Keats, Jonathan J.

Abstract In an attempt to identify novel genetic abnormalities in multiple myeloma (MM) we analyzed 68 MM patient samples and 42 human myeloma cell lines (HMCL) with high-resolution (60kb) array-based comparative genomic hybridization (aCGH). We concentrated on bi-allelic genomic deletions with the expectation that these regions might contain novel tumor suppressor genes and identified a common abnormality at 14q32. Fine mapping of the 14q32 microdeletion by PCR demonstrated a 45 kb minimal deletion encompassing two genes; TRAF3, a negative regulator of the non-canonical NF-kB pathway, and AMN. To determine the frequency of copy number abnormalities of this region a cohort of 161 patients were screened with a FISH probe mapping to the minimally deleted region. This identified 7 (4.4%) patients with bi-allelic deletion and 19 (11.8%) patients with a single copy of the target region. Sequencing of all TRAF3 coding exons in 62 patients and 42 HMCL identified inactivating mutations in 9 patient samples and 4 HMCL. Overall, the incidence of TRAF3 inactivation, bi-allelic deletion or mutation, is 7/42 (16.7%) in HMCL and 12/62 (19.4%) in patients, making it one of the most common genetic abnormalities identified in MM. Importantly, dysregulation of NF-kB pathways is a common event in MM, but the mechanism for this dysregulation is largely unknown. Although TRAF3 is a negative regulator of the non-canonical NF-kB pathway it has not previously been implicated in cancer. Therefore, we tested the tumor suppressor function of TRAF3 by reintroducing TRAF3 into HMCL harboring TRAF3 abnormalities using an adenovirus gene transfer system. Expression of TRAF3 in HMCL with TRAF3 abnormalities rapidly reversed cellular processing of NFKB2 from p100 (an inactive isoform) to p52 (active) and additionally led to a 60% reduction in cellular proliferation (range, 10–89%) associated with Go/G1 cell cycle arrest and induction of cell death by apoptosis. At 48 hrs post infection the proportion of cells entering S-phase or G2/M declined by 31% (range, 8.1–56.1) and the proportion undergoing apoptosis increased by 28% (range 11.7–47.4%). In contrast, over-expression of TRAF3 in control HMCL without TRAF3 abnormalities had no effect. Overall, TRAF3 is identified as a novel tumor suppressor that regulates the non-canonical NF-kB pathway and is inactivated in ~ 20% of MM patients. Given the involvement of the NF-kB pathway in multiple human malignancies and the near constitutive expression of TRAF3 we propose that inactivation of TRAF3, a novel tumor suppressor identified for the first time in this study, may occur in other cancers. In this regard, we have recently identified a Burkitt lymphoma cell line that does not express TRAF3 and thus has constitutive processing of p100 to p52. The clinical and therapeutic consequences of this finding and its frequency in other tumor types are currently the focus of further investigation. In conclusion, the abnormalities identified in this study represent the first mutations identified that cause constitutive NF-kB activation in MM.

