Molecular B-cell clonality assay in minor salivary glands as a useful tool for the lymphoma risk assessment in Sjögren's syndrome.

OBJECTIVES: Non-Hodgkin's lymphoma (NHL) risk assessment is crucial in Sjögren's syndrome (SS). We studied the prevalence of clonal immunoglobulin gene rearrangements in minor salivary glands (MSG) and their correlations with lymphoma occurrence and with previously established NHL predictors. METHODS: Molecular B-cell expansion was studied in fresh-frozen MSG of 207 patients with either suspected SS or with suspected lymphoma during SS, using a standardised multiplex PCR assay combined with heteroduplex analysis by microcapillary electrophoresis. The assignation of clonal cases was based on EuroClonality consortium guidelines. RESULTS: Among 207 studied patients, 31 (15%) had MSG monoclonal B-cell infiltration. Monoclonality was significantly more frequent in patients with SS (28/123, 22.8%) compared with patients without SS (3/84, 3.6%, P<0.001). Monoclonal B-cell infiltration in MSG of SS patients correlated significantly with ongoing salivary gland NHL, salivary gland swelling, CD4+ T-cell lymphopenia, rheumatoid factor (RF) activity, low complement levels and type 2 mixed cryoglobulinemia. The accumulation of biological risk factors was associated with a higher rate of MSG B-cell monoclonality given that patients with only positive RF had no probability of MSG B-cell monoclonality, RF-positive patients with 1 or 2 other risk factors had a 25.0% and 85.7% probability of MSG B-cell monoclonality, respectively. CONCLUSION: The detection of MSG monoclonal B-cell expansion by this easy-to-perform molecular assay is useful, both at the time of diagnosis and during the course of SS. Monoclonal B-cell expansion is associated with a subset of SS patients presenting either ongoing lymphoma or other established lymphoma predictive factors.

Extreme Gradient Boosting Tuned with Metaheuristic Algorithms for Predicting Myeloid NGS Onco-Somatic Variant Pathogenicity.

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.

Adrenomedullin Secreted by Melanoma Cells Promotes Melanoma Tumor Growth through Angiogenesis and Lymphangiogenesis.

INTRODUCTION: Metastatic melanoma is an aggressive tumor and can constitute a real therapeutic challenge despite the significant progress achieved with targeted therapies and immunotherapies, thus highlighting the need for the identification of new therapeutic targets. Adrenomedullin (AM) is a peptide with significant expression in multiple types of tumors and is multifunctional. AM impacts angiogenesis and tumor growth and binds to calcitonin receptor-like receptor/receptor activity-modifying protein 2 or 3 (CLR/RAMP2; CLR/RAMP3). METHODS: In vitro and in vivo studies were performed to determine the functional role of AM in melanoma growth and tumor-associated angiogenesis and lymphangiogenesis. RESULTS: In this study, AM and AM receptors were immunohistochemically localized in the tumoral compartment of melanoma tissue, suggesting that the AM system plays a role in melanoma growth. We used A375, SK-MEL-28, and MeWo cells, for which we demonstrate an expression of AM and its receptors; hypoxia induces the expression of AM in melanoma cells. The proliferation of A375 and SK-MEL-28 cells is decreased by anti-AM antibody (αAM) and anti-AMR antibodies (αAMR), supporting the fact that AM may function as a potent autocrine/paracrine growth factor for melanoma cells. Furthermore, migration and invasion of melanoma cells increased after treatment with AM and decreased after treatment with αAMR, thus indicating that melanoma cells are regulated by AM. Systemic administration of αAMR reduced neovascularization of in vivo Matrigel plugs containing melanoma cells, as demonstrated by reduced numbers of vessel structures, which suggests that AM is one of the melanoma cells-derived factors responsible for endothelial cell-like and pericyte recruitment in the construction of neovascularization. In vivo, αAMR therapy blocked angiogenesis and lymphangiogenesis and decreased proliferation in MeWo xenografts, thereby resulting in tumor regression. Histological examination of αAMR-treated tumors showed evidence of the disruption of tumor vascularity, with depletion of vascular endothelial cells and a significant decrease in lymphatic endothelial cells. CONCLUSIONS: The expression of AM by melanoma cells promotes tumor growth and neovascularization by supplying/amplifying signals for neoangiogenesis and lymphangiogenesis.

Comparison between Immunocytochemistry, FISH and NGS for ALK and ROS1 Rearrangement Detection in Cytological Samples.

