MALAT1 expression is associated with aggressive behavior in indolent B-cell neoplasms.

MALAT1 long non-coding RNA has oncogenic roles but has been poorly studied in indolent B-cell neoplasms. Here, MALAT1 expression was analyzed using RNA-seq, microarrays or qRT-PCR in primary samples from clinico-biological subtypes of chronic lymphocytic leukemia (CLL, n = 266), paired Richter transformation (RT, n = 6) and follicular lymphoma (FL, n = 61). In peripheral blood (PB) CLL samples, high MALAT1 expression was associated with a significantly shorter time to treatment independently from other known prognostic factors. Coding genes expressed in association with MALAT1 in CLL were predominantly related to oncogenic pathways stimulated in the lymph node (LN) microenvironment. In RT paired samples, MALAT1 levels were lower, concordant with their acquired increased independency of external signals. Moreover, MALAT1 levels in paired PB/LN CLLs were similar, suggesting that the prognostic value of MALAT1 expression in PB is mirroring expression differences already present in LN. Similarly, high MALAT1 expression in FL predicted for a shorter progression-free survival, in association with expression pathways promoting FL pathogenesis. In summary, MALAT1 expression is related to pathophysiology and more aggressive clinical behavior of indolent B-cell neoplasms. Particularly in CLL, its levels could be a surrogate marker of the microenvironment stimulation and may contribute to refine the clinical management of these patients.

RFcaller: a machine learning approach combined with read-level features to detect somatic mutations.

The cost reduction in sequencing and the extensive genomic characterization of a wide variety of cancers are expanding tumor sequencing to a wide number of research groups and the clinical practice. Although specific pipelines have been generated for the identification of somatic mutations, their results usually differ considerably, and a common approach is to use several callers to achieve a more reliable set of mutations. This procedure is computationally expensive and time-consuming, and it suffers from the same limitations in sensitivity and specificity as other approaches. Expert revision of mutant calls is therefore required to verify calls that might be used for clinical diagnosis. This step could take advantage of machine learning techniques, as they provide a useful approach to incorporate expert-reviewed information for the identification of somatic mutations. Here we present RFcaller, a pipeline based on machine learning algorithms, for the detection of somatic mutations in tumor-normal paired samples that does not require large computing resources. RFcaller shows high accuracy for the detection of substitutions and insertions/deletions from whole genome or exome data. It allows the detection of mutations in driver genes missed by other approaches, and has been validated by comparison to deep and Sanger sequencing.

The Oncogenic FOXL2 C134W Mutation Is a Key Driver of Granulosa Cell Tumors.

Adult-type granulosa cell tumors (AGCT) are the most common type of malignant ovarian sex cord-stromal tumors. Most AGCTs carry the somatic variant c.402C>G (p.C134W) affecting the transcription factor FOXL2. Germline dominant variants in FOXL2 are responsible for blepharophimosis syndrome, which is characterized by underdevelopment of the eyelid. In this work, we generated a mouse model harboring the C134W variant of FOXL2 to evaluate in vivo the poorly understood oncogenic role of FOXL2. The mutation was dominant regarding eyelid hypoplasia, reminiscent of blepharophimosis syndrome. Interestingly, Foxl2+/C134W female mice had reduced fertility and developed AGCTs through a progression from abnormal ovaries with aberrant granulosa cells to ovaries with stromal hyperplasia and atypia and on to tumors in adut mice. The genes dysregulated in mouse AGCTs exhibited the hallmarks of cancer and were consistent with a gain-of-function of the mutated allele affecting TGFß signaling. A comparison of these data with previous results on human AGCTs indicated similar deregulated pathways. Finally, a mutational analysis of mouse AGCT transcriptomic data suggested the absence of additional driver mutations apart from FOXL2-C134W. These results provide a clear in vivo example in which a single mutational hit triggers tumor development associated with profound transcriptomic alterations. SIGNIFICANCE: A newly generated mouse model carrying a FOXL2 mutation characteristic of adult-type granulosa cell tumors shows that FOXL2 C134W shifts the transcriptome towards a signature of granulosa cell cancer and drives tumorigenesis.

Molecular map of chronic lymphocytic leukemia and its impact on outcome.

