Biology subjects

Sousos, N.

Publications and source records attributed to Sousos, N..

7 recordsLinked to original sources

bioRxiv2023

A pro-inflammatory stem cell niche drives myelofibrosis through a targetable galectin 1 axis

Myeloproliferative neoplasms are stem cell-driven cancers associated with a large burden of morbidity and mortality. The majority of patients present with early-stage disease, but a substantial proportion progress to myelofibrosis and/or secondary leukemia, advanced cancers with a poor prognosis and high symptom burden. Currently, it remains difficult to predict progression, and we lack therapies that reliably prevent or reverse fibrosis development. A major bottleneck to the discovery of disease-modifying therapies has been an incomplete understanding of the interplay between perturbed cellular and molecular states. Several cell types have individually been implicated, but a comprehensive analysis of myelofibrotic bone marrow is lacking. We therefore mapped the crosstalk between bone marrow cell types in myelofibrotic bone marrow. We found that inflammation and fibrosis are orchestrated by a quartet of immune and stromal cell lineages - with basophils and mast cells creating a TNF signaling hub, communicating with megakaryocytes, mesenchymal stromal cells and pro-inflammatory fibroblasts. We identified the y-galactoside binding protein galectin 1 as a striking biomarker of progression to myelofibrosis and poor survival in multiple patient cohorts, and as a promising therapeutic target, with reduced myeloproliferation and fibrosis in vitro and in vivo and improved survival following galectin 1 inhibition. In human bone marrow organoids, TNF increased galectin 1 expression, suggesting a feedback loop wherein the pro-inflammatory MPN clone creates a self-reinforcing niche, fueling progression to advanced disease. This study provides a valuable resource for studying hematopoietic cell-niche interactions, with broad relevance for cancer-associated inflammation and disorders of tissue fibrosis.

cancer biology↗

bioRxiv2022

Multipartite super-enhancers function in an orientation-dependent manner

Transcriptional enhancers regulate gene expression in a developmental-stage and cell-specific manner. They were originally defined as individual regulatory elements that activate expression regardless of distance and orientation to their cognate genes. Genome-wide studies have shown that the mammalian enhancer landscape is much more complex, with different classes of individual enhancers and clusters of enhancer-like elements combining in additive, synergistic and redundant manners, possibly acting as single, integrated regulatory elements. These so-called super-enhancers are largely defined as clusters of enhancer-like elements which recruit particularly high levels of Mediator and often drive high levels of expression of key lineage-specific genes. Here, we analysed 78 erythroid-specific super-enhancers and showed that, as units, they preferentially interact in a directional manner, to drive expression of their cognate genes. Using the well characterised -globin super-enhancer, we show that inverting this entire structure severely downregulates -globin expression and activates flanking genes 5 of the super-enhancer. Our detailed genetic dissection of the -globin locus clearly attributes the clusters functional directionality to its sequence orientation, demonstrating that, unlike regular enhancers, super-enhancers act in an orientation-dependent manner. Together, these findings identify a novel emergent property of super-enhancers and revise current models by which enhancers are thought to contact and activate their cognate genes.

molecular biology↗

bioRxiv2022

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

TP53 is the most commonly mutated gene in human cancer, typically occurring in association with complex cytogenetics and dismal outcomes. Understanding the genetic and non-genetic determinants of TP53-mutation driven clonal evolution and subsequent transformation is a crucial step towards the design of rational therapeutic strategies. Here, we carry out allelic resolution single-cell multi-omic analysis of haematopoietic stem/progenitor cells (HSPC) from patients with a myeloproliferative neoplasm who transform to TP53-mutant secondary acute myeloid leukaemia (AML), a tractable model of TP53-mutant cancer evolution. All patients showed dominant TP53 multi-hit HSPC clones at transformation, with a leukaemia stem cell transcriptional signature strongly predictive of adverse outcome in independent cohorts, across both TP53-mutant and wild-type AML. Through analysis of serial samples and antecedent TP53-heterozygous clones, we demonstrate a hitherto unrecognised effect of chronic inflammation, which supressed TP53 wild-type HSPC whilst enhancing the fitness advantage of TP53 mutant cells. Our findings will facilitate the development of risk-stratification, early detection and treatment strategies for TP53-mutant leukaemia, and are of broader relevance to other cancer types.

cancer biology↗

bioRxiv2019

Improving the diagnosis and classification of Ph-negative myeloproliferative neoplasms through deep phenotyping

