A highly scalable peptide-based assay system for proteomics.

We report a scalable and cost-effective technology for generating and screening high-complexity customizable peptide sets. The peptides are made as peptide-cDNA fusions by in vitro transcription/translation from pools of DNA templates generated by microarray-based synthesis. This approach enables large custom sets of peptides to be designed in silico, manufactured cost-effectively in parallel, and assayed efficiently in a multiplexed fashion. The utility of our peptide-cDNA fusion pools was demonstrated in two activity-based assays designed to discover protease and kinase substrates. In the protease assay, cleaved peptide substrates were separated from uncleaved and identified by digital sequencing of their cognate cDNAs. We screened the 3,011 amino acid HCV proteome for susceptibility to cleavage by the HCV NS3/4A protease and identified all 3 known trans cleavage sites with high specificity. In the kinase assay, peptide substrates phosphorylated by tyrosine kinases were captured and identified by sequencing of their cDNAs. We screened a pool of 3,243 peptides against Abl kinase and showed that phosphorylation events detected were specific and consistent with the known substrate preferences of Abl kinase. Our approach is scalable and adaptable to other protein-based assays.

New details of HCV NS3/4A proteinase functionality revealed by a high-throughput cleavage assay.

BACKGROUND: The hepatitis C virus (HCV) genome encodes a long polyprotein, which is processed by host cell and viral proteases to the individual structural and non-structural (NS) proteins. HCV NS3/4A serine proteinase (NS3/4A) is a non-covalent heterodimer of the N-terminal, ∼180-residue portion of the 631-residue NS3 protein with the NS4A co-factor. NS3/4A cleaves the polyprotein sequence at four specific regions. NS3/4A is essential for viral replication and has been considered an attractive drug target. METHODOLOGY/PRINCIPAL FINDINGS: Using a novel multiplex cleavage assay and over 2,660 peptide sequences derived from the polyprotein and from introducing mutations into the known NS3/4A cleavage sites, we obtained the first detailed fingerprint of NS3/4A cleavage preferences. Our data identified structural requirements illuminating the importance of both the short-range (P1-P1') and long-range (P6-P5) interactions in defining the NS3/4A substrate cleavage specificity. A newly observed feature of NS3/4A was a high frequency of either Asp or Glu at both P5 and P6 positions in a subset of the most efficient NS3/4A substrates. In turn, aberrations of this negatively charged sequence such as an insertion of a positively charged or hydrophobic residue between the negatively charged residues resulted in inefficient substrates. Because NS5B misincorporates bases at a high rate, HCV constantly mutates as it replicates. Our analysis revealed that mutations do not interfere with polyprotein processing in over 5,000 HCV isolates indicating a pivotal role of NS3/4A proteolysis in the virus life cycle. CONCLUSIONS/SIGNIFICANCE: Our multiplex assay technology in light of the growing appreciation of the role of proteolytic processes in human health and disease will likely have widespread applications in the proteolysis research field and provide new therapeutic opportunities.

IGFBP-4 tumor and serum levels are increased across all stages of epithelial ovarian cancer.

BACKGROUND: We sought to identify candidate serum biomarkers for the detection and surveillance of EOC. Based on RNA-Seq transcriptome analysis of patient-derived tumors, highly expressed secreted proteins were identified using a bioinformatic approach. METHODS: RNA-Seq was used to quantify papillary serous ovarian cancer transcriptomes. Paired end sequencing of 22 flash frozen tumors was performed. Sequence alignments were processed with the program ELAND, expression levels with ERANGE and then bioinformatically screened for secreted protein signatures. Serum samples from women with benign and malignant pelvic masses and serial samples from women during chemotherapy regimens were measured for IGFBP-4 by ELISA. Student's t Test, ANOVA, and ROC curves were used for statistical analysis. RESULTS: Insulin-like growth factor binding protein (IGFBP-4) was consistently present in the top 7.5% of all expressed genes in all tumor samples. We then screened serum samples to determine if increased tumor expression correlated with serum expression. In an initial discovery set of 21 samples, IGFBP-4 levels were found to be elevated in patients, including those with early stage disease and normal CA125 levels. In a larger and independent validation set (82 controls, 78 cases), IGFBP-4 levels were significantly increased (p < 5 × 10-5). IGFBP-4 levels were ~3× greater in women with malignant pelvic masses compared to women with benign masses. ROC sensitivity was 73% at 93% specificity (AUC 0.816). In women receiving chemotherapy, average IGFBP-4 levels were below the ROC-determined threshold and lower in NED patients compared to AWD patients. CONCLUSIONS: This study, the first to our knowledge to use RNA-Seq for biomarker discovery, identified IGFBP-4 as overexpressed in ovarian cancer patients. Beyond this, these studies identified two additional intriguing findings. First, IGFBP-4 can be elevated in early stage disease without elevated CA125. Second, IGFBP-4 levels are significantly elevated with malignant versus benign disease. These findings provide the rationale for future validation studies.

