Showing papers by "Todd R. Golub published in 2018"

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes

Abstract: Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.

Genetic and transcriptional evolution alters cancer cell line drug response

Abstract: Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.

Developmental and oncogenic programs in H3K27M gliomas dissected by single-cell RNA-seq

Abstract: Gliomas with histone H3 lysine27-to-methionine mutations (H3K27M-glioma) arise primarily in the midline of the central nervous system of young children, suggesting a cooperation between genetics and cellular context in tumorigenesis. Although the genetics of H3K27M-glioma are well characterized, their cellular architecture remains uncharted. We performed single-cell RNA sequencing in 3321 cells from six primary H3K27M-glioma and matched models. We found that H3K27M-glioma primarily contain cells that resemble oligodendrocyte precursor cells (OPC-like), whereas more differentiated malignant cells are a minority. OPC-like cells exhibit greater proliferation and tumor-propagating potential than their more differentiated counterparts and are at least in part sustained by PDGFRA signaling. Our study characterizes oncogenic and developmental programs in H3K27M-glioma at single-cell resolution and across genetic subclones, suggesting potential therapeutic targets in this disease.

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

Abstract: The availability of multiple datasets comprising genome-scale RNAi viability screens in hundreds of diverse cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated cell line screen-quality parameters and hierarchical Bayesian inference into DEMETER2, an analytical framework for analyzing RNAi screens ( https://depmap.org/R2-D2 ). This model substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes and agreement with CRISPR/Cas9-based viability screens. It also allows us to integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.

Selective gene dependencies in MYCN-amplified neuroblastoma include the core transcriptional regulatory circuitry.

Abstract: Childhood high-risk neuroblastomas with MYCN gene amplification are difficult to treat effectively1. This has focused attention on tumor-specific gene dependencies that underlie tumorigenesis and thus provide valuable targets for the development of novel therapeutics. Using unbiased genome-scale CRISPR–Cas9 approaches to detect genes involved in tumor cell growth and survival2–6, we identified 147 candidate gene dependencies selective for MYCN-amplified neuroblastoma cell lines, compared to over 300 other human cancer cell lines. We then used genome-wide chromatin-immunoprecipitation coupled to high-throughput sequencing analysis to demonstrate that a small number of essential transcription factors—MYCN, HAND2, ISL1, PHOX2B, GATA3, and TBX2—are members of the transcriptional core regulatory circuitry (CRC) that maintains cell state in MYCN-amplified neuroblastoma. To disable the CRC, we tested a combination of BRD4 and CDK7 inhibitors, which act synergistically, in vitro and in vivo, with rapid downregulation of CRC transcription factor gene expression. This study defines a set of critical dependency genes in MYCN-amplified neuroblastoma that are essential for cell state and survival in this tumor. This study identifies a set of critical dependency genes in MYCN-amplified neuroblastoma that make up the oncogenic transcriptional regulatory circuitry underlying cell state and tumor survival.

Association of Cell-Free DNA Tumor Fraction and Somatic Copy Number Alterations With Survival in Metastatic Triple-Negative Breast Cancer.

Abstract: Purpose Cell-free DNA (cfDNA) offers the potential for minimally invasive genome-wide profiling of tumor alterations without tumor biopsy and may be associated with patient prognosis. Triple-negative breast cancer (TNBC) is characterized by few mutations but extensive somatic copy number alterations (SCNAs), yet little is known regarding SCNAs in metastatic TNBC. We sought to evaluate SCNAs in metastatic TNBC exclusively via cfDNA and determine if cfDNA tumor fraction is associated with overall survival in metastatic TNBC. Patients and Methods In this retrospective cohort study, we identified 164 patients with biopsy-proven metastatic TNBC at a single tertiary care institution who received prior chemotherapy in the (neo)adjuvant or metastatic setting. We performed low-coverage genome-wide sequencing of cfDNA from plasma. Results Without prior knowledge of tumor mutations, we determined tumor fraction of cfDNA for 96.3% of patients and SCNAs for 63.9% of patients. Copy number profiles and percent genome altered were remarkably similar between metastatic and primary TNBCs. Certain SCNAs were more frequent in metastatic TNBCs relative to paired primary tumors and primary TNBCs in publicly available data sets The Cancer Genome Atlas and METABRIC, including chromosomal gains in drivers NOTCH2, AKT2, and AKT3. Prespecified cfDNA tumor fraction threshold of ≥ 10% was associated with significantly worse metastatic survival (median, 6.4 v 15.9 months) and remained significant independent of clinicopathologic factors (hazard ratio, 2.14; 95% CI, 1.4 to 3.8; P < .001). Conclusion We present the largest genomic characterization of metastatic TNBC to our knowledge, exclusively from cfDNA. Evaluation of cfDNA tumor fraction was feasible for nearly all patients, and tumor fraction ≥ 10% is associated with significantly worse survival in this large metastatic TNBC cohort. Specific SCNAs are enriched and prognostic in metastatic TNBC, with implications for metastasis, resistance, and novel therapeutic approaches.

