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PubMed2026

SLA2 is Associated With Immune evasion and Exhaustion of CD8+ T Cells in Gastric Cancer.

The Src-like adaptor 2 (SLA2) functions as a negative regulator of T cell receptor signalling. However, its involvement in the tumour microenvironment (TME) of gastric cancer (GC) remains unexplored. In this study, we found that SLA2 expression was significantly elevated in GC tissues, and a high level of SLA2 was associated with poor prognosis in GC patients. Bioinformatics analyses revealed a close association between SLA2 and TME in GC. Single-cell RNA sequencing analysis indicated that SLA2 was significantly enriched in CD8+ T cells in GC tissues. Functional validation demonstrated that SLA2 overexpression contributed to the exhaustion of CD8+ T cells by suppressing their proliferation, upregulating the expression of exhaustion markers, reducing the secretion of effector cytokines (IFN-γ and TNF-α) and impairing cytotoxic function. SLA2 knockdown in in vitro-generated exhausted CD8 T cells significantly alleviated T cell exhaustion. Mechanistically, we found that inverse promoter methylation and active histone marks (H3K27ac, H3K4me3 and H3K4me1) may regulate SLA2 expression. Our findings suggest that SLA2 may modulate the TME and promote immune evasion via CD8+ T cell exhaustion in GC.

Humans↗

PubMed2026

Tumor-associated macrophages display differential protein cargo sorting in extracellular vesicles associated with poor survival in ovarian cancer.

Ovarian cancer (OC) progression and metastasis are promoted by ascites, which constitutes a central part of the tumor microenvironment (TME). In this fluid, tumor-associated macrophages (TAMs) represent a prominent immune cell type. In addition to tumor and other host cells such as TAMs, ascites is highly enriched in soluble factors as well as extracellular vesicles (EVs). How TAMs contribute to the EV compartment of the OC TME remains, however, underexplored. In this work peripheral blood monocytes from healthy donors were differentiated into monocyte-derived macrophages (MDMs) and polarized into classically activated (M1-like), alternatively activated (M2-like) and TAM-like (by ascites incubation). For all subtypes, serum-free conditioned medium was collected for 24 h and EVs were isolated and characterized by nano-flow cytometry (nFC), label-free mass spectrometry-based proteomics and electron microscopy, among others. Our results demonstrated distinct traits for EV release and cargo across the different macrophage subtypes. Specifically, TAM-like macrophages exhibited impaired release of small EVs and reduced frequency of tetraspanin-positive particles. These EV subpopulations displayed sizing profiles closer to M1-like than to M2-like samples. Also, the low EV release in TAM-like MDMs was accompanied by altered expression of biogenesis-related markers like flotillin-1 (FLOT1) and a decreased N-glycosylation of CD63 protein, which was validated in patient-derived samples. Remarkably, the EV-associated proteome of TAMs displayed significant enrichment in both pro- and anti-inflammatory molecules with clinical value. Markers significantly enriched in the ascites TAM-EV signature were mostly associated with poor prognosis, whereas M1-like EV-related markers (pro-inflammatory) were mostly associated with longer survival. Our results confirmed previous data for proteins like CD163 and MRC1 to be associated to TAM-EVs, while also describing novel candidates with diagnostic (i.e., COLEC12) and/or prognostic (i.e., MSR1) value in plasma. Taken together, our data support a unique secretory profile of TAMs in OC and provide new EV-associated biomarkers with translational impact. Our results pave the way for a better understanding of the mechanisms behind TAM-EV cargo loading and function, and how these cells participate in the TME landscape.

Humans↗

PubMed2026

A per- and polyfluoroalkyl substances-based gene signature links prognosis to immune landscapes in thyroid cancer.

BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy with a rising global incidence and significant heterogeneity. Although per- and polyfluoroalkyl substances (PFAS) exposure is linked to thyroid dysfunction, the prognostic value of per- and polyfluoroalkyl substances-related genes (PFASRGs) and their role in the tumor immune microenvironment (TME) remain poorly understood. This study aims to systematically screen key PFASRGs and evaluate their prognostic value as biomarkers for THCA. METHODS: Utilizing The Cancer Genome Atlas (TCGA)-THCA transcriptomic data and PFASRGs, we constructed a prognostic model through differential expression analysis, univariate and multivariate Cox regression analyses, and the least absolute shrinkage and selection operator (LASSO). The model's robustness was validated using receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, and clinical nomograms. Furthermore, the TME, immunotherapy response, and drug sensitivities were systematically evaluated. Distinct molecular landscapes were characterized by stratifying the cohort via unsupervised consensus clustering analysis. RESULTS: The eight-gene prognostic model demonstrated robust performance, with area under the curve (AUC) values exceeding 0.85 across all validation cohorts. High-risk patients exhibited significantly shorter overall survival and an "inflamed" TME characterized by high immune scores and checkpoint expression. In contrast, the therapeutic efficacy of anti-programmed death-ligand 1 (PD-L1) agents was more pronounced in the low-risk category, as evidenced by a superior objective response. Furthermore, distinct molecular subtypes and risk-specific sensitivities to targeted agents, such as sorafenib and sunitinib, were identified, highlighting the model's clinical utility for personalized treatment. CONCLUSIONS: We established a novel THCA prognostic framework based on eight PFASRGs. This model exhibits superior performance in risk stratification, effectively distinguishing cohorts with divergent clinical trajectories, unique immune microenvironment features, and varied therapeutic responses. Our findings provide a powerful predictive tool for refining prognostic evaluation and facilitating the implementation of personalized management strategies for THCA patients.

Per- and polyfluoroalkyl substances-related genes ↗

PubMed2025

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

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

Aged↗

PubMed2026

Construction and validation of a β-hydroxybutyrylation-related molecular model for predicting prognosis of papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) usually has a favorable prognosis, yet a subset of patients develops persistent, recurrent, or biologically aggressive disease. The clinical relevance of lysine β-hydroxybutyrylation (Kbhb)-related transcriptional programs in PTC remains unclear. Accordingly, this study aimed to characterize Kbhb-related molecular heterogeneity in PTC, construct a prognostic signature, and explore its association with the tumor microenvironment (TME). METHODS: Transcriptomic and clinical data from PTC samples within The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) cohort were analyzed to identify Kbhb-related differentially expressed genes (DEGs), define molecular subtypes, construct a prognostic signature, and characterize tumor microenvironmental features. Single-cell RNA-sequencing data from PTC were further used to explore the cellular distribution of representative genes. RESULTS: We identified 51 Kbhb-related DEGs in PTC and defined two Kbhb molecular subtypes. The Kbhb_C2 subtype showed shorter progression-free interval (PFI) and a more immune- and stroma-enriched microenvironment. A six-gene prognostic signature comprising TARID, CDSN, PIMREG, KLRC1, SYT13, and NPR3 was then established. High-risk patients had significantly worse PFI in the full, training, and testing cohorts, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.715, 0.793, and 0.771, respectively, in the full cohort. High-risk tumors also exhibited higher stromal, immune, and ESTIMATE scores, altered immune infiltration, and increased expression of multiple immune checkpoint molecules. Single-cell analysis confirmed distinct cell-type-specific expression patterns of representative genes. CONCLUSIONS: Kbhb-related transcriptional programs define clinically relevant molecular heterogeneity in PTC and are closely associated with prognosis and TME remodeling. The identified six-gene signature provides a biologically interpretable framework for risk stratification in PTC.

Papillary thyroid carcinoma (PTC)↗

PubMed2026

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

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

Animals↗

PubMed2026

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

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

Humans↗

PubMed2026

Integrated Genomic and Proteomic Analysis Reveals T-B Lymphocyte Signatures in the MYCN Driven "Immune Desert" of Specific Neuroblastoma Subtypes.

