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PubMed2026

Lymphangiogenesis-related gene signature-based risk model for prognostic assessment of cervical cancer: immune-metabolic characterization and molecular subtype analysis.

BACKGROUND: Lymphangiogenesis promotes tumor dissemination and may shape the immune contexture of cervical cancer, yet lymphangiogenesis-related prognostic stratification and its immunometabolic implications remain insufficiently defined in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). METHODS: TCGA-CESC transcriptomes and clinical data were obtained from UCSC Xena and integrated with normal cervix tissues from the Genotype-Tissue Expression Project after batch correction. Prognostic LYMRGs were first identified from the differentially expressed set using univariable Cox proportional hazards analysis. Candidate genes were then reduced using an L1-regularized Cox model (Least Absolute Shrinkage and Selection Operator), and the remaining markers were entered into a multivariable Cox regression to obtain the final coefficients and compute an individualized risk score. The model's prognostic value was further assessed in an independent Gene Expression Omnibus dataset. In addition, expression patterns of the signature genes were leveraged for molecular subtyping of TCGA samples via non-negative matrix factorization (NMF). Immune infiltration and immunotherapy-associated characteristics were interrogated through a multi-algorithm strategy (single-sample gene set enrichment analysis, CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore . Additional analyses included pathway enrichment (GSEA/GO/KEGG), drug sensitivity prediction (pRRophetic/CellMiner), and ceRNA network analysis. RESULTS: A six-gene LYMRG signature robustly stratified survival. High-risk patients had significantly worse overall survival in The Cancer Genome Atlas with AUCs of 0.819/0.801/0.801 at 1/3/5 years, and in GSE52903 (P = 0.001) with AUCs of 0.733/0.719/0.725. NMF identified two subtypes with distinct prognosis (P = 0.01) and divergent immune landscapes. Risk groups and subtypes exhibited consistent differences in immune infiltration, checkpoint expression, TIDE/IPS patterns, and pathway enrichment. Predicted chemosensitivity differed by risk group, and the ceRNA network suggested candidate upstream lncRNA regulators of the signature. CONCLUSION: A lymphangiogenesis-related six-gene model enables clinically meaningful prognostic stratification of CESC and links lymphangiogenesis programs to distinct tumor immune phenotypes and therapeutic vulnerabilities.

cancer↗

PubMed2026

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer.

Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential for guiding the use of postoperative adjuvant chemotherapy (ACT). In this study, we identified novel prognostic gene expression biomarkers in patients with pStage II CRC and developed a new risk stratification framework for ACT decision-making. First, genome-wide biomarker discovery was conducted to identify prognostic gene expression biomarkers associated with recurrence risk in pStage II CRC. This analysis identified 10 differentially expressed genes as potential biomarkers for recurrence. The efficacy of these biomarkers was then tested using 188 clinical surgical specimens obtained from patients with pStage II CRC. A predictive panel was developed using qRT-PCR and used to assess 93 clinical specimens with an area under the curve (AUC) of 0.82, and its performance was further validated in an independent cohort (n = 95). By incorporating key clinicopathological features, a Gene expression-based Prediction of Recurrence in pStage II CRC (GPRSC) signature was developed, which robustly predicted postoperative recurrence (AUC: 0.80). Finally, combining the GPRSC signature, microsatellite instability status, and conventional criteria, we developed a novel risk stratification system for postoperative ACT decision-making in pStage II CRC. Overall, we identified novel gene expression biomarkers and developed a prognostic signature that informs clinical decision-making regarding postoperative ACT in patients with pStage II CRC.

Humans↗

PubMed2026

Coordinated inflammatory macrophage and vascular smooth muscle cell remodeling signatures in human atherosclerosis: An integrative single-cell and bulk transcriptomic analysis.

