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SARS-CoV-2 receptor is co-expressed with elements of the kinin-kallikrein, renin-angiotensin and coagulation systems in alveolar cells.
SARS-CoV-2, the pathogenic agent of COVID-19, employs angiotensin converting enzyme-2 (ACE2) as its cell entry receptor. Clinical data reveal that in severe COVID-19, SARS-CoV-2 infects the lung, leading to a frequently lethal triad of respiratory insufficiency, acute cardiovascular failure, and coagulopathy. Physiologically, ACE2 plays a role in the regulation of three systems that could potentially be involved in the pathogenesis of severe COVID-19: the kinin-kallikrein system, resulting in acute lung inflammatory edema; the renin-angiotensin system, promoting cardiovascular instability; and the coagulation system, leading to thromboembolism. Here we assembled a healthy human lung cell atlas meta-analysis with ~ 130,000 public single-cell transcriptomes and show that key elements of the bradykinin, angiotensin and coagulation systems are co-expressed with ACE2 in alveolar cells and associated with their differentiation dynamics, which could explain how changes in ACE2 promoted by SARS-CoV-2 cell entry result in the development of the three most severe clinical components of COVID-19.
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Prognostic and immunological roles of ammonia-induced cell death-related genes in non-small cell lung cancer.
BACKGROUND: Lung cancer remains the predominant cause of cancer-related mortality globally, with non-small cell lung cancer (NSCLC) comprising approximately 85% of cases, despite advancements in immunotherapy. This challenge is primarily due to the persistent dysfunction of effector T cells within the tumor microenvironment (TME). Ammonia-induced cell death (AICD), a newly identified form of programmed cell death, leads to the attrition of CD8⁺ T cells and contributes to immune suppression. However, the clinical significance of AICD in NSCLC has yet to be elucidated. In light of this context, the current study seeks to investigate AICD-related genes and their prognostic and immunological implications in NSCLC. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were integrated with single-cell RNA sequencing and functional assays. Glutamine metabolism–related genes were retrieved from GeneCards and intersected with NSCLC differentially expressed genes to identify candidate AICD regulators. Prognostic value was evaluated by Kaplan–Meier survival and ROC analyses. Single-cell and immune infiltration analyses were used to define gene expression across malignant and immune subsets. Finally, Jurkat T cells were exposed to ammonia stress to validate gene function in AICD. RESULTS: Four genes—SLC7A5, SLC2A1, CAV1, and SPP1—emerged as key regulators of AICD in NSCLC. These genes were aberrantly expressed in tumors, stratified patient survival, and correlated with immune checkpoint activity and TME immunosuppression. A gene signature derived from the four regulators effectively predicted overall survival and immune response. Single-cell analysis confirmed their distribution across malignant and immune subpopulations. Functional assays demonstrated that CAV1, SPP1, and SLC7A5 protected against ammonia-induced T cell death, whereas SLC2A1 increased susceptibility. CONCLUSION: This study establishes AICD as a clinically relevant metabolic cell death mechanism in NSCLC and identifies SLC7A5, SLC2A1, CAV1, and SPP1 as potential prognostic biomarkers and therapeutic targets. Targeting ammonia metabolism may offer new strategies to overcome immune resistance and enhance immunotherapy efficacy in NSCLC.
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Reciprocal regulation of hMENA and TGF-β signaling in cancer-associated fibroblasts promotes EMT, immunosuppression, poor prognosis, and ICT resistance in NSCLC.