The detection of ROS1 and ALK rearrangements is performed for advanced-stage non-small cell lung cancer. Several techniques can be used on cytological samples, such as immunocytochemistry (ICC), fluorescence in situ hybridization (FISH) and, more recently, next-generation sequencing (NGS), which is gradually becoming the gold standard. We performed a retrospective study to compare ALK and ROS1 rearrangement results from immunocytochemistry, FISH and NGS methods from 131 cytological samples. Compared to NGS, the sensitivity and specificity of ICC were 0.79 and 0.91, respectively, for ALK, and 1 and 0.87 for ROS1. Regarding FISH, the sensitivity and specificity were both at 1 for ALK and ROS1 probes. False-positive cases obtained by ICC were systematically corrected by FISH. When using ICC and FISH techniques, results are very close to NGS. The false-positive cases obtained by ICC are corrected by FISH, and the true-positive cases are confirmed. NGS has the potential to improve the detection of ALK and ROS1 rearrangements in cytological samples; however, the cost of this technique is still much higher than the sequential use of ICC and FISH.

Machine learning random forest for predicting oncosomatic variant NGS analysis.

Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but are found to be negative upon further investigation. Can any machine learning algorithm (ML) help us classify NGS variants? This has led us to investigate which ML can fit our NGS data and to develop a tool that can be routinely implemented to help biologists. Currently, one of the greatest challenges in medicine is processing a significant quantity of data. This is particularly true in molecular biology with the advantage of next-generation sequencing (NGS) for profiling and identifying molecular tumors and their treatment. In addition to bioinformatics pipelines, artificial intelligence (AI) can be valuable in helping to analyze mutation variants. Generating sequencing data from patient DNA samples has become easy to perform in clinical trials. However, analyzing the massive quantities of genomic or transcriptomic data and extracting the key biomarkers associated with a clinical response to a specific therapy requires a formidable combination of scientific expertise, biomolecular skills and a panel of bioinformatic and biostatistic tools, in which artificial intelligence is now successful in developing future routine diagnostics. However, cancer genome complexity and technical artifacts make identifying real variants challenging. We present a machine learning method for classifying pathogenic single nucleotide variants (SNVs), single nucleotide polymorphisms (SNPs), multiple nucleotide variants (MNVs), insertions, and deletions detected by NGS from different types of tumor specimens, such as: colorectal, melanoma, lung and glioma cancer. We compared our NGS data to different machine learning algorithms using the k-fold cross-validation method and to neural networks (deep learning) to measure the performance of the different ML algorithms and determine which one is a valid model for confirming NGS variant calls in cancer diagnosis. We trained our machine learning with 70% of our data samples, extracted from our local database (our data structure had 7 parameters: chromosome, position, exon, variant allele frequency, minor allele frequency, coverage and protein description) and validated it with the 30% remaining data. The model offering the best accuracy was chosen and implemented in the NGS analysis routine. Artificial intelligence was developed with the R script language version 3.6.0. We trained our model on 70% of 102,011 variants. Our best error rate (0.22%) was found with random forest machine learning (ntree = 500 and mtry = 4), with an AUC of 0.99. Neural networks achieved some good scores. The final trained model with the neural network achieved an accuracy of 98% and an ROC-AUC of 0.99 with validation data. We tested our RF model to interpret more than 2000 variants from our NGS database: 20 variants were misclassified (error rate < 1%). The errors were nomenclature problems and false positives. After adding false positives to our training database and implementing our RF model routinely, our error rate was always < 0.5%. The RF model shows excellent results for oncosomatic NGS interpretation and can easily be implemented in other molecular biology laboratories. AI is becoming increasingly important in molecular biomedical analysis and can be very helpful in processing medical data. Neural networks show a good capacity in variant classification, and in the future, they may be useful in predicting more complex variants.

First case of B ALL with KMT2A-MAML2 rearrangement: a case report.

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.

Detection of CALR and MPL Mutations in Low Allelic Burden JAK2 V617F Essential Thrombocythemia.

Myeloproliferative neoplasms are clonal hematopoietic stem cell disorders characterized by aberrant proliferation and an increased tendency toward leukemic transformation. The genes JAK2, MPL, and CALR are frequently altered in these syndromes, and their mutations are often a strong argument for diagnosis. We analyzed the mutational profiles of these three genes in a cohort of 164 suspected myeloproliferative neoplasms. JAK2 V617F mutation was detected by real-time PCR, whereas high-resolution melting analysis followed by Sanger sequencing were used for searching for mutations in JAK2 exon 12, CALR, and MPL. JAK2 V617F mutation was associated with CALR (n = 4) and MPL (n = 4) mutations in 8 of 103 essential thrombocytosis patients. These cases were harboring a JAK2 V617F allelic burden of <4% and a significantly higher platelet count compared with JAK2 V617F (P < 0.001) and CALR (P = 0.001) single-mutation patients. The findings from this study support the possibility of coexisting mutations of the JAK2, CALR, and MPL genes in myeloproliferative neoplasms and suggest that CALR and MPL should be analyzed not only in JAK2-negative patients but also in low V617F mutation patients. Follow-up of these double-mutation cases will be important for determining whether this group of patients presents particular evolution or complications.