Abstract 1028: Patient-derived xenografts undergo mouse-specific tumor evolution

Abstract: Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of pre-existing minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Importantly, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have important implications for PDX-based modeling of human cancer. Citation Format: Uri Ben-David, Gavin Ha, Yuen-Yi Tseng, Noah F. Greenwald, Coyin Oh, Juliann Shih, James M. McFarland, Bang Wong, Jesse S. Boehm, Rameen Beroukhim, Todd R. Golub. Patient-derived xenografts undergo mouse-specific tumor evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1028.

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

Abstract: The availability of multiple datasets together comprising hundreds of genome-scale RNAi viability screens across a diverse range of cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated estimation of cell line screen quality parameters and hierarchical Bayesian inference into an analytical framework for analyzing RNAi screens (DEMETER2; https://depmap.org/R2-D2). We applied this model to individual large-scale datasets and show that it substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes as well as agreement with CRISPR-Cas9-based viability screens. This model also allows us to effectively integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.

Drug and disease signature integration identifies synergistic combinations in glioblastoma.

Abstract: Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations.

Abstract: Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics.

WRN Helicase is a Synthetic Lethal Target in Microsatellite Unstable Cancers

Abstract: Summary paragraph Synthetic lethality, an interaction whereby the co-occurrence of two or more genetic events lead to cell death but one event alone does not, can be exploited to develop novel cancer therapeutics1. DNA repair processes represent attractive synthetic lethal targets since many cancers exhibit an impaired DNA repair pathway, which can lead these cells to become dependent on specific repair proteins2. The success of poly (ADP-ribose) polymerase 1 (PARP-1) inhibitors in homologous recombination-deficient cancers highlights the potential of this approach in clinical oncology3,4. Hypothesizing that other DNA repair defects would give rise to alternative synthetic lethal relationships, we asked if there are specific dependencies in cancers with microsatellite instability (MSI), which results from impaired DNA mismatch repair (MMR). Here we analyzed data from large-scale CRISPR/Cas9 knockout and RNA interference (RNAi) silencing screens and found that the RecQ DNA helicase WRN was selectively essential in MSI cell lines, yet dispensable in microsatellite stable (MSS) cell lines. WRN depletion induced double-strand DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models specifically required the helicase activity, but not the exonuclease activity of WRN. These findings expose WRN as a synthetic lethal vulnerability and promising drug target in MSI cancers.

Therapeutically targeting tumor microenvironment–mediated drug resistance in estrogen receptor–positive breast cancer

Abstract: Drug resistance to approved systemic therapies in estrogen receptor-positive (ER+) breast cancer remains common. We hypothesized that factors present in the human tumor microenvironment (TME) drive drug resistance. Screening of a library of recombinant secreted microenvironmental proteins revealed fibroblast growth factor 2 (FGF2) as a potent mediator of resistance to anti-estrogens, mTORC1 inhibition, and phosphatidylinositol 3-kinase inhibition in ER+ breast cancer. Phosphoproteomic analyses identified ERK1/2 as a major output of FGF2 signaling via FGF receptors (FGFRs), with consequent up-regulation of Cyclin D1 and down-regulation of Bim as mediators of drug resistance. FGF2-driven drug resistance in anti-estrogen-sensitive and -resistant models, including patient-derived xenografts, was reverted by neutralizing FGF2 or FGFRs. A transcriptomic signature of FGF2 signaling in primary tumors predicted shorter recurrence-free survival independently of age, grade, stage, and FGFR amplification status. These findings delineate FGF2 signaling as a ligand-based drug resistance mechanism and highlights an underdeveloped aspect of precision oncology: characterizing and treating patients according to their TME constitution.

