scholarly journals Identification and Verification of a 17 Immune-Related Gene Pair Prognostic Signature for Colon Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Qianshi Zhang ◽  
Zhen Feng ◽  
Yongnian Zhang ◽  
Shasha Shi ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Poor Prognosis ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Prognostic Signature ◽  
Discovery Cohort ◽  
Immune Related Gene

Background. Colon cancer (CC) is a malignant tumor with a high incidence and poor prognosis. Accumulating evidence shows that the immune signature plays an important role in the tumorigenesis, progression, and prognosis of CC. Our study is aimed at establishing a novel robust immune-related gene pair signature for predicting the prognosis of CC. Methods. Gene expression profiles and corresponding clinical information are obtained from two public data sets: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO, GSE39582). We screened out immune-related gene pairs (IRGPs) associated with prognosis in the discovery cohort. Lasso-Cox proportional hazard regression was used to develop the best prognostic signature model. According to this, the patients in the validation cohort were divided into high immune-risk group and low immune-risk group, and the prediction ability of the signature model was verified by survival analysis and independent prognostic analysis. Results. A total of 17 IRGPs composed of 26 IRGs were used to construct a prognostic-related risk scoring model. This model accurately predicted the prognosis of CC patients, and the patients in the high immune-risk group indicated poor prognosis in the discovery cohort and validation cohort. Besides, whether in univariate or multivariate analysis, the IRGP signature was an independent prognostic factor. T cell CD4 memory resting in the low-risk group was significantly higher than that in the high-risk group. Functional analysis showed that the biological processes of the low-risk group included “TCA cycle” and “RNA degradation,” while the high-risk group was enriched in the “CAMs” and “focal adhesion” pathways. Conclusion. We have successfully established a signature model composed of 17 IRGPs, which provides a novel idea to predict the prognosis of CC patients.

scholarly journals Development and validation of an individualized immune-related gene pairs prognostic signature in papillary renal cell carcinoma

2020 ◽  
Author(s):  
Xianghong Zhou ◽  
Shi Qiu ◽  
Di Jin ◽  
Kun Jin ◽  
Xiaonan Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Prognostic Signature ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Immune Related Genes

Abstract Background: Papillary renal carcinoma (PRCC) is one of the important subtypes of kidney cancer, with a high degree of heterogeneity. At present, there is still a lack of robust and accurate biomarkers for the diagnosis, prognosis and treatment selection of PRCC. Considering the important role of tumor immunity in PRCC, we aim to construct a signature based on immune-related gene pairs (IRGPs) to estimate the prognostic of patients with PRCC.Methods: We obtained gene expression profiling and clinical information of patients with PRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), which were divided into discovery and validation cohorts, respectively. The immune-related genes in the samples were used to construct gene pairs, and the immune-related genes pairs (IRGPs) with robust impact for overall survival (OS) were screened out to construct the signature by univariate analysis, multivariate Cox analysis, and least absolute shrinkage and selection operator (Lasso) analysis. Then we verified the prognostic role of the signature, and assessed the relationship between this signature with tumor immune infiltration and functional pathways.Results: A total of 315 patients were included in our study, and divided to discovery (n=287) and validation (n=28) cohorts. Finally, we selected 14 IRGPs with a panel of 22 unique genes to construct the prognostic signature. According to the signature, we stratified patients into high-risk group and low-risk group. In both discovery and validation cohorts, the results of Kaplan-Meier analysis showed that there were significant differences in OS between the two groups (p<0.001). Combined with multiple clinical pathological factors, the results of multivariate analyses confirmed that this signature was an independent predictor of OS (HR, 3.548; 95%CI, 2.096−6.006; p<0.001). The results of immune infiltration analysis demonstrated that the abundance of multiple tumor-infiltration lymphocytes such as CD8+ T cells, Tregs, and T follicular cell helper were significantly higher in the high-risk group. Functional analysis showed that multiple immune-related signaling pathways were enriched in the high-risk group.Conclusions: We successfully established an individualized prognostic immune-related gene pairs signature, which can accurately and independently predict the OS of patients with PRCC.

