scholarly journals Development and Verification of an Immune-Related Gene Pairs Prognostic Signature in Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiaofei Feng ◽  
Shanshan Mu ◽  
Yao Ma ◽  
Wenji Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Prognostic Signature ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Risk Patients

With the increasing prevalence of Hepatocellular carcinoma (HCC) and the poor prognosis of immunotherapy, reliable immune-related gene pairs (IRGPs) prognostic signature is required for personalized management and treatment of patients. Gene expression profiles and clinical information of HCC patients were obtained from the TCGA and ICGC databases. The IRGPs are constructed using immune-related genes (IRGs) with large variations. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct IRGPs signature. The IRGPs signature was verified through the ICGC cohort. 1,309 IRGPs were constructed from 90 IRGs with high variability. We obtained 50 IRGPs that were significantly connected to the prognosis and constructed a signature that included 17 IRGPs. In the TCGA and ICGC cohorts, patients were divided into high and low-risk patients by the IRGPs signature. The overall survival time of low-risk patients is longer than that of high-risk patients. After adjustment for clinical and pathological factors, multivariate analysis showed that the IRGPs signature is an independent prognostic factor. The Receiver operating characteristic (ROC) curve confirmed the accuracy of the signature. Besides, gene set enrichment analysis (GSEA) revealed that the signature is related to immune biological processes, and the immune microenvironment status is distinct in different risk patients. The proposed IRGPs signature can effectively assess the overall survival of HCC, and provide the relationship between the signature and the reactivity of immune checkpoint therapy and the sensitivity of targeted drugs, thereby providing new ideas for the diagnosis and treatment of the disease.

scholarly journals Prognostic Implications of Immune-Related Gene Pairs Signatures in Bladder Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Hui Xiong ◽  
Hui Gao ◽  
Jinding Hu ◽  
Yun Dai ◽  
Hanbo Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Related Gene ◽  
Gene Pairs ◽  
Immune Related Gene

Compelling evidence indicates that immune function is correlated with the prognosis of bladder cancer (BC). Here, we aimed to develop a clinically translatable immune-related gene pairs (IRGPs) prognostic signature to estimate the overall survival (OS) of bladder cancer. From the 251 prognostic-related IRGPs, 37 prognostic-related IRGPs were identified using LASSO regression. We identified IRGPs with the potential to be prognostic markers. The established risk scores divided BC patients into high and low risk score groups, and the survival analysis showed that risk score was related to OS in the TCGA-training set ( p < 0.001 ; HR = 7.5 [5.3, 10]). ROC curve analysis showed that the AUC for the 1-year, 3-year, and 5-year follow-up was 0.820, 0.883, and 0.879, respectively. The model was verified in the TCGA-testing set and external dataset GSE13507. Multivariate analysis showed that risk score was an independent prognostic predictor in patients with BC. In addition, significant differences were found in gene mutations, copy number variations, and gene expression levels in patients with BC between the high and low risk score groups. Gene set enrichment analysis showed that, in the high-risk score group, multiple immune-related pathways were inhibited, and multiple mesenchymal phenotype-related pathways were activated. Immune infiltration analysis revealed that immune cells associated with poor prognosis of BC were upregulated in the high-risk score group, whereas immune cells associated with a better prognosis of BC were downregulated in the high-risk score group. Other immunoregulatory genes were also differentially expressed between high and low risk score groups. A 37 IRGPs-based risk score signature is presented in this study. This signature can efficiently classify BC patients into high and low risk score groups. This signature can be exploited to select high-risk BC patients for more targeted treatment.