Atherosclerotic plaque progression is shaped by coordinated inflammatory and remodeling programs involving immune cells and vascular wall cells. Inflammatory macrophage activation and vascular smooth muscle cell (VSMC) phenotypic remodeling are central features of human atherosclerosis, but their transcriptomic relationships during plaque progression remain incompletely characterized. This study integrated single-cell and bulk transcriptomic datasets to examine highly inflammatory macrophage states, VSMC remodeling-related transcriptional programs, and candidate ligand-receptor expression patterns in human atherosclerotic plaques. Human atherosclerotic plaque single-cell RNA sequencing data from GSE260657 and bulk transcriptomic data from GSE28829 were analyzed. After quality control, 7628 cells were retained for single-cell analysis. Major cell types were annotated using canonical markers, followed by reclustering of macrophages and VSMC-related cells. Functional module scoring, differential expression analysis, Gene Ontology biological process enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to characterize macrophage transcriptional states. Slingshot was applied to infer VSMC pseudotime ordering. CellChat and NicheNet were used to prioritize candidate ligand-receptor expression patterns and ligand-associated VSMC target gene programs. External bulk transcriptomic analysis was performed to examine whether single-cell-derived inflammatory and remodeling signatures were represented at the tissue-transcriptome level during plaque progression. Macrophage reclustering identified a highly inflammatory macrophage state characterized by prominent inflammatory activation, cytokine-response, and stress-response features. Genes upregulated in this population were enriched in pathways related to tumor necrosis factor (TNF) response, nuclear factor kappa B signaling, leukocyte activation, cytokine signaling, lipid and atherosclerosis, toll-like receptor signaling, and inflammasome-associated inflammation. VSMC reclustering revealed contractile VSMCs, PTHLH+ synthetic VSMCs, KRT7+ VSMC-like cells, interferon-responsive VSMCs, pericyte-like mural cells, and osteogenic/modulated VSMCs. Pseudotime analysis showed a broad contractile-to-osteogenic/modulated transcriptional continuum accompanied by increased expression of remodeling-associated genes and selected inflammatory or remodeling-associated receptor genes. CellChat and NicheNet analyses prioritized candidate ligand-receptor and ligand-associated target gene expression patterns involving SPP1-CD44, TNF-TNFRSF1A, IL1B-IL1R1/IL1RAP, MIF-ACKR3, PDGFB-PDGFRB, and FN1-SDC1/ITGB1. In GSE28829, inflammatory macrophage-, osteogenic/modulated VSMC-, candidate ligand-receptor expression-, SPP1-CD44 candidate axis-, and NicheNet-prioritized target program-related signatures were more prominent in advanced plaques and were positively correlated with each other. This integrative transcriptomic analysis identified a highly inflammatory macrophage state and a VSMC remodeling continuum in human atherosclerotic plaques. Candidate ligand-receptor and ligand-associated target gene expression patterns linked inflammatory macrophage activation with osteogenic/modulated VSMC remodeling at the computational level. External bulk data further showed coordinated enrichment of inflammatory and remodeling signatures in advanced plaques. These findings provide a descriptive and hypothesis-generating transcriptomic framework for understanding inflammatory macrophage activation and VSMC remodeling in human atherosclerosis.

atherosclerosis↗

PubMed2026

Age-Associated Four-Gene Prognostic Signature in Breast Cancer.

BACKGROUND: Young-onset breast cancer is associated with inferior disease-free survival (DFS), but the contribution of additional molecular heterogeneity remains unclear. AIMS: To identify an exploratory age-associated gene expression signature linked to recurrence-related outcomes and evaluate its prognostic association. METHODS AND RESULTS: We analyzed clinicopathological and RNA-sequencing data from 821 patients with Stages I-III invasive ductal or lobular carcinoma in The Cancer Genome Atlas, including 142 patients aged ≤ 45 years. Genes associated with both age and DFS were screened, followed by LASSO-Cox and stepwise multivariable Cox regression. A four-gene signature (Sig4: C4orf14 [NOA1], LINC01124, ZNF704, and AGFG2) was identified. Young patients had significantly worse DFS than older patients, whereas overall and disease-specific survival did not differ significantly. After adjustment for clinicopathological factors, young age remained associated with worse DFS. Following inclusion of the continuous Sig4 score, the age association was attenuated and no longer statistically significant, while Sig4 remained independently associated with worse DFS. Sig4-high tumors were enriched for proliferation, cell-cycle, DNA-repair, metabolic, and stress-response pathways. In METABRIC, the fixed TCGA-derived Sig4 score was associated with worse relapse-free survival in the overall cohort but not in patients aged ≤ 45 years. CONCLUSION: Sig4 is an exploratory age-associated four-gene signature with potential general prognostic relevance in breast cancer. Its utility for risk stratification specifically in young-onset breast cancer was not externally validated and requires confirmation in independent prospective cohorts enriched for young patients.

Humans↗

PubMed2025

Metagenome-Based Characterization of the Gut Virome Signatures in Patients With Gout.

