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PubMed2025

Prognostic and immunological implications of sialylation-associated gene signatures in hepatocellular carcinoma.

OBJECTIVE: The absence of effective biomarkers continues to limit early diagnostic accuracy and prognostic evaluation in patients with hepatocellular carcinoma (HCC). Aberrant sialylation (SI) has been demonstrated to contribute to therapeutic resistance and tumor progression. The aim of this investigation was to identify a sialylation-related gene (SRG) signature, evaluate its prognostic significance, and investigate associated immunological characteristics in HCC. METHODS: Transcriptomic profiles and corresponding clinical data for patients with HCC were obtained from UCSC Xena, the International Cancer Genome Consortium (ICGC), and the Molecular Signatures Database (MsigDB). Differential expression analysis, Cox regression analysis modeling, and least absolute shrinkage and selection operator (LASSO) regression analysis were applied to identify independent prognostic markers and develop predictive models. The tumor immune microenvironment and its relationship with the identified SRGs were assessed by evaluating immune infiltration patterns. A gene co-expression network for the prognostic SRGs was constructed using GeneMANIA to identify potentially targetable signaling pathways. RESULTS: Four SRGs (ST6GALNAC4, B4GALT5, B4GALNT1, and NEU1) were significantly associated with the prognosis of patients with HCC. Prognostic models constructed using these genes demonstrated strong predictive performance. Notable differences were observed in immune cell populations and immune checkpoint expression between the high-risk and low-risk groups. Additionally, the half-maximal inhibitory concentration values for 101 therapeutic compounds varied between these groups. Lipopolysaccharide and sphingolipid metabolism were identified as key biological processes linked to tumor progression and modulation of the immune microenvironment. CONCLUSION: The four identified SRGs were significantly associated with clinical outcomes and immunological features in HCC. These findings provide a foundation for advancing early diagnostic strategies, refining prognostic assessments, and guiding personalized therapeutic approaches for patients with HCC.

Humans↗

PubMed2026

Development and internal validation of a six-gene prognostic model based on galactose metabolism for overall survival in lung adenocarcinoma.

BACKGROUND: Lung cancer remains a leading cause of cancer incidence and mortality globally. Metabolic reprogramming promotes tumor progression and shapes an immunosuppressive tumor microenvironment. Galactose metabolism is involved in multiple malignancies, but its prognostic value in lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop and internally validate a galactose metabolism-related multigene prognostic model for LUAD. METHODS: A retrospective prognostic model development and internal validation study was performed using RNA sequencing (RNA-seq) and clinical data from 585 LUAD patients in The Cancer Genome Atlas (TCGA). Differential expression, functional enrichment, univariate and multivariate Cox regression were applied to construct a prognostic gene signature. Internal validation was performed using bootstrap resampling. Model performance was evaluated by time-dependent receiver operating characteristic (ROC), C-index, calibration, and Kaplan-Meier analysis. Associations between the model and immune infiltration, immunotherapy responsiveness, and tumor stemness were also analyzed. RESULTS: A six-gene prognostic model (GALT, GANC, PGM1, GALM, B4GALT1, PGM2) was developed. The model showed good discrimination with 1-, 3-, and 5-year area under the curve (AUC) values of 0.719, 0.693, and 0.684, respectively. The low-risk group exhibited significantly longer survival, increased antitumor immune infiltration (CD8+ T cells, M1 macrophages, activated CD4+ memory T cells), higher expression of T cell proliferation-related genes, lower immune checkpoint expression, better predicted immunotherapy response, and lower tumor stemness compared with the high-risk group. CONCLUSIONS: We developed and internally validated a six-gene prognostic model for LUAD based on galactose metabolism. The model shows moderate prognostic performance and is associated with antitumor immunity and tumor stemness. It may be used for prognostic risk stratification and to guide personalized immunotherapy in LUAD.

Galactose metabolism↗

PubMed2026

Loss of XRCC1 promotes cGAS/STING mediated innate immune signaling in gastric cancer.

