Identification and validation of a novel 17 coagulation-related genes signature for predicting prognostic risk in colorectal cancer
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SUBMITTER: Jin T
PROVIDER: S-EPMC11233961 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
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Project description:Background: This study aimed to explore the biological functions and prognostic role of Epithelial-mesenchymal transition (Epithelial-mesenchymal transition)-related lncRNAs in colorectal cancer (CRC). Methods: The Cancer Genome Atlas database was applied to retrieve gene expression data and clinical information. An EMT-related lncRNA risk signature was constructed relying on univariate Cox regression, Least Absolute Shrinkage and Selector Operation (LASSO) and multivariate Cox regression analysis of the EMT-related lncRNA expression data and clinical information. Then, an individualized prognostic prediction model based on the nomogram was developed and the predictive accuracy and discriminative ability of the nomogram were determined by the receiver operating characteristic curve and calibration curve. Finally, a series of analyses, such as functional analysis and unsupervised cluster analysis, were conducted to explore the influence of independent lncRNAs on CRC. Results: A total of 581 patients were enrolled and an eleven-EMT-related lncRNA risk signature was identified relying on the comprehensive analysis of the EMT-related lncRNA expression data and clinical information in the training cohort. Then, risk scores were calculated to divide patients into high and low-risk groups, and the Kaplan-Meier curve analysis showed that low-risk patients tended to have better overall survival (OS). Multivariate Cox regression analysis indicated that the EMT-related lncRNA signature was significantly associated with prognosis. The results were subsequently confirmed in the validation dataset. Then, we constructed and validated a predictive nomogram for overall survival based on the clinical factors and risk signature. Functional characterization confirmed this signature could predict immune-related phenotype and was associated with immune cell infiltration (i.e., macrophages M0, M1, Tregs, CD4 memory resting cells, and neutrophils), tumor mutation burden (TMB). Conclusions: Our study highlighted the value of the 11-EMT-lncRNA signature as a predictor of prognosis and immunotherapeutic response in CRC.
| S-EPMC8513715 | biostudies-literature
Project description:Long non-coding RNA (lncRNA) is an important regulator of gene expression and serves a fundamental role in immune regulation. The present study aimed to develop a novel immune-related lncRNA signature to assess the prognosis of patients with colorectal cancer (CRC). Transcriptome data and clinical information of patients with CRC were downloaded from The Cancer Genome Atlas (TCGA) and UCSC Xena platforms. Immune-related mRNAs were extracted from the Molecular Signatures Database (MSigDB), and the immune-related lncRNAs were identified based on correlation analysis. Then, univariate, Lasso and multivariate Cox regression were applied to construct an immune-related lncRNA signature, and CRC patients were divided into high- and low-risk groups according to the median risk score. Finally, we evaluated the signature from the perspectives of clinical outcome, clinicopathological parameters, tumor-infiltrating immune cells (TIICs), immune status, tumor mutation burden (TMB) and immunotherapy responsiveness. In total, 272 immune-related lncRNAs were identified, five of which were applied to construct an immune-related lncRNA signature. The signature divided patients with CRC into low- and high-risk groups, the prognosis of patients in the high-risk group were significantly poorer than those in low-risk group, and the results were further confirmed in external validation cohort. Furthermore, the high-risk group showed aggressive clinicopathological characteristics, specific TIIC and immune function status, and low sensitivity to immunotherapy. The immune-related lncRNA signature could be exploited as a promising biomarker for predicting the prognosis and immune status of patients with CRC.
