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. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide.

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. Additionally, a novel gene expression classifier, which identifies tumors with a high immune cell infiltration, was shown to enrich for response to avadomide in R/R DLBCL. Ninety-seven patients with R/R DLBCL, including 12 patients with transformed lymphoma, received 3 to 5 mg avadomide administered on continuous or intermittent schedules until unacceptable toxicity, disease progression, or withdrawal. Eighty-two patients (85%) experienced ≥1 grade 3/4 treatment-emergent adverse events (AEs), most commonly neutropenia (51%), infections (24%), anemia (12%), and febrile neutropenia (10%). Discontinuations because of AEs occurred in 10% of patients. Introduction of an intermittent 5/7-day schedule improved tolerability and reduced frequency and severity of neutropenia, febrile neutropenia, and infections. Among 84 patients with de novo R/R DLBCL, overall response rate (ORR) was 29%, including 11% complete response (CR). Responses were cell-of-origin independent. Classifier-positive DLBCL patients (de novo) had an ORR of 44%, median progression-free survival (mPFS) of 6 months, and 16% CR vs an ORR of 19%, mPFS of 1.5 months, and 5% CR in classifier-negative patients (P = .0096). Avadomide is being evaluated in combination with other antilymphoma agents. This trial was registered at www.clinicaltrials.gov as #NCT01421524.

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. METHODS AND FINDINGS: Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies. CONCLUSIONS: In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma.

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1273 newly diagnosed patients with MM, we identified 63 driver genes, some of which are novel, including IDH1, IDH2, HUWE1, KLHL6, and PTPN11 Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more driver gene abnormalities are associated with worse outcomes, as are identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3, DIS3, and PRKD2; t(11;14) with mutations in CCND1 and IRF4; t(14;16) with mutations in MAF, BRAF, DIS3, and ATM; and hyperdiploidy with gain 11q, mutations in FAM46C, and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is predetermined by the primary events upon which further dependencies are built, giving rise to a nonrandom accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.

Microhomology-mediated end joining drives complex rearrangements and overexpression of MYC and PVT1 in multiple myeloma.

MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1,267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3 We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in overexpression of key genes and chromatin immunoprecipitation-sequencing identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.

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. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. Results: PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. Availability and implementation: https://github.com/ima23/maxent-ppi. Contact: sbh11@cl.cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

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. Importantly, the pluripotency factors NANOG, OCT4, and SOX2 have an essential function in this network by actively directing differentiation. Indeed, these transcription factors control the expression of EOMESODERMIN (EOMES), which marks the onset of endoderm specification. In turn, EOMES interacts with SMAD2/3 to initiate the transcriptional network governing endoderm formation. Together, these results provide for the first time a comprehensive molecular model connecting the transition from pluripotency to endoderm specification during mammalian development.

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. We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments. RESULTS: As might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. CONCLUSIONS: Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

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. We show that BRA has distinct genome-wide binding landscapes in these two cell populations, and that BRA interacts and collaborates with SMAD1 or SMAD2/3 signalling to regulate the expression of its target genes in a cell-specific manner. Importantly, by manipulating the levels of BRA in cells exposed to different signalling environments, we demonstrate that BRA is essential for mesoderm but not for endoderm formation. Together, our data illuminate the function of BRA in the context of human embryonic development and show that the regulatory role of BRA is context dependent. Our study reinforces the importance of analysing the functions of a transcription factor in different cellular and signalling environments.

Activity of lenalidomide in mantle cell lymphoma can be explained by NK cell-mediated cytotoxicity.

Lenalidomide is an immunomodulatory agent that has demonstrated clinical benefit for patients with relapsed or refractory mantle cell lymphoma (MCL); however, despite this observed clinical activity, the mechanism of action (MOA) of lenalidomide has not been characterized in this setting. We investigated the MOA of lenalidomide in clinical samples from patients enrolled in the CC-5013-MCL-002 trial (NCT00875667) comparing single-agent lenalidomide versus investigator's choice single-agent therapy and validated our findings in pre-clinical models of MCL. Our results revealed a significant increase in natural killer (NK) cells relative to total lymphocytes in lenalidomide responders compared to non-responders that was associated with a trend towards prolonged progression-free survival and overall survival. Clinical response to lenalidomide was independent of baseline tumour microenvironment expression of its molecular target, cereblon, as well as genetic mutations reported to impact clinical response to the Bruton tyrosine kinase inhibitor ibrutinib. Preclinical experiments revealed lenalidomide enhanced NK cell-mediated cytotoxicity against MCL cells via increased lytic immunological synapse formation and secretion of granzyme B. In contrast, lenalidomide exhibited minimal direct cytotoxic effects against MCL cells. Taken together, these data provide the first insight into the clinical activity of lenalidomide against MCL, revealing a predominately immune-mediated MOA.

CC-122, a pleiotropic pathway modifier, mimics an interferon response and has antitumor activity in DLBCL.

