ALBERT

Description: The hallmark for Chroniclymphocytic leukemia (CLL) is a highly variable clinical course. An international prognostic index (CLL-IPI) is a promising tool to improve the precision of prognostic counseling and to identify patients who deserve closed monitoring. The CLL-IPI is a risk-weighted model comprising the risk factors age, stage, del(17p)/TP53 mutation, IGHV mutation status, and β2-microglobulin (β2-M)(LancetOncol 2016). The aims of the study were 1) to determine the IGHV status as well as the IGHV repertoire 2) to assess/validate the applicability of the CLL-IPI in general practice. We included all patients diagnosed of CLL according to the National Cancer Institute Working Group guidelines in our institution between 1986 and 2014 who had at least a 24 months follow-up. Amplification and sequence analysis of IGH rearrangements were performed on either DNA or cDNAusing the BIOMED-2 protocol. Sequence data were analyzed using the IMGT database and tools. Clinical and biological data were extracted from medical records and included age, stage, CD38 and ZAP-70 expression, serum LDH, β2-M, cytogenetics and lines of treatment. Overall survival (OS) was calculated from diagnosis to last follow-up or death, time to first treatment (TFT) from diagnosis to first treatment administration or last follow-up. 209 CLL patients were originally included but complete data to calculate the CLL-IPI was only available in 176 pts. Median age of the series was 65 years (range, 33 to 92), and a slight male predominance 102 (58.5%). The main clinical characteristics are detailed in Table 1. Median follow-up of patients was 71.5 months (range, 24-315). We identified 105/209 patients (50%) with unmutated IGHV. Somatic mutations among IGHV gene subgroups display a hierarchy of mutations (IGHV3〉IGHV1〉IGHV4). Among the functional IGHV genes, the most frequently encountered were IGHV1-69 (31; 14.6%). It was the most recurrently used in the unmutated group. The most represented IGHV gene within the mutated subset was IGHV4-34, which was used in 15 cases (7.1%). We have observed 39 IGHV genes. The most frequents are showed in Figure1. As previously described, patients with unmutated status showed a higher expression of CD38 and ZAP-70, unfavorable cytogenetics and a higher proportion of treated patients. The CLL-IPI index identified four groups of patients: low risk (0-1 points) n=74 (42%), intermediate (2-3) 67 (38.1%), high (H) (4-6) 29 (16.5%) and very high (VH) 6 (3.4 %). The 5-year OS and 5-year TFT of the CLL-IPI risk groups differed significantly (p〈 0.0001, log-rank test) between the low (OS 92.2%, TFT 74.1%), intermediate (OS 83.2%, TFT 34.6%) and high-very high groups (OS 61.5%, TFT 22.8%). We only identified 6 patients (3.4%) with a VH, with no difference in terms of OS and TFT between the VH and high (H) risk groups, probably due to the small number of patients. When we considered the H and VH altogether, the CLL-IPI identified three groups with significantly different TFT and OS (Figure 2) In summary, in our cohort the frequencies of the IGHV genes used in BCR rearrangements were similar to those described in the Mediterranean area and confirm a geographical-dependent leukaemic repertoire. We confirm that the CLL-IPI is a useful tool for real-life practice as it identifies three risk groups with significantly different time to first treatment and overall survival curves. In our experience, the CLL-IPI applied to the whole CLL population at diagnosis discriminates a smaller proportion of patients in the high (16.4%) and very high groups (3.4 %) compared to the original training cohort based on treated patients included in clinical trials. Our results are closely similar to the MAYO cohort that included patients consecutively diagnosed and observed. Table 1 Patient characteristics at diagnosis included in CLL-IPI analysis (n=176) Table 1. Patient characteristics at diagnosis included in CLL-IPI analysis (n=176) Figure 1 Distribution of rearrangements of the 12 most frequent IGHV genes according to mutational status. Figure 1. Distribution of rearrangements of the 12 most frequent IGHV genes according to mutational status. Figure 2 a) Overall survival b) Time to first chronic lymphocytic leukaemia treatment according to the CLL-IPI risk groups Figure 2. a) Overall survival b) Time to first chronic lymphocytic leukaemia treatment according to the CLL-IPI risk groups Disclosures No relevant conflicts of interest to declare.

