RETRACTED: A genomic approach to colon cancer risk stratification yields biologic insights into therapeutic opportunities

Abstract

Gene expression profiles provide an opportunity to dissect the heterogeneity of solid tumors, including colon cancer, to improve prognosis and predict response to therapies. Bayesian binary regression methods were used to generate a signature of disease recurrence in patients with resected early stage colon cancer validated in an independent cohort. A 50-gene signature was developed that effectively distinguished early stage colon cancer patients with a low or high risk of disease recurrence. RT-PCR analysis of the 50-gene signature validated 9 of the top 10 differentially expressed genes. When applied to two independent validation cohorts of 55 and 73 patients, the 50-gene model accurately predicted recurrence. Standard Kaplan–Meier survival analysis confirmed the prognostic accuracy ( P < 0.01, log rank), as did multivariate Cox proportional hazard models. We tested potential targeted therapeutic options for patients at high risk for disease recurrence and found a clinically important relationship between sensitivity to celecoxib, LY-294002 (PI3kinase inhibitor), retinol, and sulindac in colon cancer cell lines expressing the poor prognostic phenotype ( P < 0.01, t test), which performed better than standard chemotherapy (5-FU and oxaliplatin). We present a genomic strategy in early stage colon cancer to identify patients at highest risk of recurrence. An ability to move beyond current staging by refining the estimation of prognosis in early stage colon cancer also has implications for individualized therapy.

Prognostic Factors Assessed for 15,096 Patients with Colon Cancer in Stages I and II

“…New perspectives are given by gene and protein research [2,22,27,28], evaluation of apoptosis-regulating proteins in the context of tumor progression and response to therapy [29], and analysis of molecular signatures in colorectal cancer [30,31].…”

A Quantitative Proteomic Approach of the Different Stages of Colorectal Cancer Establishes OLFM4 as a New Nonmetastatic Tumor Marker

“…The distinction between these two cases is actually difficult, and for this reason, the identification of specific biomarkers of stage II colorectal tumors is an important goal that would allow the prediction of recurrence events. A 50-gene signature has been recently described that can separate early tumors depending on their relapse probability (15). Therefore, it will be interesting to determine whether the protein list identified in this study can be used to improve this early stage stratification to predict tumor relapse.…”

“…Elegant results have recently identified gene expression profiles that associate with specific oncogenic pathways and can eventually predict chemotherapy sensitivity (13,14). This approach has also been successfully used in CRC to identify a 50-gene signature that distinguished patients with low or high risks or recurrence at the early stage of the disease (15). These results also led to the identification of a therapeutic approach that would be specific of a particular stage of CRC.…”

Editorial: Reproducible Research in Medical Imaging

“…A series of papers on a flawed gene-expression test, published in top scientific journals by a cancer research group at Duke, have since been retracted (en.wikipedia.org/wiki/Anil_Potti). In their retraction, the authors state: "We wish to retract this article because we have been unable to reproduce certain key experiments described in the paper regarding validation and use of the colon cancer prognostic signature" [8]. It might seem too much to expect readers to be able to reproduce such research by reading these papers.…”