<i>EPS8</i> Inhibition Increases Cisplatin Sensitivity in Lung Cancer Cells

<div><p>Cisplatin, a commonly used chemotherapeutic, is associated with ototoxicity, renal toxicity and neurotoxicity, thus identifying means to increase the therapeutic index of cisplatin may allow for improved outcomes. A SNP (rs4343077) within <i>EPS8</i>, discovered through a genome wide association study of cisplatin-induced cytotoxicity and apoptosis in lymphoblastoid cell lines (LCLs), provided impetus to further study this gene. The purpose of this work was to evaluate the role of <i>EPS8</i> in cellular susceptibility to cisplatin in cancerous and non-cancerous cells. We used <i>EPS8</i> RNA interference to determine the effect of decreased <i>EPS8</i> expression on LCL and A549 lung cancer cell sensitivity to cisplatin. <i>EPS8</i> knockdown in LCLs resulted in a 7.9% increase in cisplatin-induced survival (<i>P</i> = 1.98×10⁻⁷) and an 8.7% decrease in apoptosis (<i>P</i> = 0.004) compared to control. In contrast, reduced <i>EPS8</i> expression in lung cancer cells resulted in a 20.6% decrease in cisplatin-induced survival (<i>P</i> = 5.08×10⁻⁵). We then investigated an <i>EPS8</i> inhibitor, mithramycin A, as a potential agent to increase the therapeutic index of cisplatin. Mithramycin A decreased <i>EPS8</i> expression in LCLs resulting in decreased cellular sensitivity to cisplatin as evidenced by lower caspase 3/7 activation following cisplatin treatment (42.7%±6.8% relative to control <i>P</i> = 0.0002). In 5 non-small-cell lung carcinoma (NSCLC) cell lines, mithramycin A also resulted in decreased <i>EPS8</i> expression. Adding mithramycin to 4 NSCLC cell lines and a bladder cancer cell line, resulted in increased sensitivity to cisplatin that was significantly more pronounced in tumor cell lines than in LCL lines (p<0.0001). An EGFR mutant NSCLC cell line (H1975) showed no significant change in sensitivity to cisplatin with the addition of mithramycin treatment. Therefore, an inhibitor of <i>EPS8</i>, such as mithramycin A, could improve cisplatin treatment by increasing sensitivity of tumor relative to normal cells.</p></div

Effect of mithramycin on sensitivity of molecularly distinct non-small-cell lung carcinoma cell lines.

<p>+ : Wild-type mt : Mutant.</p><p>*Mutation status of each cell line was provided from ATCC (Manassas, Virginia).</p

Percent of <i>EPS8</i> expression compared to scrambled control with standard error of the mean is shown for 5 LCLs tested at 5, 29 and 53 hrs after nucleofection and cell line A549 at 29 and 53 hrs after nucleofection (A).

<p>Values include 2 independent experiments with qRT-PCR run in duplicate. Cell line changes in percent survival (<i>P</i> = 1.98×10⁻⁷) and caspase 3/7 activity (<i>P</i> = 0.004) for all LCLs and A549 (<i>P</i> = 5.08×10⁻⁵) at 5 µM cisplatin due to <i>EPS8</i> knockdown are shown with standard error of the mean using 6 replicates from 2 independent experiments (B).</p

NSCLC cell lines and bladder cell line, HTB9, are shown for various concentrations of cisplatin with the presence and absence of mithramycin.

<p>Square shape represents cisplatin concentrations alone, while the triangle represents cisplatin with the addition of mithramycin (0.01 µM). Curves represent two independent experiments done in triplicate with standard error of the mean.</p

LCL caspase 3/7 activity for 5 µM cisplatin treatment alone compared to cisplatin plus 0.01 µM mithramycin.

