Integrative multi-omics identifies high risk multiple myeloma subgroup associated with significant DNA loss and dysregulated DNA repair and cell cycle pathways.

Background: Despite significant therapeutic advances in improving lives of multiple myeloma (MM) patients, it remains mostly incurable, with patients ultimately becoming refractory to therapies. MM is a genetically heterogeneous disease and therapeutic resistance is driven by a complex interplay of disease pathobiology and mechanisms of drug resistance. We applied a multi-omics strategy using tumor-derived gene expression, single nucleotide variant, copy number variant, and structural variant profiles to investigate molecular subgroups in 514 newly diagnosed MM (NDMM) samples and identified 12 molecularly defined MM subgroups (MDMS1-12) with distinct genomic and transcriptomic features.

Quantitative Systems Pharmacology Modeling of Avadomide-Induced Neutropenia Enables Virtual Clinical Dose and Schedule Finding Studies.

Avadomide is a cereblon E3 ligase modulator and a potent antitumor and immunomodulatory agent. Avadomide trials are challenged by neutropenia as a major adverse event and a dose-limiting toxicity. Intermittent dosing schedules supported by preclinical data provide a strategy to reduce frequency and severity of neutropenia; however, the identification of optimal dosing schedules remains a clinical challenge.

Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma.

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes.

Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials.

Background: The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases.

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research.

Avadomide monotherapy in relapsed/refractory DLBCL: safety, efficacy, and a predictive gene classifier.

Treatment options for relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) are limited, with no standard of care; prognosis is poor, with 4- to 6-month median survival. Avadomide (CC-122) is a cereblon-modulating agent with immunomodulatory and direct antitumor activities. This phase 1 dose-expansion study assessed safety and clinical activity of avadomide monotherapy in patients with de novo R/R DLBCL and transformed lymphoma.

ADAPTS: Automated deconvolution augmentation of profiles for tissue specific cells.

Immune cell infiltration of tumors and the tumor microenvironment can be an important component for determining patient outcomes. For example, immune and stromal cell presence inferred by deconvolving patient gene expression data may help identify high risk patients or suggest a course of treatment. One particularly powerful family of deconvolution techniques uses signature matrices of genes that uniquely identify each cell type as determined from single cell type purified gene expression data.

Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm.

Background: RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem.

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

Motivation: Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties.

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics.

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community.

Brachyury and SMAD signalling collaboratively orchestrate distinct mesoderm and endoderm gene regulatory networks in differentiating human embryonic stem cells.

The transcription factor brachyury (T, BRA) is one of the first markers of gastrulation and lineage specification in vertebrates. Despite its wide use and importance in stem cell and developmental biology, its functional genomic targets in human cells are largely unknown. Here, we use differentiating human embryonic stem cells to study the role of BRA in activin A-induced endoderm and BMP4-induced mesoderm progenitors.

Inhibition of phosphodiesterase-4 promotes oligodendrocyte precursor cell differentiation and enhances CNS remyelination.

The increasing effectiveness of new disease-modifying drugs that suppress disease activity in multiple sclerosis has opened up opportunities for regenerative medicines that enhance remyelination and potentially slow disease progression. Although several new targets for therapeutic enhancement of remyelination have emerged, few lend themselves readily to conventional drug development. Here, we used transcription profiling to identify mitogen-activated protein kinase (Mapk) signalling as an important regulator involved in the differentiation of oligodendrocyte progenitor cells (OPCs) into oligodendrocytes.

In vivo T-box transcription factor profiling reveals joint regulation of embryonic neuromesodermal bipotency.

The design of effective cell replacement therapies requires detailed knowledge of how embryonic stem cells form primary tissues, such as mesoderm or neurectoderm that later become skeletal muscle or nervous system. Members of the T-box transcription factor family are key in the formation of these primary tissues, but their underlying molecular activities are poorly understood. Here, we define in vivo genome-wide regulatory inputs of the T-box proteins Brachyury, Eomesodermin, and VegT, which together maintain neuromesodermal stem cells and determine their bipotential fates in frog embryos.

Single-cell gene expression profiling reveals functional heterogeneity of undifferentiated human epidermal cells.

Human epidermal stem cells express high levels of β1 integrins, delta-like 1 (DLL1) and the EGFR antagonist LRIG1. However, there is cell-to-cell variation in the relative abundance of DLL1 and LRIG1 mRNA transcripts. Single-cell global gene expression profiling showed that undifferentiated cells fell into two clusters delineated by expression of DLL1 and its binding partner syntenin.

