BackgroundColorectal cancer (CRC) is the second leading cause of cancer-related deaths in the world. This study aimed to develop a urea cycle (UC)-related gene signature that provides a theoretical foundation for the prognosis and treatment of patients with CRC.MethodsDifferentially expressed UC-related genes in CRC were confirmed using differential analysis and Venn diagrams. Univariate Cox and least absolute shrinkage and selection operator regression analyses were performed to identify UC-related prognostic genes. A UC-related signature was created and confirmed using distinct datasets. Independent prognostic predictors were authenticated using Cox analysis. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts algorithm and Spearman method were applied to probe the linkage between UC-related prognostic genes and tumor immune-infiltrating cells. The Human Protein Atlas database was used to determine the protein expression levels of prognostic genes in CRC and normal tissues. Verification of the expression levels of UC-related prognostic genes in clinical tissue samples was performed using real-time quantitative polymerase chain reaction (qPCR).ResultsA total of 49 DEUCRGs in CRC were mined. Eight prognostic genes (TIMP1, FABP4, MMP3, MMP1, CD177, CA2, S100P, and SPP1) were identified to construct a UC-related gene signature. The signature was then affirmed using an external validation set. The risk score was demonstrated to be a credible independent prognostic predictor using Cox regression analysis. Functional enrichment analysis revealed that focal adhesion, ECM-receptor interaction, IL-17 signaling pathway, and nitrogen metabolism were associated with the UC-related gene signature. Immune infiltration and correlation analyses revealed a significant correlation between UC-related prognostic genes and differential immune cells between the two risk subgroups. Finally, the qPCR results of clinical samples further confirmed the results of the public database.ConclusionTaken together, this study authenticated UC-related prognostic genes and developed a gene signature for the prognosis of CRC, which will be of great significance in the identification of prognostic molecular biomarkers, clinical prognosis prediction, and development of treatment strategies for patients with CRC.
Background Mitophagy is used by eukaryotic cells to eliminate damaged mitochondria. The deregulation of this process can lead to an accumulation of dysfunctional mitochondria and is implicated in carcinogenesis and tumorigenesis. Despite increasing evidence that mitophagy is involved in the development of colon cancer, the role of mitophagy-related genes (MRGs) in colon adenocarcinoma (COAD) prognosis and treatment remains largely unknown. Methods Differential analysis was used to identify differentially expressed mitophagy-related genes associated with COAD and conduct key module screening. Cox regression and least absolute shrinkage selection operator, and other analyses were used to characterize prognosis-related genes and verify the feasibility of the model. The model was tested using GEO data and a nomogram was constructed for future clinical application. The level of immune cell infiltration and immunotherapy were compared between the two groups, and sensitivity to treatment with many commonly used chemotherapeutic agents was assessed in individuals with different risk factors. Finally, qualitative reverse transcription polymerase chain reaction and western blotting were performed to assess the expression of prognosis-related MRGs. Results A total of 461 differentially expressed genes were mined in COAD. Four prognostic genes, PPARGC1A, SLC6A1, EPHB2, and PPP1R17, were identified to construct a mitophagy-related gene signature. The feasibility of prognostic models was assessed using Kaplan-Meier analysis, time-dependent receiver operating characteristics, risk scores, Cox regression analysis, and principal component analysis. At 1, 3, and 5 years, the area under the receiver operating characteristic curves were 0.628, 0.678, and 0.755, respectively, for TCGA cohort, and 0.609, 0.634, and 0.640, respectively, for the GEO cohort. Drug sensitivity analysis found that camptothecin, paclitaxel, bleomycin, and doxorubicin were significantly different between low- and high-risk patients. The qPCR and western blotting results of clinical samples further confirmed the public database results. Conclusions This study successfully constructed a mitophagy-related gene signature with significant predictive value for COAD, informing new possibilities for the treatment of this disease.
