Diffuse gliomas are the most common primary tumor of the brain and include different subtypes with diverse prognosis. The genomic characterization of diffuse gliomas facilitates their molecular ...diagnosis. The anatomical localization of diffuse gliomas complicates access to tumor specimens for diagnosis, in some cases incurring high-risk surgical procedures and stereotactic biopsies. Recently, cell-free circulating tumor DNA (ctDNA) has been identified in the cerebrospinal fluid (CSF) of patients with brain malignancies.
We performed an analysis of
, ATRX,
, and
gene mutations in two tumor cohorts from The Cancer Genome Atlas (TCGA) including 648 diffuse gliomas. We also performed targeted exome sequencing and droplet digital PCR (ddPCR) analysis of these seven genes in 20 clinical tumor specimens and CSF from glioma patients and performed a histopathologic characterization of the tumors.
Analysis of the mutational status of the
, and
genes allowed the classification of 79% of the 648 diffuse gliomas analyzed, into IDH-wild-type glioblastoma, IDH-mutant glioblastoma/diffuse astrocytoma and oligodendroglioma, each subtype exhibiting diverse median overall survival (1.1, 6.7, and 11.2 years, respectively). We developed a sequencing platform to simultaneously and rapidly genotype these seven genes in CSF ctDNA allowing the subclassification of diffuse gliomas.
The genomic analysis of
, and
gene mutations in CSF ctDNA facilitates the diagnosis of diffuse gliomas in a timely manner to support the surgical and clinical management of these patients.
.
Acquisition of the arterial and haemogenic endothelium fates concurrently occur in the aorta-gonad-mesonephros (AGM) region prior to haematopoietic stem cell (HSC) generation. The arterial programme ...depends on Dll4 and the haemogenic endothelium/HSC on Jag1-mediated Notch1 signalling. How Notch1 distinguishes and executes these different programmes in response to particular ligands is poorly understood. By using two Notch1 activation trap mouse models with different sensitivity, here we show that arterial endothelial cells and HSCs originate from distinct precursors, characterized by different Notch1 signal strengths. Microarray analysis on AGM subpopulations demonstrates that the Jag1 ligand stimulates low Notch strength, inhibits the endothelial programme and is permissive for HSC specification. In the absence of Jag1, endothelial cells experience high Dll4-induced Notch activity and select the endothelial programme, thus precluding HSC formation. Interference with the Dll4 signal by ligand-specific blocking antibodies is sufficient to inhibit the endothelial programme and favour specification of the haematopoietic lineage.
Cancers exhibit extensive mutational heterogeneity, and the resulting long-tail phenomenon complicates the discovery of genes and pathways that are significantly mutated in cancer. We perform a ...pan-cancer analysis of mutated networks in 3,281 samples from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a new algorithm to find mutated subnetworks that overcomes the limitations of existing single-gene, pathway and network approaches. We identify 16 significantly mutated subnetworks that comprise well-known cancer signaling pathways as well as subnetworks with less characterized roles in cancer, including cohesin, condensin and others. Many of these subnetworks exhibit co-occurring mutations across samples. These subnetworks contain dozens of genes with rare somatic mutations across multiple cancers; many of these genes have additional evidence supporting a role in cancer. By illuminating these rare combinations of mutations, pan-cancer network analyses provide a roadmap to investigate new diagnostic and therapeutic opportunities across cancer types.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
Large-scale chromatin features, such as replication time and accessibility influence the rate of somatic and germline mutations at the megabase scale. This article reviews how local chromatin ...structures –e.g., DNA wrapped around nucleosomes, transcription factors bound to DNA– affect the mutation rate at a local scale. It dissects how the interaction of some mutagenic agents and/or DNA repair systems with these local structures influence the generation of mutations. We discuss how this local mutation rate variability affects our understanding of the evolution of the genomic sequence, and the study of the evolution of organisms and tumors.
The accumulation of mutations along the genome sequence is not uniform, and this mutational distribution impacts everything from cancer, to aging, to genome evolution. In this Review, Lopez-Bigas and colleagues explore how local chromatin features contribute to variation in the mutational load along the human genome.
While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer ...Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org .
