Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures

Constructing shared genetic architecture between bioavailable testosterone and luminal A breast cancer in female

BACKGROUND

Observational studies have showed a strong association between bioavailable testosterone (BT) and breast cancer. However, the role of genetic factors in their comorbidity remains unknown.

METHODS

Using large genome-wide association study (GWAS) data, we employed linkage disequilibrium score regression (LDSC) to identify the breast cancer subtype most genetically correlated with BT. We then constructed the shared genetic architecture between BT and this subtype by: (1) applied Heritability Estimation from Summary Statistics for local genetic correlations and stratified-LDSC for partitioned heritability; (2) performed a cross-trait GWAS meta-analysis to find novel single-nucleotide polymorphism (SNP) and validated through colocalization; (3) conducted both cross-tissue and single-tissue transcriptome-wide association studies (TWAS) and validated the candidate genes through Mendelian randomization (MR); (4) investigated SNP-heritability enrichment at the gene set, tissue, and cell levels using Multi-marker Analysis of GenoMic Annotation.

RESULTS

Luminal A breast cancer (Luminal ABC) was selected as it is a common subtype of breast cancer and demonstrates a superior genetic correlation with BT. We identified strong local correlations in 132 distinct genomic regions and confirmed shared SNPs including rs1432679 and rs7175852. TWAS highlighted two pleiotropic genes, MICALL1 and TRIOBP, with TRIOBP validated by MR. We also found six shared pathways and luminal cells in mammary gland pregnancy shared between BT and Luminal ABC. For tissue-specific enrichment, BT was mainly found in the liver and adrenal gland, whereas Luminal ABC was found in the minor salivary gland.

CONCLUSIONS

This study sheds light on the genetic architecture of BT and Luminal ABC and suggests new avenues for research and therapy.

Association between breastfeeding, mammographic density, and breast cancer risk: a review

BACKGROUND

Mammographic density has been associated with breast cancer risk, and is modulated by established breast cancer risk factors, such as reproductive and hormonal history, as well as lifestyle. Recent epidemiological and biological findings underscore the recognized benefits of breastfeeding in reducing breast cancer risk, especially for aggressive subtypes. Current research exploring the association among mammographic density, breastfeeding, and breast cancer is sparse.

MAIN FINDINGS

Changes occur in the breasts during pregnancy in preparation for lactation, characterized by the proliferation of mammary gland tissues and the development of mammary alveoli. During lactation, the alveoli fill with milk, and subsequent weaning triggers the involution and remodeling of these tissues. Breastfeeding influences the breast microenvironment, potentially altering mammographic density. When breastfeeding is not initiated after birth, or is abruptly discontinued shortly after, the breast tissue undergoes forced and abrupt involution. Conversely, when breastfeeding is sustained over an extended period and concludes gradually, the breast tissue undergoes slow remodeling process known as gradual involution. Breast tissue undergoing abrupt involution displays denser stroma, altered collagen composition, heightened inflammation and proliferation, along with increased expression of estrogen receptor α (ERα) and progesterone receptor. Furthermore, elevated levels of pregnancy-associated plasma protein-A (PAPP-A) surpass those of its inhibitors during abrupt involution, enhancing insulin-like growth factor (IGF) signaling and collagen deposition. Prolactin and small molecules in breast milk may also modulate DNA methylation levels. Drawing insights from contemporary epidemiological and molecular biology studies, our review sheds light on how breastfeeding impacts mammographic density and explores its role in influencing breast cancer.

CONCLUSION

This review highlights a clear protective link between breastfeeding and reduced breast cancer risk via changes in mammographic density. Future research should investigate the effects of breastfeeding on mammographic density and breast cancer risk among various ethnic groups and elucidate the molecular mechanisms underlying these associations. Such comprehensive research will enhance our understanding and facilitate the development of targeted breast cancer prevention and treatment strategies.

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

BACKGROUND

Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women.

METHODS

A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC.

RESULTS

Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02).

CONCLUSION

Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia

PURPOSE

Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown.

METHOD

Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls.

RESULTS

Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD.

CONCLUSION

Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

The correlation of leukocyte-specific protein 1 (LSP1) rs3817198(T>C) polymorphism with breast cancer: A meta-analysis

BACKGROUND

Multiple studies have investigated the correlation of single nucleotide polymorphisms (SNPs) in leukocyte-specific protein 1 (LSP1) with susceptibility to breast cancer (BC) and have yielded inconsistent conclusions, particularly rs3817198(T > C). Consequently, we performed a meta-analysis to estimate this relationship more comprehensively.

METHODS

Four databases were utilized to locate eligible publications: PubMed, Embase, Web of Science, and China National Knowledge Infrastructure. This meta-analysis included 14 studies, including 22 reports of 33194 cases and 36661 controls. The relationship of rs3817198 polymorphism with breast cancer was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). The LSP1 co-expression network was constructed by STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using DAVIDE. Download TCGA breast cancer mRNA-seq data and analyze the relationship between LSP1 expression and breast cancer chemotherapy sensitivity.

