Colon Cancer and SARS-CoV-2: Impact of ACE2 Expression in Susceptibility to COVID-19

AbstractNovel coronavirus disease (COVID-19) pandemic has become a global health emergency. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with angiotensin-converting enzyme 2 (ACE2) to enter the cells and infects diverse human tissues. It has been reported that a few conditions, including cancer, predispose individuals to SARS-CoV-2 infection and severe form of COVID-19. These findings led us to evaluate the susceptibility of colon adenocarcinoma (COAD) patients to SARS-CoV-2 infection by investigation of ACE2 expression in their tumor tissues. The expression analysis revealed that both mRNA and protein levels of ACE2 had increased in colon cancer samples than normal group. Next, the prognosis analysis has indicated that the upregulation of ACE2 was not correlated with patient survival outcomes. Further assessment displayed the hypomethylation of the ACE2 gene promoter in COAD patients. Surprisingly, this methylation status has a strong negative correlation with ACE2 gene expression. The functional enrichment analysis of the genes that had similar expression patterns with ACE2 in colon cancer tissues demonstrated that they mainly enriched in Vitamin digestion and absorption, Sulfur relay system, and Fat digestion and absorption pathways. Finally, we found that ACE2 gene expression had a significant association with the immune cell infiltration levels in COAD patients. In conclusion, it has plausible that COAD patients are more likely to be infected with SARS-CoV-2 and experience severe injuries. Moreover, COVID-19 would bring unfavorable survival outcomes of patients with colon cancer by the way of immune cell infiltration linked process. The present study highlights the importance of preventive actions for COAD patients during the COVID-19 pandemic.

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Characteristics of the Immune Cell Infiltration Landscape in Gastric Cancer to Assistant Immunotherapy

Frontiers in Genetics ◽

10.3389/fgene.2021.793628 ◽

2022 ◽

Vol 12 ◽

Author(s):

Chenlu Li ◽

Jingjing Pan ◽

Yinyan Jiang ◽

Yan Yu ◽

Zhenlin Jin ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Signaling Pathways ◽

Poor Prognosis ◽

Immune Cell ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Therapeutic Responses

Background: Gastric cancer (GC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable indices especially immunotherapy-associated parameters that can predict the therapeutic responses to immunotherapy of GC patients.Methods: Gene expression profile of 854 GC patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE84433) with their corresponding clinical and somatic mutation data. Based on immune cell infiltration (ICI) levels, molecular clustering classification was performed to identify subtypes and ICI scores in GC patients. After functional enrichment analysis of subtypes, we further explored the correlation between ICI scores and Tumor Mutation Burden (TMB) and the significance in clinical immunotherapy response.Results: Three subtypes were identified based on ICI scores with distinct immunological and prognostic characteristics. The ICI-cluster C, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration and up-regulation of PD-L1. ICI scores were identified through using principal component analysis (PCA) and the low ICI scores were consistent with the increased TMB and the immune-activating signaling pathways. Contrarily, the high-ICI score cluster was involved in the immunosuppressive pathways, such as TGF-beta, MAPK and WNT signaling pathways, which might be responsible for poor prognosis of GC. External immunotherapy and chemotherapy cohorts validated the patients with lower ICI scores exhibited significant therapeutic responses and clinical benefits.Conclusion: This study elucidated that ICI score could sever as an effective prognostic and predictive indicator for immunotherapy in GC. These findings indicated that the systematic assessment of tumor ICI landscapes and identification of ICI scores have crucial clinical implications and facilitate tailoring optimal immunotherapeutic strategies.

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Identification of Molecular Markers Associated With the Pathophysiology and Treatment of Lupus Nephritis Based on Integrated Transcriptome Analysis

Frontiers in Genetics ◽

10.3389/fgene.2020.583629 ◽

2020 ◽

Vol 11 ◽

Author(s):

Menghui Yao ◽

Congcong Gao ◽

Chunyi Zhang ◽

Xueqi Di ◽

Wenfang Liang ◽

...