| S-EPMC9873726 | biostudies-literature
Project description:BackgroundDisruptions in calcium homeostasis are associated with a wide range of diseases, and play a pivotal role in the development of cancer. However, the construction of prognostic models using calcium extrusion-related genes in colon adenocarcinoma (COAD) has not been well studied. We aimed to identify whether calcium extrusion-related genes serve as a potential prognostic biomarker in the COAD progression.MethodsWe constructed a prognostic model based on the expression of calcium extrusion-related genes (SLC8A1, SLC8A2, SLC8A3, SLC8B1, SLC24A2, SLC24A3 and SLC24A4) in COAD. Subsequently, we evaluated the associations between the risk score calculated by calcium extrusion-related genes and mutation signature, immune cell infiltration, and immune checkpoint molecules. Then we calculated the immune score, stromal score, tumor purity and estimate score using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm. The response to immunotherapy was assessed using tumor immune dysfunction and exclusion (TIDE). Finally, colorectal cancer cells migration, growth and colony formation assays were performed in RKO cells with the overexpression or knockdown SLC8A3, SLC24A2, SLC24A3, or SLC24A4.ResultsWe found that patients with high risk score of calcium extrusion-related genes tend to have a poorer prognosis than those in the low-risk group. Additionally, patients in high-risk group had higher rates of KRAS mutations and lower MUC16 mutations, implying a strong correlation between KRAS and MUC16 mutations and calcium homeostasis in COAD. Moreover, the high-risk group showed a higher infiltration of regulatory T cells (Tregs) in the tumor microenvironment. Finally, our study identified two previously unreported model genes (SLC8A3 and SLC24A4) that contribute to the growth and migration of colorectal cancer RKO cells.ConclusionsAltogether, we developed a prognostic risk model for predicting the prognosis of COAD patients based on the expression profiles of calcium extrusion-related genes, Furthermore, we validated two previously unreported tumor suppressor genes (SLC8A3 and SLC24A4) involved in colorectal cancer progression.
| S-EPMC11246022 | biostudies-literature
Project description:Disulfidptosis, a newly revealed form of cell death, regulated by numerous genes that has been recently identified. The exact role of disulfidptosis in lung adenocarcinoma (LUAD) still uncertain. Objective of this study was to explore potential prognostic markers among disulfidptosis genes in LUAD. By combining transcriptomic information from Gene Expression Omnibus databases and The Cancer Genome Atlas, we identified differentially expressed and prognostic disulfidptosis genes. By conducting least absolute shrinkage and selection operator with multivariate Cox regression, four disulfidptosis genes were selected to create the prognostic signature. The implementation of the signature separated the training and validation cohorts into groups with high- and low-risk. Subsequently, the model was verified by conducting an independent analysis of receiver operating characteristic (ROC) curves. Further comparisons were made between the two risk-divided groups with regards the tumor microenvironment, immune cell infiltration, immunotherapy response, and drug sensitivity. The signature was constructed using four disulfidptosis-related genes: SLC7A11, SLC3A2, NCKAP1, and GYS1. According to ROC curves, the signature was effective for predicting LUAD prognosis. In addition, the prognostic signature correlated with sensitivity to chemotherapeutic agents and the efficacy of immunotherapy in LUAD. Finally, through external validation, we showed that NCKAP1 are correlated with tumor migration, proliferation, and invasion of LUAD cells. GYS1 affects immune cell, especially M2 macrophage infiltration in the tumor microenvironment. The disulfidptosis four-gene model can reliably predict the prognosis of patients diagnosed with LUAD, thereby providing valuable information for clinical applications and immunotherapy.
| S-EPMC10784160 | biostudies-literature
Project description:BackgroundImmune-related genes (IRGs) play important roles in the tumor immune microenvironment and can affect the prognosis of cancer. This study aimed to construct a novel IRG signature for prognostic evaluation of stage II colorectal cancer (CRC).MethodsGene expression profiles and clinical data for stage II CRC patients were collected from the Cancer Genome Atlas and Gene Expression Omnibus database. Univariate, multivariate Cox regression, and least absolute shrinkage and selection operator regression were used to develop the IRG signature, namely IRGCRCII. A nomogram was constructed, and the "Cell Type Identification by Estimating Relative Subsets of RNA Transcripts" (CIBERSORT) method was used to estimate immune cell infiltration. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in 30 pairs of primary stage II CRC and matched normal tissues.ResultsA total of 466 patients with stage II CRC were included, and 274 differentially expressed IRGs were identified. Six differentially expressed IRGs were detected and used to construct the IRGCRCII signature, which could significantly stratify patients into high-risk and low-risk groups in terms of disease-free survival in three cohorts: training, test, and external validation (GSE39582). Receiver operating characteristics analysis revealed that the area under the curves of the IRGCRCII signature were significantly greater than those of the OncotypeDX colon signature at 1 (0.759 vs. 0.623), 3 (0.875 vs. 0.629), and 5 years (0.906 vs. 0.698) disease-free survival, respectively. The nomogram performed well in the concordance index (0.779) and calibration curves. The high-risk group had a significantly higher percentage of infiltrated immune cells (e.g., M2 macrophages, plasma cells, resting mast cells) than the low-risk group. Finally, the results of qRT-PCR and immunohistochemistry experiments performed on 30 pairs of clinical specimens were consistent with bioinformatics analysis.ConclusionThis study developed and validated a novel immune prognostic signature based on six differentially expressed IRGs for predicting disease-free survival and immune status in patients with stage II CRC, which may reflect immune dysregulation in the tumor immune microenvironment.