Author Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Abstract: In the version of this article originally published, an asterisk was omitted from Fig. 1a. The asterisk has been added to the figure. Additionally, a “NOTCH2” label was erroneously included in Fig. 4a. The label has been removed. The errors have been corrected in the PDF and HTML versions of this article.

Retraction Note: Selective killing of cancer cells by a small molecule targeting the stress response to ROS

Abstract: This Letter is being retracted owing to issues with Fig. 1d and Supplementary Fig. 31b, and the unavailability of original data for these figures that raise concerns regarding the integrity of the figures. Nature published two previous corrections related to this Letter1,2. These issues in aggregate undermine the confidence in the integrity of this study. Authors Michael Foley, Monica Schenone, Nicola J. Tolliday, Todd R. Golub, Steven A. Carr, Alykhan F. Shamji, Andrew M. Stern and Stuart L. Schreiber agree with the Retraction. Authors Lakshmi Raj, Takao Ide, Aditi U. Gurkar, Anna Mandinova and Sam W. Lee disagree with the Retraction. Author Xiaoyu Li did not respond.

Count me in: A patient-driven research initiative to accelerate cancer research.

Abstract: e13501Background: A challenge in cancer research is the availability of tumor samples linked to clinical information. To address this, we worked with patients (pts) to develop patient-driven studie...

Abstract 5371: The Metastatic Breast Cancer Project: Partnering with patients to accelerate progress in cancer research

Abstract: The Metastatic Breast Cancer Project (MBCproject) is a research study that directly engages patients (pts) through social media and advocacy groups, and empowers them to share samples, clinical data, and experiences. The goal is to create a publicly available database of genomic, molecular, clinical, and patient-reported data to enable research. Working with pts and advocates, a website (MBCproject.org) was developed that allows pts with metastatic breast cancer (MBC) to register. Registered pts are sent an online consent form that asks for permission to obtain and analyze their medical records and samples. Once enrolled, pts are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. We contact participants9 medical providers and obtain medical records and a portion of their stored tumor biopsies. Pts may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole-exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfNDA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific pt cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data are shared via public databases. Study updates are shared with participants regularly. From 10/2015-11/2017, 4237 MBC pts registered, representing over 1,000 institutions. 95% answered the 16-question survey about their cancer, treatments, and demographic information. 2471 (58%) completed the consent form. 2,136 saliva kits were mailed to pts and 1,523 saliva samples were sent in (71%). 408 blood kits were mailed to pts and 175 blood samples have been received for cfDNA analysis. To date, we have obtained medical records from 311 pts and 190 tumors from 127 pts. In 10/2017, all data generated so far were publicly released on cbioportal.org, including WES for 103 tumors from 78 pts linked to clinical data including pathology (22 elements), medical record abstraction including all treatments and timelines/durations (67 elements), and patient-reported data (11 elements). 81% of biopsies included in this release were from the breast and 19% from metastatic sites. 75% were obtained prior to any therapy, 24% following therapy. New data will be released 4/2018 and every six months thereafter, as they are generated. Additional patient-reported data, including treatments, side effects, quality of life, family history, pregnancies, and sites of metastasis, will also be collected and shared. In summary, a patient-driven approach enabled rapid identification of thousands of MBC pts willing to share samples and clinical data. Remote acquisition of medical records, saliva, blood, and tumor tissue for pts across the U.S. is feasible. This shared clinico-genomic database should enable research in MBC and may serve as a model for patient-driven research in other cancers. Citation Format: Nikhil Wagle, Corrie Painter, Elana Anastasio, Michael Dunphy, Mary McGillicuddy, Rachel Stoddard, Esha Jain, Dewey Kim, Simona Di Lascio, Brett N. Tompson, Sara Balch, Beena Thomas, Priti Kumari, Shawn Johnson, Jamie Holloway, Ofir Cohen, Erik H. Knelson, Katie Larkin, Sam Pollock, Alicia Wong, Samira Bahl, Simone Maiwald, Andrew Zimmer, Esme O. Baker, Jen Hendry Lapan, Scott Sutherland, Scott Sassone, Viktor Adalsteinsson, Eric S. Lander, Todd R. Golub. The Metastatic Breast Cancer Project: Partnering with patients to accelerate progress in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5371.