BACKGROUND: One of the most defining features of gastric cancer (GC) is harboring deficiency in DNA repair that subsequently contributes to carcinogenesis. The X-ray repair cross complementing 1 (XRCC1) protein is a key molecular scaffold required for efficient repair of DNA single-strand breaks (SSBs) to maintain genomic stability. However, further investigation is needed to uncover the role of XRCC1 in innate immune signaling and inflammation in GC. METHODS: We evaluated how loss of XRCC1 leads to accumulation of cytosolic DNA using immunofluorescence localization assay and measuring DNA from cytosolic extract. We applied ON-TARGETplus™ SMARTpool siRNAs to knockdown XRCC1 in gastric cell lines and examined the innate immune siganling and inflammation with and without ATM inhibitor treatment. Further, we examined Type I interferon gene expression in various gastric cancer cell lines and assessed its role in cGAS-STING signaling using RT-qPCR, RNA-Seq, and immunoblot analysis. In addition, we generated conditional knockout XRCC1 mice and characterized the innate immune signaling from stomach tissue extract using RT-qPCR, western blot. Further, the DNA damage and histological analysis was done by immunohistochemistry. RESULTS: In this work, we examined the role of XRCC1 in modulating the innate immune signaling axis via cGAS/STING pathway. We find that XRCC1 deficient gastric cancer cell lines and mouse stomach tissue shows activation of cGAS/STING signaling. Further, ATM inhibition enhances robust cGAS/STING mediate innate immune signaling and PD-L1 expression in XRCC1 deficient gastric cancer cells. CONCLUSIONS: Results from this work demonstrate that XRCC1 is essential to maintain innate immune homeostasis. Further, this work suggest that ATM inhibitors may provide a potential therapeutic strategy to enhance the PD-L1 expression that could increase the efficacy of an immune checkpoint blockade (ICB) in XRCC1 deficient or low expressing GC.

X-ray Repair Cross Complementing Protein 1↗

PubMed2026

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) with anti-angiogenic agents is the preferred first-line therapy option for patients with advanced hepatocellular carcinoma (HCC), yet only a subset of patients responds, urging the quest for prediction biomarkers. We aimed to integrate genomics with radiology to propose an immune-derived radiogenomics biomarker of response to such combination immunotherapy and evaluate its added value in clinical context. METHODS: We integrated bulk RNA sequencing (RNA-seq) and proteomics data of 994 HCC patients with single-cell RNA-seq data of 11 samples across multiple datasets to identify an immune-related signature (IRS) that may influence sensitivity or resistance to such combined immunotherapy strategy, followed by verification of selected marker genes using immunohistochemistry and cytological experiments. We then trained/validated a cross-modality radiogenomics biomarker using machine learning based on TCIA database that was further tested in multi-scale independent cohorts covering 754 HCC patients. RESULTS: Integrative multi-omics analysis identifed a parsimonious 2-gene prognostic signature including KPNA2 and SMG5 that was significantly associated with immune heterogeneity and response to combination immunotherapy. Machine-learning pipeline exported the optimal 4-feature radiogenomics biomarker using support vector machine that significantly discriminated prognosis (hazard ratio 1.415–1.890; p < 0.05 for all) and modestly predicted response to ICI plus anti-angiogenic therapy (area under the curve 0.720–0.829) in independent retrospective series across major imaging modalities (computed tomography/magnetic resonance imaging). In a prospective neoadjuvant cohort, this biomarker also showed favorable performance for predicting pathological response and tumor recurrence, accompanied by biological validation through single-cell RNA-seq analysis of pre-treatment biopsies. CONCLUSIONS: Our study provides a cross-device-cross-modal radiogenomics biomarker that can improve patient selection for emerging ICI plus anti-angiogenic therapy with novel potential therapeutic targets in HCC.

