Citations

Abstract Background: Although the spectrum of genomic alterations in primary, treatment-naïve breast tumors has been described, the genomic landscape of HER2+ MBC remains underexplored. Furthermore, tumor genomic alterations that arise after progression on anti-HER2 therapy are largely unknown. Methods: We prospectively collected metastatic tumor biopsies from patients (pts) enrolled on TBCRC003 (NCT00470704), a phase II study evaluating the combination of lapatinib (L) and T in pts with HER2+ MBC who had varying degrees of prior T exposure. We performed WES on baseline metastatic biopsies and normal DNA from 57 pts. In 36 pts, we also performed WES on pre-treatment primary tumors. Tumors were analyzed for point mutations, insertions/deletions, and copy number alterations. Results: Total accrual was 116 pts. 87 pts were registered in one of two efficacy cohorts: Cohort 1 included pts w no prior T for MBC. Pts with prior adjuvant T were included if the interval from last T to 1st recurrence > 12 months. Cohort 2 included pts with 1-2 prior lines of T for MBC or recurrence within 12 months of adjuvant T. An additional 29 pts were enrolled in a biomarker cohort (Cohort 3). Per-protocol efficacy analyses for 85 pts deemed evaluable are shown below: Objective Response RateClinical Benefit RateMedian Time to ProgressionCohort 150% (90% CI 33.8-66.2%)57.5% (95% CI 40.9-73.0)7.4 monthsCohort 222.2% (90% CI 11.2-37.1%)42.2% (95% CI 27.7-57.8)5.3 months As we previously reported (Wagle et al, ASCO 2014), across 57 metastatic tumors, significant recurrently mutated genes were TP53 (n=30; 53%) and PIK3CA (n=19; 33%). The frequency of mutant TP53 and PIK3CA was not significantly different from 119 primary, treatment-naïve HER2+ tumors sequenced in the TCGA study (50%, p=0.8 and 27%, p=0.5, respectively). Recurrent copy number alterations were also similar to TCGA data. Comparing the 38 pts who received any prior T with the 19 pts who did not, there was no significant difference in the incidence of mutant TP53 (53% vs 53%, p=1.0) and PIK3CA (37% vs 26%, p=0.6). We identified mutations in the HER2 kinase domain in 4/38 pts who received prior T (11%), as compared to 0/19 T-naïve pts. HER2 kinase domain mutations have been identified in ∼2% of HER2-negative cancers but <1% of primary HER2+ cancers. 3 of the mutations were L755S, which has been shown to be resistant to L and sensitive to irreversible HER2 inhibitors. The 4th mutation was D742N, a novel kinase domain mutation. None of the 4 pts with HER2 kinase domain mutations had an objective response, though 1 pt had stable disease for 29 weeks. An analysis comparing paired archival primary tumors and baseline metastatic biopsies from 36 pts to identify genomic alterations acquired or enriched in the metastatic tumors will be presented. Conclusions: We present an analysis of the genomic landscape of HER2+ MBC, including comparisons between matched primary tumors and metastatic biopsies. Somatic HER2 kinase mutations in pts with HER2+ MBC treated with prior T suggests that these mutations may be involved in resistance to T, and may predict poor response to additional anti-HER2 therapy with combined L and T. Novel therapeutic approaches may be required for these pts. Citation Format: Nikhil Wagle, Nancy U Lin, Andrea L Richardson, Ignaty Leshchiner, Ingrid A Mayer, Andres Forero-Torres, Timothy J Hobday, Elizabeth C Dees, Rita Nanda, Mothaffar F Rimawi, Hao Guo, William T Barry, Ron Bose, Wei Shen, Antonio C Wolff, Stacey B Gabriel, Levi A Garraway, Eric P Winer, Ian E Krop. Whole exome sequencing (WES) of HER2+ metastatic breast cancer (MBC) from patients with or without prior trastuzumab (T): A correlative analysis of TBCRC003 [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 PD3-5.

