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PubMed2025

COL5A1 in the tumor microenvironment predicts the prognosis of head and neck cancer.

ObjectivesThis study aims to investigate the significance of tumor microenvironment (TME)-related genes and signal transduction pathways in head and neck cancer (HNC).MethodsGene expression and clinical data of HNC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened through a multi-step filtration approach to obtain candidate predictors. The biological role of COL5A1 in HNC was verified through rigorous bioinformatic analysis, experimental validation using quantitative real-time PCR (qRT-PCR), immunohistochemical (IHC) analysis from HNC samples, and IHC data from the Human Protein Atlas (HPA) database.ResultsCOL5A1 was significantly upregulated in HNC tissues and cell lines. High COL5A1 expression was significantly associated with advanced tumor grade (P < .05) and shorter survival (TCGA: P < .001; GSE42743: P = .004). COL5A1 was an independent prognostic indicator (univariate analysis: HR = 1.324, P = .001; Multivariate analysis: HR = 1.326, P = .005). It was enriched in pathways related to tumor invasion and immune responses, and its expression was associated with decreased levels of CD8+ T cells and increased levels of macrophages and neutrophils. Spatial distribution analysis revealed higher expression at the tumor's leading edge (vs. tumor core: P < .001). COL5A1 expression is associated with tumor stage, with more pronounced expression in advanced-stage tumors.ConclusionCOL5A1 represented a novel potential prognostic indicator and therapeutic target in an HNC database sample, as its expression is closely linked to tumor progression, immune cell infiltration, and adverse clinical outcomes. These findings, primarily derived from squamous cell carcinoma-dominated cohorts, warrant further functional validation.

Humans↗

PubMed2024

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Humans↗

PubMed2025

Construction of a prognostic model for gastric cancer based on immune infiltration and microenvironment, and exploration of MEF2C gene function.

BACKGROUND: Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. METHODS: Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. RESULTS: Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. CONCLUSIONS: Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Humans↗

PubMed2025

Habitat radiomics predicts occult lymph node metastasis and uncovers immune microenvironment of head and neck cancer.

BACKGROUND: Occult lymph node metastasis (LNM) is a key prognostic factor for patients with head and neck squamous cell carcinoma (HNSCC). This study was to establish radiomics models derived from intratumoral, peritumoral, and habitat regions for identifying occult LNM in HNSCC. METHODS: Patients with pathologically confirmed HNSCC from three medical Centers (from March 2014 to April 2024) and The Cancer Genome Atlas (TCGA) were enrolled. Center 1 was split into training (n = 330) and internal test sets (n = 154), while Center 2 and Center 3 served as the external test set (n = 183). Genomic set (n = 50) from TCGA and single-cell RNA sequencing set (n = 6) from Center 1 were used for biological analysis. We used the intratumoral, peritumoral, and habitat volumes of interest (VOIs) to extract radiomics features, respectively. Based on Logistic Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) classifiers, nine radiomics models were built to confirm the optimal predictive performance. The best-performing model, along with clinical-radiologic data, was combined to develop a hybrid model. The log-rank test was used to evaluate the model's prognostic performance. Additionally, bulk and single-cell RNA sequencing were applied for investigating the biological mechanisms underlying the optimal model. RESULTS: The RF-habitat radiomics model showed the best performance, achieving AUCs of 0.835-0.919 across all datasets. Survival analysis further confirmed the prognostic value of the RF-habitat radiomics model. The RF-habitat radiomics model and the hybrid model notably surpassed the clinical model in predictive performance. Moreover, the RF-habitat radiomics model was associated with the abundance level of exhaustion-associated CD8 + T cells, uncovering the immune microenvironment characteristics contributing to occult LNM in HNSCC. CONCLUSIONS: The RF-habitat radiomics model demonstrated excellent performance for predicting occult LNM in HNSCC across three cohorts, providing a non-invasive solution for occult LNM. Furthermore, radiogenomic analysis further revealed the biological associations of the model, primarily related to T cell dysfunction.

