Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Immune microenvironment”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5Linked to original sources

Splenic extramedullary hematopoiesis in myelofibrosis is shaped by transcriptomic and epigenetic dysregulation.

Myelofibrosis (MF) is a chronic, progressive myeloproliferative neoplasm characterized by bone marrow fibrosis, ineffective blood cell production, and neoplastic extramedullary hematopoiesis (EMH) occurring primarily within the spleen. To explore the molecular mechanisms underlying splenic EMH, we performed single-cell transcriptional and chromatin profiling of cells from MF spleens that had been surgically removed. We demonstrate significant expansion of hematopoietic stem and progenitor cells, coupled with aberrant differentiation toward the erythroid and megakaryocytic lineages, associated with a significant enrichment of inflammatory pathways with enhanced NF-κB signaling and IFN responses, as well as dysregulation of the inferred function of differentiation-defining transcription factors. Finally, we report a significant remodeling of the immune microenvironment in MF spleens, characterized by emergence of dysfunctional T cell subsets and inflammatory memory B cells, suggesting the concomitant establishment of a pro-inflammatory and immune-tolerant tumor microenvironment within the spleen that influences hematopoietic cell differentiation and impairs tumor immune surveillance.

Primary Myelofibrosis↗

PSMB8: an immune-related prognostic marker for low-grade gliomas.

BACKGROUND: Glioma is the most common primary intracranial tumor in adults. As a subunit of immune proteasome, proteasome subunit beta type-8 (PSMB8) may regulate the progression of glioma via participating in degradation and presentation of tumor antigenic peptides, but its prognostic and clinical applicant usage is under investigation. Therefore, this study aimed to comprehensively evaluate the prognostic significance of PSMB8 in low-grade glioma (LGG) and to elucidate its association with the tumor immune microenvironment and potential as a predictor for immunotherapy response. METHODS: Transcriptome data were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO) repositories. The correlations between PSMB8 expression and the clinicopathological features of LGG were investigated in our study, and the prognostic role of PSMB8 in LGGs was assessed fully and comprehensively. Furthermore, we evaluated the correlation between PSMB8 expression and LGG immune environment via the experiments and bioinformatic analysis. RESULTS: Our results indicated that, PSMB8 were highly expressed in most tumor tissues, including LGG. Lower expression of PSMB8 was significantly correlated with lower World Health Organization (WHO) grade and isocitrate dehydrogenase (IDH) mutation status. Moreover, PSMB8 showed a promising prognostic ability for LGG patients via nomogram model and receiver operating characteristic (ROC) curves. Association analysis showed that PSMB8 expression was associated with immune cell infiltration in a variety of tumors, including LGG. Our experiments validated the positive correlation between PSMB8 expression and M2-macrophage infiltration level in clinical LGG tissues and invasive ability of LGG cell. CONCLUSIONS: PSMB8 could be used as one of the prognostic indicators of LGG and it could regulate the LGG cell migratory and invasive ability. Besides, PSMB8 is expected to be a promising biomarker of cancer immunotherapy.

Low-grade glioma (LGG)↗

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

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

Laryngeal cancer↗

T cell subsets of urine-derived lymphocytes (UDLs) serve as an indicator of TILs and reflect immunological sex differences in bladder cancer.

BACKGROUND: Bladder cancer is unique among visceral malignancies in that urine, which can be easily obtained, has prolonged contact with bladder tumors. Urinary biomarkers offer the potential to provide insight into the host and tumor immune microenvironment to guide therapeutic strategies. We evaluated the immune cellular composition of urine (urine-derived lymphocytes (UDLs)) versus tumor (tumor-infiltrating lymphocytes (TILs)). METHODS: We employed high-dimensional flow cytometry analyses on immune cells from tumors (TILs), urine (UDLs), and peripheral blood (peripheral blood mononuclear cells) among patients with bladder cancer. We performed multiplexed immunofluorescence (mIF) of matched tumors to provide spatial context to our findings, comparing deep/invasive and superficial/urine-facing regions of matched tumors. RESULTS: Our findings suggest that the CD4+ and CD8+ T cell subsets of UDLs characterized by flow cytometry had similar phenotypic profiles to those found in TILs (cell clusters quantified by multidimensional scaling and differentiation states). Results of mIF imaging with a panel of phenotypic and functional T cell markers suggested that UDLs reflected TILs in both superficial and deep tumor sections. We also found sex-dependent patterns in TILs and UDLs, indicating the male bladder cancer tumor microenvironment is enriched in exhausted CD4+ and CD8+ T cells, while the female bladder cancer microenvironment is enriched for activated T cells. CONCLUSIONS: Assessment of UDLs opens avenues of non-invasive biomarker development in clinical settings where bladder cancer TILs are hypothesized to predict clinical response. UDLs may also reflect sex-based differences in antitumor immunity.

