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BackgroundGonadotoxic treatment-related infertility has a significant impact on quality of life in childhood cancer survivors. Genome-wide association analyses to delineate the risk of infertility in childhood cancer survivors have not been previously reported.MethodsLeveraging genotype data from a large survivor cohort, the Childhood Cancer Survivor Study (CCSS), we investigated the role of SNPs on future pregnancy or siring a pregnancy in survivors without pelvic, testicular, or brain radiation who had ever been married. We calculated sex-stratified hazard ratios, using Cox proportional hazards modeling, adjusting for birth cohort (before 1965 vs. 1965 or later) and doses of relevant chemotherapies; replication was attempted in the independent St. Jude Lifetime Cohort study (SJLIFE).ResultsIn the CCSS cohort, nine SNPs were found to be suggestive (P < 10-7) or statistically significantly (P < 5 × 10-8) associated with pregnancy, however, none of the SNPs were replicated in SJLIFE. Cohorts differed based on the overall pregnancy rate, frequency of sterilizing procedures, and birth cohort.ConclusionsWe were not able to replicate our findings of SNPs associated with pregnancy in childhood cancer survivors.ImpactFuture attempts at replication should be considered in cohorts treated in a comparable era. In addition, understanding the role of genetics in fertility in childhood cancer survivors may be better approached using more advanced sequencing techniques.

Simple Summary: Survivors of childhood cancer are predisposed to a range of late effects of treatment, including high symptom burden. Symptom burden may vary over time. The aim of this prospective pilot study was to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer using mobile health (mHealth) technology to evaluate symptom fluctuation and associations with future health-related quality of life (HRQOL). The 41 survivors included in this study had high adherence to symptom reporting (83%) and HRQOL reporting (95%). Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Additionally, a higher symptom burden was associated with poorer HRQOL in the future. Daily assessment of symptoms using mHealth technology revealed fluctuations in symptomology and the association between symptom burden and HRQOL. This method of symptom assessment is valuable for improving our understanding of symptom dynamics and sources of variability. Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). Methods: This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates. Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10–9.02), depression (6.32; 95% CI: 3.18–9.47), fatigue (7.93; 95% CI: 5.11–10.80), sleep (6.07; 95% CI: 3.43–8.70), pain (5.16; 95% CI: 2.11–8.22), and cognitive function (–6.89; 95% CI: –10.00 to –3.79) in the third month. Conclusions: Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability. [ABSTRACT FROM AUTHOR]

Background: What are the major determinants of women's breast cancer risk? Rare mutations such as those in the BRCA1/2 genes, polygenic scores of common alleles identified by genome-wide association studies, or nongenetic factors? Methods: The population-based Nordic Twin Study of Cancer, with 3,933 breast cancer cases among 21,054 monozygotic (MZ) and 30,939 dizygotic (DZ) female twin pairs, provides three key clues to this question: (i) the average lifetime risk, approximately 8%, does not differ by twin zygosity; (ii) the mean time interval between diagnoses when both twins develop disease (i.e., disease concordance) also does not differ by zygosity; but, (iii) conditioning on one twin having developed disease, the incidence rate in the co-twin is approximately 1% per year if the pair is MZ and 0.5% per year if DZ. Results: Assuming that nongenetic risk factors are shared similarly between twins regardless of zygosity, we can draw two conclusions from (i) to (iii). Conclusions: First, (i) and (iii) imply that the chief determinant of risk is in the germline DNA, because the conditional incidence rate is several-fold higher than the average risk (8% lifetime) in MZ twins but only half as much in DZ twins. Second, the seeming inconsistency between the two-fold conditional incidence rate (iii) and the equality of the mean inter-twin disease intervals in disease concordance (ii) can be resolved if the risk factors in the germline DNA are rare variants, not common variants. Impact: This paper details simple deductive reasoning for these conclusions and draws a critical inference regarding breast cancer etiology. [ABSTRACT FROM AUTHOR]