Description: Background: Finding the best therapy option to treat myelofibrosis (MF) represents a huge challenge. Ruxolitinib (R) is a potent JAK1/2 inhibitor that has demonstrated improved survival and symptomatology in MF patients. There are a lot researches looking for the best combination of JAK inhibitor to improve its efficacy. In a previous work, we screened different drugs to evaluate if they were synergistic with ruxolitinib, we found that ruxolitinib was synergistic with nilotinib (N) and Prednisolone (P) as well as other drugs including bortezomib and HSP-90 inhibitors. Aim: To study the synergistic behavior and mechanism of actions of ruxolitinib in combination with nilotinib and prednisolone both in patient samples and cell lines. Methods: We have studied 20 secondary or primary MF patients and cell line: BA/F3 transfected with mutated JAK2 V617F (BA/F3 JAK2V617F). Classical assay was performed for patient samples: mononuclear cells isolated from peripheral blood were cultured during 2 weeks in Methocult TM GF_H4535 with 20 ng/ml IL-3, and 50 ng/ml SCF, in presence of increasing concentrations of R, N or P or their combinations. Also, mononuclear cells were cultured as described above, during 2 weeks but without drugs. Then, cells were washed with PBS and cultured 72 hours in RPMI 10% FBS and plated at 15,000 per well in 96-well plates with increasing concentrations of drugs. After both assay, cells were labeled with Annexin V and CD13 and analyzed in the Exvitech platform, an automated multiparametric flow cytometry platform. For cell lines, these were cultured in RPMI 10% FBS in the presence of increasing concentration of drugs. After 48 h of incubation, we performed a wst-8 assay to evaluate cell viability. To analyzed effect of treatment on survival and proliferation signaling pathways, cell lines were treated for 30 min with R 0.032 µM, N 1.6 µM and P 0.8 µM or combinations and total lysates were collected. To perform western blot, we use phospho-STAT5 (Tyr 964) and STAT5 after stripping as primary antibody and β-actin as load control. Graphpad Prism or XLFit was used to analyze dose-response curves. Synergism will be evaluated by the Median Effect methods described by T-C Chou and P. Talalay. Results: In patient samples when performed the classical assay, we found synergistic interaction in all combination in most of the patients (Table 1). Briefly, all combinations showed synergetic behavior (C

Description: Introduction: The negative minimal residual disease (MRD) after treatment has been recently accepted as endpoint for Chronic Lymphocytic Leukaemia (CLL) clinical trials. Conventionally, MRD can be detected by using multi-color Flow Cytometry (FC) with high sensitivity. Determination of the clonal immunoglobulin gene rearrangement can be a useful monitoring marker in a broad range of B-cell lymphoproliferative neoplasms. Moreover, the mutational status of immunoglobulin heavy chain variable (IgHV) rearrangement is considered one of the most important prognostic factors in CLL. Therefore, the identification of the IgHV rearrangement can be a useful marker both at diagnostic and as monitoring marker for MRD. Nowadays, high-throughput sequencing (HTS) technologies has enabled highly sensitive cancer genomic testing in clinical laboratories. There are same initiatives based on HTS to use IgHV rearrangement as marker for MRD monitoring in Acute lymphoblastic leukemia or multiple myeloma, but it remains unharmonized for application on CLL in the clinical laboratory. Objective: We evaluated the performance and clinical applicability of HTS assay for IgHV rearrangement in CLL MRD monitoring in 69 samples from 19 CLL patients treated. Methods: The libraries including IGH locus were performed using the Sequencing Multiplex Kit on IGH consensus primers. To simplify and make automatic the analysis of the data obtained, we developed a specific bioinformatic pipeline that covers from preprocessing to final data summarization and interpretation. The backbone of the analysis includes read preprocessing, mapping against IMGT reference sequences, consensus IgHV reads pairwise alignment to determine mutational status and read classification into rearrangements. Assessment of IgHV mutational status by Sseq, genomic DNA (gDNA; 50-100 ng), were used for IgHV analysis. gDNA was amplified using locus-specific primer sets for IgHV designed to allow for the amplification of all known alleles of the germline IgH sequence, as described previously. Inmunophenotypic studies were performed on erythrocyte-lysed whole PB samples according to Euroflow procedures. PB white blood cells (WBC) was systematically stained with the eight color combination panel recently proposed by the ERIC group for MRD detection (Rawstron AC et al. 2016). Data acquisition was performed on a FACSCanto II flow cytometer Becton-Dickinson Biociences using the FACSDiva software (V8.0; BD). For data analysis, the Infinicyt softwareTM (Cytognos SL, Salamanca, Spain) was used. The MRD levels were reported as fraction of CLL cells of all nucleated cells. MRD negativity was define as a fraction

