Identification of Novel Protein Expression Changes Following Cisplatin Treatment and Application to Combination Therapy.

Determining the effect of chemotherapeutic treatment on changes in protein expression can provide important targets for overcoming resistance. Due to challenges in simultaneously measuring large numbers of proteins, a paucity of data exists on global changes. To overcome these challenges, we utilized microwestern arrays that allowed us to measure the abundance and modification state of hundreds of cell signaling and transcription factor proteins in cells following drug exposure. HapMap lymphoblastoid cell lines (LCLs) were exposed to cisplatin, a chemotherapeutic agent commonly used to treat testicular, head and neck, non-small cell lung, and gynecological cancers. We evaluated the expression of 259 proteins following 2, 6, and 12 h of cisplatin treatment in two LCLs with discordant sensitivity to cisplatin. Of these 259 proteins, 66 displayed significantly different protein expression changes (p < 0.05). Fifteen of these proteins were evaluated in a second pair of LCLs with discordant sensitivities to cisplatin; six demonstrated significant differences in expression. We then evaluated a subset of 63 proteins in a second set of LCLs with discordant sensitivity, and 40% of those that were significant in the first pair were also significant in the second part with concordant directionality (p < 0.05). We functionally validated one of the top proteins identified, PDK1, and demonstrated a synergistic relationship between cisplatin and a PDK1 inhibitor in multiple lung cancer lines. This study highlights the potential for identifying novel targets through an understanding of cellular changes in protein expression and modification following drug treatments.

Identification and validation of genetic variants that influence transcription factor and cell signaling protein levels.

Many genetic variants associated with human disease have been found to be associated with alterations in mRNA expression. Although it is commonly assumed that mRNA expression changes will lead to consequent changes in protein levels, methodological challenges have limited our ability to test the degree to which this assumption holds true. Here, we further developed the micro-western array approach and globally examined relationships between human genetic variation and cellular protein levels. We collected more than 250,000 protein level measurements comprising 441 transcription factor and signaling protein isoforms across 68 Yoruba (YRI) HapMap lymphoblastoid cell lines (LCLs) and identified 12 cis and 160 trans protein level QTLs (pQTLs) at a false discovery rate (FDR) of 20%. Whereas up to two thirds of cis mRNA expression QTLs (eQTLs) were also pQTLs, many pQTLs were not associated with mRNA expression. Notably, we replicated and functionally validated a trans pQTL relationship between the KARS lysyl-tRNA synthetase locus and levels of the DIDO1 protein. This study demonstrates proof of concept in applying an antibody-based microarray approach to iteratively measure the levels of human proteins and relate these levels to human genome variation and other genomic data sets. Our results suggest that protein-based mechanisms might functionally buffer genetic alterations that influence mRNA expression levels and that pQTLs might contribute phenotypic diversity to a human population independently of influences on mRNA expression.