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The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten–eleven translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type–specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model TET2 loss-of-function mutations in primary human hematopoietic stem and progenitor cells (HSPC). Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and in vivo competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of TET2-mutant clones in vivo. These results demonstrate the key role of 5hmC in normal hematopoiesis and TET2-mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of preleukemia and clonal hematopoiesis.Significance:We show that 5-hydroxymethylation profiles are cell type–specific and associated with transcriptional abundance and chromatin accessibility across human hematopoiesis. TET2 loss caused aberrant growth and differentiation phenotypes and disrupted 5hmC and transcriptional landscapes. Treatment of TET2 KO HSPCs with ascorbate or azacitidine reverted 5hmC profiles and restored aberrant phenotypes.This article is highlighted in the In This Issue feature, p. 265

Supplementary Figure from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and TET2-Mutant Preleukemia

Supplementary Table from The Cell Type–Specific 5hmC Landscape and Dynamics of Healthy Human Hematopoiesis and TET2-Mutant Preleukemia

Historically, phenotypic-based drug discovery has yielded a high percentage of novel drugs while uncovering new tumor biology. CC-671 was discovered using a phenotypic screen for compounds that preferentially induced apoptosis in triple-negative breast cancer cell lines while sparing luminal breast cancer cell lines. Detailed in vitro kinase profiling shows CC-671 potently and selectively inhibits two kinases—TTK and CLK2. Cellular mechanism of action studies demonstrate that CC-671 potently inhibits the phosphorylation of KNL1 and SRp75, direct TTK and CLK2 substrates, respectively. Furthermore, CC-671 causes mitotic acceleration and modification of pre-mRNA splicing leading to apoptosis, consistent with cellular TTK and CLK inhibition. Correlative analysis of genomic and potency data against a large panel of breast cancer cell lines identifies breast cancer cells with a dysfunctional G1–S checkpoint as more sensitive to CC-671, suggesting synthetic lethality between G1–S checkpoint and TTK/CLK2 inhibition. Furthermore, significant in vivo CC-671 efficacy was demonstrated in two cell line–derived and one patient tumor-derived xenograft models of triple-negative breast cancer (TNBC) following weekly dosing. These findings are the first to demonstrate the unique inhibitory combination activity of a dual TTK/CLK2 inhibitor that preferably kills TNBC cells and shows synthetic lethality with a compromised G1–S checkpoint in breast cancer cell lines. On the basis of these data, CC-671 was moved forward for clinical development as a potent and selective TTK/CLK2 inhibitor in a subset of patients with TNBC. Mol Cancer Ther; 17(8); 1727–38. ©2018 AACR.

SUPPLEMENTAL METHODS • Correlative analysis of CC-671 sensitivity data with genomic features in the 240 Oncopanel • Correlative analysis of CC-671 sensitivity data with genomic features or tumor subtypes in 49 breast cancer cell lines • Molecular of action studies • Xenograft efficacy studies SUPPLEMENTAL DATA • Table S1. Primer sequences for PCR • Table S2. Invitrogen kinase panel data • Table S3. Growth inhibition (IC50 and AUCR Values) of CC-671 in breast cancer panel • Table S4. CC-671 effects on cancer cell proliferation, apoptosis, and cell cycle • Table S5. Cell lines in Oncopanel with mutations in CTNNB1 exon 3 • Table S6. Correlation between CC-671 IC50 values and mutations in CTNNB1 exon 3 in cancer cell lines • Table S7. Correlation of CDKN2A and TP53 mutations with sensitivity or resistance to CC-671 in lung and melanoma cell lines from the Oncopanel • Figure S1. CLK2 knockdown by siRNA reduced phosphorylation of SRp75 in CAL51 cells • Figure S2. Induction of apoptosis in vivo with a single dose of CC-671 in MDA-MB-231 tumors • Figure S3. Antitumor activity of CC-671 in CAL51 and MDA-MB-231 TNBC xenograft models • Figure S4. CC-671 potently and selectively inhibits proliferation and induces apoptosis in cancer cell lines from different anatomic origins • Figure S5. Cancer cell lines with CTNNB1 exon 3 mutations tend to be more sensitive to CC-671 in Oncopanel, but the correlation does not reach statistical significance • Figure S6. TTK expression and CC-671 potency correlate with the growth rates (t0) of cell lines in both breast cancer panel and Oncopanel

The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten–eleven translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type–specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model TET2 loss-of-function mutations in primary human hematopoietic stem and progenitor cells (HSPC). Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and in vivo competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of TET2-mutant clones in vivo. These results demonstrate the key role of 5hmC in normal hematopoiesis and TET2-mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of preleukemia and clonal hematopoiesis. Significance: We show that 5-hydroxymethylation profiles are cell type–specific and associated with transcriptional abundance and chromatin accessibility across human hematopoiesis. TET2 loss caused aberrant growth and differentiation phenotypes and disrupted 5hmC and transcriptional landscapes. Treatment of TET2 KO HSPCs with ascorbate or azacitidine reverted 5hmC profiles and restored aberrant phenotypes. This article is highlighted in the In This Issue feature, p. 265

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease. Significance: In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880

DNA 5-hydroxymethylcytosine (5hmC) modification is known to be associated with gene transcription and frequently used as a mark to investigate dynamic DNA methylation conversion during mammalian development and in human diseases. However, the lack of genome-wide 5hmC profiles in different human tissue types impedes drawing generalized conclusions about how 5hmC is implicated in transcription activity and tissue specificity. To meet this need, we describe the development of a 5hmC tissue map by characterizing the genomic distributions of 5hmC in 19 human tissues derived from ten organ systems. Subsequent sequencing results enabled the identification of genome-wide 5hmC distributions that uniquely separates samples by tissue type. Further comparison of the 5hmC profiles with transcriptomes and histone modifications revealed that 5hmC is preferentially enriched on tissue-specific gene bodies and enhancers. Taken together, the results provide an extensive 5hmC map across diverse human tissue types that suggests a potential role of 5hmC in tissue-specific development; as well as a resource to facilitate future studies of DNA demethylation in pathogenesis and the development of 5hmC as biomarkers., DNA 5-hydroxymethylcytosine (5hmC) modification is associated with gene transcription and used as a mark of mammalian development. Here the authors report a comprehensive 5hmC tissue map and analysis of 5hmC genomic distributions in 19 human tissues derived from 10 organ systems, thus providing insights into the role of 5hmC in tissue-specific development.