RESULTS

The results indicated that rs3817198(T > C) was positively correlated to with breast malignancy (dominant model: OR = 1.11, 95%CI = 1.06-1.17; recessive model: OR = 1.10, 95%CI = 1.04-1.15; heterozygous model: OR = 1.09, 95%CI = 1.04-1.15; homozygous model: OR = 1.18, 95%CI = 1.09-1.28; additive model: OR = 1.09, 95%CI = 1.05-1.13), among Caucasians and Asians. However, rs3817198(T > C) may reduce the risk of breast carcinoma in Africans. Rs3817198(T > C) might result in breast carcinoma in individuals with BRCA1 and BRCA2 variants and can contribute to estrogen receptor (ER)-positive breast carcinoma. The expression of LSP1 was inversely correlated with the IC50 of doxorubicin (P = 8.91e-15, Cor = -0.23), 5-fluorouracil (P = 1.18e-22, Cor = -0.29), and cisplatin (P = 1.35e-42, Cor = -0.40).

CONCLUSION

Our study identified that LSP1 rs3817198 polymorphism might result in breast malignancy, particularly among Caucasians and Asians, but lower breast cancer susceptibility in African populations. The expression of LSP1 was negatively correlated with the IC50 of doxorubicin, 5-fluorouracil, and cisplatin.

The risk variant rs11836367 contributes to breast cancer onset and metastasis by attenuating Wnt signaling via regulating NTN4 expression

Most genome-wide association study (GWAS)-identified breast cancer-associated causal variants remain uncharacterized. To provide a framework of understanding GWAS-identified variants to function, we performed a comprehensive study of noncoding regulatory variants at the NTN4 locus (12q22) and NTN4 gene in breast cancer etiology. We find that rs11836367 is the more likely causal variant, disrupting enhancer activity in both enhancer reporter assays and endogenous genome editing experiments. The protective T allele of rs11837367 increases the binding of GATA3 to the distal enhancer and up-regulates NTN4 expression. In addition, we demonstrate that loss of NTN4 gene in mice leads to tumor earlier onset, progression, and metastasis. We discover that NTN4, as a tumor suppressor, can attenuate the Wnt signaling pathway by directly binding to Wnt ligands. Our findings bridge the gaps among breast cancer-associated single-nucleotide polymorphisms, transcriptional regulation of NTN4, and breast cancer biology, which provides previously unidentified insights into breast cancer prediction and prevention.

Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk

Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.

Recent Advances of m6A Demethylases Inhibitors and Their Biological Functions in Human Diseases

N6-methyladenosine (m6A) is a post-transcriptional RNA modification and one of the most abundant types of RNA chemical modifications. m6A functions as a molecular switch and is involved in a range of biomedical aspects, including cardiovascular diseases, the central nervous system, and cancers. Conceptually, m6A methylation can be dynamically and reversibly modulated by RNA methylation regulatory proteins, resulting in diverse fates of mRNAs. This review focuses on m6A demethylases fat-mass- and obesity-associated protein (FTO) and alkB homolog 5 (ALKBH5), which especially erase m6A modification from target mRNAs. Recent advances have highlighted that FTO and ALKBH5 play an oncogenic role in various cancers, such as acute myeloid leukemias (AML), glioblastoma, and breast cancer. Moreover, studies in vitro and in mouse models confirmed that FTO-specific inhibitors exhibited anti-tumor effects in several cancers. Accumulating evidence has suggested the possibility of FTO and ALKBH5 as therapeutic targets for specific diseases. In this review, we aim to illustrate the structural properties of these two m6A demethylases and the development of their specific inhibitors. Additionally, this review will summarize the biological functions of these two m6A demethylases in various types of cancers and other human diseases.

The epidemiologic factors associated with breast density: A review

In recent years, some studies have evaluated the epidemiologic factors associated with breast density. However, the variant and inconsistent results exist. In addition, breast density has been proved to be a significant risk factor associated with breast cancer. Our review summarized the published studies and emphasized the crucial factors including epidemiological factors associated with breast density. In addition, we also discussed the potential reasons for the discrepant results with risk factors. To decrease the incidence and mortality rates for breast cancer, in clinical practice, breast density should be included for clinical risk models in addition to epidemiological factors, and physicians should get more concentrate on those women with risk factors and provide risk-based breast cancer screening regimens.

Is Mammographic Breast Density an Endophenotype for Breast Cancer?

Simple Summary

Candidate endophenotypes should be systematically assessed against five criteria: (i) the endophenotype is associated with disease in the population; (ii) the endophenotype is heritable; (iii) within families, endophenotype and disease co-segregate; (iv) the endophenotype found in affected family members is found in non-affected family members at a higher rate than in the general population and (v) the endophenotype is primarily state independent (manifests in an individual whether or not disease is active). This study assesses the suitability of mammographic breast density as an endophenotype for breast cancer. Formally establishing a trait as a disease endophenotype confirms that the trait and endophenotype share a biological basis, thereby enabling genetic dissection of an endophenotype to inform disease risk. As breast density can be measured for any woman who has had a mammogram, studies investigating the genetic architecture of breast density could identify breast cancer risk variants that act through effects on this trait.

