A novel in-house deep sequencing method for non-invasive disease monitoring in multiple myeloma patients

Background: Novel and more effective treatment strategies have sig- nificantly prolonged multiple myeloma (MM) survival and raised inter- est in the depth of response. This implies the need of highly sensitive assays such as the determination of minimal residual disease (MRD) by multiparametric flow cytometry (MFC) and next generation sequencing (NGS) of immunoglobulin (IGH) gene rearrangements. Ongoing studies are examining circulating cell-free tumor DNA (cfDNA) as a sensitive measure of small amounts of residual cells. In the present study, we de- scribe and analytically validate a simplified in-house deep-sequencing method to identify and quantify residual tumor burden in MM patients from plasma samples. Methods: We retrospectively analyzed 25 MM paired tumor (n=25) and plasma samples (n=48) obtained at diagnosis and at specified time points during treatment. Genomic DNA (gDNA) and cfDNA were extracted from selected CD138+ plasma cells (PC) and from plasma (Qiagen). IGH gene rearrangements were amplified, qual- ity assessed (Agilent hsDNA kit) and sequenced on Ion Torrent PGM. Raw reads were filtered and aligned using IMGT germline database andaggregated into clonotypes. Post-processing analyses were performed using VDJtools and customized R scripts. Results: Our sequencing method successfully identified a IGH MM clonotype in 88% of tumor samples (22/25), subsequently detected in plasma of all 22 cases (me- dian 4.7% of total filtered reads). Levels of the IGH clonotype in cfDNA distinguished between groups of patients with different prognosis: pa- tients with levels >4.7% prior to therapy, had significantly shorter PFS than patients with levels10-5 vs 15\ub15 months for frequencies=10-5 vs 37\ub14 months for frequencies<10- 5). Those patients are in CR and characterized by PC frequencies <10- 5 by MFC, and are therefore defined as MRD-negative. Conclusions: Results of this study support the clinical applicability of quantifying tumor levels by our in-house deep-sequencing of IGH gene rearrange- ments in plasma of MM patients

Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma

In multiple myeloma, novel treatments with proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs) have prolonged survival but the disease remains incurable. At relapse, next-generation sequencing has shown occasional mutations of drug targets but has failed to identify unifying features that underlie chemotherapy resistance. We studied 42 patients refractory to both PIs and IMiDs. Whole-exome sequencing was performed in 40 patients, and RNA sequencing (RNA-seq) was performed in 27. We found more mutations than were reported at diagnosis and more subclonal mutations, which implies ongoing evolution of the genome of myeloma cells during treatment. The mutational landscape was different from that described in published studies on samples taken at diagnosis. The TP53 pathway was the most frequently inactivated (in 45% of patients). Conversely, point mutations of genes associated with resistance to IMiDs were rare and were always subclonal. Refractory patients were uniquely characterized by having a mutational signature linked to exposure to alkylating agents, whose role in chemotherapy resistance and disease progression remains to be elucidated. RNA-seq analysis showed that treatment or mutations had no influence on clustering, which was instead influenced by karyotypic events. We describe a cluster with both amp(1q) and del(13) characterized by CCND2 upregulation and also overexpression of MCL1, which represents a novel target for experimental treatments. Overall, high-risk features were found in 65% of patients. However, only amp(1q) predicted survival. Gene mutations of IMiD and PI targets are not a preferred mode of drug resistance in myeloma. Chemotherapy resistance of the bulk tumor population is likely attained through differential, yet converging evolution of subclones that are overall variable from patient to patient and within the same patient

A targeted sequencing approach in multiple myeloma reveals a complex landscape of genomic lesions that has implications for prognosis