Humans↗

PubMed2026

Secreted protein circuits in the gastrointestinal tumour microenvironment: determinants of immunotherapy response and resistance.

Immune checkpoint blockade has transformed treatment in selected gastrointestinal (GI) cancers, yet primary resistance, incomplete responses and acquired resistance remain common. This heterogeneity is not explained by tumour-cell genomics alone; extracellular signalling programmes within the tumour microenvironment can determine immune recruitment, access and adaptation to therapy. The tumour secretome-including cytokines, chemokines, growth factors, complement components, matricellular proteins, soluble checkpoint molecules and extracellular-vesicle-associated cargo-regulates immune-cell recruitment, exclusion, suppression, tertiary lymphoid structure formation and exhaustion across anatomical and molecular contexts. Across gastric and esophageal cancers, colorectal cancer, pancreatic ductal adenocarcinoma, hepatocellular carcinoma and biliary tract cancers, recurrent suppressive circuits include TGF-β, VEGF, CXCL12-CXCR4, CXCL8/IL-8-CXCR1/2, CCL2-CCR2, CSF1-CSF1R, IL-6-family cytokines, SPP1/osteopontin, periostin, galectins, DKK1, MIF, complement and soluble or vesicular PD-L1. Conversely, CXCL9/10/11-CXCR3 signalling and CXCL13-associated tertiary lymphoid structures characterise immune-permissive states that can support checkpoint responsiveness. We organise these circuits into four overlapping functional modules-myeloid-enriched, fibroblast-driven exclusion, angiogenic-immunosuppressive and immune-permissive-and apply a four-level evidence hierarchy that separates clinical validation from mechanistic inference. Clinically useful secretome biomarkers will therefore need to integrate cellular source, spatial localisation, receptor context, temporal dynamics and linkage to actionable immune-state transitions.

Humans↗

PubMed2026

CARS1 as a Prognostic Biomarker and Candidate Therapeutic Vulnerability in Hepatocellular Carcinoma: Insights Into Tumor Progression and the Immune Microenvironment.

BACKGROUND: Cysteinyl-tRNA synthetase 1 (CARS1) has been included in ferroptosis-related prognostic signatures, but its clinicopathological relevance, cellular functions, and relationship with the immune microenvironment in hepatocellular carcinoma (HCC) remain incompletely characterized. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset were integrated with corresponding data from an institutional HCC tissue cohort of 60 patients. CARS1 expression was evaluated by immunohistochemistry, and immune infiltration was examined using single-sample gene-set enrichment analysis (ssGSEA) and multiplex immunofluorescence, as well as by analyzing public single-cell datasets. The effects of CARS1 depletion were evaluated in MHCC97H and Hep3B cells using Cell Counting Kit-8 (CCK-8) assays, cell-cycle profiling, wound-healing assays, Transwell migration assays, western blotting, and erlotinib-sensitivity assays. RESULTS: CARS1 expression was elevated in HCC and was associated with adverse clinicopathological features and poor overall survival. Quantitative immunohistochemistry confirmed elevated CARS1 protein expression in tumor tissues. CARS1 depletion inhibited cell proliferation, altered cell-cycle distribution, impaired migration, and enhanced in vitro sensitivity to erlotinib. High CARS1 expression was also associated with increased infiltration of Th2-like immune cells. CONCLUSIONS: Elevated CARS1 expression is associated with an adverse biological and immune phenotype in HCC. These clinical, histopathological, and loss-of-function findings support further investigation of CARS1 as a prognostic marker and candidate therapeutic target in HCC, although additional mechanistic and in vivo validation is required.

Humans↗

PubMed2024

A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer.

Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.

Humans↗

PubMed2026

Targeting USP22 reprograms the tumor microenvironment and sensitizes KRAS/p53-driven lung cancer to anti-PD-1 immunotherapy.

