Ming Liu

Epoxide hydrolase 2 (EPHX2) is a key enzyme in fatty acid metabolism that metabolizes epoxyeicosatrienoic acids (EETs), lipid mediators involved in inflammation, angiogenesis, and carcinogenesis. However, the role and mechanism of EPHX2 in colorectal cancer (CRC) migration remain unclear. In this study, we employed an integrated approach of bioinformatics and functional experiments to examine EPHX2 expression, its clinical implications, and its mechanistic role in CRC migration. Our results showed that EPHX2 was significantly downregulated in CRC tissues, and its low expression correlated with poor prognosis. Overexpression of EPHX2 led to accumulation of HDHA, HEPE, and HETE in CRC cells, whereas loss of EPHX2 increased CXCL levels and suppressed mitochondrial biogenesis via EET accumulation. Furthermore, loss of EPHX2 promoted cell migration through ROS and CXCL signaling. Collectively, loss of EPHX2 accelerates cell migration via EET accumulation‐dependent chemokine elevation and mitochondrial biogenesis impairment in CRC. These findings reveal a novel metabolic‐mitochondrial axis in CRC progression and highlight EPHX2 as a potential therapeutic target.

Background: Hepatocellular carcinoma (HCC) develops from chronic inflammatory conditions to malignancy, with the immune microenvironment playing a significant role in this progression. However, the changes in the dynamic immune microenvironment during the transition from hepatitis to HCC remain poorly understood. Systematic analysis of stage-specific immune microenvironment alterations is essential for identifying therapeutic targets and creating precision strategies for HCC. Methods: Using single-cell RNA sequencing (scRNA-seq), we created dynamic transcriptome maps of the immune microenvironment across healthy liver, hepatitis, cirrhosis, and HCC stages. Cell–cell communication, trajectory, and enrichment analyses were utilized to characterize relationships between clusters. TCGA-LIHC data were used to validate gene expression and its prognosis. The spatial distribution of ligand–receptor complexes in HCC was confirmed by spatial transcriptomics and multiplexed immunofluorescence. The effects of the tumor microenvironment on cancer cell behavior were examined using co-immunoprecipitation and cell co-culture assays. Finally, the impact of the immune microenvironment on in vivo tumor progression was evaluated using a mouse transplantation model. Results: We identified specific immune cell clusters across HCC progression and revealed significant correlations between the abundance of immune cells (macrophages, B cells)and fibroblasts with disease severity. Crosstalk between SPP1 ⁺ macrophages and ITGA5 ⁺ fibroblasts was observed explicitly in HCC. In vitro and in vivo data demonstrated that the SPP1-ITGA5 interaction triggered the secretion of MMP2 by fibroblasts, thereby promoting malignant progression in HCC. Conclusions: We present a dynamic transcriptional profile of immune microenvironment evolution during HCC development, aiding in the refinement of diagnostics and the optimization of therapy strategies.

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.

Background and Aim: Cardiovascular diseases (CVD), including coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), and ischemic stroke (IS), are major causes of morbidity and mortality worldwide. Immune cells play crucial roles in CVD, but causal links between immune cell subtypes and CVD risk remain unclear. This study used Mendelian randomization (MR) to investigate these associations. Methods and Results: Exposure data were analyzed with a P < 1 × 10–5 threshold, excluding linkage disequilibrium SNPs. MR of 731 immune cell types used the inverse variance weighted (IVW) method, with pleiotropy and heterogeneity tests. Lipid profiles (HDL, LDL, VLDL, triglycerides) were assessed as mediators. Increased CD27 on unswitched memory B cells, CD28– DN T cells, and CX3CR1 on CD14– CD16+ monocytes raised CVD risk, while CD28 on Tregs and HLA DR++ monocytes were protective. For CAD, CD24+ CD27+ %B cells and SSC-A on HLA DR+ NK cells were protective, with certain T cells increasing risk. Similar trends were observed for MI, AF, and IS. Reverse MR showed no CVD effects on these positive immune traits. Lipid profiles mediated CVD risk, with HDL protective and LDL, VLDL, and triglycerides increasing risk. Mediation analyses showed LDL and triglycerides partially mediated CX3CR1-monocyte effects on MI risk. Functional enrichment identified cytokine signaling and inflammation in CVD. Conclusions: Our findings highlight immune cell subtypes and lipid traits in CVD risk. Regulatory T cells and protective phenotypes are therapeutic targets, while LDL and triglycerides mediate immune-disease pathways, emphasizing immune-lipid interactions for targeted therapies.