Recent advances in cancer characterization have consistently revealed marked heterogeneity, impeding the completion of integrated molecular and clinical maps for each malignancy. Here, we focus on chronic lymphocytic leukemia (CLL), a B cell neoplasm with variable natural history that is conventionally categorized into two subtypes distinguished by extent of somatic mutations in the heavy-chain variable region of immunoglobulin genes (IGHV). To build the 'CLL map,' we integrated genomic, transcriptomic and epigenomic data from 1,148 patients. We identified 202 candidate genetic drivers of CLL (109 new) and refined the characterization of IGHV subtypes, which revealed distinct genomic landscapes and leukemogenic trajectories. Discovery of new gene expression subtypes further subcategorized this neoplasm and proved to be independent prognostic factors. Clinical outcomes were associated with a combination of genetic, epigenetic and gene expression features, further advancing our prognostic paradigm. Overall, this work reveals fresh insights into CLL oncogenesis and prognostication.

Detection of early seeding of Richter transformation in chronic lymphocytic leukemia.

Richter transformation (RT) is a paradigmatic evolution of chronic lymphocytic leukemia (CLL) into a very aggressive large B cell lymphoma conferring a dismal prognosis. The mechanisms driving RT remain largely unknown. We characterized the whole genome, epigenome and transcriptome, combined with single-cell DNA/RNA-sequencing analyses and functional experiments, of 19 cases of CLL developing RT. Studying 54 longitudinal samples covering up to 19 years of disease course, we uncovered minute subclones carrying genomic, immunogenetic and transcriptomic features of RT cells already at CLL diagnosis, which were dormant for up to 19 years before transformation. We also identified new driver alterations, discovered a new mutational signature (SBS-RT), recognized an oxidative phosphorylation (OXPHOS)high-B cell receptor (BCR)low-signaling transcriptional axis in RT and showed that OXPHOS inhibition reduces the proliferation of RT cells. These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover potential therapeutic targets for RT.

PanCancer analysis of somatic mutations in repetitive regions reveals recurrent mutations in snRNA U2.

Current somatic mutation callers are biased against repetitive regions, preventing the identification of potential driver alterations in these loci. We developed a mutation caller for repetitive regions, and applied it to study repetitive non protein-coding genes in more than 2200 whole-genome cases. We identified a recurrent mutation at position c.28 in the gene encoding the snRNA U2. This mutation is present in B-cell derived tumors, as well as in prostate and pancreatic cancer, suggesting U2 c.28 constitutes a driver candidate associated with worse prognosis. We showed that the GRCh37 reference genome is incomplete, lacking the U2 cluster in chromosome 17, preventing the identification of mutations in this gene. Furthermore, the 5'-flanking region of WDR74, previously described as frequently mutated in cancer, constitutes a functional copy of U2. These data reinforce the relevance of non-coding mutations in cancer, and highlight current challenges of cancer genomic research in characterizing mutations affecting repetitive genes.

Altered regulation of BRCA1 exon 11 splicing is associated with breast cancer risk in carriers of BRCA1 pathogenic variants.

Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre-mRNA splicing, leading to three major in-frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull-down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.

mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies.

Mutational signatures have emerged as powerful biomarkers in cancer patients, with prognostic and therapeutic implications. Wider clinical utility requires access to reproducible algorithms, which allow characterization of mutational signatures in a given tumor sample. Here, we show how mutational signature fitting can be applied to hematological cancer genomes to identify biologically and clinically important mutational processes, highlighting the importance of careful interpretation in light of biological knowledge. Our newly released R package mmsig comes with a dynamic error-suppression procedure that improves specificity in important clinical and biological settings. In particular, mmsig allows accurate detection of mutational signatures with low abundance, such as those introduced by APOBEC cytidine deaminases. This is particularly important in the most recent mutational signature reference (COSMIC v3.1) where each signature is more clearly defined. Our mutational signature fitting algorithm mmsig is a robust tool that can be implemented immediately in the clinic.

IGLV3-21R110 identifies an aggressive biological subtype of chronic lymphocytic leukemia with intermediate epigenetics.

