scholarly journals A novel prognostic immunoscore based on The Cancer Genome Atlas to predict overall survival in colorectal cancer patients

2021 ◽  
Author(s):  
Zuxiong Tang ◽  
Yufan Wu ◽  
Ding Sun ◽  
Xiaofeng Xue ◽  
Lei Qin
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
The Novel ◽  
Survival Times ◽  
Specificity And Sensitivity

Colorectal cancer (CRC) is highly prevalent worldwide. The relationship between the infiltration of immunocytes in CRC and clinical outcome has been investigated in recent years. study aims to construct a new prognostic signature using an immunocyte panel. Our novel prognostic immunoscore included 13 types of immunocytes, which were identified by least absolute shrinkage and selection operator (LASSO)–Cox regression. The time-dependent receiver operating characteristic (ROC) curve and Kaplan–Meier survival estimates were applied to evaluate the prognostic ability. Compared with the signature based on a single immune marker (i.e., CD8 mRNA expression and CD8+ expressing T cells), the novel prognostic immunoscore possessed better specificity and sensitivity of prognosis (Area under the curves (AUCs) are 0.852, 0.856, and 0.774 for 1-, 2-, and 3-year survival times, respectively). Significant differences were identified between the high and low immunoscore groups in overall survival and disease-free survival in training and validation cohorts. Combining the immunoscore with clinical information may provide a more accurate prognosis for CRC. The immunoscore can identify patients with poor outcomes in the high Tumor Mutational Burden (TMB) group, who may benefit the most from immunotherapy. The immunoscore was also closely related to two immune checkpoints (i.e., PD-L1 and PD-1, r = 0.3087 and r = 0.3341, respectively). Collectively, Our study demonstrates that the novel prognostic immunoscore reported here may be useful in distinguishing different prognoses and may improve the clinical management of patients with CRC.

scholarly journals Development and Validation of a Unique Gignature of Cancer Stemness-related Genes for Predicting the Overall survival of Colorectal Cancer Patients

2020 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Zhao Lu ◽  
Xu Guan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Cancer Stemness ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB) and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high mRNAsi scores are associated with poor overall survival in stage Ⅳ CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-gene prognostic signature (PARPBP, KNSTRN and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusions: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

scholarly journals INHBB Is a Novel Prognostic Biomarker Associated with Cancer-Promoting Pathways in Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jinpeng Yuan ◽  
Aosi Xie ◽  
Qiangjian Cao ◽  
Xinxin Li ◽  
Juntian Chen
Keyword(s):  
Colorectal Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Disease Free Survival ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction

Background. Inhibin subunit beta B (INHBB) is a protein-coding gene that participated in the synthesis of the transforming growth factor-β (TGF-β) family members. The study is aimed at exploring the clinical significance of INHBB in patients with colorectal cancer (CRC) by bioinformatics analysis. Methods. Real-time PCR and analyses of Oncomine, Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) databases were utilized to evaluate the INHBB gene transcription level of colorectal cancer (CRC) tissue. We evaluated the INHBB methylation level and the relationship between expression and methylation levels of CpG islands in CRC tissue. The corresponding clinical data were obtained to further explore the association of INHBB with clinical and survival features. In addition, Gene Set Enrichment Analysis (GSEA) was performed to explore the gene ontology and signaling pathways of INHBB involved. Results. INHBB expression was elevated in CRC tissue. Although the promoter of INHBB was hypermethylated in CRC, methylation did not ultimately correlate with the expression of INHBB. Overexpression of INHBB was significantly and positively associated with invasion depth, distant metastasis, and TNM stage. Cox regression analyses and Kaplan-Meier survival analysis indicated that high expression of INHBB was correlated with worse overall survival (OS) and disease-free survival (DFS). GSEA showed that INHBB was closely correlated with 5 cancer-promoting signaling pathways including the Hedgehog signaling pathway, ECM receptor interaction, TGF-β signaling pathway, focal adhesion, and pathway in cancer. INHBB expression significantly promoted macrophage infiltration and inhibited memory T cell, mast cell, and dendritic cell infiltration. INHBB expression was positively correlated with stromal and immune scores of CRC samples. Conclusion. INHBB might be a potential prognostic biomarker and a novel therapeutic target for CRC.

scholarly journals Identification of prognostic immune-related lncRNA signature predicting the overall survival for colorectal cancer