Abstract

Mammographic breast density (MBD) is a strong and highly heritable predictor of breast cancer risk and a biomarker for the disease. This study systematically assesses MBD as an endophenotype for breast cancer—a quantitative trait that is heritable and genetically correlated with disease risk. Using data from the family-based kConFab Study and the 1994/1995 cross-sectional Busselton Health Study, participants were divided into three status groups—cases, relatives of cases and controls. Participant’s mammograms were used to measure absolute dense area (DA) and percentage dense area (PDA). To address each endophenotype criterion, linear mixed models and heritability analysis were conducted. Both measures of MBD were significantly associated with breast cancer risk in two independent samples. These measures were also highly heritable. Meta-analyses of both studies showed that MBD measures were higher in cases compared to relatives (β = 0.48, 95% CI = 0.10, 0.86 and β = 0.41, 95% CI = 0.06, 0.78 for DA and PDA, respectively) and in relatives compared to controls (β = 0.16, 95% CI = −0.24, 0.56 and β = 0.16, 95% CI = −0.21, 0.53 for DA and PDA, respectively). This study formally demonstrates, for the first time, that MBD is an endophenotype for breast cancer.

"Association of mammographic features with molecular breast tumor profiles"

PURPOSE

Mammographic density and tumor appearance are breast cancer prognostic factors. Conceivably, mammographic features are macroscopic reflections of tumor´s molecular composition, but to an unknown extent. Our aim was to study associations of mammographic features with molecular tumor profiles.

METHODS

Invasive breast cancers (2007-2016) in Malmö Diet and Cancer Study (MDCS) for which there were tumor RNA-sequencing analyses within Sweden Cancerome Analysis Network - Breast (SCAN-B) (n=102) or All Breast Cancer in Malmö (ABIM) (n=50) were identified. Density (fatty vs. dense), tumor appearance (mass vs. spiculation), and intrinsic subtypes were registered. Differences in gene/metagene expression and Microenvironment Cell Population Counter were analyzed with R. Overall survival was used as endpoint.

RESULTS

No gene expression differences between density groups was observed. In one cohort (but not the other), Luminal A tumors associated with fatty breasts. For spiculation vs. mass, (p<0.01, t-test) 86 genes were differentially expressed; only one gene was differentially expressed comparing density. Gene set enrichment analysis showed genes highly expressed in spiculated tumors were enriched for extracellular matrix-associated genes whereas genes highly expressed with masses were associated with proliferation. A spiculation metagene, based on differentially expressed genes, showed association with estrogen receptor positivity, lower grade, and improved survival, but it was not an independent prognostic factor.

CONCLUSION

There are clear differences in molecular composition between breast tumors with a spiculated appearance vs. a mass as the dominant tumor appearance. However, there are no apparent molecular differences related to the density of the breast in which the tumor has arisen.

Pubertal mammary gland development is a key determinant of adult mammographic density

Mammographic density refers to the radiological appearance of fibroglandular and adipose tissue on a mammogram of the breast. Women with relatively high mammographic density for their age and body mass index are at significantly higher risk for breast cancer. The association between mammographic density and breast cancer risk is well-established, however the molecular and cellular events that lead to the development of high mammographic density are yet to be elucidated. Puberty is a critical time for breast development, where endocrine and paracrine signalling drive development of the mammary gland epithelium, stroma, and adipose tissue. As the relative abundance of these cell types determines the radiological appearance of the adult breast, puberty should be considered as a key developmental stage in the establishment of mammographic density. Epidemiological studies have pointed to the significance of pubertal adipose tissue deposition, as well as timing of menarche and thelarche, on adult mammographic density and breast cancer risk. Activation of hypothalamic-pituitary axes during puberty combined with genetic and epigenetic molecular determinants, together with stromal fibroblasts, extracellular matrix, and immune signalling factors in the mammary gland, act in concert to drive breast development and the relative abundance of different cell types in the adult breast. Here, we discuss the key cellular and molecular mechanisms through which pubertal mammary gland development may affect adult mammographic density and cancer risk.

Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer (N = 49,674) and a polygenic risk score (PRS, N = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC, cm²/year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%-67%) for MD, 23% (2%-45%) for microcalcifications, and 13% (1%-25%)] for masses. The estimated heritability for MDC was essentially null (2%; 95% CI, -8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. SIGNIFICANCE: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk.

The association of single nucleotide polymorphisms (SNPs) with breast density and breast cancer survival: the Malmö Diet and Cancer Study

Background

Genetic factors are important in determining breast density, and heritable factors account for 60% of the variation. Certain single nucleotide polymorphisms (SNPs) are associated with density and risk of breast cancer but the association with prognosis is not clear.

Purpose

To investigate associations between selected SNPs and breast cancer survival in the Malmö Diet and Cancer Study (MDCS).

