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PubMed2025

Digital Immunophenotyping of Lung Atypical Carcinoids and Large Cell Neuroendocrine Carcinomas Identifies Three Subtypes With Specific Tumor-Immune Microenvironment Features.

Atypical carcinoids (ACs) and large cell neuroendocrine carcinomas (LCNECs) are defined by the WHO as intermediate- and high-grade lung neuroendocrine neoplasms, respectively, based on morphological criteria; however, treatment strategies remain debated. Given the emerging role of the tumor microenvironment (TME) and tumor-infiltrating lymphocytes (TILs) in cancer prognosis and therapy response, this study aimed to characterize the immune landscape of ACs and LCNECs comprehensively. Immunohistochemistry for T-cell markers (CD3, CD8), immune checkpoints (PD-1, PD-L1), HLA molecules (HLA-DR, HLA-I), and fibroblasts (α-SMA) was performed on a re-evaluated cohort of 56 ACs and 104 LCNECs. Digital image analysis quantified intra-tumor (iTILs) and stromal (sTILs) CD3 and CD8 TILs in the whole slide and in specific tumor regions (invasive margin [IM] and central tumor [CT]). LCNECs exhibited significantly higher stromal T-cell infiltration, immune checkpoint expression, and HLA compared to ACs (p < 0.001), while α-SMA was more prominent in ACs. No ACs showed PD-L1 tumor expression. Digital quantification confirmed greater iTILs and sTILs in LCNECs across all regions, with moderate concordance to manual counts. Interestingly, TIL parameters were higher at the IM than in the CT (p < 0.001). Using Boruta feature selection algorithm, Principal Component Analysis and Hierarchical Clustering, three patient clusters were identified: Cluster 1 (mainly ACs, low TILs, favorable prognosis), Cluster 2 (mixed histology, intermediate TILs, moderate prognosis), and Cluster 3 (mostly LCNECs, high TILs, poor prognosis), with distinct TME marker profiles. PD-L1 tumor expression was strongly linked to Cluster 3. These findings suggest that ACs and LCNECs may be stratified into three distinct immune clusters, highlighting the heterogeneity of their tumor microenvironment and providing a rationale for further translational studies.

Humans↗

PubMed2025

Spatial-Temporal Diversity of Extrachromosomal DNA Shapes Urothelial Carcinoma Evolution and Tumor-Immune Microenvironment.

Extrachromosomal DNA (ecDNA) presents a promising target for cancer therapy; however, its spatial-temporal diversity and influence on tumor evolution and the immune microenvironment remain largely unclear. We apply computational methods to analyze ecDNA from whole-genome sequencing data of 595 urothelial carcinoma (UC) patients. We demonstrate that ecDNA drives clonal evolution through structural rearrangements during malignant transformation and recurrence of UC. This supports a model wherein tumors evolve via the selective expansion of ecDNA-bearing cells. Through multi-regional sampling of tumors, we demonstrate that ecDNA contributes to the evolution of multifocality and increased intratumoral heterogeneity. EcDNA is present in 36% of UC tumors and correlates with an immunosuppressive phenotype and poor prognosis. Single-cell RNA sequencing analyses reveal that ecDNA+ malignant cells exhibit diminished expression of major histocompatibility complex class I molecules, enabling them to evade T-cell immunity. Finally, we show that sequencing of urinary sediment-derived DNA has excellent specificity in detecting ecDNA.

Journal Article↗

PubMed2025

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↗

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↗

PubMed2025

Spatially organized lymphocytic microenvironments in high grade primary prostate tumors.

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

Prostate cancer↗

PubMed2025

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↗

PubMed2026

A pancreatic cancer organoid-macrophage co-culture using starPEG-heparin hydrogel deciphers tumor-immune cell interactions.