| S-EPMC8129521 | biostudies-literature
Project description:BackgroundCoagulation is critically involved in the tumor microenvironment, cancer progression, and prognosis assessment. Nevertheless, the roles of coagulation-related long noncoding RNAs (CRLs) in colorectal cancer (CRC) remain unclear. In this study, an integrated computational framework was constructed to develop a novel coagulation-related lncRNA signature (CRLncSig) to stratify the prognosis of CRC patients, predict response to immunotherapy and chemotherapy in CRC, and explore the potential molecular mechanism.MethodsCRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the substantial bulk or single-cell RNA transcriptomics from Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR (RT-qPCR) data from CRC cell lines and paired frozen tissues were used for validation. We performed unsupervised consensus clustering of CRLs to classify patients into distinct molecular subtypes. We then used stepwise regression to establish the CRLncSig risk model, which stratified patients into high- and low-risk groups. Subsequently, diversified bioinformatics algorithms were used to explore prognosis, biological pathway alteration, immune microenvironment, immunotherapy response, and drug sensitivity across patient subgroups. In addition, weighted gene coexpression network analysis was used to construct an lncRNA-miRNA-mRNA competitive endogenous network. Expression levels of CRLncSig, immune checkpoints, and immunosuppressors were determined using RT-qPCR.ResultsWe identified two coagulation subclusters and constructed a risk score model using CRLncSig in CRC, where the patients in cluster 2 and the low-risk group had a better prognosis. The cluster and CRLncSig were confirmed as the independent risk factors, and a CRLncSig-based nomogram exhibited a robust prognostic performance. Notably, the cluster and CRLncSig were identified as the indicators of immune cell infiltration, immunoreactivity phenotype, and immunotherapy efficiency. In addition, we identified a new endogenous network of competing CRLs with microRNA/mRNA, which will provide a foundation for future mechanistic studies of CRLs in the malignant progression of CRC. Moreover, CRLncSig strongly correlated with drug susceptibility.ConclusionWe developed a reliable CRLncSig to predict the prognosis, immune landscape, immunotherapy response, and drug sensitivity in patients with CRC, which might facilitate optimizing risk stratification, guiding the applications of immunotherapy, and individualized treatments for CRC.
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Project description:BackgroundCuproptosis is a novel form of cell death referred to as copper-dependent cytotoxicity. The regulation of proptosis is becoming an increasingly popular cancer treatment modality. To date, few studies have attempted to identify the cuproptosis-related long non-coding RNAs (CRLs). In this study, we sought to investigate the CRLs and construct a novel prognostic model for colorectal cancer (CRC).MethodsThe RNA-sequencing data of CRC patients were obtained from The Cancer Genome Atlas database. An analysis was conducted to identify the differentially expressed long non-coding RNAs, and a correlation analysis was performed to identify the CRLs. A univariate Cox analysis was conducted to select the prognostic CRLs. Based on a least absolute shrinkage and selection operator regression analysis, a prognostic signature comprising the 22 identified CRLs was constructed. A survival receiver operating characteristic curve analysis was conducted to evaluate the performance of the signature. Finally, an in vitro analysis was performed to investigate the function of lncRNA AC090116.1 in the CRC cells.ResultsA signature comprising 22 CRLs was developed. The patients in the training and validation sets were divided into the low- and high-risk groups and had significantly different survival probabilities. This signature had outstanding prognostic accuracy in predicting the 5-year overall survival of patients [training set, area under the curve (AUC) =0.820; validation set, AUC =0.810]. The pathway enrichment analysis showed that the differential genes between low and high groups were enriched in several important oncogenic- and metastatic-associated processes and pathways. Finally, the in vitro experiments showed that AC090116.1 silencing promoted the cuproptosis processes and suppressed cell proliferation.ConclusionsOur findings provided promising insights into the CRLs involved in CRC. The signature based on CRLs has been successfully devised to prognosticate the clinical outcomes and treatment responses in patients.