2021 ◽  
Author(s):  
Jianxin Li ◽  
Ting Han ◽  
Xin Wang ◽  
Yinchun Wang ◽  
Qingqiang Yang
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Regression Analyses

Abstract Background Long non-coding RNA (lncRNA) is an important regulator of gene expression and serves fundamental role in immune regulation. The present study aimed to develop a novel immune-related lncRNA signature to accurately assess the prognosis of patients with colorectal cancer (CRC). Methods Transcriptome data and clinical information of patients with CRC were downloaded from The Cancer Genome Atlas (TCGA), and the immune-related mRNAs were extracted from immunomodulatory gene datasets IMMUNE RESPONSE and IMMUNE SYSTEM PROCESS based on the Molecular Signatures Database (MSigDB). Then, the immune-related lncRNAs were identified by a correlation analysis between immune-related mRNAs and lncRNAs. Subsequently, univariate, lasso and multivariate Cox regression were used to identify an immune-related lncRNA signature in training cohort, and the predict ability of the signature was further confirmed in the testing cohort and the entire TCGA cohort. Finally, the lncRNA-mRNA co-expression network was established to explore the biological role of the immune-related lncRNA signature. Results In total, 272 Immune-related lncRNAs were identified, five of which were applied to construct an immune-related lncRNA signature based on univariate, lasso and multivariate Cox regression analyses. The signature divided patients with CRC into low- and high-risk groups, and patients with CRC in high-risk group had poorer overall survival than those in low-risk group. Univariate and multivariate Cox regression analyses confirmed that the signature could be an independent prognostic factor in human CRC. Furthermore, functional enrichment analysis revealed that the immune-related lncRNA signature was significantly enriched in immune process and tumor classical pathways. Conclusions The present study revealed that the novel immune-related lncRNA signature could be exploited as underlying molecular biomarkers and therapeutic targets for the patients with CRC.

scholarly journals Identification of lnc RNAs Related to Prognosis of Patients With Colorectal Cancer

2020 ◽  
Vol 19 ◽  
pp. 153303382096212
Author(s):  
Yuqi Sun ◽  
Peng Peng ◽  
Lanlan He ◽  
Xueren Gao
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Score Model ◽  
Prognostic Prediction

The purpose of this study was to identify long noncoding RNAs (lncRNAs) related to prognosis of patients with colorectal cancer (CRC) and develop a prognostic prediction model for CRC. Transcriptome data and survival information of CRC patients were downloaded from The Cancer Genome Atlas. The differentially expressed lncRNAs (DElncRNAs) between CRC and normal colorectal tissues were identified by the edgeR package. The association of DElncRNAs expression with prognosis of CRC patients was analyzed by the survival package. A nomogram predicting 3- and 5- year overall survival of CRC patients was drawn by the rms package. A total of 1046 DElncRNAs were identified, including 271 down-regulated and 775 up-regulated lncRNAs in CRC. Multivariate Cox regression analysis showed 10 lncRNAs related to the prognosis of CRC patients. Thereinto high expression of AC004009.1, LHX1-DT, ELFN1-AS1, AL136307.1, AC087379.2, RBAKDN and AC078820.1 was associated with poorer prognosis of CRC patients. High expression of LINC01055, AL590483.1 and AC008514.1 was associated with better prognosis of CRC patients. Furthermore, the risk score model developed based on the 10 lncRNAs could effectively predict overall survival of CRC patients. In conclusion, 10 prognostic biomarkers for CRC were identified, which would be helpful to understand the role of lncRNAs in CRC progression.

scholarly journals Comprehensive Analysis Reveals a 4-Gene Signature in Predicting Response to Temozolomide in Low-Grade Glioma Patients

2019 ◽  
Vol 26 (1) ◽  
pp. 107327481985511 ◽  
Author(s):  
Qi Wang ◽  
Zongze He ◽  
Yong Chen
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Homologous Recombination ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Gene Signature ◽  
Low Grade Glioma ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Primary Therapy