The gut microbiome has been implicated in the development of autoimmune diseases, including gout. However, the role of the gut virome in gout pathogenesis remains underexplored. We employed a reference-dependent virome approach to analyze fecal metagenomic data from 102 gout patients (77 in the discovery cohort and 25 in the validation cohort) and 86 healthy controls (HCs) (63 and 23 in each cohort). A subset of gout patients in the discovery cohort provided longitudinal samples at Weeks 2, 4, and 24. Our analysis revealed significant alterations in the gut virome of gout patients, including reduced viral richness and shifts in viral family composition. Notably, Siphoviridae, Myoviridae, and Podoviridae were depleted, while Quimbyviridae, Retroviridae, and Schitoviridae were enriched in gout patients. We identified 359 viral operational taxonomic units (vOTUs) associated with gout. Enriched vOTUs in gout patients predominantly consisted of Fusobacteriaceae, Bacteroidaceae, and Selenomonadaceae phages, while control-enriched vOTUs included Ruminococcaceae, Oscillospiraceae, and Enterobacteriaceae phages. Longitudinal analysis revealed that a substantial proportion of these virome signatures remained stable over 6 months. Functional profiling highlighted the enrichment of viral auxiliary metabolic genes, suggesting potential metabolic interactions between viruses and host bacteria. Notably, gut virome signatures effectively discriminated gout patients from HCs, with high classification performance in the validation cohort. This study provides the first comprehensive characterization of the gut virome in gout, revealing its potential role in disease pathogenesis and highlighting virome-based signatures as promising biomarkers for gout diagnosis and future therapeutic strategies.

Humans↗

PubMed2025

High-fat and low-fat fermented milk and cheese intake, proteomic signatures, and risk of all-cause and cause-specific mortality.

PURPOSE: This study aimed to examine the associations between the intake of high- and low-fat fermented dairy (cheese and fermented milk), their proteomic profiles, and mortality risk. METHODS: This cohort study included 25,187 participants (mean age 57.7 years, 60.9% females). Fermented dairy intake was assessed by a modified diet history method. In a random subset of this cohort (n = 4359), we constructed proteomic signatures for fermented dairy intake using 136 candidate plasma proteins. RESULTS: During 23.5 years of follow-up, 9742 participants died. High-fat cheese (> 20% fat) intake was inversely associated with risk of all-cause mortality (HR for an increment of 20 g/day, 0.97; 95% CI, 0.96-0.99, P < 0.001) and cardiovascular disease mortality (HR, 0.96; 95% CI, 0.93-0.99, P = 0.006). Low-fat cheese intake showed an inverse association with all-cause mortality (HR, 0.98; 95% CI, 0.96-1.00, P = 0.047). Low-fat fermented milk intake was inversely associated with all-cause mortality (HR for an increment of 250 g/day, 0.91; 95% CI, 0.85-0.97, P = 0.006), while high-fat fermented milk (> 2.5% fat) showed null association. A total of 42, 26, 0, and 39 proteins were identified for the signature of high-fat cheese, low-fat cheese, high-fat fermented milk, and low-fat fermented milk, respectively. Inverse associations with all-cause mortality were observed for all three signatures with identified proteins. The identified proteins were involved in biological pathways related to immune response and inflammation. CONCLUSION: Our study indicated that consuming high-fat cheese, low-fat cheese, and low-fat fermented milk was linked to survival benefits. Plasma proteins improve our understanding of the health effects of fermented dairy.

Humans↗

PubMed2026

Integrated bulk and single-cell RNA sequencing reveals a prognostic neuro-mimicry signature in papillary thyroid carcinoma.

BACKGROUND: Cancer cells can acquire neuron-like characteristics ("neural mimicry") to promote progression. However, the role of specific ion channel genes in Papillary Thyroid Carcinoma (PTC) and their clinical significance remains unclear. METHODS: We included transcriptomic data from 521 PTC patients in the TCGA cohort. A neuron-specific gene set was used to screen for potential targets. We constructed a prognostic model using LASSO logistic regression. To verify the cellular origin of the signature, we performed single-cell RNA sequencing (scRNA-seq) analysis on the GSE184362 dataset. RESULTS: We established an 8-gene signature involving KCNN4, KCNN1, KCNT2, SNAP25, KCNK16, GABRG1, GABRG2, and GABRB2. The model demonstrated good predictive performance for lymph node metastasis, with an AUC of 0.721 (95% CI 0.677-0.765). Single-cell analysis of seven integrated tumor samples (N = 65,744 cells) confirmed that GABRB2 was specifically enriched in malignant thyrocytes (EPCAM+/KRT18+) at 200-fold higher detection rates than immune cells (20.0% vs. 0.1%, P ≈ 0), supporting tumor-intrinsic neural mimicry. High-risk patients showed immunosuppressive features with altered immune cell infiltration patterns. CONCLUSION: This study identifies a malignant cell-intrinsic signature for predicting PTC prognosis. Validated by single-cell data, our findings suggest that targeting ion channels may represent a potential therapeutic strategy for modulating neuro-immune interactions in thyroid cancer, pending experimental validation.

