Visscher, Daniel W.

Abstract Distinct subtypes of triple negative (TN) breast cancer have currently been identified by tumor expression profiling and are thought to be influenced by the tumor microenvironment. However, little is known about the relationship between distinguishing histopathologic features of TN tumors, which reflect aspects of both tumor behavior and tumor microenvironment, and molecular TN subtypes. We analyzed whole genome expression profiles of 593 TN tumors from the Triple Negative Breast Cancer Consortium (TNBCC) using the Illumina Whole Genome DASL array. Histopathologic review of mitotic index, grade, trabecular pattern, growth pattern, involution, presence of ductal carcinoma in situ, and degree of lymphoid infiltrate, necrosis, fibrosis, and lobulitis was completed for 310 of these tumors. Clusters were identified both agnostically and using genes associated with these histopathologic features, and subtypes were evaluated for enriched pathways and associations with histopathologic features. Agnostic clustering identified four stable clusters which represented a basal-like (BL) signature, a luminal signature with overexpression of androgen receptor and targets, an immune signature, and a stromal (STR) signature. Overall, the TN tumors tended to have little or no necrosis (91%), high grade (88%), a high mitotic index (80%), fibrosis (77%), an epicentric growth pattern (62%), incomplete lobular involution (55%), trabecular structures (37%), lymphocytic infiltration (25%), adjacent ductal carcinoma in situ (24%), and variable amounts of lobulitis. Using a combined total of 2,776 unique probes individually associated with the ten histopathologic features measured, we identified six distinct TN subtypes, with an additional BL and STR signature compared to the four agnostic subtypes. Our findings suggest that histopathologic features that reflect heterogeneity in tumor cell structure and behavior as well as the tumor microenvironment, particularly the presence of lymphocytic infiltrate, are critical for TN subtype identification. Further work is needed to validate these signatures and to better understand the immunologic pathways associated with each subtype. Citation Format: Kristen Purrington, Daniel Visscher, Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Arto Mannerma, Xianshu Wang, Graham Giles, Wei Zheng, Angela Cox, Hiltrud Brauch, Ute Hamann, Diana Eccles, Celine M. Vachon, Fergus J. Couch. Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1924. doi:10.1158/1538-7445.AM2015-1924

Abstract INTRODUCTION Next generation sequencing (NGS) of patients has significantly changed our ways to study cancer genomics as it provides precise estimates of gene expression, fusion transcripts, expressed single nucleotide variants (eSNVs), splice variants and copy number variants. The Breast Cancer Genome Guided Therapy (BEAUTY) is an ongoing clinical study in which RNA sequencing (RNAseq) and whole exome sequencing (WES) are performed prior to, during and after neoadjuvant chemotherapy. Here we report the use of these sequencing technologies to investigate gene expression levels and mutational profiles in a triple negative breast cancer (TNBC) patient enrolled in BEAUTY whose disease did not respond to neoadjuvant paclitaxel and anthracycline/cycphosphamide. METHODS Computational approaches were used to integrate WES and RNAseq data obtained before therapy (V1T), after 12 weekly paclitaxel treatments (V2T) and after anthracycline-based regimen at surgical resection (V3T) to study a single patient with persistent TNBC disease after neoadjuvant chemotherapy. RESULTS Using RNA-Seq data, we identified an inter-chromosomal fusion transcript between chromosome 20 and 22 (GNAS-TTC38) that was highly expressed at V1T, V2T and V3T. We also identified intra-chromosomal fusion transcripts that were expressed at two time points, such as fusion transcript (KANSL1-ARL17A) on chromosome 17 for V1T and V2T and fusion transcript (RBM12B-LINC00535) on chromosome 8 for V2T and V3T time points. Several gene expression changes were also observed. Gene expression analysis of V1T, V2T and V3T tumors was performed. Differential temporal gene expression profiles of 9884 genes that were significant and varying at different time points were obtained for pathway