Single-Cell Sequencing in Genitourinary Malignancies

Role of multi‑omics in advancing the understanding and treatment of prostate cancer (Review)

The application of multi‑omics methodologies, encompassing genomics, transcriptomics, proteomics, metabolomics and integrative genomics, has markedly enhanced the understanding of prostate cancer (PCa). These methods have facilitated the identification of molecular pathways and biomarkers crucial for the early detection, prognostic evaluation and personalized treatment of PCa. Studies using multi‑omics technologies have elucidated how alterations in gene expression and protein interactions contribute to PCa progression and treatment resistance. Furthermore, the integration of multi‑omics data has been used in the identification of novel therapeutic targets and the development of innovative treatment modalities, such as precision medicine. The evolving landscape of multi‑omics research holds promise for not only deepening the understanding of PCa biology but also for fostering the development of more effective and tailored therapeutic interventions, ultimately improving patient outcomes. The present review aims to synthesize current findings from multi‑omics studies associated with PCa and to assess their implications for the improvement of patient management and therapeutic outcomes. The insights provided may guide future research directions and clinical practices in the fight against PCa.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Cancer diagnosis and analysis devices based on multimolecular crowding

The study of the multimolecular crowding around cancer cells has opened up the possibility of developing new devices for cancer diagnosis and analysis through the measurement of intercellular communication related to cell proliferation and invasive metastasis associated with cancer malignancy. In particular, cells and extracellular vesicles that flow into the bloodstream contain metabolites and secreted products of the cancer microenvironment. These are positioned as targets for the development of new devices for the understanding and application of multimolecular crowding around cancer cells. Examples include the separation analysis of cancer cells in blood for the next generation of less invasive testing techniques, and mapping analysis using Raman scattering to detect cancer cells without staining. Another example is the evaluation of the relationship between exosomes and cancer traits for the exploration of new anti-cancer drugs, and the commercialization of exosome separation devices for ultra-early cancer diagnosis. The development of nanobiodevice engineering, which applies multimolecular crowding to conventional nanobioscience, is expected to contribute to the diagnosis and analysis of various diseases in the future.