The clonal and mutational evolution spectrum of primary triple-negative breast cancers.

Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.

Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia.

BACKGROUND: Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear. METHODS: We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis. RESULTS: AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcription-factor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumor-suppressor genes (16%), DNA-methylation-related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories. CONCLUSIONS: We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.).

The Genome of the Northern Sea Otter (Enhydra lutris kenyoni).

The northern sea otter inhabits coastal waters of the northern Pacific Ocean and is the largest member of the Mustelidae family. DNA sequencing methods that utilize microfluidic partitioned and non-partitioned library construction were used to establish the sea otter genome. The final assembly provided 2.426 Gbp of highly contiguous assembled genomic sequences with a scaffold N50 length of over 38 Mbp. We generated transcriptome data derived from a lymphoma to aid in the determination of functional elements. The assembled genome sequence and underlying sequence data are available at the National Center for Biotechnology Information (NCBI) under the BioProject accession number PRJNA388419.

The Genome of the Beluga Whale (Delphinapterus leucas).

The beluga whale is a cetacean that inhabits arctic and subarctic regions, and is the only living member of the genus Delphinapterus. The genome of the beluga whale was determined using DNA sequencing approaches that employed both microfluidic partitioning library and non-partitioned library construction. The former allowed for the construction of a highly contiguous assembly with a scaffold N50 length of over 19 Mbp and total reconstruction of 2.32 Gbp. To aid our understanding of the functional elements, transcriptome data was also derived from brain, duodenum, heart, lung, spleen, and liver tissue. Assembled sequence and all of the underlying sequence data are available at the National Center for Biotechnology Information (NCBI) under the Bioproject accession number PRJNA360851A.

Spatial heterogeneity in medulloblastoma.

Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor, which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

Preparation and analysis of microRNA libraries using the Illumina massively parallel sequencing technology.

MicroRNAs are key regulators of gene expression in diverse biological processes and their importance in embryonic stem cells is indisputable. New 'next-generation' technologies such as Illumina massively parallel sequencing offer vast improvements, in both scale and sensitivity, to microRNA profiling studies. We describe a detailed procedure for the preparation of small RNA libraries for Illumina sequencing. We further comment on approaches for analyzing the resultant sequence data for measuring microRNA abundance.

Digital gene expression by tag sequencing on the illumina genome analyzer.

This unit provides a protocol for performing digital gene expression profiling on the Illumina Genome Analyzer sequencing platform. Tag sequencing (Tag-seq) is an implementation of the LongSAGE protocol on the Illumina sequencing platform that increases utility while reducing both the cost and time required to generate gene expression profiles. The ultra-high-throughput sequencing capability of the Illumina platform allows the cost-effective generation of libraries containing an average of 20 million tags, a 200-fold improvement over classical LongSAGE. Tag-seq has less sequence composition bias, leading to a better representation of AT-rich tag sequences, and allows a more accurate profiling of a subset of the transcriptome characterized by AT-rich genes expressed at levels below the threshold of detection of LongSAGE (Morrissy et al., 2009).

Large-scale production of SAGE libraries from microdissected tissues, flow-sorted cells, and cell lines.

We describe the details of a serial analysis of gene expression (SAGE) library construction and analysis platform that has enabled the generation of >298 high-quality SAGE libraries and >30 million SAGE tags primarily from sub-microgram amounts of total RNA purified from samples acquired by microdissection. Several RNA isolation methods were used to handle the diversity of samples processed, and various measures were applied to minimize ditag PCR carryover contamination. Modifications in the SAGE protocol resulted in improved cloning and DNA sequencing efficiencies. Bioinformatic measures to automatically assess DNA sequencing results were implemented to analyze the integrity of ditag structure, linker or cross-species ditag contamination, and yield of high-quality tags per sequence read. Our analysis of singleton tag errors resulted in a method for correcting such errors to statistically determine tag accuracy. From the libraries generated, we produced an essentially complete mapping of reliable 21-base-pair tags to the mouse reference genome sequence for a meta-library of approximately 5 million tags. Our analyses led us to reject the commonly held notion that duplicate ditags are artifacts. Rather than the usual practice of discarding such tags, we conclude that they should be retained to avoid introducing bias into the results and thereby maintain the quantitative nature of the data, which is a major theoretical advantage of SAGE as a tool for global transcriptional profiling.

LongSAGE profiling of nine human embryonic stem cell lines.

To facilitate discovery of novel human embryonic stem cell (ESC) transcripts, we generated 2.5 million LongSAGE tags from 9 human ESC lines. Analysis of this data revealed that ESCs express proportionately more RNA binding proteins compared with terminally differentiated cells, and identified novel ESC transcripts, at least one of which may represent a marker of the pluripotent state.

A mouse atlas of gene expression: large-scale digital gene-expression profiles from precisely defined developing C57BL/6J mouse tissues and cells.

We analyzed 8.55 million LongSAGE tags generated from 72 libraries. Each LongSAGE library was prepared from a different mouse tissue. Analysis of the data revealed extensive overlap with existing gene data sets and evidence for the existence of approximately 24,000 previously undescribed genomic loci. The visual cortex, pancreas, mammary gland, preimplantation embryo, and placenta contain the largest number of differentially expressed transcripts, 25% of which are previously undescribed loci.