Chromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies.

T cell acute lymphoblastic leukemia (T-ALL) is an immature hematopoietic malignancy driven mainly by oncogenic activation of NOTCH1 signaling. In this study we report the presence of loss-of-function mutations and deletions of the EZH2 and SUZ12 genes, which encode crucial components of the Polycomb repressive complex 2 (PRC2), in 25% of T-ALLs. To further study the role of PRC2 in T-ALL, we used NOTCH1-dependent mouse models of the disease, as well as human T-ALL samples, and combined locus-specific and global analysis of NOTCH1-driven epigenetic changes. These studies demonstrated that activation of NOTCH1 specifically induces loss of the repressive mark Lys27 trimethylation of histone 3 (H3K27me3) by antagonizing the activity of PRC2. These studies suggest a tumor suppressor role for PRC2 in human leukemia and suggest a hitherto unrecognized dynamic interplay between oncogenic NOTCH1 and PRC2 function for the regulation of gene expression and cell transformation.

Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTP), a subpopulation of cancer cells that survive via reversible, nongenetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKI) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome. Lentiviral barcoding/single-cell RNA sequencing reveals that HER2+ breast cancer cells cycle stochastically through a "pre-DTP" state, characterized by a G0-like expression signature and enriched for diapause and/or senescence genes. Trajectory analysis/cell sorting shows that pre-DTPs preferentially yield DTPs upon HER2 TKI exposure. Cells with similar transcriptomes are present in HER2+ breast tumors and are associated with poor TKI response. Finally, biochemical experiments indicate that luminal-like DTPs survive via estrogen receptor-dependent induction of SGK3, leading to rewiring of the PI3K/AKT/mTORC1 pathway to enable AKT-independent mTORC1 activation.

Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric patients with AML. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B-cell subtype enriched in patients with high-inflammation AML, as well as an increase in CD8+GZMK+ and regulatory T cells, accompanied by a reduction in T-cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in patients with AML. Addition of the iScore refines current risk stratifications for patients with AML and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying patients with AML based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.

Clonal hematopoiesis (CH) is an aging-associated condition characterized by the clonal outgrowth of mutated preleukemic cells. Individuals with CH are at an increased risk of developing hematopoietic malignancies. Here, we describe a novel animal model carrying a recurrent TET2 missense mutation frequently found in patients with CH and leukemia. In a fashion similar to CH, animals show signs of disease late in life when they develop a wide range of myeloid neoplasms, including acute myeloid leukemia (AML). Using single-cell transcriptomic profiling of the bone marrow, we show that disease progression in aged animals correlates with an enhanced inflammatory response and the emergence of an aberrant inflammatory monocytic cell population. The gene signature characteristic of this inflammatory population is associated with poor prognosis in patients with AML. Our study illustrates an example of collaboration between a genetic lesion found in CH and inflammation, leading to transformation and the establishment of blood neoplasms.

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.

Isocitrate dehydrogenase (IDH)-mutant glioma is a distinct glioma molecular subtype for which no effective molecularly directed therapy exists. Low-grade gliomas, which are 80%-90% IDH-mutant, have high RNA levels of the cell surface Notch ligand DLL3. We sought to determine DLL3 expression by IHC in glioma molecular subtypes and the potential efficacy of an anti-DLL3 antibody-drug conjugate (ADC), rovalpituzumab tesirine (Rova-T), in IDH-mutant glioma.

Maintenance of stem cell plasticity is determined by the ability to balance opposing forces that control gene expression. Regulation of transcriptional networks, signaling cues and chromatin-modifying mechanisms constitute crucial determinants of tissue equilibrium. Histone modifications can affect chromatin compaction, therefore co-transcriptional events that influence their deposition determine the propensities toward quiescence, self-renewal, or cell specification. The Paf1 complex (Paf1C) is a critical regulator of RNA PolII elongation that controls gene expression and deposition of histone modifications, however few studies have focused on its role affecting stem cell fate decisions. Here we delineate the functions of Paf1C in pluripotency and characterize its impact in deposition of H2B ubiquitylation (H2BK120-ub) and H3K79 methylation (H3K79me), 2 fundamental histone marks that shape transcriptional regulation. We identify that H2BK120-ub is increased in the absence of Paf1C on its embryonic stem cell targets, in sharp contrast to H3K79me, suggesting opposite functions in the maintenance of self-renewal. Furthermore, we found that core pluripotency genes are characterized by a dual gain of H2BK120-ub and loss of H3K79me on their gene bodies. Our findings elucidate molecular mechanisms of cellular adaptation and reveal novel functions of Paf1C in the regulation of the self-renewal network.