Identifying an immune-related gene-pair for prognosis prediction of metastatic colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15565-e15565
Author(s):  
Qiqi Zhu ◽  
Du Cai ◽  
Wei Wang ◽  
Min-Er Zhong ◽  
Dejun Fan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Training Cohort ◽  
Gene Pairs ◽  
Immune Related Gene

e15565 Background: Few robust predictive biomarkers have been applied in clinical practice due to the heterogeneity of metastatic colorectal cancer (mCRC) . Using the gene pair method, the absolute expression value of genes can be converted into the relative order of genes, which can minimize the influence of the sequencing platform difference and batch effects, and improve the robustness of the model. The main objective of this study was to establish an immune-related gene pairs signature (IRGPs) and evaluate the impact of the IRGPs in predicting the prognosis in mCRC. Methods: A total of 205 mCRC patients containing overall survival (OS) information from the training cohort ( n = 119) and validation cohort ( n = 86) were enrolled in this study. LASSO algorithm was used to select prognosis related gene pairs. Univariate and multivariate analyses were used to validate the prognostic value of the IRGPs. Gene sets enrichment analysis (GSEA) and immune infiltration analysis were used to explore the underlying biological mechanism. Results: An IRGPs signature containing 22 gene pairs was constructed, which could significantly separate patients of the training cohort ( n = 119) and validation cohort ( n = 86) into the low-risk and high-risk group with different outcomes. Multivariate analysis with clinical factors confirmed the independent prognostic value of IRGPs that higher IRGPs was associated with worse prognosis (training cohort: hazard ratio (HR) = 10.54[4.99-22.32], P < 0.001; validation cohort: HR = 3.53[1.24-10.08], P = 0.012). GSEA showed that several metastasis and immune-related pathway including angiogenesis, TGF-β-signaling, epithelial-mesenchymal transition and inflammatory response were enriched in the high-risk group. Through further analysis of the immune factors, we found that the proportions of CD4+ memory T cell, regulatory T cell, and Myeloid dendritic cell were significantly higher in the low-risk group, while the infiltrations of the Macrophage (M0) and Neutrophil were significantly higher in the high-risk group. Conclusions: The IRGPs signature could predict the prognosis of mCRC patients. Further prospective validations are needed to confirm the clinical utility of IRGPs in the treatment decision.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse( P <0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals Validation of an Immune-related Gene Pair Index as a Prognostic Marker of Early-Stage Lung Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Zihao Wang ◽  
Xuan Xiang ◽  
Xiaoshan Wei ◽  
Linlin Ye ◽  
Yiran Niu ◽  
...  
Keyword(s):  
High Risk ◽  
Validation Cohort ◽  
Risk Group ◽  
Early Stage ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk ◽  
Data Sets ◽  
Related Gene ◽  
Immune Related Gene

Abstract Background. Lung squamous cell carcinoma (LUSC) is one of the subtypes of non-small-cell lung cancer (NSCLC) and accounts for approximately 20 to 30% of all lung cancers.Methods. In this study, we developed an immune-related gene pair index (IRGPI) for early-stage LUSC from 3 public LUSC data sets, including The Cancer Genome Atlas LUSC cohort and Gene Expression Omnibus data sets, and explored whether IRGPI could act as a prognostic marker to identify patients with early-stage LUSC at high risk.Results. IRGPI was constructed by 68 gene pairs consisting of 123 unique immune-related genes from TCGA LUSC cohort. In the derivation cohort, the hazard of death among high-risk group was 10.51 times that of the low-risk group (HR, 10.51; 95%CI, 6.96-15.86; p<0.001). The hazard of death among the high-risk group was 2.26 times that of the low-risk group (HR, 2.26; 95%CI, 1.2-4.25; p=0.009) in the GSE37745 validation cohort and was 3.2 times that of low-risk group (HR, 3.2; 95%CI, 0.98-10.4; p=0.042) in the GSE41271 validation cohort. The infiltrations of CD8+ T cells and T follicular helper cells were lower in the high-risk group, as compared with the low-risk group in the TCGA cohort (6.94% vs 9.63%, p=0.004; 2.15% vs 3%, p=0.002, respectively). The infiltrations of neutrophils, activated mast cells and monocytes were higher in the high-risk group, as compared with the low-risk group in the TCGA cohort (1.63% vs 0.72%, p=0.001; 1.64% vs 1.02%, p=0.007; 0.57% vs 0.35%, p=0.041, respectively).Conclusions. IRGPI is a significant prognostic biomarker for predicting overall survival in early-stage LUSC patients.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background. Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods. The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results. Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse(P＜0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion. We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Gene Pair ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
High Morbidity ◽  
Related Gene ◽  
Immune Genes ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis. Results Among 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

scholarly journals A Mitophagy-Related Gene Signature Associated With Prognosis and Immune Microenvironment in Colorectal Cancer

2022 ◽  
Author(s):  
Cong Zhang ◽  
Cailing Zeng ◽  
Shaoquan Xiong ◽  
Zewei Zhao ◽  
Guoyu Wu
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
High Risk Group ◽  
Related Gene ◽  
Prognostic Signature

