Droplet Digital™ PCR quantitation of HER2 expression in FFPE breast cancer samples.

UNLABELLED: The human epidermal growth factor receptor 2 (HER2, also known as erbB2) gene is involved in signal transduction for cell growth and differentiation. It is a cell surface receptor tyrosine kinase and a proto-oncogene. Overexpression of HER2 is of clinical relevance in breast cancer due to its prognostic value correlating elevated expression with worsening clinical outcome. At the same time, HER2 assessment is also of importance because successful anti-tumor treatment with Herceptin® is strongly correlated with HER2 overexpression in the tumor (approximately 30% of all breast tumors overexpress HER2). In a comprehensive national study, Wolff et al. [1] state that "Approximately 20% of current HER2 testing may be inaccurate" which underscores the importance of developing more accurate methods to determine HER2 status. Droplet Digital™ PCR (ddPCR™) has the potential to improve upon HER2 measurements due to its ability to quantitate DNA and RNA targets with high precision and accuracy. Here we present a study which investigates whether ddPCR can be used to assess HER2 transcript levels in formalin-fixed paraffin embedded (FFPE) human breast tumors and whether these ddPCR measurements agree with prior assessments of these same samples by pathologists using immunohistochemistry (IHC) and in some cases fluorescence in situ hybridization (FISH). We also determined the copy number of HER2 in these samples as compared to the CEP17 reference gene. RESULTS: Clinical FFPE samples were successfully studied using ddPCR and compared to results from standard FISH and IHC methodology. The results demonstrate that ddPCR can rank order the samples in complete agreement with the current standard methods and that ddPCR has the added benefit of providing quantitative results, rather than relying on the expert skill of a seasoned pathologist for determination.

Web-based, participant-driven studies yield novel genetic associations for common traits.

Despite the recent rapid growth in genome-wide data, much of human variation remains entirely unexplained. A significant challenge in the pursuit of the genetic basis for variation in common human traits is the efficient, coordinated collection of genotype and phenotype data. We have developed a novel research framework that facilitates the parallel study of a wide assortment of traits within a single cohort. The approach takes advantage of the interactivity of the Web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design. Here we report initial results from a participant-driven study of 22 traits. Replications of associations (in the genes OCA2, HERC2, SLC45A2, SLC24A4, IRF4, TYR, TYRP1, ASIP, and MC1R) for hair color, eye color, and freckling validate the Web-based, self-reporting paradigm. The identification of novel associations for hair morphology (rs17646946, near TCHH; rs7349332, near WNT10A; and rs1556547, near OFCC1), freckling (rs2153271, in BNC2), the ability to smell the methanethiol produced after eating asparagus (rs4481887, near OR2M7), and photic sneeze reflex (rs10427255, near ZEB2, and rs11856995, near NR2F2) illustrates the power of the approach.

High-throughput droplet digital PCR system for absolute quantitation of DNA copy number.

Digital PCR enables the absolute quantitation of nucleic acids in a sample. The lack of scalable and practical technologies for digital PCR implementation has hampered the widespread adoption of this inherently powerful technique. Here we describe a high-throughput droplet digital PCR (ddPCR) system that enables processing of ~2 million PCR reactions using conventional TaqMan assays with a 96-well plate workflow. Three applications demonstrate that the massive partitioning afforded by our ddPCR system provides orders of magnitude more precision and sensitivity than real-time PCR. First, we show the accurate measurement of germline copy number variation. Second, for rare alleles, we show sensitive detection of mutant DNA in a 100,000-fold excess of wildtype background. Third, we demonstrate absolute quantitation of circulating fetal and maternal DNA from cell-free plasma. We anticipate this ddPCR system will allow researchers to explore complex genetic landscapes, discover and validate new disease associations, and define a new era of molecular diagnostics.

eBLOCKs: enumerating conserved protein blocks to achieve maximal sensitivity and specificity.

Classifying proteins into families and superfamilies allows identification of functionally important conserved domains. The motifs and scoring matrices derived from such conserved regions provide computational tools that recognize similar patterns in novel sequences, and thus enable the prediction of protein function for genomes. The eBLOCKs database enumerates a cascade of protein blocks with varied conservation levels for each functional domain. A biologically important region is most stringently conserved among a smaller family of highly similar proteins. The same region is often found in a larger group of more remotely related proteins with a reduced stringency. Through enumeration, highly specific signatures can be generated from blocks with more columns and fewer family members, while highly sensitive signatures can be derived from blocks with fewer columns and more members as in a superfamily. By applying PSI-BLAST and a modified K-means clustering algorithm, eBLOCKs automatically groups protein sequences according to different levels of similarity. Multiple sequence alignments are made and trimmed into a series of ungapped blocks. Motifs and position-specific scoring matrices were derived from eBLOCKs and made available for sequence search and annotation. The eBLOCKs database provides a tool for high-throughput genome annotation with maximal specificity and sensitivity. The eBLOCKs database is freely available on the World Wide Web at http://motif.stanford.edu/eblocks/ to all users for online usage. Academic and not-for-profit institutions wishing copies of the program may contact Douglas L. Brutlag (brutlag@stanford.edu). Commercial firms wishing copies of the program for internal installation may contact Jacqueline Tay at the Stanford Office of Technology Licensing (jacqueline.tay@stanford.edu; http://otl.stanford.edu/).

Regularities of context-dependent codon bias in eukaryotic genes.

