Comparing mutation calls in fixed tumour samples between the affymetrix OncoScan® array and PCR based next-generation sequencing.

BACKGROUND: The importance of accurate and affordable mutation calling in fixed pathology samples is becoming increasingly important as we move into the era of personalised medicine. The Affymetrix OncoScan® Array platform is designed to produce actionable mutation calls in archival material. METHODS: We compared calls made using the OncoScan platform with calls made using a custom designed PCR panel followed by next-generation sequencing (NGS), in order to benchmark the sensitivity and specificity of the OncoScan calls in a large cohort of fixed tumour samples. 392 fixed, clinical samples were sequenced, encompassing 641 PCR regions, 403 putative positive calls and 1528 putative negative calls. RESULTS: A small number of mutations could not be validated, either due to large indels or pseudogenes impairing parts of the NGS pipeline. For the remainder, if calls were filtered according to simple quality metrics, both sensitivity and specificity for the OncoScan platform were over 98%. This applied even to samples with poorer sample quality and lower variant allele frequency (5-10%) than product claims indicated. CONCLUSIONS: This benchmarking study will be useful to users and potential users of this platform, who wish to compare technologies or interpret their own results.

Genomic complexity of urothelial bladder cancer revealed in urinary cfDNA.

Urothelial bladder cancers (UBCs) have heterogeneous clinical characteristics that are mirrored in their diverse genomic profiles. Genomic profiling of UBCs has the potential to benefit routine clinical practice by providing prognostic utility above and beyond conventional clinicopathological factors, and allowing for prediction and surveillance of treatment responses. Urinary DNAs representative of the tumour genome provide a promising resource as a liquid biopsy for non-invasive genomic profiling of UBCs. We compared the genomic profiles of urinary cellular DNA and cell-free DNA (cfDNA) from the urine with matched diagnostic formalin-fixed paraffin-embedded tumour DNAs for 23 well-characterised UBC patients. Our data show urinary DNAs to be highly representative of patient tumours, allowing for detection of recurrent clinically actionable genomic aberrations. Furthermore, a greater aberrant load (indicative of tumour genome) was observed in cfDNA over cellular DNA (P<0.001), resulting in a higher analytical sensitivity for detection of clinically actionable genomic aberrations (P<0.04) when using cfDNA. Thus, cfDNA extracted from the urine of UBC patients has a higher tumour genome burden and allows greater detection of key genomic biomarkers (90%) than cellular DNA from urine (61%) and provides a promising resource for robust whole-genome tumour profiling of UBC with potential to influence clinical decisions without invasive patient interventions.

HER2 overexpression and amplification as a potential therapeutic target in colorectal cancer: analysis of 3256 patients enrolled in the QUASAR, FOCUS and PICCOLO colorectal cancer trials.

HER2 overexpression/amplification is linked to trastuzumab response in breast/gastric cancers. One suggested anti-EGFR resistance mechanism in colorectal cancer (CRC) is aberrant MEK-AKT pathway activation through HER2 up-regulation. We assessed HER2-amplification/overexpression in stage II-III and IV CRC patients, assessing relationships to KRAS/BRAF and outcome. Pathological material was obtained from 1914 patients in the QUASAR stage II-III trial and 1342 patients in stage IV trials (FOCUS and PICCOLO). Tissue microarrays were created for HER2 immunohistochemistry. HER2-amplification was assessed using FISH and copy number variation. KRAS/BRAF mutation status was assessed by pyrosequencing. Progression-free survival (PFS) and overall survival (OS) data were obtained for FOCUS/PICCOLO and recurrence and mortality for QUASAR; 29/1342 (2.2%) stage IV and 25/1914 (1.3%) stage II-III tumours showed HER2 protein overexpression. Of the HER2-overexpressing cases, 27/28 (96.4%) stage IV tumours and 20/24 (83.3%) stage II-III tumours demonstrated HER2 amplification by FISH; 41/47 (87.2%) also showed copy number gains. HER2-overexpression was associated with KRAS/BRAF wild-type (WT) status at all stages: in 5.2% WT versus 1.0% mutated tumours (p < 0.0001) in stage IV and 2.1% versus 0.2% in stage II-III tumours (p = 0.01), respectively. HER2 was not associated with OS or PFS. At stage II-III, there was no significant correlation between HER2 overexpression and 5FU/FA response. A higher proportion of HER2-overexpressing cases experienced recurrence, but the difference was not significant. HER2-amplification/overexpression is identifiable by immunohistochemistry, occurring infrequently in stage II-III CRC, rising in stage IV and further in KRAS/BRAF WT tumours. The value of HER2-targeted therapy in patients with HER2-amplified CRC must be tested in a clinical trial. © 2015 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Cross-laboratory validation of the OncoScan® FFPE Assay, a multiplex tool for whole genome tumour profiling.