| S-EPMC10186494 | biostudies-literature
Project description:BackgroundThyroid cancer is the most common endocrine malignancy. Most PTC patients have a good prognosis; however, there are 5-20% of PTC patients with extra-thyroidal invasion, vascular invasion, or distant metastasis who have relatively poor prognoses. The aim of this study is to find new and feasible molecular pathological markers and therapeutic targets for early identification and appropriate management.MethodsThe GEO and TCGA databases were used to gather gene expression data and clinical outcomes. Based on gene expression and clinical parameters, we developed a ferroptosis-related gene-based prognostic model and a nomogram. CCK-8, wound-healing, and transwell assays were conducted to explore the proliferation, migration, and invasion abilities of thyroid cancer cells.ResultsWe found 75 genes associated with ferroptosis that were differentially expressed between normal thyroid tissue and thyroid cancer tissues. The prognostic values of the 75 ferroptosis-related gene expressions were evaluated using the TCGA-THCA dataset, and five (AKR1C3, BID, FBXW7, GPX4, and MAP3K5) of them were of significance. Following that, we chose AKR1C3 as the subject for further investigation. By combining gene expression and clinical parameters, we developed a ferroptosis-related gene-based prognostic model with an area under the curve (AUC) of 0.816, and the nomogram also achieved good predictive efficacy for the three-year survival rate of thyroid cancer patients. Knocking down AKR1C3 enhances thyroid cancer cell proliferation, invasion, and migration abilities.ConclusionsA ferroptosis-related gene-based prognostic model was constructed that provided unique insights into THCA prognosis prediction. In addition, AKR1C3 was found to be a progression promoter in thyroid cancer cell lines.
| S-EPMC9222385 | biostudies-literature
Project description:Ferroptosis, an iron-dependent form of selective cell death, is involved in the development of many cancers. However, ferroptosis related genes (FRGs) in prostate cancer (PCa) are not been well studied. In this study, we collected the mRNA expression profiles and clinical information of PCa patients from TCGA and MSKCC databases. The univariate, LASSO, and multivariate Cox regression analyses were performed to construct a prognostic signature. Seven FRGs, AKR1C3, ALOXE3, ATP5MC3, CARS1, MT1G, PTGS2, and TFRC, were included to establish a risk model, which was validated in the MSKCC dataset. The results showed that the high-risk group was apparently correlated with copy number alteration load, tumor burden mutation, immune cell infiltration, mRNAsi, immunotherapy, and bicalutamide response. Moreover, we found that TFRC overexpression induced the proliferation and invasion of PCa cell lines in vitro. These results demonstrate that this risk model can accurately predict prognosis, suggesting that FRGs are promising prognostic biomarkers and potential drug targets in PCa patients.
| S-EPMC8320699 | biostudies-literature
Project description:BACKGROUND: Gene expression signatures have been commonly used as diagnostic and prognostic markers for cancer subtyping. However, expression signatures frequently include many passengers, which are not directly related to cancer progression. Their upstream regulators such as transcription factors (TFs) may take a more critical role as drivers or master regulators to provide better clues on the underlying regulatory mechanisms and therapeutic applications. RESULTS: In order to identify prognostic master regulators, we took the known 85 prognostic signature genes for colorectal cancer and inferred their upstream TFs. To this end, a global transcriptional regulatory network was constructed with total >200,000 TF-target links using the ARACNE algorithm. We selected the top 10 TFs as candidate master regulators to show the highest coverage of the signature genes among the total 846 TF-target sub-networks or regulons. The selected TFs showed a comparable or slightly better prognostic performance than the original 85 signature genes in spite of greatly reduced number of marker genes from 85 to 10. Notably, these TFs were selected solely from inferred regulatory links using gene expression profiles and included many TFs regulating tumorigenic processes such as proliferation, metastasis, and differentiation. CONCLUSIONS: Our network approach leads to the identification of the upstream transcription factors for prognostic signature genes to provide leads to their regulatory mechanisms. We demonstrate that our approach could identify upstream biomarkers for a given set of signature genes with markedly smaller size and comparable performances. The utility of our method may be expandable to other types of signatures such as diagnosis and drug response.
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