ALBERT

Description: Motivation Next-generation sequencing has become the go-to standard method for the detection of single-nucleotide variants in tumor cells. The use of such technologies requires a PCR amplification step and a sequencing step, steps in which artifacts are introduced at very low frequencies. These artifacts are often confused with true low-frequency variants that can be found in tumor cells and cell-free DNA. The recent use of unique molecular identifiers (UMI) in targeted sequencing protocols has offered a trustworthy approach to filter out artefactual variants and accurately call low-frequency variants. However, the integration of UMI analysis in the variant calling process led to developing tools that are significantly slower and more memory consuming than raw-reads-based variant callers. Results We present UMI-VarCal, a UMI-based variant caller for targeted sequencing data with better sensitivity compared to other variant callers. Being developed with performance in mind, UMI-VarCal stands out from the crowd by being one of the few variant callers that do not rely on SAMtools to do their pileup. Instead, at its core runs an innovative homemade pileup algorithm specifically designed to treat the UMI tags in the reads. After the pileup, a Poisson statistical test is applied at every position to determine if the frequency of the variant is significantly higher than the background error noise. Finally, an analysis of UMI tags is performed, a strand bias and a homopolymer length filter are applied to achieve better accuracy. We illustrate the results obtained using UMI-VarCal through the sequencing of tumor samples and we show how UMI-VarCal is both faster and more sensitive than other publicly available solutions. Availability and implementation The entire pipeline is available at https://gitlab.com/vincent-sater/umi-varcal-master under MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

