Champion, Mia D.

Abstract Immunomodulatory drugs (IMiDs) are widely used in the treatment of patients with Multiple Myeloma (MM) however, only 30% of relapsed MM patients respond to single agent therapy and most patients eventually develop drug resistance. The molecular target of IMiDs in MM is cereblon but other parallel pathways or downstream events which enhance or preclude drug responsiveness are unknown. We therefore conducted a genome scale small interfering RNA (siRNA) lethality study in MM in the presence of increasing concentrations of lenalidomide. Primary screening was performed in a single-siRNA-per-well format with the human druggable genome siRNA set V4 comprising four siRNAs targeting each of 6,992 genes (total 27968 siRNAs). Lenalidomide was added 24 hours post transfection and cell viability was measured by ATP-dependent luminescence at 144 hours after transfection. Primary screen data was rigorously evaluated for multiple quality control metrics and found to exceed all expected performance parameters with >98% global transfection efficiency, <0.25 CV values, and minimal plate-to-plate and set-to-set variations observed. Hit selection was performed by analysis of IC50 value shift in the presence of each testing siRNA compared with three different control siRNA oligos. 160 candidate genes that enhance lenalidomide sensitivity upon silencing (sensitizers) were selected and re-screened with four siRNA oligos targeting each gene. 50 genes were identified as reproducible lenalidomide sensitizers including three Peroxisome (PEX) family proteins (PEX1, PEX10 and PEX7) and seven RAB family proteins (RAB17, RAB1A, RAB26, RAB30, RAB36, RAB4A and RAB8A). Four kinase genes were also identified in sensitizer hits and two of these, I-Kappa-B Kinase-Alpha (IKK1 or CHUK) and ribosomal protein S6 kinase (RPS6KA3 or RSK2), encode proteins that associate with significance together with a phosphorylation dependent transcription factor (CREB1) in Toll signaling pathways (p-value 0.0068). RSK2 is a serine/threonine-protein kinase that acts downstream of oncogenic FGFR3 mediated signaling and is phosphorylated by ERK (MAPK1/ERK2 and MAPK3/ERK1 signaling) during hematopoietic transformation. Phosphorylated RSK2 was previously reported to be frequently expressed in myeloma cell lines and primary myeloma cells. Using lentiviral shRNA expression, we demonstrated that knockdown of RSK2 in three genetically variable MM cell lines induced cyctocytoxiticy and consistently sensitized to lenalidomide. Two selective small molecular inhibitors of RSK2 (SL 0101-1 and BI-D1870) were then demonstrated to synergize with lenalidomide to induce myeloma cell cytotoxicixity. To further understand the mechanism underlying sensitization, immunoblotting analysis was performed to look at downstream changes after either RSK2 knockdown or RSK2 inhibition by BI-D1870. We found that both RSK2 knockdown and BI-D1870 treatment, mimicking lenalidomide treatment or cereblon inhibition, induced downregulation of both IRF4 and MYC in MM cells. The combination of lenalidomide and BI-D1870 not only produced a substantial synergistic effect inducing MM cytotoxicity, but also demonstrated a significant enhancement of downregulation of IRF4 and MYC. Forced overexpression of RSK2 attenuated the synergistic effects of lenalidomide and BI-D1870. In summary, our high throughput screen identified multiple gene targets that associate with increasing sensitivity to IMiDs in MM cells, of which, RSK2 was further validated by both shRNA silencing and specific inhibitors as an effective target to cooperate with IMiDs to induce myeloma cytotoxicity. Clinical studies of RSK2 inhibition in concert with IMiD (cereblon inhibitor) therapy would be appropriate. Disclosures: Stewart: Onyx: Consultancy, Research Funding; Millennium: Honoraria, Research Funding; Celgene: Honoraria; BMS: Honoraria.

