Citations

Abstract Multiple sclerosis preferentially affects women, and this sexual dimorphism is recapitulated in the SJL mouse model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE). In this study, we demonstrate that signaling through c-Kit exerts distinct effects on EAE susceptibility in male and female SJL mice. Previous studies in females show that Kit mutant (W/Wv) mice are less susceptible to EAE than are wild-type mice. However, male W/Wv mice exhibit exacerbated disease, a phenotype independent of mast cells and corresponding to a shift from a Th2- to a Th17-dominated T cell response. We demonstrate a previously undescribed deficit in c-Kit+ type 2 innate lymphoid cells (ILC2s) in W/Wv mice. ILC2s are also significantly reduced in EAE-susceptible wild-type females, indicating that both c-Kit signals and undefined male-specific factors are required for ILC2 function. We propose that deficiencies in Th2-promoting ILC2s remove an attenuating influence on the encephalitogenic T cell response and therefore increases disease susceptibility.

A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT–CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in‐depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80–0.90, p = 8.3 × 10−8). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r2 = 0.07, D′ = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10−5), rs4583925 (p = 4.0 × 10−5) and rs2735948 (p = 5.0 × 10−5). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.

Abstract Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and whether they interact to impact disease risk. Given that the development of ovarian cancer is complex, we aimed to identify DNA methylation marks that are candidates for mediating ovarian cancer genetic risk. We used 214 cases and 214 age-matched controls from the Mayo Clinic Ovarian Cancer Study. Pretreatment, blood-derived DNA was profiled for genome-wide methylation (Illumina Infinium HumanMethylation27 BeadArray) and single nucleotide polymorphisms (SNPs, Illumina Infinium HD Human610-Quad BeadArray). We employed a three-step filtering procedure, followed by the Causal Inference Test (CIT), to distinguish CpG sites that mediate genetic risk, from those that are consequential or independently acted on by genotype. Controlling for the estimated distribution of immune cells and other key covariates, we identified 1,993 out of 25,926 (7.7%) CpGs that were significantly differentially methylated between cases and controls (FDR, q < 0.05). The relationship between methylation and case-control status among these 1,993 CpGs was found to be highly consistent with the results of an independent study. Implementation of the CIT test revealed 13 CpG/SNP pairs, comprising 13 unique CpGs and 17 unique SNPs, which represent potential methylation-mediated relationships between genotype and EOC risk. These findings provide additional insight into EOC etiology and may serve as novel biomarkers for EOC susceptibility. Citation Format: Devin C. Koestler, Prabhakar Chalise, Mine S. Cicek, Julie M. Cunningham, Sebastian Armasu, Melissa C. Larson, Jeremy Chien, Matthew Block, Kimberly R. Kalli, Thomas A. Sellers, Ellen L. Goode, Brooke L. Fridley. Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian 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 260. doi:10.1158/1538-7445.AM2014-260

Abstract The mechanisms by which ovarian cancer cells are released from the primary tumor, seed throughout the peritoneal cavity, attach to local organs, and then invade these organs, are not understood. In this study, the cell adhesion molecule, Nectin-4, was investigated as a potential mediator of several steps involved in ovarian cancer progression. In particular, due to the ability of Nectin-4 to promote cell-cell adhesions, we were interested in determining its role in mediating the formation of cell-cell aggregates (spheroids) which are commonly seen in the peritoneal fluid of ovarian cancer patients. Furthermore, since spheroids are known to have a decreased rate of cell proliferation and are chemoresistant, we were also interested in the role of Nectin-4 in ovarian cancer cell proliferation and invasion. In our previous studies, we performed gene microarray analysis and identified Nectin-4 overexpression in ovarian cancer tissues compared to normal ovaries and other normal tissues. By ELISA, we found soluble Nectin-4 in the sera of 50% of women with ovarian cancer. In this study, we performed a series of experiments in which two human ovarian cancer cells lines were transfected with Nectin-4 or shRNA targeting Nectin-4, and then the resultant cells were tested in functional assays. In the first case, MA148 cells, which do not express Nectin-4, were transfected with full-length Nectin-4. The resultant MA148 cells which expressed high levels of Nectin-4 showed an increased rate of proliferation compared to control cells which did not express Nectin-4. They also formed the initial cell-cell adhesions involved in spheroid formation faster than control cells. Furthermore, the spheroids which expressed Nectin-4 were slower to disaggregate and invade through monolayers of mesothelial cells. In the second case, NIH:OVCAR5 cells, which express moderate levels of Nectin-4, were transfected with shRNA targeting Nectin-4, resulting in the partial knockdown of Nectin-4 expression. We found that the NIH:OVCAR5 cells that express lower levels of Nectin-4 on their surface required a substantially longer time to form spheroids and migrated more slowly in a wound healing assay. In both cases, we verified the expression of Nectin-4 in the transfected cells by Western immunoblotting and flow cytometry. These results suggest that Nectin-4: (a) is important in the early events of cell-cell adhesion, (b) plays a role in multicellular aggregation within the ascites of ovarian cancer patients, and (c) causes tight spheroid formations that may impede disaggregation. Additional functional studies leading to a better understanding of the role of Nectin-4 overexpression and shedding in ovarian cancer are currently underway. Understanding the role of Nectin-4 in ovarian cancer progression is critical in order to facilitate its development as a novel therapeutic target for ovarian cancer. Citation Format: Kristin L. Boylan, Adam Meyer, Petra C. Buchanan, Melissa S. DeRycke, Amy P. Skubitz. Role of nectin-4 in the progression of ovarian 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 1984. doi:10.1158/1538-7445.AM2014-1984

