SARS-CoV-2 receptor ACE2 identifies immuno-hot tumors in breast cancer

  1. Jie Mei
  2. Yun Cai
  3. Rui Xu
  4. Xinqian Yu
  5. Lingyan Chen
  6. Tao Ma
  7. Tianshu Gao
  8. Fei Gao
  9. Yichao Zhu
  10. Yan Zhang

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Abstract

Angiotensin-converting enzyme 2 (ACE2) is known as a host cell receptor for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is identified to be dysregulated in multiple tumors. Although the characterization of abnormal ACE2 expression in malignancies has been preliminarily explored, in-depth analysis of ACE2 in breast cancer (BRCA) has not been elucidated. A systematic pan-cancer analysis was conducted to assess the expression pattern and immunological role of ACE2 based on RNA-sequencing (RNA-seq) data downloaded from The Cancer Genome Atlas (TCGA). Next, correlations between ACE2 expression immunological characteristics in the BRCA tumor microenvironment (TME) were evaluated. Also, the role of ACE2 in predicting the clinical features and the response to therapeutic options in BRCA was estimated. These findings were subsequently validated in another public transcriptomic cohort as well as a recruited cohort. ACE2 was lowly expressed in most cancers compared with adjacent tissues. ACE2 was positively correlated with immunomodulators, tumor-infiltrating immune cells (TIICs), cancer immunity cycles, immune checkpoints, and tumor mutation burden (TMB). Besides, high ACE2 levels indicated the triple-negative breast cancer (TNBC) subtype of BRCA, lower response to endocrine therapy and higher response to chemotherapy, anti-ERBB therapy, antiangiogenic therapy and immunotherapy. To sum up, ACE2 correlates with an inflamed TME and identifies immuno-hot tumors, which may be used as an auxiliary biomarker for the identification of immunological characteristics in BRCA.

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    SciScore for 10.1101/2021.05.10.443377: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    The primary antibodies used in the research were as following: anti-ACE2 (1:3000 dilution, Cat. ab15348, Abcam, Cambridge, UK)
    anti-ACE2
    suggested: (Abcam Cat# ab15348, RRID:AB_301861)
    Software and Algorithms
    SentencesResources
    Public datasets retrieval: The Cancer Genome Atlas (TCGA) data: The pan-cancer normalized RNA-seq datasets, copy number variant (CNV) data processed by GISTIC algorithm, 450K methylation data, mutation profiles, the activities of transcription factor (TF) calculated by RABIT, and clinical information were obtained from UCSC Xena data portal (https://xenabrowser.net/datapages/).
    GISTIC
    suggested: (GISTIC, RRID:SCR_000151)
    The somatic mutation data were obtained from TCGA (http://cancergenome.nih.gov/) and then used to calculate the tumor mutation burden (TMB) by R package “maftools”.
    http://cancergenome.nih.gov/
    suggested: (The Cancer Genome Atlas, RRID:SCR_003193)
    Prognostic analysis using PrognoScan: PrognoScan database (http://dna00.bio.kyutech.ac.jp/PrognoScan/) was applied to assess the prognostic value of ACE2 in BRCA across a large cohort of public microarray datasets [17].
    PrognoScan: PrognoScan
    suggested: None
    The functional roles of ACE2 in BRCA was predicted using the Linked Omics tool in term of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways by the gene set enrichment analysis (GSEA).
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    Moreover, in order to avoid calculation errors resulted from various algorithms which were developed to explore the relative abundance of TIICs in TME, we comprehensively estimated the infiltration levels of TIICs using the following independent algorithms: TIMER [21], EPIC [22], MCP-counter [23], quanTIseq [24] and TISIDB [25].
    TIMER
    suggested: (TIMER, RRID:SCR_018737)
    First, BRCA-related drug-target genes were screened using the Drugbank database (https://go.drugbank.com/).
    Drugbank
    suggested: (DrugBank, RRID:SCR_002700)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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