Chromatin-based, in cis and in trans regulatory rewiring underpins distinct oncogenic transcriptomes in multiple myeloma

Super enhancer acquisition drives expression of oncogenic PPP1R15B that regulates protein homeostasis in multiple myeloma

Multiple myeloma is a hematological malignancy arising from immunoglobulin-secreting plasma cells. It remains poorly understood how chromatin rewiring of regulatory elements contributes to tumorigenesis and therapy resistance in myeloma. Here we generate a high-resolution contact map of myeloma-associated super-enhancers by integrating H3K27ac ChIP-seq and HiChIP from myeloma cell lines, patient-derived myeloma cells and normal plasma cells. Our comprehensive transcriptomic and phenomic analyses prioritize candidate genes with biological and clinical implications in myeloma. We show that myeloma cells frequently acquire SE that transcriptionally activate an oncogene PPP1R15B, which encodes a regulatory subunit of the holophosphatase complex that dephosphorylates translation initiation factor eIF2α. Epigenetic silencing or knockdown of PPP1R15B activates pro-apoptotic eIF2α-ATF4-CHOP pathway, while inhibiting protein synthesis and immunoglobulin production. Pharmacological inhibition of PPP1R15B using Raphin1 potentiates the anti-myeloma effect of bortezomib. Our study reveals that myeloma cells are vulnerable to perturbation of PPP1R15B-dependent protein homeostasis, highlighting a promising therapeutic strategy.

A comparative analysis of transcriptomics of newly diagnosed multiple myeloma: exploring drug repurposing

Multiple myeloma (MM) is an incurable malignant plasma cell disorder characterized by the infiltration of clonal plasma cells in the bone marrow compartment. Gene Expression Profiling (GEP) has emerged as a powerful investigation tool in modern myeloma research enabling the dissection of the molecular background of MM and allowing the identification of gene products that could potentially serve as targets for therapeutic intervention. In this study we investigated shared transcriptomic abnormalities across newly diagnosed multiple myeloma (NDMM) patient cohorts. In total, publicly available transcriptomic data of 7 studies from CD138+ cells from 281 NDMM patients and 44 healthy individuals were integrated and analyzed. Overall, we identified 28 genes that were consistently differentially expressed (DE) between NDMM patients and healthy donors (HD) across various studies. Of those, 9 genes were over/under-expressed in more than 75% of NDMM patients. In addition, we identified 4 genes (MT1F, PURPL, LINC01239 and LINC01480) that were not previously considered to participate in MM pathogenesis. Meanwhile, by mining three drug databases (ChEMBL, IUPHAR/BPS and DrugBank) we identified 31 FDA-approved and 144 experimental drugs that target 8 of these 28 over/under-expressed MM genes. Taken together, our study offers new insights in MM pathogenesis and importantly, it reveals potential new treatment options that need to be further investigated in future studies.

The SAGA acetyltransferase module is required for the maintenance of MAF and MYC oncogenic gene expression programs in multiple myeloma

Despite recent advances in therapeutic treatments, multiple myeloma (MM) remains an incurable malignancy. Epigenetic factors contribute to the initiation, progression, relapse, and clonal heterogeneity in MM, but our knowledge on epigenetic mechanisms underlying MM development is far from complete. The SAGA complex serves as a coactivator in transcription and catalyzes acetylation and deubiquitylation. Analyses of datasets in the Cancer Dependency Map Project revealed many SAGA components are selective dependencies in MM. To define SAGA-specific functions, we focused on ADA2B, the only subunit in the lysine acetyltransferase (KAT) module that specifically functions in SAGA. Integration of RNA-seq, ATAC-seq, and CUT&RUN results identified pathways directly regulated by ADA2B include MTORC1 signaling, MYC, E2F, and MM-specific MAF oncogenic programs. We discovered that ADA2B is recruited to MAF and MYC gene targets, and that MAF shares a majority of its targets with MYC in MM cells. Furthermore, we found the SANT domain of ADA2B is required for interaction with both GCN5 and PCAF acetyltransferases, incorporation into SAGA, and ADA2B protein stability. Our findings uncover previously unknown SAGA KAT module-dependent mechanisms controlling MM cell growth, revealing a vulnerability that might be exploited for future development of MM therapy.

Aberrant non-canonical NF-κB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma

In multiple myeloma, abnormal plasma cells establish oncogenic niches within the bone marrow by engaging the NF-κB pathway to nurture their survival while they accumulate pro-proliferative mutations. Under these conditions, many cases eventually develop genetic abnormalities endowing them with constitutive NF-κB activation. Here, we find that sustained NF-κB/p52 levels resulting from such mutations favours the recruitment of enhancers beyond the normal B-cell repertoire. Furthermore, through targeted disruption of p52, we characterise how such enhancers are complicit in the formation of super-enhancers and the establishment of cis-regulatory interactions with myeloma dependencies during constitutive activation of p52. Finally, we functionally validate the pathological impact of these cis-regulatory modules on cell and tumour phenotypes using in vitro and in vivo models, confirming RGS1 as a p52-dependent myeloma driver. We conclude that the divergent epigenomic reprogramming enforced by aberrant non-canonical NF-κB signalling potentiates transcriptional programs beneficial for multiple myeloma progression.