Humans↗

Invasive mucinous adenocarcinoma of the lung: integrating molecular landscape, imaging phenotypes, and translational therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA) of the lung is an uncommon but clinically important subtype of lung adenocarcinoma with distinctive radiologic, histopathologic, and molecular features. Its indolent symptoms, mucin-rich growth pattern, and frequent pneumonia-like or multifocal presentation can obscure early diagnosis and complicate distinction from infection, synchronous primary tumors, and intrapulmonary spread. This review integrates current evidence on the clinical course, imaging phenotypes, diagnostic workflow, histopathologic features, molecular alterations, tumor immune microenvironment, and treatment response patterns of IMA. Emphasis is placed on the relationship between radiologic appearance and underlying mucinous pathology, the clinical significance of spread through air spaces (STAS), and the need for adequate tissue sampling and comprehensive molecular profiling. Compared with non-mucinous lung adenocarcinoma, IMA is enriched for KRAS mutations and selected fusion or receptor alterations, whereas canonical EGFR mutations are less frequent. These biological differences help explain why treatment strategies extrapolated from broader non-small cell lung cancer (NSCLC) populations may be insufficient, particularly for multifocal, pneumonic-type, or advanced disease. Although surgery can provide favorable outcomes in localized disease, systemic therapy remains challenging, and the role of immunotherapy requires further clarification. Future progress will depend on integrated imaging-pathology-genomic models, prospective IMA-specific cohorts, and translational studies aimed at refining classification and developing individualized therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA)↗

Multiomics analysis reveals that senescent CXCL16+ macrophages promote lung adenocarcinoma progression through TGF-&#x3b2; signalling.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer and remains a leading cause of cancer-related mortality worldwide. Although, immunotherapy has become a cornerstone of first-line treatment, only 20-30% of patients achieve a durable clinical benefit, largely because of the complexity and heterogeneity of the tumour immune microenvironment. Emerging evidence indicates that cellular senescence, particularly within immune cells, contributes to tumour progression by impairing antitumour immunity; however, its mechanistic role in LUAD remains incompletely understood. METHODS: We performed an integrative multiomics analysis incorporating genome-wide association studies (GWASs), bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics to characterize immune heterogeneity in LUAD. Cellular senescence was validated by performing staining for senescence-associated &#x3b2;-galactosidase and the canonical markers p16 and p21. SHAP analysis was applied to evaluate the contribution of CXCL16+ macrophages. Functional roles were assessed using coculture assays, in vitro and in vivo tumour models, orthotopic tumour implantation, and multiplex immunofluorescence staining of clinical specimens. RESULTS: A summary data-based on Mendelian randomization analysis integrating GWAS and TCGA data identified CXCL16 as a senescence-associated gene that is causally linked to the LUAD risk. Single-cell RNA sequencing revealed that CXCL16 is predominantly expressed in macrophages, and the pseudotime analysis together with &#x3b2;-galactosidase staining confirmed its association with macrophage senescence. Spatial transcriptomics and immunofluorescence staining showed the marked enrichment of CXCL16+ macrophages in LUAD tissues. The cell-cell communication analysis further revealed a strong association between the number of CXCL16+ macrophages and the activation of the TGF-&#x3b2; signalling pathway within the tumour microenvironment. Functionally, CXCL16+ macrophages promoted LUAD progression via TGF-&#x3b2; signalling, as validated in vitro and in subcutaneous and orthotopic tumour models. Molecular dynamics simulations additionally suggested that LUAD patients with high levels of CXCL16+ macrophage infiltration may exhibit increased sensitivity to bosutinib. CONCLUSIONS: CXCL16 promotes macrophage senescence, and senescent CXCL16+ macrophages drive LUAD progression through TGF-&#x3b2; signalling. These findings identify CXCL16+ macrophages as a biologically and therapeutically relevant immune cell population, highlighting a potential target for precision intervention in LUAD.

