scholarly journals Identification and quantification of immune infiltration landscape on therapy and prognosis in left- and right-sided colon cancer

2021 ◽  
Author(s):  
Jun-Nan Guo ◽  
Du Chen ◽  
Shen-Hui Deng ◽  
Jia-Rong Huang ◽  
Jin-Xuan Song ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Plasma Cells ◽  
Immune Cell ◽  
Principal Component ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Cell Protein ◽  
Molecular Features ◽  
Therapeutic Benefits ◽  
Key Genes

Abstract Background The left-sided and right-sided colon cancer (LCCs and RCCs, respectively) have unique molecular features and clinical heterogeneity. This study aimed to identify the characteristics of immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. Methods The independent gene datasets, corresponding somatic mutation and clinical information were collected from The Cancer Genome Atlas and Gene Expression Omnibus. The ICI contents were evaluated by “ESTIMATE” and “CIBERSORT.” We performed two computational algorithms to identify the ICI landscape related to prognosis and found the unique infiltration characteristics. Next, principal component analysis was conducted to construct ICI score based on three ICI patterns. We analyzed the correlation between ICI score and tumor mutation burden (TMB), and stratified patients into prognostic-related high- and low- ICI score groups (HSG and LSG, respectively). The role of ICI scores in the prediction of therapeutic benefits was investigated by "pRRophetic" and verified by Immunophenoscores (IPS) (TCIA database) and an independent immunotherapy cohort (IMvigor210). The key genes were preliminary screened by weighted gene co-expression network analysis based on ICI scores. And they were further identified at various levels, including single cell, protein and immunotherapy response. The predictive ability of ICI score for prognosis was also verified in IMvigor210 cohort. Results The ICI features with a better prognosis were marked by high plasma cells, dendritic cells and mast cells, low memory CD4+ T cells, M0 macrophages, M1 macrophages, as well as M2 macrophages. A high ICI score was characterized by an increased TMB and genomic instability related signaling pathways. The prognosis, sensitivities of targeted inhibitors and immunotherapy, IPS and expression of immune checkpoints were significantly different in HSG and LSG. The genes identified by ICI scores and various levels included CA2 and TSPAN1. Conclusion The identification of ICI subtypes and ICI scores will help gain insights into the heterogeneity in LCC and RCC, and identify patients probably benefiting from treatments. ICI scores and the key genes could serve as an effective biomarker to predict prognosis and the sensitivity of immunotherapy.

scholarly journals Immunogenomic Analyses of the Prognostic Predictive Model for Patients With Renal Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Feng ◽  
Jiahui Zhao ◽  
Dechao Wei ◽  
Pengju Guo ◽  
Xiaobing Yang ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Predictive Model ◽  
Risk Score ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Immune Checkpoints ◽  
Survival Outcomes ◽  
Prognostic Signature ◽  
Therapeutic Benefits

BackgroundRenal cell carcinoma (RCC) is associated with poor prognostic outcomes. The current stratifying system does not predict prognostic outcomes and therapeutic benefits precisely for RCC patients. Here, we aim to construct an immune prognostic predictive model to assist clinician to predict RCC prognosis.MethodsHerein, an immune prognostic signature was developed, and its predictive ability was confirmed in the kidney renal clear cell carcinoma (KIRC) cohorts based on The Cancer Genome Atlas (TCGA) dataset. Several immunogenomic analyses were conducted to investigate the correlations between immune risk scores and immune cell infiltrations, immune checkpoints, cancer genotypes, tumor mutational burden, and responses to chemotherapy and immunotherapy.ResultsThe immune prognostic signature contained 14 immune-associated genes and was found to be an independent prognostic factor for KIRC. Furthermore, the immune risk score was established as a novel marker for predicting the overall survival outcomes for RCC. The risk score was correlated with some significant immunophenotypic factors, including T cell infiltration, antitumor immunity, antitumor response, oncogenic pathways, and immunotherapeutic and chemotherapeutic response.ConclusionsThe immune prognostic, predictive model can be effectively and efficiently used in the prediction of survival outcomes and immunotherapeutic responses of RCC patients.

