The U1 spliceosomal RNA is recurrently mutated in multiple cancers.

Cancers are caused by genomic alterations known as drivers. Hundreds of drivers in coding genes are known but, to date, only a handful of noncoding drivers have been discovered-despite intensive searching1,2. Attention has recently shifted to the role of altered RNA splicing in cancer; driver mutations that lead to transcriptome-wide aberrant splicing have been identified in multiple types of cancer, although these mutations have only been found in protein-coding splicing factors such as splicing factor 3b subunit 1 (SF3B1)3-6. By contrast, cancer-related alterations in the noncoding component of the spliceosome-a series of small nuclear RNAs (snRNAs)-have barely been studied, owing to the combined challenges of characterizing noncoding cancer drivers and the repetitive nature of snRNA genes1,7,8. Here we report a highly recurrent A>C somatic mutation at the third base of U1 snRNA in several types of tumour. The primary function of U1 snRNA is to recognize the 5' splice site via base-pairing. This mutation changes the preferential A-U base-pairing between U1 snRNA and the 5' splice site to C-G base-pairing, and thus creates novel splice junctions and alters the splicing pattern of multiple genes-including known drivers of cancer. Clinically, the A>C mutation is associated with heavy alcohol use in patients with hepatocellular carcinoma, and with the aggressive subtype of chronic lymphocytic leukaemia with unmutated immunoglobulin heavy-chain variable regions. The mutation in U1 snRNA also independently confers an adverse prognosis to patients with chronic lymphocytic leukaemia. Our study demonstrates a noncoding driver in spliceosomal RNAs, reveals a mechanism of aberrant splicing in cancer and may represent a new target for treatment. Our findings also suggest that driver discovery should be extended to a wider range of genomic regions.

Recurrent noncoding U1 snRNA mutations drive cryptic splicing in SHH medulloblastoma.

In cancer, recurrent somatic single-nucleotide variants-which are rare in most paediatric cancers-are confined largely to protein-coding genes1-3. Here we report highly recurrent hotspot mutations (r.3A>G) of U1 spliceosomal small nuclear RNAs (snRNAs) in about 50% of Sonic hedgehog (SHH) medulloblastomas. These mutations were not present across other subgroups of medulloblastoma, and we identified these hotspot mutations in U1 snRNA in only <0.1% of 2,442 cancers, across 36 other tumour types. The mutations occur in 97% of adults (subtype SHHδ) and 25% of adolescents (subtype SHHα) with SHH medulloblastoma, but are largely absent from SHH medulloblastoma in infants. The U1 snRNA mutations occur in the 5' splice-site binding region, and snRNA-mutant tumours have significantly disrupted RNA splicing and an excess of 5' cryptic splicing events. Alternative splicing mediated by mutant U1 snRNA inactivates tumour-suppressor genes (PTCH1) and activates oncogenes (GLI2 and CCND2), and represents a target for therapy. These U1 snRNA mutations provide an example of highly recurrent and tissue-specific mutations of a non-protein-coding gene in cancer.

Featuring BRCA1 and BRCA2 germline mutational landscape from Asturias (North Spain).

The singular BRCA1/2 mutational landscape of Asturias is updated 10 years after the first study. We analyzed BRCA1 and BRCA2 pathogenic variants in 1653 index cases. In total, 238 families were identified to carry a pathogenic variant, 163 families in BRCA1 and 75 families in BRCA2. This yielded a prevalence rate of 14.4%. Seven recurrent variants were found accounting for 55% of the cases. Among them, three are widely distributed (BRCA1 c.211A>G, c.470_471del and c.3331_3334del) and four had been reported as novel in Asturias: two in BRCA1 (c.1674del and c.2901_2902dup) and two in BRCA2 (c.2095C>T and c.4040_4035delinsC). A common haplotype was established for all recurrent variants indicating a shared ancestral origin. Three splicing analyses are shown: BRCA1:c.5152+3A>C and BRCA1:c.5333-3T>G that lead to skipping of exon 18, and 22 respectively, and BRCA1:c.5278-1G>T giving rise to two transcripts, one lacking exon 21 (p.Ille1760Glyfs*60) and one lacking the first 8 nucleotides of exon 21 (p.Phe1761Asnfs*14), supporting pathogenicity for these variants.

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.

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.

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.

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.

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.

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.

Chromosome 12p Amplification in Triple-Negative/BRCA1-Mutated Breast Cancer Associates with Emergence of Docetaxel Resistance and Carboplatin Sensitivity.

Taxanes are the mainstay of treatment in triple-negative breast cancer (TNBC), with de novo and acquired resistance limiting patient's survival. To investigate the genetic basis of docetaxel resistance in TNBC, exome sequencing was performed on matched TNBC patient-derived xenografts (PDX) sensitive to docetaxel and their counterparts that developed resistance in vivo upon continuous drug exposure. Most mutations, small insertions/deletions, and copy number alterations detected in the initial TNBC human metastatic samples were maintained after serial passages in mice and emergence of resistance. We identified a chromosomal amplification of chr12p in a human BRCA1-mutated metastatic sample and the derived chemoresistant PDX, but not in the matched docetaxel-sensitive PDX tumor. Chr12p amplification was validated in a second pair of docetaxel-sensitive/resistant BRCA1-mutated PDXs and after short-term docetaxel treatment in several TNBC/BRCA1-mutated PDXs and cell lines, as well as during metastatic recurrence in a patient with BRCA1-mutated breast cancer who had progressed on docetaxel treatment. Analysis of clinical data indicates an association between chr12p amplification and patients with TNBC/basal-like breast cancer, a BRCA1 mutational signature, and poor survival after chemotherapy. Detection of chr12p amplification in a cohort of TNBC PDX models was associated with an improved response to carboplatin. Our findings reveal tumor clonal dynamics during chemotherapy treatments and suggest that a preexisting population harboring chr12p amplification is associated with the emergence of docetaxel resistance and carboplatin responsiveness in TNBC/BRCA1-mutated tumors. SIGNIFICANCE: Chr12p copy number gains indicate rapid emergence of resistance to docetaxel and increased sensitivity to carboplatin, therefore sequential docetaxel/carboplatin treatment could improve survival in TNBC/BRCA1 patients. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/79/16/4258/F1.large.jpg.

Dissecting Degradomes: Analysis of Protease-Coding Genes.

Proteases constitute up to 3% of all protein-coding genes in a vertebrate genome and participate in numerous physiological and pathological processes. The characterization of the degradome of one organism, the set of all genes encoding proteolytic enzymes, and the comparison to the degradome of other species have proved useful to identify genetic differences that are helpful to elucidate the molecular basis of diverse biological processes, the different susceptibility to disease, and the evolution of the structure and function of proteases. Here we describe the main procedures involved in the characterization of the degradome of an organism for which its genome sequence is available.

Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance.

Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs), we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2) is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA) supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.