Humans↗

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↗

FAP+ pericyte-like cells promote monocyte differentiation into tumor-associated macrophages in glioblastoma.

Glioblastoma (GBM) is a highly aggressive primary brain tumor characterized by profound immunosuppression that facilitates tumor progression and promotes therapeutic resistance. Fibroblast activation protein (FAP), a recognized theranostic target in multiple cancers, is upregulated in GBM and predominantly expressed by pericyte-like stromal cells. Here we identify a role for FAP&#x207a; pericyte-like cells in shaping the GBM immune microenvironment through monocyte recruitment and differentiation. Analysis of The Cancer Genome Atlas (TCGA) datasets, supported by reverse-transcription quantitative PCR and immunohistochemistry, revealed that elevated FAP expression-serving as a proxy for the abundance of FAP&#x207a; pericyte-like cells-is associated with an immune-enriched tumor microenvironment characterized by higher macrophage abundance and elevated expression of M2 polarization markers. Spatial analyses, including immunofluorescence and spatial transcriptomics, demonstrated that immunosuppressive macrophages preferentially localize in proximity to FAP&#x207a; pericytes. Single-cell RNA sequencing identified these FAP&#x207a; cells as a distinct perivascular stromal subset with a unique expression pattern of extracellular matrix components and cytokines, including CCL2 and CSF1, with corresponding receptors expressed on myeloid cells. Functional assays using patient-derived FAP&#x207a; pericyte-like cells confirmed their ability to attract monocytes via soluble mediators and to promote their differentiation and polarization into tumor-associated macrophages with immunoregulatory features, partly mediated by the CSF1-CSF1R axis. Orthotopic co-implantation experiments in mice further supported their capacity to enhance myeloid infiltration in vivo. Consistent with these biological effects, a transcriptional signature characteristic of FAP&#x207a; pericytes correlated with worse overall survival in patients with GBM. Together, these findings position FAP&#x207a; pericyte-like cells as modulators of the GBM immune landscape, fostering a tumor-permissive niche by promoting the differentiation of circulating monocytes into immunoregulatory macrophages. Targeting this stromal population may offer new therapeutic avenues to reprogram tumor-associated immune responses in GBM.

Journal Article↗

Unveiling tumor heterogeneity by single cell RNA-sequencing: From basic considerations to clinical applications.

Tumor heterogeneity-encompassing diverse cellular phenotypes, genomic alterations, and microenvironmental contexts-is a principal barrier to effective cancer therapy. Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve this complexity by capturing transcriptomes at single-cell resolution. Here, we review the technical foundations required for high-quality scRNA-seq studies. We then trace the evolution of scRNA-seq platforms from manual micromanipulation to high-throughput systems, and describe the computational pipelines that enable reliable data interpretation. The application of scRNA-seq is exemplarily shown in the context of lung cancer, where single-cell profiling has revealed (i) the clonal and sub-clonal architecture of tumors, (ii) extensive remodeling of the immune microenvironment, iii) key mechanisms underlying resistance to targeted agents and immune-checkpoint blockade, and (iv) the dynamics of neo-antigen-specific T-cell responses. Integrating machine-learning techniques-such as deep-learning classifiers and graph-based models-with single-cell transcriptomic data has markedly sped up biomarker discovery, produced more accurate risk-stratification scores, and enabled the generation of patient-specific therapeutic predictions. We surveyed the major trial registry ClinicalTrials.gov and identified &#x223c;380&#xa0;ongoing or completed studies that explicitly incorporate scRNA-seq as a correlative or pharmacodynamic endpoint. Overall, the analysis shows that scRNA-seq becomes an increasingly important component of modern trials, providing high-resolution cellular and molecular readouts that complement conventional imaging and bulk-omics endpoints. While key challenges remain, ranging from costs, scalability and need for rigorous validation before routine clinical deployment, ongoing technological advances continue to expand the potential of scRNA-seq as a cornerstone of precision medicine.

Humans↗

The correlation of DPM1 overexpression with immune infiltration and poor prognosis in hepatocellular carcinoma.

