A single-cell atlas of the murine pancreatic ductal tree identifies novel cell populations with potential implications in pancreas regeneration and exocrine pathogenesis.

BACKGROUND AND AIMS: Pancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network. METHODS: We used scRNA-seq to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis. RESULTS: We have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro, including Wnt-responsive-population, ciliated-population and FLRT3+ cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples. The expression of WNT-responsive, IFN-responsive and EMT-population markers increases in chronic pancreatitis and tumor samples. CONCLUSIONS: In light of our discovery of previously unidentified ductal populations, we unmask potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis. Thus, novel lineage tracing models are needed to investigate ductal specific populations in vivo.

A single-cell atlas of the murine pancreatic ductal tree identifies novel cell populations with potential implications in pancreas regeneration and exocrine pathogenesis.

Background and aims: Pancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network. Methods: We used scRNA-seq to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis. Results: We have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro , including Wnt-responsive-population, ciliated-population and FLRT3 + cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples, highlighting a putative role of WNT-responsive, IFN-responsive and EMT-populations in pancreatic exocrine pathogenesis as their expression increases in chronic pancreatitis and PanIN lesions. Conclusions: In light of our discovery of previously unidentified ductal populations, we unmask the potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis.

Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells.

The main critical step in single-cell transcriptomics is sample preparation. Several methods have been developed to preserve cells after dissociation to uncouple sample handling from library preparation. Yet, the suitability of these methods depends on the cell types to be processed. In this project, we perform a systematic comparison of preservation methods for droplet-based single-cell RNA-seq on neural and glial cells derived from induced pluripotent stem cells. Our results show that while DMSO provides the highest cell quality in terms of RNA molecules and genes detected per cell, it strongly affects the cellular composition and induces the expression of stress and apoptosis genes. In contrast, methanol fixed samples display a cellular composition similar to fresh samples and provide a good cell quality and little expression biases. Taken together, our results show that methanol fixation is the method of choice for performing droplet-based single-cell transcriptomics experiments on neural cell populations.

Transplanting rejuvenated blood stem cells extends lifespan of aged immunocompromised mice.

One goal of regenerative medicine is to rejuvenate tissues and extend lifespan by restoring the function of endogenous aged stem cells. However, evidence that somatic stem cells can be targeted in vivo to extend lifespan is still lacking. Here, we demonstrate that after a short systemic treatment with a specific inhibitor of the small RhoGTPase Cdc42 (CASIN), transplanting aged hematopoietic stem cells (HSCs) from treated mice is sufficient to extend the healthspan and lifespan of aged immunocompromised mice without additional treatment. In detail, we show that systemic CASIN treatment improves strength and endurance of aged mice by increasing the myogenic regenerative potential of aged skeletal muscle stem cells. Further, we show that CASIN modifies niche localization and H4K16ac polarity of HSCs in vivo. Single-cell profiling reveals changes in HSC transcriptome, which underlie enhanced lymphoid and regenerative capacity in serial transplantation assays. Overall, we provide proof-of-concept evidence that a short systemic treatment to decrease Cdc42 activity improves the regenerative capacity of different endogenous aged stem cells in vivo, and that rejuvenated HSCs exert a broad systemic effect sufficient to extend murine health- and lifespan.

The evolution of relapse of adult T cell acute lymphoblastic leukemia.

BACKGROUND: Adult T cell acute lymphoblastic leukemia (T-ALL) is a rare disease that affects less than 10 individuals in one million. It has been less studied than its cognate pediatric malignancy, which is more prevalent. A higher percentage of the adult patients relapse, compared to children. It is thus essential to study the mechanisms of relapse of adult T-ALL cases. RESULTS: We profile whole-genome somatic mutations of 19 primary T-ALLs from adult patients and the corresponding relapse malignancies and analyze their evolution upon treatment in comparison with 238 pediatric and young adult ALL cases. We compare the mutational processes and driver mutations active in primary and relapse adult T-ALLs with those of pediatric patients. A precise estimation of clock-like mutations in leukemic cells shows that the emergence of the relapse clone occurs several months before the diagnosis of the primary T-ALL. Specifically, through the doubling time of the leukemic population, we find that in at least 14 out of the 19 patients, the population of relapse leukemia present at the moment of diagnosis comprises more than one but fewer than 108 blasts. Using simulations, we show that in all patients the relapse appears to be driven by genetic mutations. CONCLUSIONS: The early appearance of a population of leukemic cells with genetic mechanisms of resistance across adult T-ALL cases constitutes a challenge for treatment. Improving early detection of the malignancy is thus key to prevent its relapse.

A compendium of mutational cancer driver genes.

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers.

MOTIVATION: Identification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes. RESULTS: We have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or penta-nucleotide context substitutions observed in the cohort under study. Our method can identify known clusters and bona-fide cancer drivers across cohorts of tumor whole-exomes, outperforming the existing OncodriveCLUST algorithm and complementing other methods based on different signals of positive selection. Our results indicate that OncodriveCLUSTL can be applied to the analysis of non-coding genomic elements and non-human mutations data. AVAILABILITY AND IMPLEMENTATION: OncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Author Correction: Reduced mutation rate in exons due to differential mismatch repair.

