Racial Disparities in Triple Negative Breast Cancer: Toward a Causal Architecture Approach

Siegel, Scott D.; Brooks, Madeline; Lynch, Shannon M.; Sims‐Mourtada, Jennifer; Schug, Zachary T.; Curriero, Frank C.

doi:10.21203/rs.3.rs-1177963/v1

Cited by 4 publications

(4 citation statements)

References 38 publications

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“…For example, a model trained for predicting triple negative breast cancer treatment response should enrich for Black patients with the disease, as they are subject to a disproportionate incidence and mortality burden. 35…”

Section: Training Data Set Constructionmentioning

confidence: 99%

Translating Intersectionality to Fair Machine Learning in Health Sciences

Lett¹,

Cava²

2023

Preprint

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Machine learning (ML)-derived tools are rapidly being deployed as an additional input in the clinical decision-making process to optimize health interventions. However, ML models also risk propagating societal discrimination and exacerbating existing health inequities. The field of ML fairness has focused on developing approaches to mitigate bias in ML models. To date, the focus has been on the model fitting process, simplifying the processes of structural discrimination to definitions of model bias based on performance metrics. Here, we reframe the ML task through the lens of intersectionality, a Black feminist theoretical framework that contextualizes individuals in interacting systems of power and oppression, linking inquiry into measuring fairness to the pursuit of health justice. In doing so, we present intersectional ML fairness as a paradigm shift that moves from an emphasis on model metrics to an approach for ML that is centered around achieving more equitable health outcomes.

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Section: Training Data Set Constructionmentioning

confidence: 99%

Translating Intersectionality to Fair Machine Learning in Health Sciences

Lett¹,

Cava²

2023

Preprint

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“…Triple-negative breast cancer (TNBC) accounts for 15-20% of invasive breast cancer worldwide and exhibits heterogeneous molecular features [13,14]. According to epidemiologic studies, incidence of TNBC vary with race and ethnicity, possibly owing to differences in lifestyle, including both biologic and non-biologic factors [15,16]. Due to the lack of therapeutic targets (ER, PR, and HER2), RT and systemic chemotherapy are often used pre-or postoperatively for treating TNBC [17].…”

Section: Introductionmentioning

confidence: 99%

Obesity promotes radioresistance through SERPINE1-mediated aggressiveness and DNA repair of triple-negative breast cancer

Ann

et al. 2023

Cell Death Dis

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Obesity is a risk factor in various types of cancer, including breast cancer. The disturbance of adipose tissue in obesity highly correlates with cancer progression and resistance to standard treatments such as chemo- and radio-therapies. In this study, in a syngeneic mouse model of triple-negative breast cancer (TNBC), diet-induced obesity (DIO) not only promoted tumor growth, but also reduced tumor response to radiotherapy. Serpine1 (Pai-1) was elevated in the circulation of obese mice and was enriched within tumor microenvironment. In vitro co-culture of human white adipocytes-conditioned medium (hAd-CM) with TNBC cells potentiated the aggressive phenotypes and radioresistance of TNBC cells. Moreover, inhibition of both cancer cell autonomous and non-autonomous SERPINE1 by either genetic or pharmacological strategy markedly dampened the aggressive phenotypes and radioresistance of TNBC cells. Mechanistically, we uncovered a previously unrecognized role of SERPINE1 in DNA damage response. Ionizing radiation-induced DNA double-strand breaks (DSBs) increased the expression of SERPINE1 in cancer cells in an ATM/ATR-dependent manner, and promoted nuclear localization of SERPINE1 to facilitate DSB repair. By analyzing public clinical datasets, higher SERPINE1 expression in TNBC correlated with patients’ BMI as well as poor outcomes. Elevated SERPINE1 expression and nuclear localization were also observed in radioresistant breast cancer cells. Collectively, we reveal a link between obesity and radioresistance in TNBC and identify SERPINE1 to be a crucial factor mediating obesity-associated tumor radioresistance.

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“…1). This conceptualization of health disparities has been applied when examining other cancer types and diseases [30,[36][37][38][39][40][41], and recently in TNBC cases in Louisiana and Delaware [42,43]. Using the Louisiana tumor registry from 2010 to 2012, Hossain and colleagues found a higher incidence of TNBC among non-Hispanic Black patients and a signi cant association between living in more disadvantaged neighborhoods and worse stage at diagnosis [42].…”

Section: Introductionmentioning

confidence: 99%

“…Using the Louisiana tumor registry from 2010 to 2012, Hossain and colleagues found a higher incidence of TNBC among non-Hispanic Black patients and a signi cant association between living in more disadvantaged neighborhoods and worse stage at diagnosis [42]. Using the Delaware tumor registry from 2012 to 2020, Siegal and colleagues also found signi cant neighborhood effects on TNBC incidence [43].…”

Section: Introductionmentioning

confidence: 99%

Neighborhood and racial influences on triple negative breast cancer: evidence from Northeast Ohio

Eom

Berg²,

Joseph³

et al. 2023

Breast Cancer Res Treat

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Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer (BC) with higher recurrence rates and poorer prognoses and most prevalent among non-Hispanic Black women. Studies of multiple health conditions and care processes suggest that neighborhood socioeconomic position is a key driver of health disparities. We examined roles of patients' neighborhood-level characteristics and race on prevalence, stage at diagnosis, and mortality among patients diagnosed with BC at a large safety-net healthcare system in Northeast Ohio. MethodsWe used tumor registry to identify BC cases from 2007-2020 and electronic health records and American Community Survey for individual-and area-level factors. We performed multivariable regression analyses to estimate associations between neighborhood-level characteristics, measured by the Area Deprivation Index (ADI), race and comparative TNBC prevalence, stage at diagnosis, and total mortality. ResultsTNBC was more common among non-Hispanic Black (53.7%) vs. non-Hispanic white patients (46.4%). Race and ADI were individually signi cant predictors of TNBC prevalence, stage at diagnosis, and total mortality. Race remained signi cantly associated with TNBC subtype, adjusting for covariates. Accounting for TNBC status, a more disadvantaged neighborhood was signi cantly associated with a worse stage at diagnosis and higher death rates. ConclusionOur ndings suggest that both neighborhood socioeconomic position and race are strongly associated with TNBC vs. other BC subtypes. The burden of TNBC appears to be highest among Black women in the most socioeconomically disadvantaged neighborhoods. Our study suggests a complex interplay of social conditions and biological disease characteristics contributing to racial disparities in BC outcomes.

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Racial Disparities in Triple Negative Breast Cancer: Toward a Causal Architecture Approach

Cited by 4 publications

References 38 publications

Translating Intersectionality to Fair Machine Learning in Health Sciences

Translating Intersectionality to Fair Machine Learning in Health Sciences

Obesity promotes radioresistance through SERPINE1-mediated aggressiveness and DNA repair of triple-negative breast cancer

Neighborhood and racial influences on triple negative breast cancer: evidence from Northeast Ohio

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