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S1. Schematic diagram of NSD2 isoform indicating domains, the location of amino acid E1099 within the SET domain, and the targets of the shRNAs. S2. NSD2 Overexpression in B-ALL Cell Lines Does Not Impart Clonal Advantage. S3. Overexpression of REIIBP in B-ALL Cell Lines Does Not Impart Clonal Advantage. S4. Knockdown of WT NSD2 in B-ALL Cell Lines Does Not Lead to Phenotypic Differences. S5. Knockdown of NSD2 in RS4;11 and RCH-ACV lines leads to increased chemosensitivity. S6. Sensitivity to 6-MP Upon Knockdown of NSD2 in RS4;11 is Not Depedent of Level of Knockdown. S7. Knockdown of NSD2 in WT B-ALL Cell Lines Does Not Lead to Increased Sensitivity. S8. NSD2 WT and EK Overexpression in B-ALL Cell Lines Leads to Distinct Genetic Signature Unique to Each Cell Line. S9. NSD2 WT and EK Overexpression in B-ALL Cell Lines Leads to Distinct Epigenetic Signature Resulting in Gene Expression Changes. S10. NSD2 Knockdown in Mutant B-ALL Cell Lines Leads to Distinct Genetic Signature Unique to Each Cell Line. S11. ATAC peaks significantly correlate with gene expression for RS4;11 and RCH-ACV cell lines.

The BCL2 family plays important roles in acute myeloid leukemia (AML). Venetoclax, a selective BCL2 inhibitor, has received FDA approval for the treatment of AML. However, drug resistance ensues after prolonged treatment, highlighting the need for a greater understanding of the underlying mechanisms. Using a genome-wide CRISPR/Cas9 screen in human AML, we identified genes whose inactivation sensitizes AML blasts to venetoclax. Genes involved in mitochondrial organization and function were significantly depleted throughout our screen, including the mitochondrial chaperonin CLPB. We demonstrated that CLPB is upregulated in human AML, it is further induced upon acquisition of venetoclax resistance, and its ablation sensitizes AML to venetoclax. Mechanistically, CLPB maintains the mitochondrial cristae structure via its interaction with the cristae-shaping protein OPA1, whereas its loss promotes apoptosis by inducing cristae remodeling and mitochondrial stress responses. Overall, our data suggest that targeting mitochondrial architecture may provide a promising approach to circumvent venetoclax resistance.Significance:A genome-wide CRISPR/Cas9 screen reveals genes involved in mitochondrial biological processes participate in the acquisition of venetoclax resistance. Loss of the mitochondrial protein CLPB leads to structural and functional defects of mitochondria, hence sensitizing AML cells to apoptosis. Targeting CLPB synergizes with venetoclax and the venetoclax/azacitidine combination in AML in a p53-independent manner.See related commentary by Savona and Rathmell, p. 831.This article is highlighted in the In This Issue feature, p. 813

Cell line IC50 values

sgRNA guide sequences, shRNA sequences and qPCR primers used in this study

Raw counts and gene-based CRISPR score analysis of the genome wide CRIPR/Cas9 loss-of-function screen

Relative quantification of metabolites in the hybrid panel in CLPB knockout MOLM-13

Supplementary Tables and Methods

Supplementary Figures and Figure Legends

Supplementary materials and methods and supplementary figure legends.

CLPB interacting mitochondrial proteins in AML

This paper aims at identifying key determinants, which influence and motivates households to wash hand on a regular basis with soap and water before taking meal and after open defecation in urban Uttar Pradesh using household-level 76th round NSSO data (July-December 2018). Binary logistic regression model results show households those are having access to safe and sufficient water throughout the year are also more likely to wash their hands compare to those households that don’t have access to water. Therefore, increasing investment in WASH services would act as an important mechanism to mitigate the secondary effects of Covid-19 in communities.

