Background: Previous researches have reported that tripartite motif-containing 44 (TRIM44) is related to the prognosis of multiple human tumors. This study was designed to systematically assess the prognostic value of TRIM44 in human malignancies and summarize its possible tumor-related mechanisms. Methods: The available databases were searched for eligible studies that evaluated the clinicopathological and prognostic roles of TRIM44 in patients with malignancies. The hazard ratios (HR) and odds ratios (OR) were combined to assess the predictive role of TRIM44 using Stata/SE 14.1 software. Results: A total of 1740 patients from thirteen original studies were finally included in this study. The results of the combined analysis showed that over-expression of TRIM44 protein was significantly correlated with shorter overall survival (OS) (HR = 1.94, 95% CI: 1.60-2.35) and worse disease-free survival (DFS) (HR = 2.13, 95% CI: 1.24-3.65) in cancer patients. Additionally, the combined ORs indicated that elevated expression level of TRIM44 protein was significantly associated with lymph node metastasis (OR = 2.69, 95% CI: 1.71-4.24), distant metastasis (OR = 10.35, 95% CI: 1.01-106.24), poor tumor differentiation (OR = 1.78, 95% CI: 1.03-3.09), increased depth of tumor invasion (OR = 2.72, 95% CI: 1.73-4.30), advanced clinical stage (OR = 2.75, 95% CI: 2.04-3.71), and recurrence (OR = 2.30, 95% CI: 1.34-3.95). Furthermore, analysis results using Gene Expression Profiling Interactive Analysis (GEPIA) showed that the expression level of TRIM44 mRNA was higher in most tumor tissues than in the corresponding normal tissues, and the relationship between TRIM44 mRNA level and prognosis in various malignant tumors also explored in GEPIA and OS analysis webservers. Conclusions: TRIM44 may serve as a valuable prognostic biomarker and a potential therapeutic target for patients with malignancies.
Introduction: Hepatocellular carcinoma (HCC) patients may benefit from chemotherapy, but drug resistance is an important obstacle to favorable prognoses. Overcoming drug resistance is an urgent problem to be solved.Methods: Differential expression analysis was used to identify long non-coding RNAs (LncRNAs) that differed in chemotherapy-sensitive and chemotherapy-resistant patients. Machine learning algorithms including random forest (RF), lasso regression (LR), and support vector machines (SVMs) were used to identify important chemotherapy-related LncRNAs. A back propagation (BP) network was then used to validate the predictive capacity of important LncRNAs. The molecular functions of hub LncRNAs were investigated via qRT-PCR and cell proliferation assay. Molecular-docking technique was used to explore candidate drug of targets of hub LncRNA in the model.Results: A total of 125 differentially expressed LncRNAs between sensitive and resistant patients. Seventeen important LncRNAs were identified via RF, and seven factors were identified via LR. With respect to SVM, the top 15 LncRNAs of AvgRank were selected. Five merge chemotherapy-related LncRNAs were used to predict chemotherapy resistance with high accuracy. CAHM was a hub LncRNA of model and expression high in sorafenib resistance cell lines. In addition, the results of CCK8 showed that the sensitivity of HepG2-sorafenib cells to sorafenib was significantly lower than that of HepG2; and the sensitivity of HepG2-sorafenib cells transfected with sh-CAHM was significantly higher than that of Sorafenib. In the non-transfection group, the results of clone formation experiments showed that the number of clones formed by HepG2-sorafenib cells treated with sorafenib was significantly more than that of HepG2; after HepG2-sorafenib cells were transfected with sh-CAHM, the number of clones formed by Sorafenib treatment was significantly higher than that of HepG2 cells. The number was significantly less than that of HepG2-s + sh-NC group. Molecular Docking results indicate that Moschus was candidate drug for target protein of CAHM.Conclusion: Five chemotherapy-related LncRNAs could predict drug resistance in HCC with high accuracy, and the hub LncRNA CAHM has potential as a new biomarker for HCC chemotherapy resistance.
