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Purpose: Breast terminal duct lobular units undergo two distinctive physiological processes of involution: age-related lobular involution (LI), which is gradual and associated with decreased breast cancer risk, and postlactational involution, which is relatively precipitous, occurs with weaning, and has been associated with potentiation of tumor aggressiveness in animal models. Here we assessed whether markers of postlactational involution are associated with ongoing LI in a retrospective tissue cohort., Methods: We selected 57 women from the Mayo Clinic Benign Breast Disease Cohort who underwent multiple biopsies and who were average age 48 at initial biopsy. Women were classified as having progressive or non-progressive LI between initial and subsequent biopsy. Serial tissue sections were immunostained for plasminogen, matrix metalloproteinase 9 (MMP-9), phospho-STAT3 (pSTAT3), tenascin C, Ki67, CD44, cytokeratin 14 (CK14), cytokeratin 19 (CK19), and c-myc. All but Ki67 were digitally quantified. Associations between maximal marker expression per sample and progressive versus non-progressive LI were assessed using logistic regression and adjusted for potential confounders., Results: While no biomarker showed statistically significant association with LI progression when evaluated individually, lower expression of pSTAT3 (OR 0.35, 95% CI 0.13-0.82, p = 0.01) and higher expression of plasminogen (OR 2.89, 95% CI 1.14-8.81, p = 0.02) were associated with progressive LI in models simultaneously adjusted for all biomarkers. Sensitivity analyses indicated that the strengthening in association for pSTAT3 and plasminogen with progressive LI was due to collinearity between these two markers., Conclusions: This is the first study to identify biomarkers of active LI. Our findings that plasminogen and pSTAT3 are significantly associated with LI suggest that they may represent signaling nodes or biomarkers of pathways common to the processes of postlactational involution and LI.

Background: Atypical hyperplasia (AH) and mammographic breast density (MBD) are established risk factors for breast cancer (BC), but their joint contributions are not well understood. We examine associations of MBD and BC by histologic impression, including AH, in a subcohort of women from the Mayo Clinic Benign Breast Disease Cohort., Methods: Women with a diagnosis of BBD and mammogram between 1985 and 2001 were eligible. Histologic impression was assessed via pathology review and coded as non-proliferative disease (NP), proliferative disease without atypia (PDWA) and AH. MBD was assessed clinically using parenchymal pattern (PP) or BI-RADS criteria and categorized as low, moderate or high. Percent density (PD) was also available for a subset of women. BC and clinical information were obtained by questionnaires, medical records and the Mayo Clinic Tumor Registry. Women were followed from date of benign biopsy to BC, death or last contact. Standardized incidence ratios (SIRs) compared the observed number of BCs to expected counts. Cox regression estimated multivariate-adjusted MBD hazard ratios., Results: Of the 6271 women included in the study, 1132 (18.0%) had low MBD, 2921 (46.6%) had moderate MBD, and 2218 (35.4%) had high MBD. A total of 3532 women (56.3%) had NP, 2269 (36.2%) had PDWA and 470 (7.5%) had AH. Over a median follow-up of 14.3 years, 528 BCs were observed. The association of MBD and BC risk differed by histologic impression (p-interaction = 0.03), such that there was a strong MBD and BC association among NP (p < 0.001) but non-significant associations for PDWA (p = 0.27) and AH (p = 0.96). MBD and BC associations for AH women were not significant within subsets defined by type of MBD measure (PP vs. BI-RADS), age at biopsy, number of foci of AH, type of AH (lobular vs. ductal) and body mass index, and after adjustment for potential confounding variables. Women with atypia who also had high PD (>50%) demonstrated marginal evidence of increased BC risk (SIR 4.98), but results were not statistically significant., Conclusion: We found no evidence of an association between MBD and subsequent BC risk in women with AH.

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Background: Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results: As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (< 5%), and collectively shared a "C > T|G > A" mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions: Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency. [ABSTRACT FROM AUTHOR]