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Key Points MicroRNAs (miRNAs) have important functions in controlling many cell properties, including cell growth and differentiation. Their dysregulation is a frequent contributor to cancer growth and progression. miRNAs post-transcriptionally regulate biological processes through their coordinated activities on pathways and networks. miRNAs act cooperatively with other miRNAs and with transcription factors, which are frequent targets of miRNAs. miRNAs typically act as control nodes or hubs in regulatory networks. Delineating their functional effects requires elucidation of their upstream regulators and downstream targets. In silico and experimental methods for identifying direct targets of miRNAs are advancing rapidly. Information from patient-derived mass-transcriptomic data sets will contribute enormously to future efforts to derive clinically relevant outcomes from complex biological networks. MicroRNAs (miRNAs) have emerged as crucial components of gene-regulatory networks, in which they act alone or cooperatively to regulate gene expression. Here, the authors provide a systems-biological view of miRNA function and how disruption of miRNA networks can lead to malignancy. MicroRNAs (miRNAs) participate in most aspects of cellular differentiation and homeostasis, and consequently have roles in many pathologies, including cancer. These small non-coding RNAs exert their effects in the context of complex regulatory networks, often made all the more extensive by the inclusion of transcription factors as their direct targets. In recent years, the increased availability of gene expression data and the development of methodologies that profile miRNA targets en masse have fuelled our understanding of miRNA functions, and of the sources and consequences of miRNA dysregulation. Advances in experimental and computational approaches are revealing not just cancer pathways controlled by single miRNAs but also intermeshed regulatory networks controlled by multiple miRNAs, which often engage in reciprocal feedback interactions with the targets that they regulate.

An analysis of the HLA class I loci in 7,930 tumor samples detects recurrent mutation 'hotspots' in these genes. Detection of somatic mutations in human leukocyte antigen (HLA) genes using whole-exome sequencing (WES) is hampered by the high polymorphism of the HLA loci, which prevents alignment of sequencing reads to the human reference genome. We describe a computational pipeline that enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using the inferred alleles as a reference. Analysis of WES data from 7,930 pairs of tumor and healthy tissue from the same patient revealed 298 nonsilent HLA mutations in tumors from 266 patients. These 298 mutations are enriched for likely functional mutations, including putative loss-of-function events. Recurrence of mutations suggested that these 'hotspot' sites were positively selected. Cancers with recurrent somatic HLA mutations were associated with upregulation of signatures of cytolytic activity characteristic of tumor infiltration by effector lymphocytes, supporting immune evasion by altered HLA function as a contributory mechanism in cancer.

Key Points RNA-based measurements have the potential for application across diverse areas of human health, including disease diagnosis, prognosis and therapeutic selection. Current clinical applications include infectious diseases, cancer, transplant medicine and fetal monitoring. RNA sequencing (RNA-seq) allows for the detection of a wide variety of RNA species, including mRNA, non-coding RNA, pathogen RNA, chimeric gene fusions, transcript isoforms and splice variants, and provides the capability to quantify known, pre-defined RNA species and rare RNA transcript variants within a sample. In addition to differential expression and detection of novel transcripts, RNA-seq also supports the detection of mutations and germline variation for hundreds to thousands of expressed genetic variants, facilitating assessment of allele-specific expression of these variants. Circulating RNAs and small regulatory RNAs, such as microRNAs, are very stable. These RNA species are vigorously being tested for their potential as biomarkers. However, there are currently few agreed upon methods for isolation or quantitative measurements and a current lack of quality controls that can be used to test platform accuracy and sample preparation quality. Analytical, bioinformatic and regulatory challenges exist, and ongoing efforts toward the establishment of benchmark standards, assay optimization for clinical conditions and demonstration of assay reproducibility are required to expand the clinical utility of RNA-seq. RNA sequencing (RNA-seq) is a powerful approach for comprehensive analyses of transcriptomes. This Review describes the widespread potential applications of RNA-seq in clinical medicine, such as detecting disease-associated mutations and gene expression disruptions, as well as characteristic non-coding RNAs, circulating extracellular RNAs or pathogen RNAs. The authors also highlight the challenges in adopting RNA-seq routinely into clinical practice. With the emergence of RNA sequencing (RNA-seq) technologies, RNA-based biomolecules hold expanded promise for their diagnostic, prognostic and therapeutic applicability in various diseases, including cancers and infectious diseases. Detection of gene fusions and differential expression of known disease-causing transcripts by RNA-seq represent some of the most immediate opportunities. However, it is the diversity of RNA species detected through RNA-seq that holds new promise for the multi-faceted clinical applicability of RNA-based measures, including the potential of extracellular RNAs as non-invasive diagnostic indicators of disease. Ongoing efforts towards the establishment of benchmark standards, assay optimization for clinical conditions and demonstration of assay reproducibility are required to expand the clinical utility of RNA-seq.