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 Neoadjuvant endocrine therapy (ET) in patients (pts) with locally advanced estrogen receptor positive (ER+) breast cancer (BC) improves breast conservation rate, and importantly offers an opportunity for individualized assessment of tumor responsiveness to ET to guide subsequent treatment. Previous neoadjuvant ET trials demonstrated that pathologic tumor size (pT), axillary lymph node status (N), and tumor Ki67 value at surgery predicted risk of relapse. Preoperative endocrine prognostic index (PEPI) was therefore developed to assign risk scores based on these factors. Modified PEPI 0, defined by pT1-2 N0 Ki67< 2.7%, was associated with extremely low risk of recurrence without adjuvant chemotherapy. In addition, high Ki67 post 2-4 weeks (wks) of neoadjuvant ET identified resistant tumors with poor outcome. ALTERNATE trial is a three-arm phase III neoadjuvant/adjuvant ET trial designed to achieve two primary objectives. The first is to prospectively validate that modified PEPI 0 predicts > 95% relapse-free survival (RFS). The second is to determine whether fulvestrant (F), or fulvestrant (F) plus anastrozole (A), is superior to A in inducing a higher rate of modified PEPI 0. Secondary objectives include assessing RFS for pts with endocrine resistant tumor, defined by Ki67 > 10% at 4 or 12 wk, disease progression, or modified PEPI non-0, and pathologic responses of resistant tumors to neoadjuvant chemotherapy. Correlative studies include degrees of Ki67 suppression and ER level post treatment. In addition, ongoing research sequencing studies of DNA and RNA will be performed to contrast sensitive vs resistant tumors. During the first phase of the trial, 1200 pts are randomized 1:1:1 to the F, A or F/A. This provides an 82% chance, 1-sided alpha 0.025 chi-square test to detect at least 10% difference in modified PEPI 0 rate comparing F or F/A with A. While waiting for result of analysis, the A arm will continue for the 2nd phase enrollment. Only the F-containing arm(s) superior over A will be continued to the 2nd phase. During the 2nd phase, an additional 540 pts in each arm is estimated to obtain 317 pts with PEPI score 0. This will have a 90% chance, with a one-sided alpha=0.025 nonparametric Brookmeyer-Crowley type one sample survival test, rejecting that 5 year RFS rate is 95%. The maximum sample size is 2820 pts. Eligible pts include postmenopausal women with newly diagnosed clinical stage II or III ER+ (Allred score 6-8) HER2- BC. Tumor biopsy is required at baseline, 4 wk, and surgery for central Ki67 analysis. Treatment decision is individualized based on 4 wk Ki67 and modified PEPI score. Pts with Ki67 > 10% at 4 wk are switched to chemotherapy. Pts with a modified PEPI score of 0 are recommended not to receive chemotherapy, but continue the assigned ET for 1.5 years followed by 3 years of A. This trial is currently accruing pts through CTSU. This research is supported in part by NCI BIQSFP, and grants from Breast Cancer Research Foundation, Genentech, and the Investigator-Sponsored Study Program of AstraZeneca. The Clinical Trials.gov Identifier: NCT01953588. Citation Format: Cynthia X Ma, Vera Suman, A Marilyn Leitch, Souzan Sanati, Katherine DeSchryver, Gary W Unzeitig, Paul Haluska, Mark Watson, Olwen Hahn, Jo Anne Zujewski, Kelly Hunt, Eric P Winer, Cliff A Hudis, Matthew J Ellis. Alliance A011106: ALTernate approaches for clinical stage II or III Estrogen Receptor positive breast cancer NeoAdjuvant TrEatment (ALTERNATE) in postmenopausal women: A phase III 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 OT2-1-04.

Abstract Introduction Pancreatic cancer is a highly lethal malignancy due to late diagnosis and aggressiveness of the tumor. Characterization of high-risk populations for monitoring, intervention and early detection remains challenging. Obesity and diabetes are potentially modifiable contributors to pancreatic cancer. Genetic factors modifying the risk of obesity- and diabetes-induced pancreatic cancer have previously not been fully investigated at the genome-wide level. Hypothesis There are potential genetic factors modifying the associations between obesity/diabetes and pancreatic cancer. Methods Integrating genotype with risk factor data from a GWAS for the Pancreatic Cancer Case Control Consortium, we performed a genome-wide gene-environment interaction (G x E) scan for 457,688 SNPs in a discovery study of 2,028 cases and 2,109 controls using state-of-the-art methods including case-only (CO), case-control (CC), Empirical Hierarchical Bayes (EHB), Empirical-Bayes test (EB) and three 2-step approaches (DG2, EG2, DGEG2). Results We detected a genome-wide significant (P < 1.09 x 10-7 ) interaction of diabetes with rs13061928 (in CNTN4) in CO (P = 8.8 x 10-8 ), which was independent of diabetes in control group (P = 0.08). The minor allele was in a synergism with diabetes on the cancer risk: diabetics carrying GA/AA genotype had a 3.39-fold (95% CI: 2.47-4.65) increased disease risk compared with non-diabetics carrying GG genotype. Consistently, the SNP-diabetes interaction had a high ranking statistic in EHB (No.1) and high p-value ranks for EG2 and DGEG2 methods (No.1, P= 5.44 x 10-5). Conclusions These observations, once validated/confirmed, may help define at-risk subpopulation and initiate targeted intervention and prevention of pancreatic cancer. Genome-wide G x E analysis requires larger sample size than genetic main effects scan; combining the CO method with alternative methods may be the optimal scheme for genome-wide G x E analysis. Citation Format: Hongwei Tang, Eric J. Duell, Harvey A. Risch Risch, Sara H. Olson, H. Bas Bueno-de-Mesquita, Steven Gallinger, Elizabeth A. Holly, Gloria M. Petersen, Paige M. Bracci, Robert R. McWilliams, Mazda Jenab, Elio Riboli, Anne Tjønneland, Marie Christine Boutron-Ruault, Rudolf Kaaks, Dimitrios Trichopoulos, Salvatore Panico, Malin Sund, Petra H. M Peeters, Kay-Tee Khaw, Christopher I Amos, Donghui Li, Peng Wei. Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium. [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 2214. doi:10.1158/1538-7445.AM2014-2214