Pancreatic cancer is often detected late, when curative therapies are no longer possible. Here, we present non-invasive detection of pancreatic ductal adenocarcinoma (PDAC) by 5-hydroxymethylcytosine (5hmC) changes in circulating cell free DNA from a PDAC cohort (n = 64) in comparison with a non-cancer cohort (n = 243). Differential hydroxymethylation is found in thousands of genes, most significantly in genes related to pancreas development or function (GATA4, GATA6, PROX1, ONECUT1, MEIS2), and cancer pathogenesis (YAP1, TEAD1, PROX1, IGF1). cfDNA hydroxymethylome in PDAC cohort is differentially enriched for genes that are commonly de-regulated in PDAC tumors upon activation of KRAS and inactivation of TP53. Regularized regression models built using 5hmC densities in genes perform with AUC of 0.92 (discovery dataset, n = 79) and 0.92–0.94 (two independent test sets, n = 228). Furthermore, tissue-derived 5hmC features can be used to classify PDAC cfDNA (AUC = 0.88). These findings suggest that 5hmC changes enable classification of PDAC even during early stage disease., Circulating DNA detected in plasma can be used for diagnostic purposes. Here, the authors show that the 5-hydroxymethyl cytosine biomarker from plasma-derived cell free DNA can be used to detect early stage pancreatic cancer.

BACKGROUNDPancreatic cancer (PaC) has poor (10%) 5-year overall survival, largely due to predominant late-stage diagnosis. Patients with new-onset diabetes (NOD) are at a six-to eightfold increased risk for PaC. We developed a pancreatic cancer detection test for the use in a clinical setting that employs a logistic regression model based on 5-hydroxymethylcytosine (5hmC) profiling of cell-free DNA (cfDNA).METHODScfDNA was isolated from plasma from 89 subjects with PaC and 596 case-control non-cancer subjects, and 5hmC libraries were generated and sequenced. These data coupled with machine-learning, were used to generate a predictive model for PaC detection, which was independently validated on 79 subjects with PaC, 163 non-cancer subjects, and 506 patients with non-PaC cancers.RESULTSThe area under the receiver operating characteristic curve for PaC classification was 0.93 across the training data. Training sensitivity was 58.4% (95% confidence interval [CI]: 47.5– 68.6) after setting a classification probability threshold that resulted in 98% (95% CI: 96.5–99) specificity. The independent validation dataset sensitivity and specificity were 51.9% (95% CI: 40.4–63.3) and 100.0% (95% CI: 97.8–100.0), respectively. Early-stage (stage 1 and 2) PaC detection was 47.6% (95% CI: 23%–58%) and 39.4% (95% CI: 32%–64%) in the training and independent validation datasets, respectively. Sensitivity and specificity in NOD patients were 55.2% [95% CI: 35.7–73.6] and 98.4% [95% CI: 91.3–100.0], respectively. The PaC signal was identified in intraductal papillary mucinous neoplasm (64%), pancreatitis (56%), and non-PaC cancers (17%).CONCLUSIONSThe pancreatic cancer detection assay showed robust performance in the tested cohorts and carries the promise of becoming an essential clinical tool to enable early detection in high-risk NOD patients.

Our study employed the detection of 5-hydroxymethyl cytosine (5hmC) profiles on cell free DNA (cfDNA) from the plasma of cancer patients using a novel enrichment technology coupled with sequencing and machine learning based classification method. These classification methods were develoiped to detect the presence of disease in the plasma of cancer and control subjects. Cancer and control patient cfDNA cohorts were accrued from multiple sites consisting of 48 breast, 55 lung, 32 prostate and 53 pancreatic cancer subjects. In addition, a control cohort of 180 subjects (non-cancer) was employed to match cancer patient demographics (age, sex and smoking status) in a case-control study design.Logistic regression methods applied to each cancer case cohort individually, with a balancing non-cancer cohort, were able to classify cancer and control samples with measurably high performance. Measures of predictive performance by using 5-fold cross validation coupled with out-of-fold area under the curve (AUC) measures were established for breast, lung, pancreatic and prostate cancer to be 0.89, 0.84, 0.95 and 0.83 respectively. The genes defining each of these predictive models were enriched for pathways relevant to disease specific etiology, notably in the control of gene regulation in these same pathways. The breast cancer cohort consisted primarily of stage I and II patients, including tumors < 2 cm and these samples exhibited a high cancer probability score. This suggests that the 5hmC derived classification methodology may yield epigenomic detection of early stage disease in plasma. Same observation was made for the pancreatic dataset where >50% of cancers were stage I and II and showed the highest cancer probability score.

Historically, phenotypic-based drug discovery has yielded a high percentage of novel drugs while uncovering new tumor biology. CC-671 was discovered using a phenotypic screen for compounds that preferentially induced apoptosis in triple-negative breast cancer cell lines while sparing luminal breast cancer cell lines. Detailed in vitro kinase profiling shows CC-671 potently and selectively inhibits two kinases—TTK and CLK2. Cellular mechanism of action studies demonstrate that CC-671 potently inhibits the phosphorylation of KNL1 and SRp75, direct TTK and CLK2 substrates, respectively. Furthermore, CC-671 causes mitotic acceleration and modification of pre-mRNA splicing leading to apoptosis, consistent with cellular TTK and CLK inhibition. Correlative analysis of genomic and potency data against a large panel of breast cancer cell lines identifies breast cancer cells with a dysfunctional G1–S checkpoint as more sensitive to CC-671, suggesting synthetic lethality between G1–S checkpoint and TTK/CLK2 inhibition. Furthermore, significant in vivo CC-671 efficacy was demonstrated in two cell line–derived and one patient tumor-derived xenograft models of triple-negative breast cancer (TNBC) following weekly dosing. These findings are the first to demonstrate the unique inhibitory combination activity of a dual TTK/CLK2 inhibitor that preferably kills TNBC cells and shows synthetic lethality with a compromised G1–S checkpoint in breast cancer cell lines. On the basis of these data, CC-671 was moved forward for clinical development as a potent and selective TTK/CLK2 inhibitor in a subset of patients with TNBC. Mol Cancer Ther; 17(8); 1727–38. ©2018 AACR.