We report here an update to the draft genome sequence of Kluyvera intestini sp. nov. strain GT-16, generated using MinION long-read sequencing technology. The complete genome sequence of the human-derived strain GT-16 measured 5,768,848 bp. An improved high-quality complete genome sequence provides insights into the mobility potential of resistance genes in this species.

Low-grade astrocytomas (LGAs) carry neomorphic mutations in isocitrate dehydrogenase (IDH) concurrently with P53 and ATRX loss. To model LGA formation, we introduced R132H IDH1, P53 shRNA, and ATRX shRNA into human neural stem cells (NSCs). These oncogenic hits blocked NSC differentiation, increased invasiveness in vivo, and led to a DNA methylation and transcriptional profile resembling IDH1 mutant human LGAs. The differentiation block was caused by transcriptional silencing of the transcription factor SOX2 secondary to disassociation of its promoter from a putative enhancer. This occurred because of reduced binding of the chromatin organizer CTCF to its DNA motifs and disrupted chromatin looping. Our human model of IDH mutant LGA formation implicates impaired NSC differentiation because of repression of SOX2 as an early driver of gliomagenesis.

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.

Loss of β cell identity, the presence of polyhormonal cells, and reprogramming are emerging as important features of β cell dysfunction in patients with type 1 and type 2 diabetes. In this study, we have demonstrated that the transcription factor NKX2.2 is essential for the active maintenance of adult β cell identity as well as function. Deletion of Nkx2.2 in β cells caused rapid onset of a diabetic phenotype in mice that was attributed to loss of insulin and downregulation of many β cell functional genes. Concomitantly, NKX2.2-deficient murine β cells acquired non-β cell endocrine features, resulting in populations of completely reprogrammed cells and bihormonal cells that displayed hybrid endocrine cell morphological characteristics. Molecular analysis in mouse and human islets revealed that NKX2.2 is a conserved master regulatory protein that controls the acquisition and maintenance of a functional, monohormonal β cell identity by directly activating critical β cell genes and actively repressing genes that specify the alternative islet endocrine cell lineages. This study demonstrates the highly volatile nature of the β cell, indicating that acquiring and sustaining β cell identity and function requires not only active maintaining of the expression of genes involved in β cell function, but also continual repression of closely related endocrine gene programs.

Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI response in advanced melanoma.

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.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing whole-slide images for predicting mutated BRAF. In the first method, whole-slide images of melanomas from 256 patients were used to train a deep convolutional neural network to develop a fully automated model that first selects for tumor-rich areas (area under the curve = 0.96) and then predicts for mutated BRAF (area under the curve = 0.71). Saliency mapping was performed and revealed that pixels corresponding to nuclei were the most relevant to network learning. In the second method, whole-slide images were analyzed using a pathomics pipeline that first annotates nuclei and then quantifies nuclear features, showing that mutated BRAF nuclei were significantly larger and rounder than BRAF‒wild-type nuclei. Finally, we developed a model that combines clinical information, deep learning, and pathomics that improves the predictive performance for mutated BRAF to an area under the curve of 0.89. Not only does this provide additional insights on how BRAF mutations affect tumor structural characteristics, but machine learning‒based analysis of whole-slide images also has the potential to be integrated into higher-order models for understanding tumor biology.