AIMS: This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high-risk neuroblastoma, elucidating key mechanisms underlying immune evasion. METHODS: We performed an integrated multi-omics analysis of bulk RNA-seq (n = 721), single-cell RNA-seq (n = 9), proteomic data (n = 49) and spatial transcriptomics (Visium, with external validation in melanoma). Analyses included unsupervised clustering, cell-cell communication inference, transcriptional regulatory network reconstruction, and spatial proximity assessment to map the immune landscape. RESULTS: A distinct molecular subtype (Class C), defined by MYCN amplification and poor prognosis, exhibited a comprehensive "immune desert" phenotype characterized by low immune scores and minimal leukocyte infiltration. Single-cell analysis confirmed significant depletion of T and B lymphocytes within the Class C TME. Dysregulated transcriptional networks were identified, including upregulation of REL and EOMES in T cells-with EOMES potentially driving exhaustion via regulation of Transient Receptor Potential (TRP) genes, and REL inhibition enhancing cytotoxic function in vitro. A unique immunosuppressive B-cell subset (B7) engaged in enhanced crosstalk with exhausted T cells and harbored a MYC-centered network linked to cell cycle dysregulation and poor survival. Spatial transcriptomics revealed significant proximity between B7-active regions and Treg/exhaustion-enriched areas, externally validated in melanoma. Proteomic data validated elevated REL expression in MYCN-amplified tumors. CONCLUSION: This work delineates the immunosuppressive architecture of MYCN-driven neuroblastoma, revealing novel regulatory nodes within specific lymphocyte compartments. Integrating single-cell, spatial, and proteomic evidence, we propose REL inhibition as a therapeutic candidate, the EOMES/TRP axis as a bioinformatically supported hypothesis, and the B7/MYC hub as a hypothesis supported by transcriptomic and spatial evidence.

Humans↗

PubMed2026

Icaritin Sensitizes Hepatocellular Carcinoma to PD-L1 Therapy by NQO1-Dependent Ferroptosis Induction.

Hepatocellular carcinoma (HCC) remains challenging with limited immunotherapy response. Despite its clinical promise in advanced HCC, the mechanisms of icaritin, especially concerning ferroptosis induction and immune modulation, remain elusive. This study aims to determine if the antitumor effect of icaritin involves the induction of ferroptosis via NAD(P)H quinone oxidoreductase 1 (NQO1) and if it can augment the efficacy of programmed cell death 1 ligand 1 (PD-L1) therapy by potentiating natural killer (NK) cell activity. Using human HCC cell lines (Huh7, Hep3B, PLC/PRF/5, SNU-449, and MHCC97-H) and two synergistic mouse models (Hepa1-6 and SgPten/c-Met), we examined icaritin's inhibition of tumor growth and induction of ferroptosis via the NQO1 pathway, monitoring key markers (reactive oxygen species [ROS], glutathione peroxidase 4 [GPX4], ferritin heavy chain 1 [FTH1]). The NQO1 inhibitor dicoumarol was employed to validate the pathway. Tumor microenvironment (TME) remodeling was assessed through cancer-associated fibroblasts (CAFs) markers and immune cell profiling, focusing on NK cell infiltration. Combination therapy with anti-PD-L1 was tested in vivo. Icaritin significantly inhibited HCC growth in vitro and in vivo. Its antitumor effect was mediated by NQO1-mediated ferroptosis, via elevated ROS, diminished mitochondrial membrane potential, and downregulated GPX4 and FTH1. Analysis of The Cancer Genome Atlas (TCGA) data revealed that NQO1 is overexpressed in human HCC tissues. Icaritin enhanced NK cell infiltration while reducing CAF abundance and suppressing recombinant focal adhesion kinase (FAK) and discoidin domain receptor 1 (DDR1) signaling. Notably, icaritin synergized with anti-PD-L1 therapy to enhance tumor suppression without increasing toxicity, correlating with potentiated NK cell immunity. Our findings demonstrate that icaritin triggered NQO1-mediated ferroptosis and remodeled TME to enhance NK cell recruitment and PD-L1 therapy efficacy. This provides rationale for evaluating icaritin-based combination immunotherapy in HCC through dual action on ferroptosis and NK cell activation.

Ferroptosis↗

PubMed2026

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and potential therapeutic targets. Multi-source transcriptomic datasets (TCGA-COAD, GSE39582, GSE17536) and single-cell RNA-seq data were analyzed. Ten machine learning algorithms were integrated to construct an acRG-based prognostic signature (acRGBS). Immune microenvironment (TME) and genomic profiling were performed, with in vitro functional experiments validating TUBA1C's role. acRGBS, comprising four hub genes (SARAF, CDC42SE2, TSPYL2, TUBA1C), effectively stratified COAD patients into high- and low-risk groups with distinct survival outcomes and was an independent prognostic factor. High-risk patients exhibited increased genomic instability and immunosuppressive TME, while low-risk patients had favorable immunotherapy response. TUBA1C was overexpressed in COAD cells, and its knockdown inhibited proliferation/migration and induced apoptosis. The acRGBS is a robust prognostic tool for COAD, and TUBA1C serves as a candidate therapeutic target, providing new insights for personalized COAD management.

