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Background A large number of chromosomal translocations of the human KMT2A gene, better known as the MLL gene, have so far been characterized. Genetic rearrangements involving KMT2A gene are frequently involved in lymphoid, myeloid and mixed lineage leukemia. One of its rare fusion partners, the mastermind like 2 ( MAML2 ) gene has been reported in four cases of myeloid neoplasms after chemotherapy so far: two acute myeloid leukemias (AML) and two myelodysplasic syndrome (MDS), and two cases of secondary T-cell acute lymphoblastic leukemia (T-ALL). Case presentation Here we report the case of a KMT2A - MAML2 fusion discovered by Next-Generation Sequencing (NGS) analysis in front of an inv11 (q21q23) present in a 47-year-old female previously treated for a sarcoma in 2014, who had a B acute lymphoid leukemia (B ALL). Conclusion It is, to our knowledge, the first case of B acute lymphoblastic leukemia with this fusion gene. At the molecular level, two rearrangements were detected using RNA sequencing juxtaposing exon 7 to exon 2 and exon 9 to intron 1–2 of the KMT2A and MAML2 genes respectively, and one rearrangement using Sanger sequencing juxtaposing exon 8 and exon 2.

The advent of next-generation sequencing (NGS) technologies has revolutionized the field of bioinformatics and genomics, particularly in the area of onco-somatic genetics. NGS has provided a wealth of information about the genetic changes that underlie cancer and has considerably improved our ability to diagnose and treat cancer. However, the large amount of data generated by NGS makes it difficult to interpret the variants. To address this, machine learning algorithms such as Extreme Gradient Boosting (XGBoost) have become increasingly important tools in the analysis of NGS data. In this paper, we present a machine learning tool that uses XGBoost to predict the pathogenicity of a mutation in the myeloid panel. We optimized the performance of XGBoost using metaheuristic algorithms and compared our predictions with the decisions of biologists and other prediction tools. The myeloid panel is a critical component in the diagnosis and treatment of myeloid neoplasms, and the sequencing of this panel allows for the identification of specific genetic mutations, enabling more accurate diagnoses and tailored treatment plans. We used datasets collected from our myeloid panel NGS analysis to train the XGBoost algorithm. It represents a data collection of 15,977 mutations variants composed of a collection of 13,221 Single Nucleotide Variants (SNVs), 73 Multiple Nucleoid Variants (MNVs), and 2683 insertion deletions (INDELs). The optimal XGBoost hyperparameters were found with Differential Evolution (DE), with an accuracy of 99.35%, precision of 98.70%, specificity of 98.71%, and sensitivity of 1.

Myeloproliferative neoplasms (MPN) are clonal hematopoietic stem cell-derived disorders characterized by uncontrolled proliferation of differentiated myeloid cells. Two main groups of MPN, BCR::ABL1-positive (Chronic Myeloid Leukemia) and BCR::ABL1-negative (Polycythemia Vera, Essential Thrombocytosis, Primary Myelofibrosis) are distinguished. For many years, cytomorphologic and histologic features were the only proof of MPN and attempted to distinguish the different entities of the subgroup BCR::ABL1-negative MPN. World Health Organization (WHO) classification of myeloid neoplasms evolves over the years and increasingly considers molecular abnormalities to prove the clonal hematopoiesis. In addition to morphological clues, the detection of JAK2, MPL and CALR mutations are considered driver events belonging to the major diagnostic criteria of BCR::ABL1-negative MPN. This highlights the preponderant place of molecular features in the MPN diagnosis. Moreover, the advent of next-generation sequencing (NGS) allowed the identification of additional somatic mutations involved in clonal hematopoiesis and playing a role in the prognosis of MPN. Nowadays, careful cytomorphology and molecular biology are inseparable and complementary to provide a specific diagnosis and to permit the best follow-up of these diseases.