analysis. Pathway analysis of 9884 genes identified up regulation and down regulation of several transcription factors with a fold change of 2x or more. When compared to blood, DNA tumor and RNA-Seq data, we identified 81 common somatic eSNVs that were expressed in both V1T and V2T time points and we are in the process of investigating V3T data. We found alterations of key transporter domains (CD225, Coatamer_beta_C, DUF2435, Dynamitin, EI24, GLTP, LMF1, Porin_3, V-ATPase_C) in our V1T and V2T SNV data. Similar to gene expression analysis, we are in the process of obtaining the list of mutations at various time points to identify driver and passenger mutation candidate genes for this specific TNBC patient. CONCLUSIONS Our initial time-series analysis of eSNV, fusion transcripts and gene expression data demonstrate that intensive analysis for individual patients is feasible. Further investigation of drug transporters and transcription regulators may help develop personalized treatment strategies for patients with disease resistant to current regimens. Citation Format: Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Douglas W. Mahoney, Poulami Barman, Jason P. Sinnwell, Hugues Sicotte, Peter Vedell, Steven N. Hart, Travis J. Dockter, Katie N. Jones, Amy L. Conners, Ann M. Moyer, Daniel W. Visscher, Jia Yu, Bowen Gao, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Jean-Pierre A. Kocher, Eric D. Wieben, Gianrico Farrugia, Cloann G. Schultz, James N. Ingle, Richard Weinshilboum, Matthew P. Goetz, Liewei Wang, Judy C. Boughey. Analysis of sequencing data to identify potential drug targets for an individual newly diagnosed with basal breast cancer who failed to respond to current standard neoadjuvant chemotherapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4185. doi:10.1158/1538-7445.AM2014-4185

Abstract Introduction: Histologic characteristics of nonmalignant breast tissues (epithelial proliferation and involution) are associated with future breast cancer (BC) risk. We evaluated immune infiltration (lobulitis) in benign breast lobules and its association with features of BC risk. Methods: We analyzed archived nonmalignant breast tissue samples from 81 women in age-matched groups of varying cancer risk: 27 with benign breast disease (BBD) who later developed BC (cases), 27 with BBD without subsequent BC (controls), and 27 normal women without clinical breast disease from the Komen Tissue Bank at Indiana University (KTB). Up to 10 lobules in each sample were characterized by H&E for lobulitis, involution (none, partial, complete), and fibrocystic (FC) status (normal, nonproliferative, proliferative). Lobulitis was defined by H&E staining as lymphocyte nuclei in the intralobular stroma at low magnification and between adjacent acini at high magnification. Data was analyzed by mixed effects logistic regression. Results: Median age was 57 years (range 37-70). Among 81 breast tissue samples, 750 lobules were evaluated: 249 in BBD Cases, 265 in BBD Controls, and 236 in KTB donors. 56% of lobules were normal and 44% were FC, with 87% of FC lobules occurring in BBD samples. Lobulitis was present in 44% of lobules and varied according to subject age and individual lobule features. Younger women were more likely to have lobulitis (p=0.002); among women <50 the median proportion of lobules with lobulitis was 50%, versus 30% among women 50+. Lobulitis was less frequent in lobules with complete involution (37%) compared to partial (74%) or no involution (84%), p<0.0001. Lobulitis was common in normal lobules (52%) and decreased with increasing epithelial abnormality-39% of nonproliferative lobules and 27% of proliferative lobules (p<0.0001). In multivariate analysis including all 3 variables, all 3 remained significantly associated with lobulitis: age (p=0.03), proliferation (p<0.0001), and involution (p=0.0001). Lobules with lobulitis were less frequent in groups of women with increased breast cancer risk-55% of lobules in normal KTB samples, 43% in BBD controls, and 35% in BBD cases (p = 0.02). Conclusion: Lobulitis is common in normal and benign breast tissue lobules but varies with age, involution status, and epithelial abnormality. Further work is needed to understand the role of immune infiltrates in breast cancer risk. Citation Format: Rushin D. Brahmbhatt, Daniel W. Visscher, Tanya L. Hoskin, Derek C. Radisky, Linda M. Murphy, Melody L. Stallings Mann, Erin Miller, Vernon S. Pankratz, Lynn C. Hartmann, Marlene H. Frost, Amy C. Degnim. Immune infiltration of normal and benign breast lobules varies in breast tissues based on cancer risk. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1652. doi:10.1158/1538-7445.AM2014-1652

