Genome-Wide Association Study Identifies ROBO2 as a Novel Susceptibility Gene for Anthracycline-Related Cardiomyopathy in Childhood Cancer Survivors

Anthracycline Toxicity: Light at the End of the Tunnel?

Anthracycline-induced cardiotoxicity (AIC) is a serious and common side effect of anthracycline therapy. Identification of genes and genetic variants associated with AIC risk has clinical potential as a cardiotoxicity predictive tool and to allow the development of personalized therapies. In this review, we provide an overview of the function of known AIC genes identified by association studies and categorize them based on their mechanistic implication in AIC. We also discuss the importance of functional validation of AIC-associated variants in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to advance the implementation of genetic predictive biomarkers. Finally, we review how patient-specific hiPSC-CMs can be used to identify novel patient-relevant functional targets and for the discovery of cardioprotectant drugs to prevent AIC. Implementation of functional validation and use of hiPSC-CMs for drug discovery will identify the next generation of highly effective and personalized cardioprotectants and accelerate the inclusion of approved AIC biomarkers into clinical practice.

Priorities in Cardio-Oncology Basic and Translational Science: GCOS 2023 Symposium Proceedings: JACC: CardioOncology State-of-the-Art Review

Despite improvements in cancer survival, cancer therapy-related cardiovascular toxicity has risen to become a prominent clinical challenge. This has led to the growth of the burgeoning field of cardio-oncology, which aims to advance the cardiovascular health of cancer patients and survivors, through actionable and translatable science. In these Global Cardio-Oncology Symposium 2023 scientific symposium proceedings, we present a focused review on the mechanisms that contribute to common cardiovascular toxicities discussed at this meeting, the ongoing international collaborative efforts to improve patient outcomes, and the bidirectional challenges of translating basic research to clinical care. We acknowledge that there are many additional therapies that are of significance but were not topics of discussion at this symposium. We hope that through this symposium-based review we can highlight the knowledge gaps and clinical priorities to inform the design of future studies that aim to prevent and mitigate cardiovascular disease in cancer patients and survivors.

Gene-Level Analysis of Anthracycline-Induced Cardiomyopathy in Cancer Survivors: A Report From COG-ALTE03N1, BMTSS, and CCSS

Background

Anthracyclines are highly effective in treating cancer, albeit with increased cardiomyopathy risk. Although risk is attributed to associations with single nucleotide polymorphisms (SNPs), multiple SNPs on a gene and their interactions remain unexamined.

Objectives

This study examined gene-level associations with cardiomyopathy among cancer survivors using whole-exome sequencing data.

Methods

For discovery, 278 childhood cancer survivors (129 cases; 149 matched control subjects) from the COG (Children's Oncology Group) study ALTE03N1 were included. Logic regression (machine learning) was used to identify gene-level SNP combinations for 7,212 genes and ordinal logistic regression to estimate gene-level associations with cardiomyopathy. Models were adjusted for primary cancer, age at cancer diagnosis, sex, race/ethnicity, cumulative anthracycline dose, chest radiation, cardiovascular risk factors, and 3 principal components. Statistical significance threshold of 6.93 × 10-6 accounted for multiple testing. Three independent cancer survivor populations (COG study, BMTSS [Blood or Marrow Transplant Survivor Study] and CCSS [Childhood Cancer Survivor Study]) were used to replicate gene-level associations and examine SNP-level associations from discovery genes using ordinal logistic, conditional logistic, and Cox regression models, respectively.

Results

Median age at cancer diagnosis for discovery cases and control subjects was 6 years and 8 years, respectively. Gene-level association for P2RX7 (OR: 0.10; 95% CI: 0.04-0.27; P = 2.19 × 10-6) was successfully replicated (HR: 0.65; 95% CI: 0.47-0.90; P = 0.009) in the CCSS cohort. Additional signals were identified on TNIK, LRRK2, MEFV, NOBOX, and FBN3. Individual SNPs across all discovery genes, except FBN3, were replicated.

Conclusions

In our study, SNP sets having 1 or no copies of P2RX7 variant alleles were associated with reduced risk of cardiomyopathy, presenting a potential therapeutic target to mitigate cardiac outcomes in cancer survivors.

Comprehensive investigating of mismatch repair genes (MMR) polymorphisms in participants with chronic hepatitis B virus infection

Background and aim: In this study, we focused on the relationship between single nucleotide polymorphisms in MMR genes and the occurrence and development of HBV infection. Materials and methods: A total of 3,128 participants were divided into five groups: negative control group (NeC), spontaneous clearance group (SC), chronic hepatitis B group (CHB), liver cirrhosis group (LC) and hepatocellular carcinoma group (HCC), CHB, liver cirrhosis and hepatocellular carcinoma constitute HLD. We conducted three case-control studies: NeC (840 cases) vs. HLD (1792 cases), SC (486 cases) vs. HLD (1792 cases) and CHB + LC (1,371 cases) vs. HCC (421 cases). 11 polymorphic loci in MLH1, MLH3, MSH5, PMS1 and PMS2 were involved in genotyping by Sequenom MassArray. The SNPStats performed Hardy-Weinberg equilibrium test. Linkage disequilibrium patterns were visualized using Haploview4.2. The GMDR (v0.9) was conducted to generalized multifactor dimension reduction analysis. The correlation, multiplicative interaction and additive interaction analyses were calculated by Logistic Regression through SPSS21.0. Matrix and programmed excel were also involved in the calculation of additive interaction. Results: In NeC vs. HLD group, MSH5-rs1150793(G) was a risk base to HBV susceptibility (nominal p = 0.002, OR = 1.346). We found multiplicative interaction between MLH1-rs1540354 (AA + AT) and PMS1-rs1233255 (AA) (nominal p = 0.024, OR = 1.240). There was additive interaction between PMS1-rs1233255 (AA) and PMS1-rs256554(CA + CC). In SC vs. HLD group, MLH1-rs1540354 (TT) was a risk genotype (nominal p < 0.05, OR>1). Through haplotype analysis, we found the linkage disequilibrium of three loci in MLH1. The results of GMDR showed the optimal five-locus model about the spontaneous clearance of HBV. In CHB + LC vs. HCC group, PMS2-rs12112229(A) was related to the cancerization of liver. Conclusion: We found rs1150793(G), rs1540354(T) and rs12112229(A) were significantly related to HBV susceptibility, spontaneous clearance of HBV and cancerization after infection, respectively.