Humans↗

PubMed2026

Pan-cancer single-cell atlas of immunotherapy response identifies ZNF385A as a regulator of immune evasion in small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of solid tumors, response rates in patients with small cell lung cancer (SCLC) remain limited, and acquired resistance is highly prevalent. The underlying mechanisms of this immunotherapy resistance remain to be fully elucidated. Clinically, SCLC typically manifests as an "immune-cold" tumor, characterized by a low abundance of CD8+ T cell infiltration and the rare formation of tertiary lymphoid structures (TLS). While DNA damage repair (DDR) is closely linked to innate immune responses, how DDR networks orchestrate the SCLC immune microenvironment remains obscure. In this study, we integrated single-cell transcriptomic data (comprising 344,447 high-quality cells) from six cancer types (BCC, CRC, HCC, HNSCC, iCCA, and SCLC). Our comparative analysis revealed a fundamental depletion of TLS-associated cellular subpopulations (e.g., CXCL13+ CD8+ T cells, HLA-DRB5+ B cells, and CXCL9+ dendritic cells) in SCLC, which was significantly correlated with aberrant DDR activity. Through high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified ZNF385A as the core hub gene within the DDR-associated module. ZNF385A is highly expressed in SCLC and is associated with poorer prognosis. In vitro, ZNF385A depletion suppressed SCLC cell proliferation and induced apoptosis, accompanied by R-loop accumulation and activation of cGAS-STING signaling, indicating a potential link between ZNF385A, genomic stability and tumor-intrinsic innate immune signaling. Collectively, these findings identify ZNF385A as a potential regulator associated with TLS deficiency and immune evasion in SCLC.

Immunotherapy resistance↗

PubMed2026

Therapy induced senescence promotes immunogenicity in acute myeloid Leukemia through reduced EZH2 activity.

Chemotherapy resistance and disease relapse are major determinants of treatment failure in acute myeloid leukemia (AML). Therapy-induced senescence (TIS) is one outcome of chemotherapy, but its immunological consequences in AML remain unclear. Here we show that ex vivo chemotherapy induces senescence in a subset of therapy-naïve AML samples. TIS is marked by elevated interferon signaling, upregulation of human leukocyte antigen (HLA) class I and II molecules, and increased presentation of leukemia- and senescence-associated peptides, conferring AML cells antigen-presenting cell-like features. These changes enhance autologous CD4+ and CD8+ T cell responses against AML, both ex vivo and in patient-derived xenograft models. TIS also restores AML sensitivity to immune checkpoint blockade therapy. Mechanistically, we identify reduced Polycomb Repressive Complex 2 (PRC2) activity as central to TIS induction and its immunogenicity. PRC2 inhibition reactivates senescence-related genes and HLA expression in non-senescent AML cells, enabling T cell activation. These findings uncover a senescence-driven immune mechanism with potential to improve therapy outcomes in AML.

Humans↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Immune-Like Malignant Epithelial Programs Shape Tumor-Immune Interactions and Inform Prognostic Stratification in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is characterized by marked cellular heterogeneity, yet how malignant epithelial states contribute to immune regulation and clinical outcomes remains incompletely defined. We integrated single-cell RNA-sequencing data to map the cellular landscape of LUAD and identify malignant epithelial cells based on inferred copy-number alterations. Epithelial states were further examined through trajectory inference, transcription factor analysis, and cell-cell communication profiling. Single-cell-derived genes were subsequently integrated with TCGA and independent GEO cohorts to construct and validate a machine learning-based prognostic signature. Malignant epithelial cells displayed distinct functional programs, including an immune-like state associated with genomic instability, immune-related transcriptional activity, tumor-immune communication, and patient outcomes. The resulting immune-like malignant epithelial cell signature (IMEC-Sig) consistently stratified survival across multiple cohorts. Low IMEC-Sig scores were accompanied by greater immune infiltration, higher immune checkpoint expression, and increased immunophenoscore, whereas high scores were linked to a comparatively immunosuppressive phenotype. Pan-cancer analyses further identified KRT8 as a gene associated with unfavorable prognosis, and functional experiments showed that KRT8 silencing suppressed proliferation, migration, invasion, and colony formation in LUAD cells. Together, these findings connect malignant epithelial heterogeneity with the immune context and clinical outcomes, support IMEC-Sig as a biologically informed prognostic tool, and nominate KRT8 as a potential therapeutic target in LUAD.

Humans↗

PubMed2026

Intratumoral PD-1+LAG-3+CD8+ T cells are associated with improved prognosis in gastric cancer.

