Upregulation of trefoil factor 3 (TFF3) after rectal cancer chemoradiotherapy is an adverse prognostic factor and a potential therapeutic target.

PURPOSE: Management of locally advanced rectal cancer (RC) consists of neoadjuvant chemoradiotherapy (CRT) with fluoropyrimidines, followed by total mesorectal excision. We sought to evaluate the expression of selected genes, some of which were derived from a previous undirected SAGE (serial analysis of gene expression)-based approach, before and after CRT, to identify mechanisms of resistance. METHODS: This retrospective cohort study included 129 consecutive patients. Quantitative polymerase chain reaction of 53 candidate genes was performed on the biopsy specimen before treatment and on the surgical specimen after CRT. A paired-samples t test was performed to determine genes that were significantly changed after CRT. The result was correlated with patients' disease-free survival. RESULTS: Twenty-two genes were significantly upregulated, and two were significantly downregulated. Several of the upregulated genes have roles in cell cycle control; these include CCNB1IP1, RCC1, EEF2, CDKN1, TFF3, and BCL2. The upregulation of TFF3 was associated with worse disease-free survival on multivariate analyses (hazard ratio, 2.64; P=.027). Patients whose surgical specimens immunohistochemically showed secretion of TFF3 into the lumen of the tumoral microglands had a higher risk of relapse (hazard ratio, 2.51; P=.014). In vitro experiments showed that DLD-1 cells stably transfected with TFF3 were significantly less sensitive to 5-fluorouracil and showed upregulation of genes involved in the transcriptional machinery and in resistance to apoptosis. CONCLUSION: Upregulation of TFF3 after CRT for RC is associated with a higher risk of relapse. The physiological role of TFF3 in restoring the mucosa during CRT could be interfering with treatment efficacy. Our results could reveal not only a novel RC prognostic marker but also a therapeutic target.

A combined strategy of SAGE and quantitative PCR Provides a 13-gene signature that predicts preoperative chemoradiotherapy response and outcome in rectal cancer.

PURPOSE: Preoperative chemoradiotherapy (CRT) is the treatment of choice for rectal cancer (RC), but half of the patients do not respond, suffer unnecessary toxicities, and surgery delays. We aimed to develop a model that could predict a clinically meaningful response to CRT by using formalin-fixed paraffin-embedded (FFPE) biopsies. EXPERIMENTAL DESIGN: We first carried out an exploratory screening of candidate genes by using SAGE technology to evaluate dynamic changes in the RC transcriptome in selected refractory patients before and after CRT. Next, 53 genes (24 from SAGE and 29 from the literature) were analyzed by qPCR arrays in FFPE initial biopsies from 94 stage II/III RC patients who were preoperatively treated with CRT. Tumor response was defined by using Dworak's tumor regression grade (2-3-4 vs. 0-1). Multivariate Cox methods and stepwise algorithms were applied to generate an optimized predictor of response and outcome. RESULTS: In the training cohort (57 patients), a 13-gene signature predicted tumor response with 86% accuracy, 87% sensitivity, and 82% specificity. In a testing cohort (37 patients), the model correctly classified 6 of 7 nonresponders, with an overall accuracy of 76%. A signature-based score identified patients with a higher risk of relapse in univariate (3-year disease-free survival 64% vs. 90%, P = 0.001) and multivariate analysis (HR = 4.35 95% CI: 1.2-15.75, P = 0.02), in which it remained the only statistically significant prognostic factor. CONCLUSIONS: A basal 13-gene signature efficiently predicted CRT response and outcome. Multicentric validation by the GEMCAD collaborative group is currently ongoing. If confirmed, the predictor could be used to improve patient selection in RC studies.

Parallel anticancer drug development and molecular stratification to qualify predictive biomarkers: dealing with obstacles hindering progress.

Current anticancer drug development still largely follows the classic designs developed for chemotherapeutic agents over the past 4 to 5 decades, remaining slow, costly, and inefficient, with continuing high risks of costly late drug attrition. A Pharmacologic Audit Trail has been described to decrease these risks, incorporating pharmacokinetic, pharmacodynamic, intermediate efficacy endpoints, as well as patient stratification molecular biomarkers. Molecular biomarker-based patient selection in hypothesis-testing early clinical trials is critical to clinically qualify putative predictive biomarkers for rationally designed, molecularly targeted drugs as early as possible. Nevertheless, major concerns have been raised about the impact of using such biomarkers in early trials, in view of the costs and time involved to develop multiple certified assays for clinical use. The rapid evolution of novel technologies of utility to this field, such as next-generation sequencing and circulating tumor-cell isolation, makes these valid concerns of critical importance. We therefore propose a more efficient parallel predictive biomarker and clinical anticancer drug development process to deal with the obstacles hindering progress.