Abstract Background: Colorectal cancer (CRC) is a heterogeneous disease and one of the most common malignancies in the world. Previous studies have found that mitophagy plays an important role in the progression of colorectal cancer. This study is aimed to investigate the relationship between mitophagy-related genes and the prognosis of patients with CRC.Methods: Gene expression profiles and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis were used to establish the prognostic signature composed of mitophagy related genes. Kaplan-Meier curve and receiver operating characteristic (ROC) curve were used to analyze patient survival and verify the predictive accuracy of the signature, respectively. Construction of a nomogram prognostic prediction model was based on risk scores and clinicopathological parameters. Using the Genomics of Drug Sensitivity in Cancer (GDSC) database and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to estimate the sensitivity of chemotherapy, targeted therapy and immunotherapy. Results: A total of 44 mitophagy-driven genes connected with CRC survival were identified, and prognostic signature was established based on the expression of 10 of them (AMBRA1, ATG14, MAP1LC3A, MAP1LC3B, OPTN, VDAC1, ATG5, CSNK2A2, MFN1, TOMM22). Patients were divided into high-risk and low-risk groups based on the median risk score, and the survival of patients in the high-risk group was significantly shorter than that of the low-risk group among the TCGA cohort (median OS 67.3 months vs not reached, p=0.00059) and two independent cohorts from GEO (median OS in GSE17536: 54.0 months vs not reached, p=0.0082; in GSE245: 7.7 months vs not reached, p=0.025). ROC curve showed that the area under the curves (AUC) of 1-, 3- and 5-year survival were 0.66, 0.66 and 0.64, respectively. Multivariate Cox regression analysis confirmed the independent prognostic value of the signature. Then we constructed a nomogram combining the risk score, age and M stage, which had a concordance index of survival prediction of 0.77 (95% CI=0.71-0.83) and more robust predictive sensitivity and specificity. Results showed that CD8+ T cells, regulatory T cells and activated NK cells were significantly more abundant in the high-risk group. Furthermore, patients in the high-risk group were more sensitive to potential targeted therapies, including Motesanib, ATRA, Olaparib, Selumetinib, AZD8055 and immunotherapy. Conclusion: In conclusion, we constructed and validated a novel mitophagy related gene signature that can be used as an independent prognostic biomarker for CRC, and may lead to better stratification and selection of precise treatment for CRC patients.

scholarly journals Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Gene Pair ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
High Morbidity ◽  
Related Gene ◽  
Immune Genes ◽  
Immune Related Gene

Abstract Background. Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD. Methods. The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis. Results. Among 1,647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P＜0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group. Conclusion. We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

scholarly journals Immune-Related Gene Expression and Cytokine Secretion Is Reduced Among African American Colon Cancer Patients

2020 ◽  
Vol 10 ◽  
Author(s):  
Jenny Paredes ◽  
Jovanny Zabaleta ◽  
Jone Garai ◽  
Ping Ji ◽  
Sayed Imtiaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
African American ◽  
Cancer Patients ◽  
Cytokine Secretion ◽  
Related Gene ◽  
Immune Related Gene

scholarly journals Establishment of Immune-related Gene Pair Signature to Predict Lung Adenocarcinoma Prognosis

2020 ◽  
Vol 29 ◽  
pp. 096368972097713
Author(s):  
Xueping Jiang ◽  
Yanping Gao ◽  
Nannan Zhang ◽  
Cheng Yuan ◽  
Yuan Luo ◽  
...  
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Gene Pair ◽  
Risk Group ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
M2 Macrophage ◽  
Related Gene ◽  
Immune Related Gene ◽  
Potential Biomarker

Tumor microenvironment (TME) has critical impacts on the pathogenesis of lung adenocarcinoma (LUAD). However, the molecular mechanism of TME effects on the prognosis of LUAD patients remains unclear. Our study aimed to establish an immune-related gene pair (IRGP) model for prognosis prediction and internal mechanism investigation. Based on 702 TME-related differentially expressed genes (DEGs) extracted from The Cancer Genome Atlas (TCGA) training cohort using the ESTIMATE algorithm, a 10-IRGP signature was established to predict LUAD patient prognosis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that DEGs were significantly associated with tumor immune response. In both TCGA training and Gene Expression Omnibus validation datasets, the risk score was an independent prognostic factor for LUAD patients using Lasso-Cox analysis, and patients in the high-risk group had poorer prognosis than those in the low-risk one. In the high-risk group, M2 macrophage and neutrophil infiltrations were higher, while the levels of T cell follicular helpers were significantly lower. The gene set enrichment analysis results showed that DNA repair signaling pathways were involved. In summary, we established an IRGP signature as a potential biomarker to predict the prognosis of LUAD patients.

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