Determination of complex subclonal structures of hematological malignancies by multiplexed genotyping of blood progenitor colonies.

Current next-generation sequencing (NGS) technologies allow unprecedented insights into the mutational profiles of tumors. Recent studies in myeloproliferative neoplasms have further demonstrated that, not only the mutational profile, but also the order in which these mutations are acquired is relevant for our understanding of the disease. Our ability to assign mutation order from NGS data alone is, however, limited. Here, we present a strategy of highly multiplexed genotyping of burst forming unit-erythroid colonies based on NGS results to assess subclonal tumor structure. This allowed for the generation of complex clonal hierarchies and determination of order of mutation acquisition far more accurately than was possible from NGS data alone.Work in ARG lab has been supported by the Leukemia and Lymphoma Society (grant 7001-12), the National Institute of Health Research (grant NF-SI-0512-10079) and core support grants by the MRC and Wellcome Trust to the Cambridge Institute for Medical Research (100140/Z/12/Z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z). Work in ARG's laboratory has in addition been supported by Cancer Research UK (grants C1163/A12765 and C1163/A21762), Bloodwise (grant 13003) and the Wellcome Trust (grant 104710/Z/14/Z

MARIMO cells harbor a CALR mutation but are not dependent on JAK2/STAT5 signaling.

Work in the Green lab is supported by Leukemia and Lymphoma Research, Cancer Research UK, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre, and the Leukemia and Lymphoma Society of America. WW is supported by the Austrian Science Foundation (J 3578-B21). JN is supported by a Kay Kendall Leukaemia Clinical Fellowship.This is the final published version. It first appeared at http://www.nature.com/leu/journal/vaop/ncurrent/full/leu2014285a.html

The C allele of JAK2 rs4495487 is an additional candidate locus that contributes to myeloproliferative neoplasm predisposition in the Japanese population

<p>Abstract</p> <p>Background</p> <p>Polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF) are myeloproliferative neoplasms (MPNs) characterized in most cases by a unique somatic mutation, <it>JAK2 </it>V617F. Recent studies revealed that <it>JAK2 </it>V617F occurs more frequently in a specific <it>JAK2 </it>haplotype, named <it>JAK2 </it>46/1 or GGCC haplotype, which is tagged by rs10974944 (C/G) and/or rs12343867 (T/C). This study examined the impact of single nucleotide polymorphisms (SNPs) of the <it>JAK2 </it>locus on MPNs in a Japanese population.</p> <p>Methods</p> <p>We sequenced 24 <it>JAK2 </it>SNPs in Japanese patients with PV. We then genotyped 138 MPN patients (33 PV, 96 ET, and 9 PMF) with known <it>JAK2 </it>mutational status and 107 controls for a novel SNP, in addition to two SNPs known to be part of the 46/1 haplotype (rs10974944 and rs12343867). Associations with risk of MPN were estimated by odds ratios and their 95% confidence intervals using logistic regression.</p> <p>Results</p> <p>A novel locus, rs4495487 (T/C), with a mutated T allele was significantly associated with PV. Similar to rs10974944 and rs12343867, rs4495487 in the <it>JAK2 </it>locus is significantly associated with <it>JAK2</it>-positive MPN. Based on the results of SNP analysis of the three <it>JAK2 </it>locus, we defined the "GCC genotype" as having at least one minor allele in each SNP (G allele in rs10974944, C allele in rs4495487, and C allele in rs12343867). The GCC genotype was associated with increased risk of both <it>JAK2 </it>V617F-positive and <it>JAK2 </it>V617F-negative MPN. In ET patients, leukocyte count and hemoglobin were significantly associated with <it>JAK2 </it>V617F, rather than the GCC genotype. In contrast, none of the <it>JAK2 </it>V617F-negative ET patients without the GCC genotype had thrombosis, and splenomegaly was frequently seen in this subset of ET patients. PV patients without the GCC genotype were significantly associated with high platelet count.</p> <p>Conclusions</p> <p>Our results indicate that the C allele of <it>JAK2 </it>rs4495487, in addition to the 46/1 haplotype, contributes significantly to the occurrence of <it>JAK2 </it>V617F-positive and <it>JAK2 </it>V617F-negative MPNs in the Japanese population. Because lack of the GCC genotype represents a distinct clinical-hematological subset of MPN, analyzing <it>JAK2 </it>SNPs and quantifying <it>JAK2 </it>V617F mutations will provide further insights into the molecular pathogenesis of MPN.</p

A novel signalling screen demonstrates that CALR mutations activate essential MAPK signalling and facilitate megakaryocyte differentiation.

