The SARS-CoV-2 host cell membrane fusion protein TMPRSS2 is a tumor suppressor and its downregulation correlates with increased antitumor immunity and immunotherapy response in lung adenocarcinoma

  1. Zhixian Liu
  2. Zhilan Zhang
  3. Qiushi Feng
  4. Xiaosheng Wang

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Abstract

Background

TMPRSS2 is a host cell membrane fusion protein for SARS-CoV-2 invading human host cells. It also has an association with cancer, particularly prostate cancer. However, its association with lung cancer remains insufficiently explored. Thus, an in-depth investigation into the association between TMPRSS2 and lung cancer is significant, considering that lung cancer is the leading cause of cancer death and that the lungs are the primary organ SARS-CoV-2 attacks.

Methods

Using five lung adenocarcinoma (LUAD) genomics datasets, we explored associations between TMPRSS2 expression and immune signatures, cancer-associated pathways, tumor progression phenotypes, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we validated the findings from the bioinformatics analysis by performing in vitro experiments with the human LUAD cell line A549 and in vivo experiments with mouse tumor models. We also validated our findings in LUAD patients from Jiangsu Cancer Hospital, China.

Results

TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD8+ T and NK cells and immune cytolytic activity in LUAD, which represent antitumor immune signatures. Meanwhile, TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD4+ regulatory T cells and myeloid-derived suppressor cells and PD-L1 expression levels in LUAD, which represent antitumor immunosuppressive signatures. However, TMPRSS2 expression levels showed a significant positive correlation with the ratios of immune-stimulatory/immune-inhibitory signatures (CD8+ T cells/PD-L1) in LUAD. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory signatures than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with elevated activities of many oncogenic pathways in LUAD, including cell cycle, mismatch repair, p53, and extracellular matrix (ECM) signaling. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor advancement, and worse survival in LUAD. In vitro and in vivo experiments validated the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2 -knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1.

Conclusions

TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a connection between lung cancer and pneumonia caused by SARS-CoV-2 infection.

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  1. ScreenIT

    SciScore for 10.1101/2021.06.30.450490: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: Tumor volumes did not exceed the maximum allowable size according to the LJI IACUC animal experimental protocol.
    Sex as a biological variablenot detected.
    RandomizationThe migrated cells were counted at 200x magnification under the microscope using three randomly selected visual fields.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    PE anti-mouse TNF-α antibody (12-7321-81)
    anti-mouse TNF-α
    suggested: None
    , APC anti-mouse IFN-γ antibody (17-7311-81)
    anti-mouse IFN-γ
    suggested: None
    , APC anti-mouse CD279 (PD-1) antibody (12-9985-81), and APC anti-mouse CD223 (LAG-3) antibody (12-2231-81) were purchased from eBioscience (San Diego, CA).
    APC anti-mouse CD279
    suggested: None
    anti-mouse CD279
    suggested: None
    PD-1
    suggested: (Thermo Fisher Scientific Cat# 12-9985-81, RRID:AB_466294)
    anti-mouse CD223
    suggested: None
    LAG-3
    suggested: (Thermo Fisher Scientific Cat# 12-2231-81, RRID:AB_494216)
    Immunofluorescence of CD8, CD49b and PD-L1: Paraffin-embedded mice tumor tissue sections (3 µm thick) were subjected to immunofluorescence with CD8 (Abcam, ab22378), CD49b (Abcam, ab181548), or PD-L1 (Abcam, ab2134808) primary antibodies.
    CD8
    suggested: (Abcam Cat# ab22378, RRID:AB_447033)
    CD49b
    suggested: None
    PD-L1 (Abcam,
    suggested: None
    After antigen retrieval, 3% H2O2-methanol solution blocking inactivated enzymes, and goat serum blocking, tissue slides were incubated in wet box for 2 hours at 37°C with anti-CD8, CD49b, or anti-PD-L1 rabbit primary antibodies (1:100 dilution) in blocking solution, and were then dropped with FITC (1:100 dilution) secondary antibody 50-100ul and incubated at 37° for 1 hour in the dark.
    anti-PD-L1
    suggested: (Bio X Cell Cat# BE0101, RRID:AB_10949073)
    Experimental Models: Cell Lines
    SentencesResources
    A549 cells were seeded on the six well plate at a density of 5×104 cells/well, and NK92 cells were seeded on the membrane (polyethylene terephthalate, pore size of 0.4 µm) of the transwell chamber at a density of 5×104 cells/chamber.
    A549
    suggested: None
    NK92
    suggested: None
    Recombinant DNA
    SentencesResources
    1 plasmid to generate pLKO.
    pLKO
    suggested: RRID:Addgene_52920)
    1/vector and pLKO.1/ShTMPRSS2, respectively.
    pLKO.1/ShTMPRSS2
    suggested: None
    Software and Algorithms
    SentencesResources
    Datasets: We downloaded RNA-Seq gene expression profiling (level 3 and RSEM normalized), protein expression profiling, and clinical data for the TCGA-LUAD cohort from the Genomic Data Commons Data Portal (https://portal.gdc.cancer.gov/).
    https://portal.gdc.cancer.gov/
    suggested: (Genomic Data Commons Data Portal (GDC Data Portal, RRID:SCR_014514)
    We downloaded microarray gene expression profiling (normalized) and clinical data for other four LUAD cohorts (GSE12667 [10], GSE30219 [11], GSE31210 [12], and GSE50081 [13]) from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    We used GSEA [15] to identify KEGG [16] pathways significantly associated with a gene set with a threshold of adjusted p value < 0.05.
    GSEA
    suggested: (SeqGSEA, RRID:SCR_005724)
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    We performed the statistical analyses using the R programming software (https://cran.r-project.org/).
    https://cran.r-project.org/
    suggested: (CRAN, RRID:SCR_003005)
    Overlay images were reconstructed by using the free-share ImageJ software.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

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

    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 10.1101/2021.06.30.450490v1 on bioRxiv