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Results for “TME”

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PubMed2025

Integrative multi-omics analysis proposes a metabolic classification of gliomas: distinct metabolic states, immune infiltration, and prognosis.

BACKGROUND: The tumor microenvironment (TME) of glioma harbors diverse cell types; however, cell metabolic heterogeneity remains to be explored. This study aims to characterize the metabolic features of different cell types in the TME by integrating multiple datasets, including genomics, bulk and single-cell transcriptomics, and metabolomics. METHODS: Unsupervised machine learning was used to construct an energy metabolic classifier based on the metabolic pathways identified from bulk RNA-seq of gliomas in the TCGA dataset. The classifier was externally validated using multiple datasets, including genomics, bulk RNA-seq, snRNA-seq, and the metabolomics data. Furthermore, metabolic heterogeneity associated with the classifier was further characterized at single-cell resolution. RESULTS: The energy metabolism-based classifier stratified patients into two prognostic clusters: patients in cluster 1 were characterized by high pathway activity of glycolysis, the pentose phosphate pathway (PPP), and fatty acid oxidation (FAO), whereas patients in cluster 2 exhibited higher activity in glutaminolysis. This metabolic classifier revealed both intratumoral and intertumoral metabolic heterogeneity, and the complexity was further validated by the metabolomics profiling and snRNA-seq data from the CPTAC dataset. Notably, OSMR, highly expressed in cluster 1, showed significant co-expression with key glycolytic enzyme genes. The OSM/OSMR/JAK1/STAT3 axis potently drives malignant progression of glioma cells, specially enhancing their invasive and migratory capabilities. Single-cell resolution analyses demonstrated that tumor metabolic heterogeneity is primarily driven by malignant cells rather than non-malignant components, while tumor microenvironment (TME) factors were also found to modulate malignant cell metabolism. Significantly, glycolytic activity in glioma cells increased during the phenotypic transition from PN (proneural) to MES (mesenchymal), with cluster 1 metabolic phenotypes predominating in the tumor core. Compared to cluster 2, cluster 1 patients exhibited higher mRNA expression of immunosuppressive checkpoint genes, which correlated with pronounced immunosuppression in the TME. Furthermore, various immune cells demonstrated distinct metabolic preferences at single-cell resolution. CONCLUSIONS: This study developed an energy metabolic-based classifier for gliomas with prognostic and therapeutic potential. Metabolic reprogramming was linked with the PN-to-MES transition of glioma cells and immunosuppression in the tumor microenvironment. Multi-omics data, especially snRNA-seq, offered insights into metabolism heterogeneity at single-cell resolution, enabling personalized treatment strategies.

Humans↗

PubMed2024

Interactions between microbiota and uterine corpus endometrial cancer: A bioinformatic investigation of potential immunotherapy.

Microorganisms in the gut and other niches may contribute to carcinogenesis while also altering cancer immune surveillance and therapeutic response. However, determining the impact of genetic variations and interplay with intestinal microbes' environment is difficult and unanswered. Here, we examined the frequency of thirteen mutant genes that caused aberrant gut in thirty different types of cancer using The Cancer Genomic Atlas (TCGA) database. Substantially, our findings show that all these mutated genes are quite frequent in uterine corpus endometrial cancer (UCEC). Further, these mutant genes are implicated in the infiltration of different subset of immune cells within the Tumor Microenvironment (TME) of UCEC patients. The top-ranking mutant genes that promote immune cell invasion into the TME of UCEC patients were PGLYRP2, OLFM4, and TLR5. In this regard, we used the same deconvolution of the TCGA database to analyze the microbiome that have a strong association with immune cells invasion with TME of UCEC patients. Several bacteria and viruses have been linked to the invasion of immune cells, such as B cell memory and T cell regulatory (Tregs), into the TME of UCEC patients. As a result, our findings pave the way for future research into generating novel immunizations against bacteria or viruses as immunotherapy for UCEC patients.

Humans↗

PubMed1976

Transmissible mink encephalopathy. Reduced spongiform degeneration in aged mink of the Chediak-Higashi genotype.