Abstract Background:A goal of “post-genomic” cancer care is development of specific, affordable, reliable and rapid next-generation sequencing-based assays determining prognosis, therapeutic selection and minimal disease monitoring, replacing older technologies in the diagnostic and monitoring workup. In this regard, we designed and deployed a custom gene panel for identification of mutations, copy-number changes and clonal frequency in multiple myeloma (MM) samples. Methods: The MM Mutation Panel Version 2.0 (M3P 2.0)1 includes 1271 amplicons from 77 genes that are either mutated in MM (genes with a published mutation incidence ≥3%), represent critical pathophysiological pathways, are targetable with small molecule-based therapies and/or are associated with drug resistance (eg. XBP-1, CRBN, IZKF, IRF4). The amplicons are spread across 21 chromosomes, allowing the identification of copy-number changes in these regions. Results: We have sequenced 38 MM cases (150 will be presented) with paired tumor-germline DNA samples, using only 20ng of DNA for library preparation. Patients (Pts) included 29 untreated and 9 MM pts with multi drug refractory disease. Coverage depth averaged 964X. Hyperdiploid MM was successfully identified in 45% of cases, del(13q) in 34%, del(1p) in 18%, del(17p) in 8% and gain of 1q in 13%. Array CGH in representative cases confirmed concordance with semiconductor sequencing. Overall, 71 exonic missense and 3 nonsense mutations were detected, and 7 frameshift indels. In 89% of the pts a mutation in at least one M3P2.0 gene was identified (range 1-8). 92% of mutations were predicted damaging (Provean, Polyphene-2 or SIFT). Most commonly mutated were KRAS (37%), NRAS (21%), BRAF (13%), TP53, CDKN1B, DIS3 (each 11%), FAM46C, STAT3, and IRF4 (each 8%). The MEK-ERK pathway was mutated in 61% of cases and in 3 cases more than one gene in this pathway (NRAS, KRAS, BRAF) was simultaneously mutated. Six mutations in BRAF were identified in 5 untreated pts, 3 of them known to be activating and targetable (Val600E). Other commonly mutated pathways were the NFKB pathway in 24% of pts and the Cyclin D pathway, mutated in 16% of cases. Genes of the cereblon pathway (CRBN, IRF4, IKZF3), essential for the action of lenalidomide (len) were mutated in 5 Pts. One newly diagnosed and len refractory Pt harbored a subclonal CRBN mutation (Asn316Lys, allelic fraction [AF] 20%) as well as 4 clonal IRF4 mutations within the DNA binding domain of the gene (Lys89Asn (AF 78%), Lys77Glu, Ser48Arg and Cys49Ser (AF 80% each). Another IRF4 mutated (Lys123Arg, AF 90%) hemodialysis dependent Pt was responsive to dose adapted treatment of len and dexamethasone (dex). Mutations in the C2H2-type 3 region of IKZF3 in a len resistant (Gly191Arg, AF 48%) pt occured as well as in a len and dex responsive (Arg242Gly, AF 52%) Pt. Furthermore, we identified a truncating XBP1 mutation (p.Leu232*, 97% AF) in a Pt refractory to bortezomib. One patient harbored a mutation in the steroid receptor NR3C1 (Pro255Leu, 22% variant reads). Finally, integrated mutation and copy-number data identified biallelic deletions of CDKN2C and FAM46C in a multi drug refractory Pt. Mutation and/or copy-number losses in both alleles were found in DIS3 in 4 Pts, in CYLD, TP53 and TRAF3 in 2 Pts and in CARD11, CDKN2A, CDKN1B, RB1and STAT3 in one Pt each. Conclusion: In summary, we report the initial results from 38 MM Pts using a custom MM sequencing panel which employs small amounts of DNA requiring very few cells and providing deep coverage in clinically meaningful timeframes. Our findings frequently include prognostically significant information, actionable targets and mutations in genes related to drug resistance. Targeted mutation profiling will likely become part of the clinical workup in MM and our M3P2.0 mutation panel is a suitable tool to provide information needed to guide precision therapy and to set the basis for individually tailored treatment decisions. 1. Kortuem KM. et al. Development Of a 47 Gene Sequencing Panel For Common Mutations Present In Multiple Myeloma: Preliminary Results In 77 p53 Deleted Patients, ASH 2013. Disclosures Stewart: Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Array BioPharma: Consultancy; Sanofi: Consultancy; Takeda Pharmaceuticals International Co.: Research Funding; Novartis: Consultancy. Bruins:OncoSpire: Salary support Other. Vasmatzis:OncoSpire: Salary Support Other. Kumar:Celgene: Consultancy, Research Funding; Millennium: The Takeda Oncology Co.: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding; Sanofi-Aventis: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Skyline Diagnostics: Membership on an entity's Board of Directors or advisory committees. Fonseca:Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium, AMGEN: Consultancy, patent for the prognostication of MM based on genetic categorization of the disease. He also has sponsored research from Cylene and Onyx Other, Research Funding. Bergsagel:MundiPharma: Research Funding; OncoEthix: Research Funding; Constellation Pharmaceutical: Research Funding; Novartis: Research Funding.

