A risk prediction model mediated by genes of APOD/APOC1/SQLE associates with prognosis in cervical cancer

Correlation study of serum lipid levels and lipid metabolism-related genes in cervical cancer

Objective

Lipid metabolism plays an important role in cancer. The aim of this study was to investigate the relationship between lipid metabolism and the development of cervical cancer, and to explore the prognostic significance of lipid metabolism-related genes in patients with cervical cancer.

Methods

Initially, we retrospectively collected data from 1589 cervical cancer patients treated at the Affiliated Hospital of Qingdao University, with 1589 healthy individuals from the physical examination center serving as the control group. The correlation between their serum lipid levels and cervical cancer was analyzed. Subsequently, leveraging public databases, we conducted comprehensive studies on lipid metabolism-related genes. Additionally, we analyzed RNA expression profiling and clinical information sourced from TCGA and GTEx databases. Finally, we established a prognostic model integrating 9 genes associated with lipid metabolism and generated a nomogram model using R. GO and KEGG were performed to explore the functions and pathways of lipid metabolism-related genes.

Results

Our findings revealed that patients with cervical cancer exhibited dyslipidemia, characterized by elevated levels of TC, TG, and LDL-C, alongside reduced HDL-C levels compared to controls (P<0.05). Interestingly, compared with early-stage patients, advanced patients had lower HDL-C level and higher LDL-C level. Regression analysis further highlighted high TC, TG, and LDL-C as significant risk factors for cervical cancer. Then a total of 188 lipid metabolism-related genes were identified and a prognostic signature based on 9 genes was established and validated. The results of the GO and KEGG functional analysis indicated that the lipid metabolism-related genes are primarily concentrated on pathways associated with fatty acid metabolism.

Conclusion

Our study underscores the varying degrees of dyslipidemia observed in patients with cervical cancer, emphasizing the relevance of serum lipids in disease development. Our prognostic riskScore model predicted the overall survival time of patients based on 9 genes associated with lipid metabolism. These 9 genes may be tumor biomarkers and new targets for the treatment of cervical cancer.

A Novel Eight-Gene Signature for Lipid Metabolism Predicts the Progression of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Recently, studies on the mechanisms underlying lipid metabolic reprogramming in cancer have increased. However, its significance in cervical cancer remains unclear. In the present study, a prognostic signature was constructed for patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) using the expression profiles of lipid metabolism-related genes (LMRGs). Furthermore, using various bioinformatics methods, a prognostic gene signature was developed for progression-free survival (PFS). This signature was externally validated using a cervical cancer dataset (GSE44001). The characteristics of the molecular subgroups of LMRGs were analyzed, and target LMRGs were identified via differential gene analysis of the expression profiles and weighted gene correlation network analysis. Thereafter, the identified target genes were used to develop the prognostic gene signature using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The performance of the LMRG signature was evaluated using Kaplan-Meier curves, time-dependent receiver operating characteristic curves, decision curve analysis, mutation landscapes, gene set enrichment analysis, and immune score calculation. As a result, a novel eight-LMRG signature comprising ALDH3B2, CERS3, FA2H, GLTP, NR1H3, PLIN3, SLC44A3, and SQLE was constructed. Using this gene signature, patients with CESC and significantly distinguished PFS were divided. This eight-LMRG signature exhibited independent prognostic potential and superior predictive performance compared with a previously developed 12-gene signature. Our findings suggest that our novel eight-LMRG signature contributes to the implementation of precision medicine strategies for managing patients with cervical cancer by facilitating CESC prognosis.

The macrophage-associated prognostic gene ANXA5 promotes immunotherapy resistance in gastric cancer through angiogenesis

Gastric cancer (GC) remains a predominant form of malignant tumor globally, necessitating innovative non-surgical therapeutic approaches. This investigation aimed to delineate the expression landscape of macrophage-associated genes in GC and to evaluate their prognostic significance and influence on immunotherapeutic responsiveness. Utilizing the CellMarker2.0 database, we identified 69 immune cell markers with prognostic relevance in GC, including 12 macrophage-specific genes. A Weighted Gene Co-Expression Network Analysis (WGCNA) isolated 3,181 genes correlated with these macrophage markers. The Cancer Genome Atlas (TCGA-STAD) dataset was employed as the training set, while data from the GSE62254 served as the validation cohort. 13 genes were shortlisted through LASSO-Cox regression to formulate a prognostic model. Multivariable Cox regression substantiated that the calculated risk score serves as an imperative independent predictor of overall survival (OS). Distinct macrophage infiltration profiles, pathway associations, treatment susceptibilities, and drug sensitivities were observed between high- and low-risk groups. The preliminary validation of ANXA5 in predicting the survival rates of GC patients at 1 year, 3 years, and 5 years, as well as its expression levels were higher and role in promoting tumor angiogenesis in GC through immunohistochemistry and angiogenesis experiments. In summary, macrophage-related genes were potentially a novel crosstalk mechanism between macrophages and endothelial cells in the tumor microenvironment, and the interplay between inflammation and angiogenesis might have also offered new therapeutic targets, providing a new avenue for personalized treatment interventions.