Winham, Stacey J.

Abstract Purpose: Little is known about the role of the immune system in the earliest stages of breast carcinogenesis. We studied quantitative differences in immune cell types between breast tissues from normal donors and those from women with benign breast disease (BBD). Experimental Design: A breast tissue matched case–control study was created from donors to the Susan G. Komen for the Cure Tissue Bank (KTB) and from women diagnosed with BBD at Mayo Clinic (Rochester, MN) who either subsequently developed cancer (BBD cases) or remained cancer-free (BBD controls). Serial tissue sections underwent immunostaining and digital quantification of cell number per mm2 for CD4+ T cells, CD8+ T cells, CD20+ B cells, and CD68+ macrophages and quantification of positive pixel measure for CD11c (dendritic cells). Results: In 94 age-matched triplets, BBD lobules showed greater densities of CD8+ T cells, CD11c+ dendritic cells, CD20+ B cells, and CD68+ macrophages compared with KTB normals. Relative to BBD controls, BBD cases had lower CD20+ cell density (P = 0.04). Nearly 42% of BBD cases had no CD20+ B cells in evaluated lobules compared with 28% of BBD controls (P = 0.02). The absence of CD20+ cells versus the presence in all lobules showed an adjusted OR of 5.7 (95% confidence interval, 1.4–23.1) for subsequent breast cancer risk. Conclusions: Elevated infiltration of both innate and adaptive immune effectors in BBD tissues suggests an immunogenic microenvironment. The reduced B-cell infiltration in women with later breast cancer suggests a role for B cells in preventing disease progression and as a possible biomarker for breast cancer risk. Clin Cancer Res; 23(14); 3945–52. ©2017 AACR.

Abstract Background: The strongest known risk factor for endometrial cancer is obesity. To determine whether SNPs associated with increased body mass index (BMI) or waist–hip ratio (WHR) are associated with endometrial cancer risk, independent of measured BMI, we investigated relationships between 77 BMI and 47 WHR SNPs and endometrial cancer in 6,609 cases and 37,926 country-matched controls. Methods: Logistic regression analysis and fixed effects meta-analysis were used to test for associations between endometrial cancer risk and (i) individual BMI or WHR SNPs, (ii) a combined weighted genetic risk score (wGRS) for BMI or WHR. Causality of BMI for endometrial cancer was assessed using Mendelian randomization, with BMIwGRS as instrumental variable. Results: The BMIwGRS was significantly associated with endometrial cancer risk (P = 3.4 × 10−17). Scaling the effect of the BMIwGRS on endometrial cancer risk by its effect on BMI, the endometrial cancer OR per 5 kg/m2 of genetically predicted BMI was 2.06 [95% confidence interval (CI), 1.89–2.21], larger than the observed effect of BMI on endometrial cancer risk (OR = 1.55; 95% CI, 1.44–1.68, per 5 kg/m2). The association attenuated but remained significant after adjusting for BMI (OR = 1.22; 95% CI, 1.10–1.39; P = 5.3 × 10−4). There was evidence of directional pleiotropy (P = 1.5 × 10−4). BMI SNP rs2075650 was associated with endometrial cancer at study-wide significance (P < 4.0 × 10−4), independent of BMI. Endometrial cancer was not significantly associated with individual WHR SNPs or the WHRwGRS. Conclusions: BMI, but not WHR, is causally associated with endometrial cancer risk, with evidence that some BMI-associated SNPs alter endometrial cancer risk via mechanisms other than measurable BMI. Impact: The causal association between BMI SNPs and endometrial cancer has possible implications for endometrial cancer risk modeling. Cancer Epidemiol Biomarkers Prev; 25(11); 1503–10. ©2016 AACR.