Epigenomic Characterization of Lymphoid Neoplasms

Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.

MyeloDB: a multi-omics resource for multiple myeloma

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all hematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high-throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 25 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes, i.e., CBFB, MANF, MBNL1, SEPHS2, and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB Database URL: https://project.iith.ac.in/cgntlab/myelodb/ .

MAF functions as a pioneer transcription factor that initiates and sustains myelomagenesis

Deregulated expression of lineage-affiliated transcription factors (TFs) is a major mechanism of oncogenesis. However, how the deregulation of nonlineage affiliated TF affects chromatin to initiate oncogenic transcriptional programs is not well-known. To address this, we studied the chromatin effects imposed by oncogenic MAF as the cancer-initiating driver in the plasma cell cancer multiple myeloma. We found that the ectopically expressed MAF endows myeloma plasma cells with migratory and proliferative transcriptional potential. This potential is regulated by the activation of enhancers and superenhancers, previously inactive in healthy B cells and plasma cells, and the cooperation of MAF with the plasma cell-defining TF IRF4. Forced ectopic MAF expression confirms the de novo ability of oncogenic MAF to convert transcriptionally inert chromatin to active chromatin with the features of superenhancers, leading to the activation of the MAF-specific oncogenic transcriptome and the acquisition of cancer-related cellular phenotypes such as CCR1-dependent cell migration. These findings establish oncogenic MAF as a pioneer transcription factor that can initiate as well as sustain oncogenic transcriptomes and cancer phenotypes. However, despite its pioneer function, myeloma cells remain MAF-dependent, thus validating oncogenic MAF as a therapeutic target that would be able to circumvent the challenges of subsequent genetic diversification driving disease relapse and drug resistance.

MLL-AF4 cooperates with PAF1 and FACT to drive high-density enhancer interactions in leukemia

Aberrant enhancer activation is a key mechanism driving oncogene expression in many cancers. While much is known about the regulation of larger chromosome domains in eukaryotes, the details of enhancer-promoter interactions remain poorly understood. Recent work suggests co-activators like BRD4 and Mediator have little impact on enhancer-promoter interactions. In leukemias controlled by the MLL-AF4 fusion protein, we use the ultra-high resolution technique Micro-Capture-C (MCC) to show that MLL-AF4 binding promotes broad, high-density regions of enhancer-promoter interactions at a subset of key targets. These enhancers are enriched for transcription elongation factors like PAF1C and FACT, and the loss of these factors abolishes enhancer-promoter contact. This work not only provides an additional model for how MLL-AF4 is able to drive high levels of transcription at key genes in leukemia but also suggests a more general model linking enhancer-promoter crosstalk and transcription elongation.

Enhancer in cancer pathogenesis and treatment

Enhancers are essential cis-acting regulatory elements that determine cell identity and tumor progression. Enhancer function is dependent on the physical interaction between the enhancer and its target promoter inside its local chromatin environment. Enhancer reprogramming is an important mechanism in cancer pathogenesis and can be driven by both cis and trans factors. Super enhancers are acquired at oncogenes in numerous cancer types and represent potential targets for cancer treatment. BET and CDK inhibitors act through mechanisms of enhancer function and have shown promising results in therapy for various types of cancer. Genome editing is another way to reprogram enhancers in cancer treatment. The relationship between enhancers and cancer has been revised by several authors in the past few years, which mainly focuses on the mechanisms by which enhancers can impact cancer. Here, we emphasize SE's role in cancer pathogenesis and the new therapies involving epigenetic regulators (BETi and CDKi). We suggest that understanding mechanisms of activity would aid clinical success for these anti-cancer agents.

Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites

Super-enhancers evolve as elements at the top of the hierarchical control of gene expression. They are important end-gatherers of signaling pathways that control stemness, differentiation or adaptive responses. Many epigenetic regulations focus on these regions, and not surprisingly, during the process of tumorigenesis, various alterations can account for their dysfunction. Super-enhancers are emerging as key drivers of the aberrant gene expression landscape that sustain the aggressiveness of cancer cells. In this review, we will describe and discuss about the structure of super-enhancers, their epigenetic regulation, and the major changes affecting their functionality in cancer.