Myeloproliferative neoplasms (MPNs) are clonal disorders characterized by excessive proliferation of myeloid lineages. Accurate classification and appropriate management of MPNs requires integration of clinical, morphological and genetic findings. Despite major advances in understanding the molecular and genetic basis, morphological assessment of the bone marrow trephine (BMT) remains paramount in differentiating between MPN subtypes and reactive conditions. However, morphological assessment is heavily constrained by a reliance on subjective, qualitative and poorly reproducible criteria. To address this, we have developed a machine-learning strategy for the automated identification and quantitative analysis of megakaryocyte morphology using clinical BMT samples. Using a sample cohort of recently diagnosed or established ET (n = 48) and reactive control cases (n = 42) we demonstrated a high predictive accuracy (AUC = 0.95) of automated tissue ET diagnosis based upon these specific megakaryocyte phenotypes. These separate morphological phenotypes showed evidence of specific genotype associations, which offers promise that an automated cell phenotyping approach may be of clinical diagnostic utility as an adjunct to standard genetic and molecular tests. This has great potential to assist in the routine assessment of newly diagnosed or suspected MPN patients and those undergoing treatment / clinical follow-up. The extraction of quantitative morphological data from BMT sections will also have value in the assessment of new therapeutic strategies directed towards the bone marrow microenvironment and can provide clinicians and researchers with objective, quantitative data without significant demands upon current routine specimen workflows.

pathology↗

bioRxiv2019

Single-cell analyses reveal aberrant pathways for megakaryocyte-biased hematopoiesis in myelofibrosis and identify mutant clone-specific targets

Myelofibrosis is a severe myeloproliferative neoplasm characterised by increased numbers of abnormal bone marrow megakaryocytes that induce progressive fibrosis, destroying the hematopoietic microenvironment. To determine the cellular and molecular basis for aberrant megakaryopoiesis in myelofibrosis, we performed high-throughput single-cell transcriptome profiling of 50,538 hematopoietic stem/progenitor cells (HSPCs), single-cell proteomics, genomics and functional assays. We identified an aberrant pathway for direct megakaryocyte differentiation from the earliest stages of hematopoiesis in myelofibrosis and associated aberrant molecular signatures, including surface antigens selectively expressed by JAK2-mutant HSPCs. Myelofibrosis megakaryocyte progenitors were heterogeneous, with distinct expression of fibrosis and proliferation-associated genes and putative therapy targets. We validated the immunoglobulin receptor G6B as a promising JAK2-mutant clone-specific antigen warranting further development as an immunotherapy target. Our study paves the way for selective targeting of the myelofibrosis clone and more broadly illustrates the power of single-cell multi-omics to discover tumor-specific therapeutic targets and mediators of tissue fibrosis.

cancer biology↗

bioRxiv2019

Heterogeneous disease-propagating stem cells in juvenile myelomonocytic leukemia

Juvenile Myelomonocytic Leukemia (JMML) is a poor prognosis childhood leukemia usually caused by germline or somatic RAS-activating mutations. The cellular hierarchy in JMML is poorly characterized, including the identity of leukemia stem cells (LSCs). FACS and single-cell RNA-sequencing reveal marked heterogeneity of JMML hematopoietic stem/progenitor cells (HSPCs), including an aberrant Lin-CD34+CD38-CD90+CD45RA+ population. Single-cell HSPC index-sorting and clonogenic assays show that (1) all somatic mutations can be backtracked to the phenotypic HSC compartment with RAS-activating mutations as a \"first hit\", (2) mutations are acquired with both linear and branching patterns of clonal evolution and (3) mutant HSPCs are present after allogeneic HSC transplant before molecular/clinical evidence of relapse. Stem cell assays reveal inter-patient heterogeneity of JMML-LSCs which are present in, but not confined to, the phenotypic HSC compartment. RNA-sequencing of JMML-LSCs reveals upregulation of stem cell and fetal genes (HLF, MEIS1, CNN3, VNN2, HMGA2) and candidate therapeutic targets/biomarkers (MTOR, SLC2A1, CD96) paving the way for LSC-directed disease monitoring and therapy in this disease.

cancer biology↗

bioRxiv2018

Unraveling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA-sequencing

Single-cell RNA-sequencing has emerged as a powerful tool to resolve transcriptional heterogeneity. However, its application to study cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells, which prevents correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single-cells from both genomic and coding DNA, in parallel with unbiased, high-depth whole transcriptome analysis. We demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasm stem/progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq provides a powerful tool to resolve molecular signatures of genetically distinct subclones of tumor cells.

genomics↗