Human gut microbiota play an essential role in both healthy and diseased states of humans. In the past decade, the interactions between microorganisms and tumors have attracted much attention in the efforts to understand various features of the complex microbial communities, as well as the possible mechanisms through which the microbiota are involved in cancer prevention, carcinogenesis, and anti-cancer therapy. A large number of studies have indicated that microbial dysbiosis contributes to cancer susceptibility via multiple pathways. Further studies have suggested that the microbiota and their associated metabolites are not only closely related to carcinogenesis by inducing inflammation and immune dysregulation, which lead to genetic instability, but also interfere with the pharmacodynamics of anticancer agents. In this article, we mainly reviewed the influence of gut microbiota on cancers in the gastrointestinal (GI) tract (including esophageal, gastric, colorectal, liver, and pancreatic cancers) and the regulation of microbiota by diet, prebiotics, probiotics, synbiotics, antibiotics, or the Traditional Chinese Medicine. We also proposed some new strategies in the prevention and treatment of GI cancers that could be explored in the future. We hope that this review could provide a comprehensive overview of the studies on the interactions between the gut microbiota and GI cancers, which are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, diagnosis, and treatment.

Identifying patients at high risk of diabetic kidney disease (DKD) helps improve clinical outcome. PURPOSETo establish a model for predicting DKD. DATA SOURCESThe derivation cohort was from a meta-analysis. The validation cohort was from a Chinese cohort. STUDY SELECTIONCohort studies that reported risk factors of DKD with their corresponding risk ratios (RRs) in patients with type 2 diabetes were selected. All patients had estimated glomerular filtration rate (eGFR) ‡60 mL/min/1.73 m 2 and urinary albumin-tocreatinine ratio (UACR) <30 mg/g at baseline. DATA EXTRACTIONRisk factors and their corresponding RRs were extracted. Only risk factors with statistical significance were included in our DKD risk prediction model. DATA SYNTHESISTwenty cohorts including 41,271 patients with type 2 diabetes were included in our meta-analysis. Age, BMI, smoking, diabetic retinopathy, hemoglobin A 1c , systolic blood pressure, HDL cholesterol, triglycerides, UACR, and eGFR were statistically significant. All these risk factors were included in the model except eGFR because of the significant heterogeneity among studies. All risk factors were scored according to their weightings, and the highest score was 37.0. The model was validated in an external cohort with a median follow-up of 2.9 years. A cutoff value of 16 was selected with a sensitivity of 0.847 and a specificity of 0.677. LIMITATIONSThere was huge heterogeneity among studies involving eGFR. More evidence is needed to power it as a risk factor of DKD. CONCLUSIONSThe DKD risk prediction model consisting of nine risk factors established in this study is a simple tool for detecting patients at high risk of DKD.

Background:The protumor activities of cancer-associated fibroblasts (CAFs) suggest that they are potential therapeutic targets for the treatment of cancer. The mechanism of CAF heterogeneity in gastric cancer (GC) remains unclear and has slowed translational advances in targeting CAFs. Therefore, a comprehensive understanding of the classification, function, activation stage, and spatial distribution of the CAF subsets in GC is urgently needed. Methods: In this study, the characteristics of the CAF subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by the CAF subsets were analyzed by performing single-cell RNA sequencing of eight pairs of GC and adjacent mucosal (AM) samples. The spatial distribution of the CAF subsets in different Lauren subtypes of GC, as well as the neighborhood relations between these CAF subsets and the protumor immune cell subsets were evaluated by performing multistaining registration. Results: Tumor epithelial cells exhibited significant intratumor and intertumor variabilities, while CAFs mainly exhibited intratumor variability. Moreover, we identified four CAF subsets with different properties in GC. These four CAF subsets shared similar properties with their resident fibroblast counterparts in the adjacent mucosa but also exhibited enhanced protumor activities. Additionally, two CAF subsets, inflammatory CAFs (iCAFs) and extracellular matrix CAFs (eCAFs), communicated with adjacent immune cell subsets in the GC TME. iCAFs interacted with T cells by secreting interleukin (IL)-6 and C-X-C motif chemokine ligand 12 (CXCL12), while eCAFs correlated with M2 macrophages via the expression of periostin (POSTN). eCAFs, which function as a pro-invasive CAF subset, decreased the overall survival time of patients with GC. Conclusions: iCAFs and eCAFs not only exhibited enhanced pro-invasive activities but also mobilized the surrounding immune cells to construct a tumor-favorable microenvironment. Therefore, inhibiting their activation restrains the GC 'seed' and simultaneously improves the 'GC' soil, suggesting that it represents a promising therapeutic strategy for the treatment of GC.

Purpose: No antiangiogenic treatment is yet approved for extrapancreatic neuroendocrine tumors (NET). Surufatinib (HMPL-012, previously named sulfatinib) is a small-molecule inhibitor targeting vascular endothelial growth factor receptors, fibroblast growth factor receptor 1 and colony-stimulating factor 1 receptor. We conducted a single-arm phase Ib/II study of surufatinib in advanced NETs.Patients and Methods: Patients with histologically welldifferentiated, low or intermittent grade, inoperable or metastatic NETs were enrolled into a pancreatic or extrapancreatic NET cohort. Patients were treated with surufatinib 300 mg orally, once daily. The primary endpoints were safety and objective response rate (ORR) according to Response Evaluation Criteria in Solid Tumors (version 1.1).Results: Of the 81 patients enrolled, 42 had pancreatic NETs and 39 had extrapancreatic NETs. Most patients had radiologic progression within 1 year prior to enrollment (32 patients in each cohort). In the pancreatic and extrapancreatic NET cohorts, ORRs were 19% [95% confidence intervals (CI), 9-34] and 15% (95% CI, 6-31), disease control rates were 91% (95% CI, 77-97) and 92% (95% CI, 79-98), and median progression-free survival was 21.2 months (95% CI, 15.9-24.8) and 13.4 months (95% CI, 7.6-19.3), respectively. The most common grade !3 treatment-related adverse events were hypertension (33%), proteinuria (12%), hyperuricemia (10%), hypertriglyceridemia, and diarrhea (6% for each), and increased alanine aminotransferase (5%).Conclusions: Surufatinib showed encouraging antitumor activity and manageable toxicities in patients with advanced NETs. Two ongoing phase III studies, validating the efficacy of surufatinib in patients with NETs, will contribute to the clinical evidence.