The role of stress-derived vesicles in the bystander effect and cancer related cachexia

Extracellular vesicles are small, lipid bound structures that are involved in intercellular signalling. They are known to be involved in numerous processes within the body, including in disease. One interesting function of EVs appears to be the induction of the bystander effect. The bystander effect refers to the non-targeted effects of stress, whereby stressed cells induce damage in neighbouring cells. EVs released from cells following irradiation have previously been shown to induce the bystander effect. EVs have also been implicated in the induction of cancer-cachexia, a muscle wasting disease. This disease is common in patients with cancer and is often linked to poor prognosis. In this project the ability of EVs released from heat shocked cells to induce bystander effects has been assessed. EVs released from cancer cells following 45°C treatment induced the bystander effect and the bystander cells were shown to be more resistant to subsequent stress treatment. EVs retained this functionality for up to two weeks when stored at -80°C. EVs released following short, 70°C treatment were also able to induce bystander effects. The ability of EVs from both stressed (cisplatin) and unstressed cancer cells to induce cachexia was also examined. Cancer EVs were able to reduce differentiation in vitro, but no effects were observed when these EVs were injected into mice. The proteome of these EVs and their parent cells was also identified via liquid chromatography-mass spectrometry and pathway analysis was carried out on these proteins. These data suggest possible roles for EVs in cell-cell communication during stress and disease, with EVs being able to induce bystander effects and alter muscle development in vitro

CKS1 inhibition depletes leukemic stem cells and protects healthy hematopoietic stem cells in acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive hematological disorder comprising a hierarchy of quiescent leukemic stem cells (LSCs) and proliferating blasts with limited self-renewal ability. AML has a dismal prognosis, with extremely low 2-year survival rates in the poorest cytogenetic risk patients, primarily due to the failure of intensive chemotherapy protocols to deplete LSCs and toxicity of therapy toward healthy hematopoietic cells. We studied the role of cyclin-dependent kinase regulatory subunit 1 (CKS1)-dependent protein degradation in primary human AML and healthy hematopoiesis xenograft models in vivo. Using a small-molecule inhibitor (CKS1i), we demonstrate a dual role for CKS1-dependent protein degradation in reducing patient-derived AML blasts in vivo and, importantly, depleting LSCs, whereas inhibition of CKS1 has the opposite effect on normal hematopoiesis, protecting normal hematopoietic stem cells from chemotherapeutic toxicity. Proteomic analysis of responses to CKS1i in our patient-derived xenograft mouse model demonstrate that inhibition of CKS1 in AML leads to hyper-activation of RAC1 and accumulation of lethal reactive oxygen species, whereas healthy hematopoietic cells enter quiescence in response to CKS1i, protecting hematopoietic stem cells. Together, these findings demonstrate that CKS1-dependent proteostasis is a key vulnerability in malignant stem cell biology.Peer reviewe

Germline ERCC excision repair 6 like 2 (ERCC6L2) mutations lead to impaired erythropoiesis and reshaping of the bone marrow microenvironment

Despite the inclusion of inherited myeloid malignancies as a separate entity in the World Health Organization Classification, many established predisposing loci continue to lack functional characterization. While germline mutations in the DNA repair factor ERCC excision repair 6 like 2 (ERCC6L2) give rise to bone marrow failure and acute myeloid leukaemia, their consequences on normal haematopoiesis remain unclear. To functionally characterise the dual impact of germline ERCC6L2 loss on human primary haematopoietic stem/progenitor cells (HSPCs) and mesenchymal stromal cells (MSCs), we challenged ERCC6L2-silenced and patient-derived cells ex vivo. Here, we show for the first time that ERCC6L2-deficiency in HSPCs significantly impedes their clonogenic potential and leads to delayed erythroid differentiation. This observation was confirmed by CIBERSORTx RNA-sequencing deconvolution performed on ERCC6L2-silenced erythroid-committed cells, which demonstrated higher proportions of polychromatic erythroblasts and reduced orthochromatic erythroblasts versus controls. In parallel, we demonstrate that the consequences of ERCC6L2-deficiency are not limited to HSPCs, as we observe a striking phenotype in patient-derived and ERCC6L2-silenced MSCs, which exhibit enhanced osteogenesis and suppressed adipogenesis. Altogether, our study introduces a valuable surrogate model to study the impact of inherited myeloid mutations and highlights the importance of accounting for the influence of germline mutations in HSPCs and their microenvironment.Peer reviewe

Integrative phosphoproteomics defines two biologically distinct groups of KMT2A rearranged acute myeloid leukaemia with different drug response phenotypes

