Discover Oncology, Год журнала: 2025, Номер 16(1)
Опубликована: Июнь 4, 2025
Язык: Английский
Expert Opinion on Biological Therapy, Год журнала: 2025, Номер unknown
Опубликована: Март 31, 2025
Introduction Immunotherapy combined with anti-angiogenesis has become a useful strategy in cancer treatment. Ivonescimab, the first approved bispecific antibody targeting both immune checkpoint inhibition and anti-angiogenesis, represents breakthrough over conventional dual-drug combination approach. The emerging clinical evidence demonstrates promising efficacy manageable safety profile of ivonescimab treatment non-small cell lung (NSCLC), suggesting its potential role as cornerstone next generation immunotherapy.
Язык: Английский
Процитировано
0
Journal of Cellular and Molecular Medicine, Год журнала: 2025, Номер 29(7)
Опубликована: Март 30, 2025
ABSTRACT Immune checkpoint inhibitors (ICIs) represent a groundbreaking advancement in cancer therapy, substantially improving patient survival rates. Our comprehensive research reveals significant positive correlation between coagulation scores and immune‐related gene expression across 30 diverse types. Notably, tumours exhibiting high demonstrated enhanced infiltration of cytotoxic immune cells, including CD8 + T natural killer (NK) macrophages. Leveraging the TCGA pan‐cancer database, we developed Coagulation.Sig model, sophisticated predictive framework utilising coagulation‐related genes (CRGs) to forecast immunotherapy outcomes. Through rigorous analysis ten ICI‐treated cohorts, identified validated seven critical CRGs: BIRC2, HMGB1, STAT2, IFNAR1, BID, SPATA2, IL33 IFNG, which form foundation our model. Functional analyses revealed that low‐risk characterised by higher cell populations, particularly superior ICI responses. These also exhibited increased mutation rates, elevated neoantigen loads, greater TCR/BCR diversity. Conversely, high‐risk displayed pronounced intratumor heterogeneity (ITH) NRF2 pathway activity, mechanisms strongly associated with evasion. Experimental validation highlighted BIRC2 as promising therapeutic target. Targeted knockdown, when combined anti‐PD‐1 significantly suppressed tumour growth, infiltration, amplified IFN‐γ TNF‐α secretion models. findings position model novel, approach personalised treatment, emerging both biomarker potential intervention point.
Язык: Английский
Процитировано
0
Frontiers in Molecular Biosciences, Год журнала: 2025, Номер 12
Опубликована: Апрель 4, 2025
Background Breast cancer (BRCA) is a significant threat to women’s health worldwide, and its progression closely associated with the tumor microenvironment gene regulation. Lactylation modification, as key epigenetic mechanism in biology, has not yet been fully elucidated context of BRCA. This study examines regulatory mechanisms lactylation-related genes (LRGs), specifically PRDX1, their prognostic significance Methods We integrated data from multiple databases, including Genome-Wide Association Study (GWAS) summary statistics, single-cell RNA sequencing, spatial transcriptomics, bulk sequencing The Cancer Genome Atlas (TCGA) Gene Expression Omnibus (GEO) databases. Using Summary-based Mendelian Randomization (SMR) analysis, we identified LRGs BRCA comprehensively analysed expression patterns cell-cell communication networks, heterogeneity. Furthermore, constructed validated model based on profile PRDX1-positive monocytes, evaluating it through Cox regression LASSO analyses. Results PRDX1 was LRG significantly risk (p_SMR = 0.0026). Single-cell analysis revealed upregulation enhanced between monocytes fibroblasts. Spatial transcriptomics uncovered heterogeneous nest regions, highlighting interaction demonstrated high accuracy predicting patient survival both training validation cohorts. High-risk patients exhibited immune-suppressive characteristics, reduced immune cell infiltration checkpoint expression. Conclusion reveals role progression, mainly regulation escape mechanisms. prediction shows robust potential, future research should focus integrating other biomarkers enhance precision personalised medicine.
Язык: Английский
Процитировано
0
Frontiers in Immunology, Год журнала: 2025, Номер 16
Опубликована: Апрель 16, 2025
Background Lung adenocarcinoma is the most prevalent type of small-cell carcinoma, with a poor prognosis. For advanced-stage patients, efficacy immunotherapy suboptimal. The STING signaling pathway plays pivotal role in lung adenocarcinoma; therefore, further investigation into relationship between and warranted. Methods We conducted comprehensive analysis integrating single-cell RNA sequencing (scRNA-seq) data bulk transcriptomic profiles from public databases (GEO, TCGA). pathway-related genes were identified through Genecard database. Advanced bioinformatics analyses using R packages (Seurat, CellChat) revealed heterogeneity, intercellular communication networks, immune landscape characteristics. developed signature (STINGsig) 101 machine learning frameworks. functional significance ERRFI1, key component STINGsig, was validated mouse models multicolor flow cytometry, particularly examining its enhancing antitumor immunity potential synergy α-PD1 therapy. Results Our characterized 15 distinct cell populations, including epithelial cells, macrophages, fibroblasts, T B endothelial each unique marker gene profiles. activity scoring elevated activation neutrophils, contrasting lower inflammatory macrophages. Cell-cell demonstrated enhanced interaction networks high-STING-score evident fibroblasts cells. STINGsig showed robust prognostic value microenvironment characteristics risk groups. Notably, ERRFI1 knockdown experiments confirmed significant modulating therapy response. Conclusion STING-related exhibited expression levels across high-score cells showing tumor-promoting pathways, active interactions, enrichment IFI27+ In contrast, low-score associated phenotypes reduced activity. (STINGsig), which linked to microenvironment. Through vivo experiments, we that critical within significantly enhances synergizes cancer model, underscoring therapeutic responses.
