Defining an Optimized Workflow for Enriching and Analyzing Residual Tumor Populations Using Intracellular Markers.

Tumor relapse is well recognized to arise from treatment-resistant residual populations. Strategies enriching such populations for in-depth downstream analyses focus on tumor-specific surface markers; however, enrichment using intracellular biomarkers remains challenging. Using B-cell lymphoma as an exemplar, we demonstrate feasibility to enrich B-cell lymphoma 2 (BCL2)high populations, a surrogate marker for t(14;18)+ lymphomas, for use in downstream applications. Different fixation protocols were assessed for impact on antibody expression and RNA integrity; glyoxal fixation demonstrated superior results regarding minimal effects on surface and intracellular expression, and RNA quality, compared with alternative fixatives evaluated. Furthermore, t(14;18)+ B cells were effectively detected using intracellular BCL2 overexpression to facilitate tumor cell enrichment. Tumor cell populations were enriched using the cellenONE F1.4 single-cell sorting platform, which detected and dispensed BCL2high-expressing cells directly into library preparation reagents for transcriptome analyses. Sorted glyoxal-fixed cells generated good quality sequencing libraries, with high concordance between live and fixed single-cell transcriptomic profiles, discriminating cell populations predominantly on B-cell biology. Overall, we successfully developed a proof-of-concept workflow employing a robust cell preparation protocol for intracellular markers combined with cell enrichment using the cellenONE platform, providing an alternative to droplet-based technologies when cellular input is low or requires prior enrichment to detect rare populations. This workflow has wider prognostic and therapeutic potential to study residual cells in a pan-cancer setting.

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multigene 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 tumors at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile 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 nonmetastasizing and 86 metastasizing) were collected retrospectively from four centers. 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-center study and larger prospective multicenter studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC.

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.

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% of patients with diffuse large B-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 focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell-like (ABC) to germinal center B-cell-like (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 <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.

The transcription factor DDIT3 is a potential driver of dyserythropoiesis in myelodysplastic syndromes.

Myelodysplastic syndromes (MDS) are hematopoietic stem cell (HSC) malignancies characterized by ineffective hematopoiesis, with increased incidence in older individuals. Here we analyze the transcriptome of human HSCs purified from young and older healthy adults, as well as MDS patients, identifying transcriptional alterations following different patterns of expression. While aging-associated lesions seem to predispose HSCs to myeloid transformation, disease-specific alterations may trigger MDS development. Among MDS-specific lesions, we detect the upregulation of the transcription factor DNA Damage Inducible Transcript 3 (DDIT3). Overexpression of DDIT3 in human healthy HSCs induces an MDS-like transcriptional state, and dyserythropoiesis, an effect associated with a failure in the activation of transcriptional programs required for normal erythroid differentiation. Moreover, DDIT3 knockdown in CD34+ cells from MDS patients with anemia is able to restore erythropoiesis. These results identify DDIT3 as a driver of dyserythropoiesis, and a potential therapeutic target to restore the inefficient erythroid differentiation characterizing MDS patients.

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.

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 hyperactivation 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.

Genome-wide whole-blood transcriptome profiling across inherited bone marrow failure subtypes.

Gene expression profiling has long been used in understanding the contribution of genes and related pathways in disease pathogenesis and susceptibility. We have performed whole-blood transcriptomic profiling in a subset of patients with inherited bone marrow failure (IBMF) whose diseases are clinically and genetically characterized as Fanconi anemia (FA), Shwachman-Diamond syndrome (SDS), and dyskeratosis congenita (DC). We hypothesized that annotating whole-blood transcripts genome wide will aid in understanding the complexity of gene regulation across these IBMF subtypes. Initial analysis of these blood-derived transcriptomes revealed significant skewing toward upregulated genes in patients with FA when compared with controls. Patients with SDS or DC also showed similar skewing profiles in their transcriptional status revealing a common pattern across these different IBMF subtypes. Gene set enrichment analysis revealed shared pathways involved in protein translation and elongation (ribosome constituents), RNA metabolism (nonsense-mediated decay), and mitochondrial function (electron transport chain). We further identified a discovery set of 26 upregulated genes at stringent cutoff (false discovery rate < 0.05) that appeared as a unified signature across the IBMF subtypes. Subsequent transcriptomic analysis on genetically uncharacterized patients with BMF revealed a striking overlap of genes, including 22 from the discovery set, which indicates a unified transcriptional drive across the classic (FA, SDS, and DC) and uncharacterized BMF subtypes. This study has relevance in disease pathogenesis, for example, in explaining the features (including the BMF) common to all patients with IBMF and suggests harnessing this transcriptional signature for patient benefit.