The NSD2 p.E1099K (EK) mutation has been shown to be enriched in patients with relapsed ALL and found to play a role in clonal fitness dependent on the underlying genetic/epigenetic landscape of the cells. To uncover 3D chromatin architecture-related mechanisms underlying drug resistance, we systematically integrated Hi-C, ATAC-seq, RNA-seq and ChIP-seq data from three B-ALL cell lines heterozygous for NSD2 EK (RS4;11, RCH-ACV, SEM) and assessed changes upon knockdown. NSD2 knockdown revealed widespread remodeling of the 3D genome, specifically in terms of compartmentalization. Systematic integration of these datasets revealed significant switches in A/B compartments with a strong bias towards B compartments upon knockdown, suggesting that NSD2 EK plays a prominent role in maintaining A compartments through enrichment of H3K36me2 epigenetic marks. In contrast, we identified few changes in intra-TAD activity suggesting that the NSD2 EK impacts transcriptional changes through a remarkable dependence on compartmentalization. Furthermore, EK-mediated reorganization of compartments highlights the existence of a common core of compacting loci shared across the three cell lines that explain previously described phenotypes as well as serve as targets for therapeutic intervention. This study offers a novel mechanism by which NSD2 EK drives clonal evolution and drug resistance.

ARID2 is the most recurrently mutated SWI/SNF complex member in melanoma; however, its tumor-suppressive mechanisms in the context of the chromatin landscape remain to be elucidated. Here, we model ARID2 deficiency in melanoma cells, which results in defective PBAF complex assembly with a concomitant genomic redistribution of the BAF complex. Upon ARID2 depletion, a subset of PBAF and shared BAF-PBAF-occupied regions displays diminished chromatin accessibility and associated gene expression, while BAF-occupied enhancers gain chromatin accessibility and expression of genes linked to the process of invasion. As a function of altered accessibility, the genomic occupancy of melanoma-relevant transcription factors is affected and significantly correlates with the observed transcriptional changes. We further demonstrate that ARID2-deficient cells acquire the ability to colonize distal organs in multiple animal models. Taken together, our results reveal a role for ARID2 in mediating BAF and PBAF subcomplex chromatin dynamics with consequences for melanoma metastasis.

Summary: A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies. : Sakellaropoulos et al. designed a machine learning workflow to predict drug response and survival of cancer patients. All pipelines are trained on a large panel of cancer cell lines and tested in clinical cohorts. DNN outperforms other machine learning algorithms by capturing pathways that link gene expression with drug response. Keywords: drug response prediction, precision medicine, machine learning, deep neural networks, DNN

Although B-cell acute lymphoblastic leukemia (B-ALL) is the most common malignancy in children and while highly curable, it remains a leading cause of cancer-related mortality. The outgrowth of tumor subclones carrying mutations in genes responsible for resistance to therapy has led to a Darwinian model of clonal selection. Previous work has indicated that alterations in the epigenome might contribute to clonal selection, yet the extent to which the chromatin state is altered under the selective pressures of therapy is unknown. To address this, we performed chromatin immunoprecipitation, gene expression analysis, and enhanced reduced representation bisulfite sequencing on a cohort of paired diagnosis and relapse samples from individual patients who all but one relapsed within 36 months of initial diagnosis. The chromatin state at diagnosis varied widely among patients, while the majority of peaks remained stable between diagnosis and relapse. Yet a significant fraction was either lost or newly gained, with some patients showing few differences and others showing massive changes of the epigenetic state. Evolution of the epigenome was associated with pathways previously linked to therapy resistance as well as novel candidate pathways through alterations in pyrimidine biosynthesis and downregulation of polycomb repressive complex 2 targets. Three novel, relapse-specific superenhancers were shared by a majority of patients including one associated with S100A8, the top upregulated gene seen at relapse in childhood B-ALL. Overall, our results support a role of the epigenome in clonal evolution and uncover new candidate pathways associated with relapse. Significance: This study suggests a major role for epigenetic mechanisms in driving clonal evolution in B-ALL and identifies novel pathways associated with drug resistance.