Low-grade gliomas (LGGs) are a highly heterogeneous group of slow-growing, lethal, diffusive brain tumors. Temozolomide (TMZ) is a frequently used primary chemotherapeutic agent for LGGs. Currently there is no consensus as to the optimal biomarkers to predict the efficacy of TMZ, which calls for decision-making for each patient while considering molecular profiles. Low-grade glioma data sets were retrieved from The Cancer Genome Atlas. Cox regression and survival analyses were applied to identify clinical features significantly associated with survival. Subsequently, Ordinal logistic regression, co-expression, and Cox regression analyses were applied to identify genes that correlate significantly with response rate, disease-free survival, and overall survival of patients receiving TMZ as primary therapy. Finally, gene expression and methylation analyses were exploited to explain the mechanism between these gene expression and TMZ efficacy in LGG patients. Overall survival was significantly correlated with age, Karnofsky Performance Status score, and histological grade, but not with IDH1 mutation status. Using 3 distinct efficacy end points, regression and co-expression analyses further identified a novel 4-gene signature of ASPM, CCNB1, EXO1, and KIF23 which negatively correlated with response to TMZ therapy. In addition, expression of the 4-gene signature was associated with those of genes involved in homologous recombination. Finally, expression and methylation profiling identified a largely unknown olfactory receptor OR51F2 as potential mediator of the roles of the 4-gene signature in reducing TMZ efficacy. Taken together, these findings propose the 4-gene signature as a novel panel of efficacy predictors of TMZ therapy, as well as potential downstream mechanisms, including homologous recombination, OR51F2, and DNA methylation independent of MGMT.

scholarly journals Identification and Validation of EMT-Related lncRNA Prognostic Signature for Colorectal Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Danfeng Li ◽  
Xiaosheng Lin ◽  
Binlie Chen ◽  
Zhiyan Ma ◽  
Yongming Zeng ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Clinical Information ◽  
Low Risk ◽  
Expression Data ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis

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.

scholarly journals Colorectal Cancer Prognosis is Not Associated with BRAF and KRAS Mutations-A STROBE Compliant Study

2019 ◽  
Vol 8 (1) ◽  
pp. 111 ◽  
Author(s):  
Joon-Hyop Lee ◽  
Jiyoung Ahn ◽  
Won Seo Park ◽  
Eun Kyung Choe ◽  
Eunyoung Kim ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Braf Mutation ◽  
Disease Free Survival ◽  
The Cancer Genome Atlas ◽  
Kras Mutations ◽  
Viral Oncogene ◽  
Mutational Status ◽  
Mutation Group ◽  
Viral Oncogene Homolog

Background: We investigated the associations between v-Raf murine sarcoma viral oncogene homolog B1 (BRAFV600E, henceforth BRAF) and v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations and colorectal cancer (CRC) prognosis, using The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GSE39582) datasets. Materials and Methods: The effects of BRAF and KRAS mutations on overall survival (OS) and disease-free survival (DFS) of CRC were evaluated. Results: The mutational status of BRAF and KRAS genes was not associated with overall survival (OS) or DFS of the CRC patients drawn from the TCGA database. The 3-year OS and DFS rates of the BRAF mutation (+) vs. mutation (−) groups were 92.6% vs. 90.4% and 79.7% vs. 68.4%, respectively. The 3-year OS and DFS rates of the KRAS mutation (+) vs. mutation (−) groups were 90.4% vs. 90.5% and 65.3% vs. 73.5%, respectively. In stage II patients, however, the 3-year OS rate was lower in the BRAF mutation (+) group than in the mutation (−) group (85.5% vs. 97.7%, p <0.001). The mutational status of BRAF genes of 497 CRC patients drawn from the GSE39582 database was not associated with OS or DFS. The 3-year OS and DFS rates of BRAF mutation (+) vs. mutation (−) groups were 75.7% vs. 78.9% and 73.6% vs. 71.1%, respectively. However, KRAS mutational status had an effect on 3-year OS rate (71.9% mutation (+) vs. 83% mutation (−), p = 0.05) and DFS rate (66.3% mutation (+) vs. 74.6% mutation (−), p = 0.013). Conclusions: We found no consistent association between the mutational status of BRAF nor KRAS and the OS and DFS of CRC patients from the TCGA and GSE39582 databases. Studies with longer-term records and larger patient numbers may be necessary to expound the influence of BRAF and KRAS mutations on the outcomes of CRC.

scholarly journals The tumor immune microenvironment transcriptomic subtypes of colorectal cancer for prognosis and development of precise immunotherapy

2020 ◽  
Vol 8 (5) ◽  
pp. 381-389
Author(s):  
Yun-Qiang Tang ◽  
Tu-Feng Chen ◽  
Yan Zhang ◽  
Xiao-Chen Zhao ◽  
Yu-Zi Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
T Cell ◽  
T Cell Activation ◽  
Immune Activation ◽  
Cox Regression ◽  
Immune Dysfunction ◽  
The Cancer Genome Atlas ◽  
High Level ◽  
Cluster 2