B-cell receptor (BCR) signaling is crucial for chronic lymphocytic leukemia (CLL) biology. IGLV3-21-expressing B cells may acquire a single point mutation (R110) that triggers autonomous BCR signaling, conferring aggressive behavior. Epigenetic studies have defined 3 CLL subtypes based on methylation signatures reminiscent of naïve-like (n-CLL), intermediate (i-CLL), and memory-like (m-CLL) B cells with different biological features. i-CLL carries a borderline IGHV mutational load and significantly higher use of IGHV3-21/IGLV3-21. To determine the clinical and biological features of IGLV3-21R110 CLL and its relationship to these epigenetic subtypes, we characterized the immunoglobulin gene of 584 CLL cases using whole-genome/exome and RNA sequencing. IGLV3-21R110 was detected in 6.5% of cases: 30 (38%) of 79 i-CLLs, 5 (1.7%) of 291 m-CLLs, and 1 (0.5%) of 189 n-CLLs. All stereotype subset 2 cases carried IGLV3-21R110, whereas 62% of IGLV3-21R110 i-CLL cases had nonstereotyped BCR immunoglobulins. IGLV3-21R110 i-CLL had a significantly higher number of SF3B1 and ATM mutations and total number of driver alterations. However, the R110 mutation was the sole alteration in 1 i-CLL and was accompanied only by del(13q) in 3. Although IGHV mutational status varied, IGLV3-21R110 i-CLL transcriptomically resembled n-CLL/unmutated IGHV CLL with a specific signature including WNT5A/B overexpression. In contrast, i-CLL lacking IGLV3-21R110 mirrored m-CLL/mutated IGHV. Patients with IGLV3-21R110 i-CLL had a short time to first treatment and overall survival similar to those of n-CLL/unmutated IGHV patients, whereas patients with non-IGLV3-21R110 i-CLL had a good prognosis similar to that of patients with m-CLL/mutated IGHV. IGLV3-21R110 defines a CLL subgroup with specific biological features and an unfavorable prognosis independent of IGHV mutational status and epigenetic subtype.

Circulating tumour DNA from the cerebrospinal fluid allows the characterisation and monitoring of medulloblastoma.

The molecular characterisation of medulloblastoma, the most common paediatric brain tumour, is crucial for the correct management and treatment of this heterogenous disease. However, insufficient tissue sample, the presence of tumour heterogeneity, or disseminated disease can challenge its diagnosis and monitoring. Here, we report that the cerebrospinal fluid (CSF) circulating tumour DNA (ctDNA) recapitulates the genomic alterations of the tumour and facilitates subgrouping and risk stratification, providing valuable information about diagnosis and prognosis. CSF ctDNA also characterises the intra-tumour genomic heterogeneity identifying small subclones. ctDNA is abundant in the CSF but barely present in plasma and longitudinal analysis of CSF ctDNA allows the study of minimal residual disease, genomic evolution and the characterisation of tumours at recurrence. Ultimately, CSF ctDNA analysis could facilitate the clinical management of medulloblastoma patients and help the design of tailored therapeutic strategies, increasing treatment efficacy while reducing excessive treatment to prevent long-term secondary effects.

IgCaller for reconstructing immunoglobulin gene rearrangements and oncogenic translocations from whole-genome sequencing in lymphoid neoplasms.

Immunoglobulin (Ig) gene rearrangements and oncogenic translocations are routinely assessed during the characterization of B cell neoplasms and stratification of patients with distinct clinical and biological features, with the assessment done using Sanger sequencing, targeted next-generation sequencing, or fluorescence in situ hybridization (FISH). Currently, a complete Ig characterization cannot be extracted from whole-genome sequencing (WGS) data due to the inherent complexity of the Ig loci. Here, we introduce IgCaller, an algorithm designed to fully characterize Ig gene rearrangements and oncogenic translocations from short-read WGS data. Using a cohort of 404 patients comprising different subtypes of B cell neoplasms, we demonstrate that IgCaller identifies both heavy and light chain rearrangements to provide additional information on their functionality, somatic mutational status, class switch recombination, and oncogenic Ig translocations. Our data thus support IgCaller to be a reliable alternative to Sanger sequencing and FISH for studying the genetic properties of the Ig loci.

Genomic and epigenomic insights into the origin, pathogenesis, and clinical behavior of mantle cell lymphoma subtypes.

