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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

A pan-cancer single-cell atlas uncovers the role of sex hormones and chromosomes in sex-divergent reprogramming of the tumor microenvironment.

BACKGROUND: Sex bias is pervasive in tumors; however, how sex chromosomes and hormone-responsive signaling shape the tumor microenvironment (TME) remains insufficiently characterized. Considering the critical impact of the TME on tumor progression and response to immunotherapy, a pan-cancer investigation of sex-specific and cancer-context-dependent TME features is warranted. METHOD: Based on stringent inclusion criteria, we constructed a high-resolution pan-cancer single-cell sequencing atlas by integrating 31 publicly available single-cell RNA-seq datasets, comprising a total of 1,831,436 cells by integrating 468 samples from eight types of non-sex-specific solid tumors (282 males and 186 females). After correcting for batch effects, we identified major and minor cellular subsets. Multiple computational approaches were applied to investigate sex-associated differences in cellular composition, gene expression, pathway activity, malignant cell states and intercellular communication. RESULTS: We systematically compared sex-specific TME features across eight common solid malignancies. Male-biased CD8+ T cell exhaustion emerged as a recurrent but non-uniform feature, with its magnitude varying across cancer types and being modified by tissue-specific contexts. This pattern was associated with androgen-response signature scores and expression-based loss of the Y chromosome (LOY) scores. M2-like macrophage polarization showed a more cancer-type-dependent pattern; although female-biased enrichment was observed in selected malignancies, it did not represent a uniform pan-cancer feature. Expression-based X chromosome inactivation (XCI)/XCI escape-related programs, estrogen-response signature scores and stromal components, including fibroblasts and endothelial cells, were associated with macrophage and immune-regulatory states in specific tumor contexts. Tumor cells of male origin displayed higher genomic instability and more aggressive phenotypes, with androgen-response signatures and LOY contributing to the development of a male biased malignant state. Furthermore, expression-based LOY scores in malignant cells were associated with CD8+ T cell exhaustion based on transcriptomic proxies. CONCLUSION: Our study uncovers extensive but heterogeneous sex-specific differences in the TME across multiple cancer types. We propose a regulatory framework linking sex chromosomes, hormone-responsive signaling and TME interactions, which is consistent with recurrent male-biased CD8⁺ T cell exhaustion and context-dependent M2-like macrophage polarization. Importantly, the magnitude and, in some cancers, the direction of these sex-biased features are modified by tissue-specific contexts. These findings underscore the need to include sex chromosome and hormone status as essential biological variables in studies of the tumor microenvironment and the design of immunotherapies.

Tumor Microenvironment

Oncogenic Mutations and Tumor Microenvironment Alterations in Diffuse Large B-Cell Lymphoma With Bulky Disease.

BACKGROUND: Bulky disease represents a clinically aggressive subset of diffuse large B-cell lymphoma (DLBCL) associated with adverse clinical outcomes. The aim of this study was to investigate the influence of oncogenic mutations and tumor microenvironment alterations on bulky disease in DLBCL. METHODS: We analyzed a cohort of 939 patients with newly diagnosed DLBCL. Using DNA (n = 934) and RNA (n = 524) sequencing, we compared oncogenic mutations and tumor microenvironment (TME) alterations based on tumor diameter, with cutoff values at 5.0 cm and 10.0 cm. Further stratification by mutations in key genes (CD58, STAT6, EBF1) correlated with tumor diameter revealed distinct transcriptomic and immunologic profiles. Subsequent single-cell RNA sequencing, guided by these mutational signatures, resolved the cellular heterogeneity within the TME. RESULTS: Integrative analysis revealed that tumor diameter correlated with increased incidence of mutations in CD58, STAT6, and EBF1; adverse genetic subtypes such as EZB-like MYC+ and TP53Mut; activation of oncogenic pathways (JAK/STAT, BCR, PI3K, and MYC); and an immunosuppressive tumor microenvironment. Notably, immune checkpoint molecules varied across the bulky stages, with CTLA-4, TIGIT, ICOS, and CD28 expression inversely correlated with tumor diameter, while CD70 and 4-1BBL expression positively correlated. Single-cell RNA sequencing further revealed mutation-specific tumor microenvironment insights. CD58-mutated tumor exhibited a profoundly immune-deserted microenvironment dominated by malignant B cells with minimal immune infiltration, whereas STAT6-mutated tumor was associated with increased fibroblasts and CD4 + T cells, particularly regulatory T cells (Treg) and Th1-like cells; EBF1-mutated tumor was characterized by increased proportions of malignant B cells. CONCLUSIONS: Collectively, our findings highlight the biological complexity of bulky disease, identifying candidate molecular targets and providing a biological framework for future therapeutic hypothesis generation in this clinically aggressive subset of DLBCL.

