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An Orthotopic Bladder Tumor Model and the Evaluation of Intravesical saRNA Treatment
Published on: July 28, 2012
Neoadjuvant Systemic Therapy in Kidney and Bladder Cancer: Current Evidence and Emerging Paradigms
Rana R McKay1, Asha Tipirneni2, Rick Bangs3
1Moores Cancer Center, University of California San Diego, La Jolla, CA.
Abstract:
Neoadjuvant systemic therapy has emerged as a strategy to improve outcomes in high-risk localized genitourinary malignancies. In bladder cancer, neoadjuvant cisplatin-based chemotherapy with or without immunotherapy is standard of care, with pathologic complete response (pCR) serving as a validated surrogate for survival after chemotherapy and a promising potential surrogate for survival after other neoadjuvant treatments like immunotherapy. Enfortumab vedotin and immune checkpoint inhibitors have expanded treatment options, with ongoing studies evaluating novel adjuvant approaches tailored to patients' postoperative circulating tumor DNA. In renal cell carcinoma (RCC), the field is nascent, no approved neoadjuvant regimens exist, and treatment outside clinical trials is not recommended. Early trials of tyrosine kinase inhibitor monotherapy showed limited pathologic responses, while immune checkpoint inhibitor-based combinations have demonstrated feasibility, safety, and the capacity to induce pathologic responses including pCR. Critical gaps remain in both diseases. In RCC, standardized pathologic response criteria are lacking, and surrogacy between pathologic end points and long-term outcomes has not been established. In bladder cancer, optimal post-pCR management and integration of novel agents require further study. Emerging technologies, particularly artificial intelligence (AI)-driven digital pathology, offer potential to enhance diagnosis, refine prognostic stratification, and predict treatment response, although prospective validation across diverse populations is needed. This chapter examines neoadjuvant therapy and pathologic response assessment in RCC and bladder cancer, explores pathologic biomarker development including AI applications, and highlights future directions to optimize therapeutic sequencing and outcomes.
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