Key Points DNA methyltransferase 3A (DNMT3A) belongs to a family of highly conserved DNA methyltransferases that catalyse 5-methylcytosine methylation. Regulatory domains of DNMT3A allow interactions with histone methyltransferases and histones to influence gene expression. DNMT3A is important in embryonic and haematopoietic stem cell (HSC) differentiation, and interacts with DNMT3B to regulate the function of stem cells. Loss of murine Dnmt3a causes unprecedented HSC expansion, clonal dominance, aberrant DNA methylation, an unrepressed stem cell programme and, eventually, haematological malignancies. DNMT3A mutations occur in human HSCs, in which they can act as a pre-leukaemic lesion. Mutant HSC progeny are found in all differentiated lineages in some patients with acute myeloid leukaemia (AML), and mutant HSCs persist during disease remission. DNMT3A mutations occur in diverse haematological malignancies with unique mutational profiles. The R882 hotspot mutation occurs most frequently in AML and has been shown to act as a dominant-negative inhibitor of wild-type DNMT3A enzymatic activity. DNMT3A mutations non-randomly co-occur with a number of other mutations but can also be essentially mutually exclusive of others. This pattern suggests important biological relationships among these genes. The prognostic impact of DNMT3A mutations across various haematological malignancies is inconclusive. A number of studies have found that mutations of DNMT3A confer a poor prognosis, but others have found that DNMT3A status is prognostically neutral. Haematopoiesis becomes clonal in a significant portion of ageing individuals and is associated with increased incidence of haematological malignancy and all-cause mortality; mutations in DNMT3A are highly associated with this phenomenon. Given the strong association between DNMT3A mutations and many types of haematological malignancy and the relatively poor understanding of its mechanistic function, DNMT3A represents an important new target for research and novel therapeutic approaches. Mutations in the gene encoding DNA methyltransferase 3A (DNMT3A) have been reported in patients with various haematological malignancies, suggesting that DNMT3A could be a tumour suppressor. In this Review, Yang et al . put data from basic science studies into clinical context, opening stimulating discussions regarding possible new therapeutic avenues. DNA methylation patterns are disrupted in various malignancies, suggesting a role in the development of cancer, but genetic aberrations directly linking the DNA methylation machinery to malignancies were rarely observed, so this association remained largely correlative. Recently, however, mutations in the gene encoding DNA methyltransferase 3A (DNMT3A) were reported in patients with acute myeloid leukaemia (AML), and subsequently in patients with various other haematological malignancies, pointing to DNMT3A as a critically important new tumour suppressor. Here, we review the clinical findings related to DNMT3A, tie these data to insights from basic science studies conducted over the past 20 years and present a roadmap for future research that should advance the agenda for new therapeutic strategies.

Key Points Methods for tracing lineage can be divided into two groups. Prospective methods trace lineage forwards from the application of an experimentally delivered marker, and retrospective methods trace lineage backwards, using endogenous marks that naturally accumulate in the genome. Early methods using sparse retroviral labelling for prospective lineage tracing have given way to retroviral barcodes of essentially unlimited complexity, allowing the labelling and recovery of large populations of cells for lineage tracing experiments. Genetic recombination with Cre- loxP or engineered transposon systems is a popular method for lineage tracing in genetically accessible model organisms. Recent work has demonstrated that CRISPR–Cas9 genome editing is a promising way to track and synthetically reconstruct cell lineage relationships in complex multicellular organisms, and may supplement or supplant older recombination-based systems in the future. Recent advances in single-cell genome amplification and sequencing make it possible to harness naturally occurring somatic mutations to infer cell lineage information retrospectively. Somatic mutations of many classes, including long interspersed nuclear element 1 (L1; also known as LINE-1) retrotransposition events, copy-number variants, single-nucleotide variants and microsatellite length variants, are appropriate for lineage tracing. Single-cell genome-sequencing experiments require genome amplification, and investigators must consider the frequencies and types of errors that are introduced by different amplification methods to select an approach that best balances signal and noise for the experiment at hand. When designing a lineage tracing experiment, it is important to consider the strengths and weaknesses of either a prospective or a retrospective approach. Prospective approaches require genetic access to the cell population being labelled, but can often be higher throughput and less expensive than retrospective approaches. Retrospective approaches use marks that accumulate in the genome, making any purifiable population accessible to analysis, but can be low-throughput and expensive. Lineage analyses of multicellular organisms provide key insights into developmental mechanisms and how these developmental trajectories go awry in diverse diseases. This Review discusses the features, technical challenges and latest opportunities of an evolving range of sophisticated genetic techniques for tracking cell lineages in organisms. These strategies include methods for prospective tracking using engineered genetic constructs, as well as retrospective tracking based on naturally occurring somatic mutations. Resolving lineage relationships between cells in an organism is a fundamental interest of developmental biology. Furthermore, investigating lineage can drive understanding of pathological states, including cancer, as well as understanding of developmental pathways that are amenable to manipulation by directed differentiation. Although lineage tracking through the injection of retroviral libraries has long been the state of the art, a recent explosion of methodological advances in exogenous labelling and single-cell sequencing have enabled lineage tracking at larger scales, in more detail, and in a wider range of species than was previously considered possible. In this Review, we discuss these techniques for cell lineage tracking, with attention both to those that trace lineage forwards from experimental labelling, and those that trace backwards across the life history of an organism.