Humans↗

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↗

PubMed2026

A novel lactylation-related gene signature deciphers the immunosuppressive microenvironment and stratifies precision therapy in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer mortality, largely due to the heterogeneity of the tumor microenvironment (TME) and the limited efficacy of immunotherapy in microsatellite stable (MSS) tumors. Histone lactylation, a post-translational modification derived from the Warburg effect, serves as a critical bridge linking metabolic reprogramming to gene regulation and immune evasion; however, its specific prognostic value and clinical implications in CRC remain to be fully elucidated. METHODS: In this study, we systematically analyzed transcriptome profiling data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, supplemented by single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) protein-level validation. By integrating univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox regression, we constructed a novel lactylation-related gene (LRG) risk signature. We extensively evaluated the association between this risk signature and patient prognosis, immune infiltration patterns, somatic mutations, and therapeutic sensitivity. RESULTS: A robust 9-gene prognostic signature (DHRS7, SPR, MBD2, RBM17, CSRP2, S100A4, TMSB4X, TKT, COPS4) was identified and corroborated at the protein level. Patients with high risk scores exhibited significantly worse overall survival (OS) across the training and two independent validation cohorts. Immunogenomic and scRNA-seq analyses revealed that high-risk tumors were characterized by an immunosuppressive and stromal-dense microenvironment-with stromal cells exhibiting the highest lactylation risk scores-enriched with regulatory T cells (Tregs), and frequently harbored PIK3CA mutations. Differential expression analysis indicated that this immune exclusion is structurally maintained by enriched extracellular matrix (ECM) organization and TGF-β signaling. Conversely, low-risk tumors displayed an inflamed phenotype with active antitumor immunity. Pharmacogenomic prediction identified distinct therapeutic stratifications: low-risk patients exhibited significant sensitivity to standard chemotherapeutics (fluorouracil, oxaliplatin) and EGFR/HER2 inhibitors (e.g., lapatinib, erlotinib). In contrast, high-risk patients showed specific vulnerabilities to novel targeted agents, including PI3K pathway inhibitors (TG-100-115, XL765), microenvironment-modulating agents (sildenafil, GANT-61), and epigenetic inhibitors (UNC0638). CONCLUSION: We established a novel lactylation-related risk signature that effectively stratifies CRC patients by prognosis and TME characteristics. By elucidating the crosstalk between metabolic dysregulation, stromal barriers, and immune exclusion, this study provides potential biomarkers and stratified therapeutic strategies-ranging from standard chemotherapy to targeted metabolic and stromal interventions-to optimize precision medicine for CRC patients.

Colorectal cancer↗

PubMed2026

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

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

Lung cancer↗

PubMed2025

Implications of EGFR expression on EGFR signaling dependency and adaptive immunity against EGFR-mutated lung adenocarcinoma.

BACKGROUND: In EGFR-mutated lung adenocarcinoma (EGFRm LUAD), EGFR mutations do not necessarily result in increased EGFR expression (EGFR-exp), which differs among patients. However, the factors influencing EGFR-exp and the impact of EGFR-exp on tumor characteristics in patients with EGFRm LUAD remain unclear. PATIENTS AND METHODS: Whole-exome and RNA sequencing were performed for patients with early- and advanced-stage EGFRm LUAD. The patients were classified into low or high EGFR-exp groups based on the median transcripts per million. We retrospectively examined the association between EGFR-exp, genomic characteristics, downstream EGFR signaling activity, tumor microenvironment (TME) status, and clinical outcomes. RESULTS: This study included 450 and 45 patients in the early- and advanced-stage cohorts, respectively. In both cohorts, the EGFR-exp low group exhibited a lower incidence of TP53 co-mutations and EGFR amplification and a higher incidence of EGFR subclonal mutations than the EGFR-exp high group. Furthermore, downstream EGFR signaling pathways, such as the MAPK signaling, were less activated in the EGFR-exp low group. However, this group showed significantly enriched adaptive immune response pathways (Q < 0.0001) and an immune-inflamed TME. Additionally, a low EGFR-exp was a significantly favorable factor for postoperative relapse (odds ratio [OR], 0.6; P = 0.04). However, in the advanced-stage cohort, a low EGFR-exp was a significant risk factor for non-responders to osimertinib (OR, 17.5; P = 0.03). CONCLUSIONS: In EGFRm LUAD, significant associations were observed between EGFR-exp levels and both EGFR signaling pathways and adaptive immune status, which in turn influence clinical outcomes. This large-scale multi-omics analysis highlights the heterogeneity among patients with EGFRm LUAD and emphasizes the need to assess EGFR-exp levels alongside mutation status for optimal treatment strategies in EGFRm LUAD.

