SynthesisPloS one2012
Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.
Synthesis in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.PloS one · 2014Trial
- Prognostic aging gene-based score for colorectal cancer: unveiling links to drug resistance, mutation burden, and personalized treatment strategies.Discover oncology · 2024Article
- Enhanced Clinical Utility of Molecular Budding Signature as a Recurrence Risk Determinant in Stage II and III Colon Cancer Patients.Annals of surgical oncology · 2023Article
- Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer.Cancers · 2023Article
- Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma.BioData mining · 2023Article
- Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning.BioData mining · 2022Article
- Molecular Biomarker of Drug Resistance Developed From Patient-Derived Organoids Predicts Survival of Colorectal Cancer Patients.Frontiers in oncology · 2022Article
- Adoptive NK Cell Transfer as a Treatment in Colorectal Cancer Patients: Analyses of Tumour Cell Determinants Correlating With EfficacyFrontiers in immunology · 2022Article
- Overexpression of DDIT4 and TPTEP1 are associated with metastasis and advanced stages in colorectal cancer patients: a study utilizing bioinformatics prediction and experimental validation.Cancer cell international · 2021Article
- Update of the recommendations for the determination of biomarkers in colorectal carcinoma: National Consensus of the Spanish Society of Medical Oncology and the Spanish Society of Pathology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020Article
- Machine learning identifies two autophagy-related genes as markers of recurrence in colorectal cancer.The Journal of international medical research · 2020Article
- Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis.PLoS medicine · 2020Article
- Interplay between DNA damage repair and apoptosis shapes cancer evolution through aneuploidy and microsatellite instability.Nature communications · 2020Article
- Article
- Multigene Biomarkers of Pyrethroid Exposure: Exploratory Experiments.Environmental toxicology and chemistry · 2019Article
- The Expression Profile and Prognostic Significance of Metallothionein Genes in Colorectal Cancer.International journal of molecular sciences · 2019Article
- Integrative analysis from multi-centre studies identifies a function-derived personalized multi-gene signature of outcome in colorectal cancer.Journal of cellular and molecular medicine · 2019Article
- Identification of a 6-gene signature predicting prognosis for colorectal cancer.Cancer cell international · 2019Article
- Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling.BMC genomics · 2018Article
- Evolving notions on immune response in colorectal cancer and their implications for biomarker development.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2018Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets.
methodsA literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples.
resultsFive gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system.
conclusionsThe published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.
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