RATIONALE: Ubiquitin-specific peptidase 22 (USP22), a deubiquitinase and component of the "Death-from-Cancer" 11-gene signature, is overexpressed in multiple malignancies and linked to recurrence, therapy resistance, and poor prognosis. Its role in KRAS/p53-driven lung cancer and the response to immune checkpoint inhibitors (ICIs) remains poorly defined. Here, we investigated USP22 as a potential therapeutic target in KRAS/p53-driven lung cancer. METHODS: A conditional Usp22 knockout (Usp22-KO) was generated in the KRASG12D; p53-/- (KP) mouse model. Cancer progression was monitored by micro-computed tomography (micro-CT). Multiplex immunofluorescence (mIF), RNA sequencing, and spatial transcriptomics profiled cancer and tumor microenvironment (TME) changes. Responses to anti-PD-1/PD-L1 therapies were compared between KP and Usp22-KO KP (KPU-) lung cancers. RESULTS: USP22 was highly expressed in early-stage KRAS/p53-driven mouse lung cancers and strongly correlated with proliferation marker Ki67. Usp22 deletion suppressed cancer growth, prolonged survival, and promoted cancer differentiation. Spatial transcriptomics and mIF revealed reduced CD206+ M2 macrophages, myeloid-derived suppressor cells (MDSCs), TGF-β1, and angiogenesis, along with increased functional CD8+ T cells. Mechanistically, USP22 regulated gene expression and protein stability, reducing c-Myc, PD-L1, TGF-β1, and SPARC upon Usp22 loss. Compared with KP cancer, KPU- and SPARC-knockdown KP cancers showed reduced macrophage chemotaxis and impaired basal- and TGF-β1-induced M2 polarization of RAW264.7 cells, suggesting that TGF-β1 and SPARC downregulation partially contributes to decreased M2 macrophage infiltration in KPU- cancers. Notably, Usp22 loss enhanced the efficacy of anti-PD-L1 and anti-PD-1 therapies in orthotopic and subcutaneous KP lung cancer models, respectively. USP22 and SPARC expression were also strongly correlated in human lung cancers. CONCLUSIONS: USP22 promotes progression and immune evasion in KRAS/p53-driven lung cancer. Targeting USP22 reprograms the TME, suppresses oncogenic signaling, and sensitizes tumors to ICI, establishing USP22 as a promising therapeutic target.

Animals↗

PubMed2026

ATRX Condensates as Candidate Organizers of Enhancer-Centered Nuclear Microenvironments in Neural Progenitors: A Hypothesis for Enhancer-Associated ATRX Function in Neural Progenitors.

Neural progenitor cells (NPCs) must preserve lineage identity while remaining responsive to developmental cues. Here, we discuss the hypothesis that ATRX condensates help organize enhancer-centered nuclear microenvironments in NPCs. ATRX has long been studied in heterochromatin maintenance, histone variant deposition, and chromatin remodeling; earlier work has also shown that ATRX can occupy euchromatic and active regulatory regions and contribute to transcriptional regulation. Recent evidence in human NPCs indicates that ATRX forms nuclear puncta with condensate-like properties, associates with neurogenic enhancer-rich regions, and incorporates regulatory factors such as CHD7 and p300. Perturbation of ATRX condensate formation is associated with changes in enhancer-associated ATRX occupancy, neural gene-expression programs, and neuroepithelial organization, suggesting a regulatory mode that may complement canonical heterochromatin-associated functions. We propose a dual-mode model in which folded domains contribute to chromatin anchoring at repressive regions, whereas intrinsically disordered regions support condensate-associated organization at active developmental enhancers. We emphasize that whether ATRX condensates activate enhancers de novo, stabilize pre-existing enhancer states, buffer transcriptional variability, or primarily organize cofactor localization remains unresolved. We also discuss limitations of the current evidence and outline acute, locus-specific experiments needed to test the model.

