Oligodendroglioma is characterized by unique clinical, pathological, and genetic features. Recurrent losses of chromosomes 1p and 19q are strongly associated with this brain cancer but knowledge of the identity and function of the genes affected by these alterations is limited. We performed exome sequencing on a discovery set of 16 oligodendrogliomas with 1p/19q co-deletion to identify new molecular features at base-pair resolution. As anticipated, there was a high rate of IDH mutations: all cases had mutations in either IDH1 (14/16) or IDH2 (2/16). In addition, we discovered somatic mutations and insertions/deletions in the CIC gene on chromosome 19q13.2 in 13/16 tumours. These discovery set mutations were validated by deep sequencing of 13 additional tumours, which revealed 7 others with CIC mutations, thus bringing the overall mutation rate in oligodendrogliomas in this study to 20/29 (69%). In contrast, deep sequencing of astrocytomas and oligoastrocytomas without 1p/19q loss revealed that CIC alterations were otherwise rare (1/60; 2%). Of the 21 non-synonymous somatic mutations in 20 CIC-mutant oligodendrogliomas, 9 were in exon 5 within an annotated DNA interacting domain and 3 were in exon 20 within an annotated protein interacting domain. The remaining 9 were found in other exons and frequently included truncations. CIC mutations were highly associated with oligodendroglioma histology, 1p/19q co-deletion and IDH1/2 mutation (p<0.001). Although we observed no differences in the clinical outcomes of CIC mutant versus wild-type tumors, in a background of 1p/19q co-deletion, hemizygous CIC mutations are likely important. We hypothesize that the mutant CIC on the single retained 19q allele is linked to the pathogenesis of oligodendrogliomas with IDH mutation. Our detailed study of genetic aberrations in oligodendroglioma suggests a functional interaction between CIC mutation, IDH1/2 mutation and 1p/19q co-deletion.

Cryptococcus neoformans is a basidiomycetous yeast ubiquitous in the environment, a model for fungal pathogenesis, and an opportunistic human pathogen of global importance. We have sequenced its ~20-megabase genome, which contains ~6500 intron-rich gene structures and encodes a transcriptome abundant in alternatively spliced and antisense messages. The genome is rich in transposons, many of which cluster at candidate centromeric regions. The presence of these transposons may drive karyotype instability and phenotypic variation. C. neoformans encodes unique genes that may contribute to its unusual virulence properties, and comparison of two phenotypically distinct strains reveals variation in gene content in addition to sequence polymorphisms between the genomes.

Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome—in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)—which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.

Malformations of the cardiovascular system are the most common type of birth defect in humans, frequently affecting the formation of valves and septa. During heart valve and septa formation, cells from the atrio-ventricular canal (AVC) and outflow tract (OFT) regions of the heart undergo an epithelial-to-mesenchymal transformation (EMT) and invade the underlying extracellular matrix to give rise to endocardial cushions. Subsequent maturation of newly formed mesenchyme cells leads to thin stress-resistant leaflets. TWIST1 is a basic helix-loop-helix transcription factor expressed in newly formed mesenchyme cells of the AVC and OFT that has been shown to play roles in cell survival, cell proliferation and differentiation. However, the downstream targets of TWIST1 during heart valve formation remain unclear. To identify genes important for heart valve development downstream of TWIST1, we performed global gene expression profiling of AVC, OFT, atria and ventricles of the embryonic day 10.5 mouse heart by tag-sequencing (Tag-seq). Using this resource we identified a novel set of 939 genes, including 123 regulators of transcription, enriched in the valve forming regions of the heart. We compared these genes to a Tag-seq library from the Twist1 null developing valves revealing significant gene expression changes. These changes were consistent with a role of TWIST1 in controlling differentiation of mesenchymal cells following their transformation from endothelium in the mouse. To study the role of TWIST1 at the DNA level we performed chromatin immunoprecipitation and identified novel direct targets of TWIST1 in the developing heart valves. Our findings support a role for TWIST1 in the differentiation of AVC mesenchyme post-EMT in the mouse, and suggest that TWIST1 can exert its function by direct DNA binding to activate valve specific gene expression.