Eradication of T315I mutation in chronic myeloid leukemia without third-generation tyrosine kinase inhibitor: a case report.

We report the case of a patient bearing a T315I-mutant chronic myeloid leukemia resistant to nilotinib, successfully treated with omacetaxine and then with dasatinib. After 9 months of nilotinib, the patient achieved a major molecular response but relapsed 3 months later due to the T315I mutation. Because third-generation tyrosine kinase inhibitor was not available and the patient refused bone marrow transplantation, he received two cycles of omacetaxine. This treatment had been stopped after two cycles because of clinical intolerance, but a major molecular response and total disappearance of the T315I clone was obtained. Treatment with dasatinib was then started and after 34-month follow-up the patient is still in major molecular response, thus suggesting that eradication of the T315I mutation could be achieved without third-generation tyrosine kinase inhibitors.

Characterization of the novel Sezary lymphoma cell line BKP1.

Cutaneous T-cell lymphomas (CTCL) are a heterogeneous group of lymphomas primarily involving the skin. The most common types are mycosis fungoides (MF) and Sezary Syndrome (SS). We report a novel long-term fast-growing SS line termed BKP1 that was characterized by flow cytometry (FC), conventional and molecular cytogenetic [FISH/multi-FISH together with array comparative genomic hybridization (aCGH)]. FC immunophenotype of the BKP1 is CD2+CD5+CD3+CD4+CD8-CD7-CD25-CD26-CD30-CD158k+. The TCRγ characterization of BKP1 by PCR identified a clonal rearrangement. The conventional cytogenetic and Multi-FISH analysis showed complex chromosomal rearrangements. aCGH analysis highlighted the loss of genes involved in cell cycle control, in immune response (HLA, complement complex) and DNA damage repair mechanisms. The BKP1 is another lymphoma cell line thoroughly characterized that can be a valuable tool for both basic and applied research such as identification of deregulated genes and/or pathways and screening for new antilymphoma drugs.

Hypoxia-inducible factor-1α as prognostic marker.

INTRODUCTION: Hypoxia-inducible factor-1α (HIF-1α) is a key player in the signaling pathway that mediates a complex and pleiotropic range of adaptive responses to hypoxia. It serves as cellular hypoxia sensor and plays a critical role in physiologic processes including glucose metabolism, iron metabolism, erythropoiesis, angiogenesis, cell survival and apoptosis, but also, pathologic processes such as carcinogenesis, progression and metastasis of many cancers. With the recent advent of new molecular targeted therapies, there is a growing need of molecular understanding of physiology and physiopathology and increased demand of diagnosis, prognosis and follow-up markers. AREAS COVERED: This paper reviews the biology of regulation of HIF-1α, its physiological and physiopathological effects. EXPERT OPINION: The authors discuss the potential diagnosis and the prognosis significance of HIF-1α that was evaluated in recent studies.

Hypoxia-inducible factor (HIF1α) gene expression in human shock states.

INTRODUCTION: Hypoxia-inducible factor-1 (HIF1) controls the expression of genes involved in the cellular response to hypoxia. No information is available on its expression in critically ill patients. Thus, we designed the first clinical study in order to evaluate the role of HIF1α as a prognosis marker in patients with shock. METHODS: 50 consecutive adult patients with shock and 11 healthy volunteers were prospectively included. RNA was extracted from whole blood samples and expression of HIF1α was assessed over the first 4 hours of shock. The primary objective was to assess HIF1α as a prognostic marker in shock. Secondary objectives were to evaluate the role of HIF1α as a diagnostic and follow-up marker. Patient survival was evaluated at day 28. RESULTS: The causes of shock were sepsis (78%), hemorrhage (18%), and cardiac dysfunction (4%). The HIF1α expression was significantly higher in the shock patients than in the healthy volunteers (121 [72-168] vs. 48 [38-54] normalized copies, p < 0.01), whatever the measured isoforms. It was similar in non-survivors and survivors (108 [range 84-183] vs. 121 [range 72-185] normalized copies, p = 0.92), and did not significantly change within the study period. CONCLUSIONS: The present study is the first to demonstrate the increased expression of HIF1α in patients with shock. Further studies are needed to clarify the potential association with outcome. Our findings reinforce the value of monitoring plasma lactate levels to guide the treatment of shock.

