In the present study, the biology of colon cancer metastasis was modeled in immunocompetent mice to develop a gene expression classifier that discriminates recurrence and survival outcomes in human patients with colon cancer. Patients with stage II and stage III primary colon cancers that reflected the recurrence-associated gene expression pattern were at greater relative risk of recurrence than patients who did not (HR = 13.1 and 4.7, respectively). This gene expression profile, tested with a recurrence scoring method, performed independently of conventional pathologic staging.
Perhaps most importantly, this metastasis score identifies patients with stage II colon cancer at high risk of recurrence and death and patients with stage III colon cancer at low risk of recurrence and death. Our biological model has identified a subset of high-risk stage II patients who may benefit from adjuvant therapy and a subset of low-risk stage II patients who may have an excellent outcome after surgical resection without adjuvant therapy. We found that the 5-year survival rate was >95% in patients with stage II colon cancer who had a low metastasis score, suggesting that adjuvant CTX would provide minimal benefit in this group of patients. In contrast, 31% of patients with stage II colon cancer with a high metastasis score died of cancer. Our preliminary analyses of these data suggest that patients with stage II colon cancer with high metastasis scores should be further studied to determine whether they will benefit from adjuvant therapy.
A unique aspect of our study is the inclusion of sufficient numbers of patients with stage III colon cancer who did not receive adjuvant CTX in the MCC database. This enabled an evaluation of whether the molecular metastasis score could predict response to adjuvant therapy. Of the patients with stage III colon cancer with high metastasis scores who were treated with adjuvant CTX only 36.4% died of cancer, whereas 85.7% of the patients with high scores who did not receive adjuvant CTX died of cancer. Despite the small numbers in these subgroups, the differences were statistically significant. More importantly, equally low proportions of patients with stage III colon cancer with a low metastasis score died of cancer regardless of administration of CTX. Our data suggest that there is a low-risk group of patients with stage III colon cancer who could be surgically cured and spared the morbidity, expense, and potential mortality associated with adjuvant CTX. This is consistent with prior observations from randomized clinical trials that established the benefits of adjuvant CTX in stage III colon cancer whereby 40%–44% of patients enrolled in the surgery-only groups did not recur in 5 years even without adjuvant treatment.2
Determination of an objective scoring method whereby the 34-gene classifier can be tested in a prospective fashion is ongoing and will be required to determine whether the 34-gene– based metastasis score can be used clinically to guide decisions about adjuvant therapy for patients with stage III colon cancer.
Several investigative groups have reported gene expression classifiers with predictive power in breast, lung, liver, and colorectal cancers.22–27
Like the previously described colon cancer classifiers, a weakness of our model is the retrospective analysis of prospectively collected clinical data. A 43-gene poor-prognosis signature for colorectal cancer provides a classifier for patients with stage II and stage III as a molecular staging device.28
In a more recent study, a computational model was used to derive a 50-gene signature and a metastasis score for early-stage colon cancer.29
We found minimal overlap between our 34-gene classifier and the previously published, computationally derived colon cancer gene signatures. We were not surprised at this finding because the prior models were computationally determined, and ours is founded on the biology of metastasis.
We find it interesting that 13 of the 34 genes in our proposed classifier have previously described roles in cancer, and several others are involved in cell–cell signaling, immune response, cell proliferation, embryonic development, and cell migration. Inflammation plays a potent role in gastrointestinal tract tumor promotion, and tumor progression is associated with immune suppression.30–32
In this study, microarray analysis identified perturbations in gene networks related to both carcinogenesis and inflammation. Ongoing work in our laboratory aims to unravel the molecular mechanisms by which these 2 gene networks may interact to promote metastasis in our experimental model.
The cross-species functional genomics approach yields insights into the molecular mechanisms of the metastatic process. Consistent with our approach, gene expression patterns identified in wound healing have been applied successfully to breast cancer outcomes.33
In addition, cell culture and mouse models have also shown relevance to clinical outcomes in hepatocellular carcinoma with the use of gene expression profiling.34,35
Similarly, our approach has uncovered a gene classifier with prognostic significance in colon cancer.
Although a high score based on the 34-gene recurrence classifier worked well in this study, the number of significant genes reported was not based on the smallest number of genes that could discriminate the survival endpoint, but was based on the combined statistical, biological, and clinical evidence in the available data. There is also the possibility that some of the computationally derived genes discovered in human datasets would be missed in a mouse model; however, the biological basis of the 34-gene classifier derived from our mouse model seems to be a robust predictor. The possibility of achieving similar or better survival discrimination with different subsets of the genes certainly exists; however, we feel that the biological basis of our study provides a solid foundation for further translational application and testing of our model.
In conclusion, the 34-gene– based metastasis score can identify patients with stage II and III colon cancer at greater risk of colon cancer recurrence and death. Our biologically based expression classifier identifies a potential method for more appropriate selection of patients for systemic therapy after curative-intent surgical resection of colon cancer. Future prospective studies are needed to confirm whether CTX may be safely avoided in patients with stage III colon cancer with a low metastasis score and whether patients with stage II colon cancer with a high metastasis score can achieve a better outcome if they receive adjuvant CTX.