The issue of heterozygosity continues to be a challenge in the analysis of genome sequences. In this article, we describe the use of allele ratios to distinguish biologically significant single-nucleotide variants from background noise. An application of this approach is the identification of lethal mutations in Caenorhabditis elegans essential genes, which must be maintained by the presence of a wild-type allele on a balancer. The h448 allele of let-504 is rescued by the duplication balancer sDp2. We readily identified the extent of the duplication when the percentage of read support for the lesion was between 70 and 80%. Examination of the EMS-induced changes throughout the genome revealed that these mutations exist in contiguous blocks. During early embryonic division in self-fertilizing C. elegans, alkylated guanines pair with thymines. As a result, EMS-induced changes become fixed as either G→A or C→T changes along the length of the chromosome. Thus, examination of the distribution of EMS-induced changes revealed the mutational and recombinational history of the chromosome, even generations later. We identified the mutational change responsible for the h448 mutation and sequenced PCR products for an additional four alleles, correlating let-504 with the DNA-coding region for an ortholog of a NFκB-activating protein, NKAP. Our results confirm that whole-genome sequencing is an efficient and inexpensive way of identifying nucleotide alterations responsible for lethal phenotypes and can be applied on a large scale to identify the molecular basis of essential genes.

Motivation: Identification of somatic single nucleotide variants (SNVs) in tumour genomes is a necessary step in defining the mutational landscapes of cancers. Experimental designs for genome-wide ascertainment of somatic mutations now routinely include next-generation sequencing (NGS) of tumour DNA and matched constitutional DNA from the same individual. This allows investigators to control for germline polymorphisms and distinguish somatic mutations that are unique to the tumour, thus reducing the burden of labour-intensive and expensive downstream experiments needed to verify initial predictions. In order to make full use of such paired datasets, computational tools for simultaneous analysis of tumour–normal paired sequence data are required, but are currently under-developed and under-represented in the bioinformatics literature.

Results: In this contribution, we introduce two novel probabilistic graphical models called JointSNVMix1 and JointSNVMix2 for jointly analysing paired tumour–normal digital allelic count data from NGS experiments. In contrast to independent analysis of the tumour and normal data, our method allows statistical strength to be borrowed across the samples and therefore amplifies the statistical power to identify and distinguish both germline and somatic events in a unified probabilistic framework.

Availability: The JointSNVMix models and four other models discussed in the article are part of the JointSNVMix software package available for download at http://compbio.bccrc.ca

Contact: sshah@bccrc.ca

Supplementary information:Supplementary data are available at Bioinformatics online.

Next generation sequencing has brought epigenomic studies to the forefront of current research. The power of massively parallel sequencing coupled to innovative molecular and computational techniques has allowed researchers to profile the epigenome at resolutions that were unimaginable only a few years ago. With early proof of concept studies published, the field is now moving into the next phase where the importance of method standardization and rigorous quality control are becoming paramount. In this review we will describe methodologies that have been developed to profile the epigenome using next generation sequencing platforms. We will discuss these in terms of library preparation, sequence platforms and analysis techniques.

Motivation: The study of cancer genomes now routinely involves using next-generation sequencing technology (NGS) to profile tumours for single nucleotide variant (SNV) somatic mutations. However, surprisingly few published bioinformatics methods exist for the specific purpose of identifying somatic mutations from NGS data and existing tools are often inaccurate, yielding intolerably high false prediction rates. As such, the computational problem of accurately inferring somatic mutations from paired tumour/normal NGS data remains an unsolved challenge.