Macrophages are among the most abundant immune cells in the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) and play a key role in regulating the immunosuppressive niche that facilitates tumor growth. Although recent three-dimensional (3D) culture systems using patient-derived materials have advanced our understanding of tumor biology, most models lack key cellular TME components and thus fail to capture tumor-immune cell interactions. To address this gap, we developed an in-vitro 3D co-culture model incorporating PDAC patient-derived organoids (PDOs) and macrophages within a synthetic hydrogel matrix. We optimized culture conditions by tuning medium and matrix conditions to support both cell lineages. Flow cytometry and transcriptomic analyses revealed that initially undifferentiated macrophages adopt an M2-like profile upon exposure to PDAC PDOs in starPEG-heparin hydrogels, mirroring the macrophage phenotypes observed by multiplex immunohistochemistry in the matched primary PDAC tissues. Cytokine secretome profiling revealed PDO-specific differences, indicating distinct underlying macrophage polarization subtypes. Collectively, our starPEG-heparin hydrogel-based 3D co-culture enables hypothesis-driven and physiologically relevant studies of tumor-macrophage interactions and may advance immune-modulatory treatment strategies in patients with PDAC.

Journal Article↗

PubMed2026

Spatial Omics in High-Grade Gliomas: Mapping Immune-Tumor Niches for Precision Therapy.

High-grade gliomas (HGGs), particularly glioblastoma (GBM), remain among the most lethal human cancers despite decades of molecular profiling and therapeutic innovation. A primary reason for treatment failure is that HGG biology is spatial: malignant cell states, immune suppression, metabolic stress, and therapeutic resistance are organized into distinct anatomical and functional niches. Spatial omics technologies now enable high-dimensional mapping of gene expression, protein signaling, immune architecture, and metabolic activity within intact tumor tissue. These approaches reveal how proneural and mesenchymal transcriptional states coexist yet localize to distinct regions, alongside hypoxic, invasive, and stem-enriched niches. Spatial analyses show that key clinical determinants, including O6-methylguanine-DNA methyltransferase (MGMT)-associated temozolomide resistance, radiotherapy tolerance in hypoxic regions, and immunotherapy failure driven by myeloid-dominated immune exclusion, are influenced not only by molecular programs but also by cellular location. Beyond biological insight, spatial omics is reshaping clinical paradigms by enabling region-specific patient stratification, early assessment of treatment response, and identification of therapy-resistant reservoirs that seed recurrence. Prior bulk and single-cell studies defined HGG cell states and pathways but often treated resistance as tumor-wide. This review presents a spatially explicit framework that synthesizes spatial transcriptomic and immune-profiling studies to identify tumor-immune niches and spatial bottlenecks that drive therapeutic failure and recurrence.

Humans↗

PubMed2026

Context-dependent roles of DHX9 in Cancer: Molecular mechanisms, biomarker potential, and therapeutic perspectives.

DExH-box helicase 9 (DHX9) is a multifunctional nucleic acid helicase that participates in R-loop homeostasis, genome maintenance, RNA metabolism, and innate immune signaling. Accumulating evidence has linked aberrant DHX9 expression or activity to tumorigenesis, tumor progression, treatment response, and patient prognosis. However, its role in cancer is highly context-dependent, rather than uniformly oncogenic or tumor suppressive. Depending on its molecular partners, subcellular localization, post-translational modifications, tumor genotype, and immune microenvironment, DHX9 may either promote malignant phenotypes or contribute to tumor-restraining processes. In this review, we summarize the molecular characteristics and regulatory properties of DHX9, discuss its roles in genome stability, transcriptional and post-transcriptional control, circular RNA (circRNA) biogenesis, and tumor-immune crosstalk, and evaluate its emerging value as a potential biomarker and therapeutic target. We also highlight key challenges in this field, including mechanistic heterogeneity, insufficient translational validation, and the urgent need for context-informed patient stratification to maximize the clinical utility of DHX9-targeted strategies.

Humans↗

PubMed2026

Identification of molecular subtypes in clear cell renal cell carcinoma based on chromatin regulators and tumor immune microenvironment profiling.