In the version of this article initially published, the x axis on the fourth plot in Fig. 2e was incorrectly labeled "H3K36me3 exon-to-intron ratio (lower to higher)." The x axis on this plot should read "Genic H3K36me3 coverage bins (higher to lower)".

Comprehensive Characterization of Cancer Driver Genes and Mutations.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

Reduced mutation rate in exons due to differential mismatch repair.

While recent studies have identified higher than anticipated heterogeneity of mutation rate across genomic regions, mutations in exons and introns are assumed to be generated at the same rate. Here we find fewer somatic mutations in exons than expected from their sequence content and demonstrate that this is not due to purifying selection. Instead, we show that it is caused by higher mismatch-repair activity in exonic than in intronic regions. Our findings have important implications for understanding of mutational and DNA repair processes and knowledge of the evolution of eukaryotic genes, and they have practical ramifications for the study of evolution of both tumors and species.

Whole-genome landscapes of major melanoma subtypes.

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. Here we report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. However, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequences was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. Most melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.

The Pancreatic Islet Regulome Browser.

The pancreatic islet is a highly specialized tissue embedded in the exocrine pancreas whose primary function is that of controlling glucose homeostasis. Thus, understanding the transcriptional control of islet-cell may help to puzzle out the pathogenesis of glucose metabolism disorders. Integrative computational analyses of transcriptomic and epigenomic data allows predicting genomic coordinates of putative regulatory elements across the genome and, decipher tissue-specific functions of the non-coding genome. We herein present the Islet Regulome Browser, a tool that allows fast access and exploration of pancreatic islet epigenomic and transcriptomic data produced by different labs worldwide. The Islet Regulome Browser is now accessible on the internet or may be installed locally. It allows uploading custom tracks as well as providing interactive access to a wealth of information including Genome-Wide Association Studies (GWAS) variants, different classes of regulatory elements, together with enhancer clusters, stretch-enhancers and transcription factor binding sites in pancreatic progenitors and adult human pancreatic islets. Integration and visualization of such data may allow a deeper understanding of the regulatory networks driving tissue-specific transcription and guide the identification of regulatory variants. We believe that such tool will facilitate the access to pancreatic islet public genomic datasets providing a major boost to functional genomics studies in glucose metabolism related traits including diabetes.

Discovery of Cancer Driver Long Noncoding RNAs across 1112 Tumour Genomes: New Candidates and Distinguishing Features.

Long noncoding RNAs (lncRNAs) represent a vast unexplored genetic space that may hold missing drivers of tumourigenesis, but few such "driver lncRNAs" are known. Until now, they have been discovered through changes in expression, leading to problems in distinguishing between causative roles and passenger effects. We here present a different approach for driver lncRNA discovery using mutational patterns in tumour DNA. Our pipeline, ExInAtor, identifies genes with excess load of somatic single nucleotide variants (SNVs) across panels of tumour genomes. Heterogeneity in mutational signatures between cancer types and individuals is accounted for using a simple local trinucleotide background model, which yields high precision and low computational demands. We use ExInAtor to predict drivers from the GENCODE annotation across 1112 entire genomes from 23 cancer types. Using a stratified approach, we identify 15 high-confidence candidates: 9 novel and 6 known cancer-related genes, including MALAT1, NEAT1 and SAMMSON. Both known and novel driver lncRNAs are distinguished by elevated gene length, evolutionary conservation and expression. We have presented a first catalogue of mutated lncRNA genes driving cancer, which will grow and improve with the application of ExInAtor to future tumour genome projects.

OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations.

Distinguishing the driver mutations from somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is more acute and far from solved for non-coding mutations. Here we present OncodriveFML, a method designed to analyze the pattern of somatic mutations across tumors in both coding and non-coding genomic regions to identify signals of positive selection, and therefore, their involvement in tumorigenesis. We describe the method and illustrate its usefulness to identify protein-coding genes, promoters, untranslated regions, intronic splice regions, and lncRNAs-containing driver mutations in several malignancies.

Nucleotide excision repair is impaired by binding of transcription factors to DNA.

Somatic mutations are the driving force of cancer genome evolution. The rate of somatic mutations appears to be greatly variable across the genome due to variations in chromatin organization, DNA accessibility and replication timing. However, other variables that may influence the mutation rate locally are unknown, such as a role for DNA-binding proteins, for example. Here we demonstrate that the rate of somatic mutations in melanomas is highly increased at active transcription factor binding sites and nucleosome embedded DNA, compared to their flanking regions. Using recently available excision-repair sequencing (XR-seq) data, we show that the higher mutation rate at these sites is caused by a decrease of the levels of nucleotide excision repair (NER) activity. Our work demonstrates that DNA-bound proteins interfere with the NER machinery, which results in an increased rate of DNA mutations at the protein binding sites. This finding has important implications for our understanding of mutational and DNA repair processes and in the identification of cancer driver mutations.