Planar cell polarity (PCP) and neural tube defects (NTDs) are linked, with a subset of NTD patients found to harbor mutations in PCP genes, but there is limited data on whether these mutations disrupt PCP signaling in vivo. The core PCP geneVan Gogh(Vang),Vangl1/2 in mammals, is the most specific for PCP. We thus addressed potential causality of NTD-associatedVangl1/2 mutations, from either mouse or human patients, inDrosophilaallowing intricate analysis of the PCP pathway. Introducing the respective mammalian mutations intoDrosophila Vangrevealed defective phenotypic and functional behaviors, with changes to Vang localization, post-translational modification, and mechanistic function, such as its ability to interact with PCP effectors. Our findings provide mechanistic insight into how different mammalian mutations contribute to developmental disorders and strengthen the link between PCP and NTD. Importantly, analyses of the human mutations revealed that each is a causative factor for the associated NTD.

Lack of cellular differentiation is a hallmark of many human cancers, including acute myeloid leukemia (AML). Strategies to overcome such a differentiation blockade are an approach for treating AML. To identify targets for differentiation-based therapies, we applied an integrated cell surface-based CRISPR platform to assess genes involved in maintaining the undifferentiated state of leukemia cells. Here we identify the RNA-binding protein ZFP36L2 as a critical regulator of AML maintenance and differentiation. Mechanistically, ZFP36L2 interacts with the 3' untranslated region of key myeloid maturation genes, including the ZFP36 paralogs, to promote their mRNA degradation and suppress terminal myeloid cell differentiation. Genetic inhibition of ZFP36L2 restores the mRNA stability of these targeted transcripts and ultimately triggers myeloid differentiation in leukemia cells. Epigenome profiling of several individuals with primary AML revealed enhancer modules near ZFP36L2 that associated with distinct AML cell states, establishing a coordinated epigenetic and post-transcriptional mechanism that shapes leukemic differentiation.

The NSD2 p.E1099K (EK) mutation is observed in 10% of acute lymphoblastic leukemia (ALL) samples with enrichment at relapse indicating a role in clonal evolution and drug resistance. To discover mechanisms that mediate clonal expansion, we engineered B-precursor ALL (B-ALL) cell lines (Reh, 697) to overexpress wildtype (WT) and EK NSD2, but observed no differences in proliferation, clonal growth, or chemosensitivity. To address whether NSD2 EK acts collaboratively with other pathways, we used short hairpin RNAs to knockdown expression of NSD2 in B-ALL cell lines heterozygous for NSD2 EK (RS4;11, RCH-ACV, SEM). Knockdown resulted in decreased proliferation in all lines, decreased clonal growth in RCH-ACV, and increased sensitivity to cytotoxic chemotherapeutic agents, although the pattern of drug sensitivity varied among cell lines implying that the oncogenic properties of NSD2 mutations are likely cell context specific and rely on cooperative pathways. Knockdown of both Type II and REIIBP EK isoforms had a greater impact than knockdown of Type II alone, suggesting that both SET containing EK isoforms contribute to phenotypic changes driving relapse. Furthermore, in vivo models using both cell lines and patient samples revealed dramatically enhanced proliferation of NSD2 EK compared with WT and reduced sensitivity to 6-mercaptopurine in the relapse sample relative to diagnosis. Finally, EK-mediated changes in chromatin state and transcriptional output differed dramatically among cell lines further supporting a cell context–specific role of NSD2 EK. These results demonstrate a unique role of NSD2 EK in mediating clonal fitness through pleiotropic mechanisms dependent on the genetic and epigenetic landscape. Implications: NSD2 EK mutation leads to drug resistance and a clonal advantage in childhood B-ALL.