Acute myeloid leukaemia (AML) patients harbouring certain chromosome abnormalities have particularly adverse prognosis. For these patients, targeted therapies have not yet made a significant clinical impact. To understand the molecular landscape of poor prognosis AML we profiled 74 patients from two different centres (in UK and Finland) at the proteomic, phosphoproteomic and drug response phenotypic levels. These data were complemented with transcriptomics analysis for 39 cases. Data integration highlighted a phosphoproteomics signature that define two biologically distinct groups of KMT2A rearranged leukaemia, which we term MLLGA and MLLGB. MLLGA presented increased DOT1L phosphorylation, HOXA gene expression, CDK1 activity and phosphorylation of proteins involved in RNA metabolism, replication and DNA damage when compared to MLLGB and no KMT2A rearranged samples. MLLGA was particularly sensitive to 15 compounds including genotoxic drugs and inhibitors of mitotic kinases and inosine-5-monosphosphate dehydrogenase (IMPDH) relative to other cases. Intermediate-risk KMT2A-MLLT3 cases were mainly represented in a third group closer to MLLGA than to MLLGB. The expression of IMPDH2 and multiple nucleolar proteins was higher in MLLGA and correlated with the response to IMPDH inhibition in KMT2A rearranged leukaemia, suggesting a role of the nucleolar activity in sensitivity to treatment. In summary, our multilayer molecular profiling of AML with poor prognosis and KMT2A-MLLT3 karyotypes identified a phosphoproteomics signature that defines two biologically and phenotypically distinct groups of KMT2A rearranged leukaemia. These data provide a rationale for the potential development of specific therapies for AML patients characterised by the MLLGA phosphoproteomics signature identified in this study.Peer reviewe

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis

Background: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management.Objective: To develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.Methods: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.Results: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.Limitations: This was a retrospective 4-centre study and larger prospective multicentre studies are now required.Conclusion: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type Diffuse Large B Cell Lymphoma

Despite the effectiveness of immuno-chemotherapy, 40\cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focussed attention on the changes in gene expression profile accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo DLBCL patients. Cell of origin remained stable from diagnosis to relapse in 80\ with only a single patient showing COO switching from ABC to GCB. Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes, that defined clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of \lt;60-year-old patients with superior PFS and OS treated with Ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials

ACSNI: An unsupervised machine-learning tool for prediction of tissue-specific pathway components using gene expression profiles

Summary: Determining the tissue- and disease-specific circuit of biological pathways remains a fundamental goal of molecular biology. Many components of these biological pathways still remain unknown, hindering the full and accurate characterization of biological processes of interest. Here we describe ACSNI, an algorithm that combines prior knowledge of biological processes with a deep neural network to effectively decompose gene expression profiles (GEPs) into multi-variable pathway activities and identify unknown pathway components. Experiments on public GEP data show that ACSNI predicts cogent components of mTOR, ATF2, and HOTAIRM1 signaling that recapitulate regulatory information from genetic perturbation and transcription factor binding datasets. Our framework provides a fast and easy-to-use method to identify components of signaling pathways as a tool for molecular mechanism discovery and to prioritize genes for designing future targeted experiments (https://github.com/caanene1/ACSNI). The bigger picture: Methods that group genes into functional units to quantify pathway activities are critical in the analysis of biological systems. Although many components of biological pathways have been described in detail, these tend to be limited to well-studied genes. In contrast, the majority of possible components remain unexplored. Here, we present a machine-learning tool for constructing and predicting tissue-specific components of biological pathways from large biological datasets. Our algorithm, ACSNI, can tackle incomplete pathway descriptions and enhance current pathway analysis methods' performance. We anticipate that, by dissecting the complex signals in biological data in a flexible and context-specific manner, ACSNI can facilitate the full characterization of physiological systems of interest

A frameshift variant in specificity protein 1 triggers superactivation of Sp1-mediated transcription in familial bone marrow failure

Inherited bone marrow failure (BMF) syndromes are a heterogeneous group of diseases characterized by defective hematopoiesis and often predisposing to myelodysplastic syndrome (MDS) and acute myelogenous leukemia. We have studied a large family consisting of several affected individuals with hematologic abnormalities, including one family member who died of acute leukemia. By whole-exome sequencing, we identified a novel frameshift variant in the ubiquitously expressed transcription factor specificity protein 1 (SP1). This heterozygous variant (c.1995delA) truncates the canonical Sp1 molecule in the highly conserved C-terminal DNA-binding zinc finger domains. Transcriptomic analysis and gene promoter characterization in patients’ blood revealed a hypermorphic effect of this Sp1 variant, triggering superactivation of Sp1-mediated transcription and driving significant up-regulation of Sp1 target genes. This familial genetic study indicates a central role for Sp1 in causing autosomal dominant transmission of BMF, thereby confirming its critical role in hematopoiesis in humans