Mink which are 18 months or older and are dying of transmissible mink encephalopathy (TME) have been found to have a marked reduction in spongiform degeneration of the brain if they are homozygous for the Aleutian gene and thus exhibit the autosomal recessive disorder known as the Chediak Higashi (CH) syndrome. CH mink younger than 1 year, and young or old non-CH mink have a typical lesion profile with widespread microvacuolation of the neuropile. Whereas aged CH mink have reduced spongiform degeneration at both the light and electron microscopic level, there is no other apparent alteration in the TME disease process. The length of incubation, clinical signs, astrocytic response, and brain concentration of the TME agent are comparable to those seen in non-CH mink. We conclude that spongiform degeneration is a secondary change in TME and speculate that vacuolation may be the result of lysosomal enzymes causing an increase in ganglioside catabolism.

Age Factors↗

PubMed2026

Integrated Genomic and Tumor Microenvironment Subtyping Improved Risk Stratification in Primary Central Nervous System Lymphoma.

Current prognostic models fail to capture the biological complexity of primary central nervous system lymphoma (PCNSL). We integrated whole-genome sequencing and multiplex immunofluorescence in 68 treatment-naïve patients to define four genomic subtypes (C1, C2, C3, and C4) with divergent survival (C4 worst: median overall survival [OS], 26 months). In parallel, a novel tumor microenvironment (TME) classification based on CD8+T/M2 macrophage ratio stratified patients into High (> 1.5), Intermediate (0.8-1.5), and Low (< 0.8) groups. Unexpectedly, the Intermediate TME group showed the poorest outcomes (5-year OS: 10%). Integration revealed a lethal subgroup (C4 + Intermediate TME; 9.8% of cohort) with a median OS of 3.0 months (hazard ratio = 7.24, p = 0.006). Prognostic nomograms incorporating these subtypes showed promising discriminative performance in internal validation (C-index > 0.78), but external validation is needed. Together, these findings identify a high-risk biological subset and provide a hypothesis-generating framework for future biomarker-driven risk stratification and therapeutic discovery in PCNSL.

Humans↗

PubMed2026

Impact of Genomic Mutations on the Transcriptional Pathways and Tumor Microenvironment Landscape of Localized Early Prostate Cancer.

BACKGROUND: The management of intermediate-risk early prostate cancer (PCa) is challenging due to the difficulty in distinguishing indolent from aggressive tumors. This study explores the association between genomic alterations and the tumor and its microenvironment (TME) and implications for disease progression. METHODS: We performed multi-omic profiling in a cohort of 53 localized PCa using targeted sequencing, transcriptional, and proteomic spatial profiling. RESULTS: Somatic mutations and copy number alterations in RB1 (21%), PTEN (18%), and TP53 (9%) were identified. Kaplan-Meier analysis revealed that alterations in the RB and Cell Cycle pathways, particularly aberrations in PTEN, TP53, or RB1, were associated with shorter biochemical recurrence-free survival (p < 0.001). Spatial proteomic analysis demonstrated a complex immune landscape in patients with mutations. The tumor compartment demonstrated higher expression of immune checkpoint markers, T-cell activation proteins, and proliferation markers; and a TME that is enriched with CD8 + T cells and antigen-presenting cells, but also with immunosuppressive M2 macrophages, suggesting adaptive immune resistance. CONCLUSIONS: Our analysis demonstrates that genomic alterations in PTEN, TP53, or RB1 are not only prognostic for poor outcomes but are also associated with a unique, immunologically complex TME in this Brazilian cohort.

Humans↗

PubMed2025

Integrating necroptosis and immune landscapes: a multi-omics-derived NecropImmScore stratifies prognosis and therapy in ovarian cancer.