Relapse-enriched somatic variants drive drug resistance in childhood acute lymphoblastic leukemia. We used digital droplet-based polymerase chain reaction to establish whether relapse-enriched mutations in emerging subclones could be detected in peripheral blood samples before frank relapse. Although limitations in sensitivity for some probes hindered detection of certain variants, we successfully detected variants in NT5C2 and PRPS1 at a fractional abundance of 0.005% to 0.3%, 41 to 116 days before relapse. As mutations in both these genes confer resistance to thiopurines, early detection protocols using peripheral blood could be implemented to preemptively alter maintenance therapy to extinguish resistant clones before overt relapse.

Planar cell polarity (PCP) and neural tube defects (NTDs) are linked, with a subset of NTD patients found to harbor mutations in PCP genes, but there is limited data on whether these mutations disrupt PCP signaling in vivo. The core PCP gene Van Gogh (Vang), Vangl1/2 in mammals, is the most specific for PCP. We thus addressed potential causality of NTD-associated Vangl1/2 mutations, from either mouse or human patients, in Drosophila allowing intricate analysis of the PCP pathway. Introducing the respective mammalian mutations into Drosophila Vang revealed defective phenotypic and functional behaviors, with changes to Vang localization, post-translational modification, and mechanistic function, such as its ability to interact with PCP effectors. Our findings provide mechanistic insight into how different mammalian mutations contribute to developmental disorders and strengthen the link between PCP and NTD. Importantly, analyses of the human mutations revealed that each is a causative factor for the associated NTD., eLife digest As an embryo develops, its cells must work together to build mature tissues and organs. During the formation of the nervous system, for example, a sheet of cells destined to become the brain and spinal cord folds up into a tube spanning the length of the embryo. Normally, this tube – known as the ‘neural tube’ – zips up, and the cells that will eventually become skin and other surrounding tissues close in over it. If the neural tube does not close completely, different parts of the spinal cord or brain can remain unprotected. This can cause diseases called neural tube defects, such as spina bifida, which is characterized by holes in the backbone exposing the spinal cord and surrounding membranes. Patients with neural tube defects can have similar genetic mutations, for example, in the genes controlling a process called “planar cell polarity”, or PCP for short. Cells arranged in flat sheets use the PCP process to sense direction, and it is this process that allows structures, such as the scales on a fish or the hairs on a mouse, to all point in the same direction. PCP is also important in embryonic development: sheets of cells that can sense direction correctly can therefore move collectively to complete complex tasks (such as closing the neural tube). However, no-one knew whether the specific PCP gene mutations implicated in neural tube defects in humans actually affected the cells’ ability to sense direction, or indeed whether they were even involved in causing the diseases. Humphries et al. set out to find out more about these mutations using fruit flies as a model system. The fruit fly is widely used to study the genes and signals involved in direction sensing, especially PCP. Problems with PCP produce easily measurable changes in the wing and eye, showing what went wrong and how badly. Humphries et al. genetically engineered fruit flies to have the same mutations as human patients and revealed that these mutations did indeed alter cells’ ability to sense direction. These experiments also showed that each mutation did so in a different way, and with varying severity. This explained why the same mutations caused different levels of neural defects in mice (which are commonly used to study human diseases) and suggests that they might contribute to neural tube disorders in humans. These results show potential connections between neural tube defects and direction sensing in cells. In the future, this study and follow-up work could help researchers to understand what types of mutation have the most impact, which may eventually allow doctors to better predict who is most at risk of being affected by these conditions.

