Transcriptional variability accelerates preleukemia by cell diversification and perturbation of protein synthesis.

Transcriptional variability facilitates stochastic cell diversification and can in turn underpin adaptation to stress or injury. We hypothesize that it may analogously facilitate progression of premalignancy to cancer. To investigate this, we initiated preleukemia in mouse cells with enhanced transcriptional variability due to conditional disruption of the histone lysine acetyltransferase gene Kat2a. By combining single-cell RNA sequencing of preleukemia with functional analysis of transformation, we show that Kat2a loss results in global variegation of cell identity and accumulation of preleukemic cells. Leukemia progression is subsequently facilitated by destabilization of ribosome biogenesis and protein synthesis, which confer a transient transformation advantage. The contribution of transcriptional variability to early cancer evolution reflects a generic role in promoting cell fate transitions, which, in the case of well-adapted malignancies, contrastingly differentiates and depletes cancer stem cells. That is, transcriptional variability confers forward momentum to cell fate systems, with differential multistage impact throughout cancer evolution.

KAT2A complexes ATAC and SAGA play unique roles in cell maintenance and identity in hematopoiesis and leukemia.

Epigenetic histone modifiers are key regulators of cell fate decisions in normal and malignant hematopoiesis. Their enzymatic activities are of particular significance as putative therapeutic targets in leukemia. In contrast, less is known about the contextual role in which those enzymatic activities are exercised and specifically how different macromolecular complexes configure the same enzymatic activity with distinct molecular and cellular consequences. We focus on KAT2A, a lysine acetyltransferase responsible for histone H3 lysine 9 acetylation, which we recently identified as a dependence in acute myeloid leukemia stem cells and that participates in 2 distinct macromolecular complexes: Ada two-A-containing (ATAC) and Spt-Ada-Gcn5-Acetyltransferase (SAGA). Through analysis of human cord blood hematopoietic stem cells and progenitors, and of myeloid leukemia cells, we identify unique respective contributions of the ATAC complex to regulation of biosynthetic activity in undifferentiated self-renewing cells and of the SAGA complex to stabilization or correct progression of cell type-specific programs with putative preservation of cell identity. Cell type and stage-specific dependencies on ATAC and SAGA-regulated programs explain multilevel KAT2A requirements in leukemia and in erythroid lineage specification and development. Importantly, they set a paradigm against which lineage specification and identity can be explored across developmental stem cell systems.

The Cancer Therapy-Related Clonal Hematopoiesis Driver Gene Ppm1d Promotes Inflammation and Non-Ischemic Heart Failure in Mice.

[Figure: see text].

Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells.

Acute Myeloid Leukemia (AML) is an aggressive hematological malignancy with abnormal progenitor self-renewal and defective white blood cell differentiation. Its pathogenesis comprises subversion of transcriptional regulation, through mutation and by hijacking normal chromatin regulation. Kat2a is a histone acetyltransferase central to promoter activity, that we recently associated with stability of pluripotency networks, and identified as a genetic vulnerability in AML. Through combined chromatin profiling and single-cell transcriptomics of a conditional knockout mouse, we demonstrate that Kat2a contributes to leukemia propagation through preservation of leukemia stem-like cells. Kat2a loss impacts transcription factor binding and reduces transcriptional burst frequency in a subset of gene promoters, generating enhanced variability of transcript levels. Destabilization of target programs shifts leukemia cell fate out of self-renewal into differentiation. We propose that control of transcriptional variability is central to leukemia stem-like cell propagation, and establish a paradigm exploitable in different tumors and distinct stages of cancer evolution.

Less than 30% of patients with acute myeloid leukaemia ­ an aggressive cancer of the white blood cells ­ survive five years post-diagnosis. This disease disrupts the maturation of white blood cells, resulting in the accumulation of immature cells that multiply and survive but are incapable of completing their maturation process. Amongst these, a group of cancer cells known as leukemic stem cells is responsible for continually replenishing the leukaemia, thus perpetuating its growth. Cancers develop when cells in the body acquire changes or mutations to their genetic makeup. The mutations that lead to acute myeloid leukaemia often affect the activity of genes known as epigenetic regulators. These genes regulate which proteins and other molecules cells make by controlling the way in which cells 'read' their genetic instructions. The epigenetic regulator Kat2a is thought to 'tune' the frequency at which cells read their genetic instructions. This tuning mechanism decreases random fluctuations in the execution of the instructions cells receive to make proteins and other molecules. In turn, this helps to ensure that individual cells of the same type behave in a similar way, for example by keeping leukaemia cells in an immature state. Here, Domingues, Kulkarni et al. investigated whether interfering with Kat2a can make acute myeloid leukaemia less aggressive by allowing the immature white blood cells to mature. Domingues, Kulkarni et al. genetically engineered mice to remove Kat2a from blood cells on demand and then inserted a mutation that causes acute myeloid leukaemia. The experiments showed that the loss of Kat2a delayed the development of leukaemia in the mice and progressively depleted leukaemia stem cells, causing the disease to become less aggressive. The results also showed that loss of Kat2a caused more fluctuations in how the white blood cells read their genetic code, which resulted in more variability in the molecules they produced and increased the tendency of the cells to mature. These findings establish that loss of Kat2a causes leukaemia stem cells to mature and stop multiplying by untuning the frequency at which the cells read their genetic instructions. In the future, it may be possible to develop drugs that target human KAT2A to treat acute myeloid leukaemia.

