Carter, Jodi M.

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 Existing risk models underperform among women who have undergone a benign breast disease (BBD) biopsy (&gt; one million performed annually in the US) and with respect to estimating the risk of aggressive BCs. We've shown that molecular pathologic analysis of BBD biopsies can improve individual risk prediction, compared with standard risk models relying on self-reported factors, and provide insights into mechanisms mediating BC risk. BC risk factors such as obesity and ethanol use are proposed to increase production of cytokines and chemokines, resulting in chronic inflammation, and leading to production of DNA damaging free radicals and growth factors (e.g., VEGF, IGFs) that activate pro-carcinogenic pathways (e.g. NF-KB and JAK/STAT). The effects of most BC risk factors on immunity are poorly understood. Further, whereas experimental models implicate immunity throughout carcinogenesis, knowledge of immune markers and mechanisms related to BC development among women is limited. Therefore, we aim to define tissue immune cell content throughout BC development, and particularly at the earliest stages, to improve risk assessment and discover immune-based prevention strategies. Our study combines novel resources and technologies to define the immune landscape in: 1) normal breast tissues in relation to BC risk factors, 2) BBD with respect to BC risk, and 3) invasive BC in relation to neoantigen expression and molecular subtype. We will perform NanoString GeoMxTM Digital Spatial Profiling (DSP) to quantitatively map expression of key immune proteins in healthy breast tissues donated to the Komen Tissue Bank (KTB) in relation to BC risk factors and in BBD biopsies from two cohorts to predict BC risk. We will re-analyze top prognostic markers in BBD biopsies using Vectra multiplex IF staining with machine learning algorithms to refine how immune cell content and organization impacts prognosis, and assess critical immune pathways related to BBD progression with the NanoString PanCancer IO 360 panel, which provides RNA expression of 770 immune genes (13 signatures). Finally, we will evaluate immune responses in BCs categorized for predicted neoantigen load and underlying mutation type with our novel bioinformatics pipeline that enables accurate prediction of MHC class I and class II missense, fusion and frameshift mutation neoantigens generated through faulty DNA repair, aberrant DNA and RNA splicing, insertions, and deletions. Our project demonstrates a novel approach to defining the immune processes in early stages of BC development which may improve BC risk prediction and prevention. We present a plan to comprehensively analyze immunity throughout BC development and define changes that accompany transitions from normal to BBD and BBD to BC. Citation Format: Doug Hinerfeld, Keith Knutson, Derek Radisky, E. Aubrey Thompson, Yan Asmann, Kim McCoy, Amy Degnim, Jodi Carter, Stacey Winham, Michele Cote, Jeroen van der Laak, Mark Sherman. Analysis of the immune microenvironment to advance breast cancer risk prediction and prevention [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 651.

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.

Objective: The purpose of this study is to evaluate diffusion weighted magnetic rsonance imaging (MRI) acquisitions in delineating posterior extent of breast tumors and in predicting chest wall invasion prior to treatment. To our knowledge, there has not been any literature specifically evaluating the utility of diffusion-weighted acquisitions in chest wall invasion of breast tumors. Materials and Methods: A retrospective review of our breast imaging database for keywords “chest wall invasion” and “breast MRI” was performed over the last 14 years. Diffusion sequences, T1 sequences (pre and post contrast), and T2 sequences were evaluated. Apparent diffusion coefficient (ADC) values in tumor and chest wall were assessed. Imaging findings were correlated with surgical pathology. Results: 23 patients met inclusion criteria. All 23 had loss of fat plane on T2 sequences. 22/23 had loss of fat plane on postcontrast T1 sequences. Pectoralis muscle enhancement was present in 19/23 (83%) tumors and chest wall enhancement was present 9/23 (39%) tumors. Qualitative restricted diffusion within the pectoralis muscle was present in 18/23 (71%) tumors and in the chest wall was present in 8/23 (35%) tumors. Mean ADC values were 1.15 s/mm2 in the tumor and 1.29 s/mm2 in the chest wall. Sensitivity, specificity, positive predictive value and negative predictive value were 100%, 36%, 63%, and 100% for chest wall enhancement respectively and 69%, 36%, 61%, and 80% for chest wall diffusion-weighted imaging restriction respectively. Conclusion: Diffusion weighted sequences can be helpful in characterizing chest wall invasion of breast tumors.