Abstract Introduction Tumor specific somatic mutations can potentially influence patient response to targeted immunotherapies. Since somatic mutations generate neoantigens, novel tumor-specific peptides can be processed, loaded into MHC class I molecules, and presented to T-cells as potentially immunogenic targets. Indeed, both somatic mutation burden and neoantigen burden have been correlated with responsiveness to checkpoint inhibitor blockade in highly mutagenic advanced melanoma and lung cancer. However, correlation of response with mutation and neoantigen burden has not been reported for cancers of lower characteristic mutational burden such as multiple myeloma (MM). Indeed early results of checkpoint inhibitors in MM have been underwhelming. We therefore wished to better understand the mutation and neoantigen landscape of MM patients as it relates to responsiveness to current and future therapies. Materials/Methods Somatic mutation burden, neoantigen load, and response to therapy was obtained using interim data from theCoMMpassstudy (NCT01454297), a study by the Multiple Myeloma Research Foundation that collects longitudinal clinical and molecular data on 1,000 newly diagnosed MM patients from baseline through treatment and disease progression. Next-generation exome sequencing data was used to call somatic mutations andbioinformaticallydetermine patient specific HLA type. Neoantigen binding affinity was predicted for all unique patient specific somatic missense mutation and HLA allele combinations using a well validated neural network and machine learning based algorithm. Binding affinity of the corresponding non-mutated peptide was also predicted to identify mutated neoantigens witha high binding affinity while the wild type counterpart has low predicted binding affinity. Results For 627 patients with available sequencing and clinical data, mutation and neoantigen profiles were created. Within this population, the mean overall canonical somatic mutation load was 405.84 (s=608.55) mutations per patient. These mutations included 38,222 unique missense mutations in 12,994 genes. The mean somatic missense mutation load was 64.51(s=95.29) mutations per patient including immunoglobulin genes (52.70, s=94.85 excluding immunoglobulins). There was a positive linear correlation between mutation burden and neoantigen burden. The mean neoantigen load using thresholds of mutant peptide binding affinity (half maximal inhibitory concentration, IC50) less than 500nM was 69.57 (s=124.76) neoantigens (58.53, s=123.58 excluding immunoglobulins). Limiting binding affinity of wild type peptide sequence to greater than 500nM decreased the mean neoantigen load to 23.84 (s=53.55) neoantigens (20.74, s=53.28 excluding immunoglobulins). Progression free survival (PFS) following induction therapy was used to determine correlates of mutation burden excluding immunoglobulin mutations with response. Kaplan-Meier survival analysis revealed significantly shorter PFS time in patients with greater than average tumor somatic missense mutation load (N=126) relative to those with less than average mutation load (49.1% vs. 73.0% PFS at 2yrs, p=0.0055, Figure 1) Similarly, patients with greater than average neoantigen load (N=164) had significantly shorter PFS relative to those with less than average neoantigen load (48.0% vs. 74.2% PFS at 2yrs, p=0.00259, Figure 2). Moreover, patients with both high mutation and neoantigen load (N=85) had significantly shorter PFS relative to those with less than average mutation and neoantigen load (45.3% vs. 72% PFS at 2yrs, p= 0.0168). Conclusion While mutation and neoantigen load has been correlated with response to targeted immunotherapies in highly mutated solid tumors, we report here a negative correlation between mutation, neoantigen load and MM patient survival. This indicates that a high mutation andneoantigen load negatively impacts survival of myeloma patients under current standard of care. It is hypothesized that this is because current treatments fail to recruit T cell immunity necessary to exploit tumor neoantigens fundamental to immune-mediated killing of cancer cells. This presents an encouraging basis for pursuing targeted and personalized immunotherapies for multiple myeloma, especially for patients with a higher mutational burden. PFS and mutation load. PFS and mutation load. PFS and neoantigen load. PFS and neoantigen load. Disclosures Lonial: BMS: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Novartis: Consultancy; BMS: Consultancy; Millenium: Consultancy; Merck: Consultancy.

Abstract Reliable model systems are critical for investigating the genetic and molecular drivers of disease pathogenesis. Although the number of cell line model systems for multiple myeloma is extensive, recent studies showed patient tumors and cell lines clustering separately based on gene expression profiles. Furthermore, the hyperdiploid karyotype, present in approximately 50% of myeloma patients, is also extremely underrepresented in established human myeloma cell lines (HMCLs): only one of 59 HMCLs contains this phenotype. These data suggests that the average HMCL does not accurately represent the average myeloma patient and questions the validity of using HMCLs as model systems. However, most HMCLs were established from patients with pleural effusions or plasma cell leukemia, which are highly progressed and rare forms of myeloma. To assess how cell lines correlate with patient material, we performed a copy number abnormality (CNA) comparison between four myeloma primary tumors and their corresponding HMCLs. Here, we show that established HMCLs maintain the majority of the CNAs, contain a ten-fold greater frequency of 7q gains compared to patients, and that KP-6 is the second hyperdiploid HMCL known to date. CNAs were identified using array comparative genomic hybridization (Agilent 244k) with data analyzed at a resolution of 26kb. On average 59% (46.7-77.3) of the CNAs were shared between the tumors and their cell lines, 17% (8.5-25.9) were unique to the patient samples, and 24% (13.6-36.6) were only detected in the HMCLs. To put these differences in context we also compared the diagnostic material from which JMW-1 was established with a progression sample collected 9 months later after 3 cycles of VAD followed by an autologous peripheral blood stem cell transplant. The patient diagnostic and relapse tumors showed 58% similarity based on CNAs while the diagnostic and relapse tumors contained 8% and 34% unique events respectively. These results indicate that established HMCLs are no more divergent from their primary cells as is the same patient's relapse material. Overall the HMCLs studied appear highly representative of the patient from which they were derived, with most differences attributed to an enrichment of subclonal populations present in the primary tumor admixture. Of particular interest, ubiquitous 7q gains were an unexpected unifying event across all patient tumors and their HMCLs. We then analyzed the 729 baseline myeloma tumors with copy number data from the MMRF CoMMpass study against our panel of 59 similarly characterized HMCLs. We observed that HMCLs contained a 10-fold increase in the occurrence of 7q gains with respect to non-hyperdiploid patients with 7q gains (35/59 in HMCLs and 19/344 in patients). Because 97% of HMCLs are non-hyperdiploid and 7q gains are extremely rare in this population, over-representation of 7q gains in cell lines suggests that this event may promote extra-medullary growth and the establishment of cell lines. Profiling of patient tumors for gains on 7q may therefore increase the probability of establishing a new HMCL and help expand our model systems for understanding this disease. Further studies are required to understand the potential biological significance of this event in vitro . We also identified the KP-6 cell line as a novel hyperdiploid HMCL established from an extramedullary site of an advanced hyperdiploid patient. The presence of trisomies for at least four of the odd-numbered chromosomes is characteristic of a hyperdiploid myeloma patient. From the patient's tumor, clear trisomies were observed on chromosomes 3, 7, 11, 15, 19, and 21 and the HMCL established from this hyperdiploid patient maintains full trisomies of chromosomes 15, 19, and 21, with partial p-arm trisomies on chromosomes 7, 11, and 17. Since this is only the second bona fied hyperdiploid myeloma cell line to date, KP-6 promises to play a major role in our ability to understand the pathogenesis and progression of this prominent patient population. Overall, our research indicates that, based on CNAs, HMCLs are as representative of the primary tumor as is the same patient's tumor at a later time point. Additionally, HMCLs contain a 10-fold overabundance of 7q gains. Finally, we showed that KP-6 is the second hyperdiploid HMCL known to date. Taken together, these results suggest that HMCLs are reliable model systems for investigating the underlying biology of multiple myeloma. Disclosures No relevant conflicts of interest to declare.

Abstract Previous work in our laboratory has identified the importance of the NFB signaling pathway for plasma cell (PC) survival and accumulation in Multiple Myeloma (MM). Although up to 43% of patient PCs appear to have activated NFkB by gene expression profiling (GEP), the remainder must rely on an alternate signaling pathway for their survival. We examined our MM GEP datasets and supervised the clustering of patients according to an index of NFkB activity. The majority of patients not activating NFkB were associated with a high IL-6/Stat3 signature, which included the protein phosphatase of regenerating liver-3 (PRL-3). Interestingly, analysis of the PRL-3 promoter revealed competing binding sites for both NFkB and STAT3 within the first intron, suggesting that these play a role in the transcriptional regulation of this gene. PRL-3 has been previously demonstrated to be absent in most normal tissues while its expression in MM cells is quite elevated. As normal PCs have low levels of PRL-3 expression, we determined the upper limit of normal to be 3SD above the mean of these cells. Using this cutoff we report that elevated PRL-3 expression is observed in plasma cells from 1/15 normal individuals, 4/22 MGUS patients and 47/126 patients with either smoldering or overt MM (6.7%, 18.2% and 45.6% respectively). Less than 10% of patients were seen to have both an elevated NFkB index and high PRL-3 expression. Patients with higher expression of PRL-3 were found to have statistically significant higher mean values of creatinine, C-reactive protein, lower albumin levels and a lower overall survival in our Mayo Clinic MM dataset. To examine the role PRL-3 in MM biology we first stimulated MM cell lines with IL-6 and observed PRL-3 up-regulation in two cell lines (INA6, OPM1) but not in JK6L (an NFkB activated cell line). Using a luciferase reporter we have determined that STAT3 induction of PRL3 expression requires the first intron of the PRL3 gene which contains the putative STAT3 binding site. Finally we show that PRL-3 inhibition by shRNA leads to decreased cell growth and loss of IL-6 responsiveness in vitro in at least one cell line. Based on these results, we propose that the majority of MM patients depend on either the NFkB or STAT3 signaling pathways for their survival and that these are to a large degree mutually exclusive. Our experimental results suggest that PRL-3 plays a role in IL-6/STAT3 signaling and that it is a promising target for drug development.

Abstract Abstract 724 Background: Chromosome content identifies two pathogenic pathways, each occurring in about half of patients with MGUS and multiple myeloma (MM). Hyperdiploid MM (HRD) has 48–75 chromosomes with multiple trisomies selectively involving chromosomes 3, 5, 7, 9, 11, 15, 19 and 21; only 10% of these HRD tumors have primary IgH translocations and no frequent focal genetic mutations have been identified. In contrast primary IgH translocations are identified in over 70% of non-hyperdiploid MM (NHRD). Rearrangements of MYC have been detected by FISH in only 16% of untreated MM, but over 90% of MM cell lines, identifying a late role for MYC in the progression of MM. The introduction of a MYC transgene into a mouse strain predisposed to MGUS results in mice that uniformly develop MM, suggesting a distinct early role of MYC in the progression of MGUS to MM. We report here that rearrangements in a 4Mb region surrounding MYC are present in 70% of HRD, representing the most frequent focal genetic mutation in this genetic subtype of MM. Results: We analyzed the MMRC reference collection of gene expression (Affymetrix Hu133Plus2) and copy number (Agilent 244k CGH) data and performed FISH to identify MYC rearrangements with IgH or IgL loci in 218 patients with untreated and relapsed MM. We found MYC rearrangements in 48% of MM (identified only by FISH in 5%, only by aCGH in 33%, and by both FISH and aCGH in 10%), including 43% of untreated, and 51% of relapsed MM. Using a hyperdiploid index calculated from the median copy number of the chromosomes involved in trisomies we determined that rearrangements of MYC were present in 70% of the top third, 35% of the middle third, and 25% of the bottom third. Using the paired gene expression data we found that the expression of MYC was approximately two-fold higher in the samples with rearrangements compared to those without rearrangements (p<0.001) and about three-fold higher in MM tumors without rearrangements compared to MGUS (p<0001). Using paired RNA and DNA from the MMRC reference collection we determined in 22 informative patients that MYC rearrangements are associated with monoallelic expression of MYC (p<0.01), consistent with cis-dysregulation of MYC. Analysis of the various changes on aCGH, and fine mapping of the genetic architecture of the rearrangements using next generation sequencing identifies a promiscuous array of rearrangements that often result in the introduction of an enhancer within the MYC locus, resulting in its cis-dysregulation. Since they cannot be comprehensively identified by either CGH or FISH alone, more sensitive techniques, such as next generation sequencing approaches, will be required to comprehensively identify all MYC rearrangements in MM. Conclusions: Rearrangements of MYC are the most frequent focal genetic mutation in untreated MM and are particularly prevalent in hyperdiploid MM. While only one third involve an immunoglobulin locus, they all result in cis-dysregulated expression of MYC, and may be one mechanism responsible for the progression of MGUS to MM. Tumors lacking MYC rearrangements bi-allelically over-express MYC by a trans mechanism including potentially inactivating mutations of BLIMP1/PRDM1, or activating mutations of IRF4. We propose two largely non-overlapping pathogenic pathways in MM: HRD associated with frequent MYC rearrangements, and NHRD associated with frequent primary IgH translocations. The prevalence of MYC rearrangements increases with tumor progression, identifying a role for MYC both early and late in tumorigenesis. As therapies that have been reported to target MYC (e.g., IMiDs®, bortezomib, bromodomain inhibitors) are used in the clinic, it will be important to associate their effect with the presence or absence of MYC rearrangements. Disclosures: Bergsagel: Constellation Pharmaceuticals: Consultancy. Keats:Tgen: Employment.

Abstract Abstract 832 We hypothesized that new therapeutic targets for multiple myeloma (MM) could be discovered through the integrative computational analysis of genomic data. Accordingly, we generated gene expression profiling and copy number data on 250 clinically-annotated MM patient samples. Utilizing an outlier statistical approach, we identified HOXA9 as the top candidate gene for further investigation. HOXA9 expression was particularly high in patients lacking canonical MM chromosomal translocations, and allele-specific expression analysis suggested that this overexpression was mono-allelic. Indeed, focal copy number amplifications at the HOXA locus were observed in some patients. Outlier HOXA9 expression was further validated in both a collection of 52 MM cell lines and 414 primary patient samples previously described. To further verify the aberrant expression of HOXA9 in MM, we performed quantitative RT-PCR, which confirmed expression in all MM patients and cell lines tested, with high-level expression in a subset. To further investigate the mechanism of aberrant HOXA9 expression, we interrogated the pattern of histone modification at the HOXA locus because HOXA gene expression is particularly regulated by such chromatin marks. Accordingly, immunoprecipitation studies showed an aberrantly low level of histone 3 lysine 27 trimethylation marks (H3K27me3) at the HOXA9 locus. H3K27me3 modification is normally associated with silencing of HOXA9 in normal B-cell development. As such, it appears likely that the aberrant expression of HOXA9 in MM is due at least in part to defects in histone modification at this locus. To determine the functional consequences of HOXA9 expression in MM, we performed RNAi-mediated knock-down experiments in MM cell lines. Seven independent HOXA9 shRNAs that diminished HOXA9 expression resulted in growth inhibition of 12/14 MM cell lines tested. Taken together, these experiments indicate that HOXA9 is essential for survival of MM cells, and that the mechanism of HOXA9 expression relates to aberrant histone modification at the HOXA9 locus. The data thus suggest that HOXA9 is an attractive new therapeutic target for MM. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 1808 Poster Board I-834 We have developed the first mouse model of multiple myeloma (MM), Vk*MYC, in an immune competent mouse, with indolent plasma cell (PC) growth confined to the bone marrow, and in which the major biological and clinical features of the human disease are recapitulated, including the post germinal center origin of the tumor cells, the presence of a M-spike in the serum, anemia, diffuse bone disease and drug sensitivity. To further characterize karyotypically and phenotypically the Vk*MYC tumors, we performed gene expression profile (GEP) and aCGH analysis on CD138+ purified MM cells from Vk*MYC mice. For GEP, we analyzed 33 individual tumors on the Affymetrix 430_2 array for which publicly available datasets can be used to compare levels of gene expression. For aCGH, we used the Agilent 244K array to analyze 19 individual tumors. By GEP we first confirmed the PC origin of the Vk*MYC tumors, that clearly express the typical PC markers, including CD138, IRF4, BLIMP, XBP1, IgG or IgA, but not B cell markers like IgM, IgD, PAX5, or BCL6. Next, we analyzed the expression of the three cyclin D, that are almost universally dysregulated in human myeloma patients and cell lines, but are not expressed in normal human or murine PCs. We found that the Vk*MYC tumors express high levels of cyclin D2, and occasionally cyclin D1, but never cyclin D3 that, instead, is commonly expressed in B cells. Interestingly, in one sample lacking any D type cyclin expression we detected loss of Rb expression (and homozygous deletion of the gene, see below), as in the “TC none” group of human MM patients, highlighting once again the importance of this pathway in both human and mouse myeloma. aGCH analysis indicated that the genomic complexity of Vk*MYC tumors is low, and complex rearrangements were rarely observed. In contrast with the recurrent trisomy of odd number chromosomes present in approximately 50% of human MM patients, we found no evidences of hyperdiploidy in Vk*MYC mice, except perhaps in one tumor with trisomy 15 and 17. Instead, we detected monosomy 5 in 10/19, monosomy 14 in 4/19 and trisomy 16 in 4/19 tumors. Interestingly a large portion of the murine chr.14 is syntenic to the human chr.13, frequently lost in MM patients. After monosomy 13, the most frequent chromosomal change in human MM is loss of a sex chromosome. In the mouse, the most common numerical abnormality identified was loss of a sex chromosome: 10/11 male had loss of Y and 5/8 female had loss of X. From the analysis of aCGH data publicly available on the MMRC portal, we have generated a list of the most common bi-allelic deletions present in human myeloma patients and cell lines. Interestingly, several of these lesions are also present in Vk*MYC tumors. The Rb1 gene, frequently affected by monosomy 13 in human MM, is bi-allelically lost in 3/19 Vk*MYC tumors. In one case, we also detected a focal monoallelic deletion encompassing Rb1, in addition to the four tumors with monosomy 14. Other focal bi-allelic deletion identified are: Cdkn2a (p16 and p19ARF), FHIT and PTEN. The latter was found in a Vk*MYC tumor selected in-vivo to be bortezomib resistant. On chr.X we identified recurrent (5/19 tumors) bi-allelic deletions of UTX, the histone demethylase gene recently reported to be deleted in various cancers, including MM tumors and human myeloma cell lines. While we are in the process of performing functional studies in human cell lines to identify a role for UTX in myeloma pathogenesis, we took advantage of the relative genetic uniformity of the Vk*MYC mice to identify by GEP a signature associated with UTX lost. We separated our cohort of Vk*MYC tumors for which GEP data are available in two groups based on expression of UTX and generated by volcano plot a list of genes that distinguished the two groups. Strikingly, loss of UTX was associated with loss of expression of a subset of lymphoid genes and acquisition of a “macrophage signature”, suggesting a role for UTX in lineage commitment. These data provide a genetic basis for tumor plasticity similar to epithelial mesenchymal transition observed in some solid tumors, in which the tumor gradually acquires supporting characteristics of its microenvironment. We conclude that the Vk*MYC provide a remarkably faithful model of MM not only phenotypically but also genetically, that provides an excellent framework for functional characterization of the molecular pathogenesis of MM Disclosures Bergsagel: Genentech: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Merck: Research Funding.

High levels of circulating miR-16 in the serum of multiple myeloma (MM) patients are independently associated with longer survival. Although the tumor suppressor function of intracellular miR-16 in MM plasma cells (PCs) has been elucidated, its extracellular role in maintaining a nonsupportive cancer microenvironment has not been fully explored. Here, we show that miR-16 is abundantly released by MM cells through extracellular vesicles (EVs) and that differences in its intracellular expression as associated with chromosome 13 deletion (Del13) are correlated to extracellular miR-16 levels. We also demonstrate that EVs isolated from MM patients and from the conditioned media of MM-PCs carrying Del13 more strongly differentiate circulating monocytes to M2-tumor supportive macrophages (TAMs), compared with MM-PCs without this chromosomal aberration. Mechanistically, our data show that miR-16 directly targets the IKKα/β complex of the NF-κB canonical pathway, which is critical not only in supporting MM cell growth, but also in polarizing macrophages toward an M2 phenotype. By using a miR–15a-16-1–KO mouse model, we found that loss of the miR-16 cluster supports polarization to M2 macrophages. Finally, we demonstrate the therapeutic benefit of miR-16 overexpression in potentiating the anti-MM activity by a proteasome inhibitor in the presence of MM-resident bone marrow TAM.

Abstract Recent years have seen an explosion in the availability of paired molecular profiling and drug screen data, providing an unprecedented opportunity for the development of targeted therapies based on an individual’s genetic background. Despite a number of recent successes in diseases ranging from cystic fibrosis to cancer, significant hurdles remain in our ability to accurately predict treatments based on molecular profiling data. In particular, few such tools exist that allow the integration of heterogeneous data types (e.g. genomic, transcriptomic, and somatic mutations), along with high-throughput drug screen data to make predictions about treatment efficacy. Here, we describe a generalized open-source pipeline developed for the analysis of precision medicine data, Pharmacogenomics Prediction Pipeline, or “P3”. The modular design of P3 enables the inclusion of arbitrary input data types and the selection from multiple alternative machine learning algorithms, while automated statistical and visualization reporting steps incorporated throughout the pipeline assist in parameter tuning and early detection of problematic data components. Molecular profiling data is further enriched by the incorporation of external biological information in the form of pathway and gene set annotations such and Gene Ontology (GO) and The Molecular Signatures Database (MSigDB). To demonstrate the use of P3 for preclinical biomarker prediction, we applied P3 to an unpublished multiple myeloma dataset consisting of exome, RNA-Seq, CNV, and drug screen data for 1,912 compounds across 47 tumor cell lines. Specifically, P3 was used to predict molecular features associated with response to treatment for all drugs where a differential response to treatment was observed across patients. Furthermore, molecular profiling and drug screen data for 267 drugs and over a thousand cell lines spanning multiple cancer types from the Genomics of Drug Sensitivity in Cancer (GDSC) project were analyzed using P3, providing insights into shared mechanisms of drug sensitivity and resistance across different cancer and treatment types. Citation Format: V Keith Hughitt, Sayeh Gorjifard, Aleksandra M. Michalowski, John K. Simmons, Ryan Dale, Eric C. Polley, Jonathan J. Keats, Beverly A. Mock. A flexible pipeline for precision medicine biomarker detection and prediction of treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5113.

