Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer

Abstract

Background & aims: Staging inadequately predicts metastatic risk in patients with colon cancer. We used a gene expression profile derived from invasive, murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify patients with colon cancer at risk of recurrence.

Methods: This phase 1, exploratory biomarker study used 55 patients with colorectal cancer from Vanderbilt Medical Center (VMC) as the training dataset and 177 patients from the Moffitt Cancer Center as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined with comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A metastasis score derived from the biologically based classifier was tested in the Moffitt dataset.

Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathologic stages and specifically in stage II and stage III patients. The metastasis score was shown to independently predict risk of cancer recurrence and death in univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk of cancer recurrence (hazard ratio, 4.7; 95% confidence interval, 1.566-14.05). Furthermore, the metastasis score identified patients with stage III disease whose 5-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not increase survival time.

Conclusion: A gene expression profile identified from an experimental model of colon cancer metastasis predicted cancer recurrence and death, independently of conventional measures, in patients with colon cancer.

Conflict of interest statement

Conflicts of interest

The authors disclose no conflicts.

Copyright 2010 AGA Institute. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Cell culture and mouse model: murine model of metastasis, in vivo monitoring, and ex vivo proof of metastases. (A) MC-38 parental cells (heterogeneous, blue and red) were subjected to 6 sequential passages through matrigel-coated transwells (enrichment of invasive subpopulations of MC-38 cells [red]) called “MC-38inv.” After in vivo passage, a stabilized cell line (pink cells) called “MC-38met” was established. (B) MC-38inv cells were tested alongside MC-38 parental cells for the ability to form lung metastasis in a tail vein assay. The figure shows representative tumor progression in live mice by bioluminescent imaging (days 1–21) and at the time of autopsy (day 21).

Figure 2

(A) Recurrence classifier development. VMC 2-step schematic for enrichment and establishment of the 34-gene recurrence classifier for colon cancer. Mouse genes were mapped to human orthologs, and 300 differentially expressed genes (MC-38 parental versus MC-38met) were identified. These 300 genes were next refined with 19 high-risk patients from the VMC training dataset for concordance. This analysis showed 34 genes with concordant expression among the 19 high-risk patients and the MC-38met cells. The 34-gene recurrence classifier was then applied to the independent MCC database to determine whether it could be used to discriminate patients on the basis of outcomes. (B) Functional genomic cluster analysis of the 34-gene recurrence classifier. Mean-centered gene expression data (rows) clustered with individual VMC patients (columns) results in 2 distinct patient groups (cluster 1, pink; cluster 2, green). The 19 VMC high-risk patients used in the concordance analysis are marked with a red asterisk.

Figure 3

The 34-gene recurrence classifier as tested in the MCC dataset across all stages. Kaplan–Meier estimates of overall and disease-specific survival in the MCC test set. Expression data for probes corresponding to the 34-gene recurrence classifier were used to build the Cox proportional hazard model from patient data in the Vanderbilt dataset. Plots represent survival analyses in the MCC patient dataset, based on β and Wald statistics (see Supplementary Methods) from the Vanderbilt dataset. (A) Overall and (B) disease-specific survival analyses were performed.

Figure 4

Kaplan–Meier estimates from 114 patients with colon cancer (stages II and III) under study at MCC were analyzed with the 34-gene–based metastasis score. Lower-than-median metastasis score is denoted in black and higher-than-median metastasis score is noted in red. A low score was associated with better disease-specific and disease-free survival in patients with stage II (A cancer-related death, n = 57 patients; high scores [9 of 9 total deaths] and B disease-free survival; n = 55; high scores [10 of 11 total events]). Similarly, a low score was associated with better disease-specific and disease-free survival in patients with stage III colon cancer (C cancer-related death, n = 57 patients, high scores [14 of 17 total deaths] and D disease-free survival, n = 56, high scores [16 of 20 total events]). Five-year mortality and recurrence rates are shown for patients with stage II and III colon cancer (A to D).