2026· American journal of clinical and experimental urology· Vol 14 3, pp.
64-85
· 2 citations
Medicine
TL;DR
Recent discoveries from single-cell and spatial analyses are summarized, their implications for biomarker development and treatment stratification are discussed, and ongoing technical challenges are outlined, including standardization, reproducibility, and clinical scalability.
Abstract
Prostate cancer is a heterogeneous disease shaped by evolving cellular states within a spatially organized tumor ecosystem. Advances in single-cell RNA-sequencing, single-nucleus sequencing, and spatial transcriptomics have facilitated high-resolution dissection of epithelial lineage hierarchies, tumor-associated luminal states, and microenvironmental remodeling. These approaches have revealed that progression from androgen receptor-dependent adenocarcinoma to castration-resistant prostate cancer and the development of neuroendocrine phenotypes reflect lineage plasticity and epigenetic reprogramming rather than simple linear genetic progression. Single-cell studies have indicated that immunosuppressive niches, cancer-associated fibroblast heterogeneity, endothelial activation, and metabolic adaptation collectively contribute to therapeutic resistance. The integration of multi-omics data with spatial context has begun to redefine prostate cancer taxonomy based on cellular state composition and ecosystem architecture. In this review, we summarize recent discoveries from single-cell and spatial analyses, discuss their implications for biomarker development and treatment stratification, and outline ongoing technical challenges, including standardization, reproducibility, and clinical scalability. Overall, this review provides valuable insights for the development of a state-informed framework to understand prostate cancer progression and guide precision oncology strategies.
Prostate cancer is a hormone-driven malignancy, but its clinical behavior cannot be explained by androgen receptor (AR) signaling alone. Single-cell and spatial omics are redefining prostate cancer as an evolving metabolic-immune ecosystem in which malignant epithelial states, stromal niches, myeloid programs, T-cell exclusion, vascular remodeling, and treatment-imposed selection pressures jointly shape progression and resistance. These technologies have resolved the normal prostate epithelial hierarchy, pre-existing castration-resistant-like cells, basal-like, club-like, and hillock-like programs, neuroendocrine transformation states, immunosuppressive macrophage populations, fibroblast states, and spatial neighborhoods that are difficult to detect by bulk sequencing. Treatment-associated changes have been characterized most directly in androgen-axis and immune contexts, whereas evidence related to taxanes, DNA damage response (DDR)-targeted therapy, and radioligand therapy remains emerging or hypothesis-generating. This review synthesizes single-cell and spatial omics evidence for metabolic-immune ecosystems in prostate cancer, emphasizing the transition from androgen dependence to castration resistance, lineage plasticity, metastatic niche adaptation, and therapy resistance. We argue that the next translational step is not simply to catalog additional cell types, but to connect longitudinal cell-state maps, spatially resolved metabolic dependencies, immune-neighborhood biomarkers, and mechanism-matched combination therapies.
How single-cell and spatial omics are reshaping the understanding of metabolic reprogramming and tumor–immune ecosystems in NSCLC is discussed, and how these findings may inform biomarker discovery, patient stratification, resistance monitoring, and rational combination therapy are discussed.
Zhenzhen Lian, Xu-Jing Wu, Yangyang Zhou et al.· Frontiers in Immunology· 0 citations
Aging is a major risk factor for the development of many cancers, yet the tissue-level mechanisms linking physiological aging to tumor progression remain unclear. Although age-related accumulation of genetic mutations contributes to tumorigenesis, increasing evidence indicates that the aging tissue microenvironment also plays a critical role in shaping cancer susceptibility. In this study, we integrated single-cell RNA sequencing and spatial transcriptomic datasets from healthy human skin and major skin cancers, including melanoma, squamous cell carcinoma, and basal cell carcinoma, to define cell-type-specific aging programs and assess their representation in tumor-associated microenvironments. In healthy skin, aging was associated with widespread but cell-type-specific transcriptional remodeling across epithelial, immune, vascular, and stromal compartments, involving pathways related to inflammation, extracellular matrix organization, and intercellular communication. Projection of these aging signatures into skin cancer datasets revealed that aging-associated programs were not restricted to immune cells but were also prominent in stromal compartments. Age-adjusted survival analysis in melanoma further identified the fibroblast aging program as the most prominent stromal signature, with higher program activity being associated with poor patient outcomes, motivating a focused analysis of fibroblast remodeling in skin cancers. Within this fibroblast-centered framework, we found that SFRP2-expressing fibroblasts accumulated in aged skin and were also enriched in tumor-associated stroma, suggesting that this pre-existing fibroblast state may become incorporated into and potentially support the tumor microenvironment during skin cancer development. Spatial analyses in basal cell carcinoma and squamous cell carcinoma showed that SFRP2-associated fibroblast signals were enriched near tumor-associated regions and WNT-active niches. Additional spatial proxy analyses and expression profiling of matrix-remodeling and growth factor-related genes further supported the association of this fibroblast state with tumor-associated stromal remodeling. Together, our findings suggest that aging-associated fibroblast remodeling may contribute to a tumor-permissive skin microenvironment and provide a framework for understanding how aging tissue ecosystems influence skin cancer progression.