Humans

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

Targeting Regnase-1 in B7-H3-CAR T cells reprograms the tumor microenvironment and enhances antitumor efficacy for osteosarcoma.

The microenvironment in solid tumors represents an immunosuppressive therapeutic barrier to CAR T cell therapy, and it is currently unknown whether it can be reshaped by the deletion of negative regulators in CAR T cells. To address this knowledge gap, we evaluated the intrinsic and extrinsic effects of deleting the negative regulator Regnase-1 (Reg-1) in B7-H3-CAR T cells for the immunotherapy of osteosarcoma. Reg-1 knockout (KO) improved the antitumor activity of human and murine B7-H3-CAR T cells in vivo. In immune-competent models, Reg-1 KO also endowed murine B7-H3-CAR T cells with the ability to create a proinflammatory landscape characterized by an influx of interferon gamma (IFN-γ)-producing endogenous T cells and natural killer (NK) cells and a reduction of inhibitory myeloid cells, including M2-like macrophages. Thus, deleting Reg-1 has cell- and non-cell-autonomous benefits, nominating Reg-1 KO B7-H3-CAR T cells as a promising cell product for early-phase clinical testing in patients with solid tumors.

Animals

Modulation of the tumor microenvironment by the ubiquitin-proteasome system in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with the tumor microenvironment (TME) playing a pivotal role in its progression and therapeutic resistance. The ubiquitin-proteasome system (UPS), a central regulator of intracellular protein degradation, is increasingly recognized for its involvement in cancer pathogenesis, though its specific role in modulating the CRC TME remains to be fully elucidated. This review aims to systematically summarize current evidence on how the UPS influences the immunosuppressive network within the CRC TME and to evaluate its potential as a therapeutic target. METHODS: We conducted a comprehensive literature search in PubMed, Web of Science, and Scopus databases for original research articles and reviews published between January 2010 and August 2025, using keywords including "ubiquitin-proteasome system," "colorectal cancer," "tumor microenvironment,""immune escape,"and "targeted therapy." Studies were selected based on their relevance to UPS-mediated regulatory mechanisms in CRC TME remodeling, immune cell function, and treatment response. RESULTS: Our analysis of preclinical and clinical evidence reveals that the UPS critically regulates immune evasion in CRC through multiple mechanisms: (1) USP14 stabilizes indoleamine 2,3-dioxygenase 1 (IDO1), enhancing tryptophan catabolism and kynurenine accumulation, which suppresses T-cell activity; (2) E3 ligases including SPOP, C-Cbl, KLHL22, and FBW7 modulate PD-L1/PD-1 protein stability via ubiquitination, thereby influencing immune checkpoint signaling; and (3) ZFP91 facilitates K63-linked ubiquitination of PP2Ac, impairing mTORC1-mediated glycolysis in T cells and reinforcing regulatory T-cell immunosuppression. Additionally, the UPS intersects with key oncogenic pathways such as Wnt/β-catenin, NF-κB, and p53, further shaping the immunosuppressive landscape of CRC. CONCLUSIONS: Targeting the UPS represents a promising strategy to reverse immunosuppression and overcome therapy resistance in CRC. The primary advantage of this approach lies in its ability to simultaneously disrupt multiple immunosuppressive pathways within the TME, offering a potential solution to the limitations of single-target therapies. Current approaches include proteasome inhibitors, E3 ligase modulators, and deubiquitinating enzyme inhibitors, with combination regimens-such as UPS inhibitors with immune checkpoint blockade-showing synergistic efficacy in preclinical models. Future efforts should focus on enhancing the selectivity of UPS-targeting agents, minimizing off-target effects, and integrating genomic profiling to guide personalized treatment. While current evidence strongly supports the therapeutic potential of UPS targeting, its establishment as a reliable alternative therapy in the clinic will depend on overcoming these challenges and validating efficacy in human trials. This review underscores the UPS as a central regulator of the CRC TME and provides a rational basis for novel therapeutic development.