BACKGROUND: Ovarian cancer (OC) remains the deadliest gynecologic malignancy, largely due to its immunosuppressive tumor microenvironment (TME) and resistance to therapy. Necroptosis, a regulated lytic cell death pathway mediated by the RIPK1-RIPK3-MLKL axis, can trigger immunogenic cell death, but its specific role in shaping the OC immune landscape and its clinical translation potential are posorly understood. METHODS: We employed multi-omics analysis (transcriptomics, genomics, clinical data) from TCGA-OV (n = 380), ICGC OV-AU, and IMvigor210 cohorts, combined with rigorous in vitro functional validation using OC cell lines (SKOV3, HEY), macrophages (THP-1 derived), and T cells (Jurkat). Computational immunology approaches (ESTIMATE, CIBERSORT, ssGSEA) quantified immune infiltration. We identified MLKL-associated immune genes, performed survival analysis (Kaplan-Meier, Cox regression), and constructed a necroptosis-immune signature (NecropImmScore) using consensus clustering and PCA of 102 prognostic genes. Drug sensitivity was predicted via pRRophetic and CellMiner. RESULTS: MLKL emerged as a protective prognostic biomarker (p = 0.018), significantly correlated with enhanced immune infiltration (ImmuneScore, StromalScore, ESTIMATEScore; p < 2.22e-16), M1 macrophage polarization (p = 0.006), activated CD4 + T cells (p = 0.003), and elevated immune checkpoint expression (PD-L1, CTLA4, LAG3, TIGIT). In vitro, MLKL overexpression in OC cells promoted M1 polarization (p < 0.05), activated Jurkat T cells (upregulated CCR4/5/7/9, CD69, CD3D/E, GZMB; p < 0.05), and induced key chemokines (CXCL9/10/11/13) critical for immune cell recruitment. Integration of MLKL-related and immune-related DEGs (n = 632) revealed enrichment in T-cell activation, chemokine signaling, and antigen presentation pathways (FDR < 0.05). Consensus clustering based on 102 survival-associated genes defined three molecular subtypes (Clusters A-C) with divergent survival (p = 0.019), necroptosis activity, and immune infiltration (Cluster C: best prognosis, highest MLKL/ImmuneScore). The derived NecropImmScore robustly stratified patients: high-score correlated with superior overall survival (TCGA: p < 0.001; ICGC: p = 0.014), inflamed TME phenotype, elevated checkpoint expression, and improved response to anti-PD-L1 in IMvigor210. Critically, high NecropImmScore predicted higher BRCA1 mutation frequency (AUC = 0.802), synergy with BRCA1 status for prognosis, higher homologous recombination deficiency (HRD) score, sensitivity to cisplatin (p = 0.014), paclitaxel (p = 0.016), gemcitabine (p = 0.017), and provided superior prognostic stratification when combined with TMB and HRD score (p < 0.001). CONCLUSION: This study establishes MLKL as a master regulator of anti-tumor immunity in OC, driving chemokine-mediated immune cell recruitment and TME reprogramming. The novel NecropImmScore is a multifaceted biomarker that effectively predicts prognosis, immunotherapy response, BRCA1 deficiency, and chemosensitivity, offering significant potential for guiding precision therapeutic strategies in OC.

Humans↗

PubMed1977

Electron-microscopic appearance of the DA virus, a demyelinating murine virus.

The DA virus is a neurotropic murine virus which can induce acute encephalomyelitis in suckling mice and a chronic myelopathy in weanlings. The agent has been attenuated by serial passage in baby hamster kidney (BHK-21) cells. When attenuated virus is inoculated in 8-week-old C3HeJ mice a myelopathy of delayed onset with prominent demyelination of lateral and anterior columns occurs. The DA virus is believed to be related to the Theiler murine encephalomyelitis (TME) viruses because of the similar clinical and pathological conditions which it causes, and because neutralization tests indicate shared antigens between it and GD7, a TME virus. This paper reports electron-microscopic studies of BHK-21 cells infected with DA virus. The cells were prepared 24 and 48 hr after inoculation. Cytopathic effects were observed and infected cells contained plaques consisting of numerous 25 nm virus particles in crystalline array. The virions were exclusively intracytoplasmic and were morphologically indistinguishable from human poliomyelitis virus. These observations appear to establish DA as a picorna virus, related to the TME virus group. The chronic myelopathy caused by DA may prove relevant to chronic demyelinative myelopathies in man, such as multiple sclerosis, and also to amyotrophic lateral sclerosis.

