Development and Application of Genetic Ancestry Reconstruction Methods to Study Diversity of Patient-Derived Models in the NCI PDXNet Consortium.

Precision medicine holds great promise for improving cancer outcomes. Yet, there are large inequities in the demographics of patients from whom genomic data and models, including patient-derived xenografts (PDX), are developed and for whom treatments are optimized. In this study, we developed a genetic ancestry pipeline for the Cancer Genomics Cloud, which we used to assess the diversity of models currently available in the National Cancer Institute-supported PDX Development and Trial Centers Research Network (PDXNet). We showed that there is an under-representation of models derived from patients of non-European ancestry, consistent with other cancer model resources. We discussed these findings in the context of disparities in cancer incidence and outcomes among demographic groups in the US, as well as power analyses for biomarker discovery, to highlight the immediate need for developing models from minority populations to address cancer health equity in precision medicine. Our analyses identified key priority disparity-associated cancer types for which new models should be developed. SIGNIFICANCE: Understanding whether and how tumor genetic factors drive differences in outcomes among U.S. minority groups is critical to addressing cancer health disparities. Our findings suggest that many additional models will be necessary to understand the genome-driven sources of these disparities.

Multiregional Sequencing Analysis Reveals Extensive Genetic Heterogeneity in Gastric Tumors from Latinos.

Gastric cancer is a leading cause of cancer mortality and health disparities in Latinos. We evaluated gastric intratumoral heterogeneity using multiregional sequencing of >700 cancer genes in 115 tumor biopsies from 32 patients, 29 who were Latinos. Analyses focused on comparisons with The Cancer Genome Atlas (TCGA) and on mutation clonality, druggability, and signatures. We found that only approximately 30% of all mutations were clonal and that only 61% of the known TCGA gastric cancer drivers harbored clonal mutations. Multiple clonal mutations were found in new candidate gastric cancer drivers such as EYS, FAT4, PCDHA1, RAD50, EXO1, RECQL4, and FSIP2. The genomically stable (GS) molecular subtype, which has the worse prognosis, was identified in 48% of our Latino patients, a fraction that was >2.3-fold higher than in TCGA Asian and White patients. Only a third of all tumors harbored clonal pathogenic mutations in druggable genes, with most (93%) GS tumors lacking actionable clonal mutations. Mutation signature analyses revealed that, in microsatellite-stable (MSS) tumors, DNA repair mutations were common for both tumor initiation and progression, while tobacco, POLE, and inflammation signatures likely initiate carcinogenesis. MSS tumor progression was likely driven by aging- and aflatoxin-associated mutations, as these latter changes were usually nonclonal. In microsatellite-unstable tumors, nonclonal tobacco-associated mutations were common. Our study, therefore, contributed to advancing gastric cancer molecular diagnostics and suggests clonal status is important to understanding gastric tumorigenesis. Our findings of a higher frequency of a poor prognosis associated molecular subtype in Latinos and a possible new aflatoxin gastric cancer etiology also advance cancer disparities research. Significance: Our study contributes to advancing our knowledge of gastric carcinogenesis, diagnostics, and cancer health disparities.

Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Is Associated with Indigenous American Ancestry in Latin American Women.

Women of Latin American origin in the United States are more likely to be diagnosed with advanced breast cancer and have a higher risk of mortality than non-Hispanic White women. Studies in U.S. Latinas and Latin American women have reported a high incidence of HER2 positive (+) tumors; however, the factors contributing to this observation are unknown. Genome-wide genotype data for 1,312 patients from the Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC) were used to estimate genetic ancestry. We tested the association between HER2 status and genetic ancestry using logistic and multinomial logistic regression models. Findings were replicated in 616 samples from Mexico and Colombia. Average Indigenous American (IA) ancestry differed by subtype. In multivariate models, the odds of having an HER2+ tumor increased by a factor of 1.20 with every 10% increase in IA ancestry proportion (95% CI, 1.07-1.35; P = 0.001). The association between HER2 status and IA ancestry was independently replicated in samples from Mexico and Colombia. Results suggest that the high prevalence of HER2+ tumors in Latinas could be due in part to the presence of population-specific genetic variant(s) affecting HER2 expression in breast cancer. SIGNIFICANCE: The positive association between Indigenous American genetic ancestry and HER2+ breast cancer suggests that the high incidence of HER2+ subtypes in Latinas might be due to population and subtype-specific genetic risk variants.

A Polygenic Risk Score for Breast Cancer in US Latinas and Latin American Women.

BACKGROUND: More than 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Because most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry. METHODS: We conducted a pooled case-control analysis of US Latinas and Latin American women (4658 cases and 7622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (P < 5 × 10-8). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression, and assessed discrimination using an area under the receiver operating characteristic curve. We also assessed PRS performance across quartiles of Indigenous American genetic ancestry. All statistical tests were two-sided. RESULTS: Of 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally statistically significant (P < .05). The PRS was associated with breast cancer risk, with an odds ratio per SD increment of 1.58 (95% confidence interval [CI = 1.52 to 1.64) and an area under the receiver operating characteristic curve of 0.63 (95% CI = 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry. CONCLUSIONS: The 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry.

Resolving gastric cancer aetiology: an update in genetic predisposition.

Every year gastric cancer accounts for nearly 1 million new cases and more than 720 000 deaths worldwide. Prognosis is dismal because most patients are diagnosed with advanced disease; as such, gastric cancer outcomes will benefit from better methods for identification of at-risk individuals that can be targeted for early detection. One approach to targeting high-risk populations is to identify individuals who are genetically predisposed to gastric cancer, as up to 15% of all patients report family history of the disease. On the basis of clinical manifestations, three gastric cancer syndromes have been described, but the diagnosis of some of these syndromes is suboptimal and could benefit from genetic information. Over the past decade, genome-wide association and next-generation sequencing studies have identified several low penetrance variants and high-risk genes, considerably increasing our understanding of inherited gastric cancer predisposition. From these studies, PALB2 has emerged as a new familial gastric cancer gene. Furthermore, genetic analyses in patients with sporadic gastric cancer suggest that more than 10% of all cases have pathogenic mutations, a finding of great importance for cancer aetiology. In this Review, we summarise the role of genetics in gastric cancer aetiology and the implications of genetics findings for the prevention of this malignancy.

StochHMM: a flexible hidden Markov model tool and C++ library.

UNLABELLED: Hidden Markov models (HMMs) are probabilistic models that are well-suited to solve many different classification problems in computation biology. StochHMM provides a command-line program and C++ library that can implement a traditional HMM from a simple text file. StochHMM provides researchers the flexibility to create higher-order emissions, integrate additional data sources and/or user-defined functions into multiple points within the HMM framework. Additional features include user-defined alphabets, ability to handle ambiguous characters in an emission-dependent manner, user-defined weighting of state paths and ability to tie transition probabilities to sequence. AVAILABILITY AND IMPLEMENTATION: StochHMM is implemented in C++ and is available under the MIT License. Software, source code, documentation and examples can be found at http://github.com/KorfLab/StochHMM.