A prognostic fibroblast-related risk signature in colorectal cancer.
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ABSTRACT:
SUBMITTER: Xu H
PROVIDER: S-EPMC8610139 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundColorectal cancer (CRC) is the third most common cancer worldwide. The opening of the TCGA and GEO databases has promoted the progress of CRC prognostic assessment, while the aging-related risk signature has never been mentioned.MethodsR software packages, GSEA software, Venn diagram, Metascape, STRING, Cytoscape, cBioPortal, TIMER and GeneMANIA website were used in this study.ResultsAging-related gene sets, GO_AGING, GO_CELL_AGING and GO_CELLULAR_SENESCENCE, were activated significantly in CRC tissues. We constructed an aging-related risk signature using LASSO COX regression in training group TCGA and validated in testing group GSE39582. The risk score was significantly associated with the overall survival of CRC patients, whose stability was clarified by stratified survival analysis and accuracy was demonstrated using the ROC curve. The risk score was significantly increased in the advanced stage, T3-4, N1-3 and M1 and positively correlated with the richness of immune cell infiltration in the tumor microenvironment. We further investigated the molecular characteristics of 15 hub genes at the DNA and protein levels and performed GSEA between high- and low-risk groups.ConclusionsThe aging-related signature is a reliable prognostic analysis model and can predict the severity and immune cell infiltration of CRC patients.
| S-EPMC7993742 | biostudies-literature
Project description:Traditionally, cancer-associated fibroblasts (CAFs), an essential component of tumor microenvironment, were exert a crucial part in colon cancer progression. In this study, single-cell RNA-sequencing (scRNA-seq) data from 23 and bulk RNA-seq data from 452 colon cancer patients were extracted from the GEO database and TCGA-COAD and GEO databases, respectively. From single-cell analysis, 825 differentially expressed genes (DEGs) in CAFs were identified between each pair of six newly defined CAFs, named enCAF, adCAF, vaCAF, meCAF, erCAF, and cyCAF. Cell communication analysis with the iTALK package showed communication relationship between CAFs, including cell autocrine, cytokine, and growth factor subtypes, such as receptor-ligand pairs of TNFSF14-LTBR, IL6-F3, and IL6-IL6ST. Herein, we demonstrated the presence and prognostic value of adCAF and erCAF in colon cancer based on CIBERSORTx, combining single-cell marker genes and transcriptomics data. The prognostic significance of the enCAF and erCAF has been indirectly proved by both the correlation analysis with macrophages and CAFs, and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) experiment based on 20 paired tumor samples. A prognostic model was constructed with 10 DEGs using the LASSO Cox regression method. The model was validated using two testing datasets, indicate a significant survival accuracy (p < 0.0025). Correlation analyses between clinical information, such as age, gender, tumor stage and tumor features (tumor purity and immune score), and risk scores revealed our CAF-related model’s robustness and excellent performance. Cell infiltration analysis by xCell revealed that the interaction between CAFs and multiple non-specific immune cells such as macrophages and the dendritic cell was a vital factor affecting immune score and prognosis. Finally, we analyzed how common anti-cancer drugs, including camptothecin, docetaxel and bortezomib, and immunotherapy, such as anti-PD-1 treatment, could be different in low-risk and high-risk patients inferred from our CAF-related model. In conclusion, the study utilized refined colon cancer fibroblast subsets and established the prognostic effects from the interaction with nonspecific immune cell.