BACKGROUND: Adoption of new technology in both basic research and clinical settings requires rigorous validation of analytical performance. The OncoScan® FFPE Assay is a multiplexing tool that offers genome-wide copy number and loss of heterozygosity detection, as well as identification of frequently tested somatic mutations. METHODS: In this study, 162 formalin fixed paraffin embedded samples, representing six different tumour types, were profiled in triplicate across three independent laboratories. OncoScan® formalin fixed paraffin embedded assay data was then analysed for reproducibility of genome-wide copy number, loss of heterozygosity and somatic mutations. Where available, somatic mutation data was compared to data from orthogonal technologies (pyro/sanger sequencing). RESULTS: Cross site comparisons of genome-wide copy number and loss of heterozygosity profiles showed greater than 95% average agreement between sites. Somatic mutations pre-validated by orthogonal technologies showed greater than 90% agreement with OncoScan® somatic mutation calls and somatic mutation concordance between sites averaged 97%. CONCLUSIONS: Reproducibility of whole-genome copy number, loss of heterozygosity and somatic mutation data using the OncoScan® assay has been demonstrated with comparatively low DNA inputs from a range of highly degraded formalin fixed paraffin embedded samples. In addition, our data shows examples of clinically-relevant aberrations that demonstrate the potential utility of the OncoScan® assay as a robust clinical tool for guiding tumour therapy.

LipidHome: a database of theoretical lipids optimized for high throughput mass spectrometry lipidomics.

Protein sequence databases are the pillar upon which modern proteomics is supported, representing a stable reference space of predicted and validated proteins. One example of such resources is UniProt, enriched with both expertly curated and automatic annotations. Taken largely for granted, similar mature resources such as UniProt are not available yet in some other "omics" fields, lipidomics being one of them. While having a seasoned community of wet lab scientists, lipidomics lies significantly behind proteomics in the adoption of data standards and other core bioinformatics concepts. This work aims to reduce the gap by developing an equivalent resource to UniProt called 'LipidHome', providing theoretically generated lipid molecules and useful metadata. Using the 'FASTLipid' Java library, a database was populated with theoretical lipids, generated from a set of community agreed upon chemical bounds. In parallel, a web application was developed to present the information and provide computational access via a web service. Designed specifically to accommodate high throughput mass spectrometry based approaches, lipids are organised into a hierarchy that reflects the variety in the structural resolution of lipid identifications. Additionally, cross-references to other lipid related resources and papers that cite specific lipids were used to annotate lipid records. The web application encompasses a browser for viewing lipid records and a 'tools' section where an MS1 search engine is currently implemented. LipidHome can be accessed at http://www.ebi.ac.uk/apweiler-srv/lipidhome.

From Peptidome to PRIDE: public proteomics data migration at a large scale.

The PRIDE database, developed and maintained at the European Bioinformatics Institute (EBI), is one of the most prominent data repositories dedicated to high throughput MS-based proteomics data. Peptidome, developed by the National Center for Biotechnology Information (NCBI) as a sibling resource to PRIDE, was discontinued due to funding constraints in April 2011. A joint effort between the two teams was started soon after the Peptidome closure to ensure that data were not "lost" to the wider proteomics community by exporting it to PRIDE. As a result, data in the low terabyte range have been migrated from Peptidome to PRIDE and made publicly available under experiment accessions 17 900-18 271, representing 54 projects, ~53 million mass spectra, ~10 million peptide identifications, ~650,000 protein identifications, ~1.1 million biologically relevant protein modifications, and 28 species, from more than 30 different labs.

The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013.

The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.

Chromatographic retention time prediction for posttranslationally modified peptides.

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for mass spectrometry-based proteomics, especially in designing more efficient procedures for state-of-the-art targeted workflows. Additionally, accurate retention time predictions can also be used to increase confidence in identifications in shotgun experiments. Despite these obvious benefits, the use of such methods has so far not been extended to (posttranslationally) modified peptides due to the absence of efficient predictors for such peptides. We here therefore describe a new retention time predictor for modified peptides, built on the foundations of our existing Elude algorithm. We evaluated our software by applying it on five types of commonly encountered modifications. Our results show that Elude now yields equally good prediction performances for modified and unmodified peptides, with correlation coefficients between predicted and observed retention times ranging from 0.93 to 0.98 for all the investigated datasets. Furthermore, we show that our predictor handles peptides carrying multiple modifications as well. This latest version of Elude is fully portable to new chromatographic conditions and can readily be applied to other types of posttranslational modifications. Elude is available under the permissive Apache2 open source License at http://per-colator.com or can be run via a web-interface at http://elude.sbc.su.se.

PRIDE: quality control in a proteomics data repository.