Abstract Background: Age-related lobular involution (LI) is a physiological process in which the terminal duct lobular units of the breast regress as a woman ages. Analyses of breast biopsies from women with benign breast disease (BBD) have found that extent of LI is negatively associated with subsequent breast cancer development. Here we assess the natural course of LI within individual women, and the impact of progressive LI on breast cancer risk. Methods: The Mayo Clinic BBD cohort consists of 13,455 women with BBD from 1967-2001. The BBD cohort includes 1115 women who had multiple benign biopsies, 106 of whom had developed breast cancer. Within this multiple biopsy cohort, the progression of the LI process was examined by age at initial biopsy and time between biopsies. The relationship between LI progression and breast cancer risk was assessed using standardized incidence ratios (SIRs) and by Cox proportional hazards analysis. Results: Women who had multiple biopsies were younger age and had a slightly higher family history of breast cancer as compared with the overall BBD cohort. Extent of LI at subsequent biopsy was greater with increasing time between biopsies and for women age 55+ at initial biopsy. Among women with multiple biopsies, there was a significant association of higher breast cancer risk among those with involution stasis (lack of progression, HR 1.63) as compared with those with involution progression, p = 0.036. Conclusions: The multiple biopsy BBD cohort allows for a longitudinal study of the natural progression of LI. The majority of women in the multiple biopsy cohort showed progression of LI status between benign biopsies, and extent of progression was highest for women who were in the perimenopausal age range at initial biopsy. Progression of LI status between initial and subsequent biopsy was associated with decreased breast cancer risk. Citation Format: Derek Radisky, Daniel W. Visscher, Ryan Frank, Robert A. Vierkant, Stacey J. Winham, Melody L. Stallings-Mann, Tanya L. Hoskin, Aziza Nassar, Celine M. Vachon, Lori A. Denison, Lynn C. Hartmann, Marlene H. Frost, Amy C. Degnim. Natural history of age-related lobular involution and impact on breast cancer risk. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-364.

Abstract Breast density represents the stromal and epithelial tissue in the breast and is a strong risk factor for breast cancer. Reductions in breast density attributable to tamoxifen (TAM) and aromatase inhibitors (AI) may be associated with reduced risk of first primary and subsequent breast cancer. Studies assessing breast density changes have principally used two-dimensional measures. We assess changes in breast density following initiation of TAM and AI using two automated volumetric density measures that have shown strong associations to breast cancer risk. Breast cancer cases with a full field digital mammogram (FFDM) prior to diagnosis (index mammogram) and after initiation of TAM (n = 379) or AI (n = 425) were identified from the Mayo Clinic Mammography Practice and the San Francisco Mammography Registry. Volumetric percent density (VPD) and dense volume (DV) were measured on 4-view FFDM using VolparaTM (Matakina Technology) and QuantraTM (Hologic) automated software. We used linear regression to assess the effect of treatment on mean annualized change in VPD and DV (change from index to last mammogram divided by time interval) for each software type, adjusting for age, body mass index (BMI) and density at index mammogram. The median time between index mammogram and cancer diagnosis was 0.6 months (IQR: 0.2, 2.2) and median time between index and last mammogram was 3 years (IQR: 2.0, 3.9). Women on TAM were younger, had lower BMI and higher baseline VPD and DV relative to women on AI (Table). An annual decrease in VPD and DV was observed with both TAM and AI. Both Volpara and Quantra estimated a similar magnitude of change in VPD in women on TAM and AI, and a greater change in DV with TAM. Our findings suggest that both Volpara and Quantra can assess volumetric changes in breast density among women on hormone therapy. If declines in volumetric density correlate with a reduction in breast cancer risk, these automated measures could be used in clinical practice to assess response to therapy. Annualized changes in volumetric breast density estimated by linear regression.Tamoxifen (n = 379)Aromatase Inhibitors (n = 425)Baseline Median (IQR)Annualized Change (95% CI)*Baseline Median (IQR)Annualized Change (95% CI)*Age at Diagnosis50.0 (45.0, 60.0)–63.0 (58.0, 71.0)–Body Mass Index (BMI)23.6 (21.5, 26.8)–25.7 (22.7, 29.9)–Time Interval¥3.0 (2.1, 3.9)–3.0 (2.1, 3.9)–VolparaPercent Density (VPD,%)11.6 (6.8, 18.8)-0.17 (-0.27, -0.10)7.2 (5.0, 11.0)-0.19 (-0.29, -0.12)Dense Volume (DV, cm3)64.7 (45.4, 90.9)-0.90 (-1.45, -0.48)51.9 (38.9, 69.9)-0.52 (-0.93, -0.23)QuantraPercent Density (VPD,%)14.5 (9.2, 20.2)-0.42 (-0.59, -0.28)9.9 (7.1, 14.5)-0.38 (-0.54, -0.25)Dense Volume (DV, cm3)94.0 (58.0, 144.0)-2.20 (-3.52, -1.19)80.0 (49.0, 128.0)-0.95 (-1.85, -0.35)IQR = Interquartile range ¥ Median number of years between index mammogram and last mammogram post-initiation of therapy. *Annualized change estimated as change from index to last mammogram divided by time interval and adjusted for study site, age at diagnosis, BMI and density at index mammogram. Citation Format: Natalie J. Engmann, Celine M. Vachon, Christopher G. Scott, Matthew R. Jensen, Lin Ma, Kathleen R. Brandt, Amir P. Mahmoudzadeh, Serghei Malkov, Dana H. Whaley, Carrie B. Hruska, Fang F. Wu, Stacey J. Winham, Diana L. Miglioretti, Aaron D. Norman, John J. Heine, John Shepherd, V Shane Pankratz, Karla Kerlikowske. Longitudinal changes in volumetric breast density with adjuvant endocrine therapy among women with breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3424.