e16265 Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

3044 Background: Epigenomics assays have recently become popular tools for identification of molecular biomarkers, both in tissue and in plasma. In particular 5-hydroxymethyl-cytosine (5hmC) method, has been shown to enable the epigenomic regulation of gene expression and subsequent gene activity, with different patterns, across several tumor and normal tissues types. In this study we show that 5hmC profiles enable discrete classification of tumor and normal tissue for breast, colorectal, lung ovary and pancreas. Such classification was also recapitulated in cfDNA from patient with breast, colorectal, lung, ovarian and pancreatic cancers. Methods: DNA was isolated from 176 fresh frozen tissues from breast, colorectal, lung, ovary and pancreas (44 per tumor per tissue type and up to 11 tumor tissues for each stage (I-IV)) and up to 10 normal tissues per tissue type. cfDNA was isolated from plasma from 783 non-cancer individuals and 569 cancer patients. Plasma-isolated cfDNA and tumor genomic DNA, were enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to a reference genome to construct features sets of 5hmC patterns. Results: 5hmC multinomial logistic regression analysis was employed across tumor and normal tissues and identified a set of specific and discrete tumor and normal tissue gene-based features. This indicates that we can classify samples regardless of source, with a high degree of accuracy, based on tissue of origin and also distinguish between normal and tumor status.Next, we employed a stacked ensemble machine learning algorithm combining multiple logistic regression models across diverse feature sets to the cfDNA dataset composed of 783 non cancers and 569 cancers comprising 67 breast, 118 colorectal, 210 Lung, 71 ovarian and 100 pancreatic cancers. We identified a genomic signature that enable the classification of non-cancer versus cancers with an outer fold cross validation sensitivity of 49% (CI 45%-53%) at 99% specificity. Further, individual cancer outer fold cross validation sensitivity at 99% specificity, was measured as follows: breast 30% (CI 119% -42%); colorectal 41% (CI 32%-50%); lung 49% (CI 42%-56%); ovarian 72% (CI 60-82%); pancreatic 56% (CI 46%-66%). Conclusions: This study demonstrates that 5hmC profiles can distinguish cancer and normal tissues based on their origin. Further, 5hmC changes in cfDNA enables detection of the several cancer types: breast, colorectal, lung, ovarian and pancreatic cancers. Our technology provides a non-invasive tool for cancer detection with low risk sample collection enabling improved compliance than current screening methods. Among other utilities, we believe our technology could be applied to asymptomatic high-risk individuals thus enabling enrichment for those subjects that most need a diagnostic imaging follow up.

148 Background: 5-hydroxymethylcytosine (5hmC) is an epigenetic modification which regulates gene expression and is associated with active transcription. The optimization of 5hmC sequencing in cell-free DNA (cfDNA) could therefore enable assessment of gene activity through a liquid biopsy. We aimed to investigate the 5hmC landscape of metastatic castration-resistant prostate cancer (mCRPC) and to evaluate the potential of 5hmC modifications in cfDNA as biomarkers of outcome in mCRPC patients. Methods: Genome-wide 5hmC modifications were analyzed with a low-input whole-genome 5hmC sequencing method based on selective chemical labeling in DNA from 93 mCRPC tissue biopsies previously profiled with whole-genome sequencing (WGS), RNA-sequencing and whole-genome bisulfite sequencing (WGBS). In addition, we analyzed 64 cell-free DNA (cfDNA) samples, from men with mCRPC before first-line abiraterone or enzalutamide, with both 5hmC sequencing and a conventional targeted ctDNA panel assessing common genomic alterations. Results: In mCRPC tissue samples, 5hmC enrichment was more strongly associated with gene expression than promoter methylation or copy number. Among cancer hallmark pathways, the androgen response genes had the strongest association between 5hmC and gene expression, suggesting a disease specific marking of gene activation. 5hmC patterns in cfDNA could be used to estimate the circulating tumor DNA fraction (ct-fraction), which was prognostic for overall survival (tertiles of ct-fraction, HR = 1.6 95%CI 1.1-2.3, p = 0.007). Further, 5hmC levels were indicative of gain of oncogene activity (such as AR, MYC, and PIK3CA) and loss of tumor suppressor gene activity (such as RB1, TP53 and BRCA2). The number of alterations, by 5hmC levels, of common drivers of mCRPC was prognostic for overall survival, also after adjusting for ct-fraction (adjusted p = 0.00001), and the prognostic value of common alterations detected by 5hmC sequencing versus conventional targeted ctDNA sequencing was similar. Finally, 5hmC levels in cfDNA of genes not significantly altered by copy number gain or loss (and thus not routinely included in targeted ctDNA sequencing assays), such as TOP2A and EZH2, identified a high-risk subgroup of mCRPC, which was highly prognostic for overall survival independent of ct-fraction (adjusted HR = 1.8 95%CI 1.2-2.8, p = 0.007). Conclusions: 5hmC in mCRPC tissue demonstrated an association with gene expression that was highest for prostate cancer driver genes, highlighting the ability to track disease-specific biology. 5hmC in cfDNA from men with mCRPC can be used to estimate the ct-fraction of the sample, infer activity gain and loss of common drivers of mCRPC, and identify high-risk groups of mCRPC based on alterations not commonly detected with conventional ctDNA sequencing, showing its potential as a liquid biomarker. Further studies are aimed at optimizing and validating 5hmC-based biomarkers in larger cohorts.

Pomalidomide is an IMiD(®) immunomodulatory agent, which has shown clinically significant benefits in relapsed and/or refractory multiple myeloma (rrMM) patients when combined with dexamethasone, regardless of refractory status to lenalidomide or bortezomib. (Schey et al, ; San Miguel et al, 2013; Richardson et al, 2014; Scott, ) In this work, we present preclinical data showing that the combination of pomalidomide with dexamethasone (PomDex) demonstrates potent anti-proliferative and pro-apoptotic activity in both lenalidomide-sensitive and lenalidomide-resistant MM cell lines. PomDex also synergistically inhibited tumour growth compared with single-agent treatment in xenografts of lenalidomide-resistant H929 R10-1 cells. Typical hallmarks of IMiD compound activity, including IKZF3 (Aiolos) degradation, and the downregulation of interferon regulatory factor (IRF) 4 and MYC, seen in lenalidomide-sensitive H929 MM cell lines, were also observed in PomDex-treated lenalidomide-resistant H929 MM cells. Remarkably, this resulted in strong, synergistic effects on the induction of apoptosis in both lenalidomide-sensitive and resistant MM cells. Furthermore, gene expression profiling revealed a unique differential gene expression pattern in PomDex-treated samples, highlighted by the modulation of pro-apoptotic pathways in lenalidomide-resistant cells. These results provide key insights into molecular mechanisms of PomDex in the lenalidomide-resistant setting.