In the histological classification of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) accounts for the highest proportion and is the most common subtype. Despite advances in management, it continues to be associated with considerable incidence and mortality. Although surgery and systemic therapies are available, their efficacy is constrained by pronounced intratumoral heterogeneity and treatment resistance. Identifying robust biomarkers and clarifying the underlying biological mechanisms are therefore essential to improving diagnosis, risk stratification and therapeutic decision-making. In this work, we identified two ccRCC molecular subtypes displaying divergent chromatin regulator (CR) profiles and different clinical prognoses. Using the genes differentially expressed between these subgroups, we constructed a CR-related score (CRS) that effectively stratified patients according to survival. More analysis concluded that the low expression of CR was more linked with the immune-activated tumors, which encompassed the immune pathway enrichment, as well as the elevation of numerous immune cell subtypes. Moreover, elevated CRS was associated with improved immunotherapy responsiveness. Drug-sensitivity analyses nominated several candidate agents, and SMARCD3 knockdown in 786-O cells inhibited proliferation and migration and reduced sensitivity to masitinib. Collectively, these findings support the prognostic and therapeutic relevance of CR-related states in ccRCC and provide a framework for future experimental validation of chromatin-regulated tumor-immune interactions.

Humans↗

PubMed2026

Beyond the "cold" barrier: Redefining the clinical paradigm of immune checkpoint inhibitor therapy in ovarian cancer.

Ovarian cancer remains an immunologically "cold" tumor, with early all-comer immune checkpoint inhibitor (ICI) trials largely negative despite underlying immunogenicity. This review takes a clinician-centric, stage-specific view linking regimen choice, treatment line, and tumor-immune context to observed outcomes. In the neoadjuvant and first-line settings, unselected ICI combinations with chemotherapy and anti-angiogenic agents failed to improve progression-free survival, whereas adding a poly (ADP-ribose) polymerase (PARP) inhibitor to ICI maintenance yielded modest gains in biomarker-enriched cohorts. In recurrent disease, single-agent ICIs produced objective response rates of 8-15%, and most randomized combinations were negative. The phase III KEYNOTE-B96 trial in platinum-resistant disease demonstrated a progression-free survival benefit in the intention-to-treat population and an overall survival benefit in tumors with programmed death ligand 1 (PD-L1) combined positive score ≥ 1 when pembrolizumab was paired with weekly paclitaxel with or without bevacizumab, underscoring the value of an immunomodulatory chemotherapy backbone in earlier lines. Ovarian clear cell carcinoma emerges as an immunotherapy-sensitive, chemo-resistant subtype that warrants dedicated stratification. We explain why single-analyte biomarkers-PD-L1, tumor mutational burden, homologous recombination deficiency/BRCA1/2-have not reliably enriched benefit and outline a multidimensional approach integrating genomic scars (e.g., mutational signature 3), immune functional state (Immunoscore, CD8⁺ tumor-infiltrating lymphocyte density and CD8⁺: regulatory T-cell ratio), and spatial architecture (inflamed, excluded, desert phenotypes). This framework aims to move beyond the all-comer era toward context-informed precision immunotherapy in ovarian cancer.

Humans↗

PubMed2026

ITPRIPL1: A tumor immune-associated biomarker with prognostic and therapeutic implications in gastrointestinal cancer.

Inositol 1,4,5-trisphosphate receptor-interacting protein-like 1(ITPRIPL1) has recently been implicated in tumor-immune regulation, yet its tumor-type specificity and clinical relevance in gastrointestinal malignancies remain unclear. Here, we performed an integrative analysis of ITPRIPL1 across stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and esophageal carcinoma (ESCA) using bulk transcriptomics, immune pathway analyses, survival modeling, single-cell RNA sequencing, immunofluorescence validation, and therapeutic correlation analyses. Although ITPRIPL1 was upregulated across gastrointestinal cancers, its prognostic significance was highly tumor-specific, with elevated expression consistently predicting unfavorable survival only in STAD. In gastric cancer, ITPRIPL1 expression was closely associated with immune-related pathways and genomic instability features, and its prognostic association varied across immune contexts, particularly according to CD8⁺/CD4⁺ T-cell abundance, with an exploratory association also observed for zeta-chain-associated protein kinase 70 (ZAP70) expression. Single-cell and immunofluorescence analyses demonstrated preferential enrichment of ITPRIPL1 in T cells and tumor-adjacent immune structures. Notably, Exploratory analyses further showed that higher ITPRIPL1 expression was associated with favorable survival outcomes in selected external pretreatment immunotherapy cohorts and with lower IC50 values for several agents in cancer cell-line pharmacogenomic datasets. Collectively, these findings identify ITPRIPL1 as an immune-associated biomarker with primary clinical relevance in gastric cancer.

