Upregulation of COL8A1 indicates poor prognosis across human cancer types and promotes the proliferation of gastric cancer cells

Shared and specific competing endogenous RNAs network mining in four digestive system tumors

Background

Digestive system malignancies, including esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), liver hepatocellular carcinoma (LIHC), and colon adenocarcinoma (COAD), pose significant global health challenges. Identifying shared and distinct regulatory mechanisms across these cancers can lead to improved therapies. This study aims to construct and compare competing endogenous RNA (ceRNA) networks across ESCA, STAD, LIHC, and COAD to identify RNA biomarkers that could serve as precision therapeutic targets to enhance clinical outcomes and advance personalized cancer care.

Methods

Clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to predict differentially expressed RNAs using the edgeR package. The ceRNA networks were constructed using the miRcode and ENCORI databases. Functional enrichment analysis and prognostic RNA screening were performed with ConsensusPathDB and univariate Cox regression analysis.

Results

we identified 6, 88, 55, and 41 RNA biomarkers in ESCA, STAD, LIHC, and COAD, respectively. Network analysis revealed shared and specific elements, with shared nodes enriched in cell cycle and mitotic processes. Several biomarkers, including HMGB3 and RGS16 (ESCA), COL4A1 and COL6A3 (STAD), CDCA5 and CDCA8 (LIHC), and LIMK1 and OSBPL3 (COAD), were consistent with prior studies, while novel biomarkers, such as C3P1 (ESCA), P2RY6 (STAD), and N4BP2L1 and PPP1R3B (LIHC), were discovered. Based on RNA correlation analysis, 1, 23, and 2 potential ceRNA regulatory axes were identified in STAD (PVT1/miR-490-3p/HMGA2), LIHC (DLX6-AS1/miR-139-5p/TOP2A, etc.), and COAD (STRCP1 & LINC00488/miR-142-3p/GAB1), respectively.

Conclusions

This study advances the understanding of ceRNA networks in digestive cancers, highlighting RNA biomarkers with potential as therapeutic targets for personalized treatment strategies.

High expression of COL8A1 predicts poor prognosis and promotes EMT in papillary thyroid cancer

Background

Collagen type VIII α 1 chain (COL8A1), a collagen type VIII protein, has been suggested to exert various functions in progression of multiple cancers. However, the effect of COL8A1 in papillary thyroid cancer (PTC) has not been elucidated.

Methods

The Cancer Genome Atlas (TCGA) databases were applied to investigate the COL8A1 expression and its clinical significance in PTC. The COL8A1 expression level was further validated using Gene Expression Omnibus (GEO) data and clinical paired PTC tissues. Additionally, the Kaplan-Meier curve was used to analyze the prognosis. The cell's migrative and invasive abilities were evaluated by wound healing assay and Transwell assay. CCK8 assays were used to evaluate the proliferation of PTC cells. Western blotting was conducted to explore the potential mechanisms involved in the pro-tumor role of COL8A1. The correlation between immune cell infiltration and COL8A1 was analyzed using the Tumor Immune Estimation Resource (TIMER) database and the single-sample GSEA (ssGSEA) method.

Results

We found that COL8A1 was upregulated in PTC (P < 0.05). High COL8A1 expression level was significantly associated with advanced T stage (P < 0.01), N stage (P < 0.001) and poor prognosis (P = 0.0142) in PTC. Furthermore, cell migration and invasion were significantly reduced following COL8A1 knockdown (P < 0.001). Mechanistic studies demonstrated that the epithelial-to-mesenchymal transition (EMT) related proteins (FN1, MMP9, MMP7, ZEB2 and Twist1) and phosphorylation of AKT and ERK were obviously down-regulated after COL8A1 knockdown (P < 0.01). Moreover, COL8A1 expression was correlated with immune cell infiltration.

Conclusion

Our study demonstrates that COL8A1 may function as an oncogene and a potential prognostic biomarker for PTC patients.

