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
(
),
/2 in mammals, is the most specific for PCP. We thus addressed potential causality of NTD-associated
/2 mutations, from either mouse or human patients, in
allowing intricate analysis of the PCP pathway. Introducing the respective mammalian mutations into
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.
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.
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•A machine learning (ML) workflow is designed to predict drug response in cancer patients•Deep neural networks (DNNs) surpass current ML algorithms in drug response prediction•DNNs predict drug response and survival in various large clinical cohorts•DNNs capture intricate biological interactions linked to specific drug response pathways
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.
The NSD2 p.E1099K (EK) mutation is shown to be enriched in patients with relapsed acute lymphoblastic leukemia (ALL), indicating a role in clonal evolution and drug resistance.
To uncover 3D ...chromatin architecture-related mechanisms underlying drug resistance, we perform Hi-C on three B-ALL cell lines heterozygous for NSD2 EK. The NSD2 mutation leads to widespread remodeling of the 3D genome, most dramatically in terms of compartment changes with a strong bias towards A compartment shifts. Systematic integration of the Hi-C data with previously published ATAC-seq, RNA-seq, and ChIP-seq data show an expansion in H3K36me2 and a shrinkage in H3K27me3 within A compartments as well as increased gene expression and chromatin accessibility. These results suggest that NSD2 EK plays a prominent role in chromatin decompaction through enrichment of H3K36me2. In contrast, we identify few changes in intra-topologically associating domain activity. While compartment changes vary across cell lines, a common core of decompacting loci are shared, driving the expression of genes/pathways previously implicated in drug resistance. We further perform RNA sequencing on a cohort of matched diagnosis/relapse ALL patients harboring the relapse-specific NSD2 EK mutation. Changes in patient gene expression upon relapse significantly correlate with core compartment changes, further implicating the role of NSD2 EK in genome decompaction.
In spite of cell-context-dependent changes mediated by EK, there appears to be a shared transcriptional program dependent on compartment shifts which could explain phenotypic differences across EK cell lines. This core program is an attractive target for therapeutic intervention.
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.
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•ARID2 loss results in impaired PBAF complex assembly and BAF genomic redistribution•Altered SWI/SNF dynamics results in chromatin accessibility and TF binding changes•PBAF loss drives an invasive gene expression signature and phenotype in melanoma
The tumor-suppressive functions of the SWI/SNF subunit ARID2 remain ill-defined in the context of melanoma. Carcamo et al. demonstrate that, upon ARID2 depletion, the PBAF complex fails to assemble, altering BAF genomic occupancy with consequences on chromatin accessibility, transcription factor binding, and transcriptional changes that promote metastasis.
Relapsed pediatric B-cell acute lymphoblastic leukemia (B-ALL) remains one of the leading causes of cancer mortality in children. While five-year survival rates for newly diagnosed pediatric B-ALL ...have improved and now exceed 90%, up to 20% of patients will suffer relapse and face a dismal prognosis. Although recent therapeutic approaches to treating relapsed B-ALL seem encouraging, leukemia sub-clones continue to emerge through the selective pressures of therapy. Therefore, investigating the mechanisms responsible for cancer recurrence and therapy resistance is crucial for preventing and treating B-ALL relapse. Previous studies characterizing the genetic, epigenetic, and transcriptional landscapes of relapsed B-ALL have been enormously productive in yielding fundamental insights into cancer biology and novel therapeutic targets; however, recent studies suggest that an additional critical level of control is connected to the 3D structure of chromosomes. Thus far, no one has investigated B-ALL relapse through the lens of 3D chromatin organization. Here, we uncover 3D chromatin architecture-related mechanisms underlying drug resistance in relapsed B-ALL.In Chapter 1, we investigate the role 3D genome organization plays in the NSD2 EK-mediated relapse by assessing NSD2 High and NSD2 Low cell lines and patient samples. We identify a link between NSD2 EK mediated epigenetic changes and dysregulation of higher-order genomic architecture in B-ALL. Our study revealed NSD2 EK’s prominent role in chromatin decompaction through enrichment of H3K36me2 epigenetic marks. We also demonstrated NSD2 EK’s remarkable reliance on compartment reorganization over TAD activity. Despite transcriptional and chromatin accessibility heterogeneity across the three cell lines, this study highlights the existence of a common core of compacting loci that can explain previously described universal features, such as proliferation, as well as serve as targets for therapeutic intervention. Ultimately, this study offers a novel mechanism by which NSD2 EK drives ALL relapse through chromatin decompaction allowing for transcriptional reprogramming in response to selective pressures associated with treatment.In Chapter 2, we investigate the dynamics of 3D chromatin architecture in B-ALL progression by assessing 12 matched primary pediatric leukemia specimens at diagnosis and relapse. We demonstrate 3D genome organization as a critical lever of control in relapsed pediatric B-ALL through a novel cohort of matched diagnosis-relapse primary patient samples. Robust SV analysis with Hi-C data from diagnosis and relapse samples revealed various previously unidentified shared, diagnosis-specific, and relapse-specific translocations providing strong evidence for clonal evolution as a mechanism for drug resistance in B-ALL. Moreover, we identify recurrent genome wide changes in both compartments and TAD interactivity such as the MN1, ATXN1, and PCDH9 loci, indicating the convergence of selective pressures of therapy. Lastly, enrichment analysis at ATAC-seq peak anchored loops offers some insight into the key upstream regulators of 3D genome architecture in B-ALL disease progression. We characterize the 3D genomic landscape of B-ALL as well as uncover various avenues of therapeutic intervention. Overall, this study extends the landscape of genetic alterations in relapsed B-ALL through the addition of the 3D genomic landscape as well as uncovers a breadth of novel avenues of therapeutic intervention.
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.
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•Cell surface antigen-based CRISPR screens reveal regulators of AML differentiation•ZFP36L2 is required for leukemia differentiation across molecular subtypes of AML•ZFP36L2 interacts with the 3′ UTR of myeloid maturation mRNAs•Enhancer landscape nearby ZFP36L2 modulates the differentiated state of AML cells
Wang et al. performed a surface antigen-guided CRISPR screen approach to uncover genes that maintain AML differentiation and ZFP36L2 as an mRNA decay factor that deadenylates mRNAs that are involved in myeloid differentiation. Genetic inhibition of ZFP36L2 promotes AML cells to undergo terminal myeloid differentiation and impairs leukemia survival.
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.
Mutations in genes encoding epigenetic regulators are commonly observed at relapse in B cell acute lymphoblastic leukemia (B-ALL). Loss-of-function mutations in SETD2, an H3K36 methyltransferase, ...have been observed in B-ALL and other cancers. Previous studies on mutated SETD2 in solid tumors and acute myelogenous leukemia support a role in promoting resistance to DNA damaging agents. We did not observe chemoresistance, an impaired DNA damage response, nor increased mutation frequency in response to thiopurines using CRISPR-mediated knockout in wild-type B-ALL cell lines. Likewise, restoration of SETD2 in cell lines with hemizygous mutations did not increase sensitivity.
mutations affected the chromatin landscape and transcriptional output that was unique to each cell line. Collectively our data does not support a role for
mutations in driving clonal evolution and relapse in B-ALL, which is consistent with the lack of enrichment of
mutations at relapse in most studies.
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