Pan-cancer analysis from multi-omics data reveals AAMP as an unfavourable prognostic marker

Angio-associated migratory cell protein (AAMP) is a protein that participates in cell migration and is reported to be involved in cancer progression. However, the molecular mechanism of AAMP in pan-cancer is not known.

We used multi-omics data, such as TIMER, TCGA, GTEx, CPTAC, HPA, and cBioPortal to analyze AAMP expression, and gene alteration in pan-cancer. Univariate Cox regression and Kaplan-Meier were utilized to explore prognostic significance of AAMP expression level. We applied Spearman analysis to investigate the correlation between AAMP and TMB, MSI, immune cell infiltration, immune checkpoints. Moreover, we mainly studied liver hepatocellular carcinoma(LIHC) to explore AAMP expression, clinical significance, and prognosis. Cox regression analysis was used to study independent factor to predict prognosis for AAMP in LIHC. GSEA was utilized to investigate the biological function for AAMP in LIHC.

AAMP was overexpressed in most cancers, and high AAMP expression was associated with worse overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) for LIHC and adrenocortical carcinoma (ACC). Moreover, AAMP had the highest mutation frequency in uterine corpus endometrial carcinoma (UCEC). AAMP was correlated with TMB and MSI in esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), lung squamous cell carcinoma (LUSC), and thyroid carcinoma (THCA). Then, we focus on LIHC to investigate the expression and prognosis of AAMP. AAMP overexpression was related to histological grade and pathological stage in LIHC. Multivariate Cox regression analysis revealed that AAMP overexpression was an independent adverse prognostic marker for LIHC. AAMP expression was correlated with immune cell infiltration and immune checkpoints in LIHC. Function enrichment analysis indicated the participation of AAMP in the cell cycle and DNA replication.

AAMP was a latent prognostic indicator for pan-cancer and had high potential as a biomarker for the diagnosis and prognosis of LIHC.