Molecular profiling of lung cancer

• Main Author: Richards, Elizabeth
• Other Authors: Moffatt, Miriam; Cookson, William; Popat, Sanjay
• Published: Imperial College London 2013
• Subjects: 610
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.656449

Cisplatin is a first line chemotherapeutic agent for lung cancer however, although patients may respond to therapy, resistance often develops with tumour recurrence and disease progression. Somatic alterations in the tumour may alter therapeutic responses. Consequently a model of cisplatin resistance in lung cancer derived A549 cells has been created to examine the genomic changes that occur as chemo-resistance develops. Drug resistance was induced in A549 cells through multiple rounds of cisplatin dosage and recovery over two different time courses. The concentration of cisplatin required to inhibit growth (inhibitory concentration [IC] value) was calculated at each round and cycles were continued until the IC value increased at least four-fold. Cells were harvested and total RNA extracted for whole transcriptome microarray analysis. Data was analysed using R statistics and associated packages, Affy, Limma, Mfuzz and WGCNA. A five-fold increase in IC value was generated over successive doses in both regimes, accompanied by highly significant changes in gene expression. To explore these changes, temporal expression clustering and extensive network analyses were performed across the rounds of cisplatin dosing, as well as an untreated cell culture time course that acted as a comparison to the two treated regimes. The results gathered from this robust model suggest that differences in dose and frequency of chemotherapy may affect genomic changes at specific loci that confer cisplatin resistance. Interesting and relevant pathways and genes have been discovered. In combination with analyses on a small patient cohort, these results have provided insights into the mechanism of cisplatin resistance and have highlighted new clinical biomarkers of potential use in prognosis of patients undergoing cancer treatment.