This study provides comprehensive insights into the cellular composition and molecular architecture of the PCa bone metastatic TME, revealing distinct cell populations, type-specific gene signatures, and cell-cell communication networks driving bone metastasis progression.
Abstract
Background
Prostate cancer (PCa) bone metastases cause significant morbidity and mortality in advanced disease. The tumor microenvironment (TME) of bone metastases drives disease progression and therapeutic resistance, yet comprehensive characterization of its cellular heterogeneity remains limited. This study aims to characterize cellular populations and molecular signatures of PCa bone metastases using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database.
Methods
scRNA-seq data from PCa bone metastasis samples were obtained from GEO. Quality control, normalization, dimensionality reduction, and cell type identification were performed using Seurat. Differential expression, pseudotime trajectory, pathway enrichment, gene regulatory network, and cell-cell communication analyses were conducted to investigate molecular mechanisms of bone metastasis progression.
Results
Single-cell analysis identified distinct cellular populations within the bone metastatic TME, including malignant epithelial cells, fibroblasts, endothelial cells, osteoblasts, osteoclasts, and immune cells. Clustering revealed heterogeneous transcriptional signatures, while pseudotime analysis uncovered developmental transitions between cell states. Key transcription factors, enriched pathways related to bone remodeling, angiogenesis, and immune regulation, and critical signaling interactions between cancer and stromal cells were identified.
Conclusion
This study provides comprehensive insights into the cellular composition and molecular architecture of the PCa bone metastatic TME, revealing distinct cell populations, type-specific gene signatures, and cell-cell communication networks driving bone metastasis progression.
Single-cell transcriptomics of publicly available BLCA data identifies two transcriptionally distinct fibroblast states in adjacent tissue and supports an exploratory ligand–receptor interaction framework, warranting prospective validation with primary CAF populations and adequately powered multi-specimen cohorts.
Yan-Dong He, Wen-Long Lu, Guan-Qun Ju et al.· Frontiers in Cell and Develo...· 0 citations
Metastatic breast cancer represents a major societal burden and is a main cause of cancer-related death in women, with limited rationale-based treatment options and often dismal outcomes. Intra-tumor heterogeneity, tumor-stromal interactions and clonal selection are considered to play a major role in metastasis formation and disease progression, but these processes remain incompletely understood. Leveraging spatial transcriptomics as cost-effective method for generating transcriptomics data at single-cell resolution, we present a single-cell spatial transcriptomics atlas of 126 tumor samples from 44 metastatic breast cancer patients, encompassing 520,850 cells from primary and metastatic lesions, with 171,766 cancer cells and 349,084 cells belonging to the tumor microenvironment. For most patients, multiple time-points of sample collection throughout metastatic disease progression were analyzed, allowing for detection of treatment-induced transcriptional changes driving therapy resistance within the tumor cell compartment. Distinct immune cell subpopulations were enriched upon progression following specific therapeutics and were predictive for hormone receptor loss. By inferring DNA copy number alterations from the single-cell transcriptomics data, we tracked subclonal tumor cell selection upon progression and identified critical transcriptomic features of outcompeting clones with future metastatic potential. Cumulatively, we present a unique single-cell spatial framework on metastatic breast cancer development and progression, in a highly complex systemic treatment landscape.