Results: We present the comparison of four standard supervised machine learning algorithms for the purpose of somatic SNV prediction in tumour/normal NGS experiments. To evaluate these approaches (random forest, Bayesian additive regression tree, support vector machine and logistic regression), we constructed 106 features representing 3369 candidate somatic SNVs from 48 breast cancer genomes, originally predicted with naive methods and subsequently revalidated to establish ground truth labels. We trained the classifiers on this data (consisting of 1015 true somatic mutations and 2354 non-somatic mutation positions) and conducted a rigorous evaluation of these methods using a cross-validation framework and hold-out test NGS data from both exome capture and whole genome shotgun platforms. All learning algorithms employing predictive discriminative approaches with feature selection improved the predictive accuracy over standard approaches by statistically significant margins. In addition, using unsupervised clustering of the ground truth ‘false positive’ predictions, we noted several distinct classes and present evidence suggesting non-overlapping sources of technical artefacts illuminating important directions for future study.

Availability: Software called MutationSeq and datasets are available from http://compbio.bccrc.ca.

Contact: saparicio@bccrc.ca

Supplementary information: Supplementary data are available at Bioinformatics online.

The diagnosis of medulloblastoma likely encompasses several distinct entities, with recent evidence for the existence of at least four unique molecular subgroups that exhibit distinct genetic, transcriptional, demographic, and clinical features. Assignment of molecular subgroup through routine profiling of high-quality RNA on expression microarrays is likely impractical in the clinical setting. The planning and execution of medulloblastoma clinical trials that stratify by subgroup, or which are targeted to a specific subgroup requires technologies that can be economically, rapidly, reliably, and reproducibly applied to formalin-fixed paraffin embedded (FFPE) specimens. In the current study, we have developed an assay that accurately measures the expression level of 22 medulloblastoma subgroup-specific signature genes (CodeSet) using nanoString nCounter Technology. Comparison of the nanoString assay with Affymetrix expression array data on a training series of 101 medulloblastomas of known subgroup demonstrated a high concordance (Pearson correlation r = 0.86). The assay was validated on a second set of 130 non-overlapping medulloblastomas of known subgroup, correctly assigning 98% (127/130) of tumors to the appropriate subgroup. Reproducibility was demonstrated by repeating the assay in three independent laboratories in Canada, the United States, and Switzerland. Finally, the nanoString assay could confidently predict subgroup in 88% of recent FFPE cases, of which 100% had accurate subgroup assignment. We present an assay based on nanoString technology that is capable of rapidly, reliably, and reproducibly assigning clinical FFPE medulloblastoma samples to their molecular subgroup, and which is highly suited for future medulloblastoma clinical trials.

Electronic supplementary material

The online version of this article (doi:10.1007/s00401-011-0899-7) contains supplementary material, which is available to authorized users.

Skin-derived precursors (SKPs) are multipotent dermal stem cells that reside within a hair follicle niche and that share properties with embryonic neural crest precursors. Here, we have asked whether SKPs and their endogenous dermal precursors originate from the neural crest or whether, like the dermis itself, they originate from multiple developmental origins. To do this, we used two different mouse Cre lines that allow us to perform lineage tracing: Wnt1-cre, which targets cells deriving from the neural crest, and Myf5-cre, which targets cells of a somite origin. By crossing these Cre lines to reporter mice, we show that the endogenous follicle-associated dermal precursors in the face derive from the neural crest, and those in the dorsal trunk derive from the somites, as do the SKPs they generate. Despite these different developmental origins, SKPs from these two locations are functionally similar, even with regard to their ability to differentiate into Schwann cells, a cell type only thought to be generated from the neural crest. Analysis of global gene expression using microarrays confirmed that facial and dorsal SKPs exhibit a very high degree of similarity, and that they are also very similar to SKPs derived from ventral dermis, which has a lateral plate origin. However, these developmentally distinct SKPs also retain differential expression of a small number of genes that reflect their developmental origins. Thus, an adult neural crest-like dermal precursor can be generated from a non-neural crest origin, a finding with broad implications for the many neuroendocrine cells in the body.