Molecular Crosstalk between Chromatin Remodeling and Tumor Microenvironment in Multiple Myeloma

Multiple myeloma (MM) is a complex disease driven by numerous genetic and epigenetic alterations that are acquired over time. Despite recent progress in the understanding of MM pathobiology and the availability of innovative drugs, which have pronounced clinical outcome, this malignancy eventually progresses to a drug-resistant lethal stage and, thus, novel therapeutic drugs/models always play an important role in effective management of MM. Modulation of tumor microenvironment is one of the hallmarks of cancer biology, including MM, which affects the myeloma genomic architecture and disease progression subtly through chromatin modifications. The bone marrow niche has a prime role in progression, survival, and drug resistance of multiple myeloma cells. Therefore, it is important to develop means for targeting the ecosystem between multiple myeloma bone marrow microenvironment and chromatin remodeling. Extensive gene expression profile analysis has indeed provided the framework for new risk stratification of MM patients and identifying novel molecular targets and therapeutics. However, key tumor microenvironment factors/immune cells and their interactions with chromatin remodeling complex proteins that drive MM cell growth and progression remain grossly undefined.

Dissecting super-enhancer heterogeneity: time to re-examine cancer subtypes?

The heterogeneity of transcriptional regulations by super-enhancers (SEs) is poorly understood in human cancers. Herein, we summarize a bioinformatics workflow for genome-wide SE profiling and identification of subtype-specific SEs and regulatory networks. Dissecting SE heterogeneity provides new insights into cancer biology and alternative therapeutic strategies for cancer precision medicine.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality

Background

The constant evolving and development of next-generation sequencing techniques lead to high throughput data composed of datasets that include a large number of biological samples. Although a large number of samples are usually experimentally processed by batches, scientific publications are often elusive about this information, which can greatly impact the quality of the samples and confound further statistical analyzes. Because dedicated bioinformatics methods developed to detect unwanted sources of variance in the data can wrongly detect real biological signals, such methods could benefit from using a quality-aware approach.

Results

We recently developed statistical guidelines and a machine learning tool to automatically evaluate the quality of a next-generation-sequencing sample. We leveraged this quality assessment to detect and correct batch effects in 12 publicly available RNA-seq datasets with available batch information. We were able to distinguish batches by our quality score and used it to correct for some batch effects in sample clustering. Overall, the correction was evaluated as comparable to or better than the reference method that uses a priori knowledge of the batches (in 10 and 1 datasets of 12, respectively; total = 92%). When coupled to outlier removal, the correction was more often evaluated as better than the reference (comparable or better in 5 and 6 datasets of 12, respectively; total = 92%).

Conclusions

In this work, we show the capabilities of our software to detect batches in public RNA-seq datasets from differences in the predicted quality of their samples. We also use these insights to correct the batch effect and observe the relation of sample quality and batch effect. These observations reinforce our expectation that while batch effects do correlate with differences in quality, batch effects also arise from other artifacts and are more suitably  corrected statistically in well-designed experiments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04775-y.

Allostery, and how to define and measure signal transduction

Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.

Systems medicine dissection of chr1q-amp reveals a novel PBX1-FOXM1 axis for targeted therapy in multiple myeloma

Understanding the biological and clinical impact of copy number aberrations (CNAs) on the development of precision therapies in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring an adverse prognosis in several types of cancer, including in the blood cancer multiple myeloma (MM). Although several genes across chromosome 1 (chr1q) portend high-risk MM disease, the underpinning molecular etiology remains elusive. Here, with reference to the 3-dimensional (3D) chromatin structure, we integrate multi-omics data sets from patients with MM with genetic variables to obtain an associated clinical risk map across chr1q and to identify 103 adverse prognosis genes in chr1q-amp MM. Prominent among these genes, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed superenhancers, PBX1 directly regulates critical oncogenic pathways and a FOXM1-dependent transcriptional program. Together, PBX1 and FOXM1 activate a proliferative gene signature that predicts adverse prognosis across multiple types of cancer. Notably, pharmacological disruption of the PBX1-FOXM1 axis with existing agents (thiostrepton) and a novel PBX1 small molecule inhibitor (T417) is selectively toxic against chr1q-amp myeloma and solid tumor cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes, and proposes novel CNA-targeted therapy strategies in MM and other types of cancer.

Increasing Complexity of Molecular Landscapes in Human Hematopoietic Stem and Progenitor Cells during Development and Aging

The past five decades have seen significant progress in our understanding of human hematopoiesis. This has in part been due to the unprecedented development of advanced technologies, which have allowed the identification and characterization of rare subsets of human hematopoietic stem and progenitor cells and their lineage trajectories from embryonic through to adult life. Additionally, surrogate in vitro and in vivo models, although not fully recapitulating human hematopoiesis, have spurred on these scientific advances. These approaches have heightened our knowledge of hematological disorders and diseases and have led to their improved diagnosis and therapies. Here, we review human hematopoiesis at each end of the age spectrum, during embryonic and fetal development and on aging, providing exemplars of recent progress in deciphering the increasingly complex cellular and molecular hematopoietic landscapes in health and disease. This review concludes by highlighting links between chronic inflammation and metabolic and epigenetic changes associated with aging and in the development of clonal hematopoiesis.

