Dataset Information

Development of a novel splice array platform and its application in the identification of alternative splice variants

ABSTRACT: Changes in alternative splicing are associated with several pathological conditions, including cancer. Microarrays strategies, which allow for the characterization of thousands of alternative splice forms in a single test, can be applied to identify differential alternative splicing events. In this study, a novel splice array platform was developed, including the design of a high-density oligonucleotide array, a labeling procedure, and an algorithm to identify splice events. The array consists of exon probes and thermodynamically balanced junction probes. Suboptimal probes are tagged and considered in the final analysis. An unbiased labeling protocol was developed using random primers. The algorithm used to distinguish changes in expression from changes in splicing was calibrated using internal non-spliced control sequences. The performance of this splice array was first validated with artificial constructs for CDC6, VEGF, and PCBP4 isoforms. The platform was then applied to the analysis of differential splice forms for 8000 genes in lung cancer samples compared to matched normal lung tissue. The expression of lung cancer-associated splice isoforms was validated by RT-PCR. Overexpression of splice isoforms was identified for genes encoding CEACAM1, FHL-1, MLPH, and SUSD2. None of these splicing isoforms had been previously associated with lung cancer. In conclusion, this highly accurate methodology enables the detection of alternative splicing events in complex biological samples, providing a powerful tool to identify novel diagnostic and prognostic biomarkers for cancer and other pathologies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE18346 | GEO | 2009/10/06

SECONDARY ACCESSION(S): PRJNA118155

REPOSITORIES: GEO

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Project description:Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which is able to detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated down-modulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared to their controls. Splice variants identified included RAC1, OSBPL3, MKI67 and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 down-modulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers. This dataset corresponds to a publication in Molecular & Cellular Proteomics 16: 10.1074/mcp.TIR117.000056, 1850–1863, 2017, PMID: 28747380. Mass spectrometry data corresponding to this entry is available at ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD006486.

Dataset Information

Development of a novel splice array platform and its application in the identification of alternative splice variants

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