A detailed understanding of the COL10A1 and SOX9 genes interaction based on potentially damaging mutations in gastric cancer using computational techniques

Oncogenic mechanisms of COL10A1 in cancer and clinical challenges (Review)

Collagen type X α1 chain (COL10A1), a gene encoding the α‑1 chain of type X collagen, serves a key role in conferring tensile strength and structural integrity to tissues. Upregulation of COL10A1 expression has been observed in different malignancies, including lung, gastric and pancreatic cancer, and is associated with poor prognosis. The present review provides an updated synthesis of the evolving biological understanding of COL10A1, with a particular focus on its mechanisms of action and regulatory functions within the context of tumorigenesis. For example, it has been established that increased COL10A1 expression promotes cancer progression by activating multiple signaling pathways, including the TGF‑β1/Smad, MEK/ERK and focal adhesion kinase signaling pathways, thereby inducing proliferation, invasion and migration. Additionally, COL10A1 has been demonstrated to induce epithelial‑mesenchymal transition and reshapes the extracellular matrix within tumor tissues. Furthermore, on the basis of methyltransferase‑like 3‑mediated N6‑methyladenosine methylation, COL10A1 intricately regulates the epitranscriptomic machinery, thereby augmenting its oncogenic role. However, although COL10A1 serves a pivotal role in gene transcription and the orchestration of tumor growth, the question of whether COL10A1 would serve as a viable therapeutic target remains a subject of scientific hypothesis requiring rigorous examination. Variables such as distinct tumor microenvironments and treatment associations necessitate further experimental validation. Therefore, a comprehensive assessment and understanding of the functional and mechanistic roles of COL10A1 in cancer may pave the way for the development of innovative cancer treatment strategies.

High Expression of COL10A1 Is an Independent Predictive Poor Prognostic Biomarker and Associated with Immune Infiltration in Advanced Gastric Cancer Microenvironment

Medical technology has become more and more sophisticated recently, which, however, fails to contribute to a better prognosis for patients suffering advanced gastric cancer (GC). Hence, new biomarkers specific to GC diagnosis and prognosis shall be identified urgently. This study screened differentially expressed genes (DEGs) between 375 GC samples and 32 paracancer tissue samples from TCGA datasets. The expression of Collagen type X alpha 1 (COL10A1) in GC was analyzed. The chi-square test assisted in analyzing the relevance of COL10A1 to the clinicopathologic characteristics. The Kaplan-Meier method helped to assess the survival curves and log-rank tests assisted in the examination of the differences. The Cox proportional hazard regression model served for analyzing the risk factors for GC. Then, we developed a nomogram that contained the COL10A1 expression and clinical information. Finally, how COL10A1 expression was associated with the immune infiltration was also evaluated. In this study, 7179 upregulated and 3771 downregulated genes were identified. Among them, COL10A1 expression was distinctly increased in GC specimens compared with nontumor specimens. High COL10A1 expression exhibited an obvious relation to tumor T and pathologic stage. ROC assays confirmed the diagnostic value of COL10A1 expression in screening GC samples from normal samples. Survival data displayed that patients with high COL10A1 expression exhibited a shorter OS and DSS than those with low COL10A1 expression. We obtained a predictive nomogram, which could better predict the COL10A1 expression by virtue of discrimination and calibration. The prognostic value of COL10A1 expression was further confirmed in GSE84426 datasets. Immune assays revealed that COL10A1 expression was associated with tumor-filtrating immune cells, like CD8 T cells, cytotoxic cells, DC, eosinophils, iDC, macrophages, mast cells, NK CD56dim cells, NK cells, pDC, T helper cells, Tem, Th1 cells, Th17 cells, and Treg. Overall, we firstly proved that COL10A1 may be a novel and valuable prognostic and diagnostic factor for GC patients. In addition, COL10A1 has potential to be an immune indicator in GC.

Development and Validation of a Novel Prognosis Prediction Model for Patients With Stomach Adenocarcinoma

Background: Stomach adenocarcinoma (STAD) is a significant global health problem. It is urgent to identify reliable predictors and establish a potential prognostic model.

Methods: RNA-sequencing expression data of patients with STAD were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Gene expression profiling and survival analysis were performed to investigate differentially expressed genes (DEGs) with significant clinical prognosis value. Overall survival (OS) analysis and univariable and multivariable Cox regression analyses were performed to establish the prognostic model. Protein–protein interaction (PPI) network, functional enrichment analysis, and differential expression investigation were also performed to further explore the potential mechanism of the prognostic genes in STAD. Finally, nomogram establishment was undertaken by performing multivariate Cox regression analysis, and calibration plots were generated to validate the nomogram.

Results: A total of 229 overlapping DEGs were identified. Following Kaplan–Meier survival analysis and univariate and multivariate Cox regression analysis, 11 genes significantly associated with prognosis were screened and five of these genes, including COL10A1, MFAP2, CTHRC1, P4HA3, and FAP, were used to establish the risk model. The results showed that patients with high-risk scores have a poor prognosis, compared with those with low-risk scores (p = 0.0025 for the training dataset and p = 0.045 for the validation dataset). Subsequently, a nomogram (including TNM stage, age, gender, histologic grade, and risk score) was created. In addition, differential expression and immunohistochemistry stain of the five core genes in STAD and normal tissues were verified.

Conclusion: We develop a prognostic-related model based on five core genes, which may serve as an independent risk factor for survival prediction in patients with STAD.