Z. Dauyey, A. Velds, R. Gobits et al.· medRxiv· 0 citations
Lung cancer remains one of the leading causes of cancer-related mortality worldwide; beyond its rising incidence, its marked molecular heterogeneity and complex tumor microenvironment (TME) hinder treatment response and drive resistance, contributing directly to its high mortality rate. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) provide complementary approaches for dissecting these features. scRNA-seq enables high-resolution analysis of cellular diversity and transcriptional states but requires tissue dissociation and therefore loses spatial context. In contrast, ST preserves tissue architecture and provides insights into how gene-expression programs within the TME are organized, although no currently available spatial platform combines whole-transcriptome coverage with true single-cell resolution over large tissue areas. Together, these technologies have enabled detailed mapping of tumor, immune and stromal populations and of their spatial interactions, revealing functionally distinct cellular niches that contribute to immune evasion, metastasis and response to therapy. In this narrative review we organize the primary literature around a single question, how spatially structured cellular ecosystems, rather than individual cell types, determine therapeutic response and resistance in lung cancer - and we explicitly separate observations that are reproducible across independent cohorts and platforms from those that remain confined to single studies. We further summarize the technical, analytical and logistic barriers that currently prevent spatially resolved signatures from entering routine diagnostic pathology. Understanding dysregulated pathways and spatially constrained intercellular communication within the TME helps identify candidate biomarkers and may support the identification of therapeutic approaches directed at tumor-intrinsic programs as well as at microenvironment-driven resistance mechanisms.
C. Braicu, R. Pîrlog, A. Nutu et al.· Biochimica et biophysica act...· 0 citations
This study identified UBE2C+ proliferative tumor cells as a functionally relevant malignant subpopulation in SCLC and links this state to immune-stromal communication networks within the tumor microenvironment and provides a systems-level framework for investigating the cancer-immunity regulome in SCLC.
Hong-Ling Jia, Yongxuan An, Bing Chen et al.· Frontiers in Immunology· 0 citations
Bone metastases showed marked suppression of tumor-intrinsic type I interferon (IFN-I) signaling and loss of antigen presentation, features that were strongly associated with reduced bone metastasis-free survival and could inform precision therapeutic strategies for PCa.
Katie L. Owen, L. Gearing, B. Niranjan et al.· Cancer Research· 0 citations
Abstract Background Brain metastasis (BM) in renal cell carcinoma (RCC) remains a major clinical challenge and is frequently resistant to immune checkpoint inhibitor (ICI) therapy. The metabolic and immunological adaptations enabling tumor survival within the brain microenvironment remain poorly defined. A comprehensive, brain-specific characterization of the tumor–microenvironment is needed to understand immune dysfunction and therapeutic resistance in RCC BM. Methods We generated a large single-nucleus RNA sequencing dataset comprising 184,037 nuclei from 14 RCC BM patients, including matched primary kidney tumors (n = 8) and extracranial metastases (n = 5). Cell populations were identified across tumor, immune, and stromal compartments. Comparative analyses identified BM-specific transcriptional, metabolic, and immune programs. Spatial transcriptomic profiling was conducted on 12 BM samples (13,128 cells) to validate cellular localization and interactions. Ligand–receptor inference was applied to reconstruct intercellular communication. Results RCC BM is associated with extensive immune remodeling of the brain microenvironment and stromal involvement. Tumor cells show neural-like features with evidence of neuroglial cells infiltration, while stromal populations display immunomodulatory phenotypes beyond structural roles. This landscape includes expansion of immunosuppressive myeloid populations, depletion of dendritic cells, absence of tertiary lymphoid structures, and CD8+ T cells exhibiting terminal exhaustion. Across compartments, we observed coordinated metabolic shifts, including enhanced OXPHOS and MYC-associated programs. Spatial and ligand–receptor analyses confirmed interactions providing mechanistic insight and informing therapeutic targeting. Conclusion RCC BM represents a biologically distinct tumor entity shaped by neural adaptation, metabolic reprogramming, and immune dysfunction. Immunosuppressive myeloid signaling, T cell exhaustion, and impaired antigen presentation establish a brain-specific microenvironment limiting immune checkpoint efficacy. These findings highlight context-dependent resistance mechanisms and identify actionable pathways to guide brain-tailored immunotherapy. Importantly, this work supported clinical trials approval testing lenvatinib plus pembrolizumab and zanzalitinib in RCC BM patients.
M. I. Ali, Z. Akpinar, Jose A. Ovando-Ricardez et al.· Neuro-Oncology Advances· 0 citations
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