Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast

BreasTDLUSeg: A coarse-to-fine framework for segmentation of breast terminal duct lobular units on histopathological whole-slide images

Automatic segmentation of breast terminal duct lobular units (TDLUs) on histopathological whole-slide images (WSIs) is crucial for the quantitative evaluation of TDLUs in the diagnostic and prognostic analysis of breast cancer. However, TDLU segmentation remains a great challenge due to its highly heterogeneous sizes, structures, and morphologies as well as the small areas on WSIs. In this study, we propose BreasTDLUSeg, an efficient coarse-to-fine two-stage framework based on multi-scale attention to achieve localization and precise segmentation of TDLUs on hematoxylin and eosin (H&E)-stained WSIs. BreasTDLUSeg consists of two networks: a superpatch-based patch-level classification network (SPPC-Net) and a patch-based pixel-level segmentation network (PPS-Net). SPPC-Net takes a superpatch as input and adopts a sub-region classification head to classify each patch within the superpatch as TDLU positive or negative. PPS-Net takes the TDLU positive patches derived from SPPC-Net as input. PPS-Net deploys a multi-scale CNN-Transformer as an encoder to learn enhanced multi-scale morphological representations and an upsampler to generate pixel-wise segmentation masks for the TDLU positive patches. We also constructed two breast cancer TDLU datasets containing a total of 530 superpatch images with patch-level annotations and 2322 patch images with pixel-level annotations to enable the development of TDLU segmentation methods. Experiments on the two datasets demonstrate that BreasTDLUSeg outperforms other state-of-the-art methods with the highest Dice similarity coefficients of 79.97% and 92.93%, respectively. The proposed method shows great potential to assist pathologists in the pathological analysis of breast cancer. An open-source implementation of our approach can be found at https://github.com/Dian-kai/BreasTDLUSeg.

Pregnancy-Related Factors and Breast Cancer Risk for Women Across a Range of Familial Risk

Importance

Few studies have investigated whether the associations between pregnancy-related factors and breast cancer (BC) risk differ by underlying BC susceptibility. Evidence regarding variation in BC risk is critical to understanding BC causes and for developing effective risk-based screening guidelines.

Objective

To examine the association between pregnancy-related factors and BC risk, including modification by a of BC where scores are based on age and BC family history.

Design, Setting, and Participants

This cohort study included participants from the prospective Family Study Cohort (ProF-SC), which includes the 6 sites of the Breast Cancer Family Registry (US, Canada, and Australia) and the Kathleen Cuningham Foundation Consortium (Australia). Analyses were performed in a cohort of women enrolled from 1992 to 2011 without any personal history of BC who were followed up through 2017 with a median (range) follow-up of 10 (1-23) years. Data were analyzed from March 1992 to March 2017.

Exposures

Parity, number of full-term pregnancies (FTP), age at first FTP, years since last FTP, and breastfeeding.

Main Outcomes and Measures

BC diagnoses were obtained through self-report or report by a first-degree relative and confirmed through pathology and data linkages. Cox proportional hazards regression models estimated hazard ratios (HR) and 95% CIs for each exposure, examining modification by PARS of BC. Differences were assessed by estrogen receptor (ER) subtype.

Results

The study included 17 274 women (mean [SD] age, 46.7 [15.1] years; 791 African American or Black participants [4.6%], 1399 Hispanic or Latinx participants [8.2%], and 13 790 White participants [80.7%]) with 943 prospectively ascertained BC cases. Compared with nulliparous women, BC risk was higher after a recent pregnancy for those women with higher PARS (last FTP 0-5 years HR for interaction, 1.53; 95% CI, 1.13-2.07; P for interaction < .001). Associations between other exposures were limited to ER-negative disease. ER-negative BC was positively associated with increasing PARS and increasing years since last FTP (P for interaction < .001) with higher risk for recent pregnancy vs nulliparous women (last FTP 0-5 years HR for interaction, 1.54; 95% CI, 1.03-2.31). ER-negative BC was positively associated with increasing PARS and being aged 20 years or older vs less than 20 years at first FTP (P for interaction = .002) and inversely associated with multiparity vs nulliparity (P for interaction = .01).

Conclusions and Relevance

In this cohort study of women with no prior BC diagnoses, associations between pregnancy-related factors and BC risk were modified by PARS, with greater associations observed for ER-negative BC.

Mediation analysis using incomplete information from publicly available data sources

Our work was motivated by the question whether, and to what extent, well-established risk factors mediate the racial disparity observed for colorectal cancer (CRC) incidence in the United States. Mediation analysis examines the relationships between an exposure, a mediator and an outcome. All available methods require access to a single complete data set with these three variables. However, because population-based studies usually include few non-White participants, these approaches have limited utility in answering our motivating question. Recently, we developed novel methods to integrate several data sets with incomplete information for mediation analysis. These methods have two limitations: (i) they only consider a single mediator and (ii) they require a data set containing individual-level data on the mediator and exposure (and possibly confounders) obtained by independent and identically distributed sampling from the target population. Here, we propose a new method for mediation analysis with several different data sets that accommodates complex survey and registry data, and allows for multiple mediators. The proposed approach yields unbiased causal effects estimates and confidence intervals with nominal coverage in simulations. We apply our method to data from U.S. cancer registries, a U.S.-population-representative survey and summary level odds-ratio estimates, to rigorously evaluate what proportion of the difference in CRC risk between non-Hispanic Whites and Blacks is mediated by three potentially modifiable risk factors (CRC screening history, body mass index, and regular aspirin use).

