Utility of TMPRSS4 as a Prognostic Biomarker and Potential Therapeutic Target in Patients with Gastric Cancer

Transmembrane serine protease 4 expression in the prognosis of radical resection for biliary tract cancer

BACKGROUND

Recent advancements in biliary tract cancer (BTC) treatment have expanded beyond surgery to include adjuvant therapy, yet the prognosis remains poor. Identifying prognostic biomarkers could enhance the assessment of patients who have undergone radical resection for BTC.

AIM

To determine transmembrane serine protease 4 (TMPRSS4) utility as a prognostic biomarker of radical resection for BTC.

METHODS

Medical records of patients who underwent radical resection for BTC, excluding intrahepatic cholangiocarcinoma, were retrospectively reviewed. The associations between TMPRSS4 expression and clinicopathological factors, overall survival, and recurrence-free survival were analyzed.

RESULTS

Among the 85 patients undergoing radical resection for BTC, 46 (54%) were TMPRSS4-positive. The TMPRSS4-positive group exhibited significantly higher preoperative carbohydrate antigen 19-9 (CA19-9) values and greater lymphatic invasion than the TMPRSS4-negative group (P = 0.019 and 0.039, respectively). Postoperative overall survival and recurrence-free survival were significantly worse in the TMPRSS4-positive group (median survival time: 25.3 months vs not reached, P < 0.001; median survival time: 28.7 months vs not reached, P = 0.043, respectively). Multivariate overall survival analysis indicated TMPRSS4 positivity, pT3/T4, and resection status R1 were independently associated with poor prognosis (P = 0.032, 0.035 and 0.030, respectively). TMPRSS4 positivity correlated with preoperative CA19-9 values ≥ 37 U/mL and pathological tumor size ≥ 30 mm (P = 0.016 and 0.038, respectively).

CONCLUSION

TMPRSS4 is a potential prognostic biomarker of radical resection for BTC.

Effects of transmembrane serine protease 4 on the survival in patients with pancreatic ductal adenocarcinoma undergoing surgery followed by adjuvant chemotherapy

PURPOSE

The transmembrane serine protease 4 (TMPRSS4) gene is upregulated in various human cancers. However, its biological functions in pancreatic ductal adenocarcinoma remain unclear. We examined the expression of TMPRSS4 in pancreatic ductal adenocarcinoma tissues and its correlation with clinicopathological parameters in patients with pancreatic ductal adenocarcinoma who underwent surgery.

METHODS

The TMPRSS4 expression was immunohistochemically examined in 81 PDAC patients with pancreatic ductal adenocarcinoma. We analyzed the association between the TMPRSS4 expression and clinicopathological factors, the recurrence-free survival (RFS), and the overall survival (OS) and examined the effect of TMPRSS4 expression on cell migration and sensitivity to 5-fluorouracil.

RESULTS

The expression rate of TMPRSS4 in the samples was 62.9% (51/81). The TMPRSS4 expression was not correlated with any clinicopathological feature. The five-year overall and recurrence-free survival rates were significantly lower in the TMPRSS4-positive group than in the TMPRSS4-negative group. On a multivariate analysis, TMPRSS4 positivity, poorly differentiated histology, and non-adjuvant chemotherapy predicted a poor OS, while TMPRSS4 positivity and poorly differentiated histology predicted a poor RFS. TMPRSS4-silenced pancreatic ductal adenocarcinoma cells showed higher sensitivity to 5- fluorouracil than did the control siRNA-transfected cells.

CONCLUSIONS

TMPRSS4 can be considered a prognostic factor and therapeutic target for pancreatic ductal adenocarcinoma.

TMPRSS4, a type II transmembrane serine protease, as a potential therapeutic target in cancer

Proteases are involved in almost all biological processes, implying their importance for both health and pathological conditions. Dysregulation of proteases is a key event in cancer. Initially, research identified their role in invasion and metastasis, but more recent studies have shown that proteases are involved in all stages of cancer development and progression, both directly through proteolytic activity and indirectly via regulation of cellular signaling and functions. Over the past two decades, a novel subfamily of serine proteases called type II transmembrane serine proteases (TTSPs) has been identified. Many TTSPs are overexpressed by a variety of tumors and are potential novel markers of tumor development and progression; these TTSPs are possible molecular targets for anticancer therapeutics. The transmembrane protease serine 4 (TMPRSS4), a member of the TTSP family, is upregulated in pancreatic, colorectal, gastric, lung, thyroid, prostate, and several other cancers; indeed, elevated expression of TMPRSS4 often correlates with poor prognosis. Based on its broad expression profile in cancer, TMPRSS4 has been the focus of attention in anticancer research. This review summarizes up-to-date information regarding the expression, regulation, and clinical relevance of TMPRSS4, as well as its role in pathological contexts, particularly in cancer. It also provides a general overview of epithelial-mesenchymal transition and TTSPs.

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.

Establishing a cancer driver gene signature-based risk model for predicting the prognoses of gastric cancer patients

Despite the high prevalence of gastric cancer (GC), molecular biomarkers that can reliably detect GC are yet to be discovered. The present study aimed to establish a robust gene signature based on cancer driver genes (CDGs) that can predict GC prognosis. Transcriptional profiles and clinical data from GC patients were analyzed using univariate Cox regression analysis and the least absolute shrinkage and selection (LASSO)-penalized Cox regression analysis to select optimal prognosis-related genes for modeling. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analyses were done to assess the predictive power of this gene signature. A nomogram model for prediction of survival of GC patients was established using the CDG signature and clinical information, and a seven-CDG signature was identified. Risk scores were calculated using this signature, and patients were subsequently divided into high- and low-risk groups; high-risk patients in the training and validation datasets had poorer prognoses than low-risk patients. Cox regression analysis revealed that the CDG signature is an independent prognostic factor for GC. The signature and other clinical features were used to construct a nomogram for predicting overall GC patient survival. Calibration and decision curve analysis showed that the nomogram accurately predicted survival, highlighting its clinical utility. Thus, we established a novel CDG signature and nomogram for predicting GC prognosis, which may facilitate personalized treatment of GC.