PURPOSE: PD-1 and LAG-3 are frequently used as markers of T cell exhaustion, yet the prognostic relevance and phenotypic characteristics of PD-1+LAG-3+CD8+ T cells in gastric cancer (GC) remain poorly defined. This study aimed to investigate their association with clinical outcomes and characterize their immune characteristics across independent GC cohorts. METHODS: Four independent GC cohorts were analyzed: the Zhongshan Hospital cohort (ZSGC, n = 298), The Cancer Genome Atlas cohort (TCGA, n = 371), an Immune Checkpoint Blockade cohort (ICB, n = 45), and the Yonsei cohort (n = 433). Intratumoral PD-1+LAG-3+CD8+ T cell infiltration was quantified by immunofluorescence staining and transcriptomic gene signature scoring. Survival analysis was performed using Kaplan-Meier estimation and multivariate Cox regression. Functional characterization was performed by flow cytometry on resected GC tissue. The immune microenvironment composition was evaluated using computational analyses. RESULTS: PD-1+LAG-3+CD8+ T cells were enriched within tumors compared to adjacent normal mucosa, and their infiltration correlated with advanced tumor stage, poor differentiation, microsatellite instability, and Epstein-Barr virus (EBV)-positive molecular subtypes. High intratumoral infiltration was significantly associated with improved overall survival in both the ZSGC and TCGA cohorts, whereas single-positive PD-1+CD8+ or LAG-3+CD8+ T cells showed no such association. In the ICB cohort, higher infiltration was associated with a higher response rate to pembrolizumab. Intratumoral PD-1+LAG-3+CD8+ T cells exhibit an activated phenotype characterized by increased expression of CD137, IFN-γ, perforin, and CXCL13, along with elevated TCF7 and lower PD-1 levels, suggesting a tumor-reactive, pre-exhausted state. High infiltration was further associated with an immune-active tumor microenvironment. CONCLUSIONS: High intratumoral infiltration of PD-1+LAG-3+CD8+ T cells is associated with favorable prognosis and an immune-active microenvironment in GC. These cells display phenotypic features consistent with a pre-exhausted state and may serve as independent prognostic biomarkers and candidate predictive biomarkers for immunotherapy stratification.

Humans↗

PubMed2026

The fall of the genome protectors triad: PBRM1, SETD2, and BAP1's impact on metabolism and immunity in clear cell renal cell carcinoma.

The loss of chromosome 3p and the inactivation of the tumor suppressor gene von Hippel-Lindau (VHL) were identified in clear cell renal cell carcinomas (ccRCC) over three decades ago. Since then, mutations in genes for the three chromatin modulators, polybromo 1 (PBRM1), SET domain-containing 2 (SETD2), and BRCA1-associated protein-1 (BAP1), have been recognized as common in ccRCC. Although these genomic alterations are central to understanding ccRCC's development, other deregulated cellular processes are also prominent in these tumors. Metabolic reprogramming is a key hallmark of this disease, characterized by various changes linked to the stabilization of hypoxia-inducible factors (HIF), including increased aerobic glycolysis, elevated lipid levels, and glutamine dependence for cell survival. Additionally, HIF-α stabilization plays a crucial role in regulating the immune system, thereby enhancing CD8+ T lymphocyte cytotoxicity. Immune checkpoint inhibitors (ICI) are now used as first-line treatments to target the often highly infiltrated tumor microenvironment of ccRCC. However, the effectiveness of ICI varies and is difficult to predict. Although emerging studies are beginning to provide insight, evidence suggests roles for PBRM1, SETD2, and BAP1 in metabolic regulation and in shaping the tumor immune microenvironment in ccRCC. Here, we review recent advances in this field and examine their impact on the management of ccRCC.

BAP1↗

PubMed2026

Expression of PIEZO1 in lung adenocarcinoma correlates with PD-L1 expression, cell migration, and poor prognosis: an exploratory study.