X-linked Nuclear Protein↗

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↗

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

Unraveling lung cancer complexity: Spatial omics in tumor microenvironment characterization and precision medicine.

Heterogeneous tumor microenvironment (TME) in lung cancer plays a crucial role in disease progression and resistance to therapy. Despite advances in single-cell and bulk omics profiling, these methods often overlook spatial context, which is vital for understanding cell-cell interactions and regional heterogeneity. In recent years, spatial omics technologies-including spatial genomics, transcriptomics, proteomics, and metabolomics-have revolutionized the ability to map molecular landscapes while maintaining tissue architecture. These advancements have become essential components of next-generation lung cancer management. By providing unprecedented resolution in characterizing the lung cancer TME, spatial omics could reveal prognostic and predictive biomarkers and identify new therapeutic vulnerabilities. This review will provide the first critical evaluation of spatial multi-omics approaches for lung cancer prognosis. It will also assess various integration strategies for multi-omics data to explore the clinical translational potential of these tools for therapy selection and patient stratification. Therefore, a deeper understanding of spatial omics technologies and their application in lung cancer can significantly improve precision diagnostics and therapeutic decision-making.

Lung cancer↗

PubMed2026

Region-Resolved Integrative Multi-Omic Characterization Reveals Diverse Tumor and Microenvironment Features of Pituitary Neuroendocrine Tumors.

Pituitary neuroendocrine tumors are frequently invasive, with cavernous sinus invasion leading to poor treatment outcomes and high recurrence. Regional differences within these tumors remain poorly understood, hindering targeted therapy development. Here, we present the first integrative multi-omics analysis combining proteomics, metabolomics and single-cell transcriptomics to characterize tumors from the cavernous sinus and saddle regions. Our results reveal profound regional and cellular heterogeneity: cavernous sinus tumors exhibit significantly enhanced cell proliferation, driven by cancer-associated fibroblasts through the IGF1-IGF1R-MAPK1 axis. Cancer-associated fibroblasts in the cavernous sinus secrete IGF1 under regulation of the transcription factor FOXO1, which binds to receptors on tumor cells to activate proliferation. Metabolomic profiling identifies proline as a key enriched metabolite that stimulates cancer-associated fibroblasts to produce collagen fibers, reinforcing a pro-tumorigenic microenvironment. Single-cell transcriptomics further delineates a distinct subpopulation of receptor-positive malignant cells and a high abundance of cancer-associated fibroblasts in the cavernous sinus. These findings establish core mechanisms underlying the aggressive behavior of cavernous sinus-invading tumors, providing novel actionable targets for precision therapeutic strategies tailored to distinct tumor regions.

Humans↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2021

Viral infection of cells within the tumor microenvironment mediates antitumor immunotherapy via selective TBK1-IRF3 signaling.

Activating intra-tumor innate immunity might enhance tumor immune surveillance. Virotherapy is proposed to achieve tumor cell killing, while indirectly activating innate immunity. Here, we report that recombinant poliovirus therapy primarily mediates antitumor immunotherapy via direct infection of non-malignant tumor microenvironment (TME) cells, independent of malignant cell lysis. Relative to other innate immune agonists, virotherapy provokes selective, TBK1-IRF3 driven innate inflammation that is associated with sustained type-I/III interferon (IFN) release. Despite priming equivalent antitumor T cell quantities, MDA5-orchestrated TBK1-IRF3 signaling, but not NFκB-polarized TLR activation, culminates in polyfunctional and Th1-differentiated antitumor T cell phenotypes. Recombinant type-I IFN increases tumor-localized T cell function, but does not mediate durable antitumor immunotherapy without concomitant pattern recognition receptor (PRR) signaling. Thus, virus-induced MDA5-TBK1-IRF3 signaling in the TME provides PRR-contextualized IFN responses that elicit functional antitumor T cell immunity. TBK1-IRF3 innate signal transduction stimulates eventual function and differentiation of tumor-infiltrating T cells.