BACKGROUND: Cancer-associated fibroblasts (CAFs) significantly impact cancer progression and CAF subtypes are key determinants of response to immune checkpoint therapy (ICT). The transforming growth factor-β (TGF-β) signaling is a main pathway in protumorigenic activity of CAFs and resistance to ICT. The actin cytoskeleton regulator hMENA plays crucial roles in epithelial-mesenchymal transition (EMT) and regulates pathways critical to antitumor immune response, such as interferon-I and Axl-GAS6. METHODS: We constructed a single-cell atlas of CAFs using integrated public dataset. Experimental data were obtained by biochemical and molecular approaches in CAFs from freshly explanted non-small cell lung cancer (NSCLC) tissues hMENA silenced and in tumor cell lines or peripheral blood mononuclear cells treated with CAF conditioned medium. Multiparametric flow cytometry was used to characterize T cells. A gene signature indicative of ICT response was developed by a machine learning model. RESULTS: Computational analysis indicates that hMENA is primarily overexpressed in a myofibroblast cluster enriched for a TGF-β-activated CAF signature. Experimentally, we showed that TGF-β1 treatment increases hMENA expression and, reciprocally, hMENA/hMENAΔv6 modulate TGF-β1/2 production and secretion and transforming growth factor-β type II receptor expression in CAFs. Functionally, hMENA contributes to TGF-β1-driven CAF phenotype, programmed death-ligand 1 (PD-L1) upregulation, extracellular matrix remodeling and secretion of immunosuppressive cytokines/chemokines. The hMENA-driven TGF-β secretion in CAFs promotes PD-L1 expression and EMT in cancer cells by activating TGF-β signaling. On the tumor cell side, hMENA expression sustains the TGF-β signaling and EMT mediated by hMENA-driven CAFs secretome. This immunosuppressive secretome favors regulatory T cell (Treg) abundance and reduces CD8+ and CD4+ T cell functionality. Finally, based on the hMENA and TGF-β enriched CAF subtype, we developed a 9-gene signature, which in combination with hMENA/hMENAΔv6 correlates with increased Treg abundance and poor prognosis in the Cancer Genome Atlas NSCLC and associates with ICT resistance in Stand Up To Cancer (SU2C) and in phase III clinical trial (OAK) (NCT02008227) datasets. CONCLUSIONS: Our findings indicate that hMENA overexpression in CAFs defines a myofibroblast-like subset predominantly driven by TGF-β signaling, which sustains TGF-β1-mediated crosstalk between cancer cells and CAFs and impairs T-cell functionality. In NSCLC tissues, hMENAhigh CAFs associate with TGF-β and regulatory T-cell signatures and correlate with poor patient prognosis and resistance to immune checkpoint therapies, supporting their role as key contributors to an immunosuppressive, ICT-refractory tumor microenvironment.
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A single-cell atlas identifies pretreatment features of primary imatinib resistance in chronic myeloid leukemia.
Primary resistance to tyrosine kinase inhibitors (TKIs) is a significant barrier to optimal outcomes in chronic myeloid leukemia (CML), but factors contributing to response heterogeneity remain unclear. Using single-cell RNA (scRNA) sequencing, we identified 8 statistically significant features in pretreatment bone marrow, which correlated with either sensitivity (major molecular response or MMR) or extreme resistance to imatinib (eventual blast crisis [BC] transformation). Employing machine-learning, we identified leukemic stem cell (LSC) and natural killer (NK) cell gene expression profiles predicting imatinib response with >80% accuracy, including no false positives for predicting BC. A canonical erythroid-specifying (TAL1/KLF1/GATA1) regulon was a hallmark of LSCs from patients with MMR and was associated with erythroid progenitor [ERP] expansion in vivo (P < .05), and a 2- to 10-fold (6.3-fold in group A vs 1.09-fold in group C) erythroid over myeloid bias in vitro. Notably, ERPs demonstrated exquisite TKI sensitivity compared with myeloid progenitors (P < .001). These LSC features were lost with progressive resistance, and MYC- and IRF1-driven inflammatory regulons were evident in patients who progressed to transformation. Patients with MMR also exhibited a 56-fold expansion (P < .01) of a normally rare subset of hyperfunctional adaptive-like NK cells, which diminished with progressive resistance, whereas patients destined for BC accumulated inhibitory NKG2A+ NK cells favoring NK cell tolerance. Finally, we developed antibody panels to validate our scRNA-seq findings. These panels may be useful for prospective studies of primary resistance, and in assessing the contribution of predetermined vs acquired factors in TKI response heterogeneity.
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A multi-dimensional bioinformatic dissection of the molecular mechanisms in high-BMI-associated colorectal cancer: identification and validation of EGLN1 as a key target.
BACKGROUND: Colorectal cancer (CRC) represents a major global health burden, and a high body mass index (BMI) has been established as an independent risk factor. Despite this clear epidemiological association, the complex molecular mechanisms driving CRC progression in the context of high BMI remain to be fully elucidated. This study aimed to systematically investigate the genetic association and potential molecular mechanisms between high BMI and CRC through a multi-dimensional bioinformatic integrative analysis and to identify key therapeutic targets. METHODS: This study integrated global burden of disease data, a two-sample Mendelian randomization (MR) analysis of BMI and CRC, and analyses of differentially expressed genes and weighted gene co-expression network analysis (WGCNA) in CRC. By intersecting gene sets, we identified key genes in BMI-associated CRC (KGs-BACC) and subsequently performed Gene Ontology/Kyoto Encyclopedia of Genes and Genomes enrichment analysis, protein-protein interaction (PPI) network construction, and prognostic survival analysis based on The Cancer Genome Atlas cohort. Causal candidate targets were further identified through expression quantitative trait locus (eQTL)-MR and protein quantitative trait locus (pQTL)-MR analyses and subjected to a phenome-wide association study (PheWAS). The underlying mechanisms of EGLN1 were explored using single-gene gene set enrichment analysis (GSEA), single-cell RNA sequencing analysis, and a gut microbiota MR-based mediation analysis. Finally, a potential target and its corresponding compound were validated through computational drug screening, molecular docking, and in vitro cellular experiments. RESULTS: The global disease burden of CRC attributable to high BMI increased significantly from 1990 to 2021, with the age-standardized rate in males showing a more rapid increase. MR analysis confirmed that high BMI is a risk factor for CRC [inverse variance weighted (IVW): OR = 1.105, 95% CI = 1.028-1.186, P = 0.006]. We identified 120 KGs-BACC, which were primarily enriched in lipid metabolism, the HIF-1 signaling pathway, and the PPAR signaling pathway. The PPI network revealed core hub genes such as KLF4 and MAPK3 . A four-gene prognostic model derived from the KGs-BACC ( ACADVL, TGFA, SMPD1, BSG ) demonstrated robust risk stratification and survival prediction capabilities. Through eQTL-MR and pQTL-MR, EGLN1 was identified as a core causal protective target in high-BMI-associated CRC (protein level OR = 0.832, 95% CI = 0.753-0.918, P < 0.01); its expression was downregulated in tumors, and PheWAS analysis revealed limited pleiotropy. GSEA indicated that low EGLN1 expression is associated with cell proliferation and metabolic reprogramming. Single-cell analysis showed that EGLN1 is predominantly enriched in T cells and intestinal epithelial cells. Gut microbiota mediation MR analysis found that the abundance of Halarcobacter mediated approximately 34.6% of the protective effect of EGLN1 on CRC. Computational screening and molecular docking identified the natural compound cianidanol as having the strongest binding affinity to EGLN1 (binding energy = -11.24 kcal/mol). In vitro experiments confirmed that cianidanol significantly inhibited the proliferation, migration, and invasion of HCT116 CRC cells and upregulated PHD2 protein expression. CONCLUSION: This study systematically reveals the critical protective role of EGLN1 in high BMI-associated CRC and underscores its value as a potential drug target. EGLN1 influences CRC pathogenesis by modulating multiple dimensions, including the hypoxia response, energy metabolism, the immune microenvironment, and the gut microbiota. The natural compound cianidanol, as a modulator of EGLN1 , demonstrated significant anti-tumor activity in vitro . These findings provide new insights into the molecular mechanisms linking obesity and CRC and establish a theoretical foundation for developing precision therapeutic strategies targeting EGLN1 .
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RB1 Mutations Induce Smoking-Related Bladder Cancer by Modulating the Cytochrome P450 Pathway.
Cigarette smoking causes multiple cancers by directly influencing mutation burden of driver mutations. However, the mechanism between somatic mutation caused by cigarette smoking and bladder tumorigenesis remains elusive. Smoking-related mutation profile of bladder cancer was characterized by The Cancer Genome Atlas cohort. Integraticve OncoGenomics database was utilized to detect the smoking-related driver genes, and its biological mechanism predictions were interpreted based on bulk transcriptome and single-cell transcriptome, as well as cell experiments. Cigarette smoking was associated with an increased tumor mutational burden under 65 years old (p = 0.031), and generated specific mutational signatures in smokers. RB1 was identified as a differentially mutated driver gene between smokers and nonsmokers, and the mutation rate of RB1 increased twofold after smoking (p = 0.008). RB1 mutations and the 4-aminobiphenyl interference could significantly decrease the RB1 expression level and thus promote the proliferation, invasion, and migration ability of bladder cancer cells. Enrichment analysis and real-time quantitative PCR (RT-qPCR) data showed that RB1 mutations inhibited cytochrome P450 pathway by reducing expression levels of UGT1A6 and AKR1C2. In addition, we also observed that the component of immunological cells was regulated by RB1 mutations through the stronger cell-to-cell interactions between epithelial scissor+ cells and immune cells in smokers. This study highlighted that RB1 mutations could drive smoking-related bladder tumorigenesis through inhibiting cytochrome P450 pathway and regulating tumor immune microenvironment.
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Application value of a prognostic risk model based on lactate-related genes in non-small cell lung cancer.
BACKGROUND: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Despite therapeutic advances, the outcomes of patients with advanced disease are still poor. This study was conducted to identify pathogenic and prognostic lactate-related genes (LRGs) in NSCLC to improve clinical treatment and prognosis. METHODS: Consensus clustering was applied to The Cancer Genome Atlas (TCGA) training cohort to delineate subtypes associated with lactate metabolism. On this basis, we established a prognostic signature of LRGs with least absolute shrinkage and selection operator (LASSO) Cox regression and assessed its predictive value in independent Gene Expression Omnibus (GEO) datasets. To clarify the mechanisms related to the model's ability, we examined immune infiltration, estimated responses to immunotherapy, and performed single-cell analysis. In addition, the transcriptional levels of the prognostic genes were validated via real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) in lung cancer cell lines and compared with alveolar epithelial cells (AECs), thereby strengthening the reliability of the model. RESULTS: Two distinct lactate-associated clusters were identified in NSCLC. On this basis, we established an eight-gene prognostic model that stratified patients into high- and low-risk groups with markedly different survival outcomes. The model achieved strong predictive accuracy, with areas under the curve of 0.693, 0.707, and 0.704 for 1-, 3-, and 5-year survival in the training cohort, and its robustness was further confirmed in external validation datasets. In addition, the lactate risk score showed significant associations with the tumor microenvironment (TME) and revealed clear differences in responsiveness to immunotherapy. Single-cell analysis provided further insight into cell type-specific patterns of lactate metabolism. Finally, RT-qPCR validation of most prognostic genes confirmed the reliability of the model. CONCLUSIONS: We developed an LRG prognostic model for NSCLC, which offers novel insights for both diagnostic assessment and treatment strategies.
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A single-cell atlas reveals immune heterogeneity in anti-PD-1-treated non-small cell lung cancer.
Anti-PD-(L)1 treatment is standard for non-small cell lung cancer (NSCLC), but patients show variable responses to the same regimen. The tumor immune microenvironment (TIME) is associated with immunotherapy response, yet the heterogeneous underlying therapeutic outcomes remain underexplored. We applied single-cell RNA and TCR sequencing (scRNA/TCR-seq) to analyze surgical tumor samples from 234 NSCLC patients post-neoadjuvant chemo-immunotherapy. Analyses revealed five distinct TIME subtypes with varying major pathological response (MPR) rates. MPR patients had elevated levels of FGFBP2+ NK/NK-like T cells, memory B cells, or effector T cells, while non-MPR patients showed higher CCR8+ Tregs. T cell clonal expansion analyses unveiled heterogeneity in non-MPR patients, marked by varying expansions of Tex-relevant cells and CCR8+ Tregs. Precursor exhausted T cells (Texp cells) correlated with recurrence-free survival, identifying a patient subgroup with reduced recurrence risk despite lack of MPR. Our study dissects TIME heterogeneity in response to chemoimmunotherapy, offering insights for NSCLC management.
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CHMP4A in hepatocellular carcinoma: exploring its role in tumor progression, immune modulation, and potential link to TIM3 checkpoint.