| S-EPMC9329609 | biostudies-literature
Project description:Disulfidptosis (DSP), a form of cell death caused by disulphide stress, plays an important role in tumour progression. However, the mechanisms by which DSP regulates the tumour microenvironment remain unclear. Thus, we analysed the transcriptome profiles and clinical data, which were obtained from the TCGA database, of 540 patients with colorectal cancer. Compared with the patients with low DSP expression, those with high DSP expression exhibited significantly better survival outcomes; lower stromal and ESTIMATE scores; significantly higher numbers of CD4+ T cells, M2 macrophages, dendritic cells, and neutrophils; higher expression of immune checkpoint-related genes; and lower Tregs and HLA-DQB2 levels. A prognostic signature established based on DSP-related genes demonstrated an increase in risk score with a higher clinical stage. Risk scores negatively correlated with dendritic cells, eosinophils, and CD4+ T cells and significantly positively correlated with Treg cells. Patients with higher risk scores experienced significantly worse survival outcomes and immunotherapy non-response. Our nomogram model, combining clinicopathological features and risk scores, exhibited robust prognostic and predictive power. In conclusion, DSP-related genes actively participated in regulating the tumour microenvironment. Thus, they can serve as biomarkers to provide targeted treatment for colorectal cancer.
| S-EPMC10762008 | biostudies-literature
Project description:Colorectal cancer (CRC) is one of the most prevalent and deadliest illnesses all around the world. Growing proofs demonstrate that tumor-associated macrophages (TAMs) are of critical importance in CRC pathogenesis, but their mechanisms remain yet unknown. The current research was designed to recognize underlying biomarkers associated with TAMs in CRC. We screened macrophage-related gene modules through WGCNA, selected hub genes utilizing the LASSO algorithm and COX regression, and established a model. External validation was performed by expression analysis using datasets GSE14333, GSE74602, and GSE87211. After validating the bioinformatics results using real-time quantitative reverse transcription PCR, we identified SPP1, C5AR1, MMP3, TIMP1, ADAM8 as potential biomarkers associated with macrophages in CRC.
| S-EPMC10837438 | biostudies-literature
Project description:Colorectal cancer (CRC) is one of the deadliest cancers worldwide. Numerous studies have reported a correlation between uric acid (UA) level and CRC risk. Here, we investigated the role and prognostic value of UA-related genes in CRC progression. CRC-associated gene expression and clinical data were retrieved from The Cancer Genome Atlas (TCGA), and UA-related genes were identified by overlapping the TCGA and GeneCards databases. The Gene Ontology annotation, Kyoto Encyclopedia of Genes and Genomes pathway, and Molecular Signatures Database dataset were subjected to gene set enrichment analysis. A prognostic model was constructed using the univariate and multivariate COX regression and least absolute shrinkage and selection operator (LASSO) analyses and validated using the Gene Expression Omnibus cohort. Competing endogenous RNA network, CellMiner, and Human Protein Atlas were used to detect the signature of 13 UA-related genes in the prediction model. The expression of five potential UA-related genes in CRC cell lines was confirmed via qPCR. CIBERSORT was used to evaluate immune cell infiltration in the TCGA-CRC dataset. Thirteen highly prognostic UA-related genes were used to construct a prognostic model of CRC with risk score accuracy and predictive efficacy. Abundance of activated M0 macrophages, monocytes, CD8+ T cells, and natural killer cells positively correlated with the risk score. Five promising UA-related genes showed higher expression levels in CRC than in colonic cell lines. Thus, our model posits a direct relationship between UA-related genes and CRC risk, offering novel insights into diagnosis, prognosis, and treatment.
| S-EPMC10782177 | biostudies-literature
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:PurposeAlthough immunotherapy and checkpoint inhibitors contribute to the treatment of colorectal cancer (CRC), few patients can benefit from these treatments. Therefore, our goal was to develop a marker based on immune-related genes to predict the prognosis of patients with CRC to guide treatment strategies.MethodsGene expression data from colorectal cancer patients in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas were analyzed systematically. We used Cox regression to identify immune-related genes with potential prognostic value. The expression of immune genes, infiltration level of immune cells, and several immune-related molecules were further compared between the high-risk and low-risk groups. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used for functional analysis.ResultsFive GEO datasets were integrated into a merged GEO dataset, which showed obvious survival in StromalScore and ESTIMATEScore. WGCNA showed that 749 genes of the pink module are related to immunity, 95 of which are related to prognosis, correlating with cytokine-cytokine receptor interaction and natural killer cell-mediated cytotoxicity. Among these genes, an 11-gene signature was developed through stability selection and LASSO Cox regression. Univariate and multifactorial Cox regression analyses demonstrated that gene signature was an independent prognostic factor for predicting survival in patients with colorectal cancer. Samples from the low-risk group may be more sensitive to immunotherapy. In addition, the nomogram risk prediction model effectively predicted the prognosis of CRC patients by appropriately stratifying the risk scores.ConclusionIn conclusion, we developed a novel immune-related gene signature that may be useful in predicting cancer progression and prognosis, thus contributing to the individualized management of colorectal cancer patients.
