Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display

4020 - Effects of beyond KRAS mutations on the efficacy of cetuximab plus chemotherapy for patients with unresectable colorectal liver-limited metastases (BELIEF): a retrospective biomarker analysis from a Chinese trial


08 Oct 2016


Poster Display


Jianmin Xu


Annals of Oncology (2016) 27 (6): 149-206. 10.1093/annonc/mdw370


J. Xu1, L. Ren1, Y. Wei1, P. Zheng1, L. Ye2, Q. Feng1, Q. Lin1, D. Zhu1, W. Chang1, M. Ji1

Author affiliations

  • 1 Department Of General Surgery, Zhongshan Hospital, Fudan University, 200032 - Shanghai/CN
  • 2 Department Of Onological Surgery, 1st Affiliated Hospital of Wenzhou Medical College, 325000 - Wenzhou/CN


Abstract 4020


To identify predictive biomarkers for the efficacy of cetuximab.


247 patients were recruited, including ITT patients of previous RCT (NCT01564810) (primary group) and a following cohort with same inclusion criteria of previous RCT (validation group). The DNA samples were sequenced for single nucleotide polymorphisms (SNPs) of biomarkers including the well-known "new" RAS (KRAS exons 3 and 4; NRAS exons 2, 3 and 4) and other 108 genes, using Ion Torrent Personal Genome Machine (PGM) sequencing. A 5% cutoff value was used to determine mutations.


In primary group, interaction tests between biomarker status and treatment effect were performed for objective response rate, progression-free survival and overall survival. Nine potential predictive biomarkers were identified, including FGFR3, GNAS, FLT3, NOTCH1, RBMXL3, ERBB2, MDN1, PTCH1 and LY6G6D. With RAS wild-type patients in primary group, we built a predictive model for the objective response to cetuximab plus chemotherapy with Logistic regression, employing 9 identified biomarkers (wild-type vs. mutant) and treatment (cetuximab plus chemotherapy vs. chemotherapy) as variables. Our predictive model classified patients in primary group very well (AUC = 0.81, 95%CI 0.72-0.90, P 


Apart from RAS mutations, several new biomarkers were firstly correlated with efficacy of cetuximab. and our predictive model including these biomarkers were useful to further tailor the administration of cetuximab, but need further validation.

Clinical trial identification


Legal entity responsible for the study

Zhongshan Hospital, Fudan University


Merck KGaA


All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings