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.