Humans

Systematic Analysis of Tumor Microenvironment Using IOBR.

The Immuno-Oncology Biological Research (IOBR) package is an R-based analysis tool for exploring the tumor microenvironment (TME) and its influence on anti-tumor immunity. Built for high-throughput data-spanning both transcriptomic and genomic profiles-IOBR integrates six analytical modules, including transcriptomic data preprocessing, TME profiling, TME pattern identification, ligand-receptor interaction analysis, genome-TME interaction assessment, and visualization. In this chapter, we walk through a multi-omics workflow using example datasets, illustrating data preparation, distribution analyses, result interpretation, and graphical output. IOBR is open source and is available at https://github.com/IOBR/IOBR and a detailed GitBook ( https://iobr.github.io/book/ ) offers a complete manual and analysis guide for each function.

Tumor Microenvironment

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&#x2009;<&#x2009;.05) and shorter survival (TCGA: P&#x2009;<&#x2009;.001; GSE42743: P&#x2009;=&#x2009;.004). COL5A1 was an independent prognostic indicator (univariate analysis: HR&#x2009;=&#x2009;1.324, P&#x2009;=&#x2009;.001; Multivariate analysis: HR&#x2009;=&#x2009;1.326, P&#x2009;=&#x2009;.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&#x2009;<&#x2009;.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

Tumor-immune partitioning and clustering algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment.

BACKGROUND: Growing evidence supports the importance of characterizing the organizational patterns of various cellular constituents in the tumor microenvironment in precision oncology. Most existing data on immune cell infiltrates in tumors, which are based on immune cell counts or nearest neighbor-type analyses, have failed to fully capture the cellular organization and heterogeneity. METHODS: We introduce a computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), that jointly measures immune cell partitioning between tumor epithelial and stromal areas and immune cell clustering versus dispersion. As proof-of-principle, we applied TIPC to a prospective cohort incident tumor biobank containing 931 colorectal carcinoma cases. TIPC identified tumor subtypes with unique spatial patterns between tumor cells and T lymphocytes linked to certain molecular pathologic and prognostic features. T lymphocyte identification and phenotyping were achieved using multiplexed (multispectral) immunofluorescence. In a separate hepatocellular carcinoma cohort, we replaced the stromal component with specific immune cell types-CXCR3+CD68+ or CD8+-to profile their spatial relationships with CXCL9+CD68+ cells. RESULTS: Six unsupervised TIPC subtypes based on T lymphocyte distribution patterns were identified, comprising two cold and four hot subtypes. Three of the four hot subtypes were associated with significantly longer colorectal cancer (CRC)-specific survival compared to a reference cold subtype. Our analysis showed that variations in T-cell densities among the TIPC subtypes did not strictly correlate with prognostic benefits, underscoring the prognostic significance of immune cell spatial patterns. Additionally, TIPC revealed two spatially distinct and cell density-specific subtypes among microsatellite instability-high colorectal cancers, indicating its potential to upgrade tumor subtyping. TIPC was also applied to additional immune cell types, eosinophils and neutrophils, identified using morphology and supervised machine learning; here two tumor subtypes with similarly low densities, namely 'cold, tumor-rich' and 'cold, stroma-rich', exhibited differential prognostic associations. Lastly, we validated our methods and results using The Cancer Genome Atlas colon and rectal adenocarcinoma data (n = 570). Moreover, applying TIPC to hepatocellular carcinoma cases (n = 27) highlighted critical cell interactions like CXCL9-CXCR3 and CXCL9-CD8. CONCLUSIONS: Unsupervised discoveries of microgeometric tissue organizational patterns and novel tumor subtypes using the TIPC algorithm can deepen our understanding of the tumor immune microenvironment and likely inform precision cancer immunotherapy.