463 Background: The genomic assessment of cancer has been revolutionized by next-generation sequencing and is increasingly being applied in the clinic to guide therapeutic decision-making. Time to reporting of results, specimen quantity, and analyte quality have constrained initial clinical applications to gene panels and whole exome based strategies. Methods: Patients underwent surgical resection, excisional or core biopsies, or bone marrow biopsy. Samples were analyzed by whole genome or exome sequencing and RNA sequencing, bioinformatics analysis, and therapeutic target prioritization by a multi-disciplinary Clinical Genomics Board. All prioritized targets were CLIA validated using Sanger sequencing, RT-qPCR, FISH, or IHC as appropriate. Treatment was delivered using off-label FDA approved drugs, clinical trials, or single patient INDs. Results: We have enrolled 40 patients with advanced, treatment-refractory cancers of whom sequencing data is available on 33. The initial 6 patients were evaluated in a non-CLIA pilot phase and 27 in the CLIA enabled phase. Upon availability of the initial report, identified targets of putative therapeutic relevance were then prioritized by the CGB in 22/27 patients (81%) for subsequent CLIA validation. Eleven patients have been treated with genomically selected therapy with partial response in 3/10 assessed patients. A testicular cancer patient had aberrations in two testes specific genes, a copy number gain in TSSK6 and a novel gene fusion between thyroid hormone receptor associated protein 3 (THRAP3) and Tektin 2 (TEKT2). Additionally, a case of papillary renal cell carcinoma had an amplification of YAP1 and a previously unreported P287T mutation in CCND1, suggesting potential benefit with a CDK4/6 inhibitor. Treatment is ongoing and results will be reported. Conclusions: Integrated whole genome analysis in a CLIA setting is feasible. Integration of SNV, copy number and transcriptional data may allow for selection of putative driver genes to enhance targeted therapy decisions. Barriers for future broader implementation include the need for reduced time from biopsy to report and availability of therapies.

Abstract Background: Breast tumors exhibit intratumor heterogeneity resulting in targeted therapy resistance and other challenges in disease management. To address the sources of heterogeneity, we performed a unique, in-depth analysis of clonal architecture in primary chemoradiation-naïve breast cancers. We combined DNA content-based flow cytometry and ploidy analysis with aCGH and whole exome next-generation sequencing (NGS) in multiple biopsies from the tumors and involved lymph nodes (LNs). Material and methods: We sorted nuclei from distinct populations of diploid, tetraploid, and aneuploid cells in surgical tumor samples from three chemoradiation-naïve patients. Each sorted tumor cell population was interrogated with aCGH and whole exome NGS. In Patient #1, we sorted and interrogated the genomes of tumor populations from 12 fresh frozen sections morphologically mapped from within a HER2+, ER+, PR- primary invasive ductal carcinoma (IDC) of histological grade 3 with LN involvement and 2-3 sections from 2 out of 5 LNs. In Patient #2, 11 morphologically mapped fresh frozen sections were analyzed from a grade 2, ER+, PR+, HER2+, BRCA2 mutant LN- IDC. In parallel, matching samples were processed for IHC assays. In Patient #3 biopsies from a grade 2 ER+, PR+ primary tumor were profiled. Results: The 18 primary and LN biopsies from Patient #1 fell into 6 distinct ploidy groups albeit with aberrant but homogenous aCGH profiles, characterized by SARC amplification and homozygous deletions in ROBO1 and ROBO2. In contrast a dominant ploidy was identified throughout 10 biopsies in Patient #2 but with heterogeneous aCGH profiles. Patient #3 had a clonal homozygous deletion in Numb in each of 4 tumor biopsies. Mutation profiles obtained through exome sequencing further confirmed that ploidy was the main driver in Patient #1 whereas copy number aberrations played the key role in Patient #2 with the BRCA2 mutation (R3129X). A dendrogram based on exome variant calls of the aneuploid populations in Patient #1 strongly correlated with ploidy group and further revealed the specific clonal population characterized by a 5N ploidy and homozygous mutations in TP53 and PIK3CA as the progenitor to the ploidies present in the distant LNs. Strikingly, patients #1 and #2 were HER2 wild type across their clonal populations, contradicting IHC staining in a single core biopsy. Conclusions:Rather than inferring the presence of distinct tumor cell populations, our flow-sorting based approach of first identifying clonal populations and then interrogating their genomes, provides an objective method of exploring the sources and clinical significance of tumor heterogeneity. Our approach of clonal analysis has broad implications in the study of tumor heterogeneity and the identification of drivers in breast and other solid tumors that can advance more effective treatment and clinical management of patients with this disease. Citation Format: MARIACARLA ANDREOZZI, Princy Francis, Elizabeth Lenkiewicz, Mia Champion, Brady Laughlin, Karen Anderson, Heather Cunliffe, Ann E. McCullough, Michael T. Barrett, Barbara Pockaj. Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in breast cancer. [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 LB-175. doi:10.1158/1538-7445.AM2015-LB-175