Abstract Background: Despite a paucity of data on the benign breast transcriptome, reduction mammoplasty tissue is commonly used as a control for RNA biomarker discovery in breast cancer (BC). We evaluated the transcriptome of benign breast to characterize pre-menopausal and post-menopausal coding and non-coding RNA profiles. These profiles will provide insight into the metabolic landscape of benign breast and inform transcriptomic studies of BC and peri-tumoral microenvironments. Methods: With institutional approval, cryobanked fresh breast tissues from reduction mammoplasties (age 15-62y; follow-up: 4-10 y with no cancer events), with histologically-confirmed benign tissues with similar epithelial: stromal tissues were grouped into 4 age sets (&lt; 30y, N=10; 30-39y, N=11; 40-49y, N=10; ≥50y (clinically post-menopausal), N=10). Following RNA extraction, library preparation (Illumina TruSeq Stranded mRNA kit), and sequencing (Illumina HiSeq 4000), reads were processed (MAP-RSeq v3.0.0) and aligned (STAR aligner; hg38). Differential expression (DE) analysis (edgeR 2.6.2) identified DE genes from normalized RPKM reads (absolute log2 fold change (FC) &gt; 1 and false discovery rate (FDR) &lt; 0.10), corrected for intra-group biases using medians (absolute FC cut-off of &gt;1.5). Over-representation analysis [Ingenuity pathway analysis (IPA), Ingenuity® Systems] and gene set enrichment analysis [(GSEA), GeneTrail 2.0] identified significantly-enriched pathways. Results: Across the 4 age sets, 561 DE genes were identified. Compared to the post-menopausal (PM) set, the number of DE genes was highest in &lt;30 y set (N= 372) and decreased with increasing age (N= 170, age 30-39 set and N=20, age 40-49 set), generating up-regulated (PMup) and down-regulated (PMdown) PM transcriptomic profiles. The top PMdown DE genes included RANKL, WNT4, MKI67, extracellular matrix, and lactation-related genes (lactoferrin ,MUC4, MUC16, p &lt; 0.01). Top PMdown canonical pathways were cell cycle-related (CDK1, CCNA2, CCNB2, ESPL1, TOP2A)(p&lt; 0.001). Top PMup genes included those involved in adipogenesis, NPY1R, NPY2R, unsaturated fatty acid synthesis and eicosanoid signaling (P&lt; 0.001). Top PMup canonical pathways included acyl co-A hydrolysis, stearate biosynthesis, acute phase response and RXR signaling (P &lt; 0.001). GSEA of the entire gene set (N=15,466; ranked in order of 561 DE genes) identified 16 significant pathways, functionally grouped as mitochondrial energy metabolism, proteasome, and unsaturated fatty acid biosynthesis and signaling (PPAR pathway). While coding RNAs comprised 85% of DE transcripts, lncRNA comprised ˜5%. Top DE lncRNAs and precursor miRNAs included MEG3, a tumor suppressor, LIN00092, miR22 and miR1182 (p &lt; 0.0001). Conclusions: Pre and post-menopausal benign breast tissues have distinctive transcriptomic profiles. PM benign breast has down-regulated proliferation/cell-cycle-related pathways, and up-regulated genes in mitochondrial energy pathways, lipogenesis and inflammatory pathways. Notably, many of the top DE coding and non-coding RNAs in PM benign breast have been implicated in BC progression, highlighting their value in better understanding breast carcinogenesis and the need to characterize their functional roles in normal aging and menopause. Citation Format: Carter JM, Nair AA, Davila JI, Heinzen EP, Hoskin TL, Winham SJ, Radisky DC, Degnim AC, Visscher DW. Distinctive coding and non-coding RNA profiles of pre-menopausal and post-menopausal benign breast [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-06-01.