Abstract Background Cancer genomic investigations have identified recurrent genomic aberrations critical for cancer initiation, progression, and metastases. However, these investigations are typically performed in isolation, and the effects of treatment on the clonal selection of tumor cells are mostly unknown. We hypothesized that molecular profiling of residual tumors after neoadjuvant chemotherapy (NAC) would identify new drug targets/pathways in patients at high risk for disease recurrence. To better identify clonal populations of resistant breast cancer cells, we utilized DNA content-based flow sorting of nuclei to identify and isolate clonal populations for aCGH and next generation sequencing (NGS) both before and after NAC. Methods The Breast Cancer Genome Guided Therapy Study (BEAUTY) (NCT 02022202) is a prospective study of patients with high-risk breast cancer treated with neoadjuvant 12 weekly paclitaxel (T) +/- trastuzumab followed by 4 cycles of anthracycline based chemotherapy. Tumor tissue from baseline, residual disease from surgery, distant metastases, and patient derived xenografts (PDX) are obtained for cell sorting by DNA ploidy, aCGH, RNA and exome sequencing. Results: 140 patients have been enrolled, 104 have completed surgery and 30 unique PDX have been established corresponding to 26 patients prior to chemotherapy and 4 from residual disease at surgery. Baseline exome and RNA sequencing is complete in 140. Currently, genomic analyses of flow sorted matched baseline, surgical, PDX, and distant disease samples are available in 6 patients. Substantial genomic variation was observed in the surgical sample compared to the primary tumor including gain of oncogenic drivers (EGFR) and loss of negative regulators (ATG5) (Table). The PDX recapitulated these events with excellent fidelity compared to the corresponding human tumor. In patients with TNBC, RNA seq obained from matched samples demonstrated changes in immune related pathways. Evaluation of drug targets/pathways identified in the resistant tumors are ongoing using the PDX and sequencing of the remaining matched baseline/surgical disease will be reported. Clonal changes occurring over time in patients with residual disease or disease recurrence after NACTumor SubtypeResidual Cancer BurdenDisease StatusClonal Aberration Changes (baseline and post NAC)TNBC (AR subtype)3Contralateral lymph node recurrence at 150 days2p25.2 - p25.1 amplicon lost at recurrence; 6p21.32 -p21.31 amplicon lost at recurrenceTNBC (BL 1)3Bone/liver/lymph node recurrence at 135 days5q11.2 amplicon gained at surgery; 12p13.33 - p13.2 amplicon gained at surgeryTNBC (BL 1)3Disease-free at day 1506q21 amplicon lost at sugeryTNBC (BL 2)0Brain recurrence at 390 daysChr 2 chromothripsis at surgeryLuminal B3Progression during chemotherapy7p12.1 - p11.2 amplicon gained at surgeryLuminal HER23Disease-free at day 3609q33.2 amplicon lost at surgery; 15q13.1 - q13.3 amplicon lost at surgery; 15q22.2 - q24.1 amplicon lost at surgery Conclusions: We observed substantial evolutionary changes in residual breast tumors remaining after NAC. Our findings suggest that a comprehensive assessment of the mutational landscape that has evolved during NAC can inform drug development in high risk breast cancer patients. Citation Format: Matthew P Goetz, Michael T Barrett, Krishna R Kalari, Vera J Suman, Sarah A McLaughlin, Alvaro Moreno-Aspitia, Ann M Moyer, Donald W Northfelt, Richard J Gray, Jason Sinnwell, Douglas Mahoney, Poulami Barman, Peter Vedell, Xiaojia Tang, Kevin Thompson, Travis Dockter, Katie Jones, Sara J Felten, Amy Conners, Jeanette Eckel-Passow, Hughes Sicotte, Steven N Hart, Jia Yu, Daniel W Visscher, Eric D Wieben, Cloann Schultz, Minetta C Liu, James N Ingle, Liewei Wang, Richard W Weinshilboum, Judy C Boughey. Impact of neoadjuvant chemotherapy on the clonal composition of breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr PD3-3.