Animals↗

PubMed2024

Circadian rhythms of macrophages are altered by the acidic tumor microenvironment.

Tumor-associated macrophages (TAMs) are prime therapeutic targets due to their pro-tumorigenic functions, but varying efficacy of macrophage-targeting therapies highlights our incomplete understanding of how macrophages are regulated within the tumor microenvironment (TME). The circadian clock is a key regulator of macrophage function, but how circadian rhythms of macrophages are influenced by the TME remains unknown. Here, we show that conditions associated with the TME such as polarizing stimuli, acidic pH, and lactate can alter circadian rhythms in macrophages. While cyclic AMP (cAMP) has been reported to play a role in macrophage response to acidic pH, our results indicate pH-driven changes in circadian rhythms are not mediated solely by cAMP signaling. Remarkably, circadian disorder of TAMs was revealed by clock correlation distance analysis. Our data suggest that heterogeneity in circadian rhythms within the TAM population level may underlie this circadian disorder. Finally, we report that circadian regulation of macrophages suppresses tumor growth in a murine model of pancreatic cancer. Our work demonstrates a novel mechanism by which the TME influences macrophage biology through modulation of circadian rhythms.

Tumor Microenvironment↗

PubMed2024

Genomic and the tumor microenvironment heterogeneity in multifocal hepatocellular carcinoma.

BACKGROUND AND AIMS: Ambiguous understanding of tumors and tumor microenvironments (TMEs) hinders accurate diagnosis and available treatment for multifocal hepatocellular carcinoma (HCC) covering intrahepatic metastasis (IM) and multicentric occurrence (MO). Here, we characterized the diverse TMEs of IM and MO identified by whole-exome sequencing at single-cell resolution. APPROACH AND RESULTS: We performed parallel whole-exome sequencing and scRNA-seq on 23 samples from 7 patients to profile their TMEs when major results were validated by immunohistochemistry in the additional cohort. Integrative analysis of whole-exome sequencing and single-cell RNA sequencing found that malignant cells in IM showed higher intratumor heterogeneity, stemness, and more activated metabolism than those in MO. Tumors from IM shared similar TMEs while distinct TMEs were noticed in those from MO. Furthermore, CD20+ B cells, plasma cells, and conventional type II dendritic cells (cDC2s) were decreased in IM relative to MO while T cells in IM exhibited a more terminally exhausted capacity with a higher proportion of proliferative/exhausted T cells than that in MO. Both CD20 and CD1C correlated with better prognosis in multifocal HCC. Additionally, MMP9+ tumor-associated macrophages were enriched across IM and MO, which formed cellular niches with regulatory T cells and proliferative/exhausted T cells. CONCLUSIONS: Our findings deeply decipher the heterogeneous TMEs between IM and MO, which provide a comprehensive landscape of multifocal HCC.

Humans↗

PubMed2025

Spatially organized lymphocytic microenvironments in high grade primary prostate tumors.

The spatial organization and composition of the tumor-immune microenvironment (TME) play a critical role in shaping the progression of many solid cancers, but the organization of the TME in primary prostate cancer (PCa) remains poorly characterized. We therefore profiled the abundance and spatial distributions of major cell types involved in adaptive immunity in 29 radical prostatectomy specimens stratified into high (HGG; n=14) and low Gleason-grade (LGG; n=15). Compared to LGG, HGG PCa exhibited significantly greater B and T cell infiltration with many immune cells organized into clusters, some of which resembled tertiary lymphoid structures (TLSs). In HGG tumors, these clusters were dense, symmetric, rich in PD-1+ T cells, and frequently proximate to the tumor compartment. LGG clusters were less well organized, and T cell depleted. Thus, a subset of high-grade PCa harbor organized immune clusters that may play a role in tumor control and contain therapeutically targetable T and B cells.

Prostate cancer↗