<p>Each LCL experienced lower cisplatin-induced apoptotic activity with the added mithramycin relative to a no drug treatment control. Mithramycin treated 10859, 11830, 11840, and 12156 resulted in a 47.1, 40.8, 48.9, and 34.0% decrease from cisplatin alone, respectively. Data represents two separate experiments, each done in triplicate with standard error of the mean.</p

Protein Quantitative Trait Loci Identify Novel Candidates Modulating Cellular Response to Chemotherapy

<div><p>Annotating and interpreting the results of genome-wide association studies (GWAS) remains challenging. Assigning function to genetic variants as expression quantitative trait loci is an expanding and useful approach, but focuses exclusively on mRNA rather than protein levels. Many variants remain without annotation. To address this problem, we measured the steady state abundance of 441 human signaling and transcription factor proteins from 68 Yoruba HapMap lymphoblastoid cell lines to identify novel relationships between inter-individual protein levels, genetic variants, and sensitivity to chemotherapeutic agents. Proteins were measured using micro-western and reverse phase protein arrays from three independent cell line thaws to permit mixed effect modeling of protein biological replicates. We observed enrichment of protein quantitative trait loci (pQTLs) for cellular sensitivity to two commonly used chemotherapeutics: cisplatin and paclitaxel. We functionally validated the target protein of a genome-wide significant trans-pQTL for its relevance in paclitaxel-induced apoptosis. GWAS overlap results of drug-induced apoptosis and cytotoxicity for paclitaxel and cisplatin revealed unique SNPs associated with the pharmacologic traits (at p<0.001). Interestingly, GWAS SNPs from various regions of the genome implicated the same target protein (p<0.0001) that correlated with drug induced cytotoxicity or apoptosis (p≤0.05). Two genes were functionally validated for association with drug response using siRNA: SMC1A with cisplatin response and ZNF569 with paclitaxel response. This work allows pharmacogenomic discovery to progress from the transcriptome to the proteome and offers potential for identification of new therapeutic targets. This approach, linking targeted proteomic data to variation in pharmacologic response, can be generalized to other studies evaluating genotype-phenotype relationships and provide insight into chemotherapeutic mechanisms.</p></div

Functional validation of SMC1A and ZNF569.

<p>Three lymphoblastoid cell lines (18502, 19138, 19201) were evaluated 24 h and 48 h following 5 µM cisplatin treatment for cytotoxicity and apoptosis following nucleofection of pooled SMC1A and non-targeting control (a). Three lymphoblastoid cell lines (18502, 19138, 19201) were evaluated 24 h and 48 h following 12.5 nM paclitaxel treatment for cytotoxicity and apoptosis following nucleofection of pooled ZNF569 and non-targeting control (b).</p

Protein QTLs implicating SMC1A for cisplatin and ZNF569 for paclitaxel.

<p>Protein QTLs that also associate with either apoptosis or cytotoxicity are shown for each protein with bold indicating SMC1A and cisplatin and non-bold indicating ZNF569 and paclitaxel relationships. NA indicates that the p-value was greater than 0.001 for the drug phenotypes and 0.05 for the cis-eQTL associations.</p

Identification of a protein quantitative trait locus relevant for paclitaxel-induced apoptosis.

<p>On chromosome 16, rs6834 genotypes were correlated with DIDO1 protein levels (p = 2.66×10⁻¹⁵) (a). DIDO1 protein levels were also significantly (p = 0.01) correlated with paclitaxel-induced apoptosis (b). The three shades of grey circles indicate data from each of the three thaws. Rs6834 was not significantly correlated with paclitaxel apoptosis (p>0.05); however, the CC individuals had both the lowest mean DIDO1 levels and lowest paclitaxel-induced apoptosis levels (c). Three LCLs were nucleofected with pooled DIDO1 or nontargeting control and apoptosis was measured 24 hrs after 12.5 nM paclitaxel (d). Mixed effect modeling revealed a significant (p = 0.005) reduction in caspase activity.</p

Establishing hierarchical clustering of baseline protein levels correlated with cisplatin and paclitaxel phenotypes.

<p>Hierarchical clustering was performed on 370 protein levels (rows) for 5 µM cisplatin apoptosis and cytotoxicity and 12.5 nM paclitaxel apoptosis and cytotoxicity (columns). The correlation for each protein-drug phenotype pair is indicated with blue showing increased protein levels associating with greater sensitivity to the drug, red showing increased protein levels associating with resistance to the drug and white indicating no correlation (a). The number of significant clusters was determined by performing 1000 permutations of the column correlations, clustering them, and selecting the number of observed clusters at a tree height that significantly exceeded all tree heights from the permutations (k = 7, p<0.001). Clusters 1 (b) and 3 (c) depict proteins that are related in the same direction to all cellular phenotypes. Cluster 7 (d) depicts proteins more related strongly to drug sensitivity through cytotoxicity than apoptosis.</p