GABRB2↗

PubMed2026

Early oligodendrocyte dysfunction signature in Alzheimer's disease: Insights from DNA methylomics and transcriptomics.

Much research into the aetiology of Alzheimer's disease (AD) has focused on neuronal cell types, while studies on the contribution of glial cells, particularly oligodendrocytes (OLGs), are only starting to emerge. Altered brain DNA methylation, an epigenetic modification that provides the interplay between genetics and environmental cues to tightly regulate gene expression, is well documented in AD. Yet, cell-type-specific investigations remain limited. Here, we examine the role of DNA methylation and OLGs in AD, and how such changes may impact gene expression. We performed weighted-gene correlation network analysis (WGCNA) on multiple brain omics AD datasets across species: human DNA methylation data from 4 brain regions, human brain single-nuclei RNA sequencing data and mouse brain RNA sequencing data. We compared AD-associated network modules enriched for OLG genes across AD brain regions, as well as with other neurodegenerative disease DNA methylation datasets. We identified a DNA methylation signature associated with AD, enriched for OLGs, and preserved across brain regions representing early and late AD pathology stages. Genes within this signature showed altered expression in AD OLGs, confirming cell-type specificity and relevance to AD. This OLG signature was also preserved in transgenic mice with early Aβ pathology and in other neurodegenerative diseases without Aβ pathology. We reveal a consistent pattern of OLG dysfunction spanning early to late stages of AD, across DNA methylation and gene expression. Our findings highlight OLG-associated DNA methylation changes as important in AD pathogenesis, and possibly in other neurodegenerative diseases, opening new avenues for therapeutic development.

Alzheimer Disease↗

PubMed2026

Cell-type signatures of Alzheimer's disease shared across population groups.

Genomic studies at single-cell resolution have identified several cell types associated with clinical and pathological traits in Alzheimer's disease1-9, but have not examined associations that are shared across populations. To bridge this gap, here we use single-nucleus RNA sequencing and assay for transposase-accessible chromatin with sequencing to profile cortical and subcortical regions in post-mortem brain-tissue samples from Latin, white (excluding Latin) and African American (excluding Latin) individuals. Using discrete and continuous dissections of molecular programs, we identify cell-type-specific clusters associated with Alzheimer's disease in a region-specific manner across all three population groups, including microglial (GPNMB+ and CD74+ subgroups), astrocytic (SERPINH1+, CD44+ and WIF1+ subgroups) and neuronal (SST+ GABAergic and superficial-layer glutamatergic) signatures. We also report continuous gene-expression factors in astrocytes and oligodendrocytes that are not captured by discrete cluster assignments, but which show strong associations with disease phenotypes; these factors are enriched for genes associated with annotated functions such as lipid processing and neurotransmitter reuptake. Finally, we find that molecular programs reveal six distinct subgroups of individuals with cognitive impairment that span all three populations, are not captured by neuropathology, and are instead distinguished by molecular signatures that are not universally present but are nonetheless associated with ante-mortem impairment. Overall, our study identifies key cell types and gene programs implicated in Alzheimer's disease that are shared across population groups, and underscores how representative sampling can capture both shared signatures and disease heterogeneity, thereby enabling better prioritization of key cell types for further investigation.

Female↗

PubMed2026

Human Immunodeficiency Virus-Associated Proteomic Signature of Myocardial Fibrosis and Incident Heart Failure.

BACKGROUND: People with human immunodeficiency virus (HIV) (PWH) are at higher risk of myocardial fibrosis and subsequent heart failure (HF) compared to people without HIV (PWOH). Mechanisms underlying this risk and its specificity to PWH are unclear. METHODS: We measured 2594 proteins in plasma obtained concurrently with cardiovascular magnetic resonance imaging among 342 PWH and PWOH. We estimated associations with HIV serostatus and myocardial fibrosis (elevated extracellular volume fraction [ECV] ≥30% among women, ≥28% among men) using multivariable regression. Among an independent community-based cohort, we estimated associations between the identified signature and time to incident HF. RESULTS: Mean age of participants was 55 (standard deviation [SD], 6) years, 25% were female, 61% were PWH (88% on antiretroviral therapy, 74% with undetectable HIV RNA), and 52% had elevated ECV. We identified 39 proteins and 1 cluster of 42 proteins that were higher among PWH versus PWOH and positively associated with elevated ECV, independent of risk factors (false discovery rate <0.05). Among an independent cohort of 3223 PWOH (mean age, 68 [SD, 9] years; 52% female; 118 incident HF cases over a mean of 9.8 [SD, 1.4] years), we found that this protein cluster and 34 of 39 individual proteins were associated with time to incident HF. This signature was statistically enriched for T-cell activation, tumor necrosis factor signaling, ephrin signaling, and tissue maintenance and repair. CONCLUSIONS: We identified an HIV-related proteomic signature associated with myocardial fibrosis regardless of HIV serostatus and that predicted incident HF among the general population. Our results identify several novel associations related to specific immune processes that may contribute to risk of myocardial fibrosis and subsequent HF among both PWH and PWOH.

