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ImmunoHorizonsPathologyPeer-reviewed journal article

PDLIM2 Repression: A Common Mechanism in Viral Lung Infection

Feng GaoiD, Yongzheng W Chen, Steven David ShapiroiD, Gutian Xiao, Zhaoxia Qu

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Abstract

BackgroundPDLIM2, a PDZ-LIM domain-containing protein expressed highest in the lung and immune cells, serves as a unique tumor suppressor and immune modulator, mainly by turning off the activation of the master transcription factors NF-{kappa}B and STAT3. While its role in cancer is established, the involvement of PDLIM2 in viral infection remains unclear. ResultsHere, we analyzed public gene expression data of blood leukocytes, bronchoalveolar lavage cells, and lung tissues from uninfected healthy humans and those infected with the respiratory virus SARS-CoV-2 or influenza. We found that PDLIM2 expression was repressed by viral infection, and notably, this repression correlated with the severity of infectious diseases. Consistently, the expression level of PDLIM2 was negatively associated with NF-{kappa}B and STAT3 activity across a diverse range of cell types, such as macrophages, monocytes, neutrophils, T cells, alveolar type 1 and 2 epithelial cells, airway epithelial cells, and fibroblasts. Accordingly, cells with low PDLIM2 expression exhibited aberrant activation of signaling pathways essential for cellular functions and immune responses. ConclusionsThese findings highlight PDLIM2 repression as a common mechanism underlying human viral infectious diseases and suggest PDLIM2 as a potential biomarker and therapeutic target for disease prognosis, prevention, and treatment.

In-depth summary

Claude Opus 5.5 · xhigh effort · 8 Nov 2026 · from the full text of version 2 (17 Sept 2025) · CC BY 4.0

Reanalysis of public transcriptomes shows PDLIM2 is repressed in influenza and COVID-19, with lower blood leukocyte levels in severe disease and NF-κB/STAT3 hyperactivation in low-PDLIM2 cells.

PDLIM2 switches off NF-κB and STAT3 and is a known checkpoint against lung cancer, chronic obstructive pulmonary disease and pulmonary fibrosis, but its role in respiratory viral infection was unresolved. The study uses public human transcriptomes from influenza and SARS-CoV-2 infection to test for PDLIM2 repression, links to severity, and signaling changes across immune and lung cell types.

Key results

  1. SuggestedPeripheral blood leukocytes from influenza and COVID-19 patients express less PDLIM2 than those from uninfected people, and the loss is greater in more severe disease for both infections. This points to a possible noninvasive prognostic readout.

    Influenza leukocyte microarray and COVID-19 leukocyte bulk RNA-seq, one point per patient in box plots, with severity groups compared by 1-way ANOVA or 2-tailed Student's t-test (P<0.05 threshold); the text gives no group sizes, fold changes or exact P values. · PDLIM2 repression by lung viral infection and…; Figure legends; Statistics

  2. SuggestedIn influenza blood scRNA-seq, neutrophils and monocytes have reduced PDLIM2 that inversely tracks NF-κB and STAT3 activity scores; PDLIM2-low neutrophils gain degranulation, necroptosis and neutrophil extracellular trap (NETosis) signaling but lose IL-10, interferon and CXCR4 signaling.

    Student's t-test on PDLIM2 levels; correlation R of PDLIM2 with summed pathway-gene scores; Qiagen Ingenuity Pathway Analysis (IPA) z-score deviation between median-split PDLIM2-low vs -high patient cells. PDLIM2-low monocytes show higher oxidative stress, senescence-associated secretory phenotype (SASP) and cytokine storm signaling. No R or z values printed. · Association of PDLIM2 repression with…; Association of PDLIM2 repression with…; PDLIM2 level-dependent pathway and function…; Figure legends

  3. SuggestedIn COVID-19 bronchoalveolar lavage macrophages and lung T cells, PDLIM2 is markedly reduced and inversely tracks NF-κB/STAT3 activity; PDLIM2-low macrophages show weaker phagocytosis and autophagy signaling, and PDLIM2-low T cells look more exhausted with higher SASP.

    Student's t-test vs uninfected controls plus PDLIM2 vs pathway-score correlations; in PDLIM2-low vs -high patient cells, macrophages gain oxidative stress, senescence and coronavirus pathogenesis signaling and lose insulin-like growth factor and S100 signaling; T cells lose Rho GDP-dissociation inhibitor (RhoGDI) signaling. No effect sizes printed. · Association of PDLIM2 repression with pathogenic…; Association of PDLIM2 repression with T-cell…; Figure legends

  4. SuggestedIn COVID-19 lungs, alveolar type 1 and 2 (AT1, AT2) cells, airway epithelial cells and fibroblasts all show PDLIM2 repression with NF-κB/STAT3 hyperactivation plus cell-specific changes, e.g. more viral endocytic entry and immunogenic death in AT2 cells, pro-fibrotic signaling in fibroblasts.

