DNA sequence represents a single format onto which a broad range of biological phenomena can be projected for high-throughput data collection. Over the past three years, massively parallel DNA sequencing platforms have become widely available, reducing the cost of DNA sequencing by over two orders of magnitude, and democratizing the field by putting the sequencing capacity of a major genome center in the hands of individual investigators. These new technologies are rapidly evolving, and near-term challenges include the development of robust protocols for generating sequencing libraries, building effective new approaches to data-analysis, and often a rethinking of experimental design. Next-generation DNA sequencing has the potential to dramatically accelerate biological and biomedical research, by enabling the comprehensive analysis of genomes, transcriptomes and interactomes to become inexpensive, routine and widespread, rather than requiring significant production-scale efforts.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Intra-tumor heterogeneity (ITH) drives neoplastic progression and therapeutic resistance. We used EXPANDS and PyClone to detect clones >10% frequency within 1,165 exome sequences from TCGA tumors. 86% of tumors across 12 cancer types had at least two clones. ITH in nuclei morphology was associated with genetic ITH (Spearman ρ: 0.24–0.41, P<0.001). Mutation of a driver gene that typically appears in smaller clones was a survival risk factor (HR=2.15, 95% CI: 1.71–2.69). The risk of mortality also increased when >2 clones coexisted (HR=1.49, 95% CI: 1.20–1.87). In two independent datasets, copy number alterations affecting either <25% or >75% of a tumor’s genome predicted reduced risk (HR=0.15, 95% CI: 0.08–0.29). Mortality risk also declined when more than four clones coexisted in the sample, suggesting a tradeoff between costs and benefits of genomic instability. ITH and genomic instability have the potential to be useful measures universally applicable across cancers.

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SUMMARY Several cell populations have been reported to possess intestinal stem cell (ISC) activity during homeostasis and injury-induced regeneration. Here, we explored inter-relationships between putative mouse ISC populations by comparative RNA-sequencing (RNA-seq). The transcriptomes of multiple cycling ISC populations closely resembled Lgr5+ ISCs, the most well-defined ISC pool, but Bmi1-GFP+ cells were distinct and enriched for enteroendocrine (EE) markers including Prox1. Prox1-GFP+ cells exhibited sustained clonogenic growth in vitro, and lineage-tracing of Prox1+ cells revealed long-lived clones during homeostasis and after radiation-induced injury in vivo. Single-cell mRNA-seq revealed two subsets of Prox1-GFP+ cells, one of which resembled mature EE cells while the other displayed low level EE gene expression but co-expressed tuft cell markers, Lgr5 and Ascl2, reminiscent of label-retaining secretory progenitors. Our data suggest that the EE lineage, including mature EE cells, comprise a reservoir of homeostatic and injury-inducible ISCs, extending our understanding of cellular plasticity and stemness.

The application of primary organoid cultures containing epithelial and mesenchymal elements to cancer modeling holds promise for combining the accurate multilineage differentiation and physiology of in vivo systems with the facile in vitro manipulation of transformed cell lines. Here, a single air-liquid interface culture method was used without modification to engineer oncogenic mutations into primary epithelial/mesenchymal organoids from mouse colon, stomach and pancreas. Pancreatic and gastric organoids exhibited dysplasia upon KrasG12D expression and/or p53 loss, and readily generated adenocarcinoma upon in vivo transplantation. In contrast, primary colon organoids required combinatorial Apc, p53, KrasG12D and Smad4 mutations for progressive transformation to invasive adenocarcinoma-like histology in vitro and tumorigenicity in vivo, recapitulating multi-hit models of colorectal cancer (CRC), and versus more promiscuous transformation of small intestinal organoids. Colon organoid culture functionally validated the microRNA miR-483 as a dominant driver oncogene at the Insulin-like growth factor-2 (IGF2) 11p15.5 CRC amplicon, inducing dysplasia in vitro and tumorigenicity in vivo. These studies demonstrate the general utility of a highly tractable primary organoid system for cancer modeling and driver oncogene validation in diverse gastrointestinal tissues.

Single-cell RNA sequencing has enabled the characterization of highly specific cell types in many tissues, as well as both primary and stem cell-derived cell lines. An important facet of these studies is the ability to identify the transcriptional signatures that define a cell type or state. In theory, this information can be used to classify an individual cell based on its transcriptional profile. Here, we present scPred, a new generalizable method that is able to provide highly accurate classification of single cells, using a combination of unbiased feature selection from a reduced-dimension space, and machine-learning probability-based prediction method. We apply scPred to scRNA-seq data from pancreatic tissue, mononuclear cells, colorectal tumor biopsies, and circulating dendritic cells and show that scPred is able to classify individual cells with high accuracy. The generalized method is available at https://github.com/powellgenomicslab/scPred/.

Key Points• Analysis of coding genomes of FL tumor subpopulations reveals striking clonal diversity at diagnosis and progression.• Within a hierarchy of somatic evolution of FL coding genomes, many recurrent mutations are subclonal at diagnosis.Follicular lymphoma (FL) is currently incurable using conventional chemotherapy or immunotherapy regimes, compelling new strategies. Advances in high-throughput sequencing technologies that can reveal oncogenic pathways have stimulated interest in tailoring therapies toward actionable somatic mutations. However, for mutation-directed therapies to be most effective, the mutations must be uniformly present in evolved tumor cells as well as in the self-renewing tumor-cell precursors. Here, we show striking intratumoral clonal diversity within FL tumors in the representation of mutations in the majority of genes as revealed by whole exome sequencing of subpopulations. This diversity captures a clonal hierarchy, resolved using immunoglobulin somatic mutations and IGH-BCL2 translocations as a frame of reference and by comparing diagnosis and relapse tumor pairs, allowing us to distinguish early versus late genetic eventsduring lymphomagenesis. We provide evidence that IGH-BCL2 translocations and CREBBP mutations are early events, whereas MLL2 and TNFRSF14 mutations probably represent late events during disease evolution. These observations provide insight into which of the genetic lesions represent suitable candidates for targeted therapies. (Blood. 2013;121(9):1604-1611) IntroductionFollicular lymphoma (FL) is a common form of non-Hodgkin lymphoma (NHL) arising from mature B cells. FL tumor cells share identical immunoglobulin (Ig) gene rearrangements, indicating that the transforming founder mutation(s) occurs subsequent to VDJ recombination. These cells express markers of mature B-lineage including surface-Ig and CD19, and germinal center B-cell markers such as LMO2, CD10, and BCL6. 1 The B-cell marker CD20, which is also the target of the anti-lymphoma therapy Rituximab, 2,3 is expressed to a variable degree on FL tumors. 4,5 CD20 levels can predict primary responsiveness of diverse lymphomas to Rituximab,6 and changes in CD20 expression contribute to Rituximab resistance and relapse. 7,8 For instance, CD20 expression levels are associated with survival in patients with aggressive lymphomas treated with or without Rituximab. 9 These studies each found CD20 to be variably expressed on cells within the same tumor, suggesting that this may be a marker of underlying clonal diversity.The genetic hallmark of FL is the t(14;18)(q32;q21) translocation that places the antiapoptotic BCL2 oncogene under control of the Ig heavy-chain enhancer. 10 This lesion is present in Ͼ 90% of FL cases, 11 but is also detectable in the majority of older healthy adults suggesting that it is not sufficient to induce clinical disease. 12 Recently, mutation of a histone methyltransferase gene, MLL2, was identified in 89% of FL cases, indicating that this may also be a founder mutation. 13 Genes encodin...