Emerging Diagnostic and Therapeutic Strategies for Urological Cancers

About this Research Topic

Background

Urological cancers, including bladder cancer, renal cell carcinoma, prostate cancer, and urothelial carcinoma, represent a group of malignancies with high global incidence and mortality rates. Despite recent advancements in diagnostic and therapeutic technologies, early detection of urological cancers remains challenging, and advanced-stage patients often experience treatment failure due to drug resistance and tumor heterogeneity. Current clinical interventions primarily include surgery, radiotherapy, chemotherapy, and targeted therapies. However, existing treatments exhibit significant variability in efficacy, with subsets of patients prone to developing resistance or recurrence. Furthermore, the lack of highly sensitive and specific diagnostic and prognostic biomarkers hinders the development of personalized treatment strategies for urological cancers.

In recent years, rapid progress in emerging technologies—such as liquid biopsy, multi-omics analysis, and artificial intelligence (AI)-driven imaging diagnostics—has provided novel avenues for precision medicine in urological cancers. Concurrently, clinical trials of innovative therapeutic strategies, including immune checkpoint inhibitors, oncolytic virus therapies, and epigenetic regulatory drugs, have shown promising results. However, further elucidation of their molecular mechanisms and optimization of patient stratification approaches are required. Therefore, systematic investigations into the molecular characteristics, tumor microenvironment (TME) regulation, and therapeutic resistance mechanisms are critical for developing effective diagnostic and therapeutic strategies.

This Research Topic aims to compile cutting-edge studies in the field of urological cancers, with a focus on the development and translation of novel diagnostic technologies, prognostic biomarkers, and innovative therapeutic strategies. By addressing key scientific questions such as TME dynamics, metabolic reprogramming, immune evasion mechanisms, and targeted drug resistance, this collection seeks to advance precision medicine in urological oncology. Specifically, research including but not limited to the following sub-topics is welcome

● Novel Diagnostic Technologies: Early diagnostic approaches based on liquid biopsy, metabolomics, or AI-driven imaging;
● Prognostic and Predictive Biomarkers: Driver gene mutations, epigenetic modifications, non-coding RNAs, or TME-associated biomarkers
● Innovative Therapeutic Targets: Drug development targeting cancer stem cells, immune checkpoints, metabolic enzymes, or DNA damage repair pathways
● Combination Therapies: Synergistic mechanisms and clinical applications of immunotherapy combined with targeted therapy, radiotherapy, or chemotherapy
● Resistance Mechanisms: Molecular underpinnings of resistance to targeted agents or immunotherapies, and strategies to overcome resistance
● Clinical Translation: Efficacy evaluation and patient stratification models based on real-world data or prospective cohorts
● Emerging Technologies: Applications of single-cell sequencing, spatial transcriptomics, or organoid models in mechanistic studies or drug screening


Please note: Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

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Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: urinary system tumor, biomarker, tumor microenvironment, diagnostic technology, therapeutic strategy

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