Abstract Background: Genomic assessment of cancer has been revolutionized by Next-Generation sequencing and is increasingly being applied to guide clinical prognostic and therapeutic decision-making. Initial clinical applications have been limited to gene panels and whole exome based strategies due to challenges with time to reporting of results, specimen quantity, analyte quality, and ethical-legal-social issues (ELSI). Methods: Excisional or core tumor biopsies or bone marrow biopsies were obtained from consenting participants. Nucleic acid was extracted from fresh or frozen samples followed by WGS/WES/RNASeq on the Illumina HiSeq2000 or HiSeq2500 and bioinformatics analysis. Therapeutic targets were then prioritized by a multi-disciplinary Genomic Tumor Board (GTB) and CLIA validated using Sanger sequencing, RT-qPCR, FISH and/or IHC. Treatment was delivered using on/off-label FDA approved drugs, available clinical trials and single patient INDs. Results: We consented 64 and enrolled 35 patients with advanced, treatment-refractory cancers. Median age was 59 (range 27-91) with 62% male. The majority had ECOG scores of 1 (94%). A median of 79 (range 28-8891) potentially functional somatic point mutations were identified in each case. One to two mutations/case were further identified as therapeutically targetable in 60% of the cases. The median time from tissue acquisition to CLIA validated results was 116 days (range 42-282) with CLIA validation of targets achieved in 21 of 22 patients. Genomic, target directed treatment was ultimately instituted in 13 patients utilizing: on/off label FDA approved drugs (n = 9), clinical trial (n = 3) and single patient IND (n = 1). Preliminary clinical efficacy was noted in 5 patients (2 PR, 3 SD). Integration of WES, long-insert WGS and RNA-Seq identified a case with an ERRFI1 mutant allele present in only 11% of the DNA reads while 82% of the RNA-Seq reads had the mutant transcript. The patient was treated with erlotinib and achieved a partial response by RECIST criteria. In another case, a fusion between FGFR2-MGEA5 was observed in WES and RNA-Seq data leading to prioritization as a drug target. Reasons for patients not receiving targeted therapy included: inability to access treatment (n = 1), death prior to intended treatment (n = 3), results returned after death (n = 3), no targets identified (n = 2) and decision to pursue alternate therapy (n = 5). Conclusions: Integrating whole genome analysis in a CLIA setting is not only feasible, but also valuable, in the prioritization and selection of potential targeted therapies for patients with advanced tumors. Continued barriers to broad application include the need for shorter time to reporting as well as broad availability of therapies through basket studies. Citation Format: Mitesh J. Borad, Jan Egan, Mia Champion, Katherine Hunt, Robert McWilliams, Ann McCullough, Jessica Aldrich, Sara Nasser, Winnie Liang, Michael Barrett, David Craig, Ramesh Ramanathan, John Carpten, A. Keith Stewart, Alan Bryce. Implementation of CLIA enabled integrated whole genome (WGS)/exome (WES)/transcriptome (RNAseq) next-gen sequencing to identify therapeutically relevant targets in advanced cancer patients. [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 CT112. doi:10.1158/1538-7445.AM2015-CT112

Abstract Background: Next generation sequencing (NGS) has revealed that the genetic profiles of individual tumors are highly heterogeneous due to their subclonal composition. Tumor heterogeneity has profound clinical implications affecting differences in treatment response and therapeutic resistance. Methods: An estrogen receptor positive, Her2 normal breast cancer patient underwent definitive surgical treatment with modified radical mastectomy. Multiple samples were obtained from the primary cancer and metastatic lymph nodes. Flow cytometry based methods were used to isolate and classify distinct cell subpopulations according to their ploidy, and samples were processed for whole exome sequencing (WES). Comparative Genomic Hybridization (CGH) methods were used to identify somatic unique copy-number alterations (CNAs). WES-Single Nucleotide Variations (SNVs) were used to infer subclonal phylogenetic relationships using Maximum Parsimony methods and annotated with variation-cluster-barcodes (vc-barcodes) generated using a variation Bayesian mixture model (VBMM) approach that focuses on copy-number neutral sequence variations for subclone identification (SciClone). Our comparative phylogenetic-VBMM clustering method was used to