MiR‐138‐5p has been identified as a novel cancer‐related miRNA molecule in a variety of malignancies. However, the functions and mechanisms underlying miR‐138‐5p in colorectal carcinoma (CRC) remains largely unknown. In the present study, we analysed the biological effects and clinical significance of miR‐138‐5p in CRC. miR‐138‐5p expression was analysed by quantitative real‐time PCR in CRC tissues and cell lines. The effects of miR‐138‐5p on CRC cell growth was detected by cell proliferation, colony formation, cell cycle and cell apoptosis assays in vitro and in vivo. Our data showed that miR‐138‐5p was significantly downregulated in CRC. Downregulated miR‐138‐5p was related with poor prognosis in patients with CRC. miR‐138‐5p suppressed CRC growth but promoted cell death both in vitro and in vivo. Online predictions and integrated experiments identified that miR‐138‐5p targeted MCU, and downregulated miR‐138‐5p promoted mitochondrial biogenesis in CRC. In the light of the underlying mechanisms, our results indicated that downregulated miR‐138‐5p led to increased expression of MCU, which subsequently increased the production of ROS to promote CRC growth. Our results indicated that downregulated miR‐138‐5p strengthened mitochondrial biogenesis through targeting MCU, thus contributing to CRC cell growth, which may provide a potential therapeutic target for CRC.

Background: Mitochondrial calcium uniporter (MCU) complex has been reported to be associated with the tumor occurrence and development in varieties of malignancies. However, the role of MCU complex in colon adenocarcinoma (COAD) remains unclear. Therefore, we constructed a risk score signature based on the MCU complex members to predict the prognosis and response to immunotherapy for patients with COAD.

Colon adenocarcinoma (COAD), a common digestive system malignancy, involves crucial alterations in mitochondria-related genes influencing tumor growth, metastasis, and immune evasion. Despite limited studies on prognostic models for these genes in COAD, we established a mitochondrial-related risk prognostic model, including nine genes based on available TCGA and MitoCarta 3.0 databases, and validated its predictive power. We investigated the tumor microenvironment (TME), immune cell infiltration, complex cell communication, tumor mutation burden, and drug sensitivity of COAD patients using R language, CellChat, and additional bioinformatic tools from single-cell and bulk-tissue sequencing data. The risk model revealed significant differences in immune cell infiltration between high-risk and low-risk groups, with the strongest correlation found between tissue stem cells and macrophages in COAD. The risk score exhibited a robust correlation with TME signature genes and immune checkpoint molecules. Integrating the risk score with the immune score, microsatellite status, or TMB through TIDE analysis enhanced the accuracy of predicting immunotherapy benefits. Predicted drug efficacy offered options for both high- and low-risk group patients. Our study established a novel mitochondrial-related nine-gene prognostic signature, providing insights for prognostic assessment and clinical decision-making in COAD patients.

Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79–4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.