| S-EPMC8520451 | biostudies-literature
Project description: Not available
| S-EPMC11233961 | biostudies-literature
Project description:Hypoxia has been particularly associated with poor prognosis in cancer patients. Recent studies have suggested that hypoxia-related miRNAs play a critical role in various cancers, including colorectal cancer (CRC). In the present study, we found 52 differentially expressed miRNAs in HT-29 cells under hypoxic conditions versus normoxic conditions by analyzing the profiles of miRNAs. Using Cox model, we developed a hypoxia-related miRNA signature consisting of four miRNAs, which could successfully discriminate high-risk patients in the Cancer Genome Atlas (TCGA) training cohort (n=381). The prognostic value of this signature was further confirmed in the TCGA testing cohort (n=190) and an independent validation cohort composed of formalin-fixed paraffin-embedded clinical CRC samples (n=220), respectively. Multivariable Cox regression and stratified survival analysis revealed this signature was an independent prognostic factor for CRC patients. Time-dependent receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this signature was significantly larger than that of any other clinical risk factors or single miRNA alone. A nomogram was constructed for clinical use, which incorporated both the miRNA signature and clinical risk factors and performed well in the calibration plots. Collectively, this novel hypoxia-related miRNA signature was an independent prognostic factor, and it possessed a stronger predictive power in identifying high-risk CRC patients than currently used clinicopathological features.
| S-EPMC6977676 | biostudies-literature
Project description:Background: Colorectal cancer (CRC) is a common malignant tumor that affects the large bowel or the rectum. Cuproptosis, recently discovered programmed cell death process, may play an important role in CRC tumorigenesis. Long non-coding RNAs (lncRNAs) can alter the proliferation of colorectal cancer cells through the control and activation of gene expression. To date, cuproptosis-related lncRNAs, have not been investigated as potential predictive biomarkers in colorectal cancer. Methods: The mRNA and lncRNA expression data of colorectal cancer were gathered from The Tumor Genome Atlas (TCGA) database, and Pearson correlation analysis and univariate Cox regression analysis were used to identify the lncRNAs with differential prognosis. Colorectal cancer was classified using consistent clustering, and the clinical significance of different types, tumor heterogeneity, and immune microenvironment differences was investigated. The differential lncRNAs were further screened using LASSO regression to develop a risk scoring model, which was then paired with clinicopathological variables to create a nomogram. Finally, the copy number changes in the high-risk and low-risk groups were compared. Results: Two clusters were formed based on the 28 prognostic cuproptosis-related lncRNAs, and the prognosis of cluster 2 was found to be significantly lower than that of cluster 1. Cluster 1 showed increased immune cell infiltration and immunological score, as well as strong enrichment of immune checkpoint genes. Next, LASSO regression was used to select 11 distinctive lncRNAs, and a risk score model was constructed using the training set to distinguish between high and low-risk groups. Patients in the high-risk group had a lower survival rate than those in the low-risk group, and both the test set and the total set produced consistent results. The AUC value of the ROC curve revealed the scoring model's efficacy in predicting long-term OS in patients. Moreover, the model could be used as an independent predictor when combined with a multivariate analysis of clinicopathological features, and our nomogram could be used intuitively to predict prognosis. Conclusion: Collectively, we developed a risk model using 11 differential lncRNAs and demonstrated that the model has predictive value as well as clinical and therapeutic implications for predicting prognosis in CRC patients.
| S-EPMC9465626 | biostudies-literature