Vitamin D deficiency is common among individuals with obesity and metabolic disorders. Evidence on its effect on metabolic markers remains inconclusive. This systematic review and meta-analysis aimed to evaluate the impact of vitamin D supplementation on lipid profile, glycemic control, and anthropometric indices. A comprehensive search of PubMed, Embase, Cochrane Library, Web of Science, and China Knowledge Network was conducted from inception to May 2024. Randomized controlled trials (RCTs) evaluating oral vitamin D supplementation in adults with overweight, obesity, or metabolic disorders were included. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Twenty-five RCTs (30 arms) were included. Overall, vitamin D supplementation did not significantly affect triglycerides (TG), total cholesterol (TC), HDL-C, LDL-C, fasting plasma glucose (FPG), insulin, HOMA-IR, HbA1c, waist circumference (WC), or body weight (p < 0.05). Subgroup analyses showed significant effects in certain populations, such as increased HDL-C in individuals with diabetes and elevated LDL-C in younger adults and males. A significant reduction in BMI was observed after adjusting for publication bias (p < 0.05). Heterogeneity varied across outcomes, and risk of bias was generally low, although some studies had unclear reporting. Vitamin D supplementation has limited effects on metabolic and anthropometric markers in adults with obesity or related metabolic disorders. Certain subgroups may benefit, warranting further targeted research.

Breast cancer metastasis claims the majority of breast cancer‐related deaths. Anoikis resistance is a key prerequisite for CTCs survival and metastasis. Previous studies have demonstrated that Nicotinamide N‐methyltransferase (NNMT) plays a crucial role in cancer metastasis and apoptosis resistance. However, whether NNMT participates in breast cancer CTCs anoikis remains unexplored. In this study, the upregulation of NNMT was observed in CTCs from breast cancer patients and mouse CTCs models. NNMT in detached breast cancer cells is induced by FAK‐STAT3 axis and resists anoikis through FAO activation, promoting CTCs survival. Mechanistically, NNMT promotes the expression of CPT1A and CD36 by suppressing PP2A methylation to enhance FAO. Furthermore, NNMT‐induced FAO accelerates ROS clearance by maintaining NADP+/NADPH balance. In vivo experiments show that NNMT‐knockdown, NNMT inhibitors and FAO inhibitors can all reduce lung metastases formation, suggesting that targeting NNMT‐FAO suppresses the metastatic potential of breast cancer. Our study revealed that the upregulation of NNMT is induced by FAK‐STAT3 axis, which contributes to CTCs anoikis resistance in breast cancer by activating FAO. Targeting NNMT may provide new therapeutic targets for metastatic breast cancer.

Background: Acute promyelocytic leukemia (APL) mainly harbors PML-RARα fusion gene, which is sensitive to all-trans retinoic acid (ATRA) and arsenic trioxide (ATO) treatment. However, APL harboring other RARα fusion genes exhibit different drug sensitivity. Here, we investigated the role and mechanism of TBLR1-RARα, a rare RARα fusion gene, on ATO treatment in leukemia cells.

A previous research study on differentiating gastric cancer (GC) into distinct subtypes or prognostic models was mostly based on GC tissues, which neglected the role of nontumour tissues in GC subtypes. The purpose of the research was to identify GC subtypes on the basis of tumour and adjacent nontumour tissues to assess the prognosis of GC patients. We characterized three GC subtypes on the basis of the immunologic and hallmark gene sets in GC and adjacent nontumour tissues: among them, the GC patients with subtype I had the longest survival time compared to patients with other subtypes. The classification was closely associated with T stage and pathological stage of GC patients. A prognostic model containing two gene sets was constructed by LASSO analysis. KaplanMeier analysis showed that patients in the high-risk group survived longer than those in the low-risk group and the two prognostic genes sets in the model were strongly correlated with survival status. Then, GO and KEGG analyses and PPI network show that nontumour and tumour tissues are influencing the prognosis of GC patients in separate manners. In summary, we emphasized the prognostic value of nontumour tissue in GC patients and proposed a novel insight that both changes in tumour and nontumour tissues should be taken into account when selecting a treatment strategy for GC.