Animals↗

PubMed2026

Single-cell and spatial transcriptomic technologies for lung cancer tumor microenvironment analysis.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide; beyond its rising incidence, its marked molecular heterogeneity and complex tumor microenvironment (TME) hinder treatment response and drive resistance, contributing directly to its high mortality rate. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) provide complementary approaches for dissecting these features. scRNA-seq enables high-resolution analysis of cellular diversity and transcriptional states but requires tissue dissociation and therefore loses spatial context. In contrast, ST preserves tissue architecture and provides insights into how gene-expression programs within the TME are organized, although no currently available spatial platform combines whole-transcriptome coverage with true single-cell resolution over large tissue areas. Together, these technologies have enabled detailed mapping of tumor, immune and stromal populations and of their spatial interactions, revealing functionally distinct cellular niches that contribute to immune evasion, metastasis and response to therapy. In this narrative review we organize the primary literature around a single question, how spatially structured cellular ecosystems, rather than individual cell types, determine therapeutic response and resistance in lung cancer - and we explicitly separate observations that are reproducible across independent cohorts and platforms from those that remain confined to single studies. We further summarize the technical, analytical and logistic barriers that currently prevent spatially resolved signatures from entering routine diagnostic pathology. Understanding dysregulated pathways and spatially constrained intercellular communication within the TME helps identify candidate biomarkers and may support the identification of therapeutic approaches directed at tumor-intrinsic programs as well as at microenvironment-driven resistance mechanisms.

Cell-cell communication↗

PubMed2026

MIF-CD74 axis facilitates MDSC infiltration in the tumor microenvironment of pancreatic ductal adenocarcinoma.

Immune checkpoint inhibitors show insufficient efficacy against pancreatic ductal adenocarcinoma (PDAC). The tumor microenvironment (TME) has a remarkable influence on responsiveness to cancer immunotherapy. The aim of this study was to investigate immunosuppressive characteristics of TME in PDAC tissues. The flow cytometry (FCM) of PDAC surgical specimens revealed that the profile of tumor-infiltrating leukocytes was classified into myeloid cell- and T-cell-dominant subtypes; the myeloid subtype was associated with poorer patient outcomes. Myeloid-derived suppressor cells (MDSCs) showed the highest hazard ratio among various myeloid cell types. Single-cell RNA sequencing and FCM revealed that most MDSCs, but not lymphocytes, in PDAC tissues characteristically express CD74. Macrophage migration inhibitory factor (MIF), a CD74 ligand, was highly expressed in cancer-associated fibroblasts (CAFs) and cancer cells. Spatial transcriptomics demonstrated that the MIF-CD74+ myeloid cell interaction was recognized in CAF-dominant areas in PDAC tissue. CAFs expressing immune suppressor molecules such as MFAP5 and LRRC15 were consistent with MIF+ CAFs. Furthermore, MIF+ CAFs enhanced the migratory activity of MDSCs and promoted MDSC induction and activation. In the murine model, MDSCs were significantly increased in MIF-expressing PDAC tumors, as were CD74+ M-MDSCs per M-MDSC, confirming in vivo interaction between CD74 and MIF. MDSCs play a crucial role in creating an immunosuppressive TME in PDAC; the MIF-CD74 axis drives interactions between MDSCs and CAFs.

Humans↗

PubMed2026

An immune exhaustion signature predicts prognosis and identifies patients with diffuse large B-cell lymphoma (DLBCL) who derive preferential benefit from chimeric antigen receptor (CAR)-T cell therapy.

