| Literature DB >> 33231569 |
Huimin Li1,2, Longxiang Xie1, Lin Chen1, Lu Zhang1, Yali Han1, Zhongyi Yan1, Xiangqian Guo1.
Abstract
SARS-coronavirus 2 (SARS-CoV-2) has been spreading widely and posing an international challenge for both healthcare and society. At present, cancer has been identified as an individual risk factor for COVID-19. Angiotensin converting enzyme 2 (ACE2) and Cathepsin L/Cathepsin B (CTSL/B), which act as the receptor and entry-associated proteases of SARS-CoV-2 respectively, are pivotal for SARS-CoV-2 infection. To investigate the possible SARS-CoV-2 infection risk of pan-cancer, we analyzed the genetic alterations, RNA expression, DNA methylation, and the association with immune subtypes of ACE2 and CTSL/B with the prognosis in pan-cancer. Results showed the upregulation of CTSL/B and ACE2 in Pancreatic adenocarcinoma (PAAD) and Stomach adenocarcinoma (STAD) and demonstrated a positive correlation between copy number alteration (CNA) and gene expression for CTSB in PAAD and STAD. Hypomethylation and a negative correlation of gene expression and methylation for CTSB were detected in PAAD. In addition, ACE2 and CTSL/B are overexpressed in the IFN-gamma immune subtype of ovarian serous Cystadenocarcinoma (OV), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and Bladder urothelial carcinoma (BLCA). Our study presents a bioinformatics assessment for the potential risk of SARS-CoV-2 infection in pan-cancer.Entities:
Keywords: COVID-19; CTSL/B; SARS-CoV-2
Mesh:
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Year: 2020 PMID: 33231569 PMCID: PMC7746364 DOI: 10.18632/aging.104147
Source DB: PubMed Journal: Aging (Albany NY) ISSN: 1945-4589 Impact factor: 5.682
Figure 1The analyses of gene variation and epigenetics of CTSL/B and ACE2 in pan-cancer. (A) The distribution of differential expression of CTSL/B in 31 types of cancers and adjacent tissues based on TCGA and Genotype-Tissue Expression (GTEx) data (GEPIA). (B) The exhibition of tumors upregulating CTSL/B and ACE2, respectively. (C) The overlap of tumors overexpressing ACE2, CTSL/B using venny 2.0.2. (D) The significant difference analysis of CTSL/B in PAAD and STAD. (E) The mutation and CNA distribution of CTSL/B in pan-cancer (cBioportal). (F) The statistical difference graphs of DNA methylation for CTSB/L in PAAD (DiseaseMeth version 2.0). p<0.05 was regarded as significant.
Figure 2The identification of immune subtypes and prognosis for CTSL/B and ACE2 in pan-cancer. (A–C) The distribution graphs of ACE2 and CTSL/B in six immune subtypes in OV, CESC and BLCA. ACE2 and CTSL/B in OV, CESC and BLCA were most highly expressed in the C2 named IFN-gamma dominant subtype. (D–F) Forest maps analysis of overall survival for ACE2 and CTSL/B in pan-cancer (LOGpc). The blue boxes represent the overlap of tumors in which ACE2 and CTSB can predict adverse prognosis; the green boxes represent the overlap of tumors in which CTSB and CTSL can predict adverse prognosis. (G) The overall survival analyses of ACE2 and CTSB in LGG utilizing the LOGpc online tool based on TCGA data, with results showing that ACE2 and CTSB both predict poor prognosis. p<0.05 was regarded as significant; HR>1, p<0.05 represented poor prognosis.