Deregulation of oncogenic signaling pathways was used to molecularly subclassify colorectal cancers into clinically relevant subgroups with both prognostic and predictive implications, in a study from the Duke Institute for Genome Sciences and Policy in Durham, North Carolina.¹

“There is a need to individualize therapy for colorectal cancer. A main challenge is determining which patients are at risk for recurrence after resection and who should be treated with adjuvant chemotherapy,” said Joshua M. Uronis, PhD. The work was conducted in the laboratory of
David Hsu, MD, PhD.

At the 2013 Gastrointestinal Cancers Symposium, Dr. Uronis described the group’s effort to develop genetic biomarkers that are prognostic for recurrence, predictive of drug sensitivity, and applicable in both the primary and metastatic settings.

Study Design

The researchers compiled microarray data from 850 patients with primary colorectal cancer from four datasets, based on the activity of 19 oncogenic pathways, and used this information to generate unique patterns of pathway deregulation for each patient’s tumor. Six molecular subgroups of colorectal cancer were identified, and they differed significantly in their risk of recurrence. For example, while recurrence-free survival approached 100% for molecular subgroup 4, it fell to about 40% for molecular subgroup 3 (P = .0004). A similar result was observed when the model was applied to the metastatic data set (P = .046).

These patterns were then translated into gene-expression signatures and used to measure the probability of pathway activation in a panel of cell lines. Under this approach, the model proved predictive of response to certain drug treatments, Dr. Uronis reported.

“We observed that [molecular subgroups] demonstrated differential sensitivity to specific targeted agents, such as [subgroups] 1, 2, and 3 to inhibition of HER2 by lapatinib [Tykerb] and inhibition of the epidermal growth factor receptor by erlotinib [Tarceva] (P < .05),” he said. “From this we gather that we can make basic predictions using pathway signatures.”

Patient-derived Explants

The researchers’ next step was to design patient-derived colorectal cancer explants that formed the basis of a murine model of drug sensitivity. This model is being used to validate the findings. For example, the experiments have shown that molecular subgroups with high mTOR activity are highly sensitive to mTOR inhibitors, while those with low mTOR expression are resistant to these agents.

“Currently, we have developed 50 independent explants,” he said. “This will allow for in vivovalidation of the findings.”

The findings suggest that prognostic and predictive biomarkers can be derived by combining a genomic-based molecular profile of colorectal cancer with a preclinical murine model of patient-derived colorectal cancer explants, he said. ■

Disclosure: Dr. Uronis reported no potential conflicts of interest.

Reference

1. Uronis JM, VanDeusen JB, Datto MB, et al: A molecular profile of colorectal cancer to guide prognosis and therapy after resection of primary or metastatic disease. 2013 Gastrointestinal Cancers Symposium. Abstract 339. Presented January 26, 2013.