Most MPN patients lacking JAK2 mutations harbour somatic CALR mutations that are thought to activate cytokine signalling although the mechanism is unclear. To identify kinases important for survival of CALR-mutant cells we developed a novel strategy (KISMET) which utilises the full range of kinase selectivity data available from each inhibitor and thus takes advantage of off-target noise that limits conventional siRNA or inhibitor screens. KISMET successfully identified known essential kinases in haematopoietic and non-haematopoietic cell lines and identified the MAPK pathway as required for growth of the CALR-mutated MARIMO cells. Expression of mutant CALR in murine or human haematopoietic cell lines was accompanied by MPL-dependent activation of MAPK signalling, and MPN patients with CALR mutations showed increased MAPK activity in CD34-cells, platelets and megakaryocytes. Although CALR mutations resulted in protein instability and proteosomal degradation, mutant CALR was able to enhance megakaryopoiesis and pro-platelet production from human CD34+ progenitors. These data link aberrant MAPK activation to the MPN phenotype and identify it as a potential therapeutic target in CALR-mutant positive MPNs.Leukemia accepted article preview online, 14 October 2016. doi:10.1038/leu.2016.280.Work in the Green lab is supported by Leukemia and Lymphoma Research, Cancer Research UK, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the Leukemia & Lymphoma Society of America. WW is supported by the Austrian Science Foundation (J 3578-B21). CGA is supported by Kay Kendall Leukaemia Fund clinical research fellowship. UM is supported by a Cancer Research UK Clinician Scientist Fellowship. Work in the Huntly lab is supported by the European Research Council, the MRC (UK), Bloodwise, the Cambridge NIHR funded BRC, KKLF and a WT/MRC Stem Cell centre grant. Work in the Green and Huntly Labs is supported by core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research (100140/z/12/z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z)

Mathematical Modelling as a Proof of Concept for MPNs as a Human Inflammation Model for Cancer Development

<p><b>Left:</b> Typical development in stem cells (top panel A) and mature cells (bottom panel B). Healthy hematopoietic cells (full blue curves) dominate in the early phase where the number of malignant cells (stipulated red curves) are few. The total number of cells is also shown (dotted green curves). When a stem cell mutates without repairing mechanisms, a slowly increasing exponential growth starts. At a certain stage, the malignant cells become dominant, and the healthy hematopoietic cells begin to show a visible decline. Finally, the composition between the cell types results in a takeover by the malignant cells, leading to an exponential decline in hematopoietic cells and ultimately their extinction. The development is driven by an approximately exponential increase in the MPN stem cells, and the development is closely followed by the mature MPN cells. <b>Right:</b> B)The corresponding allele burden (7%, 33% and 67% corresponding to ET, PV, and PMF, respectively) defined as the ratio of MPN mature cells to the total number of mature cells.</p

Glycan labeling strategies and their use in identification and quantification

Most methods for the analysis of oligosaccharides from biological sources require a glycan derivatization step: glycans may be derivatized to introduce a chromophore or fluorophore, facilitating detection after chromatographic or electrophoretic separation. Derivatization can also be applied to link charged or hydrophobic groups at the reducing end to enhance glycan separation and mass-spectrometric detection. Moreover, derivatization steps such as permethylation aim at stabilizing sialic acid residues, enhancing mass-spectrometric sensitivity, and supporting detailed structural characterization by (tandem) mass spectrometry. Finally, many glycan labels serve as a linker for oligosaccharide attachment to surfaces or carrier proteins, thereby allowing interaction studies with carbohydrate-binding proteins. In this review, various aspects of glycan labeling, separation, and detection strategies are discussed

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

The role of JAK/STAT signalling in the pathogenesis, prognosis and treatment of solid tumours

Aberrant activation of intracellular signalling pathways confers malignant properties on cancer cells. Targeting intracellular signalling pathways has been a productive strategy for drug development, with several drugs acting on signalling pathways already in use and more continually being developed. The JAK/STAT signalling pathway provides an example of this paradigm in haematological malignancies, with the identification of JAK2 mutations in myeloproliferative neoplasms leading to the development of specific clinically effective JAK2 inhibitors, such as ruxolitinib. It is now clear that many solid tumours also show activation of JAK/STAT signalling. In this review, we focus on the role of JAK/STAT signalling in solid tumours, examining the molecular mechanisms that cause inappropriate pathway activation and their cellular consequences. We also discuss the degree to which activated JAK/STAT signalling contributes to oncogenesis. Studies showing the effect of activation of JAK/STAT signalling upon prognosis in several tumour types are summarised. Finally, we discuss the prospects for treating solid tumours using strategies targeting JAK/STAT signalling, including what can be learned from haematological malignancies and the extent to which results in solid tumours might be expected to differ