Humans↗

PubMed2025

m6A regulator-based molecular classification and hub genes associated with immune infiltration characteristics and clinical outcomes in diffuse gliomas.

BACKGROUND: m6A methylation modification is a new regulatory mechanism involved in tumorigenesis and tumor-immunity interaction. However, its impact on glioma immune microenvironment and clinical outcomes remains unclear. METHODS: Comprehensive expression profiles of 18 m6A regulators were used to identify molecular subtypes exhibiting distinct m6A modification patterns in 1673 glioma samples sourced from public datasets. A multi-genes signature was constructed for predicting clinical outcomes and response to immunotherapy in glioma patients. Immunohistochemistry and cellular experiments were performed for validation. RESULTS: Two m6A subtypes of gliomas were identified. The m6A-low-risk subtype was characterized by paucity of immune infiltrates; While the m6A-high-risk subtype had higher abundances of multiple immune cells including lymphocyte and macrophage as well as increased expression of PD-L1, corresponding to an immunosuppressive phenotype. The m6A-high-risk subtype had poorer survival than the m6A-low-risk subtype in both the glioblastoma and lower grade gliomas cohorts. Eight m6A-related hub genes of high prognostic significances were identified and selected for developing a scoring signature termed as m6Ascore. Elevated m6Ascore indicated worse survival for glioma patients under standard care, but showed enhanced response to immunotherapy. Moreover, we demonstrated that overexpression of FTO, a m6A demethylase, inhibited the expressions of m6A-related hub genes (PTX3, SPAG4), impaired glioma cell viability and reduced macrophage chemotaxis. CONCLUSION: This work develops an immune- and clinical-relevant m6A subtyping and a scoring model, which enhances our understanding of the role of m6A modification in regulating immune infiltration microenvironment in gliomas and helps to identify patients who are more likely to benefit from immunotherapy.

Humans↗

PubMed2026

Malignant epithelial states drive immune dysfunction in ampulla of Vater carcinoma.

BACKGROUND: Ampulla of Vater (AoV) carcinoma is a rare malignancy arising at the junction of intestinal and pancreatobiliary epithelium. Its heterogeneous clinical behavior and histological diversity have hindered therapeutic advances, and the cellular basis of this heterogeneity remains unclear. We aimed to construct a single-cell transcriptomic atlas of AoV carcinoma, with a focus on identifying epithelial subtypes and their interactions with the tumor microenvironment (TME). METHODS: We performed single-cell RNA sequencing on eight primary AoV tumors and four matched normal tissues. Comprehensive clustering and transcriptomic analyses identified cell-type composition, epithelial heterogeneity, and tumor-immune interactions. Findings were validated using deconvolution of bulk RNA-seq data from 62 AoV carcinoma patients. Results Malignant epithelial cells were categorized into four distinct subtypes: Int-Wnt, PB-KRAS, Int-Hypoxia, and Cycling stage. PB-KRAS cells exhibited stem-like transcriptional programs and high genomic instability. Deconvolution analysis of bulk RNA-seq data from the independent AoV cohort revealed that enrichment of the PB-KRAS subtype correlated with tumor recurrence and poor survival. Our immune profiling analysis discovered a significant association between PB-KRAS subtype and GZMK+ CD8+ T cells, which are in a pre-dysfunctional state, alongside SPP1+ macrophages exhibiting immunosuppressive traits. Spatial transcriptome data further supports the immunosuppressive natures of TME around PB-KRAS subtype malignant epithelial cells in AoV carcinoma. CONCLUSIONS: Our study presents a single-cell atlas of AoV carcinoma, highlighting the molecular diversity of malignant epithelium and its association with the immune microenvironment. The PB-KRAS subtype emerges as a stem-like, immunosuppressive tumor state associated with poor prognosis, providing insights for future therapeutic targeting.

Ampulla of Vater carcinoma↗