Abstract Background: Mammographic breast density (MBD) reflects the proportion of fibroglandular tissue in the breast, and is an established risk factor for breast cancer. Benign breast disease (BBD) is also a known risk factor for breast cancer. We previously showed an association between lobular involution (physiologic atrophy) and MBD in a large cohort study of women with BBD. We performed a comprehensive evaluation of the association of histologic features of BBD with MBD. Methods: The Mayo BBD cohort includes women, 18 to 85 years, who were diagnosed with BBD at Mayo Clinic in Rochester, MN between 01/01/1967 and 12/31/1991. For this study, we included women who had a mammogram within 6 months of BBD diagnosis, and diagnosed with BBD between 1985 and 1991 when parenchymal pattern of breast density was clinically recorded. Risk factor information such as age, and body mass index (BMI) was collected from medical records. Parenchymal pattern, assessed clinically and previously used in multiple studies of MBD and risk, classified breast density based on extent and type of density, into four categories: N1 (non-dense, no ducts visible); P1 (ductal prominence occupying <25% breast); P2 (prominent ductal pattern occupying >25% of the breast; DY (homogenous plaque-like areas of density). All assessments of benign breast tissue were performed by expert breast pathologists blinded to both MBD and BBD reports. Histologic characteristics included overall impression (non-proliferative disease (NPD), proliferative disease without atypia (PDWA), and atypical hyperplasia (AH)), proportion of normal lobules that were involuted (no (0%), partial (1 to 74%), or complete (≥75%)), type of AH (ADH or ALH), ductal and lobular hyperplasia, calcifications, sclerosing adenosis, columnar alteration, cyst, fibroadenoma, marked fibrosis, intra-ductal papilloma, radial scar (number and size), duct ectasia, and mucocele like tumors. Associations of parenchymal pattern with BBD characteristics were examined using multicategorical nominal logistic regression models. We first examined associations after adjustment for age and BMI. All variables statistically significant (p<0.05) in these models were then simultaneously included in a fully-adjusted model. Results: Of 2,257 women in the study, 14% were <40 years old, 52.7% between 40- 59 years, and 32.9% were ≥60 years. In this sample, 55.2% of women had NPD, 36% had PDWA, and AH in 8.8%. MBD was classified as N1 in 21.8%, P1 in 12.6%, P2 in 23.7% and DY in 41.9%. Age- and BMI-adjusted analyses showed that there was an association of parenchymal pattern with overall impression, lobular involution, ductal hyperplasia, sclerosing adenosis, columnar alteration, cyst, duct ectasia and fibrosis. Multivariate analyses found that women of younger age (p<0.001) and with lower BMI (p<0.001), presence of fibrosis (p<0.001) and no involution (p=0.016) were more likely to have P2 or DY parenchymal pattern than women without those characteristics. Conclusion: Among women with benign breast disease, higher MBD is associated with younger age, lower BMI, fibrosis, and lack of lobular involution. These findings, concordant with other studies of MBD, provide insight into underlying mechanisms by which MBD and BBD contribute to breast cancer risk. Citation Format: Karthik Ghosh, Robert A Vierkant, Ryan D Frank, Daniel W Visscher, Vernon S Pankratz, Christopher G Scott, Derek C Radisky, Marlene H Frost, Lynn C Hartmann, Amy C Degnim, Celine M Vachon. Association between mammographic breast density and histologic features of benign breast disease [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-10-14.

