Hoskin, Tanya L.

AbstractBackgroundVenous thromboembolism (VTE) chemoprophylaxis in breast surgery remains controversial. In 2012, we instituted a practice change of routine chemoprophylaxis for patients with invasive cancer undergoing mastectomy. Herein, we report the effects of this on rates of VTE and hematoma.MethodsOur 30‐day rates of VTE and hematoma requiring reoperation among patients with mastectomy since the practice change were retrospectively collected from National Surgical Quality Improvement Program (NSQIP). The subsequent 5‐year data (2012‐2017) was compared with historic NSQIP data (2006‐2010). We utilized information from our 30‐day follow‐up databank to assess patients not sampled by NSQIP.ResultsAfter the practice change, the heparin prophylaxis rate rose from 19.5% to 95.6% (P < .001) and the VTE rate fell from 0.8% to 0% (P = .30). There was no significant change in reoperative hematoma rate (P = .39). The majority of the current NSQIP patient population (93.1%) had a Caprini score of 5 or greater. Among 663 patients obtained from 30‐day postoperative follow‐up, there were 2 VTE (0.3%) and 7 (1.1%) reoperations for hematoma.ConclusionsThe practice change resulted in an increase of VTE chemoprophylaxis without significant change in hematoma incidence. Although not statistically significant, VTE incidence decreased. This supports the use of standardized VTE chemoprophylaxis in this population and warrants further study.

Abstract 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 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 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 library preparations. 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 fromcytosine 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 Background: Macrophages are well-established components of the inflammatory repertoire in breast cancer (BC) progression. The role of macrophages in early breast carcinogenesis is less understood. Macrophages adopt microenvironment-driven pro- or anti-inflammatory phenotypes. We evaluated macrophagic subsets in benign breast stroma to evaluate their association with future or concurrent BC. Methods: With institutional approval, FFPE tissues were identified from age-matched subjects, [with index benign breast biopsies and (a subset) interval-matched second benign tissues taken at the time of one of three events: ER+ BC, ER- BC or no cancer event (Controls) (index N=32, 26 and 30 respectively)]. Tissues were immunostained (CD68 or CD163) and stromal CD68+ and CD163+ macrophagic cell densities (MCD) (cells/mm2 stromal fibroadipose area) were digitally quantified. Statistical analysis was performed using Wilcoxon signed-rank tests for univariate analysis and conditional logistic regression models to adjust for BMI. Results: In the index age-matched biopsies (median age 54y), within subjects in all groups, the median CD163+ MCD (54.5; range: 13.9-371.3) was significantly higher than CD68+ MCD (19.6, range: 3.5-78.5) but the two were strongly correlated (r = 0.76); neither correlated with BMI (r&lt; 0.1 each). Across the groups, index benign biopsies of ER- BC had significantly lower CD68+ MCD and CD163+ MCD compared to ER+ BC (CD163: median 47.2 vs. 57.8, p=0.004; and median CD68+ MCD: 15.8 vs. 29.7, p=0.03); and ER- BC had significantly lower CD163+ MCD density than Controls (p=0.02), (all by univariate analysis and after adjusting for BMI). Comparing the index biopsy and second biopsy/excision within subjects, all showed significant increases in CD68+ MCD (median increase 27.9 for ER- BC, 16.1 for ER+ BC, and 17.8 for controls, p&lt;0.01), and only ER-BC showed an increase in CD163+ MCD (median increase 26.6, p=0.01). Thus, in the second biopsies/excisions, the CD163+ MCD and CD68+ MCD were similar across groups (median CD163+ MCD: 69.3, 75.4, and 59.3 and median CD68+ MCD: 47.4, 45.2, and 36.0 for ER+ BC, ER- BC, and controls); however, all groups had decreased CD163+:CD68+ MCD ratios compared to the index biopsies. Conclusion: Benign breast tissues have higher stromal CD163+ MCD than CD68+ MCD irrespective of future BC events and independent of BMI. However, between index and second biopsies/excisions, the stromal CD68+ MCD differentially increased in all groups, lowering CD163+:CD68+ MCD ratios, and likely shifting pro- and anti-inflammatory stromal macrophage functionality. Across groups, ER- BC index biopsies had significantly lower stromal MCD of both types compared to ER+ BC, and were the only group to increase stromal CD163+ MCD between index biopsy and cancer event. These data suggest that ER+ and ER- BC may have different pre-carcinogenic stromal inflammatory microenvironments. Citation Format: Jodi M. Carter, Ethan P. Heinzen, Tanya L. Hoskin, Stacey J. Winham, Derek C. Radisky, Daniel W. Visscher, Amy C. Degnim. Differential stromal macrophagic profiles precede ER+ and ER- breast carcinogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2705.