Abstract Intro: Male BC is a rare disease (<1% male tumors); knowledge is limited and management extrapolated from female BC. An international consortium, coordinated by EORTC and TBCRC, was created to better characterize and manage this disease, with 3 parts: 1) retrospective joint analysis 2) prospective registry 3) clinical trial(s). We report 1st results of part 1. Methods: Joint analysis of male BC pts with available FU & FFPE samples, treated in 1990-2010, in 23 centers from 9 countries. Clinical data, long term outcomes, local pathology were centrally analyzed at EORTC. FFPE samples were analyzed at 3 central labs (UK, NL, US) for histology, grade, ER, PR, AR, HER-2, Ki67. Cut-off for positivity: Allred score ≥ 3 for ER/ AR/PR; 20% for Ki67; ASCO-CAP for HER2. Outcome data (OS & RFS) analyzed per Kaplan Meier, p-values correspond to logrank test, CI’s by Brookmeyer & Crowley. Reported % use number of non-missing values as denominator. Results: 1822 pts enrolled; 349 (19%) ineligible (no valid central lab assessment); of 1473 eligible pts (1384 from EU, 89 from US) 63% diagnosed in 2001-2010. Median age at diagnosis (Dx) was 68.5 ys. Of pts with known M status at Dx, 56 (5.1%) were M1; of 1046 M0 cases, 60% were N0 and 51% had T1 tumors at Dx; 4% of pts had BCS and 18% had SLNB; half received adjuvant RT. (Neo)adjuvant CT was used in 30% of M0 pts, most (44%) anthracycline-only; 77% of M0 pts received adjuvant ET, most tamoxifen (88.4%). Central pathology: 697 cases with central histology & grade (full series ongoing): 87% ductal, 53% grade 2. In 1473 pts, at least 1 biomarker centrally assessed; 92% ER highly+ (Allred 7-8), PR had wider variation (35% highly+); 87% AR highly+; 25% Ki67 high; 5% HER2pos. Using IHC surrogates: 58% Luminal A-like, 35% LuminalB-like/HER2neg, 6% LuminalB-like/HER2pos; 0.1% HER2pos/non-Luminal; 1% TNBC (16% not classified). Outcome: For 1046 M0 pts, median FU was 5.7 yrs (0-19.2); 63% alive at analysis; in 88% cause of death was reported, mainly 33% non-cancer and 28% progression(PD)/toxicity. Significant OS improvement over time is seen. 75% (42/56) M1 pts died, mainly due PD. In M0 pts, median OS (yrs) was significantly correlated with ER+ p=0.001 [Allred 0-2: 3.9 (0.1, 6.0); 3-6: 7.1 (4.7, 11.7); 7-8: 8.8 (8.3, 10.0)] & with PR+ p=0.022 [Allred 0-2: 7.3 (6.1, 10.3), 3-6: 8.0 (7.0, 9.3), 7-8: 9.5 (8.4, 12.8)]; less correlation for AR; no major differences for HER2 or Ki67. Median OS & grade (394 cases; full series ongoing): Grade1: 12.8 yrs (6.1-15.6); Grade2: 7.9 (6.5-10.7); Grade3: 9.3 (4.9-21.1). Median OS for IHC surrogates: 8.7 (7.8-9.7) for Luminal A; 8.3 (6.9-9.4) for Luminal B/HER-2neg; 9.3 years (5.9-21.1) for Luminal B/HER-2+. Similar results were seen for RFS. ER/PR/AR using histoscores will be presented. Conclusions: a) 56% pts had T1 tumors at Dx but only 4% had BCS; b) ER was highly + in >90% but adjuvant ET given in only 77% pts; c) Male BC is usually ER+, PR+ & AR+ and of Luminal A-like subtype (5% HER2pos & 1% TNBC); d) Significant improvement in OS over time; e) ER and PR (Allred) are prognostic (high expression/better prognosis), less for AR, not for Ki67 nor IHC surrogates; f) In-depth characterization of samples is ongoing. Funding: BCRF, EBCC Council, Pink Ribbon NL, BRO. Citation Format: Fatima Cardoso, John Bartlett, Leen Slaets, Carolien van Deurzen, Elise van Leewen-Stok, Peggy Porter, Barbro Linderholm, Ingrid Hedenfalk, Carolien Schroder, John Martens, Jane Bayani, Christi van Asperen, Melissa Murray, Clifford Hudis, Lavinia Middleton, Joanna Vermeij, Stephanie Peeters, Judith Fraser, Monica Nowaczyk, Isabel Rubio, Stefan Aebi, Catherine Kelly, Kathryn Ruddy, Eric Winer, Cecilia Nilsson, Lissandra Dal Lago, Larissa Korde, Kim Benstead, Danielle Van Den Weyngaert, Oliver Bogler, Theodora Goulioti, Nicolas Dif, Carlo Messina, Konstantinos Tryfonidis, Jan Bogaerts, Sharon Giordano. Characterization of male breast cancer: First results of the EORTC10085/TBCRC/BIG/NABCG International Male BC Program [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 S6-05.