identify CNA and/or SNV drivers that are key in differentiating subclonal populations at multiple tumor sites. Results: CNA-neutral WES-SNVs from 25 subclonal populations (isolated from 4 distinct sites) clustered into 6 major groups and were used to generate vc-barcodes. A phylogenetic reconstruction of subclonal architecture annotated with vc-barcode information expedited identification of key variations underlying the differentiation of subclones at distinct tumor sites. For example, we identified an amplification event involving the Anaplastic Lymphoma Kinase (ALK) gene that was more frequent in primary biopsy subclones (12/17, ∼71%) in comparison to metastatic subclones (2/6, ∼34%). As the ALK amplification is lost, we find that most of the metastatic subclones also acquire a predicted damaging mutation in this oncogene (4/6, ∼67%). In addition, we identified a potential driver metastatic cell lineage that carries the ALK amplification in the absence of the nonsynonymous mutation. Conclusions: We developed a hybrid clustering methodology and used it to reconstruct the subclonal architecture in primary and metastatic tumors from a single breast cancer patient. Our methods have identified several CNAs and/or SNVs underlying subclonal differentiation, as well as potential biomarkers of disease progression and indicators of emerging resistance. Application of these methods to larger cohorts and types of tumors should be conducted to ascertain more precise estimates of the predictive accuracy of our processes. Citation Format: Mia D. Champion, Princy Francis, Barbara A. Pockaj, Michael T. Barrett. Hybrid clustering methodologies to distinguish CNAs and/or SNVs that drive subclonal differentiation in samples from a breast cancer patient primary tumor and metastatic lymph nodes. [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 4861. doi:10.1158/1538-7445.AM2015-4861

Abstract Background: Breast tumors exhibit intratumor heterogeneity resulting in targeted therapy resistance and other challenges in disease management. To address the sources of heterogeneity, we performed a unique, in-depth analysis of clonal architecture in primary chemoradiation-naïve breast cancers. We combined DNA content-based flow cytometry and ploidy analysis with aCGH and next-generation sequencing (NGS) in multiple biopsies from the tumors and involved lymph nodes (LNs). Material and methods: We used DNA content-based flow sorting to isolate nuclei from distinct populations of diploid and aneuploid tumor cells in surgical tumor samples from two chemoradiation-naïve patients. Each sorted tumor cell population was interrogated with aCGH and exome NGS. In Patient #1, we used 12 fresh frozen sections morphologically mapped from within a HER2+, ER+, PR- primary invasive ductal carcinoma (IDC) of histological grade 3 with LN involvement and 2-3 sections from 2 out of 5 LNs. In Patient #2, 11 morphologically mapped fresh frozen sections were analyzed from a grade 2, ER+, PR+, HER2+, BRCA2 mutant LN- IDC. In parallel, matching samples were processed for IHC assays. Results: We identified multiple co-existing aneuploid populations within the biopsies. The 17 primary and LN biopsies from Patient #1 fell into 6 distinct ploidy groups albeit with aberrant but homogenous aCGH profiles, characterized by SARC amplification and homozygous deletions in ROBO1 and ROBO2. In contrast a dominant ploidy was identified throughout Patient #2 but with heterogeneous aCGH profiles. Mutation profiles obtained through exome sequencing further confirmed that ploidy was the main driver in Patient #1 whereas copy number aberrations played the key role in Patient #2 with the BRCA2 mutation (R3129X). A dendrogram based on exome variant calls of the aneuploid populations in Patient #1 strongly correlated with ploidy group and further revealed the specific clonal population characterized by a 5N ploidy and homozygous mutations in TP53 and PIK3CA as the progenitor to the ploidies present in the distant LNs. Strikngly, both patients had no HER2 amplification or mutation across their clonal populations, contradicting the initial IHC staining in a single core biopsy. Conclusions Rather than inferring the presence of distinct tumor cell populations, our novel flow-sorting based approach of first identifying the clonal populations and then interrogating their genomes, provides an objective method of exploring the sources and clinical significance of tumor heterogeneity. Our approach of clonal analysis has broad implications in the study of tumor heterogeneity and the identification of drivers in breast and other solid tumors that can advance more effective treatment and clinical management of patients with this disease. Citation Format: Princy Francis, Lucretia M Alvarez, Elizabeth Lenkiewicz, Mia Champion, Lisa Evers, Karen L Anderson, Ann E McCullough, Michael T Barrett, Barbara Pockaj. Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in 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 P2-03-07.