Abstract 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 library preparations. 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 fromcytosine 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.

Purpose Women with atypical hyperplasia (AH) on breast biopsy have an aggregate increased risk of breast cancer (BC), but existing risk prediction models do not provide accurate individualized estimates of risk in this subset of high-risk women. Here, we used the Mayo benign breast disease cohort to develop and validate a model of BC risk prediction that is specifically for women with AH, which we have designated as AH-BC. Patients and Methods Retrospective cohorts of women age 18 to 85 years with pathologically confirmed benign AH from Rochester, MN, and Nashville, TN, were used for model development and external validation, respectively. Clinical risk factors and histologic features of the tissue biopsy were selected using L1-penalized Cox proportional hazards regression. Identified features were included in a Fine and Gray regression model to estimate BC risk, with death as a competing risk. Model discrimination and calibration were assessed in the model-building set and an external validation set. Results The model-building set consisted of 699 women with AH, 142 of whom developed BC (median follow-up, 8.1 years), and the external validation set consisted of 461 women with 114 later BC events (median follow-up, 11.4 years). The final AH-BC model included three covariates: age at biopsy, age at biopsy squared, and number of foci of AH. At 10 years, the AH-BC model demonstrated good discrimination (0.63 [95% CI, 0.57 to 0.70]) and calibration (0.87 [95% CI, 0.66 to 1.24]). In the external validation set, the model showed acceptable discrimination (0.59 [95% CI, 0.51 to 0.67]) and calibration (0.91 [95% CI, 0.65 to 1.42]). Conclusion We have created a new model with which to refine BC risk prediction for women with AH. The AH-BC model demonstrates good discrimination and calibration, and it validates in an external data set.

Abstract In breast adipose tissue, macrophages that encircle damaged adipocytes form “crown-like structures of breast” (CLS-B). Although CLS-B have been associated with breast cancer, their role in benign breast disease (BBD) and early carcinogenesis is not understood. We evaluated breast biopsies from three age-matched groups (n = 86 each, mean age 55 years), including normal tissue donors of the Susan G. Komen for the Cure Tissue Bank (KTB), and subjects in the Mayo Clinic Benign Breast Disease Cohort who developed cancer (BBD cases) or did not develop cancer (BBD controls, median follow-up 14 years). Biopsies were classified into histologic categories, and CD68-immunostained tissue sections were evaluated for the frequency and density of CLS-B. Our data demonstrate that CLS-B are associated with BBD: CLS-B–positive samples were significantly less frequent among KTB biopsies (3/86, 3.5%) than BBD controls (16/86 = 18.6%, P = 0.01) and BBD cases (21/86 = 24%, P = 0.002). CLS-B were strongly associated with body mass index (BMI); BMI &lt; 25: 7% CLS-B positive, BMI 25–29: 13%, and BMI ≥ 30: 29% (P = 0.0005). Among BBD biopsies, a high CLS-B count [&gt;5 CLS-B/sample: 10.5% (BBD cases) vs 4.7% (BBD controls), P = 0.007] conferred a breast cancer OR of 6.8 (95% CI, 1.4–32.4), P = 0.02, after adjusting for adipose tissue area (cm2), histologic impression, and BMI. As high CLS-B densities are independently associated with an increased breast cancer risk, they may be a promising histologic marker of breast cancer risk in BBD. Cancer Prev Res; 11(2); 113–9. ©2017 AACR.