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Perfect match: mTOR inhibitors and tuberous sclerosis complex
Cong Luo1, Wen-Rui Ye2, Wei Shi3
1Department of Urology, Disorders of Tuberous Sclerosis Complex (TSC) Multidisciplinary Team, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha City, 410008, Hunan Province, People's Republic of China.
Tuberous sclerosis complex (TSC) treatment with mTOR inhibitors shows promise but faces challenges with side effects and varied patient responses. Predictive indicators are needed to optimize therapy for TSC patients.
Area of Science:
- Genetics and Molecular Biology
- Neurology
- Pharmacology
Background:
- Tuberous sclerosis complex (TSC) is an autosomal dominant disorder with multisystemic manifestations.
- Neurological and organ dysfunction in TSC significantly impacts patient quality of life and survival.
- Clinical features of TSC are largely attributed to the hyperactive mammalian target of rapamycin (mTOR) pathway due to TSC1/TSC2 mutations.
Purpose of the Study:
- To review the current use of mTOR inhibitors in TSC management.
- To evaluate the efficacy and safety of mTOR inhibitors for TSC.
- To highlight the need for predictive biomarkers for mTOR inhibitor response in TSC.
Main Methods:
- Literature review of studies on mTOR inhibitors in TSC.
- Analysis of clinical trial data regarding efficacy and adverse events.
- Synthesis of current understanding of mTOR pathway in TSC pathogenesis.
Main Results:
- mTOR inhibitors (rapamycin/everolimus) offer therapeutic potential for TSC.
- Adverse events (stomatitis, infections, menstrual disorders) and variable patient responses limit widespread use.
- Lack of reliable indicators to predict treatment efficacy is a significant challenge.
Conclusions:
- mTOR inhibitors are valuable in TSC treatment but require careful monitoring due to side effects and variable efficacy.
- Further research is needed to identify biomarkers for predicting patient response to mTOR inhibitors.
- Optimizing TSC management necessitates personalized treatment strategies guided by predictive indicators.
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