Background: Our feasibility study employed a novel genomic detection methodology that enriches 5-hydroxymethylcytosine (5hmC) loci in cell free DNA (cfDNA) from the plasma of cancer patients using click chemistry coupled with sequencing and machine learning based classification methods. These classification methods were developed to detect the presence of disease in the plasma of cancer and control subjects. Cancer and control patient cfDNA cohorts were accrued from multiple sites consisting of 48 breast, 55 lung, 32 prostate and 2 pancreatic datasets consisting of 41 and 53 cancer subjects (Set 1 and 2). In addition, a control cohort of 260 subjects (non-cancer) was employed to match cancer patient demographics (age, sex and smoking status) in a case-control study design. Methods: Machine learning methods, applied to each cancer case cohort individually, with a balancing non-cancer cohort, were able to classify cancer and control samples. Measures of predictive performance using 5-fold cross validation coupled with out-of-fold Area Under the Receiver Operating Characteristic Curve (AUROC) measures were employed. Gene sets selected as part of biomarker discovery were further analyzed for disease relevance using pathway analysis tools (GSEA, mSigDB). Results: 260 controls and 229 cancers from four disease types (breast, lung, pancreas and prostate) were analyzed; more than 60% of cancer patients had early stage disease (I or II). Predictive performance, employing AUROC measures, was established for breast (0.89), lung (0.84), pancreas (set 1 - 0.95 and 2 - 0.93) and prostate (0.83). The genes defining each of these predictive models were enriched for pathways relevant to disease specific etiology, notably in the control of gene regulation in these same pathways. The breast cancer cohort consisted primarily of stage I and II patients including tumors < 2 cm and these samples exhibited a higher prediction probability score. The prostate cancer cohort consisted of both indolent and aggressive disease sample and prediction performance was equally high for both (AUROC for indolent vs aggressive was 0.81 and 0.77, respectively). Conclusions: These findings suggest that 5hmC changes in cfDNA enable non-invasive detection of early stage breast, pancreatic, prostate, and lung cancers. Furthermore, 5hmC profiling in cfDNA may enable the prediction of clinically relevant features such as tumor size in breast adenocarcinoma or indolent disease in prostate cancer. Finally, this study identified a suite of 5hmC biomarkers that may be further validated in larger, and more diverse, patient cohorts. Citation Format: Anna Bergamaschi, Jeremy Ku, Yuhong Ning, Francois Collin, Chris Ellison, Tierney Phillips, Erin McCarthy, Wendy Wang, Michael Antoine, David Haan, Aaron Scott, Paul Lloyd, Gulfem Guler, Alan Ashworth, Stephen Quake, Samuel Levy. Epigenomic detection of multiple cancers in plasma derived cell free DNA [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 783.

e21505 Background: Liquid biopsies are gaining prominence for not only cancer diagnosis but also patient monitoring. Mutational signals derived from cell-free DNA (cfDNA) show promise to assess response to cancer treatment, including immunotherapy. However, reliance of these methods on mutational data from tissue biopsies limit their applicability when a tumor biopsy is unavailable, or when mutational landscape of tumor changes under the selective pressures of cancer drug treatment. Epigenomic approaches have the potential to address these shortcomings. Methods: Blood draws were obtained from a cohort of non-small cell lung cancer (NSCLC) patients (n = 19) who went on to anti-PD1 treatment prior to therapy start and while on therapy. cfDNA was isolated from plasma and was subsequently processed to generate 5hmC genome-wide profiles. Results: We analyzed cfDNA from NSCLC patients undergoing anti-PD1 therapy to investigate whether immunotherapy response can be detected from plasma. Using a predictive model trained on lung cancer and non-cancer samples, we were able to detect changes in prediction scores in patient treated with immunotherapy that were consistent with RECIST. Patients with progressive disease (n = 3), determined by RECIST, had prediction scores that increased while they received treatment. On the other hand, majority of the patients that exhibited partial response to treatment (n = 12) had predictive scores that decreased with treatment, again consistent with RECIST. Furthermore, score changes consistent with RECIST was observed one cycle prior to the RECIST timepoint in all except one patient, where an extra blood draw after baseline was available (n = 7). Annotation of the regions that account for differential scoring identified enhancer, 5’UTR and promoter regions. Comparison of partial responders to patients with progressive disease revealed genes involved in metastasis, oncogenes and tumor suppressors that change in opposing directions between these patient groups, consistent with the underlying biology. Conclusions: Our results suggest that 5hmC profiles from cfDNA can be used to determine immunotherapy response in non-small cell lung cancer patients. Compared with mutation based liquid biopsy methods to assess response, epigenomics-based methods have the advantage of being agnostic to starting tumor mutations, and not relying on a mutational analysis from tumor biopsy. Future work will help determine applicability of this method to other kinds of therapies and cancer types.

1539 Background: Epigenomic changes in DNA methylation patterns are more precisely delineated by active demethylation events as marked by 5-hydroxymethylation (5hmC) of cytosine residues. 5hmC appears to be dynamically modulated in tumor tissues and can be employed as a cancer biomarker. Strategies which interrogate 5hmC genome-wide patterns in a liquid biopsy context may provide efficient and precise technology for early cancer screening and detection. In this study we identified genome-wide 5hmC changes in plasma based circulating free DNA (cfDNA) from breast, colorectal, lung, pancreatic and prostate cancer patients versus non-cancer individuals. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using novel click-chemistry protocol for labelling followed by sequencing and alignment to a reference genome to construct features sets of 5hmC patterns. Regularized classification models were constructed to classify cancer samples apart from non-cancer. Results: > 500 non-cancer individuals and > 500 cancer patients across five cancer types (breast, colorectal, lung, pancreas and prostate) were included in this study. About 60% of the cancer samples were early stage disease (I or II). The ability to classify non-cancer versus cancer patients was evaluated by 5-fold cross validation of our trained prediction models. Our models were able to classify all breast cancer with a test auROC of 0.86 while prediction model classification for ER negative samples had an auROC of 0.92. Colorectal performance auROC was 0.9; lung auROC = 0.92, pancreatic auROC = 0.97 and prostate auROC = 0.91. Overall sensitivity range, when allowing 2% false positive, was between 85% and 52%. Further using 5hmC signal in blood we were able to identify several signaling pathways specifically relevant to the biology of the cancers investigated. Conclusions: These findings further demonstrate that 5hmC changes in cfDNA enable non-invasive detection of breast, colorectal, lung pancreatic, and prostate cancers. Further, 5hmC signals enabled the identification of a suite of cancer signaling pathways differentially enriched in cancers versus non-cancers. These data suggest that dynamic changes in tumor cell methylation, detectable through 5-hydroxymethylation, are contained in the circulating blood and signal active disease biology.

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylation cytosine status (5hmC) of circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3’UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3-associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in statistically filtered genes or a comprehensive set of highly variable 5hmC counts in genes and performed with an AUC = 0.94-0.96 on training data. We were able to test the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on two external pancreatic cancer 5hmC data sets and found validation performance to be AUC = 0.74-0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples.