BACKGROUND: The DPM1 gene, crucial for glycosylation processes, has shown abnormal expression in various cancers, raising interest in its potential oncogenic role and as a biomarker in hepatocellular carcinoma (HCC). METHODS: Transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. DPM1 expression levels were compared between HCC tissues and adjacent normal tissues. Clinical correlations were assessed using statistical analyses, including survival analysis and multivariate Cox regression. Immune microenvironment profiling was conducted to evaluate associations between DPM1 expression and immune cell infiltration patterns. RESULTS: Elevated DPM1 levels were associated with advanced tumor stages (P&#x2009;<&#x2009;0.001), higher pathologic T stage (P&#x2009;<&#x2009;0.001), increased histologic grade (P&#x2009;<&#x2009;0.001), tumor positivity (P&#x2009;<&#x2009;0.001), tissue inflammation (P&#x2009;<&#x2009;0.001), and elevated alpha-fetoprotein levels (AFP&#x2009;>&#x2009;400 ng/mL, P&#x2009;<&#x2009;0.05). Multivariate Cox regression analysis identified DPM1 as an independent prognostic factor for reduced overall survival (HR&#x2009;=&#x2009;1.990, 95% CI 1.390-2.848). Immunological analysis revealed that DPM1 expression was positively correlated with T helper cells (R&#x2009;=&#x2009;0.268, P&#x2009;<&#x2009;0.001) and Th2 cells (R&#x2009;=&#x2009;0.295, P&#x2009;<&#x2009;0.001), and negatively correlated with plasmacytoid dendritic cells (R=-0.291, P&#x2009;<&#x2009;0.001) and cytotoxic cells (R=-0.284, P&#x2009;<&#x2009;0.001). CONCLUSIONS: DPM1 serves as a promising prognostic biomarker in HCC, with its expression correlating with unfavorable clinical outcomes and immune landscape alterations. Future studies should further validate DPM1's impact on ferroptosis and immune evasion in HCC, and explore its potential as a therapeutic target.

DPM1↗

Deep immune profiling of intrahepatic cholangiocarcinoma with CODEX multiplexed imaging.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) may be genomically subclassified by the presence of potentially actionable molecular aberrations, of which pathogenic alterations in isocitrate dehydrogenase (IDH)1 and fibroblast growth factor receptor (FGFR)2 are the most frequently observed. The impact of these molecular alterations on the tumor immune microenvironment remains incompletely understood. METHODS: We performed a high-parameter spatial immune phenotyping of iCCA samples with pathogenic FGFR2 or IDH1 alterations and FGFR2/IDH1 wild-type controls at the single-cell level using CO-Detection by indEXing. RESULTS: A total of 24 tumors were examined. Tumors with FGFR2 alterations were characterized by fewer CD8+ T cells and "M2-like" macrophages but higher levels of polymorphonuclear myeloid-derived suppressor cells as compared to FGFR2 wild-type tumors. Spatial relationships between polymorphonuclear myeloid-derived suppressor cells and multiple other cell types in the tumor microenvironment (including tumor cells, CD4+, and CD8+ T cells) were enriched in tumors with FGFR2 alterations. Tumors with IDH1 mutations had a trend toward more fibroblasts and were characterized by a closer proximity of tumor cells to CD4+ T cells, and between macrophages and multiple structural tumor microenvironment components as compared to other subtypes. CONCLUSIONS: iCCAs with pathogenic FGFR2 fusions/rearrangements and IDH1 mutations have distinct immunophenotypes. Tailoring immunotherapeutic approaches to specific molecular subsets could improve treatment outcomes across the divergent molecularly defined iCCA subtypes.

Humans↗

Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.

Hepatocellular carcinoma (HCC)↗

Immune landscape and novel therapeutic targets of epidermal growth factor receptor and anaplastic lymphoma kinase wild type never-smoker lung adenocarcinoma.