BACKGROUND: The tumor microenvironment (TME) is a key determinant of prognosis in diffuse large B-cell lymphoma (DLBCL). While T-cell exhaustion is implicated in therapeutic failure, its precise molecular hallmarks and utility for predicting response to modern immunotherapies, such as chimeric antigen receptor (CAR)-T cell therapy, remain unclear. METHODS: We performed an integrative analysis of transcriptomic and clinical data from multiple DLBCL cohorts (The Cancer Genome Atlas [TCGA], GSE181063, GSE10846, GSE248835, GSE182434). We used unsupervised clustering, exploratory analysis of single-cell RNA sequencing data, and the least absolute shrinkage and selection operator for variable selection (LASSO-Cox) regression to characterize the exhausted TME, construct a prognostic model, and evaluate its predictive value for CAR-T cell therapy. The model's dynamic behavior was assessed in a proof-of-concept longitudinal cohort of patients treated with the T-cell-engaging bispecific antibody glofitamab. RESULTS: We identified a "high-exhaustion" subtype associated with significantly poorer overall survival (OS; log-rank P = 0.016). Based on this, we developed a five-gene immune exhaustion-Related Prognostic Score (IERPS) that served as a robust independent predictor of poor OS across multiple cohorts. Critically, in a cohort of 256 relapsed/refractory patients, the IERPS was strongly prognostic for event-free survival (EFS) in the standard-of-care (SOC) arm (HR = 2.02, 95% confidence interval [95% CI]: 1.07-3.81, P = 0.029) but lost prognostic significance in the CAR-T arm (HR = 0.70, 95 % CI: 0.35-1.40, P = 0.314). This significant interaction suggests that CAR-T cell therapy may abrogate the poor prognosis associated with a high IERPS. Biologically, exploratory single-cell analysis (n = 4 samples) defined the high-IERPS state by hallmarks of classical T-cell exhaustion, and a descriptive case study showed the score dynamically tracked clinical response to glofitamab. CONCLUSIONS: A state of active T-cell exhaustion and a suppressive TME drive the adverse immune phenotype in DLBCL. Our IERPS model captures this dysfunctional state, acting as a powerful prognostic tool and, more importantly, as a potential predictive biomarker to identify high-risk patients who appear to overcome their inherently poor prognosis through CAR-T cell therapy.

Biomarkers↗

PubMed2026

Beyond oncogenesis: The emerging role of EZH2 in tumor microenvironment.

Enhancer of zeste homolog 2 (EZH2), a histone methyltransferase and the catalytic component of Polycomb Repressive Complex 2, facilitates epigenetic modifications via the repressive H3K27me3 mark, consequently modulating the expression of numerous genes implicated in cellular proliferation and survival. Overexpression or dysregulation of EZH2 has been observed extensively across several malignancies, where it plays a major role in shaping the tumor microenvironment, promoting angiogenesis, cytokine secretion, and matrix remodeling. EZH2 mediates immune evasion, particularly in response to immunotherapy and checkpoint blockade. These interactions also position EZH2 as a key mediator of therapy resistance to chemotherapy, immunotherapy, and targeted therapy. Consequently, a comprehensive understanding of EZH2's function and its interactions within the TME and during cancer progression is crucial. This review aims to enhance the current understanding of EZH2 and its roles in the TME, cancer development, and therapeutic responses. This review will discuss the canonical and non-canonical functions of EZH2, summarize its established and evolving roles in cancer and the TME, and highlight its effects on tumor immunity and therapeutic efficacy.

Humans↗

PubMed2025

Histology-Based Virtual RNA Inference Identifies Pathways Associated With Metastasis Risk in Colorectal Cancer.

Colorectal cancer (CRC) remains a major health concern, with >150,000 new diagnoses and >50,000 deaths annually in the United States, underscoring an urgent need for improved screening, prognostication, disease management, and therapeutic approaches. The tumor microenvironment (TME)-comprising cancerous and immune cells interacting within the tumor's spatial architecture-plays a critical role in disease progression and treatment outcomes, reinforcing its importance as a prognostic marker for metastasis and recurrence risk. However, traditional methods for TME characterization, such as bulk transcriptomics and multiplex protein assays, lack sufficient spatial resolution. Although spatial transcriptomics (ST) allows for the high-resolution mapping of whole transcriptomes at near-cellular resolution, current ST technologies (eg, Visium and Xenium) are limited by high costs, low throughput, and issues with reproducibility, preventing their widespread application in large-scale molecular epidemiology studies. In this study, we refined and implemented virtual RNA inference (VRI) to derive ST-level molecular information directly from hematoxylin and eosin (H&E)-stained tissue images. Our VRI models were trained on the largest matched CRC ST data set to date, comprising 45 patients and >300,000 Visium spots from primary tumors. Using state-of-the-art deep learning models (UNI, ResNet-50, Vision Transformer, and Vision Mamba), we achieved a median Spearman's correlation coefficient of 0.546 between predicted and measured spot-level expression. As validation, VRI-derived gene signatures linked to specific tissue regions (tumor, interface, submucosa, stroma, serosa, muscularis, and inflammation) showed strong concordance with signatures generated via direct ST, and VRI performed accurately in estimating cell-type proportions spatially from H&E slides. In an expanded CRC cohort controlling for tumor invasiveness and clinical factors, we further identified VRI-derived gene signatures significantly associated with key prognostic outcomes, including metastasis status. Although certain tumor-related pathways are not fully captured by histology alone, our findings highlight the ability of VRI to infer a wide range of "histology-associated" biological pathways at near-cellular resolution without requiring ST profiling. Future efforts will extend this framework to expand TME phenotyping from standard H&E tissue images, with the potential to accelerate translational CRC research at scale.