    IPA comparisons of PDLIM2-low vs -high patient cells: AT2 and airway cells lose peroxisome proliferator-activated receptor (PPAR) and RhoGDI signaling; AT1 cells lose chaperone-mediated autophagy; airway cells gain clathrin-mediated endocytosis; fibroblasts gain pulmonary fibrosis signaling and lose inhibition of matrix metalloproteases. No effect sizes printed. · Association of PDLIM2 repression with viral…; Association of PDLIM2 repression with alveolar…; Association of PDLIM2 repression with…; Association of PDLIM2 repression with…

  5. ClaimedEffects associated with PDLIM2 repression vary by cell type: CXCR4 signaling rises in PDLIM2-low monocytes but falls in neutrophils, cyclophilin signaling diverges between macrophages and neutrophils or fibroblasts, and antiviral interferon gains link to PDLIM2 loss in only some cell types.

    A Discussion synthesis of per-cell-type IPA results: antigen presentation, interferon and ISGylation signaling rise in all patient cell types, involving PDLIM2 repression in monocytes, AT1 cells, airway cells and fibroblasts, whereas PDLIM2-low neutrophils show weaker interferon and ISGylation signaling; no quantitative values given. · Discussion; Association of PDLIM2 repression with…

Methods, data and reproducibility

Retrospective reanalysis of public GEO microarray and bulk RNA-seq data (limma or DESeq2, GEO2R-style in R) and scRNA-seq data (Seurat clustering, Wilcoxon differential expression). Patient cells were median-split into PDLIM2-low and -high groups for Qiagen IPA pathway comparison, and PDLIM2 was correlated with summed-gene pathway activation scores.

  • Peripheral blood leukocyte transcriptomes: influenza (microarray) and COVID-19 (bulk RNA-seq) patients grouped by severity vs uninfected healthy donors · human · GSE101702; GSE157103 (named in microarray/bulk R scripts; virus mapping not stated)
  • Blood scRNA-seq, influenza patients vs uninfected controls (neutrophils and monocytes analyzed) · human
  • Bronchoalveolar lavage (BAL) cell scRNA-seq, COVID-19 patients vs uninfected controls (lung macrophages) · human
  • Lung tissue scRNA-seq, COVID-19 patients vs controls (AT1, AT2, airway epithelial cells, fibroblasts); lung T cells also analyzed, source dataset not specified · human
  • scRNA-seq GEO series named in the Seurat R scripts (dataset-to-cohort mapping not stated; full list in Supplementary Table 1) · human · GSE243629; GSE145926; GSE171524
Methods & tools
GEO2R-style analysis in R/RStudio, limma, DESeq2, Seurat, PCA and UMAP/t-SNE, Wilcoxon rank sum test, Qiagen Ingenuity Pathway Analysis (IPA), Reactome, Fisher's exact test (IPA), Student's t-test and one-way ANOVA, Correlation coefficient R (covariance over SD product)
Reproducibility gaps
Pathway analysis relies on Qiagen IPA; the full dataset list is given in Supplementary Table 1 and pathway gene lists only in the GitHub scripts; the scRNA-seq script URLs are printed with a stray space.
Limitations (5)
  • The design is retrospective, drawing on heterogeneous public cohorts without detailed demographics or medical history; the prognostic value of PDLIM2 still needs prospective validation, particularly for influenza and COVID-19. · stated by the authors
  • B cells, dendritic cells and natural killer cells were excluded, and the subtypes within T cells and airway epithelial cells were not resolved. · stated by the authors
  • PDLIM2-low and -high groups were defined with expression thresholds (the median) computed within each dataset, which the authors note may limit generalizability. · stated by the authors
  • All evidence is correlational transcriptomics. No PDLIM2 perturbation or infection experiment tests whether repression drives the pathway changes or follows them, so calling repression a causal mechanism goes beyond the data shown. · noted in this summary
  • Pathway scores are unweighted sums of curated gene expression. The text does not say whether single-cell tests and correlations are aggregated by donor (pseudoreplication risk), and gives no sample sizes, R or z values. Some figure callouts are mismatched (T cells cited as Fig. 4). · noted in this summary

Read this if you study host responses to influenza or SARS-CoV-2 and want a cell-type-resolved transcriptomic survey linking reduced PDLIM2 to NF-κB/STAT3 and inflammatory pathway activation.

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