Abstract Prostate cancer (PCa) will impact one in six American men and many low-risk men endure therapy, while other men die of PCa. Optimal treatment selection depends on distinguishing indolent tumors from those that will cause prostate cancer specific mortality (PCSM). To date, sequencing of prostate tumor DNA has highlighted the fact that prostate tumors develop differently than other cancers. Instead of recurrent protein-altering mutations, many prostate tumors harbor “closed chain” structural rearrangements that may mediate tumor evolution. However, we do not yet understand which somatic mutations are involved in aggressive disease and PCSM. To address this crucial question, we are using whole genome sequencing to pinpoint somatic genetic features in tumor/normal paired samples from four PCSM and six non-PCSM patients with treatment-naïve, Gleason 8+ tumors. Tumor and normal DNA were sequenced to a mean coverage of 95.3X and 48.3X, respectively. Tumor DNA purity ranged from 49%-79% and tumor ploidy ranged from 1.96 to 2.22. To define the genomic landscape of aggressive PCa, we will compare our findings with published studies and genotype high-priority candidates in at least 50 additional low- and high-grade tumors. We will also compare somatic mutations in PCSM versus non-PCSM cases and use network analysis to identify pathways that may be involved in progression and metastasis. Finally, we will characterize the clonal evolution of PCa tumors using deep digital sequencing to distinguish mutations that were present in the original tumor clone from subclonal mutations that arose after oncogenesis. In this way, we aim to identify potential oncogenic drivers and candidate mediators of progression and metastasis. Ultimately, we aim to 1) Uncover somatic mutations that are specific to aggressive tumors 2) Determine whether PCSM tumors have unique genetic features, and 3) Understand the role of clonal evolution in oncogenesis and progression. As more tumors are sequenced, this approach may yield valuable markers for diagnosis, prognosis and treatment selection. Note: This abstract was not presented at the meeting. Citation Format: Brennan J. Decker, Danielle M. Karyadi, Eric Karlins, Brian W. Davis, Lori S. Tillmans, Stephen N. Thibodeau, Elaine A. Ostrander. Whole genome sequencing of high-grade treatment-naïve prostate tumors. [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 1536. doi:10.1158/1538-7445.AM2014-1536

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

Principles and Practice of Nursing Home Care . Edited by Paul R. Katz, MD and Evan Calkins, MD. New York, Springer Publishing Company, Inc., 1989. 443 pages. $43.95.

SummaryAll vertebrates contain a diverse collection of commensal, symbiotic and pathogenic microorganisms, such as bacteria, viruses and fungi, on their various body surfaces, and the ecological community of these microorganisms is referred to as the microbiota. Mucosal sites, such as the intestine, harbour the majority of microorganisms, and the human intestine contains the largest community of commensal and symbiotic bacteria. This intestinal community of bacteria is diverse, and there is a significant variability among individuals with respect to the composition of the intestinal microbiome. Both genetic and environmental factors can influence the diversity and composition of the intestinal bacteria with the predominant environmental factor being diet. So far, studies have shown that diet‐dependent differences in the composition of intestinal bacteria can be classified into three groups, called enterotypes. Other environmental factors that can influence the composition include antibiotics, probiotics, smoking and drugs. Studies of monozygotic and dizygotic twins have proven that genetics plays a role. Recently, MHC II genes have been associated with specific microbial compositions in human infants and transgenic mice that express different HLA alleles. There is a growing list of genes/molecules that are involved with the sensing and monitoring of the intestinal lumen by the intestinal immune system that, when genetically altered, will significantly alter the composition of the intestinal microflora. The focus of this review will be on the genetic factors that influence the composition of the intestinal microflora.