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Published on: February 24, 2014
Genetic polymorphisms and platinum-induced hematological toxicity: a systematic review
Yi Zheng1, Mimi Tang2, Zheng Deng3,4
1Hunan Provincial Maternal and Child Health Care Hospital, Changsha, China.
This review identifies genetic biomarkers for platinum-induced hematological toxicity, highlighting promising variants like GSTP1 rs1695 and ERCC1 rs11615. Further validation is needed due to inconsistent results and methodological limitations.
Area of Science:
- Pharmacogenomics
- Oncology
- Clinical Genetics
Background:
- Platinum-based chemotherapy causes severe hematological toxicity, impacting treatment adherence.
- Genetic variations may influence this toxicity, but existing research is controversial and lacks comprehensive review.
- Identifying reliable genetic biomarkers is crucial for personalized cancer treatment.
Purpose of the Study:
- To systematically review and identify genetic biomarkers associated with platinum-induced hematological toxicity in cancer patients.
- To provide an overview of current evidence and highlight potential genetic markers for further investigation.
Main Methods:
- Systematic literature search of PubMed, Embase, and Web of Science databases up to January 28, 2022.
- Inclusion of studies evaluating genetic variants and platinum-related hematological toxicity with defined endpoints and scoring systems.
- Quality assessment using the STREGA checklist and narrative synthesis of results.
Main Results:
- 83 studies analyzed, examining over 682 single-nucleotide polymorphisms (SNPs) across 110 genes.
- Inconsistent findings and methodological issues (small sample size, diverse endpoints) were noted.
- 11 SNPs in 10 genes showed consistent results across multiple populations, with GSTP1 rs1695, ERCC1 rs11615, ERCC1 rs3212986, and XRCC1 rs25487 being most promising.
Conclusions:
- Several genetic variations show potential as biomarkers for platinum-induced hematological toxicity.
- Methodological limitations necessitate validation in larger, well-designed studies.
- Future research should focus on robust methodologies for definitive biomarker identification.
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