Material and Methods

A total of 724 unrelated women with breast cancer and registered radiological and pathological data were identified in MDCS 1991–2007, with genotyping available for 672 women. Associations among 15 SNPs, density, and breast cancer-specific survival were analyzed using logistic/Cox regression, adjusted for factors affecting density and survival. Variants significantly associated with either density or survival were validated in a large independent breast cancer cohort (LIBRO-1).

Results

Minor homozygotes of SNPs rs9383589, CCDC170 and rs6557161, ESR1 were associated with high breast density (adjusted odds ratio [AOR] 8.97, 95% confidence interval [CI] 1.35–59.57; AOR 2.08, 95% CI 1.19–3.65, respectively) and poorer breast cancer survival (adjusted hazard ratio [HR_adj] 6.46, 95% CI 1.95–21.39; HR_adj 2.30, 95% CI 1.33–3.96, respectively) compared to major homozygotes. For SNP rs3757318, ESR1, minor homozygotes (HR_adj 7.46, 95% CI 2.28–24.45) were associated with poorer survival. We confirmed that rs6557161, ESR1 was significantly associated with both density and survival in the LIBRO-1 study.

Conclusion

These findings support a shared genetic basis for density and breast cancer survival. The SNP significantly associated with both density and survival in both cohorts may be of interest in future research investigating polygenic risk scores for breast cancer risk and screening stratification purposes.

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

Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.

Challenges and emerging systems biology approaches to discover how the human gut microbiome impact host physiology

Research in the human gut microbiome has bloomed with advances in next generation sequencing (NGS) and other high-throughput molecular profiling technologies. This has enabled the generation of multi-omics datasets which holds promises for big data-enabled knowledge acquisition in the form of understanding the normal physiological and pathological involvement of gut microbiomes. Ample evidence suggests that distinct microbial compositions in the human gut are associated with different diseases. However, the biological mechanisms underlying these associations are often unclear. There is a need to move beyond statistical associations to discover how changes in the gut microbiota mechanistically affect host physiology and disease development. This review summarises state-of-the-art big data and systems biology approaches for mechanism discovery.

Mammographic density and breast cancer screening

Mammographic density, which is determined by the relative amounts of fibroglandular tissue and fat in the breast, varies between women. Mammographic density is associated with a range of factors, including age and body mass index. The description of mammographic density has been transformed by the digitalization of mammography, which has allowed automation of the assessment of mammographic density, rather than using visual inspection by a radiologist. High mammographic density is important because it is associated with reduced sensitivity for the detection of breast cancer at the time of mammographic screening. High mammographic density is also associated with an elevated risk of developing breast cancer. Mammographic density appears to be on the causal pathway for some breast cancer risk factors, but not others. Mammographic density needs to be considered in the context of a woman's background risk of breast cancer. There is intense debate about the use of supplementary imaging for women with high mammographic density. Should supplementary imaging be used in women with high mammographic density and a clear mammogram? If so, what modalities of imaging should be used and in which women? Trials are underway to address the risks and benefits of supplementary imaging.

Multi-omic profiling reveals associations between the gut mucosal microbiome, the metabolome, and host DNA methylation associated gene expression in patients with colorectal cancer

Background

The human gut microbiome plays a critical role in the carcinogenesis of colorectal cancer (CRC). However, a comprehensive analysis of the interaction between the host and microbiome is still lacking.

Results

We found correlations between the change in abundance of microbial taxa, butyrate-related colonic metabolites, and methylation-associated host gene expression in colonic tumour mucosa tissues compared with the adjacent normal mucosa tissues. The increase of genus Fusobacterium abundance was correlated with a decrease in the level of 4-hydroxybutyric acid (4-HB) and expression of immune-related peptidase inhibitor 16 (PI16), Fc Receptor Like A (FCRLA) and Lymphocyte Specific Protein 1 (LSP1). The decrease in the abundance of another potentially 4-HB-associated genus, Prevotella 2, was also found to be correlated with the down-regulated expression of metallothionein 1 M (MT1M). Additionally, the increase of glutamic acid-related family Halomonadaceae was correlated with the decreased expression of reelin (RELN). The decreased abundance of genus Paeniclostridium and genus Enterococcus were correlated with increased lactic acid level, and were also linked to the expression change of Phospholipase C Beta 1 (PLCB1) and Immunoglobulin Superfamily Member 9 (IGSF9) respectively. Interestingly, 4-HB, glutamic acid and lactic acid are all butyrate precursors, which may modify gene expression by epigenetic regulation such as DNA methylation.

Conclusions

Our study identified associations between previously reported CRC-related microbial taxa, butyrate-related metabolites and DNA methylation-associated gene expression in tumour and normal colonic mucosa tissues from CRC patients, which uncovered a possible mechanism of the role of microbiome in the carcinogenesis of CRC. In addition, these findings offer insight into potential new biomarkers, therapeutic and/or prevention strategies for CRC.