Background: Next-generation sequencing (NGS) studies have shown that mul- tiple myeloma is a heterogeneous disease with a complex subclonal architecture and few recurrently mutated genes. The analysis of smaller regions of interest in the genome (\u201ctargeted studies\u201d) allows interrogation of recurrent genomic events with reduces complexity of downstream analysis at a lower price. Aims: Here, we performed the largest targeted study to date in multiple myelo- ma to analyze gene mutations, deletions and amplifications, chromosomal copy number changes and immunoglobulin heavy chain locus (IGH) translo- cations and correlate results with biological and clinical features. Methods: We used Agilent SureSelect cRNA pull down baits to target: 246 genes implicated in myeloma or cancer in general in a mixed gene discovery/confirmation effort; 2538 single nucleotide polymorphisms to detect amplifications and deletions at the single-gene and chromosome level; the IGH locus to detect translocations. We sequenced unmatched DNA from CD138- purified plasma cells from 418 patients with multiple myeloma at diagnosis, with a median follow-up of 5.3 years. We sequenced at an average depth of 337x using Hiseq2000 machines (Illumina Inc.). We applied algorithms developed in- house to call genomic events, filtering out potential artifacts and germline vari- ants. We then ranker each event on its likelihood of being \u201concogenic\u201d based on clustering, recurrence and cross-reference with the COSMIC database. Results: We identified 2270 gene mutations in 412/418 patients, and of those 688 were oncogenic. 342 patients harbored at least one oncogenic mutation. 215/246 genes showed at lease one likely somatic mutation, but only 106 showed at least one oncogenic mutation. 63% of oncogenic mutations were accounted for by the top 9 driver genes previously identified (KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, TRAF3, SP140, IRF4), implying our gene discov- ery effort did not identify novel mutated genes. We included deletion of tumor suppressors, amplification of oncogenes, chromosomal copy number changes and IGH translocations for a total of 76 variables, so that 413/418 patients showed at least one informative driver genomic event, (median 4/patient). We investigated pairwise associations between events and found significant corre- lations, such as TP53 mutations and del(17p), CYLD mutations and del(16), FAM46C mutations and del(1p), SF3B1 mutations and t(11;14). Hotspots muta- tions of IRF4 lysine p.123 showed an inverse correlation with a hyperdiploid karyotype and del(16) as opposed to other missense mutations scattered along the gene, which has pathogenic implications. Survival was negatively affected by the cumulative burden of lesions in an almost linear fashion, with median survival of 10.97 and 4.07 years in patients with =7 lesions respectively, and this was independent of the nature of the genomic events. Given the het- erogeneity and complex interplay of the variables we fitted a cox-proportional hazard model to predict survival. We found that mutations in TP53, amplifications of MYC, deletions of CYLD, amp(1q), del12p13.31 and del17p13 where the only significant events, all promoting shorter survival. In particular, TP53 muta- tions and deletions, often co-occurring, had an additive effect so that carriers of both showed a dismal survival of 17 months (Figure 1).Summary/Conclusions: Due to the complex genomic landscape in MM, a discovery effort still requires large studies to derive significant associations. We conclude that a targeted sequencing approach may provide prognostic models and give insights into myeloma biology

Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups

In multiple myeloma, next-generation sequencing (NGS) has expanded our knowledge of genomic lesions, and highlighted a dynamic and heterogeneous composition of the tumor. Here we used NGS to characterize the genomic landscape of 418 multiple myeloma cases at diagnosis and correlate this with prognosis and classification. Translocations and copy number abnormalities (CNAs) had a preponderant contribution over gene mutations in defining the genotype and prognosis of each case. Known and novel independent prognostic markers were identified in our cohort of proteasome inhibitor and immunomodulatory drug-treated patients with long follow-up, including events with context-specific prognostic value, such as deletions of the PRDM1 gene. Taking advantage of the comprehensive genomic annotation of each case, we used innovative statistical approaches to identify potential novel myeloma subgroups. We observed clusters of patients stratified based on the overall number of mutations and number/type of CNAs, with distinct effects on survival, suggesting that extended genotype of multiple myeloma at diagnosis may lead to improved disease classification and prognostication

