A mutational signature for colorectal cancer prognosis prediction: Associated with immune cell infiltration.
Ontology highlight
ABSTRACT:
SUBMITTER: Xu L
PROVIDER: S-EPMC8101534 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
A mutational signature for colorectal cancer prognosis prediction: Associated with immune cell infiltration.
Xu Liang L Lin Yanyun Y Chen Xijie X Zheng Lisheng L Cheng Yufeng Y Hu Jiancong J Zheng Bin B Zhang Bin B Li Guanman G Chi Zengjie Z Guo Shuang S Liu Danling D He Xiaosheng X Lan Ping P
Clinical and translational medicine 20210501 5
Similar Datasets
Project description:BackgroundMitophagy plays essential role in the development and progression of colorectal cancer (CRC). However, the effect of mitophagy-related genes in CRC remains largely unknown.AimTo develop a mitophagy-related gene signature to predict the survival, immune infiltration and chemotherapy response of CRC patients.MethodsNon-negative matrix factorization was used to cluster CRC patients from Gene Expression Omnibus database (GSE39582, GSE17536, and GSE37892) based on mitophagy-related gene expression. The CIBERSORT method was applied for the evaluation of the relative infiltration levels of immune cell types. The performance signature in predicting chemotherapeutic sensitivity was generated using data from the Genomics of Drug Sensitivity in Cancer database.ResultsThree clusters with different clinicopathological features and prognosis were identified. Higher enrichment of activated B cells and CD4+ T cells were observed in cluster III patients with the most favorable prognosis. Next, a risk model based on mitophagy-related genes was developed. Patients in training and validation sets were categorized into low-risk and high-risk subgroups. Low risk patients showed significantly better prognosis, higher enrichment of immune activating cells and greater response to chemotherapy (oxaliplatin, irinotecan, and 5-fluorouracil) compared to high-risk patients. Further experiments identified CXCL3 as novel regulator of cell proliferation and mitophagy.ConclusionWe revealed the biological roles of mitophagy-related genes in the immune infiltration, and its ability to predict patients' prognosis and response to chemotherapy in CRC. These interesting findings would provide new insight into the therapeutic management of CRC patients.
| S-EPMC10052665 | biostudies-literature
Project description:To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.
| S-EPMC8370985 | biostudies-literature
Project description:Abstract Background The tumor microenvironment plays an essential role in the therapeutic response to immunotherapy. It is necessary to identify immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. This study aimed to evaluate the ICI score as an effective prognostic biomarker for immune response. Methods The cell-type identification by estimating relative subsets of RNA transcripts and the estimation of stromal and immune cells in malignant tumors using expression methods were used to analyse ICI landscapes in 161 colorectal cancer (CRC) samples with patients’ clinical and prognostic data, RNA sequencing data, and whole-exome sequencing data from the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). Statistical analysis and data processing were conducted to calculate ICI scores, and to analyse the prognosis of CRC patients with different ICI scores and other features. A similar analysis with RNA sequencing and clinical data of colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) database was conducted to confirm the correctness of the findings. Results The high-ICI score group with a better prognosis (hazard ratio [HR], 2.19; 95% confidence interval [CI], 1.03–4.64; log-rank test, P = 0.036) was characterized by the increased tumor mutational burden and interleukin-17 (IL-17) signaling pathway. Significant differences in the prognosis and the expression levels of immune checkpoints and chemokine marker genes were found between the two ICI score groups. For COAD samples from TCGA, the results also showed a significant difference in patients’ prognosis between the two ICI score groups (HR, 1.72; 95% CI, 1.00–2.96; log-rank test, P = 0.047). Conclusions Tumor heterogeneity induced differences in identifying ICI subtypes of CRC patients. The ICI score may serve as an effective biomarker for predicting prognosis, help identify new therapeutic markers for CRC, and develop novel effective immune checkpoint blockade therapies.
| S-EPMC10089677 | biostudies-literature
Project description:ObjectiveThe immune microenvironment influenced clinical outcomes and treatment response of gastric cancer (GC) patients. Though thousands of immune-related genes (IRGs) have been identified, their effects on GC are not fully understood. The objective of the study is to analyze the correlations between the expression and effect of IRGs and clinical outcomes. Moreover, we evaluate the efficacy and value of utilizing the immune-related genes signature as a prognosis prediction model for GC patients.MethodsWe identified the differentially expressed IRGs and systematically analyzed their functions. We constructed a novel GC prognostic signature and a new nomogram, Moreover, we explored the infiltrated immune cell types in the immune microenvironment and discussed the genetic variation in GC IRGs.ResultsEight IRGs, including CCL15, MSR1, GNAI1, NR3C1, ITGAV, NMB, AEN, and TGFBR1 were identified. Based on the prognostic signature, GC patients were distinguished into two subtype groups. As verified in multiple datasets, the prognostic signature exhibited good performance in predicting the prognosis (AUC = 0.803, P-value <0.001) and revealed the different clinical features and infiltrated immune cell types in the immune microenvironment.ConclusionsIn summary, we found that IRGs contributed to GC prognosis prediction and constructed an IRGs-based GC prognostic signature, which could serve as an effective prognostic stratification tool.
| S-EPMC10782158 | biostudies-literature
Project description:BackgroundAs the most common gastrointestinal malignancy worldwide, liver metastases occur in half colorectal cancer (CRC) patients. Early detection can help treat them early and reduce mortality in patients with colorectal cancer liver metastases (CRLM). Finding useful biomarkers for CRLM is thus essential.MethodsThe TCGA and GEO databases were used to download the expression profiles and clinical data of the patients. Differential analysis screened for genes associated with CRLM, and univariate Cox regression analysis identified genes associated with prognosis. The least absolute shrinkage and selection operator (LASSO) method further preferred genes to construct a prognostic signature. Kaplan-Meier survival curves were used to show patients' overall survival (OS). Receiver operating characteristic (ROC) curves showed the accuracy of the model. Risk scores and clinical characteristics of patients were included in multivariate Cox regression analysis to identify independent risk factors, and a nomogram was constructed. The proportion of immune cells and infiltration were assessed using the 'CIBERSORT' package and the 'ESTIMATE' package.ResultsWe constructed a signature consisting of seven CRLM-associated genes, and signature-based risk scores have great potential in estimating the prognosis of CRC patients. Moreover, the poor response to immunotherapy in high-risk patients might contribute to the poor prognosis of individuals. Furthermore, we found that overexpression of Hepcidin antimicrobial peptide (HAMP), the only gene highly expressed in CRC and liver metastatic tissues, promoted CRC development and that it was associated with tumor mutation burden (TMB), DNA mismatch repair (MMR) genes, and microsatellite instability (MSI) in various tumors. Finally, we found that in CRC patients, low expression of HAMP also represented a better immunotherapeutic outcome, reflecting the critical role of HAMP in guiding immunotherapy.ConclusionWe identified a prognostic signature containing 7 CRLM-associated genes, and the signature was specified as an independent predictor and a nomogram containing the risk score was built accordingly. In addition, the derived gene HAMP could help guide the exploration of profitable immunotherapeutic strategies.
| S-EPMC10411999 | biostudies-literature
Project description:Osteosarcoma (OS) is one of the most prevalent primary bone tumors at all ages of human development. The objective of our study was to develop a model of Cuproptosis-Related Genes (CRGs) for predicting prognosis in OS patients. All datasets of OS patients were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and Gene Expression Omnibus (GEO) database. We obtained the gene set (81 CRGs) related to cuproptosis by accessing the database and previous literature. All the CRGs were analyzed by univariate COX regression, least absolute shrinkage and selection operator (LASSO) COX regression analysis to screen for CRGs associated with prognosis in OS patients. Then these CRGs were used to construct a prognostic signature, which was further verified by independent cohort (GSE21257) and clinical correlation analysis. Afterward, to identify underlying mechanisms, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for the high-risk group by using the GSEA method. The association between the prognostic signature and 28 types of immune infiltrating cells in the tumor microenvironment was assessed. Ultimately, Lipoic Acid Synthetase (LIAS) (HR=0.632, P=0.004), Lipoyltransferase 1 (LIPT1) (HR=0.524, P=0.011), BCL2 Like 1 (BCL2L1/BCL-XL) (HR=0.593, P=0.022), and Pyruvate Dehydrogenase Kinase 1 (PDK1) (HR=0.662, P=0.025) were identified. Subsequently, they were used to calculate the risk score and build a prognostic model. In the training cohort, risk score (HR=1.878, P=0.003) could be considered as an independent prognostic factor, and OS patients with high-risk scores showed lower survival rates. Biological pathways related to substance metabolism and transport were enriched. There were significant differences in immune infiltrating cells in the tumor microenvironment. All in all, The CRGs signature is related to the tumor immune microenvironment and could be used as a credible predictor of the prognostic status in OS patients.
