
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Acta Neuropathologica Communications, Journal Year: 2025, Volume and Issue: 13(1)
Published: Jan. 11, 2025
Abstract Glioblastoma (GBM) is a highly aggressive adult brain cancer, characterised by poor prognosis and dismal five-year survival rate. Despite significant knowledge gains in tumour biology, meaningful advances patient remain elusive. The field of neuro-oncology faces many disease obstacles, one being the paucity faithful models to advance preclinical research guide personalised medicine approaches. Recent technological developments have permitted maintenance, expansion cryopreservation GBM explant organoid (GBO) tissue. GBOs represent translational leap forward are currently state-of-the-art 3D vitro culture system, retaining cancer heterogeneity, transiently maintaining immune infiltrate microenvironment (TME). Here, we provide review existing technologies, vivo xenograft approaches, evaluate in-detail key advantages limitations this rapidly emerging technology, consider solutions overcome these difficulties. hold promise, with potential emerge as tool synergise enhance next-generation omics efforts approaches for patients into future.
Language: Английский
Citations
1International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(2), P. 579 - 579
Published: Jan. 11, 2025
The field of translational bioinformatics is rapidly evolving, driving the convergence molecular sciences and computational methods with their applications in industrial clinical practice [...]
Language: Английский
Citations
0International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(6), P. 2447 - 2447
Published: March 9, 2025
Advances in single-cell multi-omics technologies have deepened our understanding of cancer biology by integrating genomic, transcriptomic, epigenomic, and proteomic data at resolution. These provide unprecedented insights into tumour heterogeneity, microenvironment, mechanisms therapeutic resistance, enabling the development precision medicine strategies. The emerging field genomic has improved patient outcomes. However, most clinical applications still depend on bulk approaches, which fail to directly capture variations driving cellular heterogeneity. In this review, we explore common platforms discuss key analytical steps for integration. Furthermore, highlight knowledge resistance immune evasion, potential new innovations informed multi-omics. Finally, future directions application technologies. By bridging gap between technological advancements implementation, review provides a roadmap leveraging improve treatment
Language: Английский
Citations
0Journal for ImmunoTherapy of Cancer, Journal Year: 2025, Volume and Issue: 13(3), P. e011002 - e011002
Published: March 1, 2025
The intrinsic characteristics of metastatic tumors are great importance in terms the development antimetastatic treatment strategies. Elucidation from a spatial immune perspective has potential to provide more comprehensive understanding mechanisms underlying escape, effectively addressing limitations relying solely on analysis cell subpopulation transcriptional profiles. Advances omics technology enable researchers precisely analyze precious liver metastasis samples high-throughput manner, revealing alterations distribution induced by and exploring molecular basis remodeling process. aggregation specific subpopulations distinct regions not only modifies local but also concurrently affects global biological behaviors tumors. Identifying pretreatment or early-stage tissue may achieve accurate clinical predictions. Moreover, developing strategies that target is promising avenue for future therapy.
Language: Английский
Citations
0Cell Reports, Journal Year: 2025, Volume and Issue: 44(4), P. 115554 - 115554
Published: April 1, 2025
Multiplex immunofluorescence (mIF) is a promising tool for immunotherapy biomarker discovery in melanoma and other solid tumors. mIF captures detailed phenotypic information of immune cells the tumor microenvironment, as well spatial data that can reveal biologically relevant interactions among cell types. Given complexity data, development automated analysis pipelines crucial advancing discovery. In pre-treatment samples from 50 patients treated with checkpoint inhibitors (ICIs), higher stromal B percentage associated clinical benefit ICI therapy. The automatic detection aggregates DBSCAN, novel application computer-aided machine learning algorithm, demonstrates potential enhanced accuracy compared to pathologist assessment lymphoid aggregates. TCF1+ LAG3- T subpopulations are enriched near cells, suggesting functional interactions. These analyses provide roadmap further biomarkers diseases.