The Metastatic Prostate Cancer project (MPCproject): Translational genomics through direct patient engagement.

Abstract: 279Background: While there has been substantial advancement in the genomic understanding of metastatic prostate cancer (MPC), there is still much to be discovered. Additional progress is dependent upon obtaining a large amount of clinically-annotated genomic data. Therefore, we piloted a direct-to-patient nationwide research initiative where patients can contribute their medical records and biospecimens to accelerate research (mpcproject.org). Methods: In collaboration with patients and advocacy groups, we have developed a website (mpcproject.org). Participants are asked to complete a 17-question survey about their experiences with prostate cancer and an electronic informed consent. All participants receive a saliva kit for germline DNA and blood kit for circulating tumor DNA (ctDNA). Additionally, medical records are collected and archived tissue samples are requested if available. Ultra low pass whole genome sequencing (ULP-WGS) and whole exome sequencing (WES) are performed on the whole blood samples. ...

Abstract PD4-08: A microenvironment secretome screen reveals FGF2 as a mediator of resistance to anti-estrogens and PI3K/mTOR pathway inhibitors in ER+ breast cancer

Abstract: Despite the clinical success of anti-estrogen therapies, phosphatidylinositol 3-kinase inhibitors (PI3Ki), and mechanistic target of rapamycin complex I inhibitors (mTORC1i) for the treatment of patients with ER+ breast cancer, disease recurrence and progression are common. We found that a tumor transcriptional profile reflecting high stromal fibroblast content was associated with poor outcome in 3 cohorts of patients with ER+ breast cancer. We hypothesized that individual factors in the tumor microenvironment (TME) significantly contribute to drug resistance. To test this hypothesis, we screened 297 recombinant secreted proteins for ability to confer resistance to the anti-estrogen fulvestrant in MCF-7 and T47D ER+ breast cancer cells. Screen results were validated, and expansion screening included the anti-estrogen tamoxifen, the PI3Ki pictilisib, and the mTORC1i everolimus in 4 cell lines. To identify hits are most likely to be relevant to ER+ breast cancer, a bioinformatics filter was developed utilizing gene and protein expression in human tissues relevant to the TMEs of ER+ breast cancer. After filtering, the top screening hit was fibroblast growth factor 2 (FGF2), which confers resistance to anti-estrogens, PI3Ki, and mTORC1i, and is highly expressed in tissues and cell types associated with ER+ breast cancer. FGF2 did not rescue cells from the CDK4/6i palbociclib or the DNA-damaging agent doxorubicin, demonstrating pathway selectivity in the rescue phenotype. FGF2 rescued cells from anti-estrogen-, PI3Ki-, and mTORC1i-induced apoptosis and cell cycle arrest via activation of FGFR signaling through FRS2a, MEK1/2, ERK1/2, and downstream upregulation of cyclin D1 and degradation of Bim. FGF2-mediated anti-cancer effects were abrogated by co-treatment with the FGF2-neutralizing antibody GAL-F2, the pan-FGFR inhibitor PD-173074, the MEK inhibitor trametinib, or palbociclib. Cell cycle- and apoptosis-specific effects of FGF2 were abrogated by RNAi targeting cyclin D1 and Bim, respectively. We generated a transcriptional signature of FGF2 response by RNA-seq of fulvestrant-treated MCF-7 and T47D cells treated +/- FGF2. In 3 cohorts of patients with ER+ breast cancer, a signature of FGF2 signaling was significantly associated with poor prognosis and predictive of anti-estrogen resistance, including in a multivariate analysis including age, tumor grade, tumor stage, and FGFR amplification status. Finally, the therapeutic potential of targeting FGF2 was confirmed in 3 mouse models of ER+ breast cancer: 1) FGF2 rescue MCF-7 xenografts from fulvestrant; 2) GAL-F2 synergized with fulvestrant to suppress growth of 59-2-HI murine mammary adenocarcinomas that recruit FGF2-secreting stroma; 3) GAL-F2 synergized with fulvestrant to induce regression of HCI-003 patient-derived xenografts. Therapeutic effects coincided with increased tumor cell apoptosis and decreased proliferation, but not changes in tumor vasculature. These findings warrant consideration of FGF2 as a novel therapeutic target in ER+ breast cancer. Citation Format: Shee K, Hinds JW, Yang W, Hampsch RA, Patel K, Varn FS, Cheng C, Jenkins NP, Kettenbach AN, Demidenko E, Owens P, Lanari C, Faber AC, Golub TR, Straussman R, Miller TW. A microenvironment secretome screen reveals FGF2 as a mediator of resistance to anti-estrogens and PI3K/mTOR pathway inhibitors in ER+ breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD4-08.