Histone Acetyltransferase KAT2A Stabilizes Pluripotency with Control of Transcriptional Heterogeneity.

Cell fate transitions in mammalian stem cell systems have often been associated with transcriptional heterogeneity; however, existing data have failed to establish a functional or mechanistic link between the two phenomena. Experiments in unicellular organisms support the notion that transcriptional heterogeneity can be used to facilitate adaptability to environmental changes and have identified conserved chromatin-associated factors that modulate levels of transcriptional noise. Herein, we show destabilization of pluripotency-associated gene regulatory networks through increased transcriptional heterogeneity of mouse embryonic stem cells in which paradigmatic histone acetyl-transferase, and candidate noise modulator, Kat2a (yeast orthologue Gcn5), have been inhibited. Functionally, network destabilization associates with reduced pluripotency and accelerated mesendodermal differentiation, with increased probability of transitions into lineage commitment. Thus, we show evidence of a relationship between transcriptional heterogeneity and cell fate transitions through manipulation of the histone acetylation landscape of mouse embryonic stem cells, suggesting a general principle that could be exploited in other normal and malignant stem cell fate transitions. Stem Cells 2018;36:1828-11.

A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is an aggressive cancer with a poor prognosis, for which mainstream treatments have not changed for decades. To identify additional therapeutic targets in AML, we optimize a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening platform and use it to identify genetic vulnerabilities in AML cells. We identify 492 AML-specific cell-essential genes, including several established therapeutic targets such as DOT1L, BCL2, and MEN1, and many other genes including clinically actionable candidates. We validate selected genes using genetic and pharmacological inhibition, and chose KAT2A as a candidate for downstream study. KAT2A inhibition demonstrated anti-AML activity by inducing myeloid differentiation and apoptosis, and suppressed the growth of primary human AMLs of diverse genotypes while sparing normal hemopoietic stem-progenitor cells. Our results propose that KAT2A inhibition should be investigated as a therapeutic strategy in AML and provide a large number of genetic vulnerabilities of this leukemia that can be pursued in downstream studies.

Identification of new interacting partners for atypical Rho GTPases: a SILAC-based approach.

In contrast to typical Rho GTPases the regulation of atypical Rho GTPases, such as the members of the RhoBTB subfamily, rarely depends on GEFs and/or GAPs. Instead, they are regulated at the level of their expression, by post-translational modifications, by their rate of degradation as well as through binding of diverse cell-specific interactors. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) is a powerful cutting-edge mass-spectrometry-based technology allowing for protein-interaction studies in vitro with removal of false-positive identifications. In this chapter, we describe how the SILAC technology can be applied to the identification of new interacting partners for atypical - constitutively active - Rho GTPases, i.e. RhoBTB3.

Monitoring of atmospheric ozone and nitrogen dioxide over the south of Portugal by ground-based and satellite observations.

The SPATRAM (Spectrometer for Atmospheric TRAcers Monitoring) instrument has been developed as a result of the collaboration between CGE-UE, ISAC-CNR and Italian National Agency for New Technologies, Energy and the Environment (ENEA). SPATRAM is a multi-purpose UV-Vis-scanning spectrometer (250 - 950 nm) and it is installed at the Observatory of the CGE, in Evora, since April 2004. A brief description of the instrument is given, highlighting the technological innovations with respect to the previous version of similar equipment. The need for such measurements automatically taken on a routine basis in south-western European regions, specifically in Portugal, has encouraged the development and installation of the equipment and constitutes a major driving force for the present work. The main features and some improvements introduced in the DOAS (Differential Optical Absorption Spectroscopy) algorithms are discussed. The results obtained applying DOAS methodology to the SPATRAM spectrometer measurements of diffused spectral sky radiation are presented in terms of diurnal and seasonal variations of nitrogen dioxide (NO(2)) and ozone (O(3)). NO(2) confirms the typical seasonal cycle reaching the maximum of (6.5 +/- 0.3) x 10(+15) molecules cm(-2) for the sunset values (PM), during the summer season, and the minimum of (1.55 +/- 0.07) x 10(+15) molecules cm(-2) for the sunrise values (AM) in winter. O(3) presents the maximum total column of (433 +/- 5) Dobson Unit (DU) in the spring season and the minimum of (284 +/- 3) DU during the fall period. The huge daily variations of the O(3) total column during the spring season are analyzed and discussed. The ground-based results obtained for NO(2) and O(3) column contents are compared with data from satellite-borne equipment (GOME - Global Ozone Monitoring Experiment; SCIAMACHY - Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY; TOMS - Total Ozone Monitoring Spectrometer) and it is shown that the two data sets are in good agreement. The correlation coefficient for the comparison of the ground-based/satellite data for O(3) is of 0.97.