Abstract Background Biomarkers based on immune context may guide prognosis prediction. T-cell inactivation, exclusion, or dysfunction could cause unfavorable tumor microenvironments, which affect immunotherapy and prognosis. However, none of the immuno-biomarkers reported to date can differentiate colorectal-cancer (CRC) patients. Thus, we aimed to classify CRC patients according to the levels of T-cell activation, exclusion, and dysfunction in the tumor microenvironment. Methods RNAseq data of 618 CRC patients from The Cancer Genome Atlas and microarray data of 316 CRC patients from Gene Expression Omnibus were analysed using the Tumor Immune Dysfunction and Exclusion algorithm. Unsupervised clustering was used to classify patients. Results Based on the expression signatures of myeloid-derived suppressor cells, cancer-associated fibroblasts, M2-like tumor-associated macrophages, cytotoxic T-lymphocytes, and PD-L1, all patients were clustered into four subtypes: cluster 1 had a high level of immune dysfunction, cluster 2 had a low level of immune activation, cluster 3 had intense immune exclusion, and cluster 4 had a high level of immune activation and a moderate level of both dysfunction and exclusion signatures. Compared with cluster 1, the hazard ratios and 95% confidential intervals for overall survival were 0.63 (0.35–1.13) for cluster 2, 0.55 (0.29–1.03) for cluster 3, and 0.30 (0.14–0.64) for cluster 4 in multivariate Cox regression. Similar immune clustering and prognosis patterns were obtained upon validation in the GSE39582 cohort. In subgroup analysis, immune clustering was significantly associated with overall survival among stage I/II patients, microsatellite stable/instability-low patients, and patients not treated with adjuvant therapy. Conclusions Our findings demonstrated that classifying CRC patients into different immune subtypes serves as a reliable prognosis predictor and may help to refine patient selection for personalized cancer immunotherapy.

scholarly journals The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shu Gong ◽  
Weijian Ye ◽  
Tiankai Liu ◽  
Shaofen Jian ◽  
Wenhua Liu
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
And Gender

Aims. The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients. Methods. The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort. Results. Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender. Conclusions. We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.

scholarly journals Predicting the Survival and Immune Landscape of Colorectal Cancer Patients Using an Immune-Related lncRNA Pair Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Ma ◽  
Xin Zhang ◽  
Xudong Zhao ◽  
Nan Zhang ◽  
Sixin Zhou ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Kinase Inhibitor ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Immune Checkpoints ◽  
Cox Regression Analysis

BackgroundAccumulating evidence has demonstrated that immune-related long non-coding ribonucleic acids (irlncRNAs) can be used as prognostic indicators of overall survival (OS) in patients with colorectal cancer (CRC). Our aim in this research, therefore, was to construct a risk model using irlncRNA pairs with no requirement for a specific expression level, in hope of reliably predicting the prognosis and immune landscape of CRC patients.MethodsClinical and transcriptome profiling data of CRC patients downloaded from the Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed (DE) irlncRNAs. The irlncRNA pairs significantly correlated with the prognosis of patients were screened out by univariable Cox regression analysis and a prognostic model was constructed by Lasso and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was then plotted, with the area under the curve calculated to confirm the reliability of the model. Based on the optimal cutoff value, CRC patients in the high- or low-risk groups were distinguished, laying the ground for evaluating the risk model from the following perspectives: survival, clinicopathological traits, tumor-infiltrating immune cells (TIICs), antitumor drug efficacy, kinase inhibitor efficacy, and molecules related to immune checkpoints.ResultsA prognostic model consisting of 15 irlncRNA pairs was constructed, which was found to have a high correlation with patient prognosis in a cohort from the TCGA (p &lt; 0.001, HR = 1.089, 95% CI [1.067–1.112]). According to both univariate and multivariate Cox analyses, this model could be used as an independent prognostic indicator in the TCGA cohort (p &lt; 0.001). Effective differentiation between high- and low-risk patients was also accomplished, on the basis of aggressive clinicopathological characteristics, sensitivity to antitumor drugs, and kinase inhibitors, the tumor immune infiltration status, and the expression levels of specific molecules related to immune checkpoints.ConclusionThe prognostic model established with irlncRNA pairs is a promising indicator for prognosis prediction in CRC patients.

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