The identification of a PTEN-associated gene signature for the prediction of prognosis and planning of therapeutic strategy in endometrial cancer.

ABSTRACT

Background: Endometrial cancer (EC) is one of the most common malignancies among women. To improve the prognosis and treatment of EC, finding out a phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-associated prognostic signature would be beneficial. Methods: EC clinical data, genetic mutation data, and transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. To clarify the specific PTEN-associated signature, cox regression analyses were performed. The clinical value of the selected signature on the overall survival (OS) and the secretoglobin family 2A member 1 (SCGB2A1)-independent analysis, immune and functional analysis were investigated respectively. Results: Five hundred and fourteen EC samples were screened and PTEN mutation occupied 57%. Enrichment analysis indicated that mutant-type PTEN was enriched for pathways related to the upregulated human T-cell leukemia virus-1 (HTLV-1) infection and estrogen signaling pathway. SCGB2A1 was identified by cox regression analysis. Immune analysis exhibited significant immune infiltration with higher expression of T cells, B cells, and macrophage groups. Immune-checkpoint transcripts CD274 molecule (CD274), and cytotoxic T-lymphocyte associated protein 4 (CTLA4), hepatitis A virus cellular receptor 2 (HAVCR2), lymphocyte activation gene 3 (LAG3), programmed cell death 1 (PDCD1), PDCD1 ligand 2 (PDCD1LG2), T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domains (TIGIT), and sialic acid binding immunoglobulin like lectin 15 (SIGLEC15) were discovered statistically different. In addition, the low-SCGB2A1 group had worse OS than the high-SCGB2A1 group. SCGB2A1 showed significant area under the curve (AUC) values in a time-dependent receiver operating characteristic (ROC) analysis. Prevalence of microsatellite instability (MSI) was detected and SCGB2A1 showed a negative correlation with EC. Immune checkpoint blockade (ICB) response indicated a worse immune response in the low-SCGB2A1 group. The distribution of one-class linear regression (OCLR) scores reflected the negative correlation between messenger RNA expression-based stemness index (mRNAsi) and prognostic gene expression. Furthermore, several SCGB2A1-related signaling pathways in EC were identified. Conclusions: SCGB2A1 is a prognostic immunometabolic signature for patients with EC, which may help improve the prognosis and therapeutic effect.