BACKGROUND AND AIMS: Lung adenocarcinoma (LUAD) treatment is challenging process. and the function of PIEZO1, a mechanically sensitive ion channel has not been systematically determined. In this study we aimed to explore the expression, potential associations, and clinical significance of PIEZO1 in LUAD. METHODS AND AIMS: A comprehensive bioinformatics analysis was performed using data from the Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus (GEO) database and other databases. Experimental validation was performed to confirm the expression patterns and preliminarily examine the associations of PIEZO1 in LUAD cell lines. RESULTS: PIEZO1 expression was significantly lower in LUAD tissues than in normal lung tissues (P < 0.05). Its expression was correlated with advanced pathological stage, lymph node involvement, and distant metastasis. High PIEZO1 expression was associated with a distinct immune-related tumor microenvironment, characterized by correlations with the expression levels of multiple immune checkpoint molecules, and was identified as an independent factor associated with poor overall survival (HR = 1.49; 95% CI 1.11-2; P < 0.007). In vitro experiments confirmed the downregulated PIEZO1 expression in LUAD cell lines, and functional knockdown experiments revealed its association with cell migration and PD-L1 expression. CONCLUSION: This exploratory study revealed that PIEZO1 expression in LUAD cell lines correlated with the expression of immune-related features and EMT-related genes, as well as poor prognosis. In vitro, PIEZO1 knockdown is associated with reduced cell migration and decreased PD-L1 expression. These findings provide a basis for future investigations into the potential role of PIEZO1 in LUAD.

Gene expression↗

PubMed2026

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↗

PubMed2026

Cancer Immune Responsiveness and MHC Class I Antigen Presentation: Mechanisms of Immune Escape and Immunotherapy Resistance in Gastrointestinal Cancers.

The Antigen Processing and Presentation Machinery (APM) is essential for immune surveillance by enabling the presentation of antigenic peptides to T lymphocytes and facilitating the elimination of infected or transformed cells. In cancer, the integrity of this process influences cancer immune responsiveness (CIR), defined as a tumour's capacity to be recognised by the immune system and respond to immunotherapy. Tumours with intact antigen presentation pathways are more likely to generate effective antitumour responses, whereas APM defects promote immune escape and therapeutic resistance. Cancer cells frequently evade immune detection through altered antigen processing or reduced expression of major histocompatibility complex (MHC) class I molecules, limiting tumour antigen presentation to cytotoxic T lymphocytes. These alterations are increasingly recognised as determinants of response to immune checkpoint inhibitors and potential predictive biomarkers. APM defects may be reversible or irreversible. Interferon-mediated signalling can restore MHC class I expression and T-cell cytotoxicity in some tumours, whereas permanent genomic alterations affecting human leukocyte antigen (HLA) class I genes, β2-microglobulin (β2-m), or interferon-γ (IFN-γ) pathway components can severely impair antigen presentation. Emerging evidence highlights four mechanistic levels of APM perturbation: peptide generation, peptide loading, MHC class I integrity, and epigenetic regulation. Each contributes to distinct patterns of immune evasion. This review examines how MHC class I alterations influence CIR and contribute to immune evasion and immunotherapy resistance in gastrointestinal malignancies, while discussing therapeutic strategies to restore or bypass APM deficiencies.

Humans↗

PubMed2026

Age and sex: dual drivers remodeling the anti-tumor immune microenvironment and shaping personalized immuno-oncology.

Despite breakthrough advancements in cancer immunotherapy, significant inter-individual heterogeneity in clinical outcomes persists, bringing the regulatory roles of intrinsic host biological variables into sharp focus. Accumulating fundamental and clinical evidence indicates that age and sex play crucial roles in determining tumor susceptibility, disease progression, and the remodeling of the anti-tumor immune microenvironment. This review systematically delineates the profound impacts of the dual dimensions of age and sex on anti-tumor immune responses and immune evasion mechanisms. In the dimension of age, this article outlines the progressive functional decline of T/B lymphocytes and innate immune subsets driven by immunosenescence, and emphatically reveals how inflammaging and its associated senescence-associated secretory phenotype (SASP) orchestrate the formation of an immunosuppressive tumor microenvironment. In the dimension of sex, we deeply explore four core mechanisms comprising sex chromosome genomics (e.g., escape from X-chromosome inactivation and loss of Y chromosome), sex hormone networks, microenvironmental metabolic reprogramming, and the host gut microbiome, elucidating the molecular basis driving the disparities in innate and adaptive immunity between males and females. In summary, thoroughly deciphering the complex immune regulatory networks driven by age and sex not only helps elucidate the disparities in efficacy and toxicity observed in patients undergoing immune checkpoint inhibitors, but also provides crucial theoretical foundations and translational insights for the future development of "age-tailored" and "sex-specific" strategies in personalized immuno-oncology.