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and HER2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. Neratinib (N), one of the experimental agents evaluated in I-SPY 2, graduated in the HR-HER2+ signature. All patients received at least standard chemotherapy (paclitaxel followed by doxorubicin/cyclophosphamide; T->AC). HER2- patients were randomized to receive N+T- >AC vs. T->AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T->AC vs. H+T->AC). Here, we assess the performance of MP1/MP2 class as a specific biomarker of neratinib response. Methods: 115 patients in the neratinib arm and 76 concurrently randomized controls had Agilent 44K microarrays and pCR data available for analysis. We assess association between MP1/MP2 and response in the neratinib and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate, and in receptor subsets. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Our analyses do not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: There are 133 MP1 patients (neratinib: 74, Control: 59) and 58 MP2 patients (neratinib: 41, Control: 17), 84% (49) of which are Her2-. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. Neratinib (n=115)Control (n=76)MP1 (n=74)MP2 (n=41)MP1 (n=59)MP2 (n=17)HER2- (n=105)0 / 1715 / 337 / 395 / 16HER2+ (n=86)22 / 574 / 85 / 200 / 1 MP2, one of the 10 eligible signatures, did not meet the graduation threshold; and MP1/MP2 did not show a significant biomarker x treatment interaction (OR in neratinib relative to control arm = 1.25). The MP1/MP2 x treatment interaction remains non-significant after adjustment for HR and HER2 status (p=0.54). In HER2- patients receiving neratinib, 45% (15/33) of MP2 patients achieved a pCR, compared to 0% (0/17) of MP1 patients. In the HER2- controls, there is a 31% pCR rate in MP2 (5/16) vs. 18% in MP1 (7/39) patients (OR=2.14). This difference in performance between treatment arms appears significant (p=0.041). 90% of HER2+ patients are MP1, thus MP1/MP2 status x treatment interaction within the HER2+ subtype cannot be evaluated. Conclusion: Within the I-SPY 2 population as a whole, MP1/MP2 stratification does not appear to be a specific biomarker of response to neratinib relative to the control arm. The number of HER2- patients is small and precludes any definitive conclusion, but these data motivate further investigation of the biological mechanisms distinguishing MP1 from MP2 to better understand chemotherapy and/or neratanib responsiveness. Citation Format: Christina Yau, Denise M Wolf, Ashish Sanil, Jo Chien, Anne Wallace, Judy Boughey, Doug Yee, Debu Tripathy, Angela DeMichele, Rita Nanda, Steven Chiu, Claudine Isaacs, Kathy Albain, Hank Kaplan, Stacey Moulder, Rebecca Viscusi, Donald Northfelt, Kirsten Edmiston, Anthony Elias, Toncred Styblo, Barbara Haley, Lamorna Brown-Swigart, Susan Flynn, Gillian L Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, W Fraser Symmans, Laura Esserman, Don Berry, Minetta C Liu, John W Park, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [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 P3-06-29.