Abstract 2352: Defining a pediatric cancer dependency map

Abstract: Many children with metastatic or recurrent pediatric solid tumors continue to have poor survival, and there is an immense need to identify novel therapeutic approaches. Moreover, these cancers typically have simple genomes with limited known druggable molecular events. In order to discover new vulnerabilities in pediatric solid tumors, we have performed genome-scale CRISPR-Cas9 loss-of-function screening and deep “omic” characterization in over 60 pediatric cancer cell lines to date, including neuroblastoma, medulloblastoma, Ewing sarcoma, malignant rhabdoid tumor and rhabdomyosarcoma lines, to begin defining a pediatric cancer dependency map. Global analyses of the pediatric dependency landscape have identified emerging classes of pediatric cancers, including epigenetic-driven, aberrant transcription factor-driven and receptor tyrosine kinase-driven malignancies. For example, the preferential dependencies identified in a subset of neuroblastoma, which has aberrantly high expression of the transcription factor MYCN, are highly enriched for an interconnected network of genes annotated to have transcription factor activity. In addition to the global evaluation, we have developed methods and tools for prioritizing targets for further validation within a cancer type. These tools computationally integrate the pediatric dependency data across multiple datasets to identify categories of genetic dependencies that are especially strong hits or enriched hits in a specific pediatric malignancy. As an example, the intersection of MYCN-amplified neuroblastoma specific dependencies and H3-lysine 27 acetylation (H3K27ac) profiling across MYCN-amplified neuroblastoma allowed us to identify a transcriptional core regulatory circuit (CRC) that may drive the malignant state. Furthermore, targeting transcription with the BRD4 inhibitor JQ1 and CDK7 inhibitor THZ1 caused synergistic killing of neuroblastoma cells suggesting a novel therapeutic approach to treating this disease. Thus, defining a comprehensive pediatric cancer dependency map and developing the methods and tools to prioritize vulnerabilities in different cancer types will allow us to discover both novel biology and new therapeutic opportunities in childhood malignancies. Citation Format: Neekesh V. Dharia, Clare Malone, Amanda Balboni Iniguez, Lillian Guenther, Liying Chen, Gabriela Alexe, Adam D. Durbin, Mark W. Zimmerman, Andrew Hong, Pratiti Bandopadhayay, Mariella G. Filbin, Thomas Howard, Brenton Paolella, Iris Fung, Josephine Lee, Phil Montgomery, John M. Krill-Burger, Brian J. Abraham, Jennifer Roth, David E. Root, Richard A. Young, A. Thomas Look, Rameen Beroukhim, Jesse S. Boehm, William C. Hahn, Todd R. Golub, Aviad Tsherniak, Francisca Vazquez, Kimberly Stegmaier. Defining a pediatric cancer dependency map [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2352.