The proteome of Toll-like receptor 3-stimulated human immortalized fibroblasts: implications for susceptibility to herpes simplex virus encephalitis.

Background: Inborn errors in Toll-like receptor 3 (TLR3)-IFN type I and III pathways have been implicated in susceptibility to herpes simplex virus encephalitis (HSE) in children, but most patients studied do not carry mutations in any of the genes presently associated with HSE susceptibility. Moreover, many patients do not display any TLR3-IFN-related fibroblastic phenotype.

Objective: To study other signaling pathways downstream of TLR3 and/or other independent pathways that may contribute to HSE susceptibility.

Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments.

Advances in sensitivity, resolution, mass accuracy, and throughput have considerably increased the number of protein identifications made via mass spectrometry. Despite these advances, state-of-the-art experimental methods for the study of protein-protein interactions yield more candidate interactions than may be expected biologically owing to biases and limitations in the experimental methodology. In silico methods, which distinguish between true and false interactions, have been developed and applied successfully to reduce the number of false positive results yielded by physical interaction assays.

Epiblast stem cell-based system reveals reprogramming synergy of germline factors.

Epigenetic reprogramming in early germ cells is critical toward the establishment of totipotency, but investigations of the germline events are intractable. An objective cell culture-based system could provide mechanistic insight on how the key determinants of primordial germ cells (PGCs), including Prdm14, induce reprogramming in germ cells to an epigenetic ground state. Here we show a Prdm14-Klf2 synergistic effect that can accelerate and enhance reversion of mouse epiblast stem cells (epiSCs) to a naive pluripotent state, including X reactivation and DNA demethylation.

Multiple Kernel Learning for Drug Discovery.

The support vector machine (SVM) methodology has become a popular and well-used component of present chemometric analysis. We assess a relatively recent development of the algorithm, multiple kernel learning (MKL), on published structure-property relationship (SPR) data. The MKL algorithm learns a weighting across multiple kernel-based representations of the data during supervised classifier creation and, thereby, may be used to describe the influence of distinct groups of structural descriptors upon a single structure-property classifier without explicitly omitting any of them.

Lrig1 controls intestinal stem-cell homeostasis by negative regulation of ErbB signalling.

Maintenance of adult tissues is carried out by stem cells and is sustained throughout life in a highly ordered manner. Homeostasis within the stem-cell compartment is governed by positive- and negative-feedback regulation of instructive extrinsic and intrinsic signals. ErbB signalling is a prerequisite for maintenance of the intestinal epithelium following injury and tumour formation.

Generation of human vascular smooth muscle subtypes provides insight into embryological origin-dependent disease susceptibility.

Heterogeneity of embryological origins is a hallmark of vascular smooth muscle cells (SMCs) and may influence the development of vascular disease. Differentiation of human pluripotent stem cells (hPSCs) into developmental origin-specific SMC subtypes remains elusive. Here we describe a chemically defined protocol in which hPSCs were initially induced to form neuroectoderm, lateral plate mesoderm or paraxial mesoderm.

Pluripotency factors regulate definitive endoderm specification through eomesodermin.

Understanding the molecular mechanisms controlling early cell fate decisions in mammals is a major objective toward the development of robust methods for the differentiation of human pluripotent stem cells into clinically relevant cell types. Here, we used human embryonic stem cells and mouse epiblast stem cells to study specification of definitive endoderm in vitro. Using a combination of whole-genome expression and chromatin immunoprecipitation (ChIP) deep sequencing (ChIP-seq) analyses, we established an hierarchy of transcription factors regulating endoderm specification.

LIF-independent JAK signalling to chromatin in embryonic stem cells uncovered from an adult stem cell disease.

Activating mutations in the tyrosine kinase Janus kinase 2 (JAK2) cause myeloproliferative neoplasms, clonal blood stem cell disorders with a propensity for leukaemic transformation. Leukaemia inhibitory factor (LIF) signalling through the JAK-signal transducer and activator of transcription (STAT) pathway enables self-renewal of embryonic stem (ES) cells. Here we show that mouse ES cells carrying the human JAK2V617F mutation were able to self-renew in chemically defined conditions without cytokines or small-molecule inhibitors, independently of JAK signalling through the STAT3 or phosphatidylinositol-3-OH kinase pathways.

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions.

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution.