AML associated oncofusion proteins PML-RARA, AML1-ETO and CBFB-MYH11 target RUNX/ETS-factor binding sites to modulate H3ac levels and drive leukemogenesis

Chromosomal translocations are one of the hallmarks of acute myeloid leukemia (AML), often leading to gene fusions and expression of an oncofusion protein. Over recent years it has become clear that most of the AML associated oncofusion proteins molecularly adopt distinct mechanisms for inducing leukemogenesis. Still these unique molecular properties of the chimeric proteins converge and give rise to a common pathogenic molecular mechanism. In the present study we compared genome-wide DNA binding and transcriptome data associated with AML1-ETO, CBFB-MYH11 and PML-RARA oncofusion protein expression to identify unique and common features. Our analyses revealed targeting of oncofusion binding sites to RUNX1 and ETS-factor occupied genomic regions. In addition, it revealed a highly comparable global histone acetylation pattern, similar expression of common target genes and related enrichment of several biological pathways critical for maintenance of AML, suggesting oncofusion proteins deregulate common gene programs despite their distinct binding signatures and mechanisms of action.Peer reviewe

Molecular subtypes of oropharyngeal cancer show distinct immune microenvironment related with immune checkpoint blockade response

Background: Oropharyngeal cancer (OPC) exhibits diverse immunological properties; however, their implications for immunotherapy are unknown. Methods: We analysed 37 surgically resected and nine recurrent or metastatic anti-programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1)-treated OPC tumours. OPCs were classified into immune-rich (IR), mesenchymal (MS) and xenobiotic (XB) subtypes based on RNA-sequencing data. Results: All IR type tumours were human papillomavirus (HPV) positive, most XB types were HPV negative, and MS types showed mixed HPV status. The IR type showed an enriched T cell exhaustion signature with PD-1+ CD8+ T cells and type I macrophages infiltrating the tumour nest on multiplex immunohistochemistry. The MS type showed an exclusion of CD8+ T cells from the tumour nest and high MS and tumour growth factor-β signatures. The XB type showed scant CD8+ T cell infiltration and focal CD73 expression. The IR type was associated with a favourable response signature during anti-PD-1/PD-L1 therapy and showed a high APOBEC mutation signature, whereas the MS and XB types showed resistance signature upregulation. Among anti-PD-1/PD-L1-treated OPC patients, the IR type showed a favourable clinical response (3/4 patients), whereas the XB type showed early progression (3/3 patients). Conclusion: Our analysis classified OPCs into three subtypes with distinct immune microenvironments that are potentially related to the response to anti-PD-1/PD-L1 therapy.ope

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles

Background: Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them. Methods: Lehman’s TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set. Results: We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug–target interactions were found among the upregulated genes in the M, IM and MSL subsets. Conclusions: Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets

HNF4A and GATA6 Loss Reveals Therapeutically Actionable Subtypes in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) can be divided into transcriptomic subtypes with two broad lineages referred to as classical (pancreatic) and squamous. We find that these two subtypes are driven by distinct metabolic phenotypes. Loss of genes that drive endodermal lineage specification, HNF4A and GATA6, switch metabolic profiles from classical (pancreatic) to predominantly squamous, with glycogen synthase kinase 3 beta (GSK3β) a key regulator of glycolysis. Pharmacological inhibition of GSK3β results in selective sensitivity in the squamous subtype; however, a subset of these squamous patient-derived cell lines (PDCLs) acquires rapid drug tolerance. Using chromatin accessibility maps, we demonstrate that the squamous subtype can be further classified using chromatin accessibility to predict responsiveness and tolerance to GSK3β inhibitors. Our findings demonstrate that distinct patterns of chromatin accessibility can be used to identify patient subgroups that are indistinguishable by gene expression profiles, highlighting the utility of chromatin-based biomarkers for patient selection in the treatment of PDAC

HNF4A and GATA6 loss reveals therapeutically actionable subtypes in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) can be divided into transcriptomic subtypes with two broad lineages referred to as classical (pancreatic) and squamous. We find that these two subtypes are driven by distinct metabolic phenotypes. Loss of genes that drive endodermal lineage specification, HNF4A and GATA6, switch metabolic profiles from classical (pancreatic) to predominantly squamous, with glycogen synthase kinase 3 beta (GSK3β) a key regulator of glycolysis. Pharmacological inhibition of GSK3β results in selective sensitivity in the squamous subtype; however, a subset of these squamous patient-derived cell lines (PDCLs) acquires rapid drug tolerance. Using chromatin accessibility maps, we demonstrate that the squamous subtype can be further classified using chromatin accessibility to predict responsiveness and tolerance to GSK3β inhibitors. Our findings demonstrate that distinct patterns of chromatin accessibility can be used to identify patient subgroups that are indistinguishable by gene expression profiles, highlighting the utility of chromatin-based biomarkers for patient selection in the treatment of PDAC

A computational framework for the comparative analysis of glioma models and patients

Diffuse Gliome bei Erwachsenen sind aggressive, unheilbare Hirntumore. Humanisierte Mausmodelle helfen, molekulare Mechanismen zu verstehen und therapeutische Ziele zu identifizieren, aber der Vergleich mit Proben von Patienten gestaltet sich schwierig. Ich habe eine computergestützte Plattform namens CAPE entwickelt, um Tumormodelle und Patienten-Expressionsprofile mit Hilfe der nicht-negativen Matrixfaktorisierung zu vergleichen. Die Anwendung von CAPE auf humanisierte Maus-Gliom-Avatar-Modelle (GSA) und diffuse Glioma-Patienten zeigte eine starke Übereinstimmung zwischen den Modellen und dem proneuralen Glioblastom-Subtyp. CAPE hat gezeigt, dass durch die Transplantation der Erwerb neuer Tumorzustände in den Modellen verbessert wurde. Durch die Kombination von reporterbasiertem genetischem Tracing und CAPE zeigte sich, dass eine Untergruppe der in vivo GSA-Populationen mit Patienten zusammenfällt, die astrozytische Merkmale aufweisen. Die Behandlung von GSA-Modellen in vitro mit menschlichem Serum, TNFα oder ionisierender Strahlung führte zu einer Verschiebung in den mesenchymalen Zustand. Einzelzell-Transkriptomik annotierte GSA-Populationen unter verschiedenen Bedingungen und zeigte alle Glioblastomzustände in vivo und bei Aktivierung durch externe Faktoren. Der Vergleich von GSA-Einzelzellpopulationen und Patienten bestätigte diese Identitäten. Die Studie etablierte einen umfassenden Rahmen für die Erprobung und Validierung von Verbesserungen der Tumormodelle, um Patienten besser abzubilden, und erweiterte das Verständnis der Tumorbiologie und Ansprechen auf Therapie.Adult-type diffuse gliomas are aggressive, incurable adult brain cancers. Humanized mouse models help understand molecular mechanisms and identify therapeutic targets, but comparing them with patient samples is difficult. I developed a computational framework, CAPE, for comparing tumor models and patient expression profiles using non-negative matrix factorization. Applying CAPE to humanized mouse glioma subtype avatar models (GSA) and adult-type diffuse glioma patients revealed a strong resemblance between models and proneural glioblastoma subtype. CAPE showed that transplantation improved new tumor state acquisition in models. Combining genetic tracing reporter phenotypic selection with CAPE showed a subset of in vivo GSA populations clustering with patients having astrocytic-like identities. In vitro treatment of GSA models with human serum, TNFα, or ionizing radiation led to a mesenchymal state shift upon reporter selection. Single-cell transcriptomics annotated GSA populations in different conditions, revealing all glioblastoma states in vivo and upon external factor activation. Comparing GSA single-cell populations and patients confirmed these identities. The study established a comprehensive framework for testing and validating tumor model improvements to resemble patients, advancing tumor biology and treatment response understanding

Induced pluripotent stem cell reporter systems for smooth muscle cell sheet engineering

Smooth muscle cells exist in many different locations within the body, including blood vessels and airways, where their principal function is contraction and relaxation. The heterogeneity of smooth muscle cells has been related to their embryological origins and could have implications in many diseases, including atherosclerosis, pulmonary hypertension, and asthma. Many of these diseases require an expandable cell source of smooth muscle cells for regenerative medicine or disease modeling. Here, we have developed Acta2hrGFP and ACTA2eGFP (GFP reporters for smooth muscle α-actin) reporter mouse and human induced pluripotent stem cells lines to track and isolate populations of smooth muscle-like cells. iPSCs were patterned to a KDR-expressing (kinase insert domain receptor) mesodermal progenitor, which was further specified towards a smooth muscle-like lineage through exposure to platelet derived growth factor (PDGF-BB) and transforming growth factor (TGF-β). The Acta2hrGFP+ or ACTA2eGFP+ cells were enriched for characteristic markers of smooth muscle cells, and these cells expressed low levels of contractile markers, reminiscent of an immature or synthetic smooth muscle cell. Aligned smooth muscle-like cell sheets were generated using these iPSC-derived populations in an enzymatically degradable hydrogel system. The cell sheets displayed mechanical behavior similar to native blood vessels, with the Acta2hrGFP+ cell sheets displaying a higher ultimate tensile strength than Acta2hrGFP- cell sheets. Furthermore, we performed global transcriptomic profiling of primary adult mouse lung vascular (Acta2hrGFP+ Cspg4DsRed+) and airway (Acta2hrGFP+ Cspg4DsRed-) smooth muscle cells from a double transgenic reporter mouse, where we identified distinct gene signatures of lung vascular SMCs and airway SMCs, with Hhip and Acta2 co-expression distinguishing airway SMCs from lung vascular SMCs. When comparing our miPSC-derived Acta2hrGFP+ cells to these primary SMC signatures, the in vitro derived cells cluster closer to aortic SMCs and lung vascular SMCs, but their transcriptomic signatures still remain significantly distinct. In addition, we have generated an Acta2hrGFP Cspg4DsRed reporter mouse iPSC line, which can be used to understand the signaling pathways involved in specification of these different smooth muscle cell subtypes. Thus, we have developed systems for isolating smooth muscle-like populations which have potential in tissue engineering applications, and we have identified gene signatures of adult lung vascular and airway smooth muscle cells to begin to address the heterogeneity of smooth muscle cell lineages