Small non-coding RNAs, such as microRNAs (miRNAs), are involved in diverse biological processes including organ development and tissue differentiation. Global disruption of miRNA biogenesis in Dicer knockout mice disrupts early embryogenesis and primordial germ cell formation. However, the role of miRNAs in early folliculogenesis is poorly understood. In order to identify a full transcriptome set of small RNAs expressed in the newborn (NB) ovary, we extracted small RNA fraction from mouse NB ovary tissues and subjected it to massive parallel sequencing using the Genome Analyzer from Illumina. Massive sequencing produced 4 655 992 reads of 33 bp each representing a total of 154 Mbp of sequence data. The Pash alignment algorithm mapped 50.13% of the reads to the mouse genome. Sequence reads were clustered based on overlapping mapping coordinates and intersected with known miRNAs, small nucleolar RNAs (snoRNAs), piwi-interacting RNA (piRNA) clusters and repetitive genomic regions; 25.2% of the reads mapped to known miRNAs, 25.5% to genomic repeats, 3.5% to piRNAs and 0.18% to snoRNAs. Three hundred and ninety-eight known miRNA species were among the sequenced small RNAs, and 118 isomiR sequences that are not in the miRBase database. Let-7 family was the most abundantly expressed miRNA, and mmu-mir-672, mmu-mir-322, mmu-mir-503 and mmu-mir-465 families are the most abundant X-linked miRNA detected. X-linked mmu-mir-503, mmu-mir-672 and mmu-mir-465 family showed preferential expression in testes and ovaries. We also identified four novel miRNAs that are preferentially expressed in gonads. Gonadal selective miRNAs may play important roles in ovarian development, folliculogenesis and female fertility.

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.

Author Summary

Genome rearrangements and associated gene fusions are known to be important oncogenic events in some cancers. We have developed a novel computational method called deFuse for detecting gene fusions in RNA-Seq data and have applied it to the discovery of novel gene fusions in sarcoma and ovarian tumors. We assessed the accuracy of our method and found that deFuse produces substantially better sensitivity and specificity than two other published methods. We have also developed a set of 60 positive and 61 negative examples that will be useful for accurate identification of gene fusions in future RNA-Seq datasets. We have trained a classifier on 11 novel features of the 121 examples, and show that the classifier is able to accurately identify real gene fusions. The 45 gene fusions reported in this study represent the first ovarian cancer fusions reported, as well as novel sarcoma fusions. By examining the expression patterns of the affected genes, we find that many fusions are predicted to have functional consequences and thus merit experimental followup to determine their clinical relevance.

Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.

Background

Clinical laboratories are adopting array genomic hybridization as a standard clinical test. A number of whole genome array genomic hybridization platforms are available, but little is known about their comparative performance in a clinical context.

Methods

We studied 30 children with idiopathic MR and both unaffected parents of each child using Affymetrix 500 K GeneChip SNP arrays, Agilent Human Genome 244 K oligonucleotide arrays and NimbleGen 385 K Whole-Genome oligonucleotide arrays. We also determined whether CNVs called on these platforms were detected by Illumina Hap550 beadchips or SMRT 32 K BAC whole genome tiling arrays and tested 15 of the 30 trios on Affymetrix 6.0 SNP arrays.

Results

The Affymetrix 500 K, Agilent and NimbleGen platforms identified 3061 autosomal and 117 X chromosomal CNVs in the 30 trios. 147 of these CNVs appeared to be de novo, but only 34 (22%) were found on more than one platform. Performing genotype-phenotype correlations, we identified 7 most likely pathogenic and 2 possibly pathogenic CNVs for MR. All 9 of these putatively pathogenic CNVs were detected by the Affymetrix 500 K, Agilent, NimbleGen and the Illumina arrays, and 5 were found by the SMRT BAC array. Both putatively pathogenic CNVs identified in the 15 trios tested with the Affymetrix 6.0 were identified by this platform.

Conclusions

Our findings demonstrate that different results are obtained with different platforms and illustrate the trade-off that exists between sensitivity and specificity. The large number of apparently false positive CNV calls on each of the platforms supports the need for validating clinically important findings with a different technology.

