A pan-cancer analysis of the oncogenic and immunological roles of apolipoprotein F (APOF) in human cancer

Abstract

Background Apolipoprotein F (APOF) has been less studied in cancers. Thus, we aimed to perform a pan-cancer analysis of the oncogenic and immunological effects of APOF on human cancer. Methods A standardized TCGA pan-cancer dataset was downloaded. Differential expression, clinical prognosis, genetic mutations, immune infiltration, epigenetic modifications, tumor stemness and heterogeneity were analyzed. We conducted all analyses through software R (version 3.6.3) and its suitable packages. Results Overall, we found that the common cancers differentially expressed between tumor and normal samples and prognostic-associated were BRCA, PRAD, KIRP, and LIHC in terms of overall survival (OS), disease-free survival (DFS) and progression-free survival (PFS). The pan-cancer Spearman analysis showed that the mRNA expression of APOF was negatively correlated with four tumor stemness indexes (DMPss, DNAss, ENHss, and EREG-METHss) with statistical significance for PRAD and was positively correlated for LIHC. In terms of BRCA and PRAD patients, we found negative correlation of APOF with TMB, MSI, neo, HRD and LOH. The mutation frequencies of BRCA and LIHC were 0.3%. APOF expression was negatively correlated with immune infiltration and positively correlated with tumor purity for PRAD patients. The mRNA expression of APOF was negatively associated with most TILs for LIHC, B cells, CD4+ T cells, neutrophils, macrophages and dendritic cells, but was positively associated with CD8+ T cells. Conclusions Our pan-cancer study offered a relatively comprehensive understanding of the roles of APOF on BRCA, PRAD, KIRP, and LIHC.

A pan-cancer analysis of the oncogenic and immunological roles of transglutaminase 1 (TGM1) in human cancer

“…Consistent with our previous study (Feng et al 2022b ; Shi et al 2023 ), we obtained the TCGA pan-cancer dataset from the USCS database ( (Goldman et al 2020 ). In addition, we integrated the TCGA prognostic dataset from previous study and extracted the expression data of TGM1 in each sample (Liu et al 2018 ).…”