Familial dysautonomia (FD) is a hereditary neuropathy caused by mutations in the IKBKAP gene, the most common of which results in variable tissue-specific mRNA splicing with skipping of exon 20. Defective splicing is especially severe in nervous tissue, leading to incomplete development and progressive degeneration of sensory and autonomic neurons. The specificity of neuron loss in FD is poorly understood due to the lack of an appropriate model system. To better understand and modelize the molecular mechanisms of IKBKAP mRNA splicing, we collected human olfactory ecto-mesenchymal stem cells (hOE-MSC) from FD patients. hOE-MSCs have a pluripotent ability to differentiate into various cell lineages, including neurons and glial cells. We confirmed IKBKAP mRNA alternative splicing in FD hOE-MSCs and identified 2 novel spliced isoforms also present in control cells. We observed a significant lower expression of both IKBKAP transcript and IKAP/hELP1 protein in FD cells resulting from the degradation of the transcript isoform skipping exon 20. We localized IKAP/hELP1 in different cell compartments, including the nucleus, which supports multiple roles for that protein. We also investigated cellular pathways altered in FD, at the genome-wide level, and confirmed that cell migration and cytoskeleton reorganization were among the processes altered in FD. Indeed, FD hOE-MSCs exhibit impaired migration compared to control cells. Moreover, we showed that kinetin improved exon 20 inclusion and restores a normal level of IKAP/hELP1 in FD hOE-MSCs. Furthermore, we were able to modify the IKBKAP splicing ratio in FD hOE-MSCs, increasing or reducing the WT (exon 20 inclusion):MU (exon 20 skipping) ratio respectively, either by producing free-floating spheres, or by inducing cells into neural differentiation. hOE-MSCs isolated from FD patients represent a new approach for modeling FD to better understand genetic expression and possible therapeutic approaches. This model could also be applied to other neurological genetic diseases.

Background Hypoxia-inducible factor 1 (HIF-1) is a master transcriptional regulator of genes regulating oxygen homeostasis. The HIF-1 protein is composed of two HIF-1α and HIF-1β/aryl hydrocarbon receptor nuclear translocator (ARNT) subunits. The prognostic relevance of HIF-1α protein overexpression has been shown in breast cancer. The impact of HIF-1α alternative splice variant expression on breast cancer prognosis in terms of metastasis risk is not well known. Methods Using real-time quantitative reverse transcription PCR assays, we measured mRNA concentrations of total HIF-1α and 4 variants in breast tissue specimens in a series of 29 normal tissues or benign lesions (normal/benign) and 53 primary carcinomas. In breast cancers HIF-1α splice variant levels were compared to clinicopathological parameters including tumour microvessel density and metastasis-free survival. Results HIF-1α isoforms containing a three base pairs TAG insertion between exon 1 and exon 2 (designated HIF-1α TAG ) and HIF-1α 736 mRNAs were found expressed at higher levels in oestrogen receptor (OR)-negative carcinomas compared to normal/benign tissues ( P = 0.009 and P = 0.004 respectively). In breast carcinoma specimens, lymph node status was significantly associated with HIF-1α TAG mRNA levels ( P = 0.037). Significant statistical association was found between tumour grade and HIF-1α TAG ( P = 0.048), and total HIF-1α ( P = 0.048) mRNA levels. HIF-1α TAG mRNA levels were also inversely correlated with both oestrogen and progesterone receptor status ( P = 0.005 and P = 0.033 respectively). Univariate analysis showed that high HIF-1α TAG mRNA levels correlated with shortened metastasis free survival ( P = 0.01). Conclusions Our results show for the first time that mRNA expression of a HIF-1α TAG splice variant reflects a stage of breast cancer progression and is associated with a worse prognosis. See commentary: http://www.biomedcentral.com/1741-7015/8/45

To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs ( PPT1 , TNF , IL1B and HIST1H1E ) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.

Minimal residual disease (MRD) assays are of a great value to assess treatment efficacy and may provide prognostic information. This is particularly relevant in the era of targeted therapy where the introduction of MRD monitoring has fundamentally transformed the way in which cancer patients are managed. While MRD guidelines are well-established for chronic myeloid leukemia, acute promyelocytic leukemia and acute lymphoblastic leukemia, areas for continuing development are available. High level of standardization and regular external quality control rounds and recommendations for data interpretation remain essential to improve MRD monitoring. In this review, we describe the different applications of MRD assays in most frequent hematologic malignancies and solid cancer and provide an overview of the strengths and potential weaknesses of each method.