An Immune-Related Gene Pairs Signature Predicts Overall Survival in Melanoma

2021 ◽  
Author(s):  
Ding Pan ◽  
Qi-Feng Ou ◽  
Pan-Feng Wu ◽  
Fang Yu ◽  
Ju-Yu Tang
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Public Data

Abstract Background:The incidence rate and mortality rate of melanoma have been increasing in recent decades. Increasing evidence has depicted the correlation between melanoma prognosis and immune signature. Therefore, the aim of this study is to develop a robust prognostic immune-related gene pairs (IRGPs) signature for estimating overall survival (OS) of melanoma.Methods:Gene expression profiling and clinical information of melanoma patients were derived from two public data sets, divided into training and validation cohorts. Immune genes significantly associated with prognosis were selected. Results:Among 1,646 immune genes, a 25 IRGPs signature was built which was significantly associated with OS in the training cohort (P=1.80×10−22; hazard ratio [HR] =9.50 [6.04, 14.93]). In the validation datasets, the IRGPs signature significantly divided patients into high- vs low- risk groups considering their prognosis (P=2.47×10−4; HR =2.99 [1.66, 5.38]) and was prognostic in multivariate analysis. Functional analysis showed that several biological processes, including keratinization and pigment phenotype-related pathways, enriched in the high-risk group. Macrophages M0, NK cells resting and T cells gamma delta were significantly higher in the high-risk group compared with the low-risk group. Conclusions:We successfully constructed a robust IRGPs signature with prognostic values for melanoma, providing new insights into post-operational treatment strategies.

Development and validation of an immune-related gene-based prognostic signature in gastric cancer

2020 ◽  
Author(s):  
Penglei Ge ◽  
Xiaofang Chen ◽  
Yang Wu ◽  
Yubin Fu ◽  
Chunbo Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Risk Score ◽  
Clinical Characteristics ◽  
Expression Profiles ◽  
Low Risk ◽  
Survival Prediction ◽  
Related Gene ◽  
Prognostic Signature ◽  
Immune Related Gene

Abstract Background: Gastric cancer is a common lethal cancer worldwide. We aimed to develop a reliable, individualized, immune-related prognostic signature that can be used to stratify and estimate prognosis in patients with gastric cancer. Methods: This retrospective study analyzed the gene expression profiles of gastric cancer with tumor tissue samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, which included 676 cases in total. Immune genes from the InnateDB database were selected to develop and validate an immune-related prognostic model for gastric cancer patients. Results: An immune-related gene pair (IRGP) model was constructed that enabled us to stratify patients into high- and low-risk immune risk groups in the training set. Patients with a low risk score had a significantly longer median survival time than those with a high risk score. Further, we compared the predictive accuracy of the IRGP model with clinical characteristics, including TNM, grade, age, and stage. The results showed that the model had the highest mean C-index (0.69) compared with grade (0.55) or stage (0.60) in survival prediction. Then, we constructed a nomogram that integrated the IRGP model with independent clinical characteristics, which showed the best prognostic accuracy compared with other signatures. Conclusion: A clinical-immune signature based on IRGP is a promising prognostic biomarker in gastric cancer. Prospective studies are needed to further validate its accuracy and to test its clinical utility in individualized treatment.

scholarly journals Construction and Validation of an Immune-related Gene Pairs Prognostic Model for Breast Cancer

2021 ◽  
Author(s):  
Ying Zhong ◽  
Zhe Wang ◽  
Yidong Zhou ◽  
Feng Mao ◽  
Yan Lin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Model ◽  
Low Risk ◽  
Cancer Prognosis ◽  
Related Gene ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Risk Patients ◽  
Immune Related Genes

