System modeling reveals the molecular mechanisms of HSC cell cycle alteration mediated by Maff and Egr3 under leukemia

Motixafortide and G-CSF to mobilize hematopoietic stem cells for autologous transplantation in multiple myeloma: a randomized phase 3 trial

Autologous hematopoietic stem cell transplantation (ASCT) improves survival in multiple myeloma (MM). However, many individuals are unable to collect optimal CD34+ hematopoietic stem and progenitor cell (HSPC) numbers with granulocyte colony-stimulating factor (G-CSF) mobilization. Motixafortide is a novel cyclic-peptide CXCR4 inhibitor with extended in vivo activity. The GENESIS trial was a prospective, phase 3, double-blind, placebo-controlled, multicenter study with the objective of assessing the superiority of motixafortide + G-CSF over placebo + G-CSF to mobilize HSPCs for ASCT in MM. The primary endpoint was the proportion of patients collecting ≥6 × 106 CD34+ cells kg-1 within two apheresis procedures; the secondary endpoint was to achieve this goal in one apheresis. A total of 122 adult patients with MM undergoing ASCT were enrolled at 18 sites across five countries and randomized (2:1) to motixafortide + G-CSF or placebo + G-CSF for HSPC mobilization. Motixafortide + G-CSF enabled 92.5% to successfully meet the primary endpoint versus 26.2% with placebo + G-CSF (odds ratio (OR) 53.3, 95% confidence interval (CI) 14.12-201.33, P < 0.0001). Motixafortide + G-CSF also enabled 88.8% to meet the secondary endpoint versus 9.5% with placebo + G-CSF (OR 118.0, 95% CI 25.36-549.35, P < 0.0001). Motixafortide + G-CSF was safe and well tolerated, with the most common treatment-emergent adverse events observed being transient, grade 1/2 injection site reactions (pain, 50%; erythema, 27.5%; pruritis, 21.3%). In conclusion, motixafortide + G-CSF mobilized significantly greater CD34+ HSPC numbers within two apheresis procedures versus placebo + G-CSF while preferentially mobilizing increased numbers of immunophenotypically and transcriptionally primitive HSPCs. Trial Registration: ClinicalTrials.gov , NCT03246529.

The immune checkpoint ICOSLG is a relapse-predicting biomarker and therapeutic target in infant t(4;11) acute lymphoblastic leukemia

The most frequent genetic aberration leading to infant ALL (iALL) is the chromosomal translocation t(4;11), generating the fusion oncogenes KMT2A:AFF1 and AFF1:KMT2A, respectively. KMT2A-r iALL displays a dismal prognosis through high relapse rates and relapse-associated mortality. Relapse occurs frequently despite ongoing chemotherapy and without the accumulation of secondary mutations. A rational explanation for the observed chemo-resistance and satisfactory treatment options remain to be elucidated. We found that elevated ICOSLG expression level at diagnosis was associated with inferior event free survival (EFS) in a cohort of 43 patients with t(4;-11) iALL and that a cohort of 18 patients with iALL at relapse displayed strongly increased ICOSLG expression. Furthermore, co-culturing t(4;11) ALL cells (ICOSLG^hi) with primary T-cells resulted in the development of T_regs. This was impaired through treatment with a neutralizing ICOSLG antibody. These findings imply ICOSLG (1) as a relapse-predicting biomarker, and (2) as a therapeutic target involved in a potential immune evasion relapse-mechanism of infant t(4;11) ALL.

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Early growth response 3 (EGR3) is a direct transactivator of the immune checkpoint gene ICOSLG

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high ICOSLG expression at diagnosis is predictive for ALL relapse

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EGR3 and ICOSLG expressions are relapse-associated

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expression of ICOSLG on t(4;11) ALL cells leads to the rapid expansion of Tregs

Comparison of machine learning and deep learning techniques in promoter prediction across diverse species

Gene promoters are the key DNA regulatory elements positioned around the transcription start sites and are responsible for regulating gene transcription process. Various alignment-based, signal-based and content-based approaches are reported for the prediction of promoters. However, since all promoter sequences do not show explicit features, the prediction performance of these techniques is poor. Therefore, many machine learning and deep learning models have been proposed for promoter prediction. In this work, we studied methods for vector encoding and promoter classification using genome sequences of three distinct higher eukaryotes viz. yeast (Saccharomyces cerevisiae), A. thaliana (plant) and human (Homo sapiens). We compared one-hot vector encoding method with frequency-based tokenization (FBT) for data pre-processing on 1-D Convolutional Neural Network (CNN) model. We found that FBT gives a shorter input dimension reducing the training time without affecting the sensitivity and specificity of classification. We employed the deep learning techniques, mainly CNN and recurrent neural network with Long Short Term Memory (LSTM) and random forest (RF) classifier for promoter classification at k-mer sizes of 2, 4 and 8. We found CNN to be superior in classification of promoters from non-promoter sequences (binary classification) as well as species-specific classification of promoter sequences (multiclass classification). In summary, the contribution of this work lies in the use of synthetic shuffled negative dataset and frequency-based tokenization for pre-processing. This study provides a comprehensive and generic framework for classification tasks in genomic applications and can be extended to various classification problems.

