A Three-dimensional Ex Vivo Viability Assay Reveals a Strong Correlation Between Response to Targeted Inhibitors and Mutation Status in Melanoma Lymph Node Metastases

Transl Oncol. 2019 Jul;12(7):951-958. doi: 10.1016/j.tranon.2019.04.001. Epub 2019 May 13.


Although clinical management of melanoma has changed considerably in recent years, intrinsic treatment resistance remains a severe problem and strategies to design personal treatment regimens are highly warranted. We have applied a three-dimensional (3D) ex vivo drug efficacy assay, exposing disaggregated cells from 38 freshly harvested melanoma lymph node metastases and 21 patient derived xenografts (PDXs) to clinical relevant drugs for 7 days, and examined its potential to evaluate therapy response. A strong association between Vemurafenib response and BRAF mutation status was achieved (P < .0001), while enhanced viability was seen in some NRAS mutated tumors. BRAF and NRAS mutated tumors responded comparably to the MEK inhibitor Cobimetinib. Based on the ex vivo results, two tumors diagnosed as BRAF wild-type by routine pathology examinations had to be re-evaluated; one was subsequently found to have a complex V600E mutation, the other a double BRAF mutation (V600E/K601 N). No BRAF inhibitor resistance mechanisms were identified, but PIK3CA and NF1 mutations were identified in two highly responsive tumors. Concordance between ex vivo drug responses using tissue from PDXs and corresponding patient tumors demonstrate that PDX models represent an indefinite source of tumor material that may allow ex vivo evaluation of numerous drugs and combinations, as well as studies of underlying molecular mechanisms. In conclusion, we have established a rapid and low cost ex vivo drug efficacy assay applicable on tumor tissue from patient biopsies. The 3D/spheroid format, limiting the influence from normal adjacent cells and allowing assessment of drug sensitivity to numerous drugs in one week, confirms its potential as a supplement to guide clinical decision, in particular in identifying non-responding patients.