Background: Previous researches reported that tripartite motif-containing 44 (TRIM44) were related to prognosis in multiple human tumors. This study was designed to systematically assess the prognostic value of TRIM44 in human malignancies and to describe its possible mechanisms of oncogenesis.Methods: available databases worldwide were searched for eligible studies that evaluated the clinicopathological and prognostic roles of TRIM44 in patients with malignancies.The hazard ratio (HR) and combined odds ratios (ORs) were combined to assess the predictive role of TRIM44 using Stata/SE 14.1 software.Results: A total of 1,740 patients from thirteen original studies were included in this study finally. The results of the combined analysis showed that over-expression of TRIM44 was significantly correlated with shorter overall survival (OS) in cancer patients (HR = 2.16, 95% CI: 1.65–2.83) as well as worse disease-free survival (DFS) (HR= 2.13 (95% CI 1.45 3.11). Additionally, the combined ORs indicated that elevated TRIM44 expression was significantly associated with lymph node metastasis (OR=2.69, 95% CI: 1.71–4.24), distant metastasis (OR=10.35, 95% CI: 1.01-106.24), poor tumor differentiation (OR=1.78, 95% CI: 1.03–3.09), high depth of tumor invasion (OR=2.72, 95% CI: 1.73–4.30), advanced clinical stage (OR=2.75, 95% CI: 2.04-3.71), and recurrence (OR=2.30, 95% CI: 1.34–3.95). Analysis of expression using GEPIA indicated that the expression of TRIM44 was higher in most tumor tissues than the corresponding normal tissues.Survival analysis indicated high levels of TRIM44 mRNA were associated with unfavorable OS and DFS in various malignancies .Conclusions: TRIM44 may serve as a valuable prognostic biomarker and a potential therapeutic target for patients with malignancies.
Liver cancer is closely linked to chronic inflammation. While observational studies have reported positive associations between extrahepatic immune-mediated diseases and systemic inflammatory biomarkers and liver cancer, the genetic association between these inflammatory traits and liver cancer remains elusive and merits further investigation. We conducted a two-sample Mendelian randomization (MR) analysis, using inflammatory traits as exposures and liver cancer as the outcome. The genetic summary data of both exposures and outcome were retrieved from previous genome-wide association studies (GWAS). Four MR methods, including inverse-variance-weighted (IVW), MR-Egger regression, weighted-median, and weighted-mode methods, were employed to examine the genetic association between inflammatory traits and liver cancer. Nine extrahepatic immune-mediated diseases, seven circulating inflammatory biomarkers, and 187 inflammatory cytokines were analyzed in this study. The IVW method suggested that none of the nine immune-mediated diseases were associated with the risk of liver cancer, with odds ratios of 1.08 (95% CI 0.87–1.35) for asthma, 0.98 (95% CI 0.91–1.06) for rheumatoid arthritis, 1.01 (95% CI 0.96–1.07) for type 1 diabetes, 1.01 (95% CI 0.98–1.03) for psoriasis, 0.98 (95% CI 0.89–1.08) for Crohn’s disease, 1.02 (95% CI 0.91–1.13) for ulcerative colitis, 0.91 (95% CI 0.74–1.11) for celiac disease, 0.93 (95% CI 0.84–1.05) for multiple sclerosis, and 1.05 (95% CI 0.97–1.13) for systemic lupus erythematosus. Similarly, no significant association was found between circulating inflammatory biomarkers and cytokines and liver cancer after correcting for multiple testing. The findings were consistent across all four MR methods used in this study. Our findings do not support a genetic association between extrahepatic inflammatory traits and liver cancer. However, larger-scale GWAS summary data and more genetic instruments are needed to confirm these findings.
Background: Previous researches have reported that tripartite motif-containing 44 (TRIM44) is related to the prognosis of multiple human tumors. This study was designed to systematically assess the prognostic value of TRIM44 in human malignancies and summarize its possible tumor-related mechanisms.Methods: The available databases were searched for eligible studies that evaluated the clinicopathological and prognostic roles of TRIM44 in patients with malignancies. The hazard ratios (HR) and odds ratios (OR) were combined to assess the predictive role of TRIM44 using Stata/SE 14.1 software.Results: A total of 1,740 patients from thirteen original studies were finally included in this study. The results of the combined analysis showed that over-expression of TRIM44 protein was significantly correlated with shorter overall survival (OS) (HR = 1.94, 95% CI: 1.60-2.35) and worse disease-free survival (DFS) (HR= 2.13, 95% CI: 1.24-3.65) in cancer patients. Additionally, the combined ORs indicated that elevated expression level of TRIM44 protein was significantly associated with lymph node metastasis (OR=2.69, 95% CI: 1.71-4.24), distant metastasis (OR=10.35, 95% CI: 1.01-106.24), poor tumor differentiation (OR=1.78, 95% CI: 1.03-3.09), increased depth of tumor invasion (OR=2.72, 95% CI: 1.73-4.30), advanced clinical stage (OR=2.75, 95% CI: 2.04-3.71), and recurrence (OR=2.30, 95% CI: 1.34-3.95). Furthermore, analysis results using Gene Expression Profiling Interactive Analysis (GEPIA) showed that the expression level of TRIM44 mRNA was higher in most tumor tissues than in the corresponding normal tissues, and the relationship between TRIM44 mRNA level and prognosis in various malignant tumors also explored in GEPIA and OS analysis webservers.Conclusions: TRIM44 may serve as a valuable prognostic biomarker and a potential therapeutic target for patients with malignancies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.