Background: Neuroinflammation represents a central pathological mechanism in Alzheimer's disease (AD). Lipopolysaccharide (LPS) is a potent inducer of neuroinflammation and demonstrates elevated circulating levels in AD patients. Objective: This study aims to investigate the genetic association between serum LPS activity level, inflammatory proteins and AD. Methods: A two-sample mendelian randomization (MR) analysis was performed to explore the causal effect of serum LPS activity level and 91 inflammatory proteins on AD, including 1, 260, 136 sporadic AD and 2, 838, 825 familial AD patients, respectively. Meta-analysis was conducted on multiple datasets to determine statistically significant results that was initially observed in one dataset. Results: Serum LPS activity level is a risk factor for early onset sporadic AD with OR = 1.392, 95% CI: 1.038–1.869. In most other sporadic AD datasets, LPS shows a trend of increasing the risk of AD onset. After meta-analysis in 10 independent datasets, no association between LPS and sporadic AD was observed. In most familial AD datasets, LPS level demonstrated a trend of decreasing AD risk in MR analysis, however, meta-analysis of the combined 8 datasets showed no statistically significant difference. Two inflammatory proteins, AXIN1 and IL-1 alpha, were identified as significant risk factors for sporadic AD. Conclusions: This study suggested that serum LPS activity level may present a risk effect in early onset sporadic AD. Two inflammatory proteins AXIN1 and IL-1 alpha were associated with the risk of sporadic AD. These findings provide a new perspective for the early diagnosis and treatment of sporadic and familial AD.

Background Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, characterized by high recurrence and mortality rates. Specific CD8⁺ T cells have a central role in pathogenesis of HCC by recognizing and destroying tumor cells. Method Common CD8 + T cell signatures were obtained from bulk RNA-seq and scRNA-seq analysis. Univariate Cox regression, LASSO regression, and Multivariate Cox regression was sequentially utilized on the CD8 + T cell signatures to establish a risk scoring model. Prognostic value of the model was verified in the external datasets GSE14520. Immune analysis and Drug Sensitivity analysis was performed in high risk and low risk group. Immunohistochemistry (IHC) was employed to ascertain the expression of model genes in 10 HCC samples and corresponding adjacent tissues. Result A three-gene risk scoring model (KLRB1, RGS2 and TNFRSF1B) was constructed from CD8⁺ T cell common signatures. In terms of immune cell infiltration, low-risk group demonstrated higher abundance of CD8⁺ T cells, and M1 Macrophages., whereas high-risk group demonstrated higher abundance of M2 Macrophages and resting mast cells. As for immunotherapy, patients in high-risk group may not respond well. BMS-754807, Gemcitabine, et al exhibited sensitive to patients in low-risk group, AZD6482 and SB505124 may serve as novel potential targeted drugs for patients in high-risk group. In comparison to normal tissues, KLRB1, RGS2, and TNFRSF1B exhibited a reduced expression level, confirming our findings in publicly available databases. Conclusion In conclusion, we constructed a CD8⁺ T cell-associated risk scoring model consisting of KLRB1, RGS2 and TNFRSF1B to predict prognosis and provide potential drugs for HCC treatment.

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.

Esophageal carcinoma (ESCA) is a common and lethal malignant tumor worldwide. The mitochondrial biomarkers were useful in finding significant prognostic gene modules associated with ESCA owing to the role of mitochondria in tumorigenesis and progression. In the present work, we obtained the transcriptome expression profiles and corresponding clinical information of ESCA from The Cancer Genome Atlas (TCGA) database. Differential expressed genes (DEGs) were overlapped with 2030 mitochondria-related genes to get mitochondria-related DEGs. The univariate cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox regression were sequentially used to define the risk scoring model for mitochondria-related DEGs, and its prognostic value was verified in the external datasets GSE53624. Based on the risk score, ESCA patients were divided into high- and low-risk groups. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to further investigate the difference between low- and high-risk groups at the gene pathway level. CIBERSORT was used to evaluate immune cell infiltration. The mutation difference between high- and low-risk groups was compared by using the R package “Maftools”. Cellminer was used to assess the association between the risk scoring model and drug sensitivity. As the most important outcome of the study, a 6-gene risk scoring model (APOOL, HIGD1A, MAOB, BCAP31, SLC44A2, and CHPT1) was constructed from 306 mitochondria-related DEGs. Pathways including the “hippo signaling pathway” and “cell–cell junction” were enriched in the DEGs between high and low groups. According to CIBERSORT, samples with high-risk scores demonstrated a higher abundance of CD4⁺ T cells, NK cells, M0 and M2 macrophages, and a lower abundance of M1 macrophages. The immune cell marker genes were correlated with the risk score. In mutation analysis, the mutation rate of TP53 was significantly different between the high- and low-risk groups. Drugs with a strong correlation with the risk model were selected. In conclusion, we focused on the role of mitochondria-related genes in cancer development and proposed a prognostic signature for individualized integrative assessment.