Humans↗

PubMed2026

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

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

Chaperone-mediated autophagy↗

PubMed2026

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma↗

PubMed2026

The pseudouridine epitranscriptomic landscape of advanced prostate cancer therapeutic resistance identifies TIMM17A as a key player.

BACKGROUND: Resistance to androgen receptor signaling inhibitors (ARSIs) remains a major barrier of advanced prostate cancer (PCa) treatment. While RNA epitranscriptomic modifications are increasingly recognized as key regulators of tumor biology, the role of pseudouridine (Ψ) in therapeutic resistance is largely unexplored. METHODS: A darolutamide-resistant PCa cell model was established and subjected to integrated multi-omics profiling using bulk RNA sequencing and photo-crosslinking-assisted Ψ sequencing (PA-Ψ-seq). Differential expression and pseudouridylation analyses were combined to identify Ψ-associated genes. Public datasets validated expression and prognosis. Functional assays including RNA knockdown, cell proliferation, colony formation, and xenograft models were conducted. Single-cell RNA sequencing investigated tumor microenvironment (TME) interactions. RESULTS: We identified extensive transcriptomic and pseudouridylation alterations associated with ARSI resistance, with a significant positive correlation between Ψ modification and mRNA expression. Integrated analysis highlighted a subset of "hyper-up" genes enriched in resistance-related pathways. Thus, TIMM17A was identified as a novel candidate. TIMM17A expression was significantly elevated in PCa and correlated with disease progression and poor prognosis. Experimental validations demonstrated that TIMM17A promoted tumor growth and resistance, while its knockdown restored sensitivity to darolutamide both in vitro and in vivo. Mechanistically, TIMM17A expression may be regulated by PUS1‑mediated pseudouridylation. Single-cell analysis further revealed that TIMM17A is enriched in malignant epithelial cells and associated with enhanced cell-cell communication within the TME. CONCLUSIONS: This study delineates the pseudouridine epitranscriptomic landscape in advanced PCa and identifies TIMM17A as a key mediator of therapeutic resistance. Targeting the Ψ-TIMM17A axis may offer a novel strategy to overcome ARSI resistance.

Advanced prostate cancer↗

PubMed2026

Intratumoral collagen correlates with histological grade and patient prognosis in breast cancer.

Histological grading, using the Nottingham Grading System (NGS), is a major prognostic indicator for breast cancer. NGS involves the scoring of cancer cell-related morphological features, yet it overlooks tumor microenvironment (TME) components such as collagen. Collagen proteins, integral to the extracellular matrix (ECM), influence tumor architecture and progression but their relationship with histological grade is not fully characterized. Here, we assessed intratumoral collagen deposition using Masson Trichrome staining of whole slides (n = 166), proteomic profiling (n = 2) and transcriptomic analyses of the METABRIC (n = 1827) and TCGA-BRCA (n = 753) cohorts. We showed that low-grade tumors display significantly higher intratumoral collagen deposition compared to high-grade tumors. Moreover, we demonstrated that collagen expression at the transcript and protein levels (Masson Trichrome) could discriminate Grade II carcinomas into distinct prognostic groups, in which patients with Grade II carcinomas with elevated levels of collagen expression were associated with lower pTNM stage and better survival outcomes. Our results support the inclusion of TME features, such as collagen deposition, to enhance prognostic accuracy in breast cancer.

Humans↗