Going Beyond Conventional Mammographic Density to Discover Novel Mammogram-Based Predictors of Breast Cancer Risk

This commentary is about predicting a woman’s breast cancer risk from her mammogram, building on the work of Wolfe, Boyd and Yaffe on mammographic density. We summarise our efforts at finding new mammogram-based risk predictors, and how they combine with the conventional mammographic density, in predicting risk for interval cancers and screen-detected breast cancers across different ages at diagnosis and for both Caucasian and Asian women. Using the OPERA (odds ratio per adjusted standard deviation) concept, in which the risk gradient is measured on an appropriate scale that takes into account other factors adjusted for by design or analysis, we show that our new mammogram-based measures are the strongest of all currently known breast cancer risk factors in terms of risk discrimination on a population-basis. We summarise our findings graphically using a path diagram in which conventional mammographic density predicts interval cancer due to its role in masking, while the new mammogram-based risk measures could have a causal effect on both interval and screen-detected breast cancer. We discuss attempts by others to pursue this line of investigation, the measurement challenge that allows different measures to be compared in an open and transparent manner on the same datasets, as well as the biological and public health consequences.

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

BACKGROUND

Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.

METHODS

Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.

RESULTS

Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.

CONCLUSIONS

The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

Diagnostic Accuracy of Breast Medical Tactile Examiners (MTEs): A Prospective Pilot Study

Background

The usefulness of clinical breast examination (CBE) in general and in breast cancer screening programs has been a matter of debate. This study investigated whether adding vision-impaired medical tactile examiners (MTEs) improves the predictiveness of CBE for suspicious lesions and analyzed the feasibility and acceptability of this approach.

Methods

The prospective study included 104 patients. Physicians and MTEs performed CBEs, and mammography and ultrasound results were used as the gold standard. Sensitivity and specificity were calculated and logistic regression models were used to compare the predictive value of CBE by physicians alone, MTEs alone, and physicians and MTEs combined.

Results

For CBEs by physicians alone, MTEs alone, and both combined, sensitivity was 71, 82, and 89% and specificity was 55, 45, and 35%, respectively. Using adjusted logistic regression models, the validated areas under the curve were 0.685, 0.692, and 0.710 (median bootstrapped p value (DeLong) = 0.381).

Conclusion

The predictive value for a suspicious breast lesion in CBEs performed by MTEs in patients without prior surgery was similar to that of physician-conducted CBEs. Including MTEs in the CBE procedure in breast units thus appears feasible and could be a way of utilizing their skills.

"A Natural Progression": Australian Women's Attitudes About an Individualized Breast Screening Model

Individualized screening is our logical next step to improve population breast cancer screening in Australia. To explore breast screening participants' views of the current program in Victoria, Australia, examine their openness to change, and attitudes toward an individualized screening model, this qualitative work was performed from a population-based breast screening cohort. This work was designed to inform the development of a decision aid to facilitate women's decisions about participating in individualized screening, and to elicit Australian consumer perspectives on the international movement toward individualized breast screening. A total of 52 women participated in one of four focus groups, and were experienced with screening with 90% of participants having had more than three mammograms. Focus group discussion was facilitated following three main themes: (i) experience of breast screening; (ii) breast cancer risk perception, and (iii) views on individualized screening. Participants had strong, positive, emotional ties to breast screening in its current structure but were supportive, with some reservations, of the idea of individualized screening. There was good understanding about the factors contributing to personalized risk and a wide range of opinions about the inclusion of genetic testing with genetic testing being considered a foreign and evolving domain. Individualized breast screening that takes account of risk factors such as mammographic density, lifestyle, and genetic factors would be acceptable to a population of women who are invested in the current system. The communication and implementation of a new program would be critical to its acceptance and potential success. Reservations may be had in regards to uptake of genetic testing, motivations behind the change, and management of the women allocated to a lower risk category.

Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures

Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p < 10^-7 ) association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all p > 0.05/299 = 1.7 × 10^-4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds

BACKGROUND

Case-control studies show that mammographic density is a better risk factor when defined at higher than conventional pixel-brightness thresholds. We asked if this applied to interval and/or screen-detected cancers.

METHOD

We conducted a nested case-control study within the prospective Melbourne Collaborative Cohort Study including 168 women with interval and 422 with screen-detected breast cancers, and 498 and 1197 matched controls, respectively. We measured absolute and percent mammographic density using the Cumulus software at the conventional threshold (Cumulus) and two increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were transformed and adjusted for age and body mass index (BMI). Using conditional logistic regression and adjusting for BMI by age at mammogram, we estimated risk discrimination by the odds ratio per adjusted standard deviation (OPERA), calculated the area under the receiver operating characteristic curve (AUC) and compared nested models using the likelihood ratio criterion and models with the same number of parameters using the difference in Bayesian information criterion (ΔBIC).

RESULTS

For interval cancer, there was very strong evidence that the association was best predicted by Cumulus as a percentage (OPERA = 2.33 (95% confidence interval (CI) 1.85-2.92); all ΔBIC > 14), and the association with BMI was independent of age at mammogram. After adjusting for percent Cumulus, no other measure was associated with risk (all P > 0.1). For screen-detected cancer, however, the associations were strongest for the absolute and percent Cirrocumulus measures (all ΔBIC > 6), and after adjusting for Cirrocumulus, no other measure was associated with risk (all P > 0.07).