Valid variant calling results are crucial for the use of next-generation sequencing in clinical routine. However, there are numerous variant calling tools that usually differ in algorithms, filtering strategies, recommendations and thus, also in the output. We evaluated eight open-source tools regarding their ability to call single nucleotide variants and short indels with allelic frequencies as low as 1% in non-matched next-generation sequencing data: GATK HaplotypeCaller, Platypus, VarScan, LoFreq, FreeBayes, SNVer, SAMtools and VarDict. We analysed two real datasets from patients with myelodysplastic syndrome, covering 54 Illumina HiSeq samples and 111 Illumina NextSeq samples. Mutations were validated by re-sequencing on the same platform, on a different platform and expert based review. In addition we considered two simulated datasets with varying coverage and error profiles, covering 50 samples each. In all cases an identical target region consisting of 19 genes (42,322 bp) was analysed. Altogether, no tool succeeded in calling all mutations. High sensitivity was always accompanied by low precision. Influence of varying coverages- and background noise on variant calling was generally low. Taking everything into account, VarDict performed best. However, our results indicate that there is a need to improve reproducibility of the results in the context of multithreading.

Arul Chinnaiyan and colleagues identify NAB2 - STAT6 fusions in 52 of 52 solitary fibrous tumor cases. Overexpression of this fusion induced cell proliferation, which could be suppressed by knockdown of EGR1 . A 44-year old woman with recurrent solitary fibrous tumor (SFT)/hemangiopericytoma was enrolled in a clinical sequencing program including whole-exome and transcriptome sequencing. A gene fusion of the transcriptional repressor NAB2 with the transcriptional activator STAT6 was detected. Transcriptome sequencing of 27 additional SFTs identified the presence of a NAB2 - STAT6 gene fusion in all tumors. Using RT-PCR and sequencing, we detected this fusion in all 51 SFTs, indicating high levels of recurrence. Expression of NAB2-STAT6 fusion proteins was confirmed in SFT, and the predicted fusion products harbor the early growth response (EGR)-binding domain of NAB2 fused to the activation domain of STAT6. Overexpression of the NAB2 - STAT6 gene fusion induced proliferation in cultured cells and activated the expression of EGR-responsive genes. These studies establish NAB2 - STAT6 as the defining driver mutation of SFT and provide an example of how neoplasia can be initiated by converting a transcriptional repressor of mitogenic pathways into a transcriptional activator.

Rameen Beroukhim, Ian Dunn, William Hahn and colleagues report genome and exome sequencing of meningiomas. They identified recurrent somatic mutations in AKT1 and SMO . Meningiomas are the most common primary nervous system tumor. The tumor suppressor NF2 is disrupted in approximately half of all meningiomas 1 , but the complete spectrum of genetic changes remains undefined. We performed whole-genome or whole-exome sequencing on 17 meningiomas and focused sequencing on an additional 48 tumors to identify and validate somatic genetic alterations. Most meningiomas had simple genomes, with fewer mutations, rearrangements and copy-number alterations than reported in other tumors in adults. However, several meningiomas harbored more complex patterns of copy-number changes and rearrangements, including one tumor with chromothripsis. We confirmed focal NF2 inactivation in 43% of tumors and found alterations in epigenetic modifiers in an additional 8% of tumors. A subset of meningiomas lacking NF2 alterations harbored recurrent oncogenic mutations in AKT1 (p.Glu17Lys) and SMO (p.Trp535Leu) and exhibited immunohistochemical evidence of activation of these pathways. These mutations were present in therapeutically challenging tumors of the skull base and higher grade. These results begin to define the spectrum of genetic alterations in meningiomas and identify potential therapeutic targets.

5-Hydroxymethylcytosine （5hmC） is an important mammalian DNA epigenetic modification that has been linked to gene regulation and cancer pathogenesis. Here we explored the diagnostic potential of 5hmC in circulating cell-free DNA （cfDNA） using a sensitive chemical labeling-based low-input shotgun sequencing approach. We sequenced cell- free 5hmC from 49 patients of seven different cancer types and found distinct features that could be used to predict cancer types and stages with high accuracy. Specifically, we discovered that lung cancer leads to a progressive global loss of 5hmC in cfDNA, whereas hepatocellular carcinoma and pancreatic cancer lead to disease-specific changes in the cell-free hydroxymethylome. Our proof-of-principle results suggest that cell-free 5hmC signatures may potentially be used not only to identify cancer types but also to track tumor stage in some cancers.

William Harbour, Anne Bowcock and colleagues identify recurrent mutations at codon 625 of SF3B1 in uveal melanomas. These mutations occur in low-grade tumors and are associated with favorable prognosis. Uveal melanoma is the most common primary cancer of the eye and often results in fatal metastasis. Here, we describe mutations occurring exclusively at codon 625 of the SF3B1 gene, encoding splicing factor 3B subunit 1, in low-grade uveal melanomas with good prognosis. Thus, uveal melanoma is among a small group of cancers associated with SF3B1 mutations, and these mutations denote a distinct molecular subset of uveal melanomas.