Reproductive factors in relation to breast cancer characterized by p53 protein expression (United States)

TP53 Pathway Function, Estrogen Receptor Status, and Breast Cancer Risk Factors in the Carolina Breast Cancer Study

BACKGROUND

TP53 and estrogen receptor (ER) both play essential roles in breast cancer development and progression, with recent research revealing cross-talk between TP53 and ER signaling pathways. Although many studies have demonstrated heterogeneity of risk factor associations across ER subtypes, associations by TP53 status have been inconsistent.

METHODS

This case-case analysis included incident breast cancer cases (47% Black) from the Carolina Breast Cancer Study (1993-2013). Formalin-fixed paraffin-embedded tumor samples were classified for TP53 functional status (mutant-like/wild-type-like) using a validated RNA signature. For IHC-based TP53 status, mutant-like was classified as at least 10% positivity. We used two-stage polytomous logistic regression to evaluate risk factor heterogeneity due to RNA-based TP53 and/or ER, adjusting for each other and for PR, HER2, and grade. We then compared this with the results when using IHC-based TP53 classification.

RESULTS

The RNA-based classifier identified 55% of tumors as TP53 wild-type-like and 45% as mutant-like. Several hormone-related factors (oral contraceptive use, menopausal status, age at menopause, and pre- and postmenopausal body mass index) were associated with TP53 mutant-like status, whereas reproductive factors (age at first birth and parity) and smoking were associated with ER status. Multiparity was associated with both TP53 and ER. When classifying TP53 status using IHC methods, no associations were observed with TP53. Associations observed with RNA-based TP53 remained after accounting for basal-like subtype.

CONCLUSIONS

This case-case study found breast cancer risk factors associated with RNA-based TP53 and ER.

IMPACT

RNA-based TP53 and ER represent an emerging etiologic schema of interest in breast cancer prevention research.

Evidence for Etiologic Subtypes of Breast Cancer in the Carolina Breast Cancer Study

BACKGROUND

Distinctions in the etiology of triple-negative versus luminal breast cancer have become well established using immunohistochemical surrogates [notably estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)]. However, it is unclear whether established immunohistochemical subtypes are the sole or definitive means of etiologically subdividing breast cancers.

METHODS

We evaluated clinical biomarkers and tumor suppressor p53 with risk factor data from cases and controls in the Carolina Breast Cancer Study, a population-based study of incident breast cancers. For each individual marker and combinations of markers, we calculated an aggregate measure to distinguish the etiologic heterogeneity of different classification schema. To compare schema, we estimated subtype-specific case-control odds ratios for individual risk factors and fit age-at-incidence curves with two-component mixture models. We also evaluated subtype concordance of metachronous contralateral breast tumors in the California Cancer Registry.

RESULTS

ER was the biomarker that individually explained the greatest variability in risk factor profiles. However, further subdivision by p53 significantly increased the degree of etiologic heterogeneity. Age at diagnosis, nulliparity, and race were heterogeneously associated with ER/p53 subtypes. The ER-/p53+ subtype exhibited a similar risk factor profile and age-at-incidence distribution to the triple-negative subtype.

CONCLUSIONS

Clinical marker-based intrinsic subtypes have established value, yet other schema may also yield important etiologic insights.

IMPACT

Novel environmental or genetic risk factors may be identifiable by considering different etiologic schema, including cross-classification based on ER/p53.

Clinicopathological and epidemiological significance of breast cancer subtype reclassification based on p53 immunohistochemical expression

