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. 2011 Feb 1;104(3):488-95.
doi: 10.1038/sj.bjc.6606054. Epub 2011 Jan 4.

Tumour gene expression predicts response to cetuximab in patients with KRAS wild-type metastatic colorectal cancer

J B Baker  1 , D Dutta, D Watson, T Maddala, B M Munneke, S Shak, E K Rowinsky, L-A Xu, C T Harbison, E A Clark, D J Mauro, S Khambata-Ford
Affiliations

Tumour gene expression predicts response to cetuximab in patients with KRAS wild-type metastatic colorectal cancer

J B Baker et al. Br J Cancer. .

Abstract

Background: Although it is accepted that metastatic colorectal cancers (mCRCs) that carry activating mutations in KRAS are unresponsive to anti-epidermal growth factor receptor (EGFR) monoclonal antibodies, a significant fraction of KRAS wild-type (wt) mCRCs are also unresponsive to anti-EGFR therapy. Genes encoding EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are promising gene expression-based markers but have not been incorporated into a test to dichotomise KRAS wt mCRC patients with respect to sensitivity to anti-EGFR treatment.

Methods: We used RT-PCR to test 110 candidate gene expression markers in primary tumours from 144 KRAS wt mCRC patients who received monotherapy with the anti-EGFR antibody cetuximab. Results were correlated with multiple clinical endpoints: disease control, objective response, and progression-free survival (PFS).

Results: Expression of many of the tested candidate genes, including EREG and AREG, strongly associate with all clinical endpoints. Using multivariate analysis with two-layer five-fold cross-validation, we constructed a four-gene predictive classifier. Strikingly, patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC.

Conclusion: Gene expression appears to identify KRAS wt mCRC patients who receive little benefit from cetuximab. It will be important to test this model in an independent validation study.

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Conflict of interest statement

The authors are employees of the respective companies listed.

Figures

Figure 1
Figure 1
(A) Distribution of likelihood ratio P-values in KRAS wt patients by gene rank (disease control). Note: formula image and += genes significantly associated with outcome, unadjusted P-value <0.05, formula image = genes associated with outcome controlling for FDR <0.05, *= genes not significantly associated with outcome. In total, 110 genes depicted. (B) Distribution of likelihood ratio P-values in KRAS wt patients by gene rank (objective response). Note: formula image and += genes significantly associated with outcome, unadjusted P-value <0.05, formula image= genes associated with outcome controlling for FDR <0.05, *= genes not significantly associated with outcome. In total, 110 genes depicted. (C) Distribution of likelihood ratio P-values in KRAS wt patients by gene rank (PFS). Note: formula image and += genes significantly associated with outcome, unadjusted P-value <0.05, formula image= genes associated with outcome controlling for FDR <0.05, *= genes not significantly associated with outcome. In total, 110 genes depicted.
Figure 2
Figure 2
Genes associated with outcome after adjusting for multiplicity across all three endpoints in KRAS wt patients.
Figure 3
Figure 3
(A) Four-gene classification model for prediction of cetuximab benefit measured by disease control rate in KRAS wt patients. (B) Four-gene classification model for prediction of cetuximab benefit measured by objective response rate in KRAS wt patients. (C) Performance measures of two patient classifiers (disease control endpoint). (D) Performance measures of two patient classifiers (objective response endpoint). The four-gene classifier includes DUSP6, SLC23A2 and the average of EREG and AREG. EREG and AREG were averaged because they tightly co-express in these colon cancer specimens (R2=0.83).
Figure 4
Figure 4
Progression-free survival in patients classified using KRAS and a four-gene classifier.
See this image and copyright information in PMC

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