Abstract Background: Immunotherapy plays an increasingly important role in the treatment of advanced female breast cancer, which has the highest mortality rate among malignant tumors. The purpose of this study was to identify immune-related genes associated with breast cancer prognosis as possible targets of immunotherapy, and their related biological processes and signaling pathways.Methods: Clinical data and gene expression profiles of patients with breast cancer were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and divided into training (n = 1053) and verification (n = 508) groups. CIBERSORT was used to predict differences in immune cell infiltration in patient subsets stratified according to risk. Gene Ontology (GO) enrichment analysis was used to identify pathways associated with immune-related genes in patient subsets stratified according to risk.Results: The prognostic model composed of 27 immune-related gene pairs significantly distinguished between high- and low-risk patients. Univariate and multivariate analyses indicated that the model was an independent prognostic factor for breast cancer. Among the identified genes, APOBEC3G, PLXNB1, and C3AR1 had not been previously studied in breast cancer and warrant further exploration. CCR chemokine receptor binding, regulation of leukocyte-mediated cytotoxicity, T cell migration, T cell receptor complex, and other pathways were significantly enriched in low-risk patients. M2 and M0 macrophages were more highly expressed in high-risk than in low-risk patients. CD8+ T cells and naïve B cells were more abundant in low-risk than in high-risk patients.Conclusion: The immune-related gene pairs prognostic model developed in the current study can help assess breast cancer prognosis and provides a potential target and research direction for breast cancer immunotherapy in the future.

scholarly journals Development and verification of an immune‐related gene pairs prognostic signature in ovarian cancer

2021 ◽  
Vol 25 (6) ◽  
pp. 2918-2930
Author(s):  
Bao Zhang ◽  
Xiaocui Nie ◽  
Xinxin Miao ◽  
Shuo Wang ◽  
Jing Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Related Gene ◽  
Prognostic Signature ◽  
Gene Pairs ◽  
Immune Related Gene

scholarly journals Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rong-zhi Huang ◽  
Min Mao ◽  
Jie Zheng ◽  
Hai-qi Liang ◽  
Feng-ling Liu ◽  
...  
Keyword(s):  
Decision Making ◽  
Skin Cancer ◽  
Metastatic Melanoma ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Gene Set Enrichment Analysis ◽  
Comprehensive Treatment ◽  
Related Gene ◽  
Gene Pairs ◽  
Immune Related Gene

AbstractMelanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make prognosis prediction and systematic treatment difficult and ineffective. Therefore, we established a novel personalized immune-related gene pairs index (IRGPI) to predict the prognosis of patients with metastatic melanoma, which was conducive to provide new insights into clinical decision-making and prognostic monitoring for metastatic melanoma. Through complex analysis and filtering, we identified 24 immune-related gene pairs to build the model and obtained the optimal cut-off value from receiver operating characteristic curves, which divided the patients into high and low immune-risk groups. Meantime, the Kaplan–Meier analysis, Cox regression analysis and subgroup analysis showed that IRGPI had excellent prognostic value. Furthermore, IRGPI was shown that was closely associated with immune system in the subsequent tumor microenvironment analysis and gene set enrichment analysis. In addition, we broken through the data processing limitations of traditional researches in different platforms through the application of gene pairs, which would provide great credibility for our model. We believe that our research would provide a new perspective for clinical decision-making and prognostic monitoring in metastatic melanoma.

scholarly journals Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chunlei Wu ◽  
Quanteng Hu ◽  
Dehua Ma
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Related Gene ◽  
Cox Regression Analysis ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Pathological Subtype

AbstractLung adenocarcinoma (LUAD) is the main pathological subtype of Non-small cell lung cancer. We downloaded the gene expression profile and immune-related gene set from the TCGA and ImmPort database, respectively, to establish immune-related gene pairs (IRGPs). Then, IRGPs were subjected to univariate Cox regression analysis, LASSO regression analysis, and multivariable Cox regression analysis to screen and develop an IRGPs signature. The receiver operating characteristic curve (ROC) was applied for evaluating the predicting accuracy of this signature by calculating the area under ROC (AUC) and data from the GEO set was used to validate this signature. The relationship of 22 tumor-infiltrating immune cells (TIICs) to the immune risk score was also investigated. An IRGPs signature with 8 IRGPs was constructed. The AUC for 1- and 3-year overall survival in the TCGA set was 0.867 and 0.870, respectively. Similar results were observed in the AUCs of GEO set 1, 2 and 3 (GEO set 1 [1-year: 0.819; 3-year: 0.803]; GEO set 2 [1-year: 0.834; 3-year: 0.870]; GEO set 3 [1-year: 0.955; 3-year: 0.827]). Survival analysis demonstrated high-risk LUAD patients exhibited poorer prognosis. The multivariable Cox regression indicated that the risk score was an independent prognostic factor. The immune risk score was highly associated with several TIICs (Plasma cells, memory B cells, resting memory CD4 T cells, and activated NK cells). We developed a novel IRGPs signature for predicting 1- and 3- year overall survival in LUAD, which would be helpful for prognosis assessment of LUAD.