Abstract 5384: The Angiosarcoma Project: Generating the genomic landscape of an exceedingly rare cancer through a nationwide patient-driven initiative

Abstract: Angiosarcoma (AS) is an exceedingly rare soft tissue sarcoma, with an incidence of 300 cases/yr and a 5-year disease-specific survival of 30%. The low incidence has impeded large-scale research efforts that may lead to improved clinical outcomes. To address this, we launched a nationwide clinical-genomics study in order to empower patients to accelerate research by sharing their normal and tumor samples and clinical information remotely. Patients can access the study through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits. The study team obtains medical records and stored FFPE tumor samples. All received FFPE samples are examined by an expert pathologist to confirm a diagnosis of angiosarcoma. In order to validate that our processes would enable the generation of a robust dataset from tissues acquired from multiple institutions, we sought to characterize previously described genes known to be altered in angiosarcoma (e.g., TP53, NF1, KDR, BRCA2, MET, ARID1A, POT1, BRCA1, ASXL1, KDM6A, BRAF, SETD2, PTPRB, NRAS). A total of 251 patients have enrolled since the project launched in March of 2017. Primary locations of AS are primary breast 59 (25%), breast with prior radiation 45 (19%), head/face/neck/scalp 52 (22%), bone/limb 26 (11%), abdomen 5 (2%), heart 5 (2%), lung 2 (1%), liver 1 (1%), lymph 1 (0.4%), multiple locations 25 (11%), and other locations 12 (5%); 107 (52%) reported being disease free at the time of enrollment. To date, we have received 129 saliva kits, 106 medical records, 19 blood samples, and 36 tissue samples. Whole-exome sequencing (WES) was performed on 21 FFPE/saliva matched pairs with a goal mean target coverage of 150x for tumors. Ultra-low pass whole-genome sequencing (0.1x) was performed on cell free DNA (cfDNA) from plasma in order to determine tumor fraction. Of 10 cfDNA samples sequenced, 4 samples met criteria to perform WES. Additionally, transcriptome sequencing was performed on 9 FFPE samples. Sequence data processing and analysis has been completed on the first 10 samples and is in progress for the subsequent samples. Alterations were detected in genes previously described to be affected in angiosarcoma. Recurrent mutations in TP53 were detected in 50% (5/10) of analyzed samples, comprising 3 missense mutations, 1 frameshift deletion, and 1 frameshift insertion. Alterations were seen in at least one sample in all other genes selected for this initial analysis. This initiative demonstrates the feasibility of studying tissues from geographically dispersed patients and serves as proof of concept that patient-driven genomics efforts can democratize research for exceedingly rare cancers. Enrollment is still in progress, and additional samples will be sequenced and analyzed at scale. The data generated from these studies will be deposited into the public domain in six-month intervals. Citation Format: Michael Dunphy, Esha Jain, Elana Anastasio, Mary McGillicuddy, Rachel Stoddard, Beena Thomas, Sara Balch, Kristin Anderka, Katie Larkin, Niall Lennon, Yen-Lin Chen, Andrew Zimmer, Esme O. Baker, Simone Maiwald, Jen Hendrey Lapan, Jason Hornick, Chandrajit Raut, George Demetri, Eric Lander, Todd Golub, Nikhil Wagle, Corrie Painter. The Angiosarcoma Project: Generating the genomic landscape of an exceedingly rare cancer through a nationwide patient-driven initiative [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5384.

Publisher Correction: Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Abstract: In the version of this article originally published, some text above the “Tri–nucleotide sequence motifs” label in Fig. 2a appeared incorrectly. The text was garbled and should have appeared as nucleotide codes. Additionally, the labels on the bars in Fig. 2c were not italicized in the original publication. These are gene symbols, and they should have been italicized. The colored labels above the graphs in Fig. 4b were also erroneously not italicized. These labels represent gene names and loci, and they should have been italicized.

Compounds and methods useful for treating or preventing cancers

Abstract: The present invention includes CSNK1A1 inhibitors that are useful in treating or preventing a cancer in a subject. In certain embodiments, the cancer comprises a hematological cancer, such as but not limited to acute myeloid leukemia (AML) and/or MDS (myelodysplastic syndrome, including 5q-MDS). In other embodiments, the cancer comprises colon cancer.