Cereblon (CRBN), a substrate receptor of the Cullin 4 RING E3 ubiquitin ligase complex, is the target of the immunomodulatory drugs lenalidomide and pomalidomide. Recently, it was demonstrated that binding of these drugs to CRBN promotes the ubiquitination and subsequent degradation of 2 common substrates, transcription factors Aiolos and Ikaros. Here we report that CC-122, a new chemical entity termed pleiotropic pathway modifier, binds CRBN and promotes degradation of Aiolos and Ikaros in diffuse large B-cell lymphoma (DLBCL) and T cells in vitro, in vivo, and in patients, resulting in both cell autonomous as well as immunostimulatory effects. In DLBCL cell lines, CC-122-induced degradation or short hairpin RNA-mediated knockdown of Aiolos and Ikaros correlates with increased transcription of interferon (IFN)-stimulated genes independent of IFN-α, -ß, and -γ production and/or secretion and results in apoptosis in both activated B-cell (ABC) and germinal center B-cell DLBCL cell lines. Our results provide mechanistic insight into the cell-of-origin independent antilymphoma activity of CC-122, in contrast to the ABC subtype selective activity of lenalidomide.

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. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis.

Demyelination causes adult CNS progenitors to revert to an immature state and express immune cues that support their migration.

The declining efficiency of myelin regeneration in individuals with multiple sclerosis has stimulated a search for ways by which it might be therapeutically enhanced. Here we have used gene expression profiling on purified murine oligodendrocyte progenitor cells (OPCs), the remyelinating cells of the adult CNS, to obtain a comprehensive picture of how they become activated after demyelination and how this enables them to contribute to remyelination. We find that adult OPCs have a transcriptome more similar to that of oligodendrocytes than to neonatal OPCs, but revert to a neonatal-like transcriptome when activated. Part of the activation response involves increased expression of two genes of the innate immune system, IL1ß and CCL2, which enhance the mobilization of OPCs. Our results add a new dimension to the role of the innate immune system in CNS regeneration, revealing how OPCs themselves contribute to the postinjury inflammatory milieu by producing cytokines that directly enhance their repopulation of areas of demyelination and hence their ability to contribute to remyelination.

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

Human epidermal stem cells express high levels of ß1 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 DLL1(+) cluster had elevated expression of genes associated with endocytosis, integrin-mediated adhesion and receptor tyrosine kinase signalling. Differentially expressed genes were not independently regulated, as overexpression of DLL1 alone or together with LRIG1 led to the upregulation of other genes in the DLL1(+) cluster. Overexpression of DLL1 and LRIG1 resulted in enhanced extracellular matrix adhesion and increased caveolin-dependent EGFR endocytosis. Further characterisation of CD46, one of the genes upregulated in the DLL1(+) cluster, revealed it to be a novel cell surface marker of human epidermal stem cells. Cells with high endogenous levels of CD46 expressed high levels of ß1 integrin and DLL1 and were highly adhesive and clonogenic. Knockdown of CD46 decreased proliferative potential and ß1 integrin-mediated adhesion. Thus, the previously unknown heterogeneity revealed by our studies results in differences in the interaction of undifferentiated basal keratinocytes with their environment.

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. Such methods may be grouped according to: (1) the type of data used: methods based on experiment-specific measurements (e.g., spectral counts or identification scores) versus methods that extract knowledge encoded in external annotations (e.g., public interaction and functional categorisation databases); (2) the type of algorithm applied: the statistical description and estimation of physical protein properties versus predictive supervised machine learning or text-mining algorithms; (3) the type of protein relation evaluated: direct (binary) interaction of two proteins in a cocomplex versus probability of any functional relationship between two proteins (e.g., co-occurrence in a pathway, sub cellular compartment); and (4) initial motivation: elucidation of experimental data by evaluation versus prediction of novel protein-protein interaction, to be experimentally validated a posteriori. This work reviews several popular computational scoring methods and software platforms for protein-protein interactions evaluation according to their methodology, comparative strengths and weaknesses, data representation, accessibility, and availability. The scoring methods and platforms described include: CompPASS, SAINT, Decontaminator, MINT, IntAct, STRING, and FunCoup. References to related work are provided throughout in order to provide a concise but thorough introduction to a rapidly growing interdisciplinary field of investigation.

Molecular architecture of the DNA replication origin activation checkpoint.

Perturbation of DNA replication initiation arrests human cells in G1, pointing towards an origin activation checkpoint. We used RNAi against Cdc7 kinase to inhibit replication initiation and dissect this checkpoint in fibroblasts. We show that the checkpoint response is dependent on three axes coordinated through the transcription factor FoxO3a. In arrested cells, FoxO3a activates the ARF-∣Hdm2-∣p53 → p21 pathway and mediates p15(INK4B) upregulation; p53 in turn activates expression of the Wnt/ß-catenin signalling antagonist Dkk3, leading to Myc and cyclin D1 downregulation. The resulting loss of CDK activity inactivates the Rb-E2F pathway and overrides the G1-S transcriptional programme. Fibroblasts concomitantly depleted of Cdc7/FoxO3a, Cdc7/p15, Cdc7/p53 or Cdc7/Dkk3 can bypass the arrest and proceed into an abortive S phase followed by apoptosis. The lack of redundancy between the checkpoint axes and reliance on several tumour suppressor proteins commonly inactivated in human tumours provides a mechanistic basis for the cancer-cell-specific killing observed with emerging Cdc7 inhibitors.