Humans↗

PubMed2026

Proteomic Immune Signatures of Severe HIV-Associated Tuberculosis in Sub-Saharan Africa: A Prospective, Multicenter Analysis From Uganda.

OBJECTIVES: Severe tuberculosis (TB) is a major cause of critical illness and death in people living with HIV (PLWH) worldwide. Despite this, the immunopathology of severe HIV-associated TB (HIV/TB) is poorly understood. We aimed to identify an immunopathologic signature of severe HIV/TB in sub-Saharan Africa. DESIGN AND SETTING: We analyzed proteomic data from two prospective observational cohorts of adults hospitalized with severe undifferentiated infection in Uganda: an urban discovery cohort (Entebbe, n = 241) and a rural validation cohort (Tororo, n = 253). PATIENTS: Adults (age ≥ 18 yr) hospitalized with severe febrile illness. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Across both cohorts, severe HIV/TB was common, affecting 18% of participants in the discovery cohort and 21% in the validation cohort. Overall mortality was significant (30-d mortality of 22% in the discovery cohort and 60-d mortality of 26% in the validation cohort). Participants were stratified into three HIV/TB phenotypes: HIV-negative without TB, PLWH without TB, and PLWH with microbiologically diagnosed TB. We applied ordinal random forest models in the discovery cohort as a supervised feature-selection approach to identify proteins associated with progressive HIV/TB phenotype. In both cohorts, PLWH with microbiologically diagnosed TB were at highest risk of critical illness and death (30-d mortality of 42% in the discovery cohort and 60-d mortality of 52% in the validation cohort). An eight-protein signature reliably distinguished this phenotype, reflecting mediators of macrophage/dendritic cell activation (lysosome-associated membrane glycoprotein 3), natural killer cell and T-cell stimulation and cytotoxicity (cluster of differentiation 70, class I-restricted T-cell-associated molecule), B-cell activation (immunoglobulin lambda constant 2), protease-mediated tissue injury (protease, serine 2 [trypsin-2]), dysregulated coagulation (serpin peptidase inhibitor, clade A [alpha-1 antitrypsin], member 5), extracellular matrix remodeling (epidermal growth factor-containing fibulin-like extracellular matrix protein 1), and growth hormone/insulin-like growth factor axis dysregulation (insulin-like growth factor binding protein 3). CONCLUSIONS: We identified an immunologic signature of severe HIV/TB defined by mediators of macrophage/dendritic cell and cytotoxic lymphocyte activation, extracellular matrix remodeling, and dysregulated coagulation. These findings offer new insight into HIV/TB pathobiology and highlight potential targets for host-directed therapies in this high-risk population.

Humans↗

PubMed2026

The association of cardiovascular health with new-onset pulmonary hypertension and the mediating role of proteomic signatures.

