Breast parenchymal patterns in women with bilateral primary breast cancer

Gene-body hypermethylation of ATM in peripheral blood DNA of bilateral breast cancer patients

Bilaterality of breast cancer is an indicator of constitutional cancer susceptibility; however, the molecular causes underlying this predisposition in the majority of cases is not known. We hypothesize that epigenetic misregulation of cancer-related genes could partially account for this predisposition. We have performed methylation microarray analysis of peripheral blood DNA from 14 women with bilateral breast cancer compared with 14 unaffected matched controls throughout 17 candidate breast cancer susceptibility genes including BRCA1, BRCA2, CHEK2, ATM, ESR1, SFN, CDKN2A, TP53, GSTP1, CDH1, CDH13, HIC1, PGR, SFRP1, MLH1, RARB and HSD17B4. We show that the majority of methylation variability is associated with intragenic repetitive elements. Detailed validation of the tiled region around ATM was performed by bisulphite modification and pyrosequencing of the same samples and in a second set of peripheral blood DNA from 190 bilateral breast cancer patients compared with 190 controls. We show significant hypermethylation of one intragenic repetitive element in breast cancer cases compared with controls (P = 0.0017), with the highest quartile of methylation associated with a 3-fold increased risk of breast cancer (OR 3.20, 95% CI 1.78–5.86, P = 0.000083). Increased methylation of this locus is associated with lower steady-state ATM mRNA level and correlates with age of cancer patients but not controls, suggesting a combined age–phenotype-related association. This research demonstrates the potential for gene-body epigenetic misregulation of ATM and other cancer-related genes in peripheral blood DNA that may be useful as a novel marker to estimate breast cancer risk.

Accession numbers: The microarray data and associated .BED and .WIG files can be accessed through Gene Expression Omnibus accession number: GSE14603.

Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis

Mammographic features are associated with breast cancer risk, but estimates of the strength of the association vary markedly between studies, and it is uncertain whether the association is modified by other risk factors. We conducted a systematic review and meta-analysis of publications on mammographic patterns in relation to breast cancer risk. Random effects models were used to combine study-specific relative risks. Aggregate data for > 14,000 cases and 226,000 noncases from 42 studies were included. Associations were consistent in studies conducted in the general population but were highly heterogeneous in symptomatic populations. They were much stronger for percentage density than for Wolfe grade or Breast Imaging Reporting and Data System classification and were 20% to 30% stronger in studies of incident than of prevalent cancer. No differences were observed by age/menopausal status at mammography or by ethnicity. For percentage density measured using prediagnostic mammograms, combined relative risks of incident breast cancer in the general population were 1.79 (95% confidence interval, 1.48-2.16), 2.11 (1.70-2.63), 2.92 (2.49-3.42), and 4.64 (3.64-5.91) for categories 5% to 24%, 25% to 49%, 50% to 74%, and > or = 75% relative to < 5%. This association remained strong after excluding cancers diagnosed in the first-year postmammography. This review explains some of the heterogeneity in associations of breast density with breast cancer risk and shows that, in well-conducted studies, this is one of the strongest risk factors for breast cancer. It also refutes the suggestion that the association is an artifact of masking bias or that it is only present in a restricted age range.

Thoracic manifestations of common nonpulmonary malignancies of women

Metastatic, gender-related, nonpulmonary malignancy can exhibit different patterns of tumor spread and different natural histories. The pulmonologist often is involved in the diagnosis and treatment of patients with pulmonary metasteses; and a thorough understanding of the patterns of metastasis from these cancers can help to guide appropriate work-up and therapy. In the case of solitary pulmonary metastases, a surgical approach may not be unreasonable based on current clinical evidence. Knowledge of the clinical spectrum of these diseases, together with their unique molecular biology, may improve the clinical care of patients.

Mammographic tissue, breast cancer risk, serial image analysis, and digital mammography. Part 1. Tissue and related risk factors

This work is presented as a sequence of two parts. In this leading section, a review of the breast tissue-risk research is provided. Although controversy remains, there is substantial evidence indicating that dense mammographic tissue (a) is a breast cancer risk factor that is at least similar, if not greater, in magnitude with the other known breast cancer risk factors and (b) may be a partial biomarker for some of the other risk factors. Understanding these influences may provide a mechanism for measuring the dynamics of breast cancer risk. The totality of this work is to provide support for an automated serial mammography study under way at the authors' institution, where digital mammographic images are acquired with a full-field digital mammography system. This is a filmless imaging system, where the image is acquired in digital format. This electronic imaging acquisition system provides a prime opportunity to easily couple and manipulate the image data with patient information such as risk probability analysis or other pertinent personal history data for improved automated decision making. In this leading section, the main focus is on understanding elements that will assist in fusing risk probability analysis with automated computer-aided diagnosis. The evidence indicates that there are many factors that influence breast tissue at any given time and thus have the ability to alter the associated radiographic image appearance over time. At the initiation of the serial study it was clear that the authors did not fully understand the nature of the problem: automatically comparing similar mammographic scenes acquired at different times. In the second part of this sequence, the more time-related tissue influences are reviewed.

Observer variation in the classification of mammographic parenchymal patterns

Wolfe has described different cancer risks associated with a classification of four patterns of the breast parenchyma on mammography, but there is however little information available on the ability of radiologists to agree on the classification of the different patterns. We have assessed inter-rater agreement on the assignment of films to one of the four mammographic patterns described by Wolfe. One hundred xeromammograms were selected, copied and distributed to 10 radiologists who were experts in mammography. Films were classified according to the presence or absence of several radiological signs, according to diagnosis and recommendation, and according to mammographic pattern. Agreement was assessed after correction for agreement expected by chance, using the Kappa statistic. In general, high levels of agreement were found for the classification of mammographic pattern. Agreement on the classification of mammographic pattern was substantially greater than agreement for any other feature of mammographic interpretation, including diagnosis and recommendation.