Faculty Bibliography

Epigenetic dysregulation plays a profound role in the pathogenesis of hematological malignancies, which is often the result of somatic mutations of chromatin regulators. Previously, these mutations were largely considered to alter gene expression in two dimensions, by activating or repressing chromatin states; however, research in the last decade has highlighted the increasing impact of the 3D organization of the genome in gene regulation and disease pathogenesis. Here, we summarize the current principles of 3D chromatin organization, how the integrity of the 3D genome governs immune cell development and malignant transformation, as well as how underlying (epi-)genetic drivers of 3D chromatin alterations might act as potential novel therapeutic targets for hematological malignancies.

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As with most cancer types, there remains a subset of B-cell acute lymphoblastic leukaemia (B-ALL) patients who will relapse and succumb to therapy-resistant disease. It is believed that tumour heterogeneity underpins therapy failure leading to a Darwinian model of clonal evolution, however, such studies do not account for the role of the bone marrow microenvironment in supporting leukaemia survival, progression and escape from treatment. Here, we perform single-cell RNA-Sequencing (scRNA-Seq) to generate a comprehensive map of the primary human B-ALL bone marrow immune microenvironment throughout three distinct stages of the human leukemic disease process: diagnosis, remission and relapse. These studies show extensive re-modelling of the immune microenvironment composition and cell-to-cell interactions throughout the course conventional chemotherapy, and uncover a role for inflammatory leukaemia-associated monocytes in promoting B-ALL pathogenesis in vivo. These monocytic subsets are predictive of Ph+ B-ALL patient event-free survival and when targeted in B-ALL animal models, lead to prolonged disease remission. Our profiling of the human B-ALL bone marrow immune microenvironment provides a greater understanding of the potential extrinsic regulators of B-ALL survival and may highlight previously unknown environmental factors influencing immune-based treatment approaches to high-risk B-ALL.

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.

BACKGROUND:Limitations to current therapies for treating non-Hodgkin B cell lymphoma include relapse, toxicity and high cost. Thus, there remains a need for novel therapies. Oncolytic viral (OV) therapy has become a promising cancer immunotherapy because of its potential effectiveness, specificity and long-lasting immunity. We describe and characterize a novel cancer immunotherapy combining Sindbis virus (SV) vectors and the agonistic monoclonal antibody (mAb) to the T cell costimulatory receptor, 4-1BB (CD137). METHODS:A20 lymphoma was transfected with luciferase and tumor cells were inoculated to BALB/c mice. Tumor growth was monitored by IVIS imaging. Tumor bearing mice were treated with Sindbis virus, α4-1BB Ab or SV plus α4-1BB Ab. On day 7 after treatment, splenocytes were harvested and surface markers, cytokines, and transcription factors were measured by flow cytometry or Elispot. Splenic T cells were isolated and RNA transcriptome analysis was performed. Tumor cured mice were rechallenged with tumor for testing immunological memory. RESULTS:SV vectors in combination with α4-1BB monoclonal antibody (mAb) completely eradicated a B-cell lymphoma in a preclinical mouse model, a result that could not be achieved with either treatment alone. Tumor elimination involves a synergistic effect of the combination that significantly boosts T cell cytotoxicity, IFNγ production, T cell proliferation, migration, and glycolysis. In addition, all mice that survived after treatment developed long lasting antitumor immunity, as shown by the rejection of A20 tumor rechallenge. We identified the molecular pathways, including upregulated cytokines, chemokines and metabolic pathways in T cells that are triggered by the combined therapy and help to achieve a highly effective anti-tumor response. CONCLUSIONS:Our study provides a novel, alternative method for B cell lymphoma treatment and describes a rationale to help translate SV vectors plus agonistic mAb into clinical applications.