Historically, phenotypic-based drug discovery has yielded a high percentage of novel drugs while uncovering new tumor biology. CC-671 was discovered using a phenotypic screen for compounds that preferentially induced apoptosis in triple-negative breast cancer cell lines while sparing luminal breast cancer cell lines. Detailed

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylated cytosines (5hmC) in circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). 5hmC profiles from PDAC and non-cancer samples were generated using a previously published modified hMe-Seal protocol that utilizes chemical labeling of 5hmC by β-glucosyltransferase and allows detection of cell free 5hmC from small amounts of cfDNA (1). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3’UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3 associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in a comprehensive set of genes with the most variable 5hmC counts and performed with an AUC = 0.94 - 0.96 on training data. We tested the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on three independent pancreatic cancer 5hmC data sets (n = 26, 23 and 7) compared with corresponding independent non-cancer cohorts (n =103, 53 and 10), and found validation performance to be AUC = 0.74 - 0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples. Reference: 1. Song, C. - X. et al. 5 - Hydroxymethylcytosine signatures in cell-free DNA provide information about tumor types and stages. Cell Res 27, 1231 (2017). Citation Format: Francois Collin, Yuhong Ning, Gulfem D. Guler, Tierney Phillips, Erin McCarthy, Aaron Scott, Chris Ellison, Chin-Jen Ku, Kim Chau, Alan Ashworth, Stephen R. Quake, Samuel Levy. Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA [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 1372.

3058 Background: Methylation and hydroxymethylation of cytosines enable the epigenomic regulation of gene suppression and activation. 5-hydroxymethyl-cytosine (5hmC) is globally decreased in tumor tissue. However, genome-wide analysis using precise 5hmC labelling techniques reveals more nuanced changes upon tumorigenesis and raises the possibility that this loss could be exploited for developing a cancer biomarker. This suggests that 5hmC profiles might enable discrete classification of not only tumor tissue but also of tumor cell-free DNA (cfDNA). We sought to identify genome-wide 5hmC changes in plasma based cfDNA from cancer patients representing multiple disease types, stages and clinical characteristics in comparison with non-cancer patients. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to the genome to determine 5hmC counts per genomic feature. Regularized regression models were constructed to classify cancer samples (age matched or corrected for smoking status) on non-overlapping training (80% of all samples) and test sample sets (20% of all samples). Results: 226 non-cancer patients and 278 cancers across four cancer types (breast, colorectal, lung-squamous and pancreas) were included in this study, where more than 60% of cancer samples were early stage disease (I or II). Upon comparison with non-cancer samples, 5hmC peaks have reduced enrichment in exons in breast, colorectal and lung cancer but not in pancreatic cancer. Further, 5hmC peaks in pancreas show different patterns of enrichment in 3’UTR, translational termination sites, promoters and LTR. Overall 5hmC signal density was reduced in late stage cancers across all four diseases. The ability to classify non-cancer versus cancer patients was evaluated via cross-validation of out of fold prediction in the training set with AUC > 0.84 for all four cancer types. Further, test set sensitivity across all four cancer types was found to be > 66% with 98% specificity. Conclusions: These findings suggest that 5hmC changes in plasma cfDNA enable classification of early stages of breast, colorectal, lung-squamous and pancreas cancer and are promising biomarkers for disease detection.

Cereblon (CRBN), the molecular target of lenalidomide and pomalidomide, is a substrate receptor of the cullin ring E3 ubiquitin ligase complex, CRL4(CRBN) . T cell co-stimulation by lenalidomide or pomalidomide is cereblon dependent: however, the CRL4(CRBN) substrates responsible for T cell co-stimulation have yet to be identified. Here we demonstrate that interaction of the transcription factors Ikaros (IKZF1, encoded by the IKZF1 gene) and Aiolos (IKZF3, encoded by the IKZF3 gene) with CRL4(CRBN) is induced by lenalidomide or pomalidomide. Each agent promotes Aiolos and Ikaros binding to CRL4(CRBN) with enhanced ubiquitination leading to cereblon-dependent proteosomal degradation in T lymphocytes. We confirm that Aiolos and Ikaros are transcriptional repressors of interleukin-2 expression. The findings link lenalidomide- or pomalidomide-induced degradation of these transcriptional suppressors to well documented T cell activation. Importantly, Aiolos could serve as a proximal pharmacodynamic marker for lenalidomide and pomalidomide, as healthy human subjects administered lenalidomide demonstrated Aiolos degradation in their peripheral T cells. In conclusion, we present a molecular model in which drug binding to cereblon results in the interaction of Ikaros and Aiolos to CRL4(CRBN) , leading to their ubiquitination, subsequent proteasomal degradation and T cell activation.

Historically, synthetic lethal-based drug discovery has yielded a high percentage of novel, first-in-class drugs while uncovering new tumor biology. Using a synthetic lethal approach, we identified one compound that preferentially induced apoptosis in triple-negative breast cancer (TNBC) cell lines while sparing luminal breast cancer cell lines. The synthetic lethal approach evolved into a targeted approach following the identification of the two kinases that were selectively inhibited by CC-671 in enzyme assays: human protein kinase monopolar spindle 1 (hMps1), also known as TTK, and CDC2-like kinase (CLK2). Detailed CC-671 cellular mechanism of action studies showed phosphorylation inhibition of the direct substrates of TTK and CLK2. The CC-671 IC50 concentration that inhibited phosphorylation of the CLK2 substrate SR protein ranged between 530 and 553 nM in CAL51 cells. Gene Set Enrichment Analyses (GSEA) of RNAseq data suggest that CC-671 CLK2 inhibition induces apoptosis by reducing expression of antiapoptotic isoforms via splicing modification. Cellular CC-671 TTK inhibition was demonstrated by significant reduction of TTK autophosphorylation at T686 and phosphorylation of KNL1, one of the well-characterized TTK substrates. CC-671 treatment also led to a decrease of cyclin B and securin protein level. As a result, the percentage of mitotic cells in nocodazole-arrested CAL51 cells was substantially reduced by CC-671. Furthermore, data from time-lapse video microscopy experiments confirmed the mitotic phase length was reduced by approximately half upon CC-671 treatment. Inhibition of phospho-Histone H3 (Ser 10) following a single CC-671 administration was observed in TNBC in vivo tumor model. More importantly, significant CC-671 in vivo efficacy was demonstrated in a cell line-derived TNBC xenograft model with weekly dosing. The data described here suggest that dual inhibition of TTK and CLK2 represents an attractive therapeutic approach for triple-negative breast cancer. CC-671 presents a unique profile for an anticancer kinase inhibitor. Citation Format: Dan Zhu, Gordafaried Deyanat-Yazdi, David Mikolon, Rama K. Narla, Sophie X. Peng, Yuhong Ning, Jennifer R. Riggs, John F. Boylan. Synthetic lethal approach identifies potent and selective TTK and CLK inhibitor with preclinical anticancer activity in triple-negative breast cancer model [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B177.