Background:Mitophagy is the degradation of dysfunctional mitochondria. Its dysregulation can lead to an accumulation of damaged mitochondria and is implicated in carcinogenesis and tumorigenesis. Despite increasing evidence that mitophagy plays a role in colon tumorigenesis, the role of mitophagy-related genes (MRGs) in colon adenocarcinoma (COAD) prognosis and treatment remains largely unknown. Methods: As a first step, we extracted 1899 mitophagy-related genes from GeneCards and screened 461 differentially expressed genes from TCGA database. Using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology terms, we constructed a protein-protein interaction network, and conducted key module screening for the differential genes. Cox regression and least absolute shrinkage and selection operator analyses were used to identify PPARGC1A, SLC6A1, EPHB2 and PPP1R17 as prognosis-related genes. We assessed the feasibility of prognostic models using Kaplan-Meier analysis, time-dependent receiver operating characteristics, risk scores, Cox regression analysis, and principal component analysis. We tested the model using the GEO database and constructed nomograms for future clinical applications. At 1, 3, and 5 years, the area under the receiver operating characteristic curve for the TCGA cohort was 0.628, 0.678, and 0.755, whereas that of the GEO cohort was 0.609, 0.634, and 0.640. In addition, we compared immune cell infiltration between the two groups and assessed sensitivity to treatment with many commonly used chemotherapeutic agents in individuals with different risk factors. Finally, we performed qualitative reverse transcription polymerase chain reaction to examine the expression of prognosis-related MRGs. Results: In this study, we investigated the potential value of MRGs in patients with colon adenocarcinoma at the gene level. Utilizing The Cancer Genome Atlas (TCGA), we developed a mitophagy-related gene model to predict the prognosis of COAD, and examined this risk model using the Gene Expression Omnibus (GEO). Conclusions: This study has successfully constructed a mitophagy-related gene signature with significant predictive value for COAD and provides new possibilities for its future treatment.
Background Colorectal cancer (CRC) is a relatively common malignancy worldwide. The diagnosis of CRC at an early stage is difficult due to the lack of effective molecular biomarkers. Consequently, CRC is associated with a high mortality rate. Researchers have shown that coagulation-related factors promote or inhibit CRC progression. The purpose of this study was to identify coagulation-related genes (CRGs) with prognostic value that can potentially serve as therapeutic targets for CRC.Methods In this study, we used data of CRC samples from The Cancer Genome Atlas to identify differentially expressed CRGs. Next, the prognostic model was constructed using Cox proportional hazards regression analysis. The accuracy of the model and survival rate of patients with CRC were analyzed using receiver operating characteristic and Kaplan–Meier curves, respectively. In addition, a nomogram was developed to provide clinical guidance. Subsequently, the model was verified using data from the Gene Expression Omnibus. We evaluated the efficacy of immunotherapy and drug sensitivity using the Tumor Immune Dysfunction and Exclusion algorithms and the Genomics of Drug Sensitivity in Cancer, respectively. The expression of inhibin subunit beta B (INHBB) was knocked down using specific siRNA, and the oncogenic effect of INHBB in colon cancer cells was investigated in vitro.Results We identified seven prognostic CRGs, and constructed a model using five of those (TIMP1, MMP10, WDR72, INHBB, F2RL2). We used the median value to divide patients with CRC into high- and low-risk groups. In The Cancer Genome Atlas cohort, the survival time of patients in the latter group was longer, and the receiver operating characteristic area under curve was ≥ 0.6. The nomogram was successfully constructed. The results of the drug sensitivity analysis suggested that cisplatin, camptothecin, foretinib, tamoxifen, and vinblastine were more effective in the high-risk group versus the low-risk group; the inverse was observed for immunotherapy. Finally, knockdown of INHBB attenuated the proliferation, invasion, and migration of CRC cells in vitro.Conclusion We identified a novel CRG marker in CRC, which may be used as a predictive biomarker and lay the foundation for the personalized treatment of patients with CRC.
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