Keyword(s):

Gene Expression ◽

Molecular Markers ◽

Molecular Docking ◽

Lupus Nephritis ◽

Rna Sequencing ◽

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration

Lupus nephritis (LN) is a well-known complication of systemic lupus erythematosus and is its leading cause of morbidity and mortality. Our study aimed to identify the molecular markers associated with the pathophysiology and treatment of LN. The renal tissue gene expression profiles of LN patients in the GSE32591 dataset were downloaded as a discovery cohort from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified; weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules of DEGs; and gene function enrichment analysis, molecular crosstalk analysis, and immune cell infiltration analysis were performed to explore the pathophysiological changes in glomeruli and tubulointerstitia of LN patients. The crosstalk genes were validated in another RNA-sequencing cohort. DEGs common in RNA-sequencing dataset and GSE32591 were uploaded to the Connectivity Map (CMap) database to find prospective LN-related drugs. Molecular docking was used to verify the targeting association between candidate small molecular compounds and the potential target. In all, 420 DEGs were identified; five modules and two modules associated with LN were extracted in glomeruli and tubulointerstitia, respectively. Functional enrichment analysis showed that type I interferon (IFN) response was highly active, and some biological processes such as metabolism, detoxification, and ion transport were impaired in LN. Gene transcription in glomeruli and tubulointerstitia might affect each other, and some crosstalk genes, such as IRF7, HLA-DRA, ISG15, PSMB8, and IFITM3, play important roles in this process. Immune cell infiltration analysis revealed that monocytes and macrophages were increased in glomeruli and tubulointerstitia, respectively. CMap analysis identified proscillaridin as a possible drug to treat LN. Molecular docking showed proscillaridin forms four hydrogen bonds with the SH2 domain of signal transducer and activator of transcription 1 (STAT1). The findings of our study may shed light on the pathophysiology of LN and provide potential therapeutic targets for LN.

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Expression, Prognosis, and Immune Infiltrates Analyses of E2Fs in Human Brain and CNS Cancer

BioMed Research International ◽

10.1155/2020/6281635 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Pan Liao ◽

Shuzhen Han ◽

Honglan Qu

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Immune Cell ◽

Expression Patterns ◽

Therapeutic Targets ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Immune Infiltration ◽

Cns Cancer

Objective. We investigated the expression patterns, potential functions, unique prognostic value, and potential therapeutic targets of E2Fs in brain and CNS cancer and tumor-infiltrating immune cell microenvironments. Methods. We analyzed E2F mRNA expression levels in diverse cancer types via Oncomine and GEPIA databases, respectively. Moreover, we evaluated the prognostic values using GEPIA database and TCGAportal database and the correlation of E2F expression with immune infiltration and the correlation between immune cell infiltration and GBM and LGG prognosis via TIMER database. Then, cBioPortal, GeneMANIA, and DAVID databases were used for mutation analysis, PPI network analysis of coexpressed gene, and functional enrichment analysis. Results. E2F1-8 expression increased in most cancers, including brain and CNS cancer. Higher expression in E2F1, 2, 4, 6, 7, and 8 indicated poor OS of LGG. Higher E2F3–6 and E2F1–8 expressions correlated with poor prognosis and increased immune infiltration levels in CD8+ T cells, macrophages, neutrophils, and DCs in GBM and CD8+ T cells, B cells, CD4+ T cells, neutrophils, macrophages, and DCs in LGG, respectively. Conclusion. E2F1–8 and E2F2–8 could be hopeful prognostic biomarkers of GBM and LGG, respectively. E2F3–6 and E2F1–8 could be likely therapeutic targets in patients with immune cell infiltration of GBM and LGG, respectively.

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Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1804506115 ◽

2018 ◽

Vol 115 (50) ◽

pp. E11701-E11710 ◽

Cited By ~ 42

Author(s):

Yoong Wearn Lim ◽

Haiyin Chen-Harris ◽

Oleg Mayba ◽

Steve Lianoglou ◽

Arthur Wuster ◽

...

Keyword(s):

Gene Expression ◽

Cancer Immunotherapy ◽

Genetic Variants ◽

Immune Cell ◽

Response To Therapy ◽

Cell Infiltration ◽

Cancer Type ◽

Immune Cell Infiltration ◽

Durable Response ◽

The Impact

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti–PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

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Glucose-6-Phosphate Dehydrogenase is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

10.21203/rs.3.rs-1232206/v1 ◽

2022 ◽

Author(s):

Yang Bu ◽

Kejun Liu ◽

Yiming Niu ◽

Ji Hao ◽

Lei Cui ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Microenvironment ◽

Liver Cancer ◽

Immune Cell ◽

Cox Regression ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Potential Biomarker ◽