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

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).

KDM5 inhibition offers a novel therapeutic strategy for the treatment of KMT2D mutant lymphomas.

Loss-of-function mutations in KMT2D are a striking feature of germinal center (GC) lymphomas, resulting in decreased histone 3 lysine 4 (H3K4) methylation and altered gene expression. We hypothesized that inhibition of the KDM5 family, which demethylates H3K4me3/me2, would reestablish H3K4 methylation and restore the expression of genes repressed on loss of KMT2D. KDM5 inhibition increased H3K4me3 levels and caused an antiproliferative response in vitro, which was markedly greater in both endogenous and gene-edited KMT2D mutant diffuse large B-cell lymphoma cell lines, whereas tumor growth was inhibited in KMT2D mutant xenografts in vivo. KDM5 inhibition reactivated both KMT2D-dependent and -independent genes, resulting in diminished B-cell signaling and altered expression of B-cell lymphoma 2 (BCL2) family members, including BCL2 itself. KDM5 inhibition may offer an effective therapeutic strategy for ameliorating KMT2D loss-of-function mutations in GC lymphomas.

The Genomic Landscape of Actinic Keratosis.

Actinic keratoses (AKs) are lesions of epidermal keratinocyte dysplasia and are precursors for invasive cutaneous squamous cell carcinoma (cSCC). Identifying the specific genomic alterations driving the progression from normal skin to skin with AK to skin with invasive cSCC is challenging because of the massive UVR-induced mutational burden characteristic at all stages of this progression. In this study, we report the largest AK whole-exome sequencing study to date and perform a mutational signature and candidate driver gene analysis on these lesions. We demonstrate in 37 AKs from both immunosuppressed and immunocompetent patients that there are significant similarities between AKs and cSCC in terms of mutational burden, copy number alterations, mutational signatures, and patterns of driver gene mutations. We identify 44 significantly mutated AK driver genes and confirm that these genes are similarly altered in cSCC. We identify azathioprine mutational signature in all AKs from patients exposed to the drug, providing further evidence for its role in keratinocyte carcinogenesis. cSCCs differ from AKs in having higher levels of intrasample heterogeneity. Alterations in signaling pathways also differ, with immune-related signaling and TGFß signaling significantly more mutated in cSCC. Integrating our findings with independent gene expression datasets confirms that dysregulated TGFß signaling may represent an important event in AK‒cSCC progression.

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.

The complex genetic landscape of familial MDS and AML reveals pathogenic germline variants.

The inclusion of familial myeloid malignancies as a separate disease entity in the revised WHO classification has renewed efforts to improve the recognition and management of this group of at risk individuals. Here we report a cohort of 86 acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) families with 49 harboring germline variants in 16 previously defined loci (57%). Whole exome sequencing in a further 37 uncharacterized families (43%) allowed us to rationalize 65 new candidate loci, including genes mutated in rare hematological syndromes (ADA, GP6, IL17RA, PRF1 and SEC23B), reported in prior MDS/AML or inherited bone marrow failure series (DNAH9, NAPRT1 and SH2B3) or variants at novel loci (DHX34) that appear specific to inherited forms of myeloid malignancies. Altogether, our series of MDS/AML families offer novel insights into the etiology of myeloid malignancies and provide a framework to prioritize variants for inclusion into routine diagnostics and patient management.

Applications and analysis of targeted genomic sequencing in cancer studies.

Next Generation Sequencing (NGS) has dramatically improved the flexibility and outcomes of cancer research and clinical trials, providing highly sensitive and accurate high-throughput platforms for large-scale genomic testing. In contrast to whole-genome (WGS) or whole-exome sequencing (WES), targeted genomic sequencing (TS) focuses on a panel of genes or targets known to have strong associations with pathogenesis of disease and/or clinical relevance, offering greater sequencing depth with reduced costs and data burden. This allows targeted sequencing to identify low frequency variants in targeted regions with high confidence, thus suitable for profiling low-quality and fragmented clinical DNA samples. As a result, TS has been widely used in clinical research and trials for patient stratification and the development of targeted therapeutics. However, its transition to routine clinical use has been slow. Many technical and analytical obstacles still remain and need to be discussed and addressed before large-scale and cross-centre implementation. Gold-standard and state-of-the-art procedures and pipelines are urgently needed to accelerate this transition. In this review we first present how TS is conducted in cancer research, including various target enrichment platforms, the construction of target panels, and selected research and clinical studies utilising TS to profile clinical samples. We then present a generalised analytical workflow for TS data discussing important parameters and filters in detail, aiming to provide the best practices of TS usage and analyses.