BACKGROUND: The cardiovascular health (CVH) metrics have been reported to play an important role in the development of noncommunicable chronic diseases, yet its link to pulmonary hypertension (PH) risk and the underlying biological mechanisms remain unclear. This study aimed to investigate the association of CVH with PH risk and elucidate the mediating role of plasma proteomic signatures. METHODS: A total of 279 220 participants without PH at enrollment of the UK Biobank were included. Cox regression was used to quantify the association between CVH and incident PH. Proteome-wide association analysis, mediation analysis, and functional enrichment analysis were conducted to identify protein mediators. Key hub proteins were further validated at the transcriptional level through quantitative polymerase chain reaction (qPCR) in an animal model of PH, as well as at the protein level, and by macrophage-specific knockdown of interleukin (IL)-6 and CCL4 to evaluate its impact on rat pulmonary artery smooth muscle cell (PASMC) migration and proliferation. RESULTS: Over a median 13.2-year follow-up, 1325 PH cases occurred. Compared to the lowest CVH, participants with moderate and high CVH had 59% [hazard ratio (HR): 0.41; 95% confidence interval (CI): 0.33-0.49] and 82% (HR: 0.18; 95% CI: 0.14-0.23) lower risk, respectively. Proteomic analyses revealed that this association was significantly mediated by a distinct plasma protein signature. Pathway enrichment analysis indicates that proteins are significantly enriched in inflammatory/immune pathways, and key hub proteins were identified as participating in the central mechanism pathway. In the lung tissue of PH rat models, the mRNA and protein expression levels of IL-6 and C-C motif chemokine ligand 4 (CCL4) were significantly elevated. Furthermore, functional assays demonstrated that knockdown of IL-6 or CCL4 in macrophages significantly attenuated the migration and proliferation of rat PASMCs in vitro. CONCLUSION: High CVH level, defined by Life's Essential 8 (LE8), is significantly linked to a reduced risk of developing PH. This protective effect is primarily mediated by a proteomic signature, revealing the role of signaling pathways such as cytokine-cytokine receptor interaction in the prevention of PH.

Hypertension, Pulmonary↗

PubMed1978

A preliminary study in the detection of cardiac disorders via phase-invariant signature algorithm of ECG.

The present paper presents a simple and unambiguous computer-assisted method for the detection of cardiac disorders by processing the electrocardiogram. A new technique "Phase Invariant Signature Algorithm (PISA)", has been described, which is useful in the detection of cardiac abnormalities by investigating certain statistical properties of the measured waveform of ECG in a "phase-locked" fashion. This method of detection of abnormalities in the heart was used in the changes in the hypoxic action potential and in the ECG due to ionic changes and ischemia in the heart of cats and dogs. The signature of the normal ECG or action potential was straight-line. Any change in the waveform of ECG or action potential was detected as spikes in the signature. This method of detection of cardiac abnormalities does not require a priori reference to any standard ECG. The results indicate that this new method is capable of detecting cardiac disorders at an early stage and hence a higher sensitivity than the presently available type of ECG analysis. This method is in the developmental stage and further studies are being carried out.

Animals↗

PubMed2026

TFPI-high myofibroblast states and a meta-program-related five-gene prognostic signature in breast cancer.

Intratumoral heterogeneity and tumor-microenvironment interactions limit prognostic stratification in breast cancer, but the prognostic relevance and cellular context of recurrent transcriptional meta-programs remain unclear. We aimed to derive a meta-program-related prognostic signature and characterize its component transcripts at single-cell resolution. Six paired institutional tumors and adjacent non-tumor tissues served as a proof-of-concept comparison. Univariable Cox screening and least absolute shrinkage and selection operator Cox regression were used to derive a five-gene score from a prespecified meta-program-related candidate set in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) training cohort; the score was tested internally and assessed in GSE20685 using fixed coefficients and cohort-specific median cutoffs. GSE161529 single-cell transcriptomic data were used to map signature transcripts across 136,526 quality-controlled cells, while donor-aware pseudobulk analysis compared upper- and lower-quartile TFPI expression states in annotated myofibroblasts. The score comprised TCN1, FOXJ1, PIGR, SLAIN1, and TFPI and was associated with overall survival in the training, testing, and external cohorts, with concordance indices of 0.782, 0.756, and 0.721, respectively. TFPI transcripts were detected across endothelial, fibroblast, and myofibroblast compartments. TFPI-high myofibroblasts showed transcriptional enrichment of extracellular matrix and collagen fibril organization, transforming growth factor beta signaling, epithelial-mesenchymal transition, and myogenesis, together with lower oxidative phosphorylation and fatty acid metabolism programs. In bulk TCGA-BRCA tissue, TFPI expression correlated positively with stromal (r = 0.48), immune (r = 0.25), and composite microenvironment scores (r = 0.40; all p < 0.001). These findings identify a hypothesis-generating five-gene bulk-tissue prognostic signature and an expression-associated TFPI-high myofibroblast state but do not establish a discrete lineage, the cellular source of bulk TFPI, a TFPI-dependent mechanism, or clinical utility. Independent prospective cohorts, spatial and protein-level validation, and functional perturbation studies are required.

