Impact of Genetic Ancestry on Prognostic Biomarkers in Uveal Melanoma

Genetic Ancestry-specific Molecular and Survival Differences in Admixed Patients With Breast Cancer

OBJECTIVE

We aim to determine whether incremental changes in genetic ancestry percentages influence molecular and clinical outcome characteristics of breast cancer in an admixed population.

BACKGROUND

Patients with breast cancer are predominantly characterized as "Black" or "White" based on self-identified race/ethnicity or arbitrary genetic ancestry cutoffs. This limits scientific discovery in populations that are admixed or of mixed race/ethnicity as they cannot be classified based on historical race/ethnicity boxes or genetic ancestry cutoffs.

METHODS

We used The Cancer Genome Atlas cohort and focused on genetically admixed patients that had less than 90% European, African, Asian, or Native American ancestry.

RESULTS

Genetically admixed patients with breast cancer exhibited improved 10-year overall survival relative to those with >90% European ancestry. Within the luminal A subtype, patients with lower African ancestry had longer 10-year overall survival compared to those with higher African ancestry. The correlation of genetic ancestry with gene expression and DNA methylation in the admixed cohort revealed novel ancestry-specific intrinsic PAM50 subtype patterns. In luminal A tumors, genetic ancestry was correlated with both the expression and methylation of signaling genes, while in basal-like tumors, genetic ancestry was correlated with stemness genes. In addition, we took a machine-learning approach to estimate genetic ancestry from gene expression or DNA methylation and were able to accurately calculate ancestry values from a reduced set of 10 genes or 50 methylation sites that were specific for each molecular subtype.

CONCLUSIONS

Our results suggest that incremental changes in genetic ancestry percentages result in ancestry-specific molecular differences even between well-established PAM50 subtypes which may influence disparities in breast cancer survival outcomes. Accounting for incremental changes in ancestry will be important in future research, prognostication, and risk stratification, particularly in ancestrally diverse populations.

Analytical protocol to identify local ancestry-associated molecular features in cancer

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the "local" ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

Mitochondrial DNA polymorphisms and biogenesis genes in primary and metastatic uveal melanoma cell lines

PURPOSE

This study was designed to identify mitochondrial (mt) DNA variations in primary and metastatic uveal melanoma (UM) cell lines and their relation with cell metabolism to gain insight into metastatic progression.

METHOD

The entire mtDNA genomes were sequenced using Sanger sequencing from two primary UM cell lines (92.1 and MEL270) and two cell lines (OMM2.3 and OMM2.5) derived from liver metastases of the MEL270 patient. The mtDNA copy numbers determined by the ratio of nDNA versus mtDNA. qRT-PCR was used to evaluate expression levels of mitochondrial biogenesis genes.

RESULTS

Sequencing showed that cell line MEL270 and metastases-derived OMM2.3 and OMM2.5 cell lines had homoplasmic single nucleotide polymorphisms (SNPs) representing J1c7a haplogroup, whereas 92.1 cells had mtDNA H31a haplogroup. mtDNA copy numbers were significantly higher in primary cell lines. The metastatic UM cells showed down-regulation of POLG, TFAM, NRF-1 and SIRT1 compared to their primary MEL270 cells. PGC-1α was downregulated in 92.1 and upregulated in MEL270, OMM2.3 and OMM2.5.

CONCLUSIONS

Our finding suggests that within metastatic cells, the heteroplasmic SNPs, copy numbers and mitochondrial biogenesis genes are modulated differentially compared to their primary UM cells. Therefore, investigating pathogenic mtDNA variants associated with cancer metabolic susceptibility may provide future therapeutic strategies in metastatic UM.