COL8A1 overexpression promotes glioma cell growth by activating focal adhesion kinase signaling cascade

We explored expression and biological roles of collagen type VIII alpha-1 chain (COL8A1) in glioma. Bioinformatics analyses unveiled COL8A1 overexpression within glioma tissues correlates with adverse clinical outcomes of patients. COL8A1 overexpression was also detected in local glioma tissues and various glioma cells. In primary and immortalized glioma cells, COL8A1 shRNA or knockout (KO) reduced cell viability, proliferation and mobility, disrupted cell cycle, and prompted apoptosis. While COL8A1 overexpression augmented the malignant behaviors in glioma cells. COL8A1 shRNA or KO in primary glioma cells decreased phosphorylation of FAK and downstream targets Akt and Erk1/2. Conversely, elevating COL8A1 expression increased their phosphorylations. In vivo experiments confirmed growth inhibition of patient-derived glioma xenografts within the mouse brain following COL8A1 KO. Hindered proliferation, lowered phosphorylation levels of FAK, Akt, and Erk1/2, as well as increased apoptosis were observed within the COL8A1 KO intracranial glioma xenografts. Thus, COL8A1 overexpression promotes glioma cell growth.

COL8A1 Regulates Esophageal Squamous Carcinoma Proliferation and Invasion Through PI3K/AKT Pathway

PURPOSE

Esophageal squamous carcinoma (ESCC) is a gastrointestinal malignancy with a high mortality, but the tumorigenesis is still unclear, restricting the target therapy development of ESCC. We explored the role of COL8A1 in ESCC development.

METHODS

Tissue microarrays were used to investigate the expression level of COL8A1 in ESCC tissues. The association between COL8A1 and the overall survival of ESCC patients was assessed. The effect of differential COL8A1 expression on tumor growth was investigated by the xenograft model. The regulation of COL8A1 on tumor growth, migration, and invasion was studied by using ESCC cell lines. The signal transduction pathways involved in COL8A1 were bioinformatically profiled and validated.

RESULTS

The COL8A1 was significantly expressed in cancerous tissues and was associated with poor prognosis in patients with ESCC. In vivo, the tumor growth obviously declined after inhibition of the COL8A1 expression. The abilities of cell proliferation and invasion were both decreased when the expression of COL8A1 was knockdown in ESCC cell line. Furthermore, we found the inactivation of the PI3K/AKT pathway that was mediated by knockdown of COL8A1 in ESCC cells, which was reversed with COL8A1 overexpression, whereas the cell proliferation and invasion ability were restored.

CONCLUSIONS

This is the first report that COL8A1 promote ESCC progression, which hopefully will provide a theoretical basis for clinical targeting of ESCC.

Molecular prognostic of nine parthanatos death-related genes in glioma, particularly in COL8A1 identification

Post-operative progression and chemotherapy resistance are the main causes of treatment failure in glioma patients. There is a lack of ideal prediction models for post-operative glioma patient progression and drug sensitivity. We aimed to develop a prognostic model of parthanatos mRNA biomarkers for glioma outcomes. A total of 11 parthanatos genes were obtained from ParthanatosCluster database. ConsensusClusterPlus and R "Limma" package were used to cluster The Cancer Genome Atlas (TCGA)-glioma cohort and analyze the differential mRNAs. Univariate Cox regression analysis, random survival forest model, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to determine the nine ParthanatosScore prognostic genes combination. ParthanatosScore was verified by 656 patients and 979 patients in TCGA and CGCA-LGG/GBM datasets. Differences in genomic mutations, tumor microenvironments, and functional pathways were assessed. Drug response prediction was performed using pRRophetic. Kaplan-Meier survival analysis was analyzed. Finally, COL8A1 was selected to evaluate its potential biological function and drug sensitivity of temozolomide and AZD3759 in glioma cells. ParthanatosScore obtained a combination of nine glioma prognostic genes, including CD58, H19, TNFAIP6, FTLP3, TNFRSF11B, SFRP2, LOXL1, COL8A1, and FABP5P7. In the TCGA-LGG/GBM dataset, glioma prognosis was poor in high ParthanatosScore. Low-score glioma patients were sensitive to AZD3759_1915, AZD5582_1617, AZD8186_1918, Dasatinib_1079, and Temozolomide_1375, while high-score patients were less sensitive to these drugs. Compared with HA cells, COL8A1 was significantly over-expressed in LN229 and U251 cells. Silencing COL8A1 inhibited the malignant characterization of LN229 and U251 cells. Temozolomide and AZD3759 also promoted parthanatos gene expression in glioma cells. Temozolomide and AZD3759 inhibited COL8A1 expression and cell viability and promoted apoptosis in glioma cells and PGM cells. ParthanatosScore can accurately predict clinical prognosis and drug sensitivity after glioma surgery. Silencing COL8A1 inhibited the malignant characterization. Temozolomide and AZD3759 inhibited COL8A1 expression and cell viability and promoted apoptosis and parthanatos gene expression, which is a target to improve glioma.