Humans↗

PubMed2026

Pan-cancer analysis identifies GPRIN1 as a prognostic biomarker and promoter of cell proliferation in pancreatic cancer.

BACKGROUND: G protein-regulated inducer of neurite outgrowth 1 (GPRIN1), an emerging modulator of GPCR signaling, has been implicated in oncogenesis. However, its comprehensive role across human cancers, particularly in reshaping the tumor microenvironment (TME), remains poorly characterized. We aimed to elucidate the pan-cancer significance of GPRIN1 in TME modulation and its therapeutic implications. METHODS: We analyzed multi-omics data from TCGA and other public databases, performing a systematic analysis of GPRIN1 regarding expression, prognosis, immune infiltration, and genomic instability across 33 cancer types. To validate these bioinformatic findings, we performed lentiviral shRNA-mediated knockdown in pancreatic (PANC-1) and hepatic (HepG2) cancer cells to assess proliferation and migration. Crucially, the clinical relevance of GPRIN1 was further validated in an independent cohort of pancreatic cancer patients (N = 17) using immunohistochemistry (IHC). RESULTS: The analysis identified a lineage-dependent expression pattern. Epithelial tumors exhibited upregulation, whereas glioblastoma samples displayed downregulation. GPRIN1 expression consistently correlated with immune subtypes and CD8+ T cell abundance. In vitro assays demonstrated that GPRIN1 depletion significantly inhibited cell proliferation and migration (P < 0.0001). In the clinical validation cohort, multivariate Cox regression analysis identified high GPRIN1 protein levels as an independent predictor of post-operative recurrence. These patients also showed a trend toward extended overall survival. CONCLUSIONS: These findings define GPRIN1 as a context-dependent regulator of the TME. By integrating computational and experimental data, this study supports GPRIN1 as a potential biomarker for risk assessment in pancreatic cancer.

Humans↗

PubMed2022

S-nitrosylation of CSF1 receptor increases the efficacy of CSF1R blockage against prostate cancer.

Sustained oxidative stress in castration-resistant prostate cancer (CRPC) cells potentiates the overall tumor microenvironment (TME). Targeting the TME using colony-stimulating factor 1 receptor (CSF1R) inhibition is a promising therapy for CRPC. However, the therapeutic response to sustained CSF1R inhibition (CSF1Ri) is limited as a monotherapy. We hypothesized that one of the underlying causes for the reduced efficacy of CSF1Ri and increased oxidation in CRPC is the upregulation and uncoupling of endothelial nitric oxide synthase (NOS3). Here we show that in high-grade PCa human specimens, NOS3 abundance positively correlates with CSF1-CSF1R signaling and remains uncoupled. The uncoupling diminishes NOS3 generation of sufficient nitric oxide (NO) required for S-nitrosylation of CSF1R at specific cysteine sites (Cys 224, Cys 278, and Cys 830). Exogenous S-nitrosothiol administration (with S-nitrosoglutathione (GSNO)) induces S-nitrosylation of CSF1R and rescues the excess oxidation in tumor regions, in turn suppressing the tumor-promoting cytokines which are ineffectively suppressed by CSF1R blockade. Together these results suggest that NO administration could act as an effective combinatorial partner with CSF1R blockade against CRPC. In this context, we further show that exogenous NO treatment with GSNOR successfully augments the anti-tumor ability of CSF1Ri to effectively reduce the overall tumor burden, decreases the intratumoral percentage of anti-inflammatory macrophages, myeloid-derived progenitor cells and increases the percentage of pro-inflammatory macrophages, cytotoxic T lymphocytes, and effector T cells, respectively. Together, these findings support the concept that the NO-CSF1Ri combination has the potential to act as a therapeutic agent that restores control over TME, which in turn could improve the outcomes of PCa patients.