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and Her2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. HER2- patients were randomized to receive standard chemotherapy or the oral PARP inhibitor veliparib in combination with carboplatin (V/C) and chemotherapy. V/C graduated in the triple-negative (TN) signature, where MP2 was not an eligible signature for graduation. Here, we assess the performance of MP1/MP2 class as a specific biomarker of response to V/C. Methods:115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. We assess association between MP1/MP2 and response in the V/C and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate. To assess MP1/MP2 in the context of the graduating signature, we added the MP2 patients to the graduating TN subset and evaluated the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). This analysis does not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: In the V/C arm vs. concurrent controls, there were 66 MP1 (V/C: 32, Control: 34) and 49 MP2 patients (V/C: 39, Control: 10), 78% of which are TN. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. V/C (n=71)Control (n=44)MP1 (n=32)MP2 (n=39)MP1 (n=34)MP2 (n=10)TN (n=59)3 / 819 / 303 / 132 / 8HR+HER2- (n=56)1 / 244 / 94 / 210 / 2 The OR between MP1/MP2 risk groups for predicting pCR is 9.71 in the V/C arm (p=6.63E-05), in comparison to an OR of 0.97 in the control arm (p=1). There is a significant biomarker x treatment interaction (p=0.023), which remains upon adjusting for HR status (p= 0.028). Based on the I-SPY 2 Bayesian model, a Phase III trial with 300 MP2 patients has a 95% predictive probability of success. When the MP2 patients are added to the graduating TN subset, the OR associated with V/C is 4.36, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼10%. Conclusion: In our exploratory analysis, MP2 suggests higher sensitivity to V/C combination therapy relative to controls. This observation has prompted an investigation into the biological mechanisms distinguishing the MP1/MP2 subtype that may account for this specificity. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Jo Chien, Anne Wallace, Angela DeMichele, Hank Kaplan, Doug Yee, Claudine Isaacs, Kathy Albain, Rebecca Viscuzi, Judy Boughey, Stacey Moulder, Steven Chui, Qamar Khan, Toncred Styblo, Kirsten Edmiston, Donald Northfelt, Anthony Elias, Barbara Haley, Debu Tripathy, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, Fraser Symmans, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo I. Olopade, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [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 P3-06-25.

Abstract Background: We hypothesize that response to the pan-ERBB inhibitor, neratinib (N), may be predicted by pre-treatment HER2-EGFR signaling. In the I-SPY 2 TRIAL, N graduated in the HR-/HER2+ signature. All patients received at least standard chemotherapy. For HER2+ patients, N was administered in place of trastuzumab. We evaluated 18 HER family signaling proteins as biomarkers of N response using reverse phase protein microarray (RPMA) data from pre-treatment LCM purified tumor epithelium. Methods: 168 patients (N: 106, concurrent controls: 62) had RPMA and pCR data. 18 biomarkers relating to HER family signaling were evaluated: AKT S473, AKT T308, EGFR, EGFR Y1068, EGFR Y1148, EGFR Y1173, EGFR Y992, ERBB2, ERBB2 Y1248, ERBB3 total, ERBB3 Y1289, ERK1/2 T202/Y204, Heregulin, mTOR, mTOR S2448, PI3K p85 Y458/p55 Y199, PTEN S380, and SHC Y317. We assessed association between biomarker and response in the N and control arms alone (likelihood ratio test), and relative performance between arms (biomarker x treatment interaction) using a logistic model. Analysis was also performed adjusting for HR/HER2 status. In an exploratory analysis, we selected the marker with the greatest interaction (phosphorylated EGFR (Y1173)) to dichotomize patients optimally based on the data and assessed it in the context of the graduating signature by adding the EGFR Y1173-High patients to the HR-/HER2+ subtype and evaluating the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data and does not account for multiplicities. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Results: 7 HER pathway markers (EGFR Y1068, EGFR Y1173, EGFR Y992, ERBB2 total, ERBB2 Y1248, ERBB3 Y1289, SHC Y317) are associated with response in the N but not the control arm. However, the difference in performance between arms did not reach significance by permutation testing. Adjusting for HR/HER2 status, EGFR Y1173 shows a significant biomarker x treatment interaction (p = 0.049). In an exploratory analysis, we dichotomized patients by their EGFR Y1173 levels and evaluated the distribution of pCR rates (Table 1). Neratinib (n=106)Control (n=62)EGFR Y1173 Low (n=31)EGFR Y1173 High (n=75)EGFR Y1173 Low (n=29)EGFR Y1173 High (n=33)HR-/HER2+ (n=28)0 / 412 / 181 / 11 / 5Not HR-/HER2+ (n=140)3 / 2724 / 575 / 285 / 28Table 1 OR between EGFR Y1173 groups in the N relative to control arm is 10.1. When EGFR Y1173 High patients are added to the graduating HR-/HER2+ subset, the OR associated with treatment is 3.2 and is comparable to that in the HR-/HER2+ signature (OR: 2.1), while increasing the prevalence of biomarker-positive patients by ∼50%. Evaluation of EGFR Y1173 under the I-SPY 2 Bayesian model is pending. Conclusion: Our sample size is too small to draw definitive conclusions. Our exploratory analysis reveals that HER family phosphoproteins associate with response to N, but only phosphorylated EGFR Y1173 appears to add value to the graduating signature. Given that this biomarker would expand the patient population that may benefit, it merits evaluation in other ongoing trials of neratinib. Citation Format: Julia D Wulfkuhle, Christina Yau, Denise M Wolf, Rosa I Gallagher, Ashish Sanil, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, I-SPY 2 TRIAL Investigators, Meredith Buxton, Angela DeMichele, Nola Hylton, William F Symmans, Laura van't Veer, Douglas Yee, Melissa Paoloni, Laura Esserman, Donald Berry, Minetta C Liu, John W Park, Emanuel F Petricoin III. Evaluation of HER family protein signaling network as a predictive biomarker for pCR for breast cancer patients treated with neratinib in the I-SPY 2 trial [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 P3-06-15.

