| Literature DB >> 36230587 |
Renske Altena1,2, Svetlana Bajalica-Lagercrantz1,3, Andri Papakonstantinou1,2,4.
Abstract
Pharmacogenomics is an emerging field in oncology, one that could provide valuable input on identifying patients with inherent risk of toxicity, thus allowing for treatment tailoring and personalization on the basis of the clinical and genetic characteristics of a patient. Cardiotoxicity is a well-known side effect of anthracyclines and anti-HER2 agents, although at a much lower incidence for the latter. Data on single-nucleotide polymorphisms related to cardiotoxicity are emerging but are still scarce, mostly being of retrospective character and heterogeneous. A literature review was performed, aiming to describe current knowledge in pharmacogenomics and prediction of cardiotoxicity related to breast cancer systemic therapies and radiotherapies. Most available data regard genes encoding various enzymes related to anthracycline metabolism and HER2 polymorphisms. The available data are presented, together with the challenges and open questions in the field.Entities:
Keywords: anti-HER2; breast cancer; cardiotoxicity; chemotherapy; hormonal therapy; immune checkpoint inhibitors; pharmacogenomics; polygenic risk scores; single-nucleotide polymorphisms (SNPs)
Year: 2022 PMID: 36230587 PMCID: PMC9563074 DOI: 10.3390/cancers14194665
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.575
Study characteristics, endpoint definition, and important findings in correlating genetic polymorphisms and risk for cardiotoxicity.
| Author, Year | Number of Patients | Gene | SNPs | Correlation to | Odds Ratio | Definition of Cardiotoxicity Endpoints |
|---|---|---|---|---|---|---|
| Drug: anthracyclines | ||||||
| Yang, 2021 | 41 studies | rs4673 | ⇑ | 1.93 (1.13–3.30) | Depending on the study | |
| Leong, 2017 | 28 studies |
| rs8187710 | ⇑ | 2.2 (1.36–3.54) | Depending on the study |
| Vulsteke, 2015 | 877 |
| rs246221 | ⇑ | 1.6 (1.1–2.3) | Asymptomatic decrease in LVEF >10% or cardiac failure grade ≥3 |
| Li, 2019 | 427 | rs7668258 | ⇑ | NR | LVEF decline ≥10% to <53%, heart failure, acute coronary artery syndrome, or fatal arrhythmia | |
| Hertz, 2016 | 166 |
| rs1056892 | ⇑ | NR | LVEF reduction to <55% |
| Lang, 2021 | 92 |
| rs1056892 | LVEF reduction from | 2.55 (0.26–25.17) for GG vs. AA; | Asymptomatic LVEF |
|
| ||||||
| Leong, 2019 | 35 studies | rs1136201 | ⇔ | 2.43 (1.17–5.06) | LVEF decline ≥10% from baseline and <53% or heart failure, acute coronary artery syndrome, or fatal | |
| Gómez Peña, 2015 | 4 studies | rs1136201 | ⇑ | 5.35 (2.55–11.73) | Depending on the study | |
| Peddi, 2022 | 666 | No polymorphisms | LVEF decline ≥10% or | |||
| Vazdar, 2021 | 177 | rs1136201 | ⇔ | NR | LVEF and diastolic dysfunction; cut-offs not clarified | |
| Stanton, 2015 | 140 | Pro1170Ala | ⇑ | 2.60 (1.02–6.62) | Symptomatic heart failure or LVEF decline ≥15% or LVEF decline ≥10% and <55% | |
| Marinko, 2022 | 101 |
| rs854560 | ⇓ | 0.35 (0.15–0.83) | NT-proBNP increase to ≥125 ng/L |
| Tan, 2020 | 91 | rs1136201 | ⇑ | 7.99 (95% CI NA; | LVEF decline ≥ 10% from baseline and <53%, or heart failure, acute coronary artery syndrome, or fatal | |
Abbreviations. ABCB1: ATP binding cassette subfamily B member 1, ABCC1: ATP binding cassette subfamily C member 1, ABCC2: ATP binding cassette subfamily C member 2, CBR3: cytosolic carbonyl reductases, CI: confidence interval, CYBA: cytochrome b-245 alpha chain, CYP3A5: cytochrome P450 family 3 subfamily A member 5, GSTP1: glutathione S-transferase pi 1, HER2: human epidermal growth factor receptor-2, LVEF: left ventricle ejection fraction, NA: not available, NT-proBNP: N-terminal prohormone of brain natriuretic peptide, NR: not reported, OR: odds ratio, PON1: paraoxonase 1, RAC2: Rac family small GTPase 2, SNP: single-nucleotide polymorphism, UGT2B7: uridine glucuronosyltransferase 2B7. ⇑: increases risk, ⇓: decreases risk, ⇔: no correlation.
Figure 1Summary of factors to be assessed concordantly with oncological treatment planning. Abbreviations: CVD: cardiovascular disease, ECHO: echocardiogram, MRI: magnetic resonance imaging, MUGA: multigated acquisition scan. Created with BioRender.com.