The H3K9me3 histone modification is often found at promoter regions, where it functions to repress transcription. However, we have previously shown that 3′ exons of zinc finger genes (ZNFs) are marked by high levels of H3K9me3. We have now further investigated this unusual location for H3K9me3 in ZNF genes. Neither bioinformatic nor experimental approaches support the hypothesis that the 3′ exons of ZNFs are promoters. We further characterized the histone modifications at the 3′ ZNF exons and found that these regions also contain H3K36me3, a mark of transcriptional elongation. A genome-wide analysis of ChIP-seq data revealed that ZNFs constitute the majority of genes that have high levels of both H3K9me3 and H3K36me3. These results suggested the possibility that the ZNF genes may be imprinted, with one allele transcribed and one allele repressed. To test the hypothesis that the contradictory modifications are due to imprinting, we used a SNP analysis of RNA-seq data to demonstrate that both alleles of certain ZNF genes having H3K9me3 and H3K36me3 are transcribed. We next analyzed isolated ZNF 3′ exons using stably integrated episomes. We found that although the H3K36me3 mark was lost when the 3′ ZNF exon was removed from its natural genomic location, the isolated ZNF 3′ exons retained the H3K9me3 mark. Thus, the H3K9me3 mark at ZNF 3′ exons does not impede transcription and it is regulated independently of the H3K36me3 mark. Finally, we demonstrate a strong relationship between the number of tandemly repeated domains in the 3′ exons and the H3K9me3 mark. We suggest that the H3K9me3 at ZNF 3′ exons may function to protect the genome from inappropriate recombination rather than to regulate transcription.

B cell lymphoma 6 (BCL6), which encodes a transcriptional repressor, is a critical oncogene in diffuse large B cell lymphomas (DLBCLs). Although a retro-inverted BCL6 peptide inhibitor (RI-BPI) was recently shown to potently kill DLBCL cells, the underlying mechanisms remain unclear. Here, we show that RI-BPI induces a particular gene expression signature in human DLBCL cell lines that included genes associated with the actions of histone deacetylase (HDAC) and Hsp90 inhibitors. BCL6 directly repressed the expression of p300 lysine acetyltransferase (EP300) and its cofactor HLA-B–associated transcript 3 (BAT3). RI-BPI induced expression of p300 and BAT3, resulting in acetylation of p300 targets including p53 and Hsp90. Induction of p300 and BAT3 was required for the antilymphoma effects of RI-BPI, since specific blockade of either protein rescued human DLBCL cell lines from the BCL6 inhibitor. Consistent with this, combination of RI-BPI with either an HDAC inhibitor (HDI) or an Hsp90 inhibitor potently suppressed or even eradicated established human DLBCL xenografts in mice. Furthermore, HDAC and Hsp90 inhibitors independently enhanced RI-BPI killing of primary human DLBCL cells in vitro. We also show that p300-inactivating mutations occur naturally in human DLBCL patients and may confer resistance to BCL6 inhibitors. Thus, BCL6 repression of EP300 provides a basis for rational targeted combinatorial therapy for patients with DLBCL.

Background

There is no cure for castration-recurrent prostate cancer (CRPC) and the mechanisms underlying this stage of the disease are unknown.

Methods

We analyzed the transcriptome of human LNCaP prostate cancer cells as they progress to CRPC in vivo using replicate LongSAGE libraries. We refer to these libraries as the LNCaP atlas and compared these gene expression profiles with current suggested models of CRPC.

Results

Three million tags were sequenced using in vivo samples at various stages of hormonal progression to reveal 96 novel genes differentially expressed in CRPC. Thirty-one genes encode proteins that are either secreted or are located at the plasma membrane, 21 genes changed levels of expression in response to androgen, and 8 genes have enriched expression in the prostate. Expression of 26, 6, 12, and 15 genes have previously been linked to prostate cancer, Gleason grade, progression, and metastasis, respectively. Expression profiles of genes in CRPC support a role for the transcriptional activity of the androgen receptor (CCNH, CUEDC2, FLNA, PSMA7), steroid synthesis and metabolism (DHCR24, DHRS7, ELOVL5, HSD17B4, OPRK1), neuroendocrine (ENO2, MAOA, OPRK1, S100A10, TRPM8), and proliferation (GAS5, GNB2L1, MT-ND3, NKX3-1, PCGEM1, PTGFR, STEAP1, TMEM30A), but neither supported nor discounted a role for cell survival genes.

