Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies

Segregating YKU80 and TLC1 Alleles Underlying Natural Variation in Telomere Properties in Wild Yeast

In yeast, as in humans, telomere length varies among individuals and is controlled by multiple loci. In a quest to define the extent of variation in telomere length, we screened 112 wild-type Saccharomyces sensu stricto isolates. We found extensive telomere length variation in S. paradoxus isolates. This phenotype correlated with their geographic origin: European strains were observed to have extremely short telomeres (<150 bp), whereas American isolates had telomeres approximately three times as long (>400 bp). Insertions of a URA3 gene near telomeres allowed accurate analysis of individual telomere lengths and telomere position effect (TPE). Crossing the American and European strains resulted in F1 spores with a continuum of telomere lengths consistent with what would be predicted if many quantitative trait loci (QTLs) were involved in length maintenance. Variation in TPE is similarly quantitative but only weakly correlated with telomere length. Genotyping F1 segregants indicated several QTLs associated with telomere length and silencing variation. These QTLs include likely candidate genes but also map to regions where there are no known genes involved in telomeric properties. We detected transgressive segregation for both phenotypes. We validated by reciprocal hemizygosity that YKU80 and TLC1 are telomere-length QTLs in the two S. paradoxus subpopulations. Furthermore, we propose that sequence divergence within the Ku heterodimer generates negative epistasis within one of the allelic combinations (American-YKU70 and European-YKU80) resulting in very short telomeres

Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used&nbsp;statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation&nbsp;to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR&nbsp;=&nbsp;2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies

Research silos in cancer disparities: obstacles to improving clinical outcomes for under-served patient populations.

Despite much-vaunted progress in cancer therapeutics and diagnostics, outcomes for many groups of non-White cancer patients remain worse than those for their White compatriots. One reason for this is the lack of inclusion and representation of non-White patients in clinical trials, preclinical datasets, and amongst researchers, a shortfall that is gaining wide recognition within the cancer research community and the lay public. Several reviews and editorials have commented on the negative impacts of the status quo on progress in cancer research towards medical breakthroughs that help all communities and not just White cancer patients. In this perspective, we describe the existence of research silos focused either on the impact of socio-economic factors proceeding from systemic racism on cancer outcomes, or on genetic ancestry as it affects the molecular biology of cancer developing in specific patient populations. While both these research areas are critical for progress towards precision medicine equity, breaking down these silos will help us gain an integrated understanding of how race and racism impact cancer development, progression, and patient outcomes. Bringing this comprehensive approach to cancer disparities research will undoubtedly improve our overall understanding of how stress and environmental factors affect the molecular biology of cancer, which will lead to the development of new diagnostics and therapeutics that are applicable across cancer patient demographics

Survival Disparities in US Black Compared to White Women with Hormone Receptor Positive-HER2 Negative Breast Cancer

Black women in the US have significantly higher breast cancer mortality than White women. Within biomarker-defined tumor subtypes, disparate outcomes seem to be limited to women with hormone receptor positive and HER2 negative (HR+/HER2−) breast cancer, a subtype usually associated with favorable prognosis. In this review, we present data from an array of studies that demonstrate significantly higher mortality in Black compared to White women with HR+/HER2-breast cancer and contrast these data to studies from integrated healthcare systems that failed to find survival differences. Then, we describe factors, both biological and non-biological, that may contribute to disparate survival in Black women

TLR4 has a TP53-dependent dual role in regulating breast cancer cell growth

Breast cancer is a leading cause of cancer-related death, and it is important to understand pathways that drive the disease to devise effective therapeutic strategies. Our results show that Toll-like receptor 4 (TLR4) drives breast cancer cell growth differentially based on the presence of TP53, a tumor suppressor. TP53 is mutationally inactivated in most types of cancer and is mutated in 30–50% of diagnosed breast tumors. We demonstrate that TLR4 activation inhibits growth of TP53 wild-type cells, but promotes growth of TP53 mutant breast cancer cells by regulating proliferation. This differential effect is mediated by changes in tumor cell cytokine secretion. Whereas TLR4 activation in TP53 mutant breast cancer cells increases secretion of progrowth cytokines, TLR4 activation in TP53 wild-type breast cancer cells increases type I IFN (IFN-γ) secretion, which is both necessary and sufficient for mediating TLR4-induced growth inhibition. This study identifies a novel dichotomous role for TLR4 as a growth regulator and a modulator of tumor microenvironment in breast tumors. These results have translational relevance, demonstrating that TP53 mutant breast tumor growth can be suppressed by pharmacologic TLR4 inhibition, whereas TLR4 inhibitors may in fact promote growth of TP53 wild-type tumors. Furthermore, using data generated by The Cancer Genome Atlas consortium, we demonstrate that the effect of TP53 mutational status on TLR4 activity may extend to ovarian, colon, and lung cancers, among others, suggesting that the viability of TLR4 as a therapeutic target depends on TP53 status in many different tumor types

Abstract 2521: Race specific differences in DNA damage repair dysregulation in breast cancer and association with outcome

Abstract African American (AA) estrogen receptor positive (ER+) breast cancer patients have worse outcomes than Caucasian Americans (CA) being 42 % more likely to die from the disease. However, AAs are severely underrepresented in currently available datasets of patient tumors, which precludes comprehensive approaches to identify race-specific molecular drivers of these poor outcomes. Endocrine therapy (ET) is the first line standard of care for ER+ breast cancer. Nevertheless, 1 in 4 patients develop ET resistance. Specific DNA damage/repair (DDR) defects have been shown to associate with poor outcome in CA patients, and to induce ET resistance. Whether these or other DDR defects contribute to poor outcomes observed in AA patients remains unknown. For the purpose of this investigation, we assessed the DDR dysregulation landscape of AA ER+ tumors using three independent tumor datasets (1) GSE78958 (2) GSE18229 (3) The Cancer Genome Atlas (TCGA) and two normal breast datasets (1) GSE43973 (2) GSE50939. This analysis identified a distinct set of AA ER+ tumors with simultaneous dysregulation of genes from multiple DDR pathways, rarely seen in CA tumors. This simultaneous dysregulation also associated with worse patient outcomes in all three datasets analyzed. This work constitutes the first systematic analysis of race-specific DDR dysregulation in ER+ breast cancer, and identifies DDR as a potential predictive biomarker for worse outcome seen in AA patients. Citation Format: Aloran Mazumder, Athena Jimenez, Rachel Ellsworth, Stephen Freedland, Sophia George, Matthew Bainbridge, Svasti Haricharan. Race specific differences in DNA damage repair dysregulation in breast cancer and association with outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2521