Although genetic alterations are initial drivers of disease, aberrantly activated transcriptional regulatory programs are often responsible for the maintenance and progression of cancer. CRLF2-overexpression in B-ALL patients leads to activation of JAK-STAT, PI3K and ERK/MAPK signaling pathways and is associated with poor outcome. Although inhibitors of these pathways are available, there remains the issue of treatment-associated toxicities, thus it is important to identify new therapeutic targets. Using a network inference approach, we reconstructed a B-ALL specific transcriptional regulatory network to evaluate the impact of CRLF2-overexpression on downstream regulatory interactions.Comparing RNA-seq from CRLF2-High and other B-ALL patients (CRLF2-Low), we defined a CRLF2-High gene signature. Patient-specific chromatin accessibility was interrogated to identify altered putative regulatory elements that could be linked to transcriptional changes. To delineate these regulatory interactions, a B-ALL cancer-specific regulatory network was inferred using 868 B-ALL patient samples from the NCI TARGET database coupled with priors generated from ATAC-seq peak TF-motif analysis. CRISPRi, siRNA knockdown and ChIP-seq of nine TFs involved in the inferred network were analyzed to validate predicted TF-gene regulatory interactions.In this study, a B-ALL specific regulatory network was constructed using ATAC-seq derived priors. Inferred interactions were used to identify differential patient-specific transcription factor activities predicted to control CRLF2-High deregulated genes, thereby enabling identification of new potential therapeutic targets.

A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into effective drug-response models. Machine learning is both an expanding and an evolving computational field that holds promise to cover such needs. Here we provide a focused overview of: 1) the various supervised and unsupervised algorithms used specifically in drug response prediction applications, 2) the strategies employed to develop these algorithms into applicable models, 3) data resources that are fed into these frameworks and 4) pitfalls and challenges to maximize model performance. In this context we also describe a novel in silico screening process, based on Association Rule Mining, for identifying genes as candidate drivers of drug response and compare it with relevant data mining frameworks, for which we generated a web application freely available at: https://compbio.nyumc.org/drugs/. This pipeline explores with high efficiency large sample-spaces, while is able to detect low frequency events and evaluate statistical significance even in the multidimensional space, presenting the results in the form of easily interpretable rules. We conclude with future prospects and challenges of applying machine learning based drug response prediction in precision medicine.

The BCL2 family plays important roles in acute myeloid leukemia (AML). Venetoclax, a selective BCL2 inhibitor, has received FDA approval for the treatment of AML. However, drug resistance ensues after prolonged treatment, highlighting the need for a greater understanding of the underlying mechanisms. Using a genome-wide CRISPR/Cas9 screen in human AML, we identified genes whose inactivation sensitizes AML blasts to venetoclax. Genes involved in mitochondrial organization and function were significantly depleted throughout our screen, including the mitochondrial chaperonin CLPB. We demonstrated that CLPB is upregulated in human AML, it is further induced upon acquisition of venetoclax resistance, and its ablation sensitizes AML to venetoclax. Mechanistically, CLPB maintains the mitochondrial cristae structure via its interaction with the cristae-shaping protein OPA1, whereas its loss promotes apoptosis by inducing cristae remodeling and mitochondrial stress responses. Overall, our data suggest that targeting mitochondrial architecture may provide a promising approach to circumvent venetoclax resistance. Significance: A genome-wide CRISPR/Cas9 screen reveals genes involved in mitochondrial biological processes participate in the acquisition of venetoclax resistance. Loss of the mitochondrial protein CLPB leads to structural and functional defects of mitochondria, hence sensitizing AML cells to apoptosis. Targeting CLPB synergizes with venetoclax and the venetoclax/azacitidine combination in AML in a p53-independent manner. See related commentary by Savona and Rathmell, p. 831. This article is highlighted in the In This Issue feature, p. 813