CONCLUSION

The amount of brighter areas is the best mammogram-based measure of screen-detected breast cancer risk, while the percentage of the breast covered by white or bright areas is the best mammogram-based measure of interval breast cancer risk, irrespective of BMI. Therefore, there are different features of mammographic images that give clinically important information about different outcomes.

The role of matricellular proteins and tissue stiffness in breast cancer: a systematic review

Malignancies consist not only of cancerous and nonmalignant cells, but also of additional elements, as extracellular matrix. The aim of this review is to summarize meta-analyses, describing breast tissue stiffness and risk of breast carcinoma (BC) assessing the potential relationship between matricellular proteins (MPs) and survival. A systematic computer-based search of published articles, according to PRISMA statement, was conducted through Ovid interface. Mammographic density and tissue stiffness are associated with the risk of BC development, suggesting that MPs may influence BC prognosis. No definitive conclusions are available and additional researches are required to definitively clarify the role of each MP, mammographic density and stiffness in BC development and the mechanisms involved in the onset of this malignancy.

A novel scoring system for acute myeloid leukemia risk assessment based on the expression levels of six genes

Acute myeloid leukemia (AML) is the most common type of acute leukemia and is a heterogeneous clonal disorder. At present, the pathogenesis of AML and potential methods to effectively prevent AML have become areas of interest in research. In the present study, two messenger ribonucleic acid sequencing datasets of patients with AML were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) of the poor and good prognosis groups were screened using the Linear Models for Microarray Data package, and the prognosis-related genes were screened using univariate Cox regression analysis. A total of 206 significant DEGs were identified. Following univariate and multivariate Cox regression analysis, 14 genes significantly associated with prognosis were screened and six of these genes, including triggering receptor expressed on myeloid cells 2 (TREML2), cysteine-glutamate transporter (SLC7A11), NACHT, LRR, and PYD domains-containing protein 2 (NLRP2), DNA damage-inducible transcript 4 protein (DDIT4), lymphocyte‑specific protein 1 (LSP1) and C-type lectin domain family 11 member A (CLEC11A), were used to construct model equations for risk assessment. The prognostic scoring system was used to evaluate risk for each patient, and the results showed that patients in the low-risk group had a longer survival time, compared with those in the high-risk group (P=9.59e-06 for the training dataset and P=0.00543 for the validation dataset). A total of eight main Kyoto Encyclopedia of Genes and Genomes pathways were identified, the top three of which were hematopoietic cell lineage, focal adhesion, and regulation of actin cytoskeleton. Taken together, the results showed that the scoring system established in the present study was credible and that the six genes were identified, which were significantly associated with the risk assessment of AML, offer potential as prognostic biomarkers. These findings may provide clues for further clarifying the pathogenesis of AML.

Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.

Genetic Modifiers of the Breast Tumor Microenvironment

Multiple nonmalignant cell types in the tumor microenvironment (TME) impact breast cancer risk, metastasis, and response to therapy, yet most heritable mechanisms that influence TME cell function and breast cancer outcomes are largely unknown. Breast cancer risk is ∼30% heritable and >170 genetic loci have been associated with breast cancer traits. However, the majority of candidate genes have poorly defined mechanistic roles in breast cancer biology. Research indicates that breast cancer risk modifiers directly impact cancer cells, yet it is equally plausible that some modifier alleles impact the nonmalignant TME. The objective of this review is to examine the list of current breast cancer candidate genes that may modify breast cancer risk and outcome through the TME.

Common genetic variation and novel loci associated with volumetric mammographic density

BACKGROUND

Mammographic density (MD) is a strong and heritable intermediate phenotype of breast cancer, but much of its genetic variation remains unexplained.

METHODS

We conducted a genetic association study of volumetric MD in a Swedish mammography screening cohort (n = 9498) to identify novel MD loci. Associations with volumetric MD phenotypes (percent dense volume, absolute dense volume, and absolute nondense volume) were estimated using linear regression adjusting for age, body mass index, menopausal status, and six principal components. We also estimated the proportion of MD variance explained by additive contributions from single-nucleotide polymorphisms (SNP-based heritability [h²_SNP]) in 4948 participants of the cohort.

RESULTS

In total, three novel MD loci were identified (at P < 5 × 10^- 8): one for percent dense volume (HABP2) and two for the absolute dense volume (INHBB, LINC01483). INHBB is an established locus for ER-negative breast cancer, and HABP2 and LINC01483 represent putative new breast cancer susceptibility loci, because both loci were associated with breast cancer in available meta-analysis data including 122,977 breast cancer cases and 105,974 control subjects (P < 0.05). h²_SNP (SE) estimates for percent dense, absolute dense, and nondense volume were 0.29 (0.07), 0.31 (0.07), and 0.25 (0.07), respectively. Corresponding ratios of h²_SNP to previously observed narrow-sense h² estimates in the same cohort were 0.46, 0.72, and 0.41, respectively.

