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.
Highlights
The 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
Global Prognosis Performance of the Published Signatures The literature search identified 29 papers reporting 31 signatures proposed as valid multi-gene tumor-outcome classification tool (Table 1 and File S4)
In the independent datasets the performance was heterogeneous and none of these five signatures could reproduce the degree of predictive ability shown in the training datasets
Summary
The 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. Recognized clinical risk factors for recurrence are emergency presentation, poorly differentiated tumor, depth of tumor invasion, and adjacent organ involvement (T4) [3,4,5]. These factors are insufficient to identify those patients with stage II CRC at high risk of recurrence and posterior metastasis or those patients with stage III CRC at low risk [6], leading to potential undertreatment or over-treatment [3]. No signature has been adopted in routine clinical practice in CRC despite a large number of gene expression profiling studies on prognosis have been performed
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