Cysteine↗

PubMed2026

Inhibiting macrophage-derived lactate transport restores cGAS-STING signalling and enhances antitumour immunity in glioblastoma.

Glioblastoma (GBM) is a malignancy with a complex tumour microenvironment (TME) dominated by GBM stem cells (GSCs) and infiltrated by tumour-associated macrophages (TAMs) and exhibits aberrant metabolic pathways. Lactate is a critical glycolytic metabolite that promotes tumour progression; however, the mechanisms of lactate transport and lactylation in the TME of GBM remain elusive. Here we show that lactate is transported from TAMs to GSCs via MCT4-MCT1. TAMs provide lactate to GSCs, promoting GSC proliferation and inducing lactylation of the non-homologous end joining protein KU70 at lysine 317 (K317), which inhibits cGAS-STING signalling and remodels the immunosuppressive TME. Inhibition of lactate transport or targeting the lactylation of KU70, in combination with the immune checkpoint blockade, demonstrates additive therapeutic benefits in immunocompetent xenograft models. This study unveils TAM-derived lactate and lactylation as critical regulators in GSCs to enforce an immunosuppressive microenvironment, opening avenues for developing combinatorial therapy for GBM.

Glioblastoma↗

PubMed2026

Endothelial cell-specific DNA methylation alterations in breast cancer.

DNA methylation alterations are well-established contributors to carcinogenesis, yet, in the tumor microenvironment (TME), patterns of lineage and cell-specific methylation alterations are not well understood. Single-cell DNA methylation profiling in the TME is limited by technical challenges and high costs. Here, we use bulk DNA methylation, cell type deconvolution (HiTIMED), and an interaction testing framework (CellDMC) to identify reproducible, computationally inferred lineage-specific epigenetic alterations in the TME supported by orthogonal data sources. Tumor endothelial cells (TECs), critical regulators of angiogenesis, vascular permeability, and immune cell trafficking, acquire structural and functional abnormalities that promote tumor growth. We hypothesize that TECs have altered DNA methylation compared with endothelial cells in non-tumor tissues. In genome-scale methylation data from discovery and validation datasets (tumor n = 1071; non-tumor n = 415), we identify and validate >4500 TEC-specific CpGs with altered methylation, many mapping to genes involved in angiogenesis and endothelial function. Integration with gene expression data indicates that TEC-specific methylation alterations may reprogram transcriptional networks controlling angiogenesis. High-resolution, cell lineage-specific epigenetic landscapes can be inferred from bulk methylation data, implicating TEC-specific DNA methylation alterations as potential drivers of cancer angiogenesis and vascular dysfunction and providing a framework for future mechanistic and translational studies of the tumor vasculature.

DNA Methylation↗

PubMed2025

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans↗

PubMed2026

Local gene editing of fibroblasts in tumors reveals a new cancer-associated fibroblast state.

Fibroblasts play critical roles in regulating cellular relationships during tissue homeostasis, immunity, and tumor biology at multiple sites. However, tools to perturb fibroblasts at just one site in vivo are limited, restricting our understanding of how these cellular relationships act locally. We optimized local gene editing of fibroblasts in mouse tumor models to investigate how fibroblast perturbations affect the tumor microenvironment (TME). By knocking out receptors Osmr, Tgfbr2, or Il1r1 on cancer-associated fibroblasts (CAFs), we uncover that TGFBR2 signaling loss induces the emergence of a new Col18a1hi CAF cell state that is associated with worse survival in pancreatic cancer patients. Combinatorial gene KOs in CAFs reveals a circuit where these Col18a1hi CAFs reshape the TME by recruiting Siglec-Fhi neutrophils via Cxcl5 expression, and where this Col18a1hi CAF cell state is dependent on TNFR1 and canonical Wnt signaling. Together, a fast, affordable, and modular engineering method is demonstrated, allowing discovery of modified fibroblast identities and local intercellular relationships in the TME.

Animals↗