BACKGROUND: Never-smoker lung adenocarcinoma (NSLA) exhibits distinct immunosuppressive profiles and a lower tumor mutation burden compared with lung adenocarcinoma in smokers. These correlate with poor responses to immune checkpoint inhibitors. In this study, we aimed to elucidate the tumor-immune microenvironment of NSLA without epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) alterations and identify novel therapeutic targets. METHODS: We analyzed genome, transcriptome, and proteomic data from 102 NSLA tumor samples and 16 normal adjacent tissues. We classified tumors into distinct immune clusters (IC) based on gene signatures by profiling the tumor-infiltrating immune cells. RESULTS: The tumors were stratified into three ICs: hot, intermediate, and cold. Notably, only 21 (20.6%) patients exhibited hot IC enriched in cytotoxic T cells, natural killer cells, and B-cell signatures, which correlated with improved recurrence-free survival. Cold ICs (37.3%) exhibited higher myeloid-derived suppressor cell (MDSC) levels and M2 macrophage signatures, with poor immune cell infiltration and relatively low stimulatory cytokines and chemokines expression. CEACAM1, and NECTIN2 were upregulated in intermediate and cold ICs and correlated with MDSC and M2 macrophage infiltration. High expression of these genes was associated with poor survival outcomes. Protein-protein network analysis of 20 upregulated molecules associated with cancer- and driver-related proteins in cold IC identified XPO 1 as a key component. CONCLUSION: Our proteogenomic analysis highlighted the immunosuppressive properties of NSLA without EGFR and ALK alterations and identified novel therapeutic targets. These findings may provide novel treatment strategies that could improve the clinical outcomes of patients with NSLA.

Humans↗

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

The neuro-immune network. Some recent developments.

Neuroimmunomodulation encompasses, by definition, numerous components and activities primarily derived from the immune system, and treats the immunoneuroendocrine interconnections at different levels of the integrated whole functioning organism. The arbitrary unit of the immunoneuroendocrine network is the immune microenvironment composed of lymphocytes, neurons, endocrine cells, nonlymphoid accessory cells, humoral factors from immune, nervous, endocrine and other tissues, receptors for endogenous and exogenous ligands, pathways for transduction of biological signals, physiological ions, various magnetic and electromagnetic compartments, and impulses from the higher nervous activity (the mind, the psyche). The neuroimmunomodulation is a marvelous mechanism from which arises an amazing quantity of variables and intercommunications in the living organism. Being a multidisciplinary science par excellence, neuroimmunomodulation is strongly antidogmatic and favors multidirectional organization of research. That means that actions of the immune, nervous and endocrine systems should be studied together in terms of intercommunications among identifiable structures and processes. Therefore, research endeavors in neuroimmunomodulation have different directions with seminal discoveries much too numerous to list here. This mini-review is confined to some recent findings dealing with the immunomodulatory activity of micromagnetic fields when applied to the brain, the humoral and cell-mediated components of certain neurological and psychiatric diseases, the autoimmune features in heroin addicts in relation to dementia and HIV infection, the neuroimmunobiology of lithium cation, and the in vivo immune function of enkephalins, and methionine-enkephalin in particular.

Animals↗

HLA class I expression and tumor immune infiltration together shape colon cancer immune contexture.

BACKGROUND: The relative contribution of HLA class I molecules-including classical HLA class Ia (HLA-A, -B, -C) and non-classical HLA class Ib (HLA-E, -F, -G)-to shaping the tumor immune microenvironment in colon cancer remains insufficiently defined. We investigated how their expression patterns relate to immune infiltration and clinical outcome. METHODS: In a retrospective cohort of 280 colon cancers, we assessed HLA class Ia and class Ib expression and quantified CD45-positive immune cell infiltration by immunohistochemistry. These features were correlated with clinicopathological variables, microsatellite instability (MSI) status, and previously established genomic immune signatures. RESULTS: High HLA class Ia expression and increased CD45-positive cell infiltration were each associated with improved overall, disease-specific, and progression-free survival. CD45-positive density correlated strongly with Immunologic Constant of Rejection scores. HLA class Ia loss was more frequent in advanced stages and in MSI-H tumors. Among HLA class Ib molecules, only HLA-E expression was associated with favorable disease-specific and progression-free survival. Integrative analysis identified three immune phenotypes with distinct prognostic profiles; tumors characterized by high HLA class Ia expression, low HLA class Ib expression, and high CD45-positive infiltration had the best outcomes. CONCLUSION: Colon cancer immunogenicity is shaped by coordinated patterns of HLA class I expression and immune infiltration. Integrating HLA class Ia/Ib expression with immune cell density provides a refined stratification of tumor immune phenotypes and may support personalized immunotherapeutic decision-making.

Antigen presentation↗

Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer.