Description: Introduction: Determination of the mutational status of rearranged immunoglobulin heavy chain variable (IgHV) genes in patients with Chronic Lymphocytic Leukaemia (CLL), is considered one of the most important prognostic factors: patients with unmutated IgHV (UM; ≥98% of identity to the germline) genes have a more aggressive disease course and develop more frequently unfavourable genetic deletions or mutations than patients with mutated IgHV (M; ≤98%). Mutational status, is currently determined by Sanger sequencing (Sseq) that allows the analysis of the major clone, however, international guidelines recommend caution in assigning mutational status in cases with "Borderline" IgHV identity (97-97.9%), and cases with double rearrangements with discordant mutational status. Objective: Analyze and determine the mutational status of the IgHV locus by High-throughput sequencing (HTS), in a cohort of CLL patients (n=51) with unclassifiable Sseq results: borderline status (n=22); double rearrangements (n=27) with discordant mutational status (n=2). Methods: We included 51 DNA samples extracted from peripheral blood of patients diagnosed of CLL according to the National Cancer Institute Working Group guidelines in our institution between 1986 and 2019 (median absolute lymphocytes 11.4x109/L [2,8-239,5x109/L]). Sseq amplification and analysis of IgHV rearrangements were performed on DNA conforming to the updated ERIC recommendations. In all the cases we were able to determinate the IGVH identity. To switch high-throughput sequencing to the clinical practice, we assessed the reliability of different library preparation methods to sequence IGH locus in patients with CLL. Amplification was performed using the Sequencing Multiplex Kit based on IGH FR (forward primers) and consensus JH (reverse primer) multiplex. PCR products were purified using Magsi-NGS Prep magnetic beads (Magnamedics Diagnostics), normalized and pooled to create a library for sequencing using a MiSeq equipment. To simplify and make automatic the analysis of the same we developed a specific bioinformatic pipeline that covers from preprocessing to final data summarization and interpretation. The backbone of the analysis includes read preprocessing, mapping against IMGT reference sequences, consensus IgHV reads pairwise alignment to determine mutational status and read classification into rearrangements. Results: This approach led to the identification of a dominant clone IgHV in all cases (n=51). Instead, the percentage of identity calculated by HTS analysis varies in: - 15/22 borderline cases whose mutational status could be recalculated into 10 MM and 5 UM. The rest 7 remaining in borderline group. - We could identify both clones in 29 double rearrangements cases, with concordant mutational status except 2/29 undetermined cases, included in UM group regarding HTS results. Our tool led to the identification of a dominant clonotypic IgHV in all cases, and when compared the HTS sequence/mutational status for the most abundant clone with Sseq and for the IgHV status determination, 15 out of 22 (68,18%), could be reclassified. This case showed a major clone with productive rearrangement mutated by Sseq but unmutated by HTS. Conclusions: Analyze and determine the mutational status of the IgHV locus by HTS, would potentially reveal multiple rearrangements and increase the prognostic precision of IgHV mutation analysis. IgHV-HTS classification is able to precisely classify patients with borderline status or/and multiple IgHV rearrangements for which Sseq is inconclusive. In this case, it has been possible to improved prognostication for 17 out of 24 patients. This is helping us to discover the advantages of the data obtained by HTS compared with current Sseq standard technique. Samples were provided by the INCLIVA Biobank. Funded by Gilead Felowship 257/17 Disclosures Terol: Abbvie: Consultancy; Janssen: Consultancy, Research Funding; Gilead: Research Funding; Roche: Consultancy; Astra Zeneca: Consultancy.

