2700 CRC patients. CRC patients were older and had larger tumors, higher staging, and worse differentiation. Nomograms demonstrated good discriminative ability, with AUCs of 0.704 and 0.694 for GC, and 0.694 and 0.701 for CRC in training and validation cohorts, respectively. The DCA curve indicates that this predictive model has a high gain in predicting metastasis and OS. Conclusions The nomograms effectively predicted metastasis risk and OS in metastatic SRCC patients, offering clinical utility in stratifying patients and guiding treatment decisions, thereby enhancing personalized treatment approaches.

Abstract 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.

Abstract Background Intake of dietary fiber is associated with a reduced risk of inflammatory bowel disease. β-Glucan (BG), a bioactive dietary fiber, has potential health-promoting effects on intestinal functions; however, the underlying mechanism remains unclear. Here, we explore the role of BG in ameliorating colitis by modulating key bacteria and metabolites, confirmed by multiple validation experiments and loss-of-function studies, and reveal a novel bacterial cross-feeding interaction. Results BG intervention ameliorates colitis and reverses Lactobacillus reduction in colitic mice, and Lactobacillus abundance was significantly negatively correlated with the severity of colitis. It was confirmed by further studies that Lactobacillus johnsonii was the most significantly enriched Lactobacillus spp. Multi-omics analysis revealed that L. johnsonii produced abundant indole-3-lactic acid (ILA) leading to the activation of aryl hydrocarbon receptor (AhR) responsible for the mitigation of colitis. Interestingly, L. johnsonii cannot utilize BG but requires a cross-feeding with Bacteroides uniformis, which degrades BG and produces nicotinamide (NAM) to promote the growth of L. johnsonii. A proof-of-concept study confirmed that BG increases L. johnsonii and B. uniformis abundance and ILA levels in healthy individuals. Conclusions These findings demonstrate the mechanism by which BG ameliorates colitis via L. johnsonii–ILA–AhR axis and reveal the important cross-feeding interaction between L. johnsonii and B. uniformis. Video Abstract Graphical Abstract

Abstract Background Small nucleolar RNA host gene 7 (SNHG7) is a novel identified oncogenic gene in tumorigenesis. However, the role that SNHG7 plays in pancreatic cancer (PC) remains unclear. In this study, we aimed to investigate the functional effects of SNHG7 on PC and the possible mechanism. Methods The expression levels of SNHG7 in tissues and cell lines were measured by RT-qPCR. Cell viability, apoptosis, migration and invasion were examined to explore the function of SNHG7 on PC. Bioinformatics methods were used to predict the target genes. The mechanism was further investigated by transfection with specific si-RNA, miRNA mimics or miRNA inhibitor. Tumor xenograft was carried out to verify the effects of SNHG7 in vivo. Results We found that SNHG7 was overexpressed in both PC tissues and cell lines. High expression level of SNHG7 was correlated with the poor prognosis. SNHG7 knockdown inhibited the proliferation, migration and invasion of PC cells. Moreover, SNHG7 was found to regulate the expression of ID4 via sponging miR-342-3p. Additionally, this finding was supported by in vivo experiments. Conclusions LncRNA SNHG7 was overexpressed in PC tissues, and knockdown of SNHG7 suppressed PC cell proliferation, migration and invasion via miR-342-3p/ID4 axis. The results indicated that SNHG7 as a potential target for clinical treatment of PC.