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

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.

SCGB2A1 is a prognostic immunometabolic signature for patients with EC, which may help improve the prognosis and therapeutic effect.

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.

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.