Humans

Effect of Tertiary Lymphoid Structures on Immune Cell Infiltration in the Tumor Microenvironment and Prognosis in Lung Adenocarcinoma.

Tertiary lymphoid structures (TLSs) modulate immune responses in various solid tumors, but their comprehensive role in lung adenocarcinoma (LUAD) remains unclear. In this study, we analyzed RNA-seq data from 539 LUAD patients in The Cancer Genome Atlas (TCGA) and microarray data from 223 samples from the Gene Expression Omnibus (GEO, GSE13213, and GSE37745). TLS signatures were evaluated via unsupervised consensus clustering based on 12 chemokine transcriptome signatures. The relationships between TLS and clinical characteristics, tumor microenvironment (TME) cell infiltration, and prognosis were assessed using ESTIMATE and CIBERSORT. A prognostic model was established using LASSO regression and validated with external datasets. Additionally, H&E and IHC analyses were performed to explore associations between intratumoral TLS density, immune-related molecular expression, and patient prognosis in LUAD. Consensus clustering of the TCGA cohort revealed two distinct LUAD patient clusters according to TLS abundance. Cluster 1 exhibited greater immune cell infiltration, more favorable prognosis, and increased expression of immune checkpoint molecules. We developed a prognostic model comprising eight survival-associated genes that act as independent prognostic factors for patient survival. H&E/IHC analyses revealed that TLS density-regardless of pathological stage-was associated with better prognosis; higher intratumoral TLS density/proportion was also related to more favorable outcomes. IHC confirmed that survival-associated genes (CD5, HLA-DMB, and P2RY13) are independent prognostic indicators in LUAD. Our study demonstrated the close relationship between TLS signatures and an active immune microenvironment, highlighting their potential as independent prognostic indicators in LUAD.

Humans

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

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&#xa0;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 NF&#x3ba;B-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

Artificial intelligence-powered spatial analysis of tumor microenvironment in patients with non-small cell lung cancer with acquired resistance to EGFR tyrosine kinase inhibitor.

PURPOSE: This study evaluated the dynamic changes in the tumor microenvironment (TME) in patients with non-small cell lung cancer (NSCLC) and acquired resistance to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) using an artificial intelligence (AI)-powered spatial TME analyzer. We then assessed the predictive efficacy of immune-checkpoint inhibitors (ICIs)-based treatment. EXPERIMENTAL DESIGN: An AI-powered whole-slide image analyzer was used to segment cancer areas (CAs) and cancer stroma and to identify tumor-infiltrating lymphocytes (TILs), tertiary lymphoid structures, fibroblasts, and endothelial cells (ECs) in the tumor tissue. We analyzed 143 NSCLC samples after resistance to EGFR-TKIs from two cohorts: (1) 89 patients treated with ICI monotherapy and (2) 54 patients from the ATTLAS phase III trial comparing atezolizumab plus bevacizumab, paclitaxel, and carboplatin (ABCP) versus pemetrexed plus carboplatin. RESULTS: Post-TKI samples showed reduced TILs in the CA (p=0.045) and increased ECs in the CA (p=0.005) compared with pre-TKI samples. These changes differed according to EGFR mutation subtype. Higher TILs in CA were associated with a better overall response rate (ORR) and progression-free survival (PFS). Similarly, higher EC levels in CA correlated with improved ORR and PFS. In the ATTLAS cohort, these factors were associated with clinical benefits from ABCP, with a significant association with TILs and a marginal association with ECs. CONCLUSION: Our findings suggest that EGFR-TKIs affect the immune landscape of patients with EGFR-mutated NSCLC. Higher TILs or ECs in the CA were significantly associated with a favorable response to subsequent ICI-based treatment. TRIAL REGISTRATION NUMBER: NCT03991403.