Introduction: Outcomes for children with relapsed acute lymphoblastic leukemia (ALL) remain poor. Mutations in epigenetic modifiers are commonly found at relapse, including the activating p.E1099K (EK) mutation within the conserved SET domain of NSD2, which has been reported in 10% of patients at relapse. NSD2 has 3 isoforms, two of which (Types II and REIIBP) contain the SET domain. Our aim was to determine the role of NSD2 in driving relapse and further elucidate the prevalence of NSD2 EK in patient samples. Methods: Whole genome/exome sequencing was performed on diagnosis/relapse ALL pairs and data were aggregated for somatic SNVs/indels. NSD2 EK positive cases at relapse were subject to ultra-deep targeted re-sequencing to determine the presence of small subclones at diagnosis. To investigate the role of NSD2 and its isoforms in mediating relapse, short hairpin RNAs (shRNAs) were used to knockdown (KD) NSD2 in three NSD2 EK mutant cell lines with non-targeting (NT) shRNA used as controls. Cells were treated with chemotherapy commonly used in pediatric ALL and assessed for cytotoxicity by CellTiter- Glo®. To determine NSD2's impact on gene expression and the epigenetic landscape, RNAseq, ChIPseq, ATACseq, and Hi-C were performed using standard techniques. Results: Examination of paired ALL patient samples revealed enrichment of NSD2 EK clones at relapse. B-ALL cell lines heterozygous for NSD2 EK (RS4;11, RCH-ACV, SEM) revealed that KD led to decreased proliferation in all lines and decreased clonal growth in RCH-ACV relative to NT. Furthermore, increased sensitivity to various chemotherapeutic agents was observed in the KD lines compared to NT controls, but the pattern of drug sensitivity varied among lines implying cell context specific drug responses. Simultaneous knockdown of Type II and REIIBP had a greater impact than Type II alone, indicating both SET containing EK isoforms contribute to phenotypic changes. When comparing gene expression changes in NT vs KD, minimal overlap in differential genes was noted among the three cell lines (4.4% upregulated, 1.7% downregulated) indicating significant diversity in transcriptional reprogramming. ATACseq of the NT and KD for all three lines revealed intergenic regions as the most affected by NSD2 with RCH-ACV and RS4;11 NT lines having more open chromatin compared to their KD whereas SEM NT displayed marked peak loss compared to its KD. Less than 2% of differential intergenic regions were shared among the lines. Hi-C analysis demonstrated disparity in chromosome architecture among NSD2 EK lines as well. Shifts in intergenic regions was further supported by ChIPseq, which revealed increased H3K36me2 across intergenic regions in RS4;11 NT compared to KD. Lastly, we noted a strong correlation of increased gene expression with increased H3K36me2, H3K9ac, and H3K27ac at promoters and gene bodies. Conclusions: NSD2 EK plays a unique role in mediating clonal fitness through pleiotropic mechanisms that are dependent on the underlying cellular context. Citation Format: Joanna Pierro, Jason Saliba, Sonali Narang, Gunjan Sethia, Shella Saint Fleur-Lominy, Ashfiyah Chowdhury, Takaya Moriyama, Kjeld Schmiegelow, Jun J. Yang, Mignon L. Loh, Patrick A. Brown, Jinghui Zhang, Xiaotu Ma, Aristotelis Tsirigos, Nikki A. Evensen, William L. Carroll. The NSD2 p.E1099K mutation is enriched at relapse and confers drug resistance in a cell context dependent manner in pediatric acute lymphoblastic leukemia [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 5399.

Defining therapeutically “vulnerable” genes that modulate anti-cancer drug response is of paramount importance in precision cancer treatment. The success of such a task largely depends on the ability to develop computational resources that integrate big “omic” data into effective drug-response models. Herein, based on the pharmacogenomic profile of 1,001 cancer cell lines we constructed a novel in silico screening process based on Association Rule Mining for identifying genes as candidate drivers of drug response. Our computational pipeline explores with high efficiency large sample-spaces, is able to detect low frequency events and evaluate statistical significance even in the multidimensional space, presenting the results in the form of easily interpretable rules. The selection algorithm was validated by in silico and experimental means. Within this context, we identified experimentally novel targets related with responsiveness to: i) Doxorubicin treatment, and ii) MAPK and PI3K inhibitor administration. The presented data mining scheme provides evidence for potential practical applications and a proof-of-concept for the implementation of precision medicine in everyday clinical practice.