Pharmacogenomic studies of fertility outcomes in pediatric cancer survivors - A systematic review.
Tayla StentaMichael AssisKatie L AyersElena Jane TuckerAndreas HalmanDebra GookAndrew H SinclairDavid A ElliottYasmin L JayasingheRachel ConyersPublished in: Clinical and translational science (2024)
For the same age, sex, and dosage, there can be significant variation in fertility outcomes in childhood cancer survivors. Genetics may explain this variation. This study aims to: (i) review the genetic contributions to infertility, (ii) search for pharmacogenomic studies looking at interactions of cancer treatment, genetic predisposition and fertility-related outcomes. Systematic searches in MEDLINE Ovid, Embase Classic+Embase, and PubMed were conducted using the following selection criteria: (i) pediatric, adolescent, and young adult cancer survivors, below 25 years old at the time of diagnosis, (ii) fertility outcome measures after cancer therapy, (iii) genetic considerations. Studies were excluded if they were (i) conducted in animal models, (ii) were not published in English, (iii) editorial letters, (iv) theses. Articles were screened in Covidence by at least two independent reviewers, followed by data extraction and a risk of bias assessment using the Quality in Prognostic Studies tool. Eight articles were reviewed with a total of 29 genes. Outcome measures included sperm concentration, azoospermia, AMH levels, assessment of premature menopause, ever being pregnant or siring a pregnancy. Three studies included replication cohorts, which attempted replication of SNP findings for NPY2R, BRSK1, FANCI, CYP2C19, CYP3A4, and CYP2B6. Six studies were rated with a high risk of bias. Differing methods may explain a lack of replication, and small cohorts may have contributed to few significant findings. Larger, prospective longitudinal studies with an unbiased genome-wide focus will be important to replicate significant results, which can be applied clinically.
Keyphrases
- genome wide
- childhood cancer
- young adults
- case control
- dna methylation
- cancer therapy
- gene expression
- adipose tissue
- copy number
- mental health
- metabolic syndrome
- preterm birth
- big data
- skeletal muscle
- artificial intelligence
- polycystic ovary syndrome
- data analysis
- drug induced
- clinical evaluation
- bioinformatics analysis