Abstract ctDNA analysis offers a non-invasive approach for monitoring response and resistance to treatment. Serial ctDNA testing during neoadjuvant therapy (NAT) may provide early indicators of emerging resistance and disease progression. In this study, we analyzed ctDNA from high-risk early breast cancer patients who received NAT and definitive surgery in the I-SPY 2 TRIAL (NCT01042379). We hypothesize that (1) assessment of ctDNA levels early in treatment will improve the performance of molecular and imaging-based predictors of pathologic complete response (pCR) to NAT; and (2) levels of ctDNA after NAT are associated with residual cancer burden and recurrence [distant recurrence free survival (DRFS)]. Methods: ctDNA analysis was performed in 84 high-risk stage II and III breast cancer patients randomized to neoadjuvant investigational agent (n=52), AKT inhibitor MK-2206 (M) in combination with paclitaxel (T) followed by doxorubicin and cyclophosphamide (AC) (M+T-&gt;AC), or standard-of-care (T-&gt;AC) (n=32). HER2+ patients also received trastuzumab (H). Serial plasma was collected before NAT (T0), early treatment (3 weeks, T1), between regimens (12 weeks, T2), and after NAT prior to surgery (T3). Mutational profiles derived from pretreatment tumor biopsy and normal matched DNA whole exome sequencing were used to design personalized assays targeting 16 patient-specific somatic variants to detect ctDNA in serial plasma. Results: Of the 84 patients in this study, 43% were HR-/HER2- (TNBC), 35% HR+/HER2-, and 23% HER2+. In total, 74% (61 of 83), 35% (28 of 79), 14% (9 of 65), and 8% (5 of 61) were positive for ctDNA at timepoints T0, T1, T2, and T3, respectively. At T0, ctDNA positivity and levels (average number of mutant molecules detected per mL) were significantly associated with increased tumor burden (by clinical and MRI examination), more aggressive tumor biology (as reflected in higher Mammaprint scores and grade) and subtype (HER2+ and TNBC). Twenty-seven percent (27%) of the 84 patients achieved a pCR and all patients who were ctDNA-positive at T3 (n=5) did not achieve a pCR. Currently, data are being collected to: (1) assess the relationship of ctDNA and MRI imaging in predicting tumor response to therapy; (2) examine the relationship of ctDNA levels before and after NAT with 3-year DRFS and event-free survival (EFS). The results of these analyses will be presented at the SABCS 2018 meeting. Conclusions: Our study provides a platform to evaluate the clinical significance of ctDNA for serial monitoring of response to NAT. Accurate and early response prediction by highly sensitive ctDNA analysis can facilitate a timely and judicious change in treatment to improve patients' chances of achieving a pCR. Finally, personalized ctDNA testing may complement imaging and pathologic evaluation of tumor response to fine-tune pCR as a surrogate endpoint for improved DRFS and EFS. Citation Format: Magbanua MJM, Brown-Swigart L, Hirst GL, Yau C, Wolf D, Ma AA, Bergin E, Venters S, Sethi H, Wu H-T, Salari R, Tin T, Sawyer S, Louie M, Zimmermann B, Lin C-HJ, Keats J, Liang WS, Cuyugan L, Enriquez D, Tripathy D, Chien AJ, Forero A, DeMichele A, Liu M, Delson AL, Asare S, Esserman L, van't Veer L, I-SPY 2 Consortium. Personalized serial circulating tumor DNA (ctDNA) analysis in high-risk early stage breast cancer patients to monitor and predict response to neoadjuvant therapy and outcome in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD2-01.