Abstract Background: Differences in ER+ and ER- breast cancer tumor biology are well-documented, but little is known about the field of background benign breast in which those cancers arise. We evaluated the transcriptome of benign breast tissues from women with concurrent ipsilateral ER+ and ER- breast cancers (BC) to characterize coding and non-coding RNA profiles. This pilot study provides insight into the transcriptomic landscapes of benign breast tissues in patients with BC, and the microenvironment of the at-risk benign tissue. Methods: With institutional approval, cryobanked breast tissues from patients with concurrent ipsilateral ER+ BC (benign ER+BC, N=14) or ER- BC (benign ER-BC, N=10), were selected for benign tissues with similar epithelial:stromal ratios and grouped into pre (preM) and post-menopausal (PM) groups. Following RNA sequencing (Illumina TruSeq Stranded mRNA kit & Illumina HiSeq 4000), reads were processed (MAP-RSeq v3.0.0) and aligned (STAR aligner; hg38). Differential expression (DE) analysis (edgeR 2.6.2) identified DE genes from normalized RPKM reads (absolute log2 fold change (FC) &gt; 1 and false discovery rate (FDR) &lt; 0.10), corrected for intra-group biases. Over-representation analysis [Ingenuity pathway analysis (IPA), Ingenuity® Systems] and gene set enrichment analysis [(GSEA), GeneTrail 2.0] identified significantly-enriched pathways. Results: In the PM group, there were 144 DE transcripts between benign ER+BC and benign ER-BC, including coding RNAs (40%), antisense RNAs (35%) and lncRNAs (7%). In contrast, the preM group had no significantly DE genes between benign ER+BC and benign ER-BC. In the PM DE coding gene set, the top DE transcripts in benign ER+BC included many genes implicated in BC development# or ER+ BC progression (*) (e.g. up-regulated: KAAG1*, DNAJB7/HSP40*, TMEM151B, ZBTB32# p &lt; 0.001 ; down-regulated: CPB1*, FOS, TPPP3#, CLEC3B#p &lt; 0.001). Top canonical pathways altered in benign ER+BC included MAPK, PI3K, and acute phase response pathways (p&lt;0.05). GSEA of the entire gene set (N=15,223; ranked in order of 144 DE genes) identified 72 altered pathways (P &lt; 0.005); those with the highest normalization enrichment scores (NES) (&gt; 0.4) functionally grouped as immune function-related (T cell function and antigen presentation). Depleted pathways with NES &gt; 0.4, (N=6) functionally grouped into proteasome-related, fatty acid biosynthesis and mitochondrial energy metabolism. Among the non-coding DE gene set, notably, the entire DE antisense RNA gene set (N=51 transcripts) was up-regulated in benign ER+ BC compared to benign ER-BC (P&lt; 0.001) with a subset (N=11) showing marked up-regulation (&gt; 4 log2FC). Among the DE antisense RNAs, 70% have reported roles in carcinogenesis or BC progression (e.g. KRT7-AS, NAV2-AS2, CCDC144NL-AS1, RP11-66B24.4, HSA-MIR4454). Conclusion: The benign breast transcriptome differs between postmenopausal women with ER+ vs ER- BC, with distinctive coding and non-coding RNA signatures. In postmenopausal women with ER+ BC, benign breast expresses a unique antisense RNA set and is enriched in genes implicated in BC development or progression. These data provide insight into at-risk benign breast and facilitate identification of potential biomarkers of carcinogenesis. Citation Format: Carter JM, Nair AA, Davila JI, Heinzen EP, Hoskin TL, Winham SJ, Radisky DC, Visscher DW, Degnim AC. A unique coding and non-coding benign breast transcriptome in post-menopausal ER+ breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-08-10.