scholarly journals BRAF Mutation as a Potential Therapeutic Target for Checkpoint Inhibitors: A Comprehensive Analysis of Immune Microenvironment in BRAF Mutated Colon Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Shuyi Cen ◽  
Kun Liu ◽  
Yu Zheng ◽  
Jianzhen Shan ◽  
Chao Jing ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Braf Mutation ◽  
Plasma Cells ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Treatment Strategies ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Immune Microenvironment ◽  
Tissue Specimens

BRAF mutated colon cancer presents with poor survival, and the treatment strategies are controversial. The tumor microenvironment, which plays a key role in tumorigenesis as well as responses to treatments, of this subtype is largely unknown. In the present study, we analyzed the differences of immune microenvironments between BRAF mutated and BRAF wild-type colon cancer utilizing datasets from The Cancer Genome Atlas and Gene Expression Omnibus and confirmed the findings by tissue specimens of patients. We found that BRAF mutated colon cancer had more stromal cells, more immune cell infiltration, and lower tumor purity. Many immunotherapeutic targets, including PD-1, PD-L1, CTLA-4, LAG-3, and TIM-3, were highly expressed in BRAF mutated patients. BRAF mutation was also correlated with higher proportions of neutrophils and macrophages M1, and lower proportions of plasma cells, dendritic cells resting, and T cells CD4 naïve. In conclusion, our study demonstrates a different pattern of the immune microenvironment in BRAF mutated colon cancer and provides insights into the future use of checkpoint inhibitors in this subgroup of patients.

scholarly journals Exploration of the role of tumor mutation burden in clinical significance, immunotherapy response predictor and immune cell infiltration in colon cancer

2020 ◽  
Author(s):  
Zhengshui Xu ◽  
Chao Qu ◽  
Jing Guo ◽  
Xiaopeng Li ◽  
Yunhua Wu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Mrna Level ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Mutation Burden ◽  
Pathologic Features

Abstract Backgroud:Tumor mutation burden has become a powerful bio-marker to predict prognosis and immunotherapy responsiveness to patients in various cancers, but the role of TMB in colon cancer is still unclear.Methods:The transcriptome profiling data of colon patients and the simple nucleotide variation data of colon cases were downloaded from the Cancer Genome Atlas (TCGA) database. The groups were divided into high TMB and low TMB group according to the median of TMB. Then we explored the relationship between immune checkpoints, immune cells and TMB, respectively. Results: Mutation profiles of 399 colon cancer samples were analyzed in TCGA database. The senior (age＞65) had a strong relationship with higher-TMB level(p=0.001). Low-TMB group correlated with advanced N stage (P＜0.001), M stage (P＜0.001), and pathologic stage(P＜0.001). High-TMB group had significantly higher mRNA level of PD-L1, TIGIT, HAVCR2, and LAG3 than low-TMB group, which indicated high-TMB referred to better immunotherapy responsiveness in colon cancer. And high-TMB level correlated with higher fractions of CD8T cells (p=0.021), higher CD4 memory T cells(p=0.039), follicular helper T cells (p=0.002)and M1 macrophages (p＜0.001), while the low-TMB groups correlated with higher regulator T cells (p=0.002). So high-TMB correlated with stronger immune cell infiltrationConclusions:The high TMB referred to better clinical pathologic features, better immunotherapy responsiveness and stronger immune cells infiltration in colon cancer. Hence TMB may be a very promising bio-marker to predict prognosis and immunotherapy responsiveness to patients in colon cancer.

scholarly journals Identification of Molecular Subtypes and a Prognostic Signature Based on Inflammation-Related Genes in Colon Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Chenjie Qiu ◽  
Wenxiang Shi ◽  
Huili Wu ◽  
Shenshan Zou ◽  
Jianchao Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Differential Expression Analysis ◽  
Human Leukocyte ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Immune Checkpoints ◽  
Prognostic Signature