The quiescent center (QC) maintains the activity of the surrounding stem cells within the root stem cell niche, yet specific molecular players sustaining the low rate of QC cell division remain ...poorly understood. Here, we identified a R2R3-MYB transcription factor, BRAVO (BRASSINOSTEROIDS AT VASCULAR AND ORGANIZING CENTER), acting as a cell-specific repressor of QC divisions in the primary root of Arabidopsis. Ectopic BRAVO expression restricts overall root growth and ceases root regeneration upon damage of the stem cells, demonstrating the role of BRAVO in counteracting Brassinosteroid (BR)-mediated cell division in the QC cells. Interestingly, BR-regulated transcription factor BES1 (BRI1-EMS SUPRESSOR 1) directly represses and physically interacts with BRAVO in vivo, creating a switch that modulates QC divisions at the root stem cell niche. Together, our results define a mechanism for BR-mediated regulation of stem cell quiescence in plants.
Display omitted
•BRAVO is a central stem cell specific component of the Brassinosteroid pathway•BRAVO counteracts BR-mediated cell division to protect the root stem cell niche•BRAVO/BES1 interaction creates a switch to control stem cell quiescence
Maintenance of the stem cell niche is essential for proper root growth, yet the players maintaining quiescence remain poorly characterized. Vilarrasa-Blasi et al. characterize BRAVO, a stem cell specific brassinosteroid-regulated transcription factor that is a negative regulator of quiescence in the root apex. BES1/BRAVO mutual regulation regulates stem cell maintenance.
Gain-of-function mutations often cluster in specific protein regions, a signal that those mutations provide an adaptive advantage to cancer cells and consequently are positively selected during ...clonal evolution of tumours. We sought to determine the overall extent of this feature in cancer and the possibility to use this feature to identify drivers.
We have developed OncodriveCLUST, a method to identify genes with a significant bias towards mutation clustering within the protein sequence. This method constructs the background model by assessing coding-silent mutations, which are assumed not to be under positive selection and thus may reflect the baseline tendency of somatic mutations to be clustered. OncodriveCLUST analysis of the Catalogue of Somatic Mutations in Cancer retrieved a list of genes enriched by the Cancer Gene Census, prioritizing those with dominant phenotypes but also highlighting some recessive cancer genes, which showed wider but still delimited mutation clusters. Assessment of datasets from The Cancer Genome Atlas demonstrated that OncodriveCLUST selected cancer genes that were nevertheless missed by methods based on frequency and functional impact criteria. This stressed the benefit of combining approaches based on complementary principles to identify driver mutations. We propose OncodriveCLUST as an effective tool for that purpose.
OncodriveCLUST has been implemented as a Python script and is freely available from http://bg.upf.edu/oncodriveclust
nuria.lopez@upf.edu or abel.gonzalez@upf.edu
Supplementary data are available at Bioinformatics online.
Recently, distinct mutational footprints observed in metastatic tumors, secondary malignancies and normal human tissues have been demonstrated to be caused by the exposure to several chemotherapeutic ...drugs. These characteristic mutations originate from specific lesions caused by these chemicals to the DNA of exposed cells. However, it is unknown whether the exposure to these chemotherapies leads to a specific footprint of larger chromosomal aberrations. Here, we address this question exploiting whole genome sequencing data of metastatic tumors obtained from patients exposed to different chemotherapeutic drugs. As a result, we discovered a specific copy number footprint across tumors from patients previously exposed to platinum-based therapies. This footprint is characterized by a significant increase in the number of chromosomal fragments of copy number 1-4 and size smaller than 10 Mb in exposed tumors with respect to their unexposed counterparts (median 14-387% greater across tumor types). The number of chromosomal fragments characteristic of the platinum-associated CN footprint increases significantly with the activity of the well known platinum-related footprint of single nucleotide variants across exposed tumors.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is ...difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.
Large efforts dedicated to detect somatic alterations across tumor genomes/exomes are expected to produce significant improvements in precision cancer medicine. However, high inter-tumor ...heterogeneity is a major obstacle to developing and applying therapeutic targeted agents to treat most cancer patients. Here, we offer a comprehensive assessment of the scope of targeted therapeutic agents in a large pan-cancer cohort. We developed an in silico prescription strategy based on identification of the driver alterations in each tumor and their druggability options. Although relatively few tumors are tractable by approved agents following clinical guidelines (5.9%), up to 40.2% could benefit from different repurposing options, and up to 73.3% considering treatments currently under clinical investigation. We also identified 80 therapeutically targetable cancer genes.
Display omitted
•Driver genes are comprehensively identified across a large pan-cancer cohort•In silico prescription links approved or experimental targeted therapies to patients•Up to 73.3% of patients could benefit from agents in clinical stages•80 therapeutically unexploited targetable cancer driver genes are identified
Using a large pan-cancer cohort, Rubio-Perez et al. develop an in silico drug prescription strategy based on driver alterations in each tumor and their druggability options and use it to identify druggable targets and promising repurposing opportunities.
PDF