Journal Article↗

PubMed2026

SERPINE1-centric inflammatory signature associates with treatment resistance and survival in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) prognosis remains poor despite treatment advances. More accurate prognostic assessment models can help guide individualized treatment and improve prognosis. Chronic inflammation contributes to tumorigenesis, yet inflammatory response-related genes (IRGs) in LSCC prognosis are underexplored. This study aimed to construct an IRG prognostic signature for LSCC and further dissect core IRG-mediated mechanisms of immune escape and chemoresistance. METHODS: Transcriptional profiles and clinical data from LSCC patients were retrieved from The Cancer Genome Atlas (TCGA). IRGs were sourced from Gene Set Enrichment Analysis (GSEA) hallmark gene set. We identified differentially expressed IRGs linked to survival outcomes in LSCC. Key IRGs were subsequently selected using least absolute shrinkage and selection operator (LASSO) Cox regression analysis to establish an inflammatory risk score model. This model underwent internal validation within the TCGA cohort and external validation using independent Gene Expression Omnibus (GEO) datasets. We further assessed the model's association with the tumor immune microenvironment and the impact of IRGs on chemotherapy response. Finally, the functional roles of interested signature IRG were experimentally validated in LSCC cell lines. RESULTS: Four significant IRGs (AQP9, ITGA5, LCK, SERPINE1) were identified to build the risk score model. The model stratified LSCC patients into distinct prognostic groups: TCGA cohort: 5-year area under the curve (AUC) =0.836, P<0.001; GSE25727 cohort: 5-year AUC =0.706, P=0.02; GSE27020 cohort: 5-year AUC =0.798, P<0.01. Multivariate analysis confirmed the risk score as an independent prognostic factor (P<0.05). High-risk patients showed reduced immune cell infiltration (CD8+ T cells, dendritic cells) and suppressed immune pathways. Multi-algorithm immune analysis further revealed defective antigen presentation and reduced anti-tumor immune infiltration in high-risk LSCC, promoting tumor immune escape. GSEA/Gene Ontology (GO) enrichment combined with drug sensitivity prediction further revealed that high-risk tumors activate invasive signaling and acquire broad chemoresistance alongside impaired anti-tumor immunity. SERPINE1 might be associated with chemotherapy resistance and exhibited the highest alteration frequency (predominantly amplification) and overexpression in LSCC tissues. Its knockdown significantly suppressed proliferation, migration, invasion and chemoresistance in LSCC cells. Immunohistochemistry (IHC) confirmed tumor SERPINE1 overexpression (P=0.002 vs. normal tissues), correlating with poor survival (P<0.001). CONCLUSIONS: The 4-IRG risk signature is a reliable prognostic indicator reflecting immune dysfunction in LSCC. SERPINE1 is validated as a therapeutic target and biomarker, enriching our understanding of gene regulation dynamics in LSCC.

Laryngeal cancer↗

PubMed2026

Microplastics and nanoplastics-related genes signature predicts prognosis in pancreatic ductal adenocarcinoma and functional validation of interleukin 1 alpha.

BACKGROUND: Microplastics and nanoplastics (MNPs), as emerging environmental pollutants, have garnered significant attention from the global scientific community due to their potential threats to human health, particularly their association with the occurrence and development of cancer. The goal of our study is to create a predictive marker for pancreatic ductal adenocarcinoma (PAAD) based on MNPs-related genes, with the purposes of predicting survival outcomes and assessing the tumor immune microenvironment. METHODS: Using multi-cohort data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and International Cancer Genome Consortium (ICGC), we assessed the association between MNPs and PAAD prognosis through the Xiantao Academic (https://www.xiantao.love/). The development of a prognostic signature was followed by an assessment of its significance through the Kaplan-Meier method, time-dependent receiver operating characteristic (ROC), and decision curve analysis (DCA). The validity of the risk model was confirmed through the ICGC and GSE71729 cohorts. The model was then assessed for levels of tumor immune infiltration. To explore MNPs-related genes expression characteristics within immune cells in PAAD, we performed single-cell RNA sequencing and spatial transcriptomics analysis through the Sparkle Platform (https://grswsci.top/). Finally, in vitro experiments were conducted to investigate the biological function of interleukin 1 alpha (IL1A). RESULTS: A four-gene signature comprising XDH, IL1A, KIF20A, and ASPM, based on MNPs, was developed to stratify PAAD patients into two distinct risk groups. The high-risk group showed a significantly poorer prognosis. A similar trend was verified in the external cohorts ICGC and GSE71729. The signature risk score affected immune cell infiltration in the PAAD microenvironment. The infiltration of B cells, CD8+ T cells, cytotoxic cells, immature dendritic cells (iDCs), mast cells, plasmacytoid dendritic cell (pDC), T cells, Tem cells, T follicular helper (TFH) cells, and T helper 17 (Th17) cells had a positive correlation with the low-risk group. In contrast, high-risk patients tended to have increased number of T helper (Th2) cells and higher expression of SIGLEC15, CD274, IGSF8. Knockdown of IL1A in PAAD cells inhibited their tumor proliferation ability in vitro. CONCLUSIONS: Using MNPs-related genes, we built a prognostic model for PAAD, revealing that patients with high-risk scores are likely to have a worse prognosis. This model is designed to develop personalized treatment strategies tailored to the specific needs of each patient, thereby improving clinical outcomes for PAAD patients. Furthermore, IL1A could be a promising therapeutic candidate for PAAD.

