Dataset Information

NTRK1 fusion in glioblastoma multiforme.

ABSTRACT: Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor, yet with no targeted therapy with substantial survival benefit. Recent studies on solid tumors showed that fusion genes often play driver roles and are promising targets for pharmaceutical intervention. To survey potential fusion genes in GBMs, we analysed RNA-Seq data from 162 GBM patients available through The Cancer Genome Atlas (TCGA), and found that 3' exons of neurotrophic tyrosine kinase receptor type 1 (NTRK1, encoding TrkA) are fused to 5' exons of the genes that are highly expressed in neuronal tissues, neurofascin (NFASC) and brevican (BCAN). The fusions preserved both the transmembrane and kinase domains of NTRK1 in frame. NTRK1 is a mediator of the pro-survival signaling of nerve growth factor (NGF) and is a known oncogene, found commonly altered in human cancer. While GBMs largely lacked NTRK1 expression, the fusion-positive GBMs expressed fusion transcripts in high abundance, and showed elevated NTRK1-pathway activity. Lentiviral transduction of the NFASC-NTRK1 fusion gene in NIH 3T3 cells increased proliferation in vitro, colony formation in soft agar, and tumor formation in mice, suggesting the possibility that the fusion contributed to the initiation or maintenance of the fusion-positive GBMs, and therefore may be a rational drug target.

SUBMITTER: Kim J

PROVIDER: S-EPMC3960150 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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NTRK1 fusion in glioblastoma multiforme.

Kim Jinkuk J Lee Yeri Y Cho Hee Jin HJ Lee Young-Eun YE An Jaeyeol J Cho Gye-Hyun GH Ko Young-Hyeh YH Joo Kyeung Min KM Nam Do-Hyun DH

PloS one 20140319 3

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor, yet with no targeted therapy with substantial survival benefit. Recent studies on solid tumors showed that fusion genes often play driver roles and are promising targets for pharmaceutical intervention. To survey potential fusion genes in GBMs, we analysed RNA-Seq data from 162 GBM patients available through The Cancer Genome Atlas (TCGA), and found that 3' exons of neurotrophic tyrosine kinase receptor type 1 (NTRK1, enco ...[more]

PMID: 24647444

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Project description:Our goals are to develop a computational histopathology pipeline for characterizing tumor types that are being generated by The Cancer Genome Atlas (TCGA) for genomic association. TCGA is a national collaborative program where different tumor types are being collected, and each tumor is being characterized using a variety of genome-wide platforms. Here, we have developed a tumor-centric analytical pipeline to process tissue sections stained with hematoxylin and eosin (H&E) for visualization and cell-by-cell quantitative analysis. Thus far, analysis is limited to Glioblastoma Multiforme (GBM) and kidney renal clear cell carcinoma tissue sections. The final results are being distributed for subtyping and linking the histology sections to the genomic data.A computational pipeline has been designed to continuously update a local image database, with limited clinical information, from an NIH repository. Each image is partitioned into blocks, where each cell in the block is characterized through a multidimensional representation (e.g., nuclear size, cellularity). A subset of morphometric indices, representing potential underlying biological processes, can then be selected for subtyping and genomic association. Simultaneously, these subtypes can also be predictive of the outcome as a result of clinical treatments. Using the cellularity index and nuclear size, the computational pipeline has revealed five subtypes, and one subtype, corresponding to the extreme high cellularity, has shown to be a predictor of survival as a result of a more aggressive therapeutic regime. Further association of this subtype with the corresponding gene expression data has identified enrichment of (i) the immune response and AP-1 signaling pathways, and (ii) IFNG, TGFB1, PKC, Cytokine, and MAPK14 hubs.While subtyping is often performed with genome-wide molecular data, we have shown that it can also be applied to categorizing histology sections. Accordingly, we have identified a subtype that is a predictor of the outcome as a result of a therapeutic regime. Computed representation has become publicly available through our Web site.

Dataset Information

NTRK1 fusion in glioblastoma multiforme.

Publications

NTRK1 fusion in glioblastoma multiforme.

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