Aged

Pan-cancer characterization of HMGA1 reveals its oncogenic role in tumor microenvironment and stemness: functional validation in pancreatic cancer migration and invasion.

BACKGROUND: HMGA1 is a chromatin-associated oncogenic factor implicated in tumor progression, epithelial-mesenchymal transition (EMT), stemness, and metastasis. However, its pan-cancer expression and prognostic patterns, epigenetic activation, and relationship with malignant-cell stemness/plasticity and tumor microenvironment (TME) remodeling in pancreatic adenocarcinoma (PAAD) remain incompletely defined. This study aimed to systematically characterize HMGA1 across cancers and clarify its clinical and biological relevance in PAAD. METHODS: Pan-cancer transcriptomic, clinical, genetic, methylation, immune, and stemness data were integrated from multiple public databases. PAAD single-cell RNA sequencing data were analyzed to localize HMGA1 expression, infer malignant-cell pseudotime, calculate a stemness module score, and assess ligand-receptor communication using CellChat. Public HMGA1-knockdown RNA sequencing data were reanalyzed to evaluate transcriptional remodeling. The Cancer Genome Atlas (TCGA)-PAAD expression and methylation data were used to assess TME-remodeling, immune-suppression, stemness/plasticity, cytokine/chemokine, checkpoint, and promoter-methylation features. HMGA1 expression and function were further examined using immunohistochemistry (IHC), quantitative real-time polymerase chain reaction, Western blotting, wound-healing assays, and Transwell migration and invasion assays. RESULTS: HMGA1 was upregulated in most tumor types, and high expression was associated with unfavorable survival in multiple cancers, including PAAD. In PAAD, HMGA1 was enriched in malignant epithelial cells and positively correlated with pseudotime (Spearman's rho =0.594), while the stemness module score increased along pseudotime (rho =0.748). HMGA1-high malignant cells showed markedly stronger CellChat-inferred outgoing communication, predominantly involving extracellular matrix (ECM)-receptor, adhesion-related, and selected immunomodulatory ligand-receptor axes. HMGA1 knockdown was associated with broad remodeling of EMT, TGF-&#x3b2;, Hedgehog, IL6/JAK/STAT3, KRAS, and cancer stem cell/stemness-related programs rather than uniform suppression of these programs. HMGA1 promoter methylation was inversely correlated with HMGA1 expression (rho =-0.633) and the TME-remodeling score (rho =-0.347). HMGA1 was associated with selected mediators, including PPIA, PLAU, ANXA1, LGALS9, TGFB1, CD276, and CD47, but not with a generalized checkpoint-high phenotype. Functionally, HMGA1 knockdown significantly reduced pancreatic cancer (PC) cell migration and invasion. CONCLUSIONS: These findings support an association-based model in which promoter hypomethylation-associated HMGA1 activation is linked to malignant epithelial stemness/plasticity, ECM/adhesion-dominant TME remodeling, selected immunomodulatory programs, and aggressive PAAD phenotypes. Further mechanistic and clinical validation is required before HMGA1 can be used for therapeutic stratification or immunotherapy-response prediction.

HMGA1

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

Effect of extracellular vesicles in remodeling the tumor microenvironment by DNMT1 downregulation for enhanced cancer immunotherapy.

