Lipid metabolism genes are a prognostic indicator for rectal adenocarcinoma

Background: It is widely accepted that an alteration in lipid metabolism can serve as an essential hallmark for the growth and progression of various malignancies. However, the potential of lipid metabolism genes (LMGs) and related pathways as drug targets for rectal adenocarcinoma (READ) treatment and prognostic evaluation requires further investigation. The objective of the present study was to construct a prognostic prediction model for READ based on LMGs, and to evaluate its performance. Methods: The RNA-seq FPKM data and clinical data from READ patients and normal rectal tissues were downloaded from The Cancer Genome Atlas database. The LMGs were acquired from the Molecular Signatures Database. Subsequently, LMGs associated with the prognosis of READ were screened, and these genes were used to construct a prognostic prediction model for READ patients. The model was then subjected to rigorous evaluation. Furthermore, immune infiltration and limma analyses were performed in different clusters, and pathway enrichment analyses were performed on the screened differentially expressed genes (DEGs). Results: A prognostic prediction model was constructed based on 5 LMGs ( PLA2G2F , CBR1 , CHKB , ETNPPL , and ARV1 ) to classify READ into high- and low-risk groups, with the low-risk group exhibiting a higher survival rate. Consequently, the prognostic model demonstrated notable predictive capability. A total of 139 DEGs were identified, 38 of which were identified as being up-regulated and 101 as being downregulated. Furthermore, a comparison of the immune microenvironment and immune pathways between the low- and high-risk groups revealed significant disparities. Conclusions: Predictive models based on 5 lipid metabolism DEGs effectively predicted the prognosis of READ patients. Moreover, these 5 LMGs have potential as molecular biomarkers and therapeutic targets for READ patients.