The PRoteomics IDEntifications (PRIDE) database is a large public proteomics data repository, containing over 270 million mass spectra (by November 2011). PRIDE is an archival database, providing the proteomics data supporting specific scientific publications in a computationally accessible manner. While PRIDE faces rapid increases in data deposition size as well as number of depositions, the major challenge is to ensure a high quality of data depositions in the context of highly diverse proteomics work flows and data representations. Here, we describe the PRIDE curation pipeline and its practical application in quality control of complex data depositions. DATABASE URL: http://www.ebi.ac.uk/pride/.

A posteriori quality control for the curation and reuse of public proteomics data.

Proteomics is a rapidly expanding field encompassing a multitude of complex techniques and data types. To date much effort has been devoted to achieving the highest possible coverage of proteomes with the aim to inform future developments in basic biology as well as in clinical settings. As a result, growing amounts of data have been deposited in publicly available proteomics databases. These data are in turn increasingly reused for orthogonal downstream purposes such as data mining and machine learning. These downstream uses however, need ways to a posteriori validate whether a particular data set is suitable for the envisioned purpose. Furthermore, the (semi-)automatic curation of repository data is dependent on analyses that can highlight misannotation and edge conditions for data sets. Such curation is an important prerequisite for efficient proteomics data reuse in the life sciences in general. We therefore present here a selection of quality control metrics and approaches for the a posteriori detection of potential issues encountered in typical proteomics data sets. We illustrate our metrics by relying on publicly available data from the Proteomics Identifications Database (PRIDE), and simultaneously show the usefulness of the large body of PRIDE data as a means to derive empirical background distributions for relevant metrics.

Bioinformatics challenges in the proteomic analysis of human plasma.

Mass spectrometry has become the method of choice for studying proteins in complex mixtures in a qualitative and quantitative fashion. The application of mass spectrometry-based proteomics analyses on plasma has correspondingly been established as an important method for disease-associated biomarker discovery and validation. Yet despite being a readily available human sample, plasma poses several important challenges to the proteomics researcher. With a focus on bioinformatics aspects, this chapter will discuss the problems involved in analyzing plasma proteomics data, along with the scope of solutions available through specialised tools and sophisticated analysis methods.

Proteomics data repositories: providing a safe haven for your data and acting as a springboard for further research.

Despite the fact that data deposition is not a generalised fact yet in the field of proteomics, several mass spectrometry (MS) based proteomics repositories are publicly available for the scientific community. The main existing resources are: the Global Proteome Machine Database (GPMDB), PeptideAtlas, the PRoteomics IDEntifications database (PRIDE), Tranche, and NCBI Peptidome. In this review the capabilities of each of these will be described, paying special attention to four key properties: data types stored, applicable data submission strategies, supported formats, and available data mining and visualization tools. Additionally, the data contents from model organisms will be enumerated for each resource. There are other valuable smaller and/or more specialized repositories but they will not be covered in this review. Finally, the concept behind the ProteomeXchange consortium, a collaborative effort among the main resources in the field, will be introduced.

The Proteomics Identifications database: 2010 update.

The Proteomics Identifications database (PRIDE, http://www.ebi.ac.uk/pride) at the European Bioinformatics Institute has become one of the main repositories of mass spectrometry-derived proteomics data. For the last 2 years, PRIDE data holdings have grown substantially, comprising 60 different species, more than 2.5 million protein identifications, 11.5 million peptides and over 50 million spectra by September 2009. We here describe several new and improved features in PRIDE, including the revised submission process, which now includes direct submission of fragment ion annotations. Correspondingly, it is now possible to visualize spectrum fragmentation annotations on tandem mass spectra, a key feature for compliance with journal data submission requirements. We also describe recent developments in the PRIDE BioMart interface, which now allows integrative queries that can join PRIDE data to a growing number of biological resources such as Reactome, Ensembl, InterPro and UniProt. This ability to perform extremely powerful across-domain queries will certainly be a cornerstone of future bioinformatics analyses. Finally, we highlight the importance of data sharing in the proteomics field, and the corresponding integration of PRIDE with other databases in the ProteomExchange consortium.

A guide to the Proteomics Identifications Database proteomics data repository.

The Proteomics Identifications Database (PRIDE, www.ebi.ac.uk/pride) is one of the main repositories of MS derived proteomics data. Here, we point out the main functionalities of PRIDE both as a submission repository and as a source for proteomics data. We describe the main features for data retrieval and visualization available through the PRIDE web and BioMart interfaces. We also highlight the mechanism by which tailored queries in the BioMart can join PRIDE to other resources such as Reactome, Ensembl or UniProt to execute extremely powerful across-domain queries. We then present the latest improvements in the PRIDE submission process, using the new easy-to-use, platform-independent graphical user interface submission tool PRIDE Converter. Finally, we speak about future plans and the role of PRIDE in the ProteomExchange consortium.