A fundamental, evolutionarily conserved biological mechanism required for long-term memory formation is rapid induction of gene transcription upon learning in relevant brain areas. For episodic types of memories, two regions undergoing this transcription are the dorsal hippocampus (dHC) and prelimbic (PL) cortex. Whether and to what extent these regions regulate similar or distinct transcriptomic profiles upon learning remain to be understood. Here, we used RNA sequencing in the dHC and PL cortex of male rats to profile their transcriptomes in untrained conditions (baseline) and at 1 h and 6 d after inhibitory avoidance learning. We found that, of 33,713 transcripts, >14,000 were significantly expressed at baseline in both regions and ∼3000 were selectively enriched in each region. Gene Ontology biological pathway analyses indicated that commonly expressed pathways included synapse organization, regulation of membrane potential, and vesicle localization. The enriched pathways in the dHC were gliogenesis, axon development, and lipid modification, while in the PL cortex included vesicle localization and synaptic vesicle cycle. At 1 h after learning, 135 transcripts changed significantly in the dHC and 478 in the PL cortex; of these, only 34 were shared. Biological pathways most significantly regulated by learning in the dHC were protein dephosphorylation, glycogen and glucan metabolism, while in the PL cortex were axon development and axonogenesis. The transcriptome profiles returned to baseline by 6 d after training. Thus, a significant portion of dHC and PL cortex transcriptomic profiles is divergent, and their regulation upon learning is largely distinct and transient.SIGNIFICANCE STATEMENT Long-term episodic memory formation requires gene transcription in several brain regions, including the hippocampus and PFC. The comprehensive profiles of the dynamic mRNA changes that occur in these regions following learning are not well understood. Here, we performed RNA sequencing in the dorsal hippocampus and prelimbic cortex, a PFC subregion, at baseline, 1 h, and 6 d after episodic learning in rats. We found that, at baseline, dorsal hippocampus and prelimbic cortex differentially express a significant portion of mRNAs. Moreover, learning produces a transient regulation of region-specific profiles of mRNA, indicating that unique biological programs in different brain regions underlie memory formation.

The metazoan genome is compartmentalized in areas of highly interacting chromatin known as topologically associating domains (TADs). TADs are demarcated by boundaries mostly conserved across cell types and even across species. However, a genome-wide characterization of TAD boundary strength in mammals is still lacking. In this study, we first use fused two-dimensional lasso as a machine learning method to improve Hi-C contact matrix reproducibility, and, subsequently, we categorize TAD boundaries based on their insulation score. We demonstrate that higher TAD boundary insulation scores are associated with elevated CTCF levels and that they may differ across cell types. Intriguingly, we observe that super-enhancers are preferentially insulated by strong boundaries. Furthermore, we demonstrate that strong TAD boundaries and super-enhancer elements are frequently co-duplicated in cancer patients. Taken together, our findings suggest that super-enhancers insulated by strong TAD boundaries may be exploited, as a functional unit, by cancer cells to promote oncogenesis.

Uncovering the causes of pregnancy complications such as preterm labor requires greater insight into how the uterus remains in a noncontractile state until term and then surmounts this state to enter labor. Here, we show that dynamic generation and erasure of the repressive histone modification tri-methyl histone H3 lysine 27 (H3K27me3) in decidual stromal cells dictate both elements of pregnancy success in mice. In early gestation, H3K27me3-induced transcriptional silencing of select gene targets ensured uterine quiescence by preventing the decidua from expressing parturition-inducing hormone receptors, manifesting type 1 immunity, and most unexpectedly, generating myofibroblasts and associated wound-healing responses. In late gestation, genome-wide H3K27 demethylation allowed for target gene upregulation, decidual activation, and labor entry. Pharmacological inhibition of H3K27 demethylation in late gestation not only prevented term parturition, but also inhibited delivery while maintaining pup viability in a noninflammatory model of preterm parturition. Immunofluorescence analysis of human specimens suggested that similar regulatory events might occur in the human decidua. Together, these results reveal the centrality of regulated gene silencing in the uterine adaptation to pregnancy and suggest new areas in the study and treatment of pregnancy disorders.

Lung adenocarcinoma (LUAD) is a clinically heterogeneous disease, which is highlighted by the unpredictable recurrence in low-stage tumors and highly variable responses observed in patients treated with immunotherapies, which cannot be explained by mutational profiles. DNA methylation-based classification and understanding of microenviromental heterogeneity may allow stratification into clinically relevant molecular subtypes of LUADs.