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. METHODS: We used the stable isotope labeling of amino acids in cell culture proteomics methodology to measure changes in the human immortalized fibroblast proteome after TLR3 activation. RESULTS: Cells from healthy controls were compared with cells from a patient with a known genetic etiology of HSE (UNC-93B-/-) and also to cells from an HSE patient with an unknown gene defect. Consistent with known variation in susceptibility of individuals to viral infections, substantial variation in the response level of different healthy controls was observed, but common functional networks could be identified, including upregulation of superoxide dismutase 2. The 2 patients with HSE studied show clear differences in functional response networks when compared with healthy controls and also when compared with each other. CONCLUSIONS: The present study delineates a number of novel proteins, TLR3-related pathways, and cellular phenotypes that may help elucidate the genetic basis of childhood HSE. Furthermore, our results reveal superoxide dismutase 2 as a potential therapeutic target for amelioration of the neurologic sequelae caused by HSE.

Derivation of pluripotent epiblast stem cells from mammalian embryos.

Although the first mouse embryonic stem (ES) cell lines were derived 25 years ago using feeder-layer-based blastocyst cultures, subsequent efforts to extend the approach to other mammals, including both laboratory and domestic species, have been relatively unsuccessful. The most notable exceptions were the derivation of non-human primate ES cell lines followed shortly thereafter by their derivation of human ES cells. Despite the apparent common origin and the similar pluripotency of mouse and human embryonic stem cells, recent studies have revealed that they use different signalling pathways to maintain their pluripotent status. Mouse ES cells depend on leukaemia inhibitory factor and bone morphogenetic protein, whereas their human counterparts rely on activin (INHBA)/nodal (NODAL) and fibroblast growth factor (FGF). Here we show that pluripotent stem cells can be derived from the late epiblast layer of post-implantation mouse and rat embryos using chemically defined, activin-containing culture medium that is sufficient for long-term maintenance of human embryonic stem cells. Our results demonstrate that activin/Nodal signalling has an evolutionarily conserved role in the derivation and the maintenance of pluripotency in these novel stem cells. Epiblast stem cells provide a valuable experimental system for determining whether distinctions between mouse and human embryonic stem cells reflect species differences or diverse temporal origins.

Kaposi sarcoma herpesvirus-induced cellular reprogramming contributes to the lymphatic endothelial gene expression in Kaposi sarcoma.

The biology of Kaposi sarcoma is poorly understood because the dominant cell type in Kaposi sarcoma lesions is not known. We show by gene expression microarrays that neoplastic cells of Kaposi sarcoma are closely related to lymphatic endothelial cells (LECs) and that Kaposi sarcoma herpesvirus (KSHV) infects both LECs and blood vascular endothelial cells (BECs) in vitro. The gene expression microarray profiles of infected LECs and BECs show that KSHV induces transcriptional reprogramming of both cell types. The lymphangiogenic molecules VEGF-D and angiopoietin-2 were elevated in the plasma of individuals with acquired immune deficiency syndrome and Kaposi sarcoma. These data show that the gene expression profile of Kaposi sarcoma resembles that of LECs, that KSHV induces a transcriptional drift in both LECs and BECs and that lymphangiogenic molecules are involved in the pathogenesis of Kaposi sarcoma.

Activin/Nodal signaling controls divergent transcriptional networks in human embryonic stem cells and in endoderm progenitors.

Activin/Nodal signaling is necessary to maintain pluripotency of human embryonic stem cells (hESCs) and to induce their differentiation toward endoderm. However, the mechanisms by which Activin/Nodal signaling achieves these opposite functions remain unclear. To unravel these mechanisms, we examined the transcriptional network controlled in hESCs by Smad2 and Smad3, which represent the direct effectors of Activin/Nodal signaling. These analyses reveal that Smad2/3 participate in the control of the core transcriptional network characterizing pluripotency, which includes Oct-4, Nanog, FoxD3, Dppa4, Tert, Myc, and UTF1. In addition, similar experiments performed on endoderm cells confirm that a broad part of the transcriptional network directing differentiation is downstream of Smad2/3. Therefore, Activin/Nodal signaling appears to control divergent transcriptional networks in hESCs and in endoderm. Importantly, we observed an overlap between the transcriptional network downstream of Nanog and Smad2/3 in hESCs; whereas, functional studies showed that both factors cooperate to control the expression of pluripotency genes. Therefore, the effect of Activin/Nodal signaling on pluripotency and differentiation could be dictated by tissue specific Smad2/3 partners such as Nanog, explaining the mechanisms by which signaling pathways can orchestrate divergent cell fate decisions.