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Single-Cell Immune Atlases to Map Small Extracellular Vesicle Cargo in Tuberculosis-Diabetes Comorbidity: A Narrative Review and Conceptual Roadmap.
Tuberculosis-diabetes mellitus (TB-DM) is increasingly recognized as a syndemic in which chronic metabolic dysregulation amplifies tuberculosis severity, delays treatment response, and increases relapse and mortality. However, conventional systemic correlates soluble cytokines and bulk whole-blood transcriptomic signatures often appear broadly similar between TB and TB-DM. This highlights a key gap: clinically meaningful immune dysfunction in TB-DM likely resides in specific lung and blood cell states that are poorly resolved by bulk assays. Small extracellular vesicles (EVs) in plasma and bronchoalveolar lavage (BAL) provide a tractable "liquid biopsy" layer because their RNA and protein cargo can integrate information from infected macrophages, neutrophils, and epithelial/endothelial compartments, and may also include pathogen-derived components. Yet most EV studies remain bulk and cell-agnostic, and interpretation is constrained by heterogeneous vesicle mixtures, selective cargo packaging, and co-isolated non-vesicular contaminants, issues that are especially problematic for nucleic-acid claims without rigorous controls. In this targeted narrative review (2010-2026), we argue that single-cell and multimodal immune reference atlases, including scRNA-seq/CITE-seq, provide a needed scaffold to link EV cargo patterns to specific immune cell states, pathways, and anatomic compartments in TB-DM, enabling prioritized candidates and testable hypotheses. We outline three complementary frameworks: reference-atlas anchoring to project EV cargo modules onto atlas-defined immune states; orthogonal triangulation combining computational inference with immunoaffinity enrichment, targeted validation, and functional assays; and cautious use of "droplet-era" extracellular signals as hypothesis-generating priors for EV-producing states. Implemented in longitudinal, clinically annotated cohorts with standardized EV workflows, atlas-guided EV profiling could yield cell-of-origin-resolved biomarkers of TB-DM immunopathology and treatment response, while prioritizing mechanistically plausible targets for host-directed intervention.
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SOD2 expression in patients with triple-negative breast cancer is associated with tumor-infiltrating lymphocytes and prognosis.
PURPOSE: Superoxide dismutase 2 (SOD2), an antioxidant enzyme, plays a pivotal role in carcinogenesis and immune regulation. In this study, we investigated the expression and implications of superoxide dismutase (SOD2) in triple-negative breast cancer (TNBC), an aggressive subtype with varying immune profiles and clinical outcomes. METHODS: Multiple TNBC cohorts were analyzed with various methodologies including immunohistochemistry (IHC), proteomics, and RNA expressions. Immunostaining of SOD2 with tissue microarrays from 229 surgical samples and 144 pre-neoadjuvant chemotherapy biopsy samples were performed. Four hundred three formalin-fixed and paraffin-embedded samples underwent deparaffinization for protein extraction and three hundred thirty-six samples remained after quality control. Ninety-one TNBC samples from The Cancer Genome Atlas data and five hundred thirty-four TNBC samples from public database were also analyzed. RESULTS: We identified positive correlations between SOD2 expression and immune-related genes, as well as tumor-infiltrating lymphocytes (TILs) levels, while observing negative associations with fibrosis-related pathways. Immunohistochemical analysis further supported the positive correlation between SOD2 and immune response. Furthermore, elevated SOD2 expression predicted favorable survival outcomes in patients with TNBC. Notably, analysis of single-cell RNA-seq data revealed increased SOD2 expression in cancer-associated fibroblasts associated with higher TILs levels, enhanced inflammatory signaling, and reduced fibrogenesis. CONCLUSION: High SOD2 expression in TNBC is associated with improved outcomes and heightened immune responses, underscoring its potential as a modulator of the tumor microenvironment.
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Targeting RECQL4 in hepatocellular carcinoma: from prognosis to therapeutic potential.
