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Updated: Jul 17, 2025
06:38
A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
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Gestational Renal Cell Cancer - An Update.
Aydin Caglayan1, Rukhshana Dina Rabbani1, Elisabet Sanchez1
1Department of Medical Oncology, Medway NHS Foundation Trust, Kent, U.K.
Anticancer Research
|August 30, 2023
Summary
Gestational renal cell carcinoma (RCC) is rare and challenging to diagnose during pregnancy. Management requires careful consideration of maternal and fetal risks due to limited treatment options.
Area of Science:
- Oncology
- Nephrology
- Obstetrics & Gynecology
Background:
- Gestational renal cell carcinoma (RCC) is a rare condition presenting diagnostic and clinical challenges.
- Symptoms are often absent or mimic normal pregnancy changes, leading to detection via antenatal ultrasonography.
- Limited imaging and treatment options exist due to risks to the fetus and pregnancy.
Purpose of the Study:
- To provide a comprehensive review of gestational RCC.
- To cover epidemiology, etiology, clinical presentation, diagnosis, prognosis, and management.
- To highlight the need for a multidisciplinary approach due to lack of established guidelines.
Main Methods:
- Literature review of gestational renal cell carcinoma.
- Analysis of diagnostic and management strategies.
- Discussion of surgical advancements and treatment considerations.
Main Results:
- Gestational RCC often detected incidentally during pregnancy via ultrasound.
- Management necessitates balancing maternal/neonatal risks and patient autonomy.
- Surgical techniques are evolving towards minimally invasive approaches like laparoscopy and robotics.
- Metastatic disease may warrant pregnancy termination to prioritize RCC treatment.
Conclusions:
- Gestational RCC requires a multidisciplinary approach due to its rarity and complexity.
- Advances in surgical techniques offer improved management options.
- Further research and guideline development are needed for optimal patient care.
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