D. Pan, Haibin Wu· Frontiers in Medicine· 0 citations
This review synthesizes key advances in understanding tumor heterogeneity: from its cellular origins and molecular mechanisms to its multidimensional manifestation in the tumor microenvironment and from metastatic heterogeneity to the fundamental causes of treatment resistance.
Jianhong Zhang, Heng Li, S. Ru et al.· Signal Transduction and Targ...· 0 citations
ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive human malignancies and has an extremely poor prognosis. Its progression is largely driven by a highly complex and immunosuppressive tumor microenvironment (TME), highlighting the urgent need for a deeper understanding of its molecular mechanisms. Recent advances in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have provided unprecedented opportunities to dissect cellular heterogeneity, spatial organization, and gene expression dynamics within the TME. In this review, we summarize the major scRNA-seq and ST technologies and their unique strengths in cancer research and highlight their integrated applications in revealing PDAC heterogeneity, stromal–immune interactions, and mechanisms of therapeutic resistance. We further discuss how these approaches can inform biomarker discovery and guide the development of novel therapeutic strategies. Together, these findings suggest that integrated single-cell and spatial transcriptomics offers transformative potential to advance precision oncology and improve outcomes for patients with pancreatic cancer.
Mengting Luo, Feng Shen, Wanli Xu et al.· Cancer Biology & Therapy· 0 citations
Background: Prostate cancer (PCa) exhibits strong multidimensional heterogeneity. The dynamic evolution of Luminal subsets and their crosstalk with the tumor microenvironment (TME) during malignant progression remain poorly understood. Conventional single-cell transcriptomics lacks spatial context, while low-resolution spatial technologies cannot resolve single-cell and subcellular interactions. This study aimed to map a high-resolution spatial transcriptomic atlas to characterize Luminal subset heterogeneity and stromal crosstalk across progressive PCa lesions. Methods: We used high-resolution CosMx spatial molecular imaging (SMI) to profile 6 treatment-naive PCa patients and constructed a single-cell spatial transcriptomic atlas covering 385 fields of view and 154,168 high-quality cells. Unsupervised clustering, functional enrichment, cell–cell communication analysis, and flow cytometry were performed. Results: We identified 28 cell clusters, including 8 Luminal subsets (0–7) and 9 Fibroblast subsets (0–8). Pathological microregion-specific spatial distribution was observed: Luminal 0–2 dominated in BPH/PIN, while Luminal 3–7 were enriched in poorly differentiated PCa and vacuolated adenocarcinoma. These subsets were functionally linked to androgen resistance, EMT, and immune regulation. COLLAGEN, FN1, and LAMININ were identified as key pathways mediating pathological-specific tumor–stromal crosstalk. Flow cytometry verified T-cell exhaustion and immunosuppression in the TME. Conclusions: This study delineated pathological microregion-specific Luminal subset plasticity and dynamic epithelial–stromal communication across the full spectrum of PCa lesions. The uncovered molecular signatures offered mechanistic clues linking EMT, hormone resistance, and local immune status during lesion evolution. Our spatial atlas provided preliminary molecular evidence to support pathological stratification and targeted precision therapeutic strategies for PCa.