For decades, the diagnosis, prognosis and thus, the treatment of acute myeloblastic leukemias and myelodysplastic neoplasms has been mainly based on morphological aspects, as evidenced by the French-American-British classification. The morphological aspects correspond quite well, in a certain number of particular cases, to particular evolutionary properties, such as acute myelomonoblastic leukemias with eosinophils or acute promyelocytic leukemias. Advances in biology, particularly “classical” cytogenetics (karyotype) and molecular cytogenetics (in situ hybridization), have made it possible to associate certain morphological features with particular molecular abnormalities, such as the pericentric inversion of chromosome 16 and translocation t(15;17) in the two preceding examples. Polymerase chain reaction techniques have made it possible to go further in these analyses by associating these karyotype abnormalities with their molecular causes, CBFbeta fusion with MYH11 and PML-RAR fusion in the previous cases. In these two examples, the molecular abnormality allows us to better define the pathophysiology of leukemia, to adapt certain treatments (all-transretinoic acid, for example), and to follow up the residual disease of strong prognostic value beyond the simple threshold of less than 5% of marrow blasts, signaling the complete remission. However, the new sequencing techniques of the next generation open up broader perspectives by being able to analyze several dozens of molecular abnormalities, improving all levels of management, from diagnosis to prognosis and treatment, even if it means that morphological aspects are increasingly relegated to the background.

Most neuronal types have a well-identified electrical phenotype. It is now admitted that a same phenotype can be produced using multiple biophysical solutions defined by ion channel expression levels. This argues that systems-level approaches are necessary to understand electrical phenotype genesis and stability. Midbrain dopaminergic (DA) neurons, although quite heterogeneous, exhibit a characteristic electrical phenotype. However, the quantitative genetic principles underlying this conserved phenotype remain unknown. Here we investigated the quantitative relationships between ion channels’ gene expression levels in midbrain DA neurons using single-cell microfluidic qPCR. Using multivariate mutual information analysis to decipher high-dimensional statistical dependences, we unravel co-varying gene modules that link neurotransmitter identity and electrical phenotype. We also identify new segregating gene modules underlying the diversity of this neuronal population. We propose that the newly identified genetic coupling between neurotransmitter identity and ion channels may play a homeostatic role in maintaining the electrophysiological phenotype of midbrain DA neurons.

Introduction Anti-MAG neuropathies are associated with an IgM monoclonal gammopathy of undetermined significance (MGUS) or with a malignant haemopathy. Our objective was to determine whether the presence of a haemopathy or somatic mutations of MYD88 and CXCR4 genes influences disease presentation and response to rituximab (RTX). Methods We included 79 patients (mean age 74 years, disease duration 9.68 years) who had a bone marrow aspiration with morphologic and immunophenotypic analysis. MYD88 L265P and CXCR4 mutations were analysed in peripheral B cells. Information collected included: inflammatory neuropathy cause and treatment sensory sum score (ISS), MRC testing, overall neuropathy limitation scale (ONLS), Rash-built Overall Disability Score (RODS), ataxia score, anti-MAG titres, peak IgM dosage, neurofilament light chain levels, motor and sensory amplitudes, motor unit index (MUNIX) and motor unit size index (MUSIX) sum scores. Efficacy of RTX was evaluated at 12 months in 26 patients. Results Malignant haematological disorders were discovered in 17 patients (22%): 13 Waldenstrom macroglobulinemia, 3 marginal zone lymphoma and one mantle cell lymphoma. MYD88 L265P mutation was detected in 29/60 (48%) patients and CXCR4 in 1 single patient. Disease severity, biological and electrophysiological data and response to RTX were comparable in patients with MGUS/lymphoma and patients with/without MYD88 L265P mutation. ISS was lower and MUSIX higher in patients improved by RTX. Conclusions MYD88 L265P mutation and underlying haemopathies are not predictive of a more severe disease. However, in cases of resistant and progressive neuropathy, they provide an opportunity to prescribe newly available drugs such as Bruton tyrosine kinase inhibitors.