Glucose 6 Phosphate Dehydrogenase

Abstract Background: Glucose-6-phosphate dehydrogenase (G6PD) plays an important role in the metabolic and immunological aspects of tumors. In hepatocellular carcinoma (HCC), the alteration of tumor microenvironment influences recurrence and metastasis. We extracted G6PD-related data from public databases of HCC tissues and used a bioinformatics approach to explore the correlation between G6PD expression and clinicopathological features and prognosis of immune cell infiltration in HCC.Methods: We extract G6PD expression information from TCGA and GEO databases in liver cancer tissues and normal tissues, validated by immunohistochemistry, and the correlation between G6PD expression and clinical features is analyzed, and the clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier, Cox regression and prognostic line graph models. Functional enrichment analysis is performed by protein-protein interaction (PPI) network, GO/KEGG, GSEA and G6PD-associated differentially expressed genes (DEGs). TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results: Our results show that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues (P < 0.001). G6PD expression is associated with histological grade, pathological stage, T-stage, vascular infiltration and AFP level (P < 0.05); HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group (P < 0.05). The level of G6PD expression also affects the levels of macrophages, unactivated dendritic cells, B cells, and follicular helper T cells in the tumor microenvironment.Conclusion: High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma, and G6PD may be a target for immunotherapy of HCC.

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Identification of immune-based prostate cancer subtypes using mRNA expression

10.21203/rs.2.23038/v1 ◽

2020 ◽

Author(s):

Jukun Song ◽

Song He ◽

Wei Wang ◽

Jiaming Su ◽

Dongbo Yuan ◽

...

Keyword(s):

Prostate Cancer ◽

Immune Response ◽

Immune Cells ◽

Immune Cell ◽

Molecular Classification ◽

Cell Types ◽

Functional Enrichment ◽

Cell Infiltration ◽

Cell Subpopulation ◽

Immune Cell Infiltration

Abstract Background Immune infiltration of Prostate cancer (PCa) was highly related to clinical outcomes. However, previous works failed to elucidate the diversity of different immune cell types that make up the function of the immune response system. The aim of the study was to uncover the composition of TIICs in PCa utilizing the CIBERSORT algorithm and further reveal the molecular characteristics of PCa subtypes. Method In the present work, we employed the CIBERSORT method to evaluate the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We analyzed the correlation between immune cell infiltration and clinical information. The tumor-infiltrating immune cells of the TCGA PCa cohort were analyzed for the first time. The fractions of 22 immune cell types were imputed to determine the correlation between each immune cell subpopulation and clinical feature. Three types of molecular classification were identified via R-package of “CancerSubtypes”. The functional enrichment was analyzed in each subtype. The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen chemotherapeutic targets for the potential treatment of PCa. Results In current work, we utilized the CIBERSORT algorithm to assess the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We investigated the correlation between immune cell infiltration and clinical data. The tumor-infiltrating immune cells in the TCGA PCa cohort were analyzed. The 22 immune cells were also calculated to determine the correlation between each immune cell subpopulation and survival and response to chemotherapy. Three types of molecular classification were identified. Each subtype has specific molecular and clinical characteristics. Meanwhile, Cluster I is defined as advanced PCa, and is more likely to respond to immunotherapy. Conclusions Our results demonstrated that differences in immune response may be important drivers of PCa progression and response to treatment. The deconvolution algorithm of gene expression microarray data by CIBERSOFT provides useful information about the immune cell composition of PCa patients. In addition, we have found a subtype of immunopositive PCa subtype and will help to explore the reasons for the poor effect of PCa on immunotherapy, and it is expected that immunotherapy will be used to guide the individualized management and treatment of PCa patients.

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A lepidic gene signature predicts patient prognosis and sensitivity to immunotherapy in lung adenocarcinoma

Genome Medicine ◽

10.1186/s13073-021-01010-w ◽

2022 ◽

Vol 14 (1) ◽

Author(s):

Thinh T. Nguyen ◽

Hyun-Sung Lee ◽

Bryan M. Burt ◽

Jia Wu ◽

Jianjun Zhang ◽

...