Abstract Background: Little transcriptomic research has compared epithelial ovarian cancer (EOC) histological subtypes. We set out to characterize the transcriptomes of high-grade serous carcinomas (HGSC) and endometrioid carcinomas (EC), which make up around 70% and 20% of EOC tumors, respectively, and have some histopathological similarities. Methods: Fresh frozen tumors from EOC patients seen at the Mayo Clinic (30 EC and 62 HGSC) were used. 1ug RNA riboZero was used for library preparation using the Illumina TruSeq kit and sequenced on a HiSeq 2000 machine. Reads were aligned using TopHat2 followed by quantification of abundances using RSEM and differential expression analysis with edgeR. We analyzed transcriptomes, conducted pathway analyses, and summarized key candidate gene sets. Expressed SNVs (eSNVs) from the RNA-seq data were determined using GATK and RVboost. Results: The analysis found 699 genes with FDR < 1×10-5 for differential expression between HGSC and EC, with most genes being up-regulated in EC. The top most associated genes were TPH1, MAP2K6, KLK2, ADAM23, TESC and TRAF3IP2 (p<10-22). Pathway analysis of the genes up-regulated in EC revealed enrichment of the “basal cell carcinoma signaling pathway” (p = 1.2×10-5). Within 1 Mb of the 25 known EOC risk loci, we observed higher expression in HGSC for RSPO1 and HPSE (p <5×10-7). For genes functionally related to EOC, we observed in HGSC up-regulation (*p < 10-5, ⁁p<0.003) for FOXM1⁁, CDKN2A⁁, CCNE1*, CCND2⁁, PIK3CA*, BRCA2⁁, BIRC5⁁, MMP9⁁, FANCD2⁁, and MAML2⁁. In contrast, we found up-regulation in EC for MDM2*, KLK4*, BCL2⁁, CCND1*, ANXA4*, CDH1⁁, MMP7⁁, and MAML3⁁. We also identified 204 eSNVs (44 non-synonymous) associated with EC v HGSC subtype (p<10-4); this included an exonic TRAF3IP2 eSNV (66% EC, 13% HGSC, p = 4×10-7, chr6:111877117). Discussion: Using one of the largest sets of identically processed fresh-frozen EOC tumors, some patterns emerged among the numerous EC v HGSC transcriptomic differences. TPH1, up-expressed in EC, is regulated by SOX4 which was also up-regulated in EC. Two sets of genes related to Kallikreins serine proteases were differentially expressed, including KLK2 which is known to regulate EGFR and pro-inflammatory cytokines and is regulated by MYC. Lastly, TRAF3IP2 encodes for a protein involved in regulating cytokines through members of the NFKB pathway. Conclusions: These findings suggest important biological insights into one of the rarer EOC histologies and may aid in the development of targeted treatment options. Research is on-going to incorporate additional features (e.g., DNA methylation, copy number) into a “systems biology” framework to better understand the molecular differences between EOC histologies. Citation Format: Brooke L. Fridley, Junqiang Dai, Rama Raghavan, Chen Wang, Pengcheng Lu, Stacey Winham, Madalene Earp, Kate Lawrenson, Simon A. Gayther, Kimberly R. Kalli, Ellen L. Goode. Transcriptome characterization of high grade serous and endometrioid epithelial ovarian cancer tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1833.

