262MO - Multi-omics signature for identification of RAS wild-type colorectal cancer liver metastases sensitive to anti-EGFR therapy

Background

There are nearly half patients with Ras wild-type metastatic colorectal cancer (mCRC) do not response to Anti-EGFR therapy. Identification of patients who are sensitive to anti-EGFR therapy may increase the response rate and reduce the adverse effect. Therefore, there is a pressing need for predicting the efficacy and the clinical benefit in RAS wild type patients. In this study, we aimed to develop and validate a multi-omics deep learning model to predict cetuximab efficacy in RAS wild type mCRC patients.

Methods

In this study, we retrospectively analyzed 213 Ras wild type mCRC patients. Patients in the Arm A (FOLFOX + cetuximab) of CHINESE study (J Clin Oncol 2013, NCT01564810) make up the training set and patients in CHINESE follow-up study (PMID: 30305811) make up the validation set. External multi-omics testing set was derived from an independent cohort and the Arm B (FOLFOX) of the CHINESE study. Based on the deep learning framework Pytorch, we first built the radiomic and genetic signature. Next, we passed the CT images and gene data into the trained ResNet18 and Random Forest and then we sum the output probabilities of two models with a weight of 3:7 to obtain the classification probability of the fusion model.

Results

The signature (area under the ROC curve) successfully predict sensitivity to anti-EGFR therapy (The radiomic signature: 0.63; the genetic signature: 0.72; the fusion signature: 0.81) but failed with chemotherapy (The fusion signature: 0.55). In cetuximab-containing sets, the fusion signature outperformed existing biomarkers for detection of treatment sensitivity and was strongly associated with progression free survival (P<.005).

Conclusions

The multi-omic signature can serve as an intermediate surrogate marker of anti-EGFR treatment sensitivity and survival. The signature outperformed known biomarkers in providing an early prediction of treatment sensitivity and could be used to Ras wild type mCRC treatment decisions.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.