Abstract
Malignant mesothelioma has a mean overall survival of around 1 year and lung adenocarcinoma with pleural spread has a mean overall survival of around 5 months. Both diseases cause fluid accumulation in the pleura, which is drained to alleviate associated symptoms such as shortness of breath. This fluid oft contains exfoliated tumor cells.
All chemotherapy regiments in use against malignant mesothelioma and lung adenocarcinoma with pleural spread have an objective response rate of 30-40%, and they all increase mean overall survival with a mere 3 months. The choice of drug combinations in the chemotherapy regiments are determined based on the statistically best drug combination. However, due to tumor heterogeneity, it is unclear whether some patients would respond better to an alternative treatment rather than the gold standard. To test this hypothesis, tumor cells were isolated from the effusions and cultured together with cytostatic drugs. After 48 or 72 h, the toxicity was measured using an automated live / dead assay, a colorimetric assay or a flow cytometer based assay and compared to an untreated control. The obtained data was then compared with patient journals, either overall survival or effect of drug treatment.
Such drug exposure assays have been performed for long, however, no drug exposure assay have seen clinical use outside of smaller studies. The work described in this thesis attempted a number of methods of improving these assays, most prominently by attempting to make the measurements tumor specific, as there is often a substantial admixture of benign inflammatory cells. Also other refinements were tested, such as increasing the concentrations of the tested drugs to above what is found in the blood of patients in order to elicit meaningful response during in vitro short drug exposure times.
The thesis concludes with a promising study, using the flowcytometer to make the readouts tumor cell specific and to show high variation. Initial data suggests this tumor specific assay indeed is able to predict patient response to given drugs.