Expression of ACE2 , the SARS-CoV-2 receptor, and TMPRSS2 in prostate epithelial cells

  1. Hanbing Song
  2. Bobak Seddighzadeh
  3. Matthew R. Cooperberg
  4. Franklin W. Huang

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Abstract

The COVID-19 pandemic has spread across more than 200 countries and resulted in over 170,000 deaths. For unclear reasons, higher mortality rates from COVID-19 have been reported in men compared to women. While the SARS-CoV-2 receptor ACE2 and serine protease TMPRSS2 have been detected in lung and other tissues, it is not clear what sex differences may exist. We analyzed a publicly-available normal human prostate single-cell RNA sequencing dataset and found TMPRSS2 and ACE2 co-expressing cells in epithelial cells, with a higher proportion in club and hillock cells. Then we investigated datasets of lung epithelial cells and also found club cells co-expressing TMPRSS2 and ACE2 . A comparison of ACE2 expression in lung tissue between males and females showed higher expression in males and a larger proportion of ACE2 + cells in male type II pneumocytes, with preliminary evidence that type II pneumocytes of all lung epithelial cell types showed the highest expression of ACE2 . These results raise the possibility that sex differences in ACE2 expression and the presence of double-positive cells in the prostate may contribute to the observed disparities of COVID-19.

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    SciScore for 10.1101/2020.04.24.056259: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThe statistical significance of expression levels between males and females was computed from an unpaired two-samples Wilcoxon test and the proportions of expression between males and females were compared using Fisher’s Exact tests.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Gene expression in each dataset was normalized and scaled following the standard Seurat workflow, and sample batch effects were removed using the integration function implemented in Seurat 3.1.4 [16].
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)

    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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.04.24.056259 on bioRxiv