CONCLUSIONS

These findings provide new insights into the genetic basis of MD and biological mechanisms linking MD to breast cancer risk. Apart from identifying three novel loci, we demonstrate that at least 25% of the MD variance is explained by common genetic variation with h²_SNP/h² ratios varying between dense and nondense MD components.

Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future

Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics

BACKGROUND

Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics.

METHODS

Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women.

RESULTS

Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05).

CONCLUSION

Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

Breast cancer risk factors and mammographic density among high-risk women in urban China

Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (P_interaction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (P_interaction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.

FTO regulates the chemo-radiotherapy resistance of cervical squamous cell carcinoma (CSCC) by targeting β-catenin through mRNA demethylation

The role of N⁶ -methyladenosine (m⁶ A) demethylase fat mass and obesity-associated protein (FTO) in the regulation of chemo-radiotherapy resistance remains largely unknown. Here, we show that the mRNA level of FTO is elevated in cervical squamous cell carcinoma (CSCC) tissues when compared with respective adjacent normal tissues. FTO enhances the chemo-radiotherapy resistance both in vitro and in vivo through regulating expression of β-catenin by reducing m⁶ A levels in its mRNA transcripts and in turn increases excision repair cross-complementation group 1 (ERCC1) activity. Clinically, the prognostic value of FTO for overall survival is found to be dependent on β-catenin expression in human CSCC samples. Taken together, these findings uncover a critical function for FTO and its substrate m⁶ A in the regulation of chemo-radiotherapy resistance, which may bear potential clinical implications for CSCC treatment.

Stromal characteristics may hold the key to mammographic density: the evidence to date

There is strong epidemiological data indicating a role for increased mammographic density (MD) in predisposing to breast cancer, however, the biological mechanisms underlying this phenomenon are less well understood. Recently, studies of human breast tissues have started to characterise the features of mammographically dense breasts, and a number of in-vitro and in-vivo studies have explored the potential mechanisms through which dense breast tissue may exert this tumourigenic risk. This article aims to review both the pathological and biological evidence implicating a key role for the breast stromal compartment in MD, how this may be modified and the clinical significance of these findings. The epidemiological context will be briefly discussed but will not be covered in detail.

Breast density: why all the fuss?

The term "breast density" or mammographic density (MD) denotes those components of breast parenchyma visualised at mammography that are denser than adipose tissue. MD is composed of a mixture of epithelial and stromal components, notably collagen, in variable proportions. MD is most commonly assessed in clinical practice with the time-honoured method of visual estimation of area-based percent density (PMD) on a mammogram, with categorisation into quartiles. The computerised semi-automated thresholding method, Cumulus, also yielding area-based percent density, is widely used for research purposes; however, the advent of fully automated volumetric methods developed as a consequence of the widespread use of digital mammography (DM) and yielding both absolute and percent dense volumes, has resulted in an explosion of interest in MD recently. Broadly, the importance of MD is twofold: firstly, the presence of marked MD significantly reduces mammographic sensitivity for breast cancer, even with state-of-the-art DM. Recognition of this led to the formation of a powerful lobby group ('Are You Dense') in the US, as a consequence of which 32 states have legislated for mandatory disclosure of MD to women undergoing mammography. Secondly, it is now widely accepted that MD is in itself a risk factor for breast cancer, with a four-to sixfold increased relative risk in women with PMD in the highest quintile compared to those with PMD in the lowest quintile. Consequently, major research efforts are underway to assess whether use of MD could provide a major step forward towards risk-adapted, personalised breast cancer prevention, imaging, and treatment.

Association between breast cancer genetic susceptibility variants and terminal duct lobular unit involution of the breast

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.

Lymphocyte-specific protein 1 inhibits the growth of hepatocellular carcinoma by suppressing ERK1/2 phosphorylation

Lymphocyte‐specific protein 1 (LSP1) has been reported to regulate cell biology in several human cancers including lymphoma and breast cancer. However, the functions of LSP1 in human hepatocellular carcinoma (HCC) are still unknown. In this study, we found that LSP1 expression was downregulated in HCC tissues and cell lines, and lower LSP1 expression was correlated with poor clinicopathological features including large tumor size, high Edmondson–Steiner grading and advanced tumor–node–metastasis (TNM) stage. Additionally, we demonstrated that patients with high LSP1 expression had significantly better overall survival and disease‐free survival. Moreover, LSP1 was found to be an independent factor for predicting the prognosis of HCC patients. In vitro and in vivo assays showed that overexpressing LSP1 inhibited HCC growth by inducing both apoptosis and growth arrest. Mechanistically, we found that expression of phosphorylated extracellular regulated protein kinases 1 and 2 (ERK1/2) was downregulated after LSP1 overexpression, indicating LSP1 could suppress HCC growth by inhibiting the ERK pathway in HCC cells. Taken together, these results indicate that LSP1 may serve as a prognostic marker and a potential therapeutic target in human HCC.

Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study

BACKGROUND

Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking.

METHODS

We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve.

