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Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date, little is known about the presence of non-ETS fusion events in prostate cancer. We used next-generation transcriptome sequencing (RNA-seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and four involving non-ETS genes such as CDKN1A (p21), CD9, and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency, but, interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement-prone phenotype.

The lack of efficient high-throughput methods for enrichment of specific sequences from genomic DNA represents a key bottleneck in exploiting the enormous potential of next-generation sequencers. Such methods would allow for a systematic and targeted analysis of relevant genomic regions. Recent studies reported sequence enrichment using a hybridization step to specific DNA capture probes as a possible solution to the problem. However, so far no method has provided sufficient depths of coverage for reliable base calling over the entire target regions. We report a strategy to multiply the enrichment performance and consequently improve depth and breadth of coverage for desired target sequences by applying two iterative cycles of hybridization with microfluidic Geniom biochips. Using this strategy, we enriched and then sequenced the cancer-related genes BRCA1 and TP53 and a set of 1000 individual dbSNP regions of 500 bp using Illumina technology. We achieved overall enrichment factors of up to 1062-fold and average coverage depths of 470-fold. Combined with high coverage uniformity, this resulted in nearly complete consensus coverages with >86% of target region covered at 20-fold or higher. Analysis of SNP calling accuracies after enrichment revealed excellent concordance, with the reference sequence closely mirroring the previously reported performance of Illumina sequencing conducted without sequence enrichment.

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.

We have developed a simple and efficient algorithm to identify each member of a large collection of DNA-linked objects through the use of hybridization, and have applied it to the manufacture of randomly assembled arrays of beads in wells. Once the algorithm has been used to determine the identity of each bead, the microarray can be used in a wide variety of applications, including single nucleotide polymorphism genotyping and gene expression profiling. The algorithm requires only a few labels and several sequential hybridizations to identify thousands of different DNA sequences with great accuracy. We have decoded tens of thousands of arrays, each with 1520 sequences represented at approximately 30-fold redundancy by up to approximately 50,000 beads, with a median error rate of <1 x 10(-4) per bead. The approach makes use of error checking codes and provides, for the first time, a direct functional quality control of every element of each array that is manufactured. The algorithm can be applied to any spatially fixed collection of objects or molecules that are associated with specific DNA sequences.

We report a flexible, sensitive, and quantitative gene-expression profiling system for assaying more than 400 genes, with three probes per gene, for 96 samples in parallel. The cDNA-mediated annealing, selection, extension and ligation (DASL) assay targets specific transcripts, using oligonucleotides containing unique address sequences that can hybridize to universal arrays. Cell-specific gene expression profiles were obtained using this assay for hormone-treated cell lines and laser-capture microdissected cancer tissues. Gene expression profiles derived from this assay were consistent with those determined by qRT-PCR. The DASL assay has been automated for use with a bead-based 96-array matrix system. The combined high-throughput assay and readout system is accurate and efficient, and can cost-effectively profile the expression of hundreds of genes in thousands of samples.

Most human cancers are characterized by genomic instability, the accumulation of multiple genetic alterations and allelic imbalance throughout the genome. Loss of heterozygosity (LOH) is a common form of allelic imbalance and the detection of LOH has been used to identify genomic regions that harbor tumor suppressor genes and to characterize tumor stages and progression. Here we describe the use of high-density oligonucleotide arrays for genome-wide scans for LOH and allelic imbalance in human tumors. The arrays contain redundant sets of probes for 600 genetic loci that are distributed across all human chromosomes. The arrays were used to detect allelic imbalance in two types of human tumors, and a subset of the results was confirmed using conventional gel-based methods. We also tested the ability to study heterogeneous cell populations and found that allelic imbalance can be detected in the presence of a substantial background of normal cells. The detection of LOH and other chromosomal changes using large numbers of single nucleotide polymorphism (SNP) markers should enable identification of patterns of allelic imbalance with potential prognostic and diagnostic utility.

A new approach to comparative nucleic acid sequence analysis is described that uses the ligation of DNA targets to high-density arrays containing complete sets of covalently attached oligonucleotides of length eight and nine. The combination of enzymatic or chemical ligation with a directed comparative analysis avoids many of the intrinsic difficulties associated with hybridization-based de novo sequence reconstruction methods described previously. Double-stranded DNA targets were fragmented and labeled to produce quasirandom populations of 5' termini suitable for ligation and detection on the arrays. Kilobase-size DNA targets were used to demonstrate that complete n-mer arrays can correctly verify known sequences and can determine the presence of sequence differences relative to a reference. By use of 9-mer arrays, sequences of 1.2-kb targets were verified with >99.9% accuracy. Mutations in target sequences were detected by directly comparing the intensity pattern obtained for an unknown with that obtained for a known reference sequence. For targets of moderate length (1.2 kb), 100% of the mutations in the queried sequences were detected with 9-mer arrays. For higher complexity targets (2.5 and 16.6 kb), a relatively high percentage of mutations (90% and 66%, respectively) were correctly identified with a low false-positive rate of <0.03 percent. The methods described provide a general approach to analyzing nucleic acid samples on the basis of the interpretation of sequence-specific patterns of hybridization and ligation on complete n-mer oligonucleotide arrays.