Description: Introduction Aggressive B-cell lymphomas are heterogeneous in their clinical course and biological characteristics. They include diffuse large B-cell lymphoma not otherwise specified (DLBCL-NOS), high grade-B-cell lymphoma with double/triple-hit or NOS (HGBL), primary mediastinal B-cell lymphoma (PMBL). In order to better differentiate these entities, the WHO classification recommends using immunohistochemistry (IHC), FISH, targeted sequencing and gene expression profiles (GEP). However, these techniques are most often performed retrospectively in clinical trials, which is not representative of real life. In order to use these information to improve the current standard of treatment with targeted therapies adapted to lymphoma biology, we have set up a national network on behalf of the LYSA called RT3 (for Real-time tailored therapy) to demonstrate that we are able to comprehensively characterize aggressive B cell lymphomas in a clinically relevant timeline. Materials and methods Patients 〉 18 years of age with untreated aggressive B-cell lymphoma were included prospectively from 21 LYSA centers. FFPE specimens were analyzed and classified according to WHO classification, benefiting from an IHC profile (Hans algorithm, BCL2, MYC), FISH analysis (BCL6, BCL2, MYC break apart and MYC-IGH/IGL/IGK fusion probes), targeted NGS analysis and a targeted GEP using RT-MLPA (Bobée et al. J Mol diagn 2017). A first part of the study phase was carried out in an oligocentric manner with only 2 referral platforms for pathological analysis and molecular characterization. The second phase was the implementation of 7 RT3 platforms spread over France. The main objective was to evaluate the capacity of the network to provide an exhaustive histopathological and molecular characterization 4 days before theoretical R-CHOP21 C3 administration (within 38 days after D1 cycle 1). Results The oligocentric cohort 1 prospectively included 72 patients in 6 months: 19 had insufficient material or inappropriate diagnosis to be qualified and 53 benefited from the complete analysis on referral platforms. A complete characterization 4 days before RCHOP-C3 was provided to the clinician in 47 cases (88.7%), allowing to further implement the network with 7 platforms and 23 clinical investigation centers. 183 patients were included in the second phase in 9 months, 35 were excluded for inadequate diagnosis/material. On this population, 143 (96.6%) complete patient-reports were provided with a median time of 32 days (1-50). Finally, 201 cases were retained in the Full Analysis Set for which tumor samples fulfilled all prerequisites and diagnosis of DLBCL was confirmed by RT3 platforms. The clinical characteristics were as follows: median age of 61 y (20-92), with 45.2% of pts with aaIPI 2-3and 67.1% with Ann Arbor stage III-IV; 1L treatment consisted mainly of RCHOP (RCHOP14/21 = 136, 72.3%). 7% of patients were treated with experimental drugs. 76% presented with extranodal involvement. After pathological review, 139 (69%) patients were classified as DLBCL-NOS (41% GCB; 58% nGCB), 11 (5%) as HGBL-NOS, 8 (4%) as HGBL-DH and 18 (9%) as PMBL, 3 (1%) as EBV+ DLBCL-NOS, 9 (4%) as FL-3B, 7 (3%) transformed DLBCL, 2 (1%) plasmablastic, 1 (0.5%) unclassified, 1 (0.5%) DLBCL with IRF4 rearrangement. By immunohistochemistry, 22 cases were CD5+, 74% were BCL2+, and 53% MYC+ and 49% as double expressors. BCL2/18q21, BCL6/3q27 and MYC/8q24 breaks were observed in 14% (29/201), 25% (50/201) and 12% (25/201) of the cases respectively. MYC partner gene was available in 10/29 cases (5 MYC-IG, 5 non-IG). At the molecular level, PIM1 was the most frequently mutated gene in the entire cohort (36%). In the ABC subtype, MYD88 was mutated in 48% of cases. In the GCB cohort, SOCS1 was the most frequently mutated gene (30%). In the HGBL cohort, MYC was the most mutated gene (43%). Conclusion This study demonstrates that this RT3 LYSA network allowed a real time pathological and molecular characterization of aggressive B-cell lymphomas according to the WHO recommendations. The RT3 network provides relevant informations to the clinician before R-CHOP21 C3, that might contribute to modify the treatment eventually adding targeted therapies or tailor a second line treatment. This network should be used as a basis for future clinical trials. Inter platforms reproducibility and prognostic relevance of the RT3 project will be presented. Disclosures Haioun: Gilead: Honoraria; Janssen: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Miltenyi: Honoraria; Servier: Honoraria; Roche: Honoraria; Celgene: Honoraria. Le Gouill:Roche Genentech, Janssen-Cilag and Abbvie, Celgene, Jazz pharmaceutical, Gilead-kite, Loxo, Daiichi-Sankyo and Servier: Honoraria; Loxo Oncology at Lilly: Consultancy. Ribrag:arGEN-X-BVBA: Research Funding; BAY1000394 studies on MCL: Patents & Royalties; Institut Gustave Roussy: Current Employment; argenX: Current equity holder in publicly-traded company, Research Funding; Epizyme: Consultancy, Current equity holder in publicly-traded company, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; MSD: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Nanostring: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Honoraria; Pharmamar: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AZD: Honoraria, Other; Eisai: Honoraria; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Immune Design: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees. Salles:Takeda: Honoraria; Karyopharm: Honoraria; Genmab: Honoraria, Other; Debiopharm: Consultancy, Honoraria, Other: consultancy or advisory role; Autolos: Other: consultancy or advisory role; Abbvie: Other: consultancy or advisory role; Roche: Honoraria, Other: consultancy or advisory role; Novartis: Honoraria, Other: consultancy or advisory role; MorphoSys: Honoraria, Other: consultancy or advisory role; Janssen: Honoraria, Other: consultancy or advisory role; Epizyme: Honoraria, Other: consultancy or advisory role; Kite, a Gilead Company: Honoraria, Other: consultancy or advisory role ; BMS/Celgene: Honoraria, Other: consultancy or advisory role. Sujobert:Sunesis: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead/Kyte: Membership on an entity's Board of Directors or advisory committees. Bouabdallah:Gilead Sciences: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Roche: Consultancy, Honoraria. Sibon:takeda france: Consultancy.

Description: Background Recently, copy number variations (CNV) impacting genes involved in oncogenic pathways have attracted an increasing attention to manage disease susceptibility. CNV is one of the most important somatic aberrations in the genome of tumor cells. Oncogene activation and tumor suppressor gene inactivation are often attributed to copy number gain/amplification or deletion, respectively, in many cancer types and stages. Recent advances in next generation sequencing protocols allow for the addition of unique molecular identifiers (UMI) to each read. Each targeted DNA fragment is labeled with a unique random nucleotide sequence added to sequencing primers. UMI are especially useful for CNV detection by making each DNA molecule in a population of reads distinct. Results Here, we present molecular Copy Number Alteration (mCNA), a new methodology allowing the detection of copy number changes using UMI. The algorithm is composed of four main steps: the construction of UMI count matrices, the use of control samples to construct a pseudo-reference, the computation of log-ratios, the segmentation and finally the statistical inference of abnormal segmented breaks. We demonstrate the success of mCNA on a dataset of patients suffering from Diffuse Large B-cell Lymphoma and we highlight that mCNA results have a strong correlation with comparative genomic hybridization. Conclusion We provide mCNA, a new approach for CNV detection, freely available at https://gitlab.com/pierrejulien.viailly/mcna/ under MIT license. mCNA can significantly improve detection accuracy of CNV changes by using UMI.