Development and application of genetic ancestry reconstruction methods to study diversity of patient-derived models in the NCI PDXNet Consortium.
Paul C LottKatherine ChiuJuanita Elizabeth QuinoApril Pangia VangMichael W LloydAnuj SrivastavaJeffrey H ChuangLuis G Carvajal CarmonaPublished in: Cancer research communications (2024)
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 (NCI) 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.
Keyphrases
- papillary thyroid
- squamous cell
- end stage renal disease
- healthcare
- clinical trial
- newly diagnosed
- public health
- peritoneal dialysis
- randomized controlled trial
- metabolic syndrome
- childhood cancer
- mental health
- machine learning
- risk factors
- dna methylation
- social media
- high throughput
- prognostic factors
- single cell
- big data
- study protocol