Abstract Introduction: Current models to predict breast cancer risk do not differentiate risk for estrogen receptor (ER) positive and negative breast cancer (BC), despite growing evidence that these tumors are biologically very different. We hypothesized that women with ER+ BC cancers have different clinical risk factors and histologic findings on prior benign breast biopsies than those with ER- BC. Methods: After IRB approval, we examined associations of age at benign biopsy and histologic features of the benign biopsy with ER status of incident BCs within the Mayo Benign Breast Disease Cohort. Benign biopsy slides were reviewed for extent of lobular involution and degree of epithelial proliferation by a single breast pathologist blinded to BC events. Invasive BCs occurring within 15 years after benign biopsy were classified as ER+ if ER staining was >1%. BC case-only associations with ER status were evaluated using multivariate logistic regression. Full-cohort hazard ratios (HR) and 95% confidence intervals (CI) for risk of ER-specific subtypes were estimated using Cox proportion hazards regression. Results: Among 13,410 women undergoing a benign breast biopsy from 1967-2001, 656 invasive BCs (459 ER+, 106 ER, 106 unknown) occurred within 15 years. Women who developed ER+ and ER- BCs were similar in age at the time of their prior benign breast biopsy (p=0.34). Although benign biopsies in women who later developed ER+ BC were more likely to show complete involution (23% vs 15% for ER- BC), this was not statistically significant (p=0.06). However, the degree of epithelial proliferation was significantly associated with ER status of later BCs (p=0.001), with ER+ BCs more likely than ER- BCs to have had a prior biopsy with atypical hyperplasia (16% vs 8%), and ER+ BCs less likely than ER- BCs to have had a prior biopsy with proliferative disease without atypia (33% vs 52%); this association remained after multivariate adjustment (p=0.003). We further pursued the association of epithelial proliferation with differential risk of ER+ and ER- BC in our overall cohort of 13,410 women (Table 1). Compared to women with non-proliferative disease, women with proliferative disease +/- atypia had ∼2-fold hazard ratios for ER- BC, whereas hazard ratios for ER+ BC were higher in women with atypical hyperplasia (∼4-fold) compared to proliferative disease. Hazard Ratio of ER+ and ER- BC within 15 years of BBD based upon degree of epithelial proliferation at benign biopsyCancer TypeGroupNN EventsHazard Ratio (95% CI)p-valueInvasive ER- ≤15 yearsNP8478421.00 (ref)<0.0001 PD4229542.63 (1.76, 3.93) AH70382.60 (1.22, 5.54) Invasive ER+ ≤15 yearsNP84782321.00 (ref)<0.0001 PD42291511.33 (1.09, 1.64) AH703744.41 (3.39, 5.73) NP=nonproliferative disease, PD=proliferative disease without atypia; AH=atypical hyperplasia Conclusion: ER+ and ER- breast cancers appear to have different features on prior benign breast biopsy, with atypical hyperplasia showing increased risk for both types of breast cancer, but a greater risk for ER+ tumors. Citation Format: Amy C Degnim, Derek C Radisky, Robert A Vierkant, Ryan D Frank, Marlene H Frost, Vernon S Pankratz, Celine M Vachon, Tanya L Hoskin, Julie M Cunningham, Chen Wang, Jean-Pierre Kocher, Teresa M Allers, Joanne L Johnson, Tina J Hieken, Karthik Ghosh, Lynn C Hartmann, Daniel W Visscher. Histologic features of benign breast biopsy tissue and association with ER positive and ER negative breast cancer in the Mayo BBD cohort study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-10-06.