Description: BACKGROUND Although the overall prognosis of patients with aggressive non-Hodgkin's lymphoma (NHL) has improved, nearly a third of patients will have refractory disease or relapse. Identification of these high-risk patients using traditional prognostic factors is limited. PET is the recommended imaging modality for the staging of FDG-avid lymphoma but the value of a comprehensive new imaging biomarkers analysis applied to PET for the prediction of patients outcome has still not been deeply investigated. New metrics estimating the overall tumor burden such as metabolic tumor volume (MTV) and those that may capture intratumoral biological heterogeneity such as total lesion glycolysis (TLG) have been used to predict progression-free survival. AIM The goal of the present work was to characterize Lymphoma lesions by extracting several metabolic volume and textural properties as radiomics features and evaluate their performance as surrogate indicators of the number of treatment cycles, and treatment response. Materials and methods In this retrospective, observational study, we included aggressive non-Hodgkin's lymphoma patients consecutively diagnosed according to the WHO 2016 between January of 2015 to December of 2017. A diagnostic PET/CT scan were essential. 1 patient without treatment was excluded. Clinical and biological data were extracted from medical records. PET/CT examinations were exported from the PACS and loaded into QUIBIM Precision 2.3 analysis platform (QUIBIM, Valencia, Spain) for the calculation of metabolic volumes and textural properties. The SUV values of the PET images were normalized to the average liver SUV, and the lesions were automatically segmented considering a threshold of 41% of the maximum SUV (SUVmax). Physiological uptakes in organs and tissues like bowel, bladder, brain, among others, were manually removed. In the lesions volumetry analysis, the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated. For the extraction of texture features, first order histogram descriptors (SUV values distribution, skewness, kurtosis) as well as second order descriptors were extracted after computing the Gray-Level Co-Occurrence Matrix (GLCM). For the statistical analysis, the Z-score of all imaging features obtained was calculated and a multi-variate analysis was performed by first calculating the intra-class correlation (ICC) to reduce redundant variables. Second, data hierarchy clustering was applied to automatically obtain patient groups according to different imaging signatures. The prognostic performance of IPI with and without the imaging signature was evaluated by a Discriminant Analysis for the number of treatment cycles and treatment response. Prognostic value of OS was performed through Kaplan-Meier analysis. Results A total of 41 patients were included. The descriptive analysis of patients recruited with demographic and clinical data can be appreciated in Table 1. Radiomics features extracted allowed to clusterize patients in different groups that were later introduced in the classifier (Figure 1). The classifier based on discriminant model including the IPI factors predicted number of treatment cycles with a 65.9% of accuracy, being the age the factor with the highest weight (0.818). Adding information about imaging features from PET increased the accuracy to 86.5%. For the treatment response assessment, the IPI factors predicted response correctly in 71.4% of cases, being ECOG the parameter with the highest weight (0.974). Prediction was fully accurate when adding the imaging features, with a 100% of accuracy. The texture feature with the highest importance was 'dissimilarity' of the pixels (weight of 15.919). Conclusion The addition of radiomics features to the conventional IPI evaluation of patients allows for a significant increase in predictive performance, both for determining which patients will have more than 1 treatment lines and those who will respond to treatment. The results of this study would have an impact in disease management with a combined IPI and radiomics-based prognostic evaluation of patients at diagnosis. Disclosures No relevant conflicts of interest to declare.