Single nucleotide polymorphisms to predict acute radiation dermatitis in breast cancer patients: A systematic review and meta-analysis

Beatriz Regina Lima de Aguiar; Elaine Barros Ferreira; Ana Gabriela Costa Normando; Juliana F Mazzeu; Daniele Xavier Assad; Eliete Neves Silva Guerra; Paula Elaine Diniz Dos Reis

doi:10.1016/j.critrevonc.2022.103651

Single nucleotide polymorphisms to predict acute radiation dermatitis in breast cancer patients: A systematic review and meta-analysis

Crit Rev Oncol Hematol. 2022 May:173:103651. doi: 10.1016/j.critrevonc.2022.103651. Epub 2022 Mar 15.

Authors

Beatriz Regina Lima de Aguiar¹, Elaine Barros Ferreira², Ana Gabriela Costa Normando³, Juliana F Mazzeu⁴, Daniele Xavier Assad⁵, Eliete Neves Silva Guerra⁶, Paula Elaine Diniz Dos Reis⁷

Affiliations

¹ Health Science Graduate Program, School of Health Sciences, University of Brasilia, Brasilia, DF, Brazil. Electronic address: [email protected].
² Nursing Department, School of Health Sciences, University of Brasilia, Brasilia, DF, Brazil. Electronic address: [email protected].
³ Oral Diagnosis Department, Piracicaba Dental School, University of Campinas, Campinas, SP, Brazil. Electronic address: [email protected].
⁴ Laboratory of Clinical Genetics, Faculty of Medicine, University of Brasilia, Brasilia, DF, Brazil. Electronic address: [email protected].
⁵ Medical Oncology Department, Sírio-Libanês Hospital, Brasilia, DF, Brazil. Electronic address: [email protected].
⁶ Laboratory of Oral Histopathology, School of Health Sciences, University of Brasilia, Brasilia, DF, Brazil. Electronic address: [email protected].
⁷ Nursing Department, School of Health Sciences,University of Brasília, Brasília, DF, Brazil. Electronic address: [email protected].

PMID: 35301098
DOI: 10.1016/j.critrevonc.2022.103651

Abstract

Purpose: To identify Single Nucleotide Polymorphisms (SNPs) that can predict acute radiation dermatitis (RD) in breast cancer patients (BC), and the association between SNPs and RD severity.

Methods: We performed the search in seven databases and the gray literature, and a meta-analysis to assess SNPs in patients with RD and to evaluate the association between SNPs and severe RD.

Results: We included sixteen single-arm cohort studies with 4742 BC. The most prevalent SNPs were the TGFβ1 rs1800469 (41%), and the GSTA1 rs3957356 (36%). Seven genotypes were associated with severe RD (PTTG1 rs3811999-CC; PTTG1 rs2961950-AA; MAD2L2 rs2294638-GG; MAT1A rs2282367-GG; GSTA1 rs3957356-CT; CD44 rs8193-CT; SH3GL1 rs243336-GC) and five SNPs were associated with lower RD (PTTG1 rs2961952-GG; CD44 rs8193-CC; PTTG1 rs3811999-CT; MAT1A rs2282367-GA; OGG1 rs2075747-AA).

Conclusions: The genotyping of SNPs more prevalent may be a strategy for predicting RD in BC, and some genotypes (GSTA1 rs3957356-CT; MAT1A rs2282367-GG) are associated with severe RD.

Keywords: Breast Neoplasms; Genetic Markers; Meta-analysis; Radiodermatitis; Radiotherapy; Single Nucleotide Polymorphisms; Systematic review.

Publication types

Meta-Analysis
Review
Systematic Review

MeSH terms

Breast Neoplasms* / genetics
Breast Neoplasms* / radiotherapy
Female
Genetic Predisposition to Disease
Genotype
Humans
Mad2 Proteins / genetics
Polymorphism, Single Nucleotide
Radiodermatitis*
Risk Factors

Substances

MAD2L2 protein, human
Mad2 Proteins