TP53 mutations are common in breast cancer and are typically associated with more aggressive tumor characteristics, but little is known about the clinicopathological and epidemiological relevance of p53 protein expression, a TP53 mutation surrogate, in breast cancer subtypes. In this study of 7226 Chinese women with invasive breast cancer, we defined breast cancer subtypes using immunohistochemical (IHC) measures of hormone receptors and HER2 in conjunction with histologic grade. p53 expression status was then used to further stratify subtypes into p53-positive and p53-negative. Odds ratios (ORs) and 95% confidence intervals (CIs) in case-only logistic regression analyses were used to examine heterogeneity across different subtypes. The frequency of p53 protein expression varied by breast cancer subtype, being lowest in the luminal A-like and highest in the triple-negative and HER2-enriched subtypes (P-value < 0.01). In luminal A-like and B-like/HER2-negative subtypes, p53 positivity was associated with early-onset tumors, high grade, high proliferative index, and basal marker (CK5/6 and EGFR) expression. Further, compared with luminal A-like/p53-negative patients, A-like/p53-positive patients were more likely to be parous [adjusted OR parous vs. nulliparous = 2.67 (1.60, 4.51); P-value < 0.01] and to have breastfed [adjusted OR ever vs. never = 1.38 (1.03, 1.85); P-value = 0.03]. p53 positivity was not associated with examined clinical and risk factors in other tumor subtypes. Overall, these findings suggest that p53 expression, which is readily available in many settings, can be used to identify phenotypes of luminal A-like breast cancer with distinct clinical and epidemiological implications.

PAM50 and Risk of Recurrence Scores for Interval Breast Cancers

Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 (n = 370) were identified by linking the Carolina Breast Cancer Study and the Carolina Mammography Registry. Among women with a registry-identified screening mammogram 0 to 24 months before diagnosis, cancers were classified as screen-detected (N = 165) or interval-detected (N = 205). Using logistic regression, we examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic), overall, and in analyses stratified on mammographic density and race. Interval cancer was associated with large tumors [>2 cm; OR, 2.3; 95% confidence interval (CI), 1.5-3.7], positive nodal status (OR, 1.8; 95% CI, 1.1-2.8), and triple-negative subtype (OR, 2.5; 95% CI, 1.1-5.5). Interval cancers were more likely to have non-Luminal A subtype (OR, 2.9; 95% CI, 1.5-5.7), whereas screen-detected cancers tended to be more indolent (96% had low risk of recurrence genomic scores; 71% were PAM50 Luminal A). When stratifying by mammographic density and race, associations between interval detection and poor prognostic features were similar by race and density status. Strong associations between interval cancers and poor-prognosis genomic features (non-Luminal A subtype and high risk of recurrence score) suggest that aggressive tumor biology is an important contributor to interval cancer rates. Cancer Prev Res; 11(6); 327-36. ©2018 AACR.

A conceptual and methodological framework for investigating etiologic heterogeneity

Cancer has traditionally been studied using the disease site of origin as the organizing framework. However, recent advances in molecular genetics have begun to challenge this taxonomy, as detailed molecular profiling of tumors has led to discoveries of subsets of tumors that have profiles that possess distinct clinical and biological characteristics. This is increasingly leading to research that seeks to investigate whether these subtypes of tumors have distinct etiologies. However, research in this field has been opportunistic and anecdotal, typically involving the comparison of distributions of individual risk factors between tumors classified on the basis of candidate tumor characteristics. The purpose of this article is to place this area of investigation within a more general conceptual and analytic framework, with a view to providing more efficient and practical strategies for designing and analyzing epidemiologic studies to investigate etiologic heterogeneity. We propose a formal definition of etiologic heterogeneity and show how classifications of tumor subtypes with larger etiologic heterogeneities inevitably possess greater disease risk predictability overall. We outline analytic strategies for estimating the degree of etiologic heterogeneity among a set of subtypes and for choosing subtypes that optimize the heterogeneity, and we discuss technical challenges that require further methodologic research. We illustrate the ideas by using a pooled case-control study of breast cancer classified by expression patterns of genes known to define distinct tumor subtypes.

Use of four biomarkers to evaluate the risk of breast cancer subtypes in the women's contraceptive and reproductive experiences study