Mantle cell lymphoma (MCL) is a mature B-cell neoplasm initially driven by CCND1 rearrangement with 2 molecular subtypes, conventional MCL (cMCL) and leukemic non-nodal MCL (nnMCL), that differ in their clinicobiological behavior. To identify the genetic and epigenetic alterations determining this diversity, we used whole-genome (n = 61) and exome (n = 21) sequencing (74% cMCL, 26% nnMCL) combined with transcriptome and DNA methylation profiles in the context of 5 MCL reference epigenomes. We identified that open and active chromatin at the major translocation cluster locus might facilitate the t(11;14)(q13;32), which modifies the 3-dimensional structure of the involved regions. This translocation is mainly acquired in precursor B cells mediated by recombination-activating genes in both MCL subtypes, whereas in 8% of cases the translocation occurs in mature B cells mediated by activation-induced cytidine deaminase. We identified novel recurrent MCL drivers, including CDKN1B, SAMHD1, BCOR, SYNE1, HNRNPH1, SMARCB1, and DAZAP1. Complex structural alterations emerge as a relevant early oncogenic mechanism in MCL, targeting key driver genes. Breakage-fusion-bridge cycles and translocations activated oncogenes (BMI1, MIR17HG, TERT, MYC, and MYCN), generating gene amplifications and remodeling regulatory regions. cMCL carried significant higher numbers of structural variants, copy number alterations, and driver changes than nnMCL, with exclusive alterations of ATM in cMCL, whereas TP53 and TERT alterations were slightly enriched in nnMCL. Several drivers had prognostic impact, but only TP53 and MYC aberrations added value independently of genomic complexity. An increasing genomic complexity, together with the presence of breakage-fusion-bridge cycles and high DNA methylation changes related to the proliferative cell history, defines patients with different clinical evolution.

Timing the initiation of multiple myeloma.

The evolution and progression of multiple myeloma and its precursors over time is poorly understood. Here, we investigate the landscape and timing of mutational processes shaping multiple myeloma evolution in a large cohort of 89 whole genomes and 973 exomes. We identify eight processes, including a mutational signature caused by exposure to melphalan. Reconstructing the chronological activity of each mutational signature, we estimate that the initial transformation of a germinal center B-cell usually occurred during the first 2nd-3rd decades of life. We define four main patterns of activation-induced deaminase (AID) and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) mutagenesis over time, including a subset of patients with evidence of prolonged AID activity during the pre-malignant phase, indicating antigen-responsiveness and germinal center reentry. Our findings provide a framework to study the etiology of multiple myeloma and explore strategies for prevention and early detection.

Genomic and Epigenomic Alterations in Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia is a common disease in Western countries and has heterogeneous clinical behavior. The relevance of the genetic basis of the disease has come to the forefront recently, with genome-wide studies that have provided a comprehensive view of structural variants, somatic mutations, and different layers of epigenetic changes. The mutational landscape is characterized by relatively common copy number alterations, a few mutated genes occurring in 10-15% of cases, and a large number of genes mutated in a small number of cases. The epigenomic profile has revealed a marked reprogramming of regulatory regions in tumor cells compared with normal B cells. All of these alterations are differentially distributed in clinical and biological subsets of the disease, indicating that they may underlie the heterogeneous evolution of the disease. These global studies are revealing the molecular complexity of chronic lymphocytic leukemia and provide new perspectives that have helped to understand its pathogenic mechanisms and improve the clinical management of patients.

Specific NOTCH1 antibody targets DLL4-induced proliferation, migration, and angiogenesis in NOTCH1-mutated CLL cells.

Targeting Notch signaling has emerged as a promising therapeutic strategy for chronic lymphocytic leukemia (CLL), particularly in NOTCH1-mutated patients. We provide first evidence that the Notch ligand DLL4 is a potent stimulator of Notch signaling in NOTCH1-mutated CLL cells while increases cell proliferation. Importantly, DLL4 is expressed in histiocytes from the lymph node, both in NOTCH1-mutated and -unmutated cases. We also show that the DLL4-induced activation of the Notch signaling pathway can be efficiently blocked with the specific anti-Notch1 antibody OMP-52M51. Accordingly, OMP-52M51 also reverses Notch-induced MYC, CCND1, and NPM1 gene expression as well as cell proliferation in NOTCH1-mutated CLL cells. In addition, DLL4 stimulation triggers the expression of protumor target genes, such as CXCR4, NRARP, and VEGFA, together with an increase in cell migration and angiogenesis. All these events can be antagonized by OMP-52M51. Collectively, our results emphasize the role of DLL4 stimulation in NOTCH1-mutated CLL and confirm the specific therapeutic targeting of Notch1 as a promising approach for this group of poor prognosis CLL patients.

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome.

We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.