BackgroundLung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.MethodThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.ResultsFourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4+ T cells, CD8+ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.ConclusionWe developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.
Colon adenocarcinoma (COAD) has a high incidence and death rate. Despite the fact that change in fatty acid metabolism promotes tumor growth and metastasis to the greatest degree among metabolite profiles, a thorough investigation on the involvement of fatty acid metabolism‐related genes (FAMRGs) in COAD has yet not been conducted. Here, the clinical data as well as the gene expression profiles were extracted from The Cancer Genome Atlas (TCGA) database. Based on the FAMRG expression data and clinical information, a FAMRG risk signature was developed using LASSO as well as multivariate and univariate Cox regression analyses. Then, the nomogram was used to create a customized prognostic prediction model, and the calibration and receiver operating characteristic curves were used to evaluate the nomogram's prediction performance and discriminative capability. Lastly, a number of studies were conducted to assess the influence of independent FAMRGs on COAD, including unsupervised cluster analysis, functional analysis, and drug sensitivity analysis. Three hundred and sixty‐seven patients were included in this study, and a 12‐FAMRG risk signature was discovered in the training cohort based on a detailed examination of the FAMRGs expression data and clinical information. After that, risk scores were computed to classify patients into low or high‐risk groups, and the Kaplan–Meier curve analysis revealed that patients in the low‐risk group exhibited an elevated overall survival (OS) rate. The FAMRG was shown to be substantially correlated with prognosis in multivariate Cox regression analysis and was validated using the validation dataset. Then, using the clinical variables and risk signature, we developed and validated a prediction nomogram for OS. Functional characterization showed a strong correlation between this signature and immune cell infiltration and immune modulation. Additionally, by evaluating the GDSC database, it was determined that the high‐risk group exhibited medication resistance to many chemotherapeutic and targeted medicines, including VX.680, gemcitabine, doxorubicin, and paclitaxel. Overall, we have revealed the significance of a FAMRG risk signature for predicting the prognosis and response to immunotherapy in COAD, and our findings might contribute to an enhanced comprehension of metabolic pathways and the future development of innovative COAD therapeutic methods.
Background Ubiquitin and ubiquitin-like (UB/UBL) conjugations are essential post-translational modifications that contribute to cancer onset and advancement. In colon adenocarcinoma (COAD), nonetheless, the biological role, as well as the clinical value of ubiquitin-related genes (URGs), is unclear. The current study sought to design and verify a ubiquitin-related gene pairs (URGPs)-related prognostic signature for predicting COAD prognoses. Methods Using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, URGP's predictive signature was discovered. Signatures differentiated high-risk and low-risk patients. ROC and Kaplan–Meier assessed URGPs' signature. Gene set enrichment analysis (GSEA) examined biological nomogram enrichment. Chemotherapy and tumor immune microenvironment were also studied. Results The predictive signature used six URGPs. High-risk patients had a worse prognosis than low-risk patients, according to Kaplan–Meier. After adjusting for other clinical characteristics, the URGPs signature could reliably predict COAD patients. In the low-risk group, we found higher amounts of invading CD4 memory-activated T cells, follicular helper T cells, macrophages, and resting dendritic cells. Moreover, low-risk group had higher immune checkpoint-related gene expression and chemosensitivity. Conclusion Our research developed a nomogram and a URGPs prognostic signature to predict COAD prognosis, which may aid in patient risk stratification and offer an effective evaluation method of individualized treatment in clinical settings.
BackgroundDNA damage repair plays an important role in the onset and progression of cancers and its resistance to treatment therapy. This study aims to assess the prognostic potential of DNA damage repair markers in skin cutaneous melanoma (SKCM).MethodIn this study, we have analyzed the gene expression profiles being downloaded from TCGA, GTEx, and GEO databases. We sequentially used univariate and LASSO Cox regression analyses to screen DNA repair genes associated with prognosis. Then, we have conducted a multivariate regression analysis to construct the prognostic profile of DNA repair-related genes (DRRGs). The risk coefficient is used to calculate the risk scores and divide the patients into two cohorts. Additionally, we validated our prognosis model on an external cohort as well as evaluated the link between immune response and the DRRGs prognostic profiles. The risk signature is compared to immune cell infiltration, chemotherapy, and immune checkpoint inhibitors (ICIs) treatment.ResultsAn analysis using LASSO-Cox stepwise regression established a prognostic signature consisting of twelve DRRGs with strong predictive ability. Disease-specific survival (DSS) is found to be lower among high-risk patients group as compared to low-risk patients. The signature may be employed as an independent prognostic predictor after controlling for clinicopathological factors, as demonstrated by validation on one external GSE65904 cohort. A strong correlation is also found between the risk score and the immune microenvironment, along with the infiltrating immune cells, and ICIs key molecules. The gene enrichment analysis results indicate a wide range of biological activities and pathways to be exhibited by high-risk groups. Furthermore, Cisplatin exhibited a considerable response sensitivity in low-risk groups as opposed to the high-risk incidents, while docetaxel exhibited a considerable response sensitivity in high-risk groups.ConclusionsOur findings provide a thorough investigation of DRRGs to develop an DSS-related prognostic indicator which may be useful in forecasting SKCM progression and enabling more enhanced clinical benefits from immunotherapy.
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