Host, reproductive, and lifestyle factors in relation to quantitative histologic metrics of the normal breast

BACKGROUND

Emerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast.

METHODS

The study participants were 4108 healthy women ages 18-75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008-2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models.

RESULTS

With increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP [β (95% Confidence Interval (CI)) = -0.28 (- 0.43, - 0.13); P < 0.001] with ESP peaks at 30-40 years and 60-70 years among pre- and postmenopausal women, respectively. Pregnancy [β (95%CI) vs nulligravid = 0.19 (0.08, 0.30); P < 0.001] and increasing number of live births (P-trend < 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP [β (95%CI) vs no breastfeeding = -0.15 (- 0.29, - 0.01); P = 0.036]. A positive family history of breast cancer (FHBC) [β (95%CI) vs no FHBC = 0.14 (0.02-0.26); P = 0.02], being overweight or obese [β (95%CI) vs normal weight = 0.18 (0.06-0.30); P = 0.004 and 0.32 (0.21-0.44); P < 0.001, respectively], and Black race [β (95%CI) vs White = 0.12 (- 0.005, 0.25); P = 0.06] were positively associated with ESP.

CONCLUSION

Our findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.

Raman microspectroscopy based TNM staging and grading of breast cancer

The tumor-node-metastasis (TNM) system is the most common way that doctors determine the anatomical extent of cancer on the basis of clinical and pathological criteria. In this study, a spectral histopathological study has been carried out to bridge Raman micro spectroscopy with the breast cancer TNM system. A total of seventy breast tissue samples, including healthy tissue, early, middle, and advanced cancer, were investigated to provide detailed insights into compositional and structural variations that accompany breast malignant evolution. After evaluating the main spectral variations in all tissue types, the generalized discriminant analysis (GDA) pathological diagnostic model was established to discriminate the TNM staging and grading information. Moreover, micro-Raman images were reconstructed by K-means clustering analysis (KCA) for visualizing the lobular acinar in healthy tissue and ductal structures in all early, middle and advanced breast cancer tissue groups. While, univariate imaging techniques were adapted to describe the distribution differences of biochemical components such as tryptophan, β-carotene, proteins, and lipids in the scanned regions. The achieved spectral histopathological results not only established a spectra-structure correlations via tissue biochemical profiles but also provided important data and discriminative model references for in vivo Raman-based breast cancer diagnosis.

Overexpression of Estrogen Receptor α in Mammary Glands of Aging Mice Is Associated with a Proliferative Risk Signature and Generation of Estrogen Receptor α-Positive Mammary Adenocarcinomas

Age is a risk factor for human estrogen receptor-positive breast cancer, with highest prevalence following menopause. While transcriptome risk profiling is available for human breast cancers, it is not yet developed for prognostication for primary or secondary breast cancer development utilizing at-risk breast tissue. Both estrogen receptor α (ER) and aromatase overexpression have been linked to human breast cancer. Herein, conditional genetically engineered mouse models of estrogen receptor 1 (Esr1) and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) were used to show that induction of Esr1 overexpression just before or with reproductive senescence and maintained through age 30 months resulted in significantly higher prevalence of estrogen receptor-positive adenocarcinomas than CYP19A1 overexpression. All adenocarcinomas tested showed high percentages of ER+ cells. Mammary cancer development was preceded by a persistent proliferative transcriptome risk signature initiated within 1 week of transgene induction that showed parallels to the Prosigna/Prediction Analysis of Microarray 50 human prognostic signature for early-stage human ER+ breast cancer. CYP19A1 mice also developed ER+ mammary cancers, but histology was more divided between adenocarcinoma and adenosquamous, with one ER- adenocarcinoma. Results demonstrate that, like humans, generation of ER+ adenocarcinoma in mice was facilitated by aging mice past the age of reproductive senescence. Esr1 overexpression was associated with a proliferative estrogen pathway-linked signature that preceded appearance of ER+ mammary adenocarcinomas.

Associations of Genetic Ancestry with Terminal Duct Lobular Unit Involution among Healthy Women

Reduced age-related terminal duct lobular unit (TDLU) involution has been linked to increased breast cancer risk and triple-negative breast cancer (TNBC). Associations of TDLU involution levels with race and ethnicity remain incompletely explored. Herein, we examined associations between genetic ancestry and TDLU involution in normal breast tissue donated by 2,014 healthy women in the US. Women of African ancestry were more likely than European women to have increased TDLU counts (odds ratio [OR]trend=1.36; 95% CI = 1.07-1.74), acini counts/TDLU (OR = 1.47; 95% CI = 1.06-2.03), and median TDLU span (ORtrend=1.44; 95% CI = 1.08-1.91), indicating lower involution; whereas East Asian descendants were associated with decreased TDLU counts (ORtrend=0.52; 95% CI = 0.35-0.78) after controlling for potential confounders. These associations are consistent with the racial variations in incidence rates of TNBC in the US and suggest opportunities for future work examining whether TDLU involution may mediate the racial differences in subtype-specific breast cancer risk.