RESULTS

For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results.

CONCLUSIONS

Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.

Raised mammographic density: causative mechanisms and biological consequences

High mammographic density is the most important risk factor for breast cancer, after ageing. However, the composition, architecture, and mechanical properties of high X-ray density soft tissues, and the causative mechanisms resulting in different mammographic densities, are not well described. Moreover, it is not known how high breast density leads to increased susceptibility for cancer, or the extent to which it causes the genomic changes that characterise the disease. An understanding of these principals may lead to new diagnostic tools and therapeutic interventions.

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.

Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies

BACKGROUND

Controversy persists about optimal mammography screening strategies.

OBJECTIVE

To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer.

DESIGN

Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality.

SETTING

United States.

PATIENTS

Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity.

INTERVENTION

Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years.

MEASUREMENTS

Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and quality-adjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens.

RESULTS

Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar benefits, but more harms than other strategies). For groups with a 2- to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years.

LIMITATION

Other imaging technologies, polygenic risk, and nonadherence were not considered.

CONCLUSION

Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Milk: an epigenetic amplifier of FTO-mediated transcription? Implications for Western diseases

Single-nucleotide polymorphisms within intron 1 of the FTO (fat mass and obesity-associated) gene are associated with enhanced FTO expression, increased body weight, obesity and type 2 diabetes mellitus (T2DM). The N⁶-methyladenosine (m⁶A) demethylase FTO plays a pivotal regulatory role for postnatal growth and energy expenditure. The purpose of this review is to provide translational evidence that links milk signaling with FTO-activated transcription of the milk recipient. FTO-dependent demethylation of m⁶A regulates mRNA splicing required for adipogenesis, increases the stability of mRNAs, and affects microRNA (miRNA) expression and miRNA biosynthesis. FTO senses branched-chain amino acids (BCAAs) and activates the nutrient sensitive kinase mechanistic target of rapamycin complex 1 (mTORC1), which plays a key role in translation. Milk provides abundant BCAAs and glutamine, critical components increasing FTO expression. CpG hypomethylation in the first intron of FTO has recently been associated with T2DM. CpG methylation is generally associated with gene silencing. In contrast, CpG demethylation generally increases transcription. DNA de novo methylation of CpG sites is facilitated by DNA methyltransferases (DNMT) 3A and 3B, whereas DNA maintenance methylation is controlled by DNMT1. MiRNA-29s target all DNMTs and thus reduce DNA CpG methylation. Cow´s milk provides substantial amounts of exosomal miRNA-29s that reach the systemic circulation and target mRNAs of the milk recipient. Via DNMT suppression, milk exosomal miRNA-29s may reduce the magnitude of FTO methylation, thereby epigenetically increasing FTO expression in the milk consumer. High lactation performance with increased milk yield has recently been associated with excessive miRNA-29 expression of dairy cow mammary epithelial cells (DCMECs). Notably, the galactopoietic hormone prolactin upregulates the transcription factor STAT3, which induces miRNA-29 expression. In a retrovirus-like manner milk exosomes may transfer DCMEC-derived miRNA-29s and bovine FTO mRNA to the milk consumer amplifying FTO expression. There is compelling evidence that obesity, T2DM, prostate and breast cancer, and neurodegenerative diseases are all associated with increased FTO expression. Maximization of lactation performance by veterinary medicine with enhanced miRNA-29s and FTO expression associated with increased exosomal miRNA-29 and FTO mRNA transfer to the milk consumer may represent key epigenetic mechanisms promoting FTO/mTORC1-mediated diseases of civilization.

Variants in 6q25.1 Are Associated with Mammographic Density in Malaysian Chinese Women

BACKGROUND

Mammographic density is an established risk factor for breast cancer and has a strong heritable component. Genome-wide association studies (GWAS) for mammographic density conducted in women of European descent have identified several genetic associations, but none of the studies have been tested in Asians. We sought to investigate whether these genetic loci, and loci associated with breast cancer risk and breast size, are associated with mammographic density in an Asian cohort.

METHODS

We conducted genotyping by mass spectrometry in 1,189 women (865 Chinese, 187 Indian, and 137 Malay). Quantitative measurements of mammographic density were performed using ImageJ, a fully automated thresholding technique. The associations of SNPs to densities were analyzed using linear regression models.

RESULTS

We successfully evaluated the associations of 36 SNPs with mammographic densities. After adjusting for age, body mass index, parity, and menopausal status, we found that in our cohort of 865 Malaysian Chinese, three SNPs in the 6q25.1 region near ESR1 (rs2046210, rs12173570, and rs10484919) that were associated with mammographic density, breast cancer risk, or breast size in previous GWAS were significantly associated with both percentage density and absolute dense area. We could not replicate the most significant association found previously in European women (rs10995190, ZNF365 gene) because the minor allele was absent for Asian women.

CONCLUSION

We found that the directions of genetic associations were similar to those reported in Caucasian women.

IMPACT

Our results show that even in Asian women with lower population risk to breast cancer, there is shared heritability between mammographic density and breast cancer risk.