Comprehensive Characterization of Transforming Growth Factor Beta Receptor 1 in Stomach Adenocarcinoma Identifies a Prognostic Signature for Predicting Clinical Outcomes and Immune Infiltrates

Abstract

Background Stomach adenocarcinoma (STAD) ranks as the third leading cause of cancer death worldwide. TGF‑β receptor 1 (TGFBR1), serving important roles in the TGF‑β family, the mechanisms whereby TGFBR1 governs tumor progression, immune cell infiltration in STAD remains unintelligible. Methods We used the TCGA, GEPIA, and HPA databases to explore TGFBR1 expression in STAD, the correlation between TGFBR1 expression and the clinical features. A receiver operating characteristic (ROC) curve and nomogram were constructed, and LASSO (the Least Absolute Shrinkage and Selection Operator)-selected features were used to build the TGFBR1 prognostic signature. GSEA is used to find the potential mechanism of TGFBR1 to promote the malignant process of STAD. We explored the influence of the TGFBR1 on the immune microenvironment of STAD through the TIMER2.0 and GEPIA database. Results In our study, TGFBR1 expression was significantly elevated in STAD and positively co-expression with pathologic stage, lymph node metastases (LNM) stage and histopathological grade. Nine factors with non-zero coefficients were identified by LASSO-selected features. Survival analysis revealed that patients with high TGFBR1 had shorter OS, FP, and PPS. Multivariate Cox analysis revealed that TGFBR1 was an independent prognostic factor for OS in STAD. The ROC analysis suggested that high diagnostic value with the AUC of TGFBR1 was 0.739. GSEA revealed that high TGFBR1 expression was correlated with pathway in cancer, MAPK signaling pathway, NOTCH signaling pathway, and VEGF-C production. ssGSEA showed that TGFBR1 is correlated with NK cells, Tem and Th17 cells. Furthermore, elevated TGFBR1 expression was found to be significantly correlated with several immune checkpoint and immune markers associated with immune cell subsets. Conclusion In summary, TGFBR1 could be a prognostic biomarker and an important regulator of immune cell infiltration in STAD. The present study revealed the probable underlying molecular mechanisms of TGFBR1 in STAD and provided a potential target for improving the prognosis.

Obesity-Dependent Association of the rs10454142 PPP1R21 with Breast Cancer

“…According to the information specified in the GeneCards database [113], in a number of rare cases, as a result of simultaneous transcription of nearby STON1 and GTF2A1L genes, a "fused" STON1-GTF2A1L mRNA is formed, which subsequently undergoes alternative splicing, which leads to the formation of various protein variants consisting of separate "elements" of stonin 1 proteins and a common TF IIA (a similar subunit 1), the function of which remains unexplored to date. A number of studies have shown the association of STON1-GTF2A1L RNA expression with such oncological diseases as ovarian cancer [114], cervical cancer [115], stomach [116,117], and colorectal cancer [104].…”

A degradome-related signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma based on machine learning procedure

“…However, the clinical outcome of STAD patients is discouraging. [ 3 ] In addition to the TNM analysis system, there are few effective markers to predict the prognosis of STAD patients. [ 4 ] As one of the most promising treatments for STAD, immunotherapy can be used to treat STAD patients who already have no chance of undergoing surgery.…”

Machine learning-based cell death signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma

“…[ 4 ] Though multidisciplinary approaches, including surgery, chemoradiotherapy, targeted therapy and immunotherapy, have been used for the treatment of STAD, the clinical outcomes of STAD patients are still poor. [ 5 ] Worse still, limited effective biomarkers for predicting the prognosis and therapy benefits of STAD patients have been put into clinical use. These grim data highlight the urgent need for markers to predict the prognosis and therapy benefits in STAD.…”