Analysis of T-cell receptor-γ gene rearrangements using heteroduplex analysis by high-resolution microcapillary electrophoresis.

Determination of T-cell clonality has an important additional value for diagnosis of T-cell lymphomas. Various molecular methods have been developed, including polymerase chain reaction (PCR) of T-cell receptor γ (TCRγ). The detection of PCR products usually relies commonly on either GeneScan (GS) analysis or heteroduplex (HD) analysis by polyacrylamide gel electrophoresis (PAGE). These techniques have their disadvantages, being relatively time-consuming and laborious or requiring expensive equipment. Here, we propose an alternative method that combines multiplex PCR and HD analysis by microcapillary electrophoresis (ME) on the Agilent 2100 Bioanalyzer. The sensitivity of the method was determined with clonal PEER T-cell line DNA dilution in polyclonal DNA and was evaluated as 1-5%. Fifty-three samples from patients with T-cell lymphoproliferative disorders were analyzed by HD analysis using ME and GS analyses. Comparison of the two techniques showed them to be highly concordant (93% similarity). The rate of clonality detection by GS analysis was higher than HD analysis by ME, but none of the discordant patients (n=5) has yet developed lymphoma. HD analysis by ME to reveal TCRγ gene rearrangements in clinical specimens was consistent with clinical data and the outcome of patients. Detection of T-cell clonality by HD analysis with ME is sensitive, practical, safe and represents a potential alternative to PAGE and GS analysis.

Establishment of the first World Health Organization International Genetic Reference Panel for quantitation of BCR-ABL mRNA.

Serial quantitation of BCR-ABL mRNA levels is an important indicator of therapeutic response for patients with chronic myelogenous leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia, but there is substantial variation in the real-time quantitative polymerase chain reaction methodologies used by different testing laboratories. To help improve the comparability of results between centers we sought to develop accredited reference reagents that are directly linked to the BCR-ABL international scale. After assessment of candidate cell lines, a reference material panel comprising 4 different dilution levels of freeze-dried preparations of K562 cells diluted in HL60 cells was prepared. After performance evaluation, the materials were assigned fixed percent BCR-ABL/control gene values according to the International Scale. A recommendation that the 4 materials be established as the first World Health Organization International Genetic Reference Panel for quantitation of BCR-ABL translocation by real-time quantitative polymerase chain reaction was approved by the Expert Committee on Biological Standardization of the World Health Organization in November 2009. We consider that the development of these reagents is a significant milestone in the standardization of this clinically important test, but because they are a limited resource we suggest that their availability is restricted to manufacturers of secondary reference materials.

E355G mutation appearing in a patient with e19a2 chronic myeloid leukaemia resistant to imatinib.

The development of imatinib is a milestone in the treatment of chronic myeloid leukaemia (CML), and its therapeutic effect has been extensively investigated in patients with CML who carry M-bcr and m-bcr BCR-ABL fusion transcripts. However, knowledge about its therapeutic effect on patients with CML who have the rare BCR-ABL fusion transcript e19a2 (mu-bcr) remains sparse. This report describes a patient with Philadelphia-positive chronic myeloid leukaemia with e19a2 rearrangement, in whom E355G mutation had been acquired. The patient was resistant to imatinib treatment based on conventional cytogenetic and fluorescence in situ hybridisation analysis.

Hypoxia inducible factor 1alpha gene (HIF-1alpha) splice variants: potential prognostic biomarkers in breast cancer.

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-1alpha and HIF-1beta/aryl hydrocarbon receptor nuclear translocator (ARNT) subunits. The prognostic relevance of HIF-1alpha protein overexpression has been shown in breast cancer. The impact of HIF-1alpha 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-1alpha 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-1alpha splice variant levels were compared to clinicopathological parameters including tumour microvessel density and metastasis-free survival. RESULTS: HIF-1alpha isoforms containing a three base pairs TAG insertion between exon 1 and exon 2 (designated HIF-1alphaTAG) and HIF-1alpha736 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-1alphaTAG mRNA levels (P = 0.037). Significant statistical association was found between tumour grade and HIF-1alphaTAG (P = 0.048), and total HIF-1alpha (P = 0.048) mRNA levels. HIF-1alphaTAG 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-1alphaTAG 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-1alphaTAG 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.