BACKGROUNDWomen with atypical hyperplasia (AH) on breast biopsy have a substantially increased risk of breast cancer (BC). Here the BC risk for the extent and subtype of AH is reported for 2 separate cohorts.METHODSAll samples containing AH were included from 2 cohorts of women with benign breast disease (Mayo Clinic and Nashville). Histology review quantified the number of foci of atypical ductal hyperplasia (ADH) and atypical lobular hyperplasia (ALH). The BC risk was stratified for the number of AH foci within AH subtypes.RESULTSThe study included 708 Mayo AH subjects and 466 Nashville AH subjects. In the Mayo cohort, an increasing number of foci of AH was associated with a significant increase in the risk of BC both for ADH (relative risks of 2.61, 5.21, and 6.36 for 1, 2, and ≥3 foci, respectively; P for linear trend = .006) and for ALH (relative risks of 2.56, 3.50, and 6.79 for 1, 2, and ≥3 foci, respectively; P for linear trend = .001). In the Nashville cohort, the relative risks of BC for ADH were 2.70, 5.17, and 15.06 for 1, 2, and ≥3 foci, respectively (P for linear trend < .001); for ALH, the relative risks also increased but not significantly (2.61, 3.48, and 4.02, respectively; P = .148). When the Mayo and Nashville samples were combined, the risk increased significantly for 1, 2, and ≥3 foci: the relative risks were 2.65, 5.19, and 8.94, respectively, for ADH (P < .001) and 2.58, 3.49, and 4.97, respectively, for ALH (P = .001).CONCLUSIONSIn 2 independent cohort studies of benign breast disease, the extent of atypia stratified the long‐term BC risk for ADH and ALH. Cancer 2016;122:2971‐2978. © 2016 American Cancer Society.

Abstract Background: Despite a large body of literature evaluating the association between recreational physical activity and epithelial ovarian cancer (EOC) risk, the extant evidence is inconclusive, and little is known about the independent association between recreational physical inactivity and EOC risk. We conducted a pooled analysis of nine studies from the Ovarian Cancer Association Consortium to investigate the association between chronic recreational physical inactivity and EOC risk. Methods: In accordance with the 2008 Physical Activity Guidelines for Americans, women reporting no regular, weekly recreational physical activity were classified as inactive. Multivariable logistic regression was utilized to estimate the ORs and 95% confidence intervals (CI) for the association between inactivity and EOC risk overall and by subgroups based upon histotype, menopausal status, race, and body mass index. Results: The current analysis included data from 8,309 EOC patients and 12,612 controls. We observed a significant positive association between inactivity and EOC risk (OR = 1.34; 95% CI, 1.14–1.57), and similar associations were observed for each histotype. Conclusions: In this large pooled analysis examining the association between recreational physical inactivity and EOC risk, we observed consistent evidence of an association between chronic inactivity and all EOC histotypes. Impact: These data add to the growing body of evidence suggesting that inactivity is an independent risk factor for cancer. If the apparent association between inactivity and EOC risk is substantiated, additional work via targeted interventions should be pursued to characterize the dose of activity required to mitigate the risk of this highly fatal disease. Cancer Epidemiol Biomarkers Prev; 25(7); 1114–24. ©2016 AACR.