BACKGROUND: Charged Multivesicular Body Protein 4A (CHMP4A), a member of the ESCRT-III family, plays a pivotal role in membrane remodeling and fission, with emerging evidence underscoring its significance in cancer immunotherapy. The complex pathogenesis and therapeutic resistance characteristic of liver hepatocellular carcinoma (LIHC) present significant challenges in clinical practice. This study investigated the potential involvement of CHMP4A in the progression of LIHC. METHODS AND RESULTS: Utilizing a comprehensive pan-cancer analysis with datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), ArrayExpress database and the International Cancer Genome Consortium (ICGC), we evaluated the prognostic significance of CHMP4A, its clinical implications, associated signaling pathways, DNA methylation status, immune cell infiltration, and response to chemotherapy. Bioinformatics analyses, corroborated by immunohistochemical validation, revealed a marked overexpression of CHMP4A in LIHC specimens relative to adjacent normal tissues. Kaplan-Meier survival analyses indicated that this elevated expression pattern was associated with poor patient outcomes. Single-cell transcriptomic analysis had identified NK/T cells and tumor cells as the predominant cellular sources of CHMP4A within the LIHC microenvironment. Functional studies employing CHMP4A-specific small interfering RNA (siRNA) revealed significant inhibition of malignant phenotypes in LIHC cells, notably affecting proliferation, migration, and invasive capabilities. Mechanistically, the knockdown of CHMP4A led to modulation of the epithelial-mesenchymal transition (EMT), as indicated by the upregulation of E-cadherin and the concurrent downregulation of vimentin and matrix metalloproteinases (MMP-2/9). A comprehensive analysis of the immune landscape demonstrated significant correlations between CHMP4A expression patterns and various immunological parameters, including immune cell infiltration, expression of checkpoint molecules, tumor mutational burden (TMB), and microsatellite instability (MSI). Notably, the silencing of CHMP4A markedly decreased the expression levels of the TIM3/LGALS9 immune checkpoint axis in LIHC. CONCLUSIONS: Our extensive analyses identified CHMP4A as a critical molecular determinant in the progression of LIHC, which may function through two oncogenic mechanisms: the promotion of tumor cell proliferation and metastatic potential, and immunomodulatory effects associated with the TIM3/LGALS9 signaling pathway. These findings indicated that CHMP4A might serve as a potential therapeutic target and prognostic biomarker in LIHC.
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HLA-G functions as a tumor-intrinsic driver of growth and survival in renal cell carcinoma.
HLA-G is a non-classical MHC class I molecule with potent immunoregulatory functions that is aberrantly expressed in multiple malignancies, yet its tumor-intrinsic role remains poorly defined. To characterize this potential oncogenic role of HLA-G in clear cell renal cell carcinoma (ccRCC), we utilized integrated transcriptomic, in vitro, and in vivo approaches. Analysis of the Cancer Genome Atlas (TCGA) ccRCC cohort revealed that elevated HLA-G expression was associated with immunosuppressive programs and cell populations. Interrogation of a publicly available ccRCC single-cell RNA sequencing dataset revealed that HLA-G expression within tumor epithelial clusters is associated with hypoxia-driven, metabolic transcriptional programs. Multiplex immunofluorescence of human ccRCC specimens confirmed the presence of tumor cell-intrinsic HLA-G expression in advanced disease. Functional studies using RCC7 cells expressing the full-length canonical HLA-G isoform (RCC7/HLA-G1) demonstrated increased proliferation, migration, clonogenicity, cell-cycle progression, and resistance to apoptosis compared with HLA-G-negative RCC7wt cells. RCC7/HLA-G1 xenografts exhibited accelerated tumor growth accompanied by the activation of proliferative, stemness-related, and metabolic programs. Multi-omics analyses further revealed enhanced mitochondrial activity and redox metabolic adaptation in HLA-G-expressing tumors. Mechanistically, HLA-G expression was associated with increased VEGF-C expression and enhanced VEGFR3 signaling, suggesting the activation of a VEGF-C/VEGFR3-associated pro-survival pathway. In three-dimensional tumor spheroid immune cell co-culture models, HLA-G expression reduced CD8⁺ T-cell-mediated cytotoxicity while promoting regulatory T-cell expansion and macrophage polarization toward an immunosuppressive M2-like phenotype. Collectively, these findings establish HLA-G as a key contributor to tumor progression and immune suppression in ccRCC and support HLA-G as a promising therapeutic target.