ArticleBritish journal of cancer2012
Genomic Grade Index predicts postoperative clinical outcome of GIST.
Article in British journal of cancer, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Study on risk stratification and treatment strategy of blood indicators in patients with moderate risk of GIST.Frontiers in oncology · 2026Article
- Application of Multi-Omics Approach in Sarcomas: A Tool for Studying Mechanism, Biomarkers, and Therapeutic Targets.Frontiers in oncology · 2022Review
- Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer.British journal of cancer · 2021Article
- Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas.NPJ precision oncology · 2021Review
- Genomic complexity in pediatric synovial sarcomas (Synobio study): the European pediatric soft tissue sarcoma group (EpSSG) experience.Cancer medicine · 2018Article
- Gene expression identifies heterogeneity of metastatic behavior among gastrointestinal stromal tumors.Journal of translational medicine · 2016Article
- Decreasing iron-related indexes without anaemia in a patient with genetic haemochromatosis.Internal and emergency medicine · 2015Article
- PDL1 expression is an independent prognostic factor in localized GIST.Oncoimmunology · 2015Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrognosis of localised gastrointestinal stromal tumour (GIST) is heterogeneous, notably for patients with AFIP intermediate or high risk of relapse, who are candidates to adjuvant imatinib. We hypothesised that gene expression profiles might improve the prognostication and help to refine the indications for imatinib.
methodsWe collected gene expression and histoclinical data of 146 pre-treatment localised GIST samples treated with surgery alone. We searched for a gene expression signature (GES) predictive for relapse-free survival (RFS) and compared its performances to that of three published prognostic proliferation-based GES (Genomic Grade Index (GGI), 16-Kinase, and CINSARC) and AFIP classification. We also analysed a data set from 28 patients with advanced GIST treated with neo-adjuvant imatinib.
resultsWe identified a 275-gene GES (gene expression signature) predictive of RFS in a learning set and validated its robustness in an independent set. However, the GGI outperformed its prognostic performances, and those of the two other signatures and the AFIP intermediate-risk classification in two independent tests sets in uni- and multivariate analyses. Importantly, GGI could split the AFIP intermediate/high-risk samples into two groups with different RFS. Genomic Grade Index 'high-risk' tumours were more proliferative and genetically unstable than 'low-risk' tumours, and more sensitive to imatinib.
conclusionGGI refines the prediction of RFS in localised GIST and might help tailor adjuvant imatinib.
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