Humans↗

PubMed2026

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)↗

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

The role of Epstein-Barr virus in NK/T cell lymphoproliferative disorders: molecular mechanisms and potential therapeutic strategies.

Epstein-Barr virus (EBV) is a widely prevalent lymphotropic γ-herpesvirus, with approximately 95% of the population showing evidence of infection at some point during their lifetime. While most infections are asymptomatic or follow a self-limiting clinical course, in certain populations, EBV can lead to a range of lymphoproliferative disorders (LPDs), particularly subtypes originating from T cells and natural killer (NK) cells, which are often characterized by highly aggressive disease progression. This review aims to systematically discuss the molecular basis of EBV infection, covering its viral biological properties, regulation of the latent and lytic cycles, key viral protein functions (e.g., LMP1, LMP2A, EBNA1), miRNA regulatory mechanisms, and the activation of various host signaling pathways (such as NF-κB, PI3K-AKT, JAK-STAT) that contribute to the maintenance of latent infection, cell transformation, and immune evasion. Additionally, the review focuses on the pathogenic contributions of these mechanisms in EBV-related T/NK cell lymphoproliferative diseases. Research highlights include the in-depth analysis of virus-host genome interaction mechanisms, the identification of novel molecular biomarkers, and the development of targeted therapeutic strategies (e.g., PD-1/PD-L1 immune checkpoint inhibitors, EBV-specific T cell therapy). Through this comprehensive review, it is hoped that personalized medicine and artificial intelligence-assisted multimodal decision-making will be applied to the precise prevention and treatment of EBV-related diseases.

Humans↗

PubMed2026

Plasma cell-CD8+ T cell co-enrichment distinguishes immunotherapy-responsive hepatocellular carcinoma subtypes.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterised by significant racial disparities in incidence and outcomes, yet whether these reflect distinct tumour biology or differential distribution of molecular subtypes among immunotherapy patients remains unclear. METHODS: We characterised molecular heterogeneity among 46 patients with HCC of differing background population from the NCI-CLARITY cohort receiving immune checkpoint inhibitor therapy, using transcriptomic and genomic profiling, with validation across multiple independent cohorts. RESULTS: Differential expression analysis comparing African American versus non-African American patients identified 126 genes, of which 55 demonstrated tumour-specific expression across independent validation cohorts with paired tumour-normal samples. Consensus clustering revealed two molecular subtypes with no significant race association, indicating these clusters capture tumour-intrinsic biology rather than ancestry. The genomic landscape showed minimal differences between subtypes. A prognostic signature derived from these expression profiles demonstrated significant risk stratification in the NCI-CLARITY cohort and TCGA-LIHC, but not in Asian cohorts, suggesting population-specific applicability. Immune deconvolution revealed that the two subtypes represent distinct immune microenvironments: one subtype exhibited markedly elevated plasma cell infiltration with strong plasma cell-CD8+T cell correlation suggesting coordinated adaptive immunity, along with elevated tertiary lymphoid structure signatures. The other subtype showed regulatory T cell-macrophage correlation and enrichment for immune-excluded phenotypes. The immune-enriched subtype trended towards higher immunotherapy response rates. CONCLUSIONS: Molecular heterogeneity in HCC reveals distinct tumour-immune ecosystems that transcend racial classification. Tumour immune heterogeneity in HCC reflects distinct molecular patterns, with immune hot tumours characterised by elevated tertiary lymphoid structure signatures and enriched plasma cell and CD8+T cells. These patterns may serve as prognostic biomarkers for immunotherapy patient stratification and demonstrate the value of diverse cohort representation in identifying clinically relevant therapeutic targets.

Gastrointestinal Cancer↗