Conclusions

The in vivo gene expression atlas for LNCaP was sequenced and support a role for the androgen receptor in CRPC.

Methods and results: We identified de novo submicroscopic chromosome 14q11.2 deletions in two children with idiopathic developmental delay and cognitive impairment. Vancouver patient 5566 has a ∼200 kb deletion and Vancouver patient 8326 has a ∼1.6 Mb deletion. The Database of Chromosomal Imbalance and Phenotype in Humans using Ensembl Resources (DECIPHER) revealed a third patient with idiopathic developmental delay and cognitive impairment, DECIPHER patient 126, who has a ∼1.1 Mb deletion of 14q11.2. The deletion of patient 5566 overlaps that of patient 126 and both of these deletions lie entirely within that of patient 8326. All three children have similar dysmorphic features, including widely‐spaced eyes, short nose with flat nasal bridge, long philtrum, prominent Cupid's bow of the upper lip, full lower lip and similar auricular anomalies.

Conclusion: The minimal common deletion region on chromosome 14q11.2 is only ∼35 kb (from 20.897 to 20.932, University of California at Santa Cruz (UCSC) Genome Browser; build hg18, March 2006) and includes only two genes, SUPT16H and CHD8, which are good candidate genes for the phenotypes. The non‐recurrent breakpoints of these patients, the presence of normal copy number variants in the region and the local genomic structure support the notion that this region has reduced stability.

Neuroblastoma (NB) is the most deadly extra-cranial solid tumour in children necessitating an urgent need for effective and less toxic treatments. One reason for the lack of efficacious treatments may be the inability of existing drugs to target the tumour-initiating or cancer stem cell population responsible for sustaining tumour growth, metastases and relapse. Here, we describe a strategy to identify compounds that selectively target patient-derived cancer stem cell-like tumour-initiating cells (TICs) while sparing normal paediatric stem cells (skin-derived precursors, SKPs) and characterize two therapeutic candidates. DECA-14 and rapamycin were identified as NB TIC-selective agents. Both compounds induced TIC death at nanomolar concentrations in vitro, significantly reduced NB xenograft tumour weight in vivo, and dramatically decreased self-renewal or tumour-initiation capacity in treated tumours. These results demonstrate that differential drug sensitivities between TICs and normal paediatric stem cells can be exploited to identify novel, patient-specific and potentially less toxic therapies.

Background

Adenocarcinomas of the tongue are rare and represent the minority (20 to 25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment.

Results

In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. There were 1,078 genes that exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations, administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumors and 9 new somatic protein coding mutations. The observed mutations and amplifications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways.

Conclusions

We conclude that complete genomic characterization of a rare tumor has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.

SUMMARY

Despite the remarkable regenerative capacity of mammalian skin, an adult dermal stem cell has not yet been identified. Here, we investigated whether skin-derived precursors (SKPs) might fulfill such a role. We show that SKPs derive from Sox2+ hair follicle dermal cells, and that these two cell populations are similar with regard to their transcriptome and functional properties. Both clonal SKPs and endogenous Sox2+ cells induce hair morphogenesis, differentiate into dermal cell types, and home to a hair follicle niche upon transplantation. Moreover, hair follicle-derived SKPs self-renew, maintain their multipotency, and serially reconstitute hair follicles. Finally, grafting experiments show that follicle-associated dermal cells move out of their niche to contribute cells for dermal maintenance and wound-healing. Thus, SKPs derive from Sox2+ follicle-associated dermal precursors and display functional properties predicted of a dermal stem cell, contributing to dermal maintenance, wound-healing, and hair follicle morphogenesis.