Cellular responses to inputs that vary both temporally and spatially are determined by complex relationships between the components of cell signaling networks. Analysis of these relationships requires access to a wide range of experimental reagents and techniques, including the ability to express the protein components of the model cells in a variety of contexts. As part of the Alliance for Cellular Signaling, we developed a robust method for cloning large numbers of signaling ORFs into Gateway® entry vectors, and we created a wide range of compatible expression platforms for proteomics applications. To date, we have generated over 3000 plasmids that are available to the scientific community via the American Type Culture Collection. We have established a website at www.signaling-gateway.org/data/plasmid/ that allows users to browse, search, and blast Alliance for Cellular Signaling plasmids. The collection primarily contains murine signaling ORFs with an emphasis on kinases and G protein signaling genes. Here we describe the cloning, databasing, and application of this proteomics resource for large scale subcellular localization screens in mammalian cell lines.

Cereblon (CRBN), the molecular target of lenalidomide and pomalidomide, is a substrate receptor of the cullin ring E3 ubiquitin ligase complex, CRL4(CRBN) . T cell co-stimulation by lenalidomide or pomalidomide is cereblon dependent: however, the CRL4(CRBN) substrates responsible for T cell co-stimulation have yet to be identified. Here we demonstrate that interaction of the transcription factors Ikaros (IKZF1, encoded by the IKZF1 gene) and Aiolos (IKZF3, encoded by the IKZF3 gene) with CRL4(CRBN) is induced by lenalidomide or pomalidomide. Each agent promotes Aiolos and Ikaros binding to CRL4(CRBN) with enhanced ubiquitination leading to cereblon-dependent proteosomal degradation in T lymphocytes. We confirm that Aiolos and Ikaros are transcriptional repressors of interleukin-2 expression. The findings link lenalidomide- or pomalidomide-induced degradation of these transcriptional suppressors to well documented T cell activation. Importantly, Aiolos could serve as a proximal pharmacodynamic marker for lenalidomide and pomalidomide, as healthy human subjects administered lenalidomide demonstrated Aiolos degradation in their peripheral T cells. In conclusion, we present a molecular model in which drug binding to cereblon results in the interaction of Ikaros and Aiolos to CRL4(CRBN) , leading to their ubiquitination, subsequent proteasomal degradation and T cell activation.

Thalidomide and the IMiD immunomodulatory drugs, lenalidomide and pomalidomide, are widely used in the treatment of multiple myeloma (MM), del(5q) myelodysplastic syndromes and other hematologic malignancies, including mantle cell lymphoma. Ito et al.1 recently identified cereblon as a key target of thalidomide. Subsequent studies confirmed cereblon to be a common target for lenalidomide and pomalidomide, and established its essential role in mediating anticancer and immunomodulatory effects of these drugs.2, 3 Cereblon is encoded by the CRBN gene on chromosome 3 containing 11 exons, and the fully spliced transcript produces a 51-kDa protein. Cereblon is a component of the cullin ring E3 ubiquitin ligase complex (CRL4CRBN) that also contains DNA damage-binding protein 1 (DDB1), cullin (Cul) 4a and regulator of cullins (Roc) 1.1 E3 ligases attach ubiquitin moieties to specific substrate proteins in the cell that can mark them for proteasomal degradation. The putative role of cereblon within the E3 ligase complex is that of a substrate receptor.

Recent clinical studies suggest that adoptive transfer of donor-derived natural killer (NK) cells may improve clinical outcome in hematological malignancies and some solid tumors by direct antitumor effects as well as by reduction of graft versus host disease (GVHD). NK cells have also been shown to enhance transplant engraftment during allogeneic hematopoietic stem cell transplantation (HSCT) for hematological malignancies. The limited ex vivo expansion potential of NK cells from peripheral blood (PB) or umbilical cord blood (UCB) has however restricted their therapeutic potential. Here we define methods to efficiently generate NK cells from donor matched, full-term human placenta perfusate (termed Human Placenta-Derived Stem Cell, HPDSC) and UCB. Following isolation from cryopreserved donor-matched HPDSC and UCB units, CD56+CD3- placenta-derived NK cells, termed pNK cells, were expanded in culture for up to 3 weeks to yield an average of 1.2 billion cells per donor that were >80% CD56+CD3-, comparable to doses previously utilized in clinical applications. Ex vivo-expanded pNK cells exhibited a marked increase in anti-tumor cytolytic activity coinciding with the significantly increased expression of NKG2D, NKp46 and NKp44 (p < 0.001, p < 0.001, and p < 0.05, respectively). Strong cytolytic activity was observed against a wide range of tumor cell lines in vitro. pNK cells display a distinct microRNA (miRNA) expression profile, immunophenotype and greater antitumor capacity in vitro compared to PB NK cells used in recent clinical trials. With further development, pNK may represent a novel and effective cellular immunotherapy for patients with high clinical needs and few other therapeutic options.

BACKGROUND: The cytidine nucleoside analogs azacitidine (AZA) and decitabine (DAC) are used for the treatment of patients with myelodysplastic syndromes and acute myeloid leukemia (AML). Few non-clinical studies have directly compared the mechanisms of action of these agents in a head-to-head fashion, and the agents are often viewed as mechanistically similar DNA hypomethylating agents. To better understand the similarities and differences in mechanisms of these drugs, we compared their in vitro effects on several end points in human AML cell lines. METHODOLOGY/PRINCIPAL FINDINGS: Both drugs effected DNA methyltransferase 1 depletion, DNA hypomethylation, and DNA damage induction, with DAC showing equivalent activity at concentrations 2- to 10-fold lower than AZA. At concentrations above 1 microM, AZA had a greater effect than DAC on reducing cell viability. Both drugs increased the sub-G1 fraction and apoptosis markers, with AZA decreasing all cell cycle phases and DAC causing an increase in G2-M. Total protein synthesis was reduced only by AZA, and drug-modulated gene expression profiles were largely non-overlapping. CONCLUSIONS/SIGNIFICANCE: These data demonstrate shared mechanisms of action of AZA and DAC on DNA-mediated markers of activity, but distinctly different effects in their actions on cell viability, protein synthesis, cell cycle, and gene expression. The differential effects of AZA may be mediated by RNA incorporation, as the distribution of AZA in nucleic acid of KG-1a cells was 65:35, RNA:DNA.

Cellular responses to inputs that vary both temporally and spatially are determined by complex relationships between the components of cell signaling networks. Analysis of these relationships requires access to a wide range of experimental reagents and techniques, including the ability to express the protein components of the model cells in a variety of contexts. As part of the Alliance for Cellular Signaling, we developed a robust method for cloning large numbers of signaling ORFs into Gateway® entry vectors, and we created a wide range of compatible expression platforms for proteomics applications. To date, we have generated over 3000 plasmids that are available to the scientific community via the American Type Culture Collection. We have established a website at www.signaling-gateway.org/data/plasmid/ that allows users to browse, search, and blast Alliance for Cellular Signaling plasmids. The collection primarily contains murine signaling ORFs with an emphasis on kinases and G protein signaling genes. Here we describe the cloning, databasing, and application of this proteomics resource for large scale subcellular localization screens in mammalian cell lines.

Recent discoveries suggest that the critical events leading to the anti-proliferative activity of the IMiD immunomodulatory agents lenalidomide and pomalidomide in multiple myeloma (MM) cells are initiated by Cereblon-dependent ubiquitination and proteasomal degradation of substrate proteins Ikaros (IKZF1) and Aiolos (IKZF3). By performing kinetic analyses, we found that the downregulation or proteasomal degradation of Ikaros and Aiolos led to specific and sequential downregulation of c-Myc followed by IRF4 and subsequent growth inhibition and apoptosis. Notably, to ensure growth inhibition and cell death, sustained downregulation of Ikaros and Aiolos, c-Myc or IRF4 expression was required. In addition, we found that the half-maximal rate, rather than the final extent of Ikaros and Aiolos degradation, correlated to the relative efficacy of growth inhibition by lenalidomide or pomalidomide. Finally, we observed that all four transcription factors were elevated in primary MM samples compared with normal plasma cells. Taken together, our results suggest a functional link between Ikaros and Aiolos, and the pathological dysregulation of c-Myc and IRF4, and provide a new mechanistic understanding of the relative efficacy of lenalidomide and pomalidomide based on the kinetics of substrate degradation and downregulation of their downstream targets.

The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells — B lymphocytes (the cells of the immune system) and cardiac myocytes — to facilitate quantitative modelling. One goal is to catalyse complementary research in individual laboratories; to facilitate this, all alliance data are freely available for use by the entire research community.

Background CRBN, a target of thalidomide and IMiDs® immunomodulatory agents lenalidomide (LEN) and pomalidomide (POM), is a component of the E3 ubiquitin cullin 4 ring ligase (CRL4) complex that also includes DDB1, Roc1, and Cul4. Two CRBN mutations have been reported in multiple myeloma (MM) patients: truncating mutation (Q99) and point mutation (R283K). One copy of the CRBN gene was shown to be deleted in the MM1S and MM1S.R cell lines. No DDB1 mutation has been described previously. Results We investigated the incidence of CRBN and DDB1 mutations by next-generation sequencing in 20 MM cell lines and MM subjects. Of 90 MM patients, 24 were newly diagnosed and 66 were relapsed and refractory of which 36 patients were LEN resistant. Out of the cell lines tested, 1 heterozygous CRBN mutation (D249Y) was found in the LEN-resistant ANBL6R cells, which is located in the putative DDB1 binding domain, and 2 single silent mutations were identified in the KMS-12-BM (rs17027638) and OPM-2 cells. One DDB1 heterozygous mutation (E303D) was identified in ANBL6 cells. In the cohort of patients assessed, no CRBN mutation was detected; however, 5 single nucleotide variations (SNV) were identified. Three of the 5 SNVs were at position 735 (Y245Y) and 1 each at position 219 (H73H) and 939 (C313C), respectively. The first 2 SNVs (rs17027638 and rs1045309) are described but not the last. We found a single SNV (P51P; rs2230356) in DDB1 gene the patient samples. Conclusion Mutations within the coding sequences of CRBN and DDB1 are rare in MM patients and cell lines. Most intrinsically LEN-resistant cells and cell lines made resistant to LEN or POM do not have CRBN or DDB1 mutations, suggesting the potential role of other sources, such as genetic or epigenetic pathways in developing resistance to IMiD drug–based therapy. Disclosures: Thakurta: Celgene: Employment, Equity Ownership. Gandhi:Celgene: Employment, Equity Ownership. Waldman:Celgene: Employment, Equity Ownership. Bjorklund:Celgene: Employment, Equity Ownership. Lentzsch:Celgene: Research Funding. Schey:Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; NAPP: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau. Orlowski:Bristol-Myers Squibb: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Millennium: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Resverlogix: Research Funding; Array: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Membership on an entity’s Board of Directors or advisory committees. Madan:Covance Genomics Lab: Employment. Ning:Celgene: Employment, Equity Ownership. Mendy:Celgene: Employment, Equity Ownership. Lopez-Girona:Celgene: Employment, Equity Ownership. Schafer:Celgene: Employment, Equity Ownership. Avet-Loiseau:Celgene: Research Funding. Chopra:Celgene: Employment, Equity Ownership.