| S-EPMC9582135 | biostudies-literature
Project description:BackgroundAn accumulating amount of studies are highlighting the impacts of cancer-associated fibroblasts (CAFs) on the initiation, metastasis, invasion, and immune evasion of lung cancer. However, it is still unclear how to tailor treatment regimens based on the transcriptomic characteristics of CAFs in the tumor microenvironment of patients with lung cancer.MethodsOur study examined single-cell RNA-sequencing data from the Gene Expression Omnibus (GEO) database to identify expression profiles for CAF marker genes and constructed a prognostic signature of lung adenocarcinoma using these genes in The Cancer Genome Atlas (TCGA) database. The signature was validated in 3 independent GEO cohorts. Univariate and multivariate analyses were used to confirm the clinical significance of the signature. Next, multiple differential gene enrichment analysis methods were used to explore the biological pathways related to the signature. Six algorithms were used to assess the relative proportion of infiltrating immune cells, and the relationship between the signature and immunotherapy response of lung adenocarcinoma (LUAD) was explored based on the tumor immune dysfunction and exclusion (TIDE) algorithm.ResultsThe signature related to CAFs in this study showed good accuracy and predictive capacity. In all clinical subgroups, the high-risk patients had a poor prognosis. The univariate and multivariate analyses confirmed that the signature was an independent prognostic marker. Moreover, the signature was closely associated with particular biological pathways related to cell cycle, DNA replication, carcinogenesis, and immune response. The 6 algorithms used to assess the relative proportion of infiltrating immune cells indicated that a lower infiltration of immune cells in the tumor microenvironment was associated with high-risk scores. Importantly, we found a negative correlation between TIDE, exclusion score, and risk score.ConclusionsOur study constructed a prognostic signature based on CAF marker genes useful for prognosis and immune infiltration estimation of lung adenocarcinoma. This tool could enhance therapy efficacy and allow individualized treatments.
| S-EPMC10089835 | biostudies-literature
Project description:This study was aimed at constructing a pyroptosis-related signature for prostate cancer (PCa) and elucidating the prognosis and immune landscape and the sensitivity of immune checkpoint blockade (ICB) therapy in signature-define subgroups of PCa. We identified 22 differentially expressed pyroptosis-related genes in PCa from The Cancer Genome Atlas (TCGA) database. The pyroptosis-related genes could divide PCa patients into two clusters with differences in survival. Seven genes were determined to construct a signature that was confirmed by qRT-PCR to be closely associated with the biological characteristics of malignant PCa. The signature could effectively and independently predict the biochemical recurrence (BCR) of PCa, which was validated in the GSE116918 and GSE21034. We found that patients in the high-risk group were more prone to BCR and closely associated with high-grade and advanced-stage disease progression. Outperforming clinical characteristics and nine published articles, our signature demonstrated excellent predictive performance. The patients in the low-risk group were strongly related to the high infiltration of various immune cells including CD8+ T cells and plasma B cells. Furthermore, the high-risk group with higher TMB levels and expression of immune checkpoints was more likely to benefit from immune checkpoint therapy such as PD-1 and CTLA-4 inhibitors. The sensitivity to chemotherapy, endocrine, and targeted therapy showed significant differences in the two risk groups. Our signature was a novel therapeutic strategy to distinguish the prognosis and guide treatment strategies.