Abstract An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [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 3285. doi:10.1158/1538-7445.AM2014-3285

Abstract Background: Renal cell carcinoma (RCC) is the most common type of kidney cancer responsible for ∼80% of kidney cancer cases. Circulating tumor cells (CTCs) are emerging as an important prognostic and predictive biomarker in several types of metastatic cancers. However, methods for CTC detection that target only EpCAM and/or cytokeratin (CK) to enrich CTCs, may fail to recognize the CTCs in clear cell RCC (ccRCC) because ccRCC lacks expression of EpCAM. The objective of this study was to develop a new technology capable of detecting CTCs including those with a mesenchymal phenotype in metastatic RCC. Methods: Blood samples from patients affected by metastatic RCC were provided by Mayo Clinic Arizona and analyzed by Creatv MicroTech. CellSieveTM microfilters, which have 7 µm diameter pores in a uniform array, with 160,000 pores in a 9 mm diameter area, were used for separation of CTCs in the blood specimen. 7.5 mL of whole blood was diluted in the prefixation buffer and filtered through the microfilter. Clinical immunohistochemical markers for RCC such as CD10 and vimentin were used to identify candidate CTCs. The cells collected on the filter were fixed, permeabilized, and stained with DAPI and fluorescent antibodies specific to CD10, vimentin, and CD45. The assay protocol was developed using three RCC cell lines, 786-O, Caki-1, and Caki-2, and validated using blood samples from patients with metastatic RCC. Results: The capture efficiencies for 786-O, Caki-1, and Caki-2 cell lines were determined to be 98%, 98% and 97%, respectively. On-filter antibody staining revealed heterogeneous expressions of vimentin and CD10 in RCC cells. Patient samples were collected in duplicate CellSaveTM tubes and processed one day later. A CD10+/vimentin+/CD45- cell population was detected in blood samples with enumeration ranging from 4 to 86 cells/7.5 mL of blood. We found that the RCC CTC profile was distinct from other types of cancers. The typical CTCs display abnormal morphology, including large nuclei (typically 15-30 µm in size), irregular cell size and shape, and high nucleus-to-cytoplasm ratio. Although CD10 and vimentin antibodies have cross-reactivity with white blood cells (WBC), the CTCs could be distinguished from WBC based on morphology, cell size and CD45- staining. Conclusions: We demonstrated that the CellSieveTM microfiltration assay is a very simple and efficient method to isolate a CD10+/vimentin+/CD45- cell population from patients affected by metastatic ccRCC. Future studies include fluorescence in situ hybridization to confirm loss of 3p, a molecular event that occurs in >90% of ccRCC. We are also analyzing blood samples from patients treated with tyrosine kinase inhibitors to determine if cell enumeration is predictive of response to treatment. This technology might greatly facilitate detection of EpCAM negative ccRCC CTCs. The clinical significance of these unusual, large, rod-shaped, naked nuclei require further molecular characterization. Citation Format: Peixuan Zhu, Thai Ho, Erik P. Castle, Richard W. Joseph, Melissa L. Stanton, Shuhong Li, Daniel Adams, Olga V. Makarova, Platte T. Amstutz, Cha-Mei Tang. Isolation and identification of circulating tumor cells in renal cell carcinoma. [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 3081. doi:10.1158/1538-7445.AM2014-3081