Identification and Verification of Potential Biomarkers in Gastric Cancer By Integrated Bioinformatic Analysis

Background: Gastric cancer (GC) is a common cancer with high mortality. This study aimed to identify its differentially expressed genes (DEGs) using bioinformatics methods.

Methods: DEGs were screened from four GEO (Gene Expression Omnibus) gene expression profiles. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. A protein–protein interaction (PPI) network was constructed. Expression and prognosis were assessed. Meta-analysis was conducted to further validate prognosis. The receiver operating characteristic curve (ROC) was analyzed to identify diagnostic markers, and a nomogram was developed. Exploration of drugs and immune cell infiltration analysis were conducted.

Results: Nine up-regulated and three down-regulated hub genes were identified, with close relations to gastric functions, extracellular activities, and structures. Overexpressed Collagen Type VIII Alpha 1 Chain (COL8A1), Collagen Type X Alpha 1 Chain (COL10A1), Collagen Triple Helix Repeat Containing 1 (CTHRC1), and Fibroblast Activation Protein (FAP) correlated with poor prognosis. The area under the curve (AUC) of ADAM Metallopeptidase With Thrombospondin Type 1 Motif 2 (ADAMTS2), COL10A1, Collagen Type XI Alpha 1 Chain (COL11A1), and CTHRC1 was >0.9. A nomogram model based on CTHRC1 was developed. Infiltration of macrophages, neutrophils, and dendritic cells positively correlated with COL8A1, COL10A1, CTHRC1, and FAP. Meta-analysis confirmed poor prognosis of overexpressed CTHRC1.

Conclusion: ADAMTS2, COL10A1, COL11A1, and CTHRC1 have diagnostic values in GC. COL8A1, COL10A1, CTHRC1, and FAP correlated with worse prognosis, showing prognostic and therapeutic values. The immune cell infiltration needs further investigations.

COL8A1 Predicts the Clinical Prognosis of Gastric Cancer and Is Related to Epithelial-Mesenchymal Transition

Background

Gastric cancer (GC) is the fifth most common malignant tumor and the third leading cause of cancer-related deaths. Because GC has the characteristics of high heterogeneity, unclear mechanism, limited treatment methods, and low five-year survival rate, it is necessary to find the prognostic biomarkers of GC and explore the mechanism of GC.

Methods

We first identified differentially expressed genes (DEGs) between gastric cancer and normal gastric cells through expression analysis. A protein-protein interaction (PPI) network was constructed to find tightly connected modules. We performed survival analysis on the DEGs in the modules to identify genes with prognostic significance. Gene set enrichment analysis (GSEA) was used to identify gene enrichment pathways. Finally, we used our own collected clinical samples of 119 gastric adenocarcinoma (STAD) tissues and 40 normal gastric tissues to perform immunohistochemical (IHC) staining to verify the differential expression of COL8A1 in STAD tissues and normal gastric tissues and its correlation with epithelial-mesenchymal transition- (EMT-) related factors.

Results

We identified 356 DEGs through differential expression analysis. Through PPI analysis and survival analysis, we determined that the collagen type VII alpha-1 chain (COL8A1) gene has prognostic significance. GSEA analysis showed that COL8A1 was significantly enriched in the EMT. IHC results showed that COL8A1 was upregulated in STAD tissues and could be used as an independent prognostic factor and was related to EMT.

Conclusion

This study shows that COL8A1 is related to the prognosis of GC patients and might affect the progress of GC through the EMT pathway. Therefore, COL8A1 may be a biomarker for predicting the prognosis of GC.

Pathogenesis of Enamel-Renal Syndrome Associated Gingival Fibromatosis: A Proteomic Approach