Romidepsin is a class I selective HDAC inhibitor approved for the treatment of cutaneous T cell lymphoma (CTCL) and peripheral T cell lymphoma (PTCL) in the US. In contrast to the 30% response rate to romidepsin in these malignancies, only rare responses have been reported in solid tumor clinical trials. A molecular understanding of the basis for romidepsin's anti-tumor effects could lead to the development of predictive biomarkers to select patients who are most likely to benefit from this agent. As an initial step towards identifying candidate predictive biomarkers, we undertook an in vitro screen for romidepsin sensitivity in over 100 cell lines representing hematologic malignancies and eight different solid tumors. Here, we report the results of this screen and its use, in conjunction with gene expression profiling (GEP) to identify TSPYL5, a novel candidate biomarker, as a predictor of resistance to romidepsin. A limitation of previously reported cell viability screens using romidepsin has been the use of prolonged incubation times which vastly exceed the clinical exposure of tumor cells to this agent. Moreover, earlier screens have based sensitivity on cell line EC50/IC50 values, suggesting that romidepsin is broadly active in solid tumors within a narrow range of sensitivities which is not consistent with clinical data in solid tumors. For our screen, we utilized a 6 hour drug exposure which is similar to the exposure of patients receiving the drug. Sensitivity to romidepsin treatment after 72 hours was assessed by Cell Titer Glo and was expressed as a composite score incorporating the IC50 and % growth inhibition or cell kill (S score). As expected, based on clinical data, the most sensitive lines (lowest S scores) are derived from hematologic malignancies, including T cell lymphomas. Solid tumor cell lines exhibit a broad range of S scores. We compared the baseline GEP of sensitive and resistant lines to identify differentially expressed genes associated with sensitivity or resistance. Two genes strongly correlated with resistance were ABCB1, encoding a drug efflux pump implicated in resistance to romidepsin and TSPYL5, encoding a protein that modulates P53 stability via interaction with the USP7 deubiquitinase. Cell lines with readily detectable expression of TSPYL5 are resistant to treatment with romidepsin. We observed a similar relationship between TSPYL5 expression and resistance to panobinostat, a pan-HDAC inhibitor and in primary human tumor cells treated with romidepsin. Cell lines in which TSPYL5 was knocked down using shRNA show increased sensitivity to treatment. Our work identifies potentially novel applications for HDAC inhibitors in the treatment of certain solid malignancies. These data may be useful to guide clinical development or as a tool in further research aimed at understanding the mode of action of HDAC inhibitors. Citation Format: Brett Garrick, Erin Schwartz, Yuhong Ning, Lin Tang, Jorge DiMarino, Torsten B. Trowe. A cell line screen identifies TSPYL5 as marker for resistance to HDAC inhibitor treatment. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4648. doi:10.1158/1538-7445.AM2013-4648

Abstract 117 Background: Parenteral azacitidine significantly improves overall survival of subjects with higher-risk MDS and WHO AML (20–30% blasts) compared to conventional care (Fenaux, Lancet Oncol 2009; 10:223). An oral formulation would be a more convenient administration route for patients and allow the evaluation of extended low-dose regimens, which could in turn lead to better treatment efficacy and lower toxicity profiles. The aim of this phase 1 study is to determine the maximum tolerated dose (MTD), dose limiting toxicities (DLTs), safety, pharmacokinetic (PK) and pharmacodynamic (PD) profiles of increasing doses of orally-administered azacitidine in subjects with MDS or AML. Methods: Subjects aged ≥ 18 years with a diagnosis of MDS or AML (not candidates for other therapies) by WHO criteria were enrolled into this multicenter, Phase 1, dose escalation study. Prior treatment with azacitidine or other demethylating agent was permitted. To allow PD/PK analyses of oral vs. subcutaneous (SC) administration, azacitidine was administered SC (75 mg/m2/day x 7 days) in Cycle 1, then orally in Cycle 2 starting at a dose of 120 mg/day x 7 days of every 28-day cycle. A standard “3+3” dose escalation design was used and an expansion cohort at the MTD was planned. Subjects were evaluated for DLT during the first cycle of oral azacitidine therapy. Azacitidine levels in plasma and urine were measured. DNA methylation was assayed using Illumina's Infinium Human Methylation27 BeadArrays. Response was assessed according to International Working Group (IWG) criteria for MDS (2006) and AML (2003). Results: To date, 45 subjects have enrolled into the study. Forty subjects received both SC and oral azacitidine; 5 subjects received SC azacitidine only. Median age is 70 years (range 31–91). Thirty-four subjects had MDS, 9 AML, and 2 CMML. Median pretreatment WBC and platelet counts of MDS subjects were 2.5 × 109/L (range 0.8–39.4) and 55.0 × 109/L (range 4.0–234.0) respectively. For subjects with AML, the median pretreatment WBC and platelet counts were 1.8 × 109/L (range 0.5–3.4) and 42.8 × 109/L (range 10.0–82.0) respectively. Baseline cytogenetics for subjects with MDS were as follows: 12 complex karyotype; 10 diploid; 1 with −7; 1 with t(11q23) and 10 whose karyotype was unknown. Doses of oral azacitidine evaluated were 120, 180, 240, 300, 360, 480 and 600 mg. The MTD of oral azacitidine on a 7-day QD treatment schedule was 480 mg. The DLT was grade 3 or 4 diarrhea in 2 of 3 subjects enrolled in the 600 mg cohort. Other grade 3 or 4 AEs reported include febrile neutropenia (6 subjects), infection (6 subjects), nausea (2 subjects), vomiting (2 subjects), fatigue (2 subjects), and thrombocytopenia (2 subjects). The bioavailability of oral azacitidine ranged from 5% to 35%. The exposure (AUCinf) of oral azacitidine was highly variable compared to SC exposure, ranging from 15% to 74% (except for one subject whose PK exposure following oral therapy was 167% of his SC exposure). Median duration of oral azacitidine was 5+ cycles (range 1–19+) for subjects with MDS and 2.5+ cycles (range 1–6+) for subjects with AML. Responses were evaluated following 6 cycles of oral therapy. To date, 14 subjects have received ≥ 6 cycles of oral azacitidine: 4 (29%) had complete response (CR), 6 (43%) had stable disease (SD), 3 (21%) had disease progression, and 1 subject (7%) was not evaluated. Among subjects with CR or SD, hematologic improvement by disease-specific IWG criteria included erythroid response (n = 5), platelet response (n = 5) and neutrophil response (n = 3). Fourteen subjects are ongoing, but have not completed 6 cycles of oral therapy; 17 subjects discontinued prior to completing 6 cycles. Changes in DNA methylation were observed in the blood of MDS and AML subjects following SC and oral azacitidine treatment, and a set of CpG loci were identified for which these changes were associated with azacitidine AUCinf and/or Cmax.. In addition, approximately 260 hypomethylated loci were common to both SC and oral therapy. Conclusions: Results to date indicate that a 7-day dosing regimen of oral azacitidine is active and well tolerated, with a manageable side effect profile in subjects with MDS or AML. Oral azacitidine exposure was highly variable and lower than that of SC azacitidine. Changes in DNA methylation were observed in the blood of MDS and AML subjects following SC and oral therapy. Evaluation of prolonged and BID treatment schedules is planned. Disclosures: Garcia-Manero: Celgene: Research Funding. Gore:Celgene: Consultancy, Equity Ownership, Research Funding; Johnson & Johnson: Research Funding. Skikne:Celgene: Employment. Cogle:Celgene: Research Funding, Speakers Bureau; Eisai: Speakers Bureau. Ning:Celgene: Employment, Equity Ownership. MacBeth:Celgene Corporation: Employment, Equity Ownership. Laille:Celgene: Employment, Equity Ownership. Ward:Celgene: Employment, Equity Ownership.