Approximately 30% of human lung cancers acquire mutations in either Keap1 or Nfe2l2, resulting in the stabilization of Nrf2, the Nfe2l2 gene product, which controls oxidative homeostasis. Here, we show that heme triggers the degradation of Bach1, a pro-metastatic transcription factor, by promoting its interaction with the ubiquitin ligase Fbxo22. Nrf2 accumulation in lung cancers causes the stabilization of Bach1 by inducing Ho1, the enzyme catabolizing heme. In mouse models of lung cancers, loss of Keap1 or Fbxo22 induces metastasis in a Bach1-dependent manner. Pharmacological inhibition of Ho1 suppresses metastasis in a Fbxo22-dependent manner. Human metastatic lung cancer display high levels of Ho1 and Bach1. Bach1 transcriptional signature is associated with poor survival and metastasis in lung cancer patients. We propose that Nrf2 activates a metastatic program by inhibiting the heme- and Fbxo22-mediated degradation of Bach1, and that Ho1 inhibitors represent an effective therapeutic strategy to prevent lung cancer metastasis.

The BCL-2 family plays important roles in acute myeloid leukemia (AML). Venetoclax, a selective BCL-2 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.

The bone marrow microenvironment has a key role in regulating haematopoiesis, but its molecular complexity and response to stress are incompletely understood. Here we map the transcriptional landscape of mouse bone marrow vascular, perivascular and osteoblast cell populations at single-cell resolution, both at homeostasis and under conditions of stress-induced haematopoiesis. This analysis revealed previously unappreciated levels of cellular heterogeneity within the bone marrow niche and resolved cellular sources of pro-haematopoietic growth factors, chemokines and membrane-bound ligands. Our studies demonstrate a considerable transcriptional remodelling of niche elements under stress conditions, including an adipocytic skewing of perivascular cells. Among the stress-induced changes, we observed that vascular Notch delta-like ligands (encoded by Dll1 and Dll4) were downregulated. In the absence of vascular Dll4, haematopoietic stem cells prematurely induced a myeloid transcriptional program. These findings refine our understanding of the cellular architecture of the bone marrow niche, reveal a dynamic and heterogeneous molecular landscape that is highly sensitive to stress and illustrate the utility of single-cell transcriptomic data in evaluating the regulation of haematopoiesis by discrete niche populations.

Background: Immune response is key in defense against cutaneous squamous cell carcinoma (cSCC). We aim to better target T cell killing to treat cancer. Method(s): CD8+ tumor infiltrating lymphocytes (TILs) obtained from fresh SCC tumor specimens from immunocompetent (n=5) versus organ transplant recipients (OTRs; n=6) were subject to single-cell RNA profiling and T-cell receptor (TCR) sequencing. Data were analyzed using scSeqR. Result(s): CD8+ TILs were clustered based on gene expression as follows: effector T cells (GZMA, GZMB, IFN-gamma); naive T cells (CCR7, LEF1, TCF7, IL7R); exhausted T cells (BTLA, CTLA4, PDCD1, TIM3, LAG3); and regulatory T cells (FOXP3, STAT3, TNFSRF). CD8+ TIL clonotypes show potential for response to known and uncharacterized antigens. CD8+ TILs from OTRs exhibited more homogeneous gene expression compared with immunocompetent patients. Regulatory and exhausted T cells were reduced in OTRs. TILs from both OTRs and immunocompetent patients showed clonality. However, more TCR clonotypes were observed in immunocompetent patients (mean = 1140) than OTRs (mean = 544). We analyzed common beta TCR from SCC via multiple bioinformatics-based approaches. Clonotypes common to more than one SCC from immune competent patients included breast cancer-associated keratin 19 and proliferation-associated striatin. OTR clonotypes included tumor-suppressor associated MOB kinase 1A and breast cancer-associated ADAM9. Conclusion(s): CD8+ TILs from cSCC showed clonotype restriction, implying T cell mediated anti-tumor response. We will refine our understanding of the SCC T cell landscape and identify and screen neoantigens with the goal of developing rational T cell-based cancer therapy.