Dataset Information

Bioinformatic Analysis of Correlation between Immune Infiltration and COVID-19 in Cancer Patients.

ABSTRACT: In 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused infections worldwide. However, the correlation between the immune infiltration and coronavirus disease 2019 (COVID-19) susceptibility or severity in cancer patients remains to be fully elucidated. ACE2 expressions in normal tissues, cancers and cell lines were comprehensively assessed. Furthermore, we compared ACE2 expression between cancers and matched normal tissues through Gene Expression Profiling Interactive Analysis (GEPIA). In addition, we performed gene set enrichment analysis (GSEA) to investigate the related signaling pathways. Finally, the correlations between ACE2 expression and immune infiltration were investigated via Tumor Immune Estimation Resource (TIMER) and GEPIA. We found that ACE2 was predominantly expressed in both adult and fetal tissues from the digestive, urinary and male reproductive tracts; moreover, ACE2 expressions in corresponding cancers were generally higher than that in matched healthy tissues. GSEA showed that various metabolic and immune-related pathways were significantly associated with ACE2 expression across multiple cancer types. Intriguingly, we found that ACE2 expression correlated significantly with immune cell infiltration in both normal and cancer tissues, especially in the stomach and colon. These findings proposed a possible fecal-oral and maternal-fetal transmission of SARS-CoV-2 and suggested that cancers of the respiratory, digestive or urinary tracts would be more vulnerable to SARS-CoV-2 infection.

SUBMITTER: Huang X

PROVIDER: S-EPMC7378636 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Bioinformatic Analysis of Correlation between Immune Infiltration and COVID-19 in Cancer Patients.

Huang Xin X He Chaobin C Hua Xin X Kan Anna A Sun Shuxin S Wang Jun J Li Shengping S

International journal of biological sciences 20200706 13

In 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused infections worldwide. However, the correlation between the immune infiltration and coronavirus disease 2019 (COVID-19) susceptibility or severity in cancer patients remains to be fully elucidated. ACE2 expressions in normal tissues, cancers and cell lines were comprehensively assessed. Furthermore, we compared ACE2 expression between cancers and matched normal tissues through Gene Expression Profiling Interactive An ...[more]

PMID: 32760213

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Project description:Systemic juvenile idiopathic arthritis (sJIA) is a rare and serious type of JIA characterized by an unknown etiology and atypical manifestations in the early stage, and early diagnosis and effective treatment are needed. We aimed to identify diagnostic biomarkers, immune cells and pathways involved in sJIA pathogenesis as well as potential treatment targets. The GSE17590, GSE80060, and GSE112057 gene expression profiles from the Gene Expression Omnibus (GEO) database were screened to obtain differentially expressed genes (DEGs) between sJIA and healthy controls. Common DEGs were subjected to pathway enrichment analysis; a protein-protein interaction network was constructed, and hub genes were identified. In addition, functional annotation of hub genes was performed with GenCLiP2. Immune infiltration analysis was then conducted with xCell, and correlation analysis between immune cells and the enriched pathways identified from gene set variation analysis was performed. The Connectivity Map database was used to identify candidate molecules for treating sJIA patients. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was carried out, and the GEO dataset GSE8361 was applied for validation of hub gene expression levels in blood samples from healthy individuals with sJIA. A total of 73 common DEGs were identified, and analysis indicated enrichment of neutrophil and platelet functions and the MAPK pathway in sJIA. Six hub genes were identified, of which three had high diagnostic sensitivity and specificity; ARG1 and PGLYRP1 were validated by qRT-PCR and microarray data of the GSE8361 dataset. We found that increased megakaryocytes and decreased Th1 cells correlated positively and negatively with the MAPK pathway, respectively. Furthermore, MEK inhibitors and some kinase inhibitors of the MAPK family were identified as candidate agents for sJIA treatment. Our results indicate two candidate markers for sJIA diagnosis and reveal the important roles of platelets and the MAPK pathway in the pathogenesis of sJIA, providing a new perspective for exploring potential molecular targets for sJIA treatment.

Dataset Information

Bioinformatic Analysis of Correlation between Immune Infiltration and COVID-19 in Cancer Patients.

Publications

Bioinformatic Analysis of Correlation between Immune Infiltration and COVID-19 in Cancer Patients.

Similar Datasets

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