MONITORING MINIMAL RESIDUAL DISEASE IN MULTIPLE MYELOMA PATIENTS BY NGS APPROACHES

Novel treatments for multiple myeloma (MM) have increased rates of complete response (CR) raising interest in more accurate methods to evaluate residual disease. Cell-free tumor DNA (cfDNA) analysis could represent a minimally invasive approach complementary to multiparameter flow cytometry (MFC) and molecular methods on bone marrow (BM) aspirates. A sequencing approach using the Ion Torrent Personal Genome Machine was applied to identify clonal immunoglobulin heavy chain (IGH) gene rearrangements in tumor plasma cells (PCs) and in serial plasma samples of 25 MM patients receiving second-line therapy. The same clonal IGH rearrangement identified in tumor PCs was detected in paired plasma samples and levels of IGH cfDNA correlated with outcome and mirrored tumor dynamics evaluated using conventional laboratory parameters. In addition, IGH cfDNA levels reflected the number of PCs enumerated by MFC immunophenotyping even in the CR context. Minimal residual disease (MRD)-negative patients by MFC were characterized by low frequencies of tumor clonotypes in cfDNA and longer survival. Despite the limited sample size, results showed that our developed deep-sequencing workflow is feasible for the identification and the monitoring of IGH gene rearrangements in tumor samples and in serial plasma samples of patients affected by MM. Moreover, since our method is based on a straightforward pipeline tailored for the analysis of the monoclonal B-cell expansion, we decided to evaluate the possibility of applying our developed NGS workflow in the non-invasive monitoring of other mature B-cell neoplasms such as diffuse large B-cell lymphomas (DLBCLs) and Hodgkin lymphomas (HLs) that have very rarely circulating tumor cells, but release tumor DNA in the bloodstream. Profiling the IGH repertoire of 26 newly diagnosed DLBCL patients we demonstrated that our NGS workflow allows the identification of clonal IGH rearrangements in archival formalin-fixed paraffin-embedded (FFPE) tissue biopsies and paired cfDNA samples. IGH cfDNA frequencies reflected levels of DLBCL burden detected by imaging modalities at diagnosis and during the course of treatment. In HL cases (n=20), data obtained applying a reverse approach and starting with the analysis of cfDNA to overcome the limitations imposed by the paucity of tumor cells in tissue biopsies, suggested that methods to select pure HL tumor cells are mandatory to exclude inflammatory contamination and to identify clonal IGH rearrangements in HL. Overall, results I have obtained during my PhD project confirm the clinical utility of IGH cfDNA in the evaluation of tumor burden and response to treatment in mature B-cell malignancies, and support the application of the developed NGS workflow in large prospective studies that will validate the feasibility in the clinical setting and the prognostic value of disease monitoring through the quantitative assessment of plasma clonotypic IGH gene rearrangements

Deconvolution of in vivo protein-RNA contacts using fractionated eCLIP-seq

Original uncropped autoradiogram and gel images in Figures 1, 2A, 5, 6A and S1.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Precision analysis of mutant U2AF1 activity reveals deployment of stress granules in myeloid malignancies. Biancon et al.

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Non-invasive molecular monitoring in multiple myeloma patients using cell-free tumor DNA: a pilot study

Novel treatments for multiple myeloma (MM) have increased rates of complete response raising interest in more accurate methods to evaluate residual disease. Cell-free tumor DNA (cfDNA) analysis may represent a minimally invasive approach complementary to multiparameter flow cytometry (MFC) and molecular methods on bone marrow aspirates. A sequencing approach using the Ion Torrent Personal Genome Machine was applied to identify clonal immunoglobulin heavy chain (IGH) gene rearrangements in tumor plasma cells (PCs) and in serial plasma samples of 25 MM patients receiving second-line therapy. The same clonal IGH rearrangement identified in tumor PCs was detected in paired plasma samples and levels of IGH cfDNA correlated with outcome and mirrored tumor dynamics evaluated using conventional laboratory parameters. In addition IGH cfDNA levels reflected the number of PCs enumerated by MFC immunophenotyping even in the complete response context. Minimal residual disease negative patients by MFC were characterized by low frequencies of tumor clonotypes in cfDNA and longer survival. This pilot study supports the clinical applicability of the non-invasive monitoring of tumor levels in plasma samples of MM patients by IGH sequencing

A novel method for the detection of minimal residual disease in B-cell malignancies : ion semiconductor sequencing for the evaluation of Igh gene rearrangements

[Poster Abstracts. 622. Non-Hodgkin Lymphoma: Biology, excluding Therapy: Poster II. A Novel Method for the Detection of Minimal Residual Disease in B-Cell Malignancies: Ion Semiconductor Sequencing for the Evaluation of Igh Gene Rearrangements]