Epidemiologic studies suggest that some hormone-related risk factors in breast cancer differentially influence risk for disease subtypes classified by the status of the estrogen and progesterone receptors (ER/PR). However, it remains unclear whether human epidermal growth factor receptor 2 (HER2) or p53 expression status further differentiates these exposure-risk group associations. We evaluated the associations of oral contraceptive (OC) use and reproductive factors with incident invasive breast cancer subtypes among 1,197 population-based cases and 2,015 controls from the Los Angeles County or Detroit components of the Women's Contraceptive and Reproductive Experiences Study. Case-control comparisons by ER/PR/HER2/p53 status were conducted by multivariable polychotomous unconditional logistic regression methods. We found that OC use was not associated with any breast cancer subtype as defined by ER/PR/HER2/p53 status, except for a 2.9-fold increased risk of so-called triple-negative tumors (ER(-)/PR(-)/HER2(-)) among women of 45 to 64 years of age who started OC use before age 18. Parity was associated with a decreased risk of luminal A (ER(+) or PR(+), HER2(-)), luminal B (ER(+) or PR(+)/HER2(+)), and ER(-)/PR(-)/HER2(+) tumors. Age at first full-term pregnancy was positively associated with luminal A tumors among older women. Neither of these reproductive factors was associated with triple-negative tumors. Long duration of breast-feeding lowered the risk of triple-negative and luminal A tumors. p53 status did not define further differential risk patterns. Our findings offer evidence of differences in the hormone-related risk factors between triple-negative cancers and other ER/PR/HER2-defined subtypes of breast cancer.

Risk factors for breast cancer characterized by the estrogen receptor alpha A908G (K303R) mutation

INTRODUCTION

Estrogen is important in the development of breast cancer, and its biological effects are mediated primarily through the two estrogen receptors alpha and beta. A point mutation in the estrogen receptor alpha gene, ESR1, referred to as A908G or K303R, was originally identified in breast hyperplasias and was reported to be hypersensitive to estrogen. We recently detected this mutation at a low frequency of 6% in invasive breast tumors of the Carolina Breast Cancer Study (CBCS).

METHODS

In this report, we evaluated risk factors for invasive breast cancer classified according to the presence or absence of the ESR1 A908G mutation in the CBCS, a population-based case-control study of breast cancer among younger and older white and African-American women in North Carolina. Of the 653 breast tumors evaluated, 37 were ESR1 A908G mutation-positive and 616 were mutation-negative.

RESULTS

ESR1 A908G mutation-positive breast cancer was significantly associated with a first-degree family history of breast cancer (odds ratio [OR] = 2.69, 95% confidence interval [CI] = 1.15 to 6.28), whereas mutation-negative breast cancer was not. Comparison of the two case subgroups supported this finding (OR = 2.65, 95% CI = 1.15 to 6.09). There was also the suggestion that longer duration of oral contraceptive (OC) use (OR = 3.73, 95% CI = 1.16 to 12.03; Ptrend = 0.02 for use of more than 10 years) and recent use of OCs (OR = 3.63, 95% CI = 0.80 to 16.45; Ptrend = 0.10 for use within 10 years) were associated with ESR1 A908G mutation-positive breast cancer; however, ORs for comparison of the two case subgroups were not statistically significant. Hormone replacement therapy use was inversely correlated with mutation-negative breast cancer, but the effect on mutation-positive cancer was unclear due to the small number of postmenopausal cases whose tumors carried the mutation. Mutation-negative breast cancer was associated with several reproductive factors, including younger age at menarche (OR = 1.46, 95% CI = 1.09 to 1.94) and greater total estimated years of ovarian function (OR = 1.82, 95% CI = 1.21 to 2.74).

CONCLUSION

These preliminary results suggest that OCs may interact with the ESR1 A908G mutant receptor to drive the development of some breast tumors.

Do we need genomic research for the prevention of common diseases with environmental causes?

Concerns have been raised about the value of genomic research for prevention and public health, especially for complex diseases with risk factors that are amenable to environmental modification. Given that gene-environment interactions underlie almost all human diseases, the public health significance of genomic research on common diseases with modifiable environmental risks is based not necessarily on finding new genetic "causes" but on improving existing approaches to identifying and modifying environmental risk factors to better prevent and treat disease. Such applied genomic research for environmentally caused diseases is important, because 1) it could help stratify disease risks and differentiate interventions for achieving population health benefits; 2) it could help identify new environmental risk factors for disease or help confirm suspected environmental risk factors; and 3) it could aid our understanding of disease occurrence in terms of transmission, natural history, severity, etiologic heterogeneity, and targets for intervention at the population level. While genomics is still in its infancy, opportunities exist for developing, testing, and applying the tools of genomics to clinical and public health research, especially for conditions with known or suspected environmental causes. This research is likely to lead to population-wide health promotion and disease prevention efforts, not only to interventions targeted according to genetic susceptibility.