OBJECTIVE: The aim of this study is to assess the clinical utility of RecQ Like Helicase 4 (RECQL4) as a prognostic marker in hepatocellular carcinoma (HCC) and investigate its associations with various biological processes, angiogenesis-related factors, immune cell infiltration, immune checkpoints, and drug sensitivity. METHODS: RECQL4 expression was analyzed across a range of cancer types utilizing data from the TCGA database. Disparities in RECQL4 expression levels between normal and malignant tissues were evaluated, alongside an analysis of progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) curves. Exploration of pertinent pathways, immune cell infiltration, single-cell RNA-seq data, and drug sensitivity was conducted employing The Cancer Genome Atlas (TCGA) and Tumor Immune Single-Cell Hub (TISCH) databases. Furthermore, validation of in-silico results was validated through qPCR, Western blotting, CCK-8 assay, EdU assay, clonogenic assay, wound-healing assay, and transwell assay. RESULTS: In HCC, RECQL4 was highly expressed and associated with poorer prognosis (p < 0.05). It positively correlated with pathways related to MYC targets, DNA replication, PI3K/AKT/mTOR signaling, DNA repair mechanisms, and the G2/M checkpoint (R > 0.24, p < 0.001). RECQL4 also showed significant correlations with angiogenesis-related genes, including PTK2 (R > 0.4, p < 0.05), suggesting a potential role in angiogenesis regulation. Immune analysis indicated that RECQL4 was associated with immune cell types such as T helper 2 cells, NK CD56bright cells, and follicular helper T cells, suggesting a positive relationship with their infiltration. High RECQL4 expression was also linked to increased sensitivity to drugs including Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Cellular experiments showed that RECQL4 expression at the mRNA and protein levels were significantly higher in HCC cell lines Hep3B and Huh7 compared to the normal liver cell line MHA. Moreover, RECQL4 knockdown resulted in reduced proliferation and migration in HCC cell lines (p < 0.05). CONCLUSIONS: RECQL4 shows promise as a biomarker for predicting recurrence and survival in HCC and may affect angiogenesis regulation. Its expression also appears to impact sensitivity to drugs such as Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Furthermore, silencing RECQL4 significantly inhibits HCC cell line proliferation and migration.
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Evolutionary and developmental specialization of foveal cell types in the marmoset.
In primates, high-acuity vision is mediated by the fovea, a small specialized central region of the retina. The fovea, unique to the anthropoid lineage among mammals, undergoes notable neuronal morphological changes during postnatal maturation. However, the extent of cellular similarity across anthropoid foveas and the molecular underpinnings of foveal maturation remain unclear. Here, we used high-throughput single-cell RNA sequencing to profile retinal cells of the common marmoset (Callithrix jacchus), an early divergent in anthropoid evolution from humans, apes, and macaques. We generated atlases of the marmoset fovea and peripheral retina for both neonates and adults. Our comparative analysis revealed that marmosets share almost all their foveal types with both humans and macaques, highlighting a conserved cellular structure among primate foveas. Furthermore, by tracing the developmental trajectory of cell types in the foveal and peripheral retina, we found distinct maturation paths for each. In-depth analysis of gene expression differences demonstrated that cone photoreceptors and Müller glia (MG), among others, show the greatest molecular divergence between these two regions. Utilizing single-cell ATAC-seq and gene-regulatory network inference, we uncovered distinct transcriptional regulations differentiating foveal cones from their peripheral counterparts. Further analysis of predicted ligand-receptor interactions suggested a potential role for MG in supporting the maturation of foveal cones. Together, these results provide valuable insights into foveal development, structure, and evolution.
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A 3D system to model human pancreas development and its reference single-cell transcriptome atlas identify signaling pathways required for progenitor expansion.
Human organogenesis remains relatively unexplored for ethical and practical reasons. Here, we report the establishment of a single-cell transcriptome atlas of the human fetal pancreas between 7 and 10 post-conceptional weeks of development. To interrogate cell-cell interactions, we describe InterCom, an R-Package we developed for identifying receptor-ligand pairs and their downstream effects. We further report the establishment of a human pancreas culture system starting from fetal tissue or human pluripotent stem cells, enabling the long-term maintenance of pancreas progenitors in a minimal, defined medium in three-dimensions. Benchmarking the cells produced in 2-dimensions and those expanded in 3-dimensions to fetal tissue identifies that progenitors expanded in 3-dimensions are transcriptionally closer to the fetal pancreas. We further demonstrate the potential of this system as a screening platform and identify the importance of the EGF and FGF pathways controlling human pancreas progenitor expansion.
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Exploring the role of PANoptosis related genes in the prognosis of oral squamous cell carcinoma subtypes based on multi-omics analysis.