scholarly journals An immune-related gene pairs signature predicts overall survival in serous ovarian carcinoma

2019 ◽  
Vol Volume 12 ◽  
pp. 7005-7014 ◽  
Author(s):  
Liuyan Zhang ◽  
Ping Zhu ◽  
Yao Tong ◽  
Yuzhuo Wang ◽  
Haifen Ma ◽  
...  
Keyword(s):  
Overall Survival ◽  
Ovarian Carcinoma ◽  
Related Gene ◽  
Gene Pairs ◽  
Serous Ovarian Carcinoma ◽  
Immune Related Gene

scholarly journals A Novel Autophagy-Related lncRNA Gene Signature to Improve the Prognosis of Patients with Melanoma

2020 ◽  
Author(s):  
Yi Ding ◽  
Tian Li ◽  
Min Li ◽  
Tuersong Tayier ◽  
MeiLin Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Model ◽  
Risk Group ◽  
Clinical Information ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Positive Regulation ◽  
Risk Patients ◽  
Cox Analysis

Abstract Background: Autophagy and long non-coding RNAs (lncRNAs) have been the focus of research on the pathogenesis of melanoma. However, the autophagy network of lncRNAs in melanoma has not been reported. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma.Methods: We downloaded RNA-sequencing data and clinical information of melanoma from The Cancer Genome Atlas. The co-expression of autophagy-related genes (ARGs) and lncRNAs was analyzed. The risk model of autophagy-related lncRNAs was established by univariate and multivariate COX regression analyses, and the best prognostic index was evaluated combined with clinical data. Finally, gene set enrichment analysis was performed on patients in the high- and low-risk groups.Results: According to the results of the univariate COX analysis, only the overexpression of LINC00520 was associated with poor overall survival, unlike HLA-DQB1-AS1, USP30-AS1, AL645929, AL365361, LINC00324, and AC055822. The results of the multivariate COX analysis showed that the overall survival of patients in the high-risk group was shorter than that recorded in the low-risk group (p<0.001). Moreover, in the receiver operating characteristic curve of the risk model we constructed, the area under the curve (AUC) was 0.734, while the AUC of T and N was 0.707 and 0.658, respectively. The Gene Ontology was mainly enriched with the positive regulation of autophagy and the activation of the immune system. The results of the Kyoto Encyclopedia of Genes and Genomes enrichment were mostly related to autophagy, immunity, and melanin metabolism.Conclusion: The positive regulation of autophagy may slow the transition from low-risk patients to high-risk patients in melanoma. Furthermore, compared with clinical information, the autophagy-related lncRNAs risk model may better predict the prognosis of patients with melanoma and provide new treatment ideas.

scholarly journals Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis

2020 ◽  
Vol 27 (1) ◽  
pp. 107327482097711
Author(s):  
Jiasheng Lei ◽  
Dengyong Zhang ◽  
Chao Yao ◽  
Sheng Ding ◽  
Zheng Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
R Package ◽  
Gene Signature ◽  
Differentially Expressed ◽  
Related Gene ◽  
Patient Cohort ◽  
Immune Related Gene ◽  
Related Risk

Background: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC. Methods: Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 106. Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package. Results: HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort ( P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort ( P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I. Conclusion: In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer.

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