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Lung Adenocarcinoma ◽

Gene Expression Analysis ◽

Immune Cell ◽

Expression Patterns ◽

Immune Cell Infiltration ◽

Histological Subtypes ◽

Genomic Features ◽

Differential Gene

Abstract Background Lung adenocarcinoma, the most common type of lung cancer, has a high level of morphologic heterogeneity and is composed of tumor cells of multiple histological subtypes. It has been reported that immune cell infiltration significantly impacts clinical outcomes of patients with lung adenocarcinoma. However, it is unclear whether histologic subtyping can reflect the tumor immune microenvironment, and whether histologic subtyping can be applied for therapeutic stratification of the current standard of care. Methods We inferred immune cell infiltration levels using a histological subtype-specific gene expression dataset. From differential gene expression analysis between different histological subtypes, we developed two gene signatures to computationally determine the relative abundance of lepidic and solid components (denoted as the L-score and S-score, respectively) in lung adenocarcinoma samples. These signatures enabled us to investigate the relationship between histological composition and clinical outcomes in lung adenocarcinoma using previously published datasets. Results We found dramatic immunological differences among histological subtypes. Differential gene expression analysis showed that the lepidic and solid subtypes could be differentiated based on their gene expression patterns while the other subtypes shared similar gene expression patterns. Our results indicated that higher L-scores were associated with prolonged survival, and higher S-scores were associated with shortened survival. L-scores and S-scores were also correlated with global genomic features such as tumor mutation burdens and driver genomic events. Interestingly, we observed significantly decreased L-scores and increased S-scores in lung adenocarcinoma samples with EGFR gene amplification but not in samples with EGFR gene mutations. In lung cancer cell lines, we observed significant correlations between L-scores and cell sensitivity to a number of targeted drugs including EGFR inhibitors. Moreover, lung cancer patients with higher L-scores were more likely to benefit from immune checkpoint blockade therapy. Conclusions Our findings provided further insights into evaluating histology composition in lung adenocarcinoma. The established signatures reflected that lepidic and solid subtypes in lung adenocarcinoma would be associated with prognosis, genomic features, and responses to targeted therapy and immunotherapy. The signatures therefore suggested potential clinical translation in predicting patient survival and treatment responses. In addition, our framework can be applied to other types of cancer with heterogeneous histological subtypes.

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CMET-30. COMPREHENSIVE METHYLOME ANALYSIS OF EGFR-MUTANT PRIMARY LUNG ADENOCARCINOMA AND MATCHED BRAIN METASTASIS

Neuro-Oncology ◽

10.1093/neuonc/noz175.231 ◽

2019 ◽

Vol 21 (Supplement_6) ◽

pp. vi58-vi58

Author(s):

Yasin Mamatjan ◽

Michael Cabanero ◽

Jeffrey Zuccato ◽

Jessica Weiss ◽

Shirin Karimi ◽

...

Keyword(s):

Dna Methylation ◽

Brain Metastasis ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Methylation Status ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Promoter Regions ◽

Primary Lung Adenocarcinoma ◽

Egfr Mutant

Abstract Brain metastasis (BM) in patients with EGFR-mutant lung adenocarcinoma is a major determinant of overall survival. Novel insight into the genetic and epigenetic underpinnings of BM development is lacking. The aim of this study is to compare the methylome of EGFR-mutant primary lung adenocarcinoma (EGFRM-PLA) and matched BM to identify important alterations for the mechanisms of BM. Matched EGFRM-PLA and BM tumors from seven patients were profiled using the Illumina Infinium MethylationEPIC BeadChip array. Unsupervised clustering analyses of the 14 samples showed a similar whole DNA methylation signatures between EGFRM-PLA and BM tumors. Furthermore, PCA plot highlighted that seven matched BM and lung tumor samples were clustered together closely based on matching pairs for the most variable probes (2.5K to 10K). These observations indicate high level of concordance and the same cell of origin. However, these fourteen samples clustered into two groups based on tumor site being lung or brain based on 83K differentially methylated CpG sites. Of the 83K probes, 2.4K were either hypermethylated or hypomethylated in all lung samples. A quarter of these 2.4K probes were located in promoter regions. Specifically, we identified differences in methylation status of EGFR/ALK promoter regions in lung tumors versus BM. CNV analyses showed higher deep deletions of chromosomes and genes in BM compared to EGFRM-PLA. Leukocytes unmethylation for purity (LUMP) scores which indicate immune cell infiltration were similar between lung and BM pairs (Mean LUMP_score=0.64) consistent with high immune cell infiltration. Our results indicated a similar whole DNA methylation signature of EGFRM-PLA and matched BM, while comprehensive analysis identified important differentially methylated probes. Distinct differences in CNV alterations were observed in lung versus brain samples. The BM and EGFRM-PLA showed similar tumor purity and immune cell components. Overall, tumor methylation profiling provides clinically important information regarding biology of BM in EGFRM-PLA.

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