Язык: Английский
Процитировано
0
Опубликована: Апрель 29, 2025
ABSTRACT The progression of differentiated thyroid carcinoma (DTC) poses significant clinical challenges, especially in determining the optimal time for intervention. To capture early signals disease progression, we employed an optimized dynamic network biomarker (DNB) method—a systems biology approach that detects abrupt molecular changes indicating a critical transition signal. This analysis revealed Stage II marks trajectory. We further developed scoring system called TCPSLevel (Thyroid Carcinoma Progression Signature Level), which quantifies individual risk based on gene expression profiles. showed strong associations with features and prognosis across multiple datasets. Our ensemble consensus clustering uncovered three robust DTC subtypes, demonstrated distinct outcomes, immune microenvironments, regulatory landscapes, therapeutic agents. A clinically applicable classifier (miniPC) was constructed using machine learning to facilitate subtype prediction. also identified ASPH as key regulator driving validated its function experimentally. Together, these findings offer new insights practical tools assessment personalized management cancer.
Язык: Английский
Процитировано
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Frontiers in Immunology, Год журнала: 2025, Номер 16
Опубликована: Май 22, 2025
Lung adenocarcinoma (LUAD) is distinguished by intricate relationships between tumor advancement and the immune microenvironment. The function of PSMD14 (Proteasome 26S Subunit, Non-ATPase 14) within context LUAD not well elucidated, especially in terms its correlation with cell infiltration prognosis patients. objective this research was to explore expression levels evaluate potential implications for immunity clinical outcomes. A multifaceted approach adopted, which included analysis RNA sequencing (RNA-seq) data, assessment infiltration, survival analysis, gene enrichment integration single-cell RNA-seq data thoroughly biological relevance PSMD14. Furthermore, we examined parameters. Immunohistochemistry techniques were employed analyze samples invasive pulmonary adenocarcinoma. Our study demonstrated that markedly elevated exhibits a positive other members JAMM family, including EIF3H PSMD7. Importantly, linked poor patient prognosis, indicating utility as biomarker. Moreover, Kyoto Encyclopedia Genes Genomes (KEGG) pathway revealed significantly associated pathways related cycle nicotine dependence, underscoring vital modulating proliferation metabolic activities. found be cells, particularly influencing T helper Th2 populations, exhibited an inverse relationship several checkpoint molecules, such PD-1 TIGIT. Insights from identified PSMD14-expressing types include dendritic (DC), monocytes, tissue stem cells. These findings highlight role evasion strategies prevalent LUAD. Additionally, notable increase protein recorded patients, correlating size, lymph node involvement, TNM classification. In summary, our underscores crucial LUAD, highlighting promise target therapy prognostic indicator. it opens up novel approaches future therapeutic interventions.
Язык: Английский
Процитировано
0
Frontiers in Immunology, Год журнала: 2025, Номер 16
Опубликована: Май 27, 2025
Background Esophageal squamous cell carcinoma (ESCC) is a highly heterogeneous malignancy. Traditional clinical staging systems have limited value in prognostic evaluation and treatment guidance, often failing to capture the profound impact of intratumoral diversity on patient outcomes. Single-cell RNA sequencing (scRNA-seq) provides new perspectives cellular makeup conditions tumor tissues, with promising implications for functional classification personalized therapeutic strategies esophageal cancer. Methods In this study, we integrated scRNA-seq data bulk RNA-seq profiles from cancer tissues construct comprehensive atlas, focusing transcriptional characteristics epithelial cells. Malignant cells were identified based copy number variation (CNV) features using inferCNV analysis. Their developmental states regulatory mechanisms further characterized via transcription factor activity inference (SCENIC) pseudotime trajectory analysis (Monocle). Based marker genes malignant subpopulations, developed multi-gene risk scoring model TCGA GEO (GSE53624) cohorts. The model’s predictive immune landscape, mutational features, drug sensitivity was also evaluated. Additionally, qRT-PCR conducted quantify expression levels ESCC tissue samples, evaluating their biological relevance. Functional roles key gene HMGB3 validated vitro through CCK-8 proliferation assays, Transwell invasion colony formation assays following knockdown lines. Results At single-cell level, ten major types six distinct subclusters, which exhibited pronounced heterogeneity cycle states, networks, differentiation trajectories. High CNV scores enrichment specific factors (e.g., FOXC1, E2F1, RUNX1) suggested proliferative immune-evasive phenotype. A six-gene (HMGB3, CHORDC1, CTSD, BTG2, MT1E, PHYHD1) showed strong accuracy overall survival GSE53624 Furthermore, score significant correlation an immunosuppressive microenvironment, increased purity, activation certain immune-related pathways. Analysis suggests that patients classified as low-risk could respond better various targeted therapies chemotherapeutic agents, underscoring potential revealed markedly suppressed proliferation, invasion, formation, supporting its oncogenic role progression. Conclusion This study systematically at resolution established markers effectively predicts prognosis, status, response. Combined experimental validation, our findings highlight pivotal progression provide novel theoretical practical framework individualized strategies.
Язык: Английский
Процитировано
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Discover Oncology, Год журнала: 2025, Номер 16(1)
Опубликована: Июнь 4, 2025
Язык: Английский
Процитировано
0