Numerous common genetic variants have been linked to breast cancer risk, but they only partially explain the total breast cancer heritability. Inference from Nordic population-based twin data indicates rare high-risk loci as the chief determinant of breast cancer risk. Here, we use haplotypes, rather than single variants, to identify rare high-risk loci for breast cancer. With computationally phased genotypes from 181,034 white British women in the UK Biobank, a genome-wide haplotype-breast cancer association analysis was conducted using sliding windows of 5 to 500 consecutive array-genotyped variants. In the discovery stage, haplotype-breast cancer associations were evaluated retrospectively in the prestudy-enrollment data including 5,487 breast cancer cases. Breast cancer hazard ratios (HR) for additive haplotypic effects were estimated using Cox regression. The replication analysis included a prospective cohort of women free of breast cancer at enrollment, of whom 3,524 later developed breast cancer. This two-stage analysis detected 13 rare loci (frequency <1%), each associated with an appreciable breast cancer-risk increase (discovery: HRs = 2.84-6.10, P < 5 × 10-8; replication: HRs = 2.08-5.61, P < 0.01). In contrast, the variants that formed these rare haplotypes individually exhibited much smaller effects. Functional annotation revealed extensive cis-regulatory DNA elements in breast cancer-related cells underlying the replicated rare haplotypes. Using phased, imputed genotypes from 30,064 cases and 25,282 controls in the DRIVE OncoArray case-control study, 6 of the 13 rare-loci associations were found generalizable (odds ratio estimates: 1.48-7.67, P < 0.05). This study demonstrates the complementary advantage of utilizing rare haplotypes to capture novel risk loci and suggests the potential for the discovery of more genetic elements contributing to cancer heritability as large data sets of germline whole-genome sequencing become available., Significance: A genome-wide two-stage haplotype analysis identifies rare haplotypes associated with breast cancer risk and suggests that the rare risk haplotypes represent long-range interactions with regulatory consequences influencing cancer risk., (©2022 American Association for Cancer Research.)

Background: Female childhood cancer survivors (CCSs) carry a risk of therapy-related gonadal dysfunction. Alkylating agents (AA) are well-established risk factors, yet inter-individual variability in ovarian function is observed. Polymorphisms in CYP450 enzymes may explain this variability in AA-induced ovarian damage. We aimed to evaluate associations between previously identified genetic polymorphisms in CYP450 enzymes and AA-related ovarian function among adult CCSs., Methods: Anti-Müllerian hormone (AMH) levels served as a proxy for ovarian function in a discovery cohort of adult female CCSs, from the pan-European PanCareLIFE cohort ( n = 743; age (years): median 25.8, interquartile range (IQR) 22.1-30.6). Using two additive genetic models in linear and logistic regression, nine genetic variants in three CYP450 enzymes were analyzed in relation to cyclophosphamide equivalent dose (CED) score and their impact on AMH levels. The main model evaluated the effect of the variant on AMH and the interaction model evaluated the modifying effect of the variant on the impact of CED score on log-transformed AMH levels. Results were validated, and meta-analysis performed, using the USA-based St. Jude Lifetime Cohort ( n = 391; age (years): median 31.3, IQR 26.6-37.4)., Results: CYP3A4*3 was significantly associated with AMH levels in the discovery and replication cohort. Meta-analysis revealed a significant main deleterious effect (Beta (95% CI): -0.706 (-1.11--0.298), p -value = 7 × 10 -4 ) of CYP3A4*3 (rs4986910) on log-transformed AMH levels. CYP2B6*2 (rs8192709) showed a significant protective interaction effect (Beta (95% CI): 0.527 (0.126-0.928), p -value = 0.01) on log-transformed AMH levels in CCSs receiving more than 8000 mg/m 2 CED., Conclusions: Female CCSs CYP3A4*3 carriers had significantly lower AMH levels, and CYP2B6*2 may have a protective effect on AMH levels. Identification of risk-contributing variants may improve individualized counselling regarding the treatment-related risk of infertility and fertility preservation options.