Assays and screens; other

A computational model based on mutations in plasma cell-free DNA (cfDNA) could help predict the time to progression in mCRC patients treated with anti-EGFR therapies. Construction of the model involves three steps: using longitudinal cfDNA samples from a patient receiving anti-EGFR therapy to measure the frequency of common mutations in BRAF, K-Ras (KRAS), neuroblastoma Ras viral oncogene (NRAS) and protein C inactivator of coagulation factors Va and VIIIa (PROC); calculating the growth rate for each mutant population; and using that growth rate and the baseline mutation frequency to predict the time until at least one mutant population will be 72.8% greater than baseline, which is a Response Evaluation Criteria In Solid Tumors (RECIST) 1.1 criterion for clinical progression. In nine mCRC patients receiving the anti-EGFR mAbs Erbitux cetuximab or Vectibix panitumumab, the model predicted times to progression that were comparable to those calculated from longitudinal detection of blood levels of CEA or CT scans using the RECIST 1.1 criteria. Next steps could include validating the model in a larger patient cohort and testing the model in other cancers treated with anti-EGFR mAbs.

Eli Lilly and Co. and Merck KGaA market Erbitux for mCRC and head and neck cancer and have the mAb in Phase III testing for gastric cancer, Phase II testing for biliary and breast cancers and Phase I/II testing for adenocarcinoma...