Differential response to cytotoxic therapy explains treatment dynamics of acute myeloid leukaemia patients: insights from a mathematical modelling approach

Disease response and durability of remission are very heterogeneous in patients with acute myeloid leukaemia (AML). There is increasing evidence that the individual risk of early relapse can be predicted based on the initial treatment response. However, it is unclear how such a correlation is linked to functional aspects of AML progression and treatment. We suggest a mathematical model in which leukaemia-initiating cells and normal/healthy haematopoietic stem and progenitor cells reversibly change between an active state characterized by proliferation and chemosensitivity and a quiescent state, in which the cells do not divide, but are also insensitive to chemotherapy. Applying this model to 275 molecular time courses of nucleophosmin 1-mutated patients, we conclude that the differential chemosensitivity of the leukaemia-initiating cells together with the cells' intrinsic proliferative capacity is sufficient to reproduce both, early relapse as well as long-lasting remission. We can, furthermore, show that the model parameters associated with individual chemosensitivity and proliferative advantage of the leukaemic cells are closely linked to the patients' time to relapse, while a reliable prediction based on early response only is not possible based on the currently available data. Although we demonstrate with our approach, that the complete response data is sufficient to quantify the aggressiveness of the disease, further investigations are necessary to study how an intensive early sampling strategy may prospectively improve risk assessment and help to optimize individual treatments.

Alternative splicing related genetic variants contribute to bladder cancer risk

Emerging evidence has shown that aberrant alternative splicing (AS) events are involved in the carcinogenesis. The association between genetic variants in AS and bladder cancer susceptibility remains to be fully elucidated. We searched for single nucleotide polymorphisms (SNPs) which are located in splicing quantitative trait loci (sQTLs) in bladder cancer through CancerSplicingQTL database and the 1000 Genomes Project. A case-control study including 580 cases and 1,101 controls was conducted to assess the association between the functional genetic variants and bladder cancer risk. Next, we used GTEx, TCGA, and GEO databases conducting sQTL analysis and gene expression differences analysis to evaluate the potential biological function of the candidate SNPs and related genes. We found that SNP rs4383 C>G was remarkably related with the reduced risk of bladder cancer (odds ratio = 0.68, 95% confidence interval = 0.59-0.79, P = 3.91 × 10^-7 ). Similar results were obtained in codominant, dominant and recessive model. Stratified analyses revealed that the effect of SNP rs4383 C>G on bladder cancer was more significant in the older subjects (age > 65), female and nonsmokers. sQTL analysis showed that SNP rs4383 was associated with the AS events of its downstream gene MAFF with a splicing event of alternative 5' splice site. The messenger RNA expression of MAFF in bladder tumor tissues was lowered compared with normal tissues. Patients with high expression of MAFF had higher survival rates. These findings indicated that SNP rs4383 related with the AS events of MAFF was associated with bladder cancer risk and could represent a possible biomarker for bladder cancer susceptibility.

CDK6 Inhibition: A Novel Approach in AML Management

Acute myeloid leukemia (AML) is a complex disease with an aggressive clinical course and high mortality rate. The standard of care for patients has only changed minimally over the past 40 years. However, potentially useful agents have moved from bench to bedside with the potential to revolutionize therapeutic strategies. As such, cell-cycle inhibitors have been discussed as alternative treatment options for AML. In this review, we focus on cyclin-dependent kinase 6 (CDK6) emerging as a key molecule with distinct functions in different subsets of AML. CDK6 exerts its effects in a kinase-dependent and -independent manner which is of clinical significance as current inhibitors only target the enzymatic activity.

CDK6 coordinates JAK2 V617F mutant MPN via NF-κB and apoptotic networks

Over 80% of patients with myeloproliferative neoplasms (MPNs) harbor the acquired somatic JAK2 ^V617F mutation. JAK inhibition is not curative and fails to induce a persistent response in most patients, illustrating the need for the development of novel therapeutic approaches. We describe a critical role for CDK6 in MPN evolution. The absence of Cdk6 ameliorates clinical symptoms and prolongs survival. The CDK6 protein interferes with 3 hallmarks of disease: besides regulating malignant stem cell quiescence, it promotes nuclear factor κB (NF-κB) signaling and contributes to cytokine production while inhibiting apoptosis. The effects are not mirrored by palbociclib, showing that the functions of CDK6 in MPN pathogenesis are largely kinase independent. Our findings thus provide a rationale for targeting CDK6 in MPN.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: putting systems biology to work

Between December 8–10, 2016, the International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held in Houston, Texas, USA. The conference included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2016, with exciting advances were presented in many areas of systems biology. Here, we selected seven high quality papers to be published in BMC Systems Biology.