Microplastics↗

PubMed2025

Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.

BACKGROUND/AIM: Tumor treatments remain unsatisfactory, as many patients continue to die despite therapy. There is an urgent need for novel drug targets, particularly for rare tumors. In this study, we sought to identify genes with prognostic significance for survival in patients with phaeochromocytoma or paraganglioma. We also examined whether these genes are relevant in other tumor entities. PATIENTS AND METHODS: We mined the TCGA-based KM Plotter and studied 186 risk genes for phaeochromocytoma and paraganglioma. RESULTS: Using Kaplan-Meier statistics, we performed 3,163 calculations based on 7,489 tumor biopsies and identified a 2-gene signature for phaeochromocytoma/paraganglioma (AQP4, FAM84H). Since the 186 risk genes are not exclusively related to the development of phaeochromocytoma/paraganglioma alone, we also investigated their prognostic relevance in 17 other tumor types. A clustered 12-gene signature has been found common in four other tumor entities (liver hepatocellular carcinoma, renal clear cell carcinoma, renal papillary cell carcinoma, lung adenocarcinoma). This signature consisted of BUB1, BUB1B, CDK1, CENPA, CKAP2L, IQGAP3, MKI67, NDC80, PBK, RRM2, TOP2A, and TTK. CONCLUSION: Our analysis provides a basis for the development of a novel prognostic test to predict the survival time of patients.

Kaplan-Meier analysis↗

PubMed2026

ZBTB16-associated NK cell alterations reveal shared immunometabolic signatures linking primary Sjögren's syndrome and type 1 diabetes mellitus.

BACKGROUND: Primary Sjögren's syndrome (pSS) and type 1 diabetes mellitus (T1DM) share immune-inflammatory features, yet conserved pathogenic signatures linking these autoimmune disorders remain incompletely understood. The present research sought to uncover common molecular markers and dissect the underlying immune-metabolic cross-talk underlying pSS and T1DM. METHODS: Gene expression profiles of patients with pSS and T1DM were retrieved from the Gene Expression Omnibus database, normalized, and corrected for batch effects prior to downstream analyses. Overlapping potential biomarkers were screened by integrating differential expression analysis, weighted gene co-expression network analysis and least absolute shrinkage and selection operator regression. Functional enrichment based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases was implemented to interpret gene biological properties, and a protein-protein interaction network was further established afterwards. Diagnostic performance was evaluated using receiver operating characteristic analysis. Experimental validation was conducted in non-obese diabetic (NOD) mice using quantitative PCR, immunohistochemistry, and flow cytometry. The CIBERSORT algorithm was adopted to quantify immune cell infiltration levels. RESULTS: ZBTB16 was identified as a shared hub biomarker in both pSS and T1DM and exhibited favorable diagnostic performance. Experimental validation confirmed significantly reduced ZBTB16 expression in peripheral blood mononuclear cells, salivary gland tissues, and pancreatic tissues of NOD mice. Gene Set Enrichment Analysis indicated that ZBTB16-associated signatures were enriched in mitochondrial-related processes, neuroactive ligand-receptor interactions, and ribosome-related pathways. Immune infiltration analysis revealed that resting natural killer (NK) cells were positively correlated with ZBTB16 expression in both diseases. Flow cytometric analysis further confirmed a reduced proportion of resting NK cells in peripheral blood of NOD mice, consistent with the CIBERSORT-based prediction. CONCLUSION: This study identifies ZBTB16 as a shared biomarker linking pSS and T1DM. Reduced resting NK-cell abundance was consistently observed in both computational and experimental analyses, and bioinformatic correlation analysis suggested a positive association with ZBTB16 expression. These findings provide evidence for shared molecular and immunological signatures underlying the two autoimmune disorders and support further investigation of the biological role and diagnostic value of ZBTB16 in pSS and T1DM.

Sjogren's Syndrome↗