BACKGROUND: Triaptosis is a recently characterized form of programmed cell death with unclear implications in cancer. This study aimed to investigate the prognostic significance and biological relevance of triaptosis in gastric cancer (GC). METHODS: Transcriptomic and clinical data from TCGA-STAD and GSE62254, and single-cell RNA sequencing data from GSE183904 were analyzed. Triaptosis-related gene (TRG) scores were calculated using single-sample gene set enrichment analysis. Differentially expressed genes identified in TRG-score and GC-versus-normal comparisons underwent functional enrichment, Cox regression, and least absolute shrinkage and selection operator regression to develop an externally validated signature. Immune profiles, pathway activity, somatic mutations, tumor mutational burden (TMB), predicted drug sensitivity, and clinical features were compared by risk group. Single-cell analyses assessed TRG activity, prognostic gene expression, cell-cell communication, and pseudotime. Reverse transcription-quantitative PCR and Western blotting assessed mRNA expression and protein levels, respectively. RESULTS: A TRG-based prognostic model comprising ASPN, GRB14, and VTN was developed and externally validated, effectively distinguishing patients into two distinct risk groups with notably different survival outcomes. mRNA expression of all three genes and their protein levels were significantly higher in SGC-7901 cells than in GES-1 cells. High-risk patients had higher stromal scores and distinct immune profiles; 15 immune cell types differed between groups. Single-cell analysis revealed fibroblasts and pericytes among high-TRG-active cell types. Prognostic genes were significantly overexpressed in fibroblasts, which also showed high TRG activity. Fibroblasts demonstrated enhanced communication with pericytes, whereas tumor-derived fibroblasts showed weaker communication with macrophages, indicating immune microenvironment remodeling. CONCLUSION: The three-gene prognostic signature predicted GC prognosis and was associated with distinct immune and genomic features, suggesting potential value for risk stratification and personalized treatment.

Humans↗

Multi-Omics Integration Identifies a Five-Gene Metabolic Signature With Experimental Validation in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is hallmarked by profound metabolic reprogramming; however, its intricate crosstalk with the tumor immune microenvironment (TIME) and its clinical ramifications remain inadequately elucidated. This study aims to systematically decipher the metabolic-immune interplay in ccRCC through multi-omics integration, with the goal of identifying robust prognostic biomarkers and actionable therapeutic vulnerabilities. AIMS: This study aims to systematically decipher the metabolic-immune interplay in clear cell renal cell carcinoma (ccRCC) through multi&#x2011;omics integration, and to identify robust prognostic biomarkers and actionable therapeutic vulnerabilities that can inform precision risk stratification and individualized treatment strategies. METHODS: We integrated bulk transcriptomic, genomic, and clinical data from multiple ccRCC cohorts. Differential expression and functional enrichment analyses were performed to characterize metabolic pathway alterations. Mendelian randomization (MR) was employed to infer causal relationships between metabolic disorders and ccRCC risk. A machine learning-based prognostic framework, incorporating SHAP (SHapley Additive exPlanations) for feature interpretability, was constructed and rigorously validated. TIME heterogeneity was dissected using deconvolution algorithms, while drug sensitivity, tumor mutation burden (TMB), and TIDE scores were utilized to assess therapeutic responses and immune evasion. Candidate gene function was evaluated through in&#xa0;vitro gain- and loss-of-function assays, with expression validated via TCGA, HPA, western blot, and qRT-PCR. RESULTS: Enrichment analysis identified coordinated dysregulation in lipid metabolism, energy homeostasis, and hypoxia response pathways. MR analysis confirmed lipid metabolism disorders as a causal risk factor for ccRCC. Our machine-learning model, centered on five core SHAP-identified features (SUCLA2, ACAT1, PC, SUCLG1, and HMGCS2), demonstrated superior predictive accuracy over conventional clinical staging. Immune profiling unveiled dichotomous TIME states: the low-risk group retained active immune surveillance, whereas the high-risk group was enriched with immunosuppressive subsets. Drug sensitivity screening pinpointed LY2109761 and carmustine as high-risk-specific candidate agents. Furthermore, TMB and TIDE analyses stratified high-risk patients displaying genomic instability and immune evasion phenotypes. Functionally, SUCLA2 knockdown significantly enhanced ccRCC cell proliferation and invasion, while its overexpression suppressed these malignant phenotypes, corroborating its tumor-suppressive role. Expression patterns of the hub genes were consistently validated across multi-level datasets and experimental assays. CONCLUSION: This study establishes a precision oncology framework for ccRCC by functionally linking metabolic biomarkers, immunophenotypes, and stratified therapeutic strategies. Importantly, we identify SUCLA2 as a potential functional tumor suppressor and a promising target for further mechanistic and translational investigation.

Humans↗