BACKGROUND: The efficacy of immunotherapy is often hindered by the suppression of immune responses via the tumor microenvironment (TME). The presence of cancer cells forces other proximal non-cancerous cells to support tumor growth and persistence. A clear example of this cancerous-to-non-cancerous communication is represented by the accumulation of myeloid-derived suppressor cells (MDSCs) within the TME. Several studies have convergently shown that the overexpression of DNA-methyl-transferase-1 (DNMT1) in these cells results in protection from necroptosis and enhanced accumulation in vivo. Conversely, targeting DNMT1 through hypo-methylating agents has shown promising therapeutic potential by not only reducing the levels of MDSCs but also enhancing cancer immunogenicity and the efficacy of immune checkpoint inhibitors (ICI). METHODS: Murine 4T1 (triple-negative breast cancer (TNBC)) and CT26 (colon carcinoma) cell lines were cultured under standard conditions and used to generate tumor models in BALB/c mice. An oncolytic adenovirus expressing a DNMT1-targeting short hairpin RNA (OAd.shDNMT1) was engineered and validated for DNMT1 knockdown and genome-wide methylation reduction. Small extracellular vesicles (sEVs) were isolated from virus-infected cancer cells and characterized for RNA content and uptake by MDSCs. MDSC differentiation and suppressive function were assessed in vitro using flow cytometry and co-culture assays with murine splenocytes. In vivo, tumor-bearing mice received intratumoral OAd.shDNMT1, systemic decitabine, or immune checkpoint inhibitors (anti-Programmed cell Death protein-1), and tumor growth, immune infiltration, and systemic MDSC levels were evaluated. RESULTS: In this study, we report that, by using virally infected TNBC murine cells as a source for shDNMT1-loaded sEVs, OAd.shDNMT1 successfully reduced MDSC levels in vitro and in vivo. Furthermore, the co-administration with ICI resulted in a significant tumor growth reduction in mice bearing poorly immunogenic TNBC 4T1 cells. Also, our treatment promoted antitumor immunity, prolonged survival, and complete tumor eradication in modestly immunogenic colon CT26 cancer cells. CONCLUSION: This multifaceted strategy, based on OV-mediated immune stimulation and reduction of MDSC levels via sEVs, may improve clinical outcomes and the success of immuno-based regimens for patients facing MDSC-rich and highly aggressive cancer subtypes.

Animals

Radiogenomic MRI biomarkers for noninvasive prediction of GPC3 expression and tumor microenvironment in hepatocellular carcinoma.

BACKGROUND: Glypican-3 (GPC3) is frequently overexpressed in hepatocellular carcinoma (HCC) and plays a key role in immune and metabolic remodeling of the tumor microenvironment. Reliable noninvasive biomarkers for predicting GPC3 status could improve patient stratification and support precision immunotherapy. METHODS: This multicenter retrospective study included 274 patients with pathologically confirmed hepatocellular carcinoma from three institutions, 34 external cases with MRI from The Cancer Imaging Archive, and 363 transcriptomic profiles from The Cancer Genome Atlas. Contrast-enhanced T1-weighted imaging and diffusion-weighted imaging were analyzed. Tumor and peritumoral regions were segmented manually and radiomic features extracted using PyRadiomics. Feature selection was performed with correlation filtering and least absolute shrinkage and selection operator regression. Machine learning classifiers including logistic regression, random forest, support vector machine, k-nearest neighbor, and decision tree were trained with 10-fold cross-validation and tested on independent external cohorts. A radiomics score was calculated for each patient. Radiogenomic analysis correlated radiomics scores with transcriptomic data using weighted gene co-expression network analysis. Hub genes and enriched pathways were identified, and immune infiltration and predicted immunotherapy response were assessed using computational methods. RESULTS: The random forest model using contrast-enhanced T1-weighted imaging achieved an area under the curve of 0.966 in training and 0.935 in internal validation. The integrated contrast-enhanced T1-weighted imaging plus diffusion-weighted imaging model reached an internal validation area under the curve of 0.979. In external testing, the best performance was obtained with a support vector machine model (area under the curve 0.756). Radiomics scores were significantly correlated with GPC3 expression (R&#x2009;=&#x2009;0.78, p&#x2009;<&#x2009;0.05). Transcriptomic analysis identified a 10-gene signature enriched in hypoxia and lipid metabolism pathways that stratified patients into prognostic subgroups (concordance index 0.720, hazard ratio 4.07, p&#x2009;<&#x2009;0.0001). High-risk patients had greater immune infiltration and a lower predicted immune evasion score, suggesting a potential benefit from immunotherapy. CONCLUSIONS: MRI-based radiomics models can noninvasively predict GPC3 expression in hepatocellular carcinoma. Radiomics scores reflect underlying hypoxia and lipid metabolism pathways and stratify patients by prognosis and predicted immunotherapy response. These findings support radiogenomics as a translational approach to imaging-guided precision treatment in hepatocellular carcinoma.

Humans

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