Clinicopathologic and gene expression parameters predict liver cancer prognosis.

BACKGROUND: The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. METHODS: Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. RESULTS: HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. CONCLUSION: When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome.

Predictive genes in adjacent normal tissue are preferentially altered by sCNV during tumorigenesis in liver cancer and may rate limiting.

BACKGROUND: In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ∼250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. CONCLUSIONS/SIGNIFICANCE: This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types.

Expression signatures that correlated with Gleason score and relapse in prostate cancer.

Predicting prognosis in prostate carcinoma remains a challenge when using clinical and pathologic criteria only. We used an array-based DASL assay to identify molecular signatures for predicting prostate cancer relapse in formalin-fixed, paraffin-embedded (FFPE) prostate cancers, through gene expression profiling of 512 prioritized genes. Of the 71 patients that we analyzed, all but 3 had no evidence of residual tumor (defined as negative surgical margins) following radical prostatectomy and no patient received adjuvant therapy following surgery. All of the 71 patients had an undetectable serum PSA following radical prostatectomy. Follow-up period was 44+/-15 months. Highly reproducible gene expression patterns were obtained with these samples (average R(2)=0.99). We identified a panel of 11 genes that correlated positively and 5 genes that correlated negatively with Gleason grade. A gene expression score (GEX) was derived from the expression levels of the 16 genes. We assessed the prognostic value of these genes and found the GEX significantly correlated with disease relapse (p=0.007). These results suggest that the approach we used is effective for expression profiling in heterogeneous FFPE tissues for cancer diagnosis/prognosis biomarker discovery and validation.

Human embryonic stem cells have a unique epigenetic signature.

Human embryonic stem (hES) cells originate during an embryonic period of active epigenetic remodeling. DNA methylation patterns are likely to be critical for their self-renewal and pluripotence. We compared the DNA methylation status of 1536 CpG sites (from 371 genes) in 14 independently isolated hES cell lines with five other cell types: 24 cancer cell lines, four adult stem cell populations, four lymphoblastoid cell lines, five normal human tissues, and an embryonal carcinoma cell line. We found that the DNA methylation profile clearly distinguished the hES cells from all of the other cell types. A subset of 49 CpG sites from 40 genes contributed most to the differences among cell types. Another set of 25 sites from 23 genes distinguished hES cells from normal differentiated cells and can be used as biomarkers to monitor differentiation. Our results indicate that hES cells have a unique epigenetic signature that may contribute to their developmental potential.

Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines.

BACKGROUND: In order to compare the gene expression profiles of human embryonic stem cell (hESC) lines and their differentiated progeny and to monitor feeder contaminations, we have examined gene expression in seven hESC lines and human fibroblast feeder cells using Illumina bead arrays that contain probes for 24,131 transcript probes. RESULTS: A total of 48 different samples (including duplicates) grown in multiple laboratories under different conditions were analyzed and pairwise comparisons were performed in all groups. Hierarchical clustering showed that blinded duplicates were correctly identified as the closest related samples. hESC lines clustered together irrespective of the laboratory in which they were maintained. hESCs could be readily distinguished from embryoid bodies (EB) differentiated from them and the karyotypically abnormal hESC line BG01V. The embryonal carcinoma (EC) line NTera2 is a useful model for evaluating characteristics of hESCs. Expression of subsets of individual genes was validated by comparing with published databases, MPSS (Massively Parallel Signature Sequencing) libraries, and parallel analysis by microarray and RT-PCR. CONCLUSION: we show that Illumina's bead array platform is a reliable, reproducible and robust method for developing base global profiles of cells and identifying similarities and differences in large number of samples.

High-throughput DNA methylation profiling using universal bead arrays.

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.

Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays.

We recently developed a sensitive and flexible gene expression profiling system that is not dependent on an intact poly-A tail and showed that it could be used to analyze degraded RNA samples. We hypothesized that the DASL (cDNA-mediated annealing, selection, extension and ligation) assay might be suitable for the analysis of formalin-fixed, paraffin-embedded tissues, an important source of archival tissue material. We now show that, using the DASL assay system, highly reproducible tissue- and cancer-specific gene expression profiles can be obtained with as little as 50 ng of total RNA isolated from formalin-fixed tissues that had been stored from 1 to over 10 years. Further, tissue- and cancer-specific markers derived from previous genome-wide expression profiling studies of fresh-frozen samples were validated in the formalin-fixed samples. The DASL assay system should prove useful for high-throughput expression profiling of archived clinical samples.

A versatile assay for high-throughput gene expression profiling on universal array matrices.

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.