Language: Английский
Citations
0Metabolites, Journal Year: 2025, Volume and Issue: 15(3), P. 144 - 144
Published: Feb. 21, 2025
Amino acids are crucial components of proteins, key molecules in cellular physiology and homeostasis. However, they also involved a variety other mechanisms, such as energy homeostasis, nitrogen exchange, further synthesis bioactive compounds, production nucleotides, or activation signaling pathways. Moreover, amino their metabolites have immunoregulatory properties, significantly affecting the behavior immune cells. Immunotherapy is one oncological treatment methods that improves cytotoxic properties one’s own system. Thus, enzymes catalyzing acid metabolism, together with themselves, can affect antitumor responses to immunotherapy. In this review, we will discuss involvement tryptophan, glutamine, asparagine metabolism cells targeted by immunotherapy summarize results most recent investigations on impact
Language: Английский
Citations
0Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 28, 2025
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, underscoring the urgent need for novel biomarkers and therapeutic targets. Through transcriptomic analysis 4456 genes in TCGA-LUAD cohorts, we identified RBMS3 as significantly downregulated tumor suppressor (log2 fold change = -1.82, adjusted P 3.2 × 10⁻5). Clinically, elevated expression was independently associated with improved overall survival (HR 0.766, 95% CI 0.602-0.973, 0.029), validated by Kaplan-Meier (Log-rank 0.027). Functionally, overexpression A549 PC-9 LUAD cells suppressed invasion (66.53% 52.46% reduction, respectively; < 0.01) induced apoptosis (total increased 6.53% 8.57%; 0.05). Cell cycle revealed accelerated G1-to-S phase transition, G1-phase proportions decreasing from 44.6 to 36.87% (P 49.83 37.13% 0.01). TIMER-based correlation demonstrated positive association between immune cell infiltration, regression line indicating significant correlations B (cor 0.16, 4.25 10⁻4), CD8 + T 0.214, 1.86 10⁻⁶), CD4 0.24, 8.99 10⁻⁸), macrophages 0.341, 1.07 10⁻14), neutrophils 0.277, 5.71 10⁻10), dendritic 0.369, 3.70 10⁻17). These findings underscore RBMS3's dual role microenvironment modulator, offering insights prognosis therapy.
Language: Английский
Citations
0medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 10, 2024
SUMMARY Quantitative assessment of multiplex immunofluorescence (mIF) data represents a powerful tool for immunotherapy biomarker discovery in melanoma and other solid tumors. In addition to providing detailed phenotypic information immune cells the tumor microenvironment, these datasets contain spatial that can reveal biologically relevant interactions among cell types. To assess quantitative mIF analysis as platform discovery, we used 12-plex panel characterize samples collected from 50 patients with prior treatment checkpoint inhibitors (ICI). Consistent studies, identified strong association between stromal B percentage response ICI therapy. We then compared pathologist lymphoid aggregates density based clustering algorithm, DBSCAN, both automatically detect quantify their size, morphology, distance tumor. Spatial neighborhood TCF1+ LAG3-T subpopulations enriched near cells. These analyses provide roadmap further development validation biomarkers diseases.
Language: Английский
Citations
2bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 4, 2024
Abstract In the ever-changing world of digital pathology, being able to extract a maximum amount information from patient tissue sample is paramount importance for better diagnosis, disease characterization, and therapeutic strategies. Recent technologies such as multiplex immunofluorescence imaging spatial transcriptomic now enable deep analysis protein gene expression while retaining context tissue. Here, we describe an innovative approach combining 34-protein Phenocycler panel transcriptome using Visium on single head neck squamous cell carcinoma section. While reveals complexity immune phenotypes involved in disease, intricate cellular states cancer cells that coexist within patient’s tumor. Finally, integrating both omics modalities, uncover unique comparison spatially resolved subspaces.
Language: Английский
Citations
1Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
Language: Английский
Citations
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