BACKGROUND: Oral squamous cell carcinoma (OSCC) has a poor prognosis. PANoptosis, involving apoptosis, pyroptosis, and necroptosis, may be linked to cancer. Identifying OSCC subtypes and creating prognostic models based on PANoptosis-related genes (PRGs) can improve diagnosis and treatment. METHODS: RNA-seq and DNA methylation data from OSCC patients in The Cancer Genome Atlas (TCGA) were analyzed. Clustering algorithms identified OSCC subtypes, which were examined for differences in spatial distribution, biological pathways, drug sensitivity, prognosis, and immune infiltration. Prognostic genes were identified using Cox regression analyses. Mendelian randomization identified genes linked to OSCC. Drug sensitivity and tumor mutation load were assessed. Single-cell RNA sequencing (scRNA-seq) data explored the expression of prognostic genes. qRT-PCR verified gene expression. RESULTS: OSCC subtypes based on PRGs showed differences in prognosis, immunity, drug sensitivity, and pathways. Pantothenate and CoA biosynthesis pathways varied among subtypes, with immune cells highly infiltrated in CS1. The prognostic model highlighted differences in prognosis and immunotherapy response. BAK1 was causally linked to OSCC risk. Combining TMB score improved patient stratification. qRT-PCR confirmed differences in gene expression between control and OSCC groups. Monocytes were identified as high-scoring cells, with TGFb and MIF pathways important in cell communication. CONCLUSION: Two OSCC subtypes and eight prognostic genes (TGFBR3, CYCS, HDAC9, PLK1, GSDMB, HSPA4, BAK1, SOD2) were identified, aiding in treatment and risk stratification. BAK1 is causally linked to OSCC risk.
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USP20 as a key regulator of immunosuppression and a novel predictor of poor prognosis in lung adenocarcinoma.
BACKGROUND: To systematically delineate the expression landscape, genetic alterations, prognostic value, and immunological relevance of ubiquitin-specific protease 20 (USP20) in lung adenocarcinoma (LUAD). By integrating bulk and single-cell transcriptomic analyses, we aimed to identify the cellular sources of USP20 and clarify its potential roles in remodeling the tumor immune microenvironment (TME), thereby evaluating its utility as a prognostic biomarker and candidate immunotherapeutic target. METHODS: USP20 expression was profiled across The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and multiple Gene Expression Omnibus (GEO) cohorts. Prognostic significance was assessed using Kaplan-Meier analysis and Cox proportional hazards models. USP20 genetic alterations were interrogated via cBioPortal. Differentially expressed genes (DEGs) associated with USP20 were identified, followed by GO/KEGG enrichment and GSEA to infer biological functions. TME characteristics were evaluated using ESTIMATE and CIBERSORT, and associations with immune checkpoint molecules were examined. Consensus clustering was performed to define USP20-related molecular subtypes and compare their immune landscapes. Single-cell RNA-seq datasets (TISCH and GSE146100) were integrated to resolve USP20 expression across tumor and immune compartments. Finally, immunohistochemistry, multiplex immunofluorescence, flow cytometry, and in vitro/in vivo functional assays were conducted to validate the biological and immunoregulatory roles of USP20 in LUAD. RESULTS: USP20 was consistently upregulated in LUAD relative to normal lung tissues across independent cohorts. High USP20 expression was associated with inferior overall survival and remained an independent prognostic risk factor. Genetic profiling showed a low mutation rate of USP20, with copy number amplification as the predominant alteration. Functional analyses indicated that USP20-associated DEGs were enriched in immune-related programs, including T-cell activation, antigen processing and presentation, interferon signaling, and immune checkpoint regulation. High USP20 expression correlated with a distinct immune contexture, featuring reshaped immune cell composition, increased infiltration of immunosuppressive populations, and elevated expression of multiple immune checkpoint molecules. Consensus clustering further revealed USP20-related molecular subtypes with divergent immunosuppressive features and clinical outcomes. Single-cell analyses demonstrated heterogeneous and cell-type-specific USP20 expression across malignant and immune populations, supporting a context-dependent immunomodulatory role. Experimental validation confirmed that USP20 promotes LUAD cell proliferation and migration and is associated with immune dysregulation within the TME. CONCLUSIONS: USP20 is aberrantly overexpressed in LUAD and portends poor prognosis. USP20 may facilitate disease progression by shaping tumor-immune interactions, including immune infiltration patterns, T-cell activation/exhaustion states, and immune checkpoint signaling. USP20 and its related molecular subtypes may serve as prognostic biomarkers and potential indicators of immunotherapeutic responsiveness, offering insights for precision immunotherapy in LUAD.
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Evaluating genetic-ancestry inference from single-cell RNA-seq data.