Extracellular vesicles released following heat stress induce bystander effect in unstressed populations.

Cells naïve to stress can display the effects of stress, such as DNA damage and apoptosis, when they are exposed to signals from stressed cells; this phenomenon is known as the bystander effect. We previously showed that bystander effect induced by ionising radiation are mediated by extracellular vesicles (EVs). Bystander effect can also be induced by other types of stress, including heat shock, but it is unclear whether EVs are involved. Here we show that EVs released from heat shocked cells are also able to induce bystander damage in unstressed populations. Naïve cells treated with media conditioned by heat shocked cells showed higher levels of DNA damage and apoptosis than cells treated with media from control cells. Treating naïve cells with EVs derived from media conditioned by heat shocked cells also induced a bystander effect when compared to control, with DNA damage and apoptosis increasing whilst the level of cell viability was reduced. We demonstrate that treatment of naïve cells with heat shocked cell-derived EVs leads to greater invasiveness in a trans-well Matrigel assay. Finally, we show that naïve cells treated with EVs from heat-shocked cells are more likely to survive a subsequent heat shock, suggesting that these EVs mediate an adaptive response. We propose that EVs released following stress mediate an intercellular response that leads to apparent stress in neighbouring cells but also greater robustness in the face of a subsequent insult.

RNAi2015 - Ten years of RNAi Oxford.

The tenth RNAi conference was held at St. Hilda's College Oxford on the 24-26 March 2015. The conference offered researchers from all over the world the chance to present, discuss and discover work pertaining to the field of RNAi. RNAi has become an essential technique in genomic research for functional validation as well as an exciting avenue to explore in therapeutic medicine. Emerging techniques such as CRISPR as well as improvements in efficiency of existing techniques and expansions in libraries have cemented the importance of RNAi at the cutting edge of research. Featured presentations and posters showcased recent research in the field ranging from RNA detection in bio fluids through to potential oligonucleotide therapies.

Meta-analysis using a novel database, miRStress, reveals miRNAs that are frequently associated with the radiation and hypoxia stress-responses.

Organisms are often exposed to environmental pressures that affect homeostasis, so it is important to understand the biological basis of stress-response. Various biological mechanisms have evolved to help cells cope with potentially cytotoxic changes in their environment. miRNAs are small non-coding RNAs which are able to regulate mRNA stability. It has been suggested that miRNAs may tip the balance between continued cytorepair and induction of apoptosis in response to stress. There is a wealth of data in the literature showing the effect of environmental stress on miRNAs, but it is scattered in a large number of disparate publications. Meta-analyses of this data would produce added insight into the molecular mechanisms of stress-response. To facilitate this we created and manually curated the miRStress database, which describes the changes in miRNA levels following an array of stress types in eukaryotic cells. Here we describe this database and validate the miRStress tool for analysing miRNAs that are regulated by stress. To validate the database we performed a cross-species analysis to identify miRNAs that respond to radiation. The analysis tool confirms miR-21 and miR-34a as frequently deregulated in response to radiation, but also identifies novel candidates as potentially important players in this stress response, including miR-15b, miR-19b, and miR-106a. Similarly, we used the miRStress tool to analyse hypoxia-responsive miRNAs. The most frequently deregulated miRNAs were miR-210 and miR-21, as expected. Several other miRNAs were also found to be associated with hypoxia, including miR-181b, miR-26a/b, miR-106a, miR-213 and miR-192. Therefore the miRStress tool has identified miRNAs with hitherto unknown or under-appreciated roles in the response to specific stress types. The miRStress tool, which can be used to uncover new insight into the biological roles of miRNAs, and also has the potential to unearth potential biomarkers for therapeutic response, is freely available at http://mudshark.brookes.ac.uk/MirStress.