Both tumour-infiltrating immune cells and inflammation-related genes that can mediate immune infiltration contribute to the initiation and prognosis of patients with colon cancer. In this study, we developed a method to predict the survival outcomes among colon cancer patients and direct immunotherapy and chemotherapy. We obtained patient data from The Cancer Genome Atlas (TCGA) and captured inflammation-related genes from the GeneCards database. The package “ConsensusClusterPlus” was used to generate molecular subtypes based on inflammation-related genes obtained by differential expression analysis and univariate Cox analysis. A prognostic signature including four genes (PLCG2, TIMP1, BDNF and IL13) was also constructed and was an independent prognostic factor. Cluster 2 and higher risk scores meant worse overall survival and higher expression of human leukocyte antigen and immune checkpoints. Immune cell infiltration calculated by the estimate, CIBERSORT, TIMER, ssGSEA algorithms, tumour immune dysfunction and exclusion (TIDE), and tumour stemness indices (TSIs) were also compared on the basis of inflammation-related molecular subtypes and the risk signature. In addition, analyses of stratification, somatic mutation, nomogram construction, chemotherapeutic response prediction and small-molecule drug prediction were performed based on the risk signature. We finally used qRT–PCR to detect the expression levels of four genes in colon cancer cell lines and obtained results consistent with the prediction. Our findings demonstrated a four-gene prognostic signature that could be useful for prognostication in colon cancer patients and designing personalized treatments, which could provide new versions of personalized management for these patients.

scholarly journals Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

scholarly journals A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

2021 ◽  
Vol 11 ◽  
Author(s):  
Ming Gao ◽  
Xinzhuang Wang ◽  
Dayong Han ◽  
Enzhou Lu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Immune Cell ◽  
Area Under The Curve ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Non Coding Rna ◽  
Cancer Genome Atlas ◽  
The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

scholarly journals SERPINE1 associated with remodeling of the tumor microenvironment in colon cancer progression: a novel therapeutic target

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaokun Wang ◽  
Li Pang ◽  
Zuolong Liu ◽  
Xiangwei Meng
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
The Relationship

Abstract Background The change of immune cell infiltration essentially influences the process of colorectal cancer development. The infiltration of immune cells can be regulated by a variety of genes. Thus, modeling the immune microenvironment of colorectal cancer by analyzing the genes involved can be more conducive to the in-depth understanding of carcinogenesis and the progression thereof. Methods In this study, the number of stromal and immune cells in malignant tumor tissues were first estimated by using expression data (ESTIMATE) and cell-type identification with relative subsets of known RNA transcripts (CIBERSORT) to calculate the proportion of infiltrating immune cell and stromal components of colon cancer samples from the Cancer Genome Atlas database. Then the relationship between the TMN Classification and prognosis of malignant tumors was evaluated. Results By investigating differentially expressed genes using COX regression and protein-protein interaction network (PPI), the candidate hub gene serine protease inhibitor family E member 1 (SERPINE1) was found to be associated with immune cell infiltration. Gene Set Enrichment Analysis (GSEA) further projected the potential pathways with elevated SERPINE1 expression to carcinogenesis and immunity. CIBERSORT was subsequently utilized to investigate the relationship between the expression differences of SERPINE1 and immune cell infiltration and to identify eight immune cells associated with SERPINE1 expression. Conclusion We found that SERPINE1 plays a role in the remodeling of the colon cancer microenvironment and the infiltration of immune cells.

scholarly journals Three Immune-Associated Subtypes of Diffuse Glioma Differ in Immune Infiltration, Immune Checkpoint Molecules, and Prognosis

2020 ◽  
Vol 10 ◽  
Author(s):  
Quanwei Zhou ◽  
Xuejun Yan ◽  
Weidong Liu ◽  
Wen Yin ◽  
Hongjuan Xu ◽  
...  
Keyword(s):  
Immune Cell ◽  
Cox Regression ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Checkpoints ◽  
Signal Pathways ◽  
Diffuse Glioma ◽  
Immune Infiltration ◽  
Immune Related Genes

Diffuse glioma is one of the most prevalent malignancies of the brain, with high heterogeneity of tumor-infiltrating immune cells. However, immune-associated subtypes of diffuse glioma have not been determined, nor has the effect of different immune-associated subtypes on disease prognosis and immune infiltration of diffuse glioma patients. We retrieved the expression profiles of immune-related genes from The Cancer Genome Atlas (TCGA) (n = 672) and GSE16011 (n = 268) cohorts and used them to identify subtypes of diffuse glioma via Consensus Cluster Plus analysis. We used the limma, clusterProfiler, ESTIMATE, and survival packages of R for differential analysis, functional enrichment, immune and stromal score evaluation respectively in three subtypes, and performed log-rank tests in immune subtypes of diffuse glioma. The immune-associated features of diffuse glioma in the two cohorts were characterized via bioinformatic analyses of the mRNA expression data of immune-related genes. Three subtypes (C1–3) of diffuse glioma were identified from TCGA data, and were verified using the GSE16011 cohort. We then evaluated their immune characteristics and clinical features. Our mRNA profiling analyses indicated that the different subtypes of diffuse glioma presented differential expression profile of specific genes and signal pathways in the TCGA cohort. Patients with subtype C1, who were mostly diagnosed with grade IV glioma, had poorer outcomes than patients with subtype C2 or C3. Subtype C1 was characterized by a higher degree of immune cell infiltration as estimated by GSVA, and more frequent wildtype IDH1. By contrast, subtype C3 included more grade II and IDH1-mutated glioma, and was associated with more infiltration of CD4+T cells. Most subtype C2 had the features between subtypes C1 and C3. Meanwhile, immune checkpoints and their ligand molecules, including PD1/(PD-L1/PDL2), CTLA4/(CD80/CD86), and B7H3/TLT2, were significantly upregulated in subtype C1 and downregulated in subtype C3. In addition, patients with subtype C1 exhibited more frequent gene mutations. Univariate and multivariate Cox regression analyses revealed that diffuse glioma subtype was an effective, independent, and better prognostic factor. Therefore, we established a novel immune-related classification of diffuse glioma, which provides potential immunotherapy targets for diffuse glioma.

scholarly journals Immune Gene Signature Delineates a Subclass of Papillary Thyroid Cancer with Unfavorable Clinical Outcomes

Cancers ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 494 ◽  
Author(s):  
Kyuryung Kim ◽  
Sora Jeon ◽  
Tae-Min Kim ◽  
Chan Jung
Keyword(s):  
Clinical Outcomes ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cytolytic Activity ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Immune Gene ◽  
Papillary Thyroid ◽  
Thyroid Cancers

Papillary thyroid carcinoma (PTC) represents a heterogeneous disease with diverse clinical outcomes highlighting a need to identify robust biomarkers with clinical relevance. We applied non-negative matrix factorization-based deconvolution to publicly available gene expression profiles of thyroid cancers in the Cancer Genome Atlas (TCGA) consortium. Among three metagene signatures identified, two signatures were enriched in canonical BRAF-like and RAS-like thyroid cancers with up-regulation of genes involved in oxidative phosphorylation and cell adhesions, respectively. The third metagene signature representing up-regulation of immune-related genes further segregated BRAF-like and RAS-like PTCs into their respective subgroups of immunoreactive (IR) and immunodeficient (ID), respectively. BRAF-IR PTCs showed enrichment of tumor infiltrating immune cells, tall cell variant PTC, and shorter recurrence-free survival compared to BRAF-ID PTCs. RAS-IR and RAS-ID PTC subtypes included majority of normal thyroid tissues and follicular variant PTC, respectively. Immunopathological features of PTC subtypes such as immune cell fraction, repertoire of T cell receptors, cytolytic activity, and expression level of immune checkpoints such as and PD-L1 and CTLA-4 were consistently observed in two different cohorts. Taken together, an immune-related metagene signature can classify PTCs into four molecular subtypes, featuring the distinct histologic type, genetic and transcriptional alterations, and potential clinical significance.

scholarly journals Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zaoqu Liu ◽  
Long Liu ◽  
Dechao Jiao ◽  
Chunguang Guo ◽  
Libo Wang ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Somatic Mutation ◽  
Antitumor Immunity ◽  
Immune Cell ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Potential Biomarker

Background: Esophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, with the benefit in EAC thus far been limited to a small fraction of patients.Methods: Using somatic mutation data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium, we delineated the somatic mutation landscape of EAC patients from US and England. Based on the expression data of TCGA cohort, multiple bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.Results: We found that RYR2 was a common frequently mutated gene in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC.Conclusion: This study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.

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