Bone Marrow Stroma-Induced Transcriptome and Regulome Signatures of Multiple Myeloma

Multiple myeloma (MM) is a hematological cancer with inevitable drug resistance. MM cells interacting with bone marrow stromal cells (BMSCs) undergo substantial changes in the transcriptome and develop de novo multi-drug resistance. As a critical component in transcriptional regulation, how the chromatin landscape is transformed in MM cells exposed to BMSCs and contributes to the transcriptional response to BMSCs remains elusive. We profiled the transcriptome and regulome for MM cells using a transwell coculture system with BMSCs. The transcriptome and regulome of MM cells from the upper transwell resembled MM cells that coexisted with BMSCs from the lower chamber but were distinctive to monoculture. BMSC-induced genes were enriched in the JAK2/STAT3 signaling pathway, unfolded protein stress, signatures of early plasma cells, and response to proteasome inhibitors. Genes with increasing accessibility at multiple regulatory sites were preferentially induced by BMSCs; these genes were enriched in functions linked to responses to drugs and unfavorable clinic outcomes. We proposed JUNB and ATF4::CEBPβ as candidate transcription factors (TFs) that modulate the BMSC-induced transformation of the regulome linked to the transcriptional response. Together, we characterized the BMSC-induced transcriptome and regulome signatures of MM cells to facilitate research on epigenetic mechanisms of BMSC-induced multi-drug resistance in MM.

Super enhancers as master gene regulators in the pathogenesis of hematologic malignancies

Transcriptional deregulation of multiple oncogenes, tumor suppressors and survival pathways is a cancer cell hallmark. Super enhancers (SE) are long stretches of active enhancers in close linear proximity that ensure extraordinarily high expression levels of key genes associated with cell lineage, function and survival. SE landscape is intrinsically prone to changes and reorganization during the course of normal cell differentiation. This functional plasticity is typically utilized by cancer cells, which remodel their SE landscapes to ensure oncogenic transcriptional reprogramming. Multiple recent studies highlighted structural genetic mechanisms in non-coding regions that create new SE or hijack already existing ones. In addition, alterations in abundance/activity of certain SE-associated proteins or certain viral infections can elicit new super enhancers and trigger SE-driven transcriptional changes. For these reasons, SE profiling emerged as a powerful tool for discovering the core transcriptional regulatory circuits in tumor cells. This, in turn, provides new insights into cancer cell biology, and identifies main nodes of key cellular pathways to be potentially targeted. Since SEs are susceptible to inhibition, their disruption results in exponentially amassing 'butterfly' effect on gene expression and cell function. Moreover, many of SE elements are druggable, opening new therapeutic opportunities. Indeed, SE targeting drugs have been studied preclinically in various hematologic malignancies with promising effects. Herein, we review the unique features of SEs, present different cis- and trans-acting mechanisms through which hematologic tumor cells acquire SEs, and finally, discuss the potential of SE targeting in the therapy of hematologic malignancies.

Hepatitis B virus DNA integration as a novel biomarker of hepatitis B virus-mediated pathogenetic properties and a barrier to the current strategies for hepatitis B virus cure

Chronic infection with Hepatitis B Virus (HBV) is a major cause of liver-related morbidity and mortality worldwide. HBV-DNA integration into the human genome is recognized as a frequent event occurring during the early phases of HBV infection and characterizing the entire course of HBV natural history. The development of refined molecular biology technologies sheds new light on the functional implications of HBV-DNA integration into the human genome, including its role in the progression of HBV-related pathogenesis and in triggering the establishment of pro-oncogenic mechanisms, promoting the development of hepatocellular carcinoma. The present review provides an updated and comprehensive overview of the current body of knowledge on HBV-DNA integration, focusing on the molecular mechanisms underlying HBV-DNA integration and its occurrence throughout the different phases characterizing the natural history of HBV infection. Furthermore, here we discuss the main clinical implications of HBV integration as a biomarker of HBV-related pathogenesis, particularly in reference to hepatocarcinogenesis, and how integration may act as a barrier to the achievement of HBV cure with current and novel antiviral therapies. Overall, a more refined insight into the mechanisms and functionality of HBV integration is paramount, since it can potentially inform the design of ad hoc diagnostic tools with the ability to reveal HBV integration events perturbating relevant intracellular pathways and for identifying novel therapeutic strategies targeting alterations directly related to HBV integration.