| S-EPMC9066377 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is the third most common tumor worldwide. Aberrant N6-methyladenosine (m6A) modification can influence the progress of the CRC. Additionally, long noncoding RNA (lncRNA) plays a critical role in CRC and has a close relationship with m6A modification. However, the prognostic potential of m6A-related lncRNAs in CRC patients still remains to be clarified.MethodsWe use "limma" R package, "glmnet" R package, and "survival" R package to screen m6A-related-lncRNAs with prognostic potential. Then, we comprehensively analysed and integrated the related lncRNAs in different TNM stages from TCGA database using the LASSO Cox regression. Meanwhile, the relationship between functional enrichment of m6A-related lncRNAs and immune microenvironment in CRC was also investigated using the TCGA database. A prognostic model was constructed and validated to determine the association between m6A-related lncRNAs in different TNM stages and the prognosis of CRC.ResultWe demonstrated that three related m6A lncRNAs in different TNM stages were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the low-risk and the high-risk groups based on the expression of these lncRNAs. The patients in the low-risk group had longer overall survival than the patients in the high-risk group (P < 0.001). We further constructed and validated a prognostic nomogram based on these genes with a C-index of 0.80. The receiver operating characteristic curves confirmed the predictive capacity of the model. Meanwhile, we also found that the low-risk group has the correlation with the dendritic cell (DC). Finally, we discovered the relationship between the m6A regulators and the three lncRNAs.ConclusionThe prognostic model based on three m6A-related lncRNAs exhibits superior predictive performance, providing a novel prognostic model for the clinical evaluation of CRC patients.
| S-EPMC8568524 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common cancers, with a wide range of symptoms and outcomes. Cancer-associated fibroblasts (CAFs) are newly identified in the tumor microenvironment (TME) and associated with GC progression, prognosis, and treatment response. A novel CAF-associated prognostic model is urgently needed to improve treatment strategies.MethodsThe detailed data of GC samples were downloaded from The Cancer Genome Atlas (TCGA), GSE62254, GSE26253, and GSE84437 datasets, then obtained 18 unique CAF-related genes from the research papers. Eight hundred eight individuals with GC were classified as TCGA or GSE84437 using consensus clustering by the selected CAF-related genes. The difference between the two subtypes revealed in this study was utilized to create the "CAF-related signature score" (CAFS-score) prognostic model and validated with the Gene Expression Omnibus (GEO) database.ResultsWe identified two CAF subtypes characterized by high and low CAFS-score in this study. GC patients in the low CAFS-score group had a better OS than those in the high CAFS-score group, and the cancer-related malignant pathways were more active in the high CAFS-score group, compared to the low CAFS-score group. We found that there was more early TNM stage in the low CAFS-score subgroup, while there was more advanced TNM stage in the high CAFS-score subgroup. The expression of TMB was significantly higher in the low CAFS-score subgroup than in the high CAFS-score subgroup. A low CAFS-score was linked to increased microsatellite instability-high (MSI-H), mutation load, and immunological activation. Furthermore, the CAFS-score was linked to the cancer stem cell (CSC) index as well as chemotherapeutic treatment sensitivity. The patients in the high CAFS-score subgroup had significantly higher proportions of monocytes, M2 macrophages, and resting mast cells, while plasma cells and follicular helper T cells were more abundant in the low-risk subgroup. The CAFS-score was also highly correlated with the sensitivity of chemotherapeutic drugs. The low CAFS-score group was more likely to have an immune response and respond to immunotherapy. We developed a nomogram to improve the CAFS-clinical score's usefulness.ConclusionThe CAFS-score may have a significant role in the TME, clinicopathological characteristics, prognosis, CSC, MSI, and drug sensitivity, according to our investigation of CAFs in GC. We also analyzed the value of the CAFS-score in immune response and immunotherapy. This work provides a foundation for improving prognosis and responding to immunotherapy in patients with GC.
| S-EPMC9372353 | biostudies-literature