Abstract Recent studies have shown that associations between common genetic variation and gene expression in breast tumors provide insight into the functional mechanisms underlying breast cancer risk loci. However, the relationship between genetic variation, gene expression, and risk of triple negative (TN) breast cancer remains largely unexplored. We performed a genome-wide expression quantitative trait locus (eQTL) analysis of TN breast cancer using 668 formalin-fixed paraffin embedded TN tumors from the Triple Negative Breast Cancer Consortium (TNBCC) to identify novel genes relevant to TN breast cancer risk and to further explore the biology underlying known TN risk loci. Cis-eQTLs were defined as correlations between single nucleotide polymorphisms (SNP) and expression of genes within 1Mb, and trans-eQTLs were defined as the remainder of all SNP-gene correlations. In a genome-wide analysis, we identified 68,012 cis-eQTLs, representing correlations between 42,193 SNPs and 2,092 genes that were significant at a 10% false discovery rate (FDR). We also identified 70 trans-eQTLs across two unique genes at the same FDR threshold. Five cis-eQTLs involved SNPs previously associated with TN breast cancer risk (p<5.0x10-5) in 3,700 TN cases and 4,700 controls from the TNBCC. Three of these, located on chromosomes 5p (cis-eQTL p=4.8x10-34; risk p=1.1x10-7), 7p (cis-eQTL p=6.1x10-10; risk p=1.3x10-7), and 17q (cis-eQTL p=1.8x10-15; risk p=2.9x10-7), have previously been reported in public databases of normal tissue. The remaining two TN breast cancer cis-eQTLs, located on chromosomes 8q (cis-eQTL p=6.3x10-6, risk p=8.3x10-6) and 14q (cis-eQTL p=3.1x10-6, risk p=1.2x10-5), have not been reported as eQTLs in other tissues. In addition, 12 of 25 known TN breast cancer risk loci (PEX14, MDM4, 2q31.1, ESR1, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, 19p13.1, MLK1), contained at least one significant cis-eQTL. In summary, we have identified five cis-eQTLs that may identify novel risk loci for TN breast cancer. Citation Format: Kristen S. Purrington, Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Angela Cox, Gianluca Severi, Christine Ambrosone, Amanda Ewart Toland, Andrew K. Godwin, Hiltrud Brauch, Peter A. Fasching, Penelope Miron, Jenny Chang-Claude, Nicholas G. Martin, Grant W. Montgomery, Vessela Kristensen, Hoda Anton-Culver, Paul Goodfellow, Janet E. Olson, Hugues Sicotte, Naresh Prodduturi, Daniel W. Visscher, Jeanette E. Eckel-Passow, S. Keith Anderson, Seth Slettedahl, Curtis Olswold, Xianshu Wang, V. Shane Pankratz, Susan Slager, Wei Zheng, Arto Mannermaa, Ute Hamann, Diana M. Eccles, Celine M. Vachon, Fergus J. Couch. Expression quantitative trait locus analysis of triple negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3266. doi:10.1158/1538-7445.AM2014-3266

Abstract INTRODUCTION Patient derived xenografts (PDX) may better reflect individual patient (pt) tumor biology; however, the feasibility of collecting PDX from percutaneous tumor biopsies (PTB) in the neoadjuvant setting is unknown. Furthermore, drug response phenotypes observed in PDX have not been prospectively compared to the corresponding pt clinical outcomes. METHODS The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective Mayo study of pts with high-risk breast cancer treated with neoadjuvant weekly paclitaxel (T) +/- trastuzumab followed by anthracycline based chemotherapy. PTB (at baseline) and residual surgical tissue (after all chemotherapy) are obtained for next generation sequencing (NGS) and PDX. Tumor biopsies (1-2 cores from 14 gauge needle) were implanted with Matrigel <1 hour of collection in the flanks of NOD-SCID or NSG mice. Low dose estradiol was supplemented in the drinking water. Primary outgrowth rate was defined as PDX tumor volume >50 mm3. Take rate was defined as development of at least 1 stably transplantable xenograft line/pt. To determine whether clinical T response assessed by MRI corresponded with in vivo T response, pretreatment PDX from 5 pts were injected into NOD-SCID mice (20 mice per pt PDX) and when tumors reached 100-200mm3, mice were randomized to no treatment vs T (20 mg/kg, ip. every 3-4 days). Two of these 5 patients had a MRI response defined as >30% decrease in longest lesion. RESULTS Pretreatment PTB from 81 unique pts were implanted in 251 mice (2-4 mice/pt). PDX outgrowth rates were 33.3% (27/81 pts) and 22 stable PDX were established (overall take rate 27.2%). Take rates were as follows: triple negative breast cancer (46%; 13/28); HER2 (27%; 6/22), Luminal B (13%; 3/22), and luminal A (0%; 0/9). Residual surgical tumor (after all treatment) from 17 pts was injected into 85 mice (average 5 mice/pt) and the initial outgrowth rate was 23% (4/17) with 3 stably transplantable lines established. PDX, derived from pretreatment PTB of 5 pts (2 responders and 3 non-responders), were assessed for in vivo T response. The size of the T treated group was significantly smaller than the no treatment group for the PDX derived from the 2 clinical responders, with complete disappearance of tumor by 18 days. In contrast, the PDX derived from the 3 clinical non-responders had no evidence for T response. CONCLUSIONS We have demonstrated the feasibility of using PTB to establish PDX in a prospective neoadjuvant clinical study and have demonstrated similar T drug response phenotypes in in the PDX as seen in the corresponding pt. These data suggest that PDX generated prospectively may be useful for biomarker validation and the development and individualization of new drug therapy. Funded by the Mayo Clinic Center for Individualized Medicine and the Mayo Clinic Cancer Center Citation Format: Jia Yu, Ping Yin, Bowen Gao, Jason P. Sinnwell, Ann M. Moyer, Daniel W. Visscher, Amy L. Conners, Travis J. Dockter, Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Hugues Sicotte, Douglas W. Mahoney, Steven N. Hart, Peter T. Vedell, Poulami Barman, Katie N. Jones, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Zhenkun Lou, Gianrico Farrugia, Richard Weinshilboum, Matthew P. Goetz, Judy C. Boughey, Liewei Wang. Feasibility of using percutaneous tumor biopsies from a prospective neoadjuvant breast cancer study to develop patient derived xenografts and assess in vivo chemotherapy sensitivity. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1195. doi:10.1158/1538-7445.AM2014-1195

Abstract Background: Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)–negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes. Methods: Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression. Results: DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; Ptrend <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; Ptrend <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (Ptrend < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER+ versus ER− tumors (Phet = 0.02), while NDA was more strongly associated with decreased risk of ER− versus ER+ tumors (Phet = 0.03). Conclusions: DA and NDA have differential associations with ER+ versus ER− tumors that vary by age. Impact: DA and NDA are important to consider when developing age- and subtype-specific risk models. Cancer Epidemiol Biomarkers Prev; 24(5); 798–809. ©2015 AACR.

Purpose Optimal early detection and prevention for breast cancer depend on accurate identification of women at increased risk. We present a risk prediction model that incorporates histologic features of biopsy tissues from women with benign breast disease (BBD) and compare its performance to the Breast Cancer Risk Assessment Tool (BCRAT). Methods We estimated the age-specific incidence of breast cancer and death from the Mayo BBD cohort and then combined these estimates with a relative risk model derived from 377 patient cases with breast cancer and 734 matched controls sampled from the Mayo BBD cohort to develop the BBD–to–breast cancer (BBD-BC) risk assessment tool. We validated the model using an independent set of 378 patient cases with breast cancer and 728 matched controls from the Mayo BBD cohort and compared the risk predictions from our model with those from the BCRAT. Results The BBD-BC model predicts the probability of breast cancer in women with BBD using tissue-based and other risk factors. The concordance statistic from the BBD-BC model was 0.665 in the model development series and 0.629 in the validation series; these values were higher than those from the BCRAT (0.567 and 0.472, respectively). The BCRAT significantly underpredicted breast cancer risk after benign biopsy (P = .004), whereas the BBD-BC predictions were appropriately calibrated to observed cancers (P = .247). Conclusion We developed a model using both demographic and histologic features to predict breast cancer risk in women with BBD. Our model more accurately classifies a woman's breast cancer risk after a benign biopsy than the BCRAT.