The enamel renal syndrome (ERS) is a rare disorder featured by amelogenesis imperfecta, gingival fibromatosis and nephrocalcinosis. ERS is caused by bi-allelic mutations in the secretory pathway pseudokinase FAM20A. How mutations in FAM20A may modify the gingival connective tissue homeostasis and cause fibromatosis is currently unknown. We here analyzed conditioned media of gingival fibroblasts (GFs) obtained from four unrelated ERS patients carrying distinct mutations and control subjects. Secretomic analysis identified 109 dysregulated proteins whose abundance had increased (69 proteins) or decreased (40 proteins) at least 1.5-fold compared to control GFs. Proteins over-represented were mainly involved in extracellular matrix organization, collagen fibril assembly, and biomineralization whereas those under-represented were extracellular matrix-associated proteins. More specifically, transforming growth factor-beta 2, a member of the TGFβ family involved in both mineralization and fibrosis was strongly increased in samples from GFs of ERS patients and so were various known targets of the TGFβ signaling pathway including Collagens, Matrix metallopeptidase 2 and Fibronectin. For the over-expressed proteins quantitative RT-PCR analysis showed increased transcript levels, suggesting increased synthesis and this was further confirmed at the tissue level. Additional immunohistochemical and western blot analyses showed activation and nuclear localization of the classical TGFβ effector phospho-Smad3 in both ERS gingival tissue and ERS GFs. Exposure of the mutant cells to TGFB1 further upregulated the expression of TGFβ targets suggesting that this pathway could be a central player in the pathogenesis of the ERS gingival fibromatosis. In conclusion our data strongly suggest that TGFβ -induced modifications of the extracellular matrix contribute to the pathogenesis of ERS. To our knowledge this is the first proteomic-based analysis of FAM20A-associated modifications.

Weighted Gene Co-expression Network Analysis Identifies a Cancer-Associated Fibroblast Signature for Predicting Prognosis and Therapeutic Responses in Gastric Cancer

Background: Cancer-associated fibroblasts (CAFs) are the most prominent cellular components in gastric cancer (GC) stroma that contribute to GC progression, treatment resistance, and immunosuppression. This study aimed at exploring stromal CAF-related factors and developing a CAF-related classifier for predicting prognosis and therapeutic effects in GC.

Methods: We downloaded mRNA expression and clinical information of 431 GC samples from Gene Expression Omnibus (GEO) and 330 GC samples from The Cancer Genome Atlas (TCGA) databases. CAF infiltrations were quantified by the estimate the proportion of immune and cancer cells (EPIC) method, and stromal scores were calculated via the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Stromal CAF-related genes were identified by weighted gene co-expression network analysis (WGCNA). A CAF risk signature was then developed using the univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. We applied the Spearman test to determine the correlation among CAF risk score, CAF markers, and CAF infiltrations (estimated via EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms). The TIDE algorithm was further used to assess immunotherapy response. Gene set enrichment analysis (GSEA) was applied to clarify the molecular mechanisms.

Results: The 4-gene (COL8A1, SPOCK1, AEBP1, and TIMP2) prognostic CAF model was constructed. GC patients were classified into high– and low–CAF-risk groups in accordance with their median CAF risk score, and patients in the high–CAF-risk group had significant worse prognosis. Spearman correlation analyses revealed the CAF risk score was strongly and positively correlated with stromal and CAF infiltrations, and the four model genes also exhibited positive correlations with CAF markers. Furthermore, TIDE analysis revealed high–CAF-risk patients were less likely to respond to immunotherapy. GSEA revealed that epithelial–mesenchymal transition (EMT), TGF-β signaling, hypoxia, and angiogenesis gene sets were significantly enriched in high–CAF-risk group patients.

Conclusion: The present four-gene prognostic CAF signature was not only reliable for predicting prognosis but also competent to estimate clinical immunotherapy response for GC patients, which might provide significant clinical implications for guiding tailored anti-CAF therapy in combination with immunotherapy for GC patients.

Natural Mutations Affect Structure and Function of gC1q Domain of Otolin-1

Otolin-1 is a scaffold protein of otoliths and otoconia, calcium carbonate biominerals from the inner ear. It contains a gC1q domain responsible for trimerization and binding of Ca²⁺. Knowledge of a structure-function relationship of gC1q domain of otolin-1 is crucial for understanding the biology of balance sensing. Here, we show how natural variants alter the structure of gC1q otolin-1 and how Ca²⁺ are able to revert some effects of the mutations. We discovered that natural substitutions: R339S, R342W and R402P negatively affect the stability of apo-gC1q otolin-1, and that Q426R has a stabilizing effect. In the presence of Ca²⁺, R342W and Q426R were stabilized at higher Ca²⁺ concentrations than the wild-type form, and R402P was completely insensitive to Ca²⁺. The mutations affected the self-association of gC1q otolin-1 by inducing detrimental aggregation (R342W) or disabling the trimerization (R402P) of the protein. Our results indicate that the natural variants of gC1q otolin-1 may have a potential to cause pathological changes in otoconia and otoconial membrane, which could affect sensing of balance and increase the probability of occurrence of benign paroxysmal positional vertigo (BPPV).