Characterizing the ancestry of donors in single-cell RNA sequencing (scRNA-seq) studies is critical to ensure the genetic homogeneity of the dataset and reduce biases in analyses, to identify ancestry-specific regulatory mechanisms and understand their downstream role in diseases, and to ensure that existing datasets are representative of human genetic diversity. While scRNA-seq is now widely available, the information on the ancestry of the donors is often missing, hindering further analysis. Here we propose a framework to evaluate methods for inferring genetic-ancestry from genetic polymorphisms detected from scRNA-seq reads. We demonstrate that widely used tools (e.g., ADMIXTURE) provide accurate inference of genetic-ancestry and admixture proportions despite the limited number of genetic polymorphisms identified and imperfect variant calling from scRNA-seq reads. We inferred genetic-ancestry for 196 donors from four scRNA-seq datasets from the Human Cell Atlas and highlighted an extremely large proportion of donors of European ancestry. For researchers generating single-cell datasets, we recommend reporting genetic-ancestry inference for all donors and generating datasets that represent diverse ancestries.
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Development and validation of a gemcitabine sensitivity-related long noncoding RNA signature for predicting the prognosis and subtypes of bladder cancer.
BACKGROUND: Bladder cancer (BLCA) is a common urogenital malignancy with significant heterogeneity, and gemcitabine serves as a key chemotherapeutic agent for BLCA. This study examined gemcitabine sensitivity-related long noncoding RNA (GSRlncRNA) in BLCA and constructed a prognostic signature. METHODS: Gene expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gemcitabine sensitivity of BLCA samples was quantitatively calculated. Using weighted gene coexpression network analysis (WGCNA), we analyzed the role of GSRlncRNA in BLCA. We developed a prognostic signature using machine learning algorithm integration, with the TCGA-BLCA cohort (n=405) serving as the training set and GSE31684 (n=93) serving as the validation cohort. Patients were stratified into low- and high-risk groups based on risk scores. Comparative analyses included prognosis, immune infiltration, mutational profiles, and pathway enrichment. Single-cell RNA sequencing (scRNA-seq) and in vitro experiments further validated the expression and functional roles of GSRlncRNA in BLCA. RESULTS: GSRlncRNAs were identified via WGCNA. The partial least squares regression for Cox (plsRcox) was selected as the optimal modeling approach. A prognostic signature comprising 37 GSRlncRNAs effectively stratified patients into distinct risk groups, which demonstrated significant differences in survival outcomes, pathway enrichment, immune infiltration, and mutational profiles. To enhance clinical utility, a nomogram and web-based calculator were developed. scRNA-seq clarified the critical roles of LINC00930 and EMX2OS in BLCA progression. Real-time quantitative polymerase chain reaction confirmed the differential expression of GSRlncRNA in BLCA compared to that in normal tissues. Functional assays demonstrated that LINC00930 and EMX2OS suppression impaired BLCA cell proliferation, migration, invasion, apoptosis, cell cycle, and gemcitabine sensitivity. CONCLUSIONS: We identified critical prognostic associations between GSRlncRNAs and BLCA. Based on these findings, we constructed a GSRlncRNA-based predictive signature, which demonstrated considerable potential for risk stratification and personalized treatment decisions. Functional experiments further validated the involvement of GSRlncRNAs in BLCA progression.
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SOX9 protein in goblet cells as a critical mediator and potential therapeutic target in Barrett's esophagus: An integrated bioinformatics analysis.
BACKGROUND: Barrett's esophagus (BE) is the only recognized precursor to esophageal adenocarcinoma, yet current diagnostic and therapeutic strategies remain limited by sampling bias and lack of reliable molecular markers. METHODS: We conducted a multi-omics analysis using four bulk RNA-seq datasets for differential expression and WGCNA. Hub genes were identified through PPI networks and LASSO regression, validated in external cohorts. scRNA-seq profiled gene expression in epithelial and stromal subtypes, with immune profiling via CIBERSORT. SOX9 expression in single-cell resolution was validated in two BE patient cohorts. RESULTS: Five upregulated genes-SOX9, COL1A2, SPARC, EPCAM, and KRT18-were identified as robust diagnostic markers, with AUC values >0.90. scRNA-seq showed increased SOX9 expression in goblet cells in BE, which was validated by IHC. SOX9 expression in goblet cells correlated with progression to high-grade dysplasia (HGD), while expression in non-goblet cells had a lower correlation. BE tissues showed distinct immune profiles, with enriched plasma cells and CD4+ memory T cells. Molecular docking identified potential druggable interactions with these proteins. CONCLUSION: Our integrative analysis provides a comprehensive molecular and cellular atlas of BE. These findings enhance current understanding of BE pathogenesis and offer clinically relevant candidates for early detection and targeted intervention.