Nucleotides surrounding a codon influence the choice of this particular codon from among the group of possible synonymous codons. The strongest influence on codon usage arises from the nucleotide immediately following the codon and is known as the N1 context. We studied the relative abundance of codons with N1 contexts in genes from four eukaryotes for which the entire genomes have been sequenced: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana. For all the studied organisms it was found that 90% of the codons have a statistically significant N1 context-dependent codon bias. The relative abundance of each codon with an N1 context was compared with the relative abundance of the same 4mer oligonucleotide in the whole genome. This comparison showed that in about half of all cases the context-dependent codon bias could not be explained by the sequence composition of the genome. Ranking statistics were applied to compare context-dependent codon biases for codons from different synonymous groups. We found regularities in N1 context-dependent codon bias with respect to the codon nucleotide composition. Codons with the same nucleotides in the second and third positions and the same N1 context have a statistically significant correlation of their relative abundances.

Cryptic distant relatives are common in both isolated and cosmopolitan genetic samples.

Although a few hundred single nucleotide polymorphisms (SNPs) suffice to infer close familial relationships, high density genome-wide SNP data make possible the inference of more distant relationships such as 2(nd) to 9(th) cousinships. In order to characterize the relationship between genetic similarity and degree of kinship given a timeframe of 100-300 years, we analyzed the sharing of DNA inferred to be identical by descent (IBD) in a subset of individuals from the 23andMe customer database (n = 22,757) and from the Human Genome Diversity Panel (HGDP-CEPH, n = 952). With data from 121 populations, we show that the average amount of DNA shared IBD in most ethnolinguistically-defined populations, for example Native American groups, Finns and Ashkenazi Jews, differs from continentally-defined populations by several orders of magnitude. Via extensive pedigree-based simulations, we determined bounds for predicted degrees of relationship given the amount of genomic IBD sharing in both endogamous and 'unrelated' population samples. Using these bounds as a guide, we detected tens of thousands of 2(nd) to 9(th) degree cousin pairs within a heterogenous set of 5,000 Europeans. The ubiquity of distant relatives, detected via IBD segments, in both ethnolinguistic populations and in large 'unrelated' populations samples has important implications for genetic genealogy, forensics and genotype/phenotype mapping studies.

Quantitative and Sensitive Detection of Cancer Genome Amplifications from Formalin Fixed Paraffin Embedded Tumors with Droplet Digital PCR.

For the analysis of cancer, there is great interest in rapid and accurate detection of cancer genome amplifications containing oncogenes that are potential therapeutic targets. The vast majority of cancer tissue samples are formalin fixed and paraffin embedded (FFPE) which enables histopathological examination and long term archiving. However, FFPE cancer genomic DNA is oftentimes degraded and generally a poor substrate for many molecular biology assays. To overcome the issues of poor DNA quality from FFPE samples and detect oncogenic copy number amplifications with high accuracy and sensitivity, we developed a novel approach. Our assay requires nanogram amounts of genomic DNA, thus facilitating study of small amounts of clinical samples. Using droplet digital PCR (ddPCR), we can determine the relative copy number of specific genomic loci even in the presence of intermingled normal tissue. We used a control dilution series to determine the limits of detection for the ddPCR assay and report its improved sensitivity on minimal amounts of DNA compared to standard real-time PCR. To develop this approach, we designed an assay for the fibroblast growth factor receptor 2 gene (FGFR2) that is amplified in a gastric and breast cancers as well as others. We successfully utilized ddPCR to ascertain FGFR2 amplifications from FFPE-preserved gastrointestinal adenocarcinomas.

A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters.

A striking feature of the human genome is the dearth of CpG dinucleotides (CpGs) interrupted occasionally by CpG islands (CGIs), regions with relatively high content of the dinucleotide. CGIs are generally associated with promoters; genes, whose promoters are especially rich in CpG sequences, tend to be expressed in most tissues. However, all working definitions of what constitutes a CGI rely on ad hoc thresholds. Here we adopt a direct and comprehensive survey to identify the locations of all CpGs in the human genome and find that promoters segregate naturally into two classes by CpG content. Seventy-two percent of promoters belong to the class with high CpG content (HCG), and 28% are in the class whose CpG content is characteristic of the overall genome (low CpG content). The enrichment of CpGs in the HCG class is symmetric and peaks around the core promoter. The broad-based expression of the HCG promoters is not a consequence of a correlation with CpG content because within the HCG class the breadth of expression is independent of the CpG content. The overall depletion of CpGs throughout the genome is thought to be a consequence of the methylation of some germ-line CpGs and their susceptibility to mutation. A comparison of the frequencies of inferred deamination mutations at CpG and GpC dinucleotides in the two classes of promoters using SNPs in human-chimpanzee sequence alignments shows that CpGs mutate at a lower frequency in the HCG promoters, suggesting that CpGs in the HCG class are hypomethylated in the germ line.

The universe of exons revisited.

We study the distribution of exons in eukaryotic genes to determine whether one can detect the reuse of exon sequences and to use the frequency of such reuse to estimate how many ancestral exon sequences there might have been. We use two databases of exons. One contained 56,276 internal exons from putatively unrelated genes (less than 20% sequence identity) and the second contained 8917 internal exons from regions of these genes that are homologous and colinear with prokaryotic genes; these are ancient conserved regions (ACRs). At the 95% significance level we find 3500 exon-sequence matches in the large database and 500 matches in the ACR database. These matches correspond to groups of similar sequences. The size-rank relationship for these groups follows a power law, the size falling off as the inverse square root of the rank. This form of the power law distribution leads us to make an estimate for the size of a possible universe of ancestral exons. Using the data corresponding to the ACR regions, that universe is estimated to be about 15,000-30,000 in size.