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Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy.

Stark AL, Hause RJ, Gorsic LK, Antao NN, Wong SS, Chung SH, Gill DF, Im HK, Myers JL, White KP, Jones RB, Dolan ME - PLoS Genet. (2014)

Bottom Line: Annotating and interpreting the results of genome-wide association studies (GWAS) remains challenging.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).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.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, The University of Chicago, Chicago, Illinois, United States of America.

ABSTRACT
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.

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Protein levels regressed against four cytotoxicity phenotypes using fixed effect or mixed effect models representing the three biological replicates.We analyzed 441 protein levels against 5 µM cisplatin induced apoptosis and cytotoxicity and 12.5 nM paclitaxel apoptosis and cytotoxicity using both fixed effect and mixed effect modeling (a). The Y-axis represents the total number of protein-drug phenotype (A, apoptosis and C, cytotoxicity) correlations (p<0.05) using fixed effect (medium grey) or mixed effect (light grey) or those that showed a correlation for both methods (dark grey). Five micromolar cisplatin induced caspase activity correlated with WHSC1 protein levels demonstrates strong association (p = 0.009) using the fixed effect, whereas the individual thaw association reveals no association from the third thaw, resulting in a greater than p>0.05 MEM result (b). Five micromolar cisplatin-induced caspase activity correlated with STAT3A (∼90 kDa) protein levels across three thaws ranging had p<0.05 ranging from 0.02 to 1.6×10−6 and a mixed effect p-value of 1.55×10−7 (c).
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pgen-1004192-g001: Protein levels regressed against four cytotoxicity phenotypes using fixed effect or mixed effect models representing the three biological replicates.We analyzed 441 protein levels against 5 µM cisplatin induced apoptosis and cytotoxicity and 12.5 nM paclitaxel apoptosis and cytotoxicity using both fixed effect and mixed effect modeling (a). The Y-axis represents the total number of protein-drug phenotype (A, apoptosis and C, cytotoxicity) correlations (p<0.05) using fixed effect (medium grey) or mixed effect (light grey) or those that showed a correlation for both methods (dark grey). Five micromolar cisplatin induced caspase activity correlated with WHSC1 protein levels demonstrates strong association (p = 0.009) using the fixed effect, whereas the individual thaw association reveals no association from the third thaw, resulting in a greater than p>0.05 MEM result (b). Five micromolar cisplatin-induced caspase activity correlated with STAT3A (∼90 kDa) protein levels across three thaws ranging had p<0.05 ranging from 0.02 to 1.6×10−6 and a mixed effect p-value of 1.55×10−7 (c).

Mentions: Prior to our global analysis, a pilot study consisting of three independent biological replicates of six cell lines demonstrated significant variation not only among protein levels from different individuals, but also among cells thawed and propagated independently from the same individual. Based on a significant thaw effect explaining 3.75% of global protein expression variation (p = 0.01, F test), we measured baseline, steady-state protein levels from three independent thaws (thawed simultaneously) from each of 68 unrelated YRI LCLs to have a more accurate estimate of inter-individual variation in protein expression. These measurements were evaluated with both fixed effect (by averaging the three thaws) and mixed effect (by incorporating a random thaw effect per individual) models. Mixed effect modeling (MEM) allowed us to gain additional power from multiple measurements compared with simply averaging across the biological replicates in a linear model (Figure 1a). Relationships identified by fixed effect that had conflicting trends (i.e. positive and negative associations) across biological replicates were more likely to be false positives (Figure 1b) than the observations that were reproducible by MEM (across biological replicates) (Figure 1c); we therefore considered the MEM to be the more robust approach and used this method for all subsequent estimates of protein-drug associations.


Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy.

Stark AL, Hause RJ, Gorsic LK, Antao NN, Wong SS, Chung SH, Gill DF, Im HK, Myers JL, White KP, Jones RB, Dolan ME - PLoS Genet. (2014)

Protein levels regressed against four cytotoxicity phenotypes using fixed effect or mixed effect models representing the three biological replicates.We analyzed 441 protein levels against 5 µM cisplatin induced apoptosis and cytotoxicity and 12.5 nM paclitaxel apoptosis and cytotoxicity using both fixed effect and mixed effect modeling (a). The Y-axis represents the total number of protein-drug phenotype (A, apoptosis and C, cytotoxicity) correlations (p<0.05) using fixed effect (medium grey) or mixed effect (light grey) or those that showed a correlation for both methods (dark grey). Five micromolar cisplatin induced caspase activity correlated with WHSC1 protein levels demonstrates strong association (p = 0.009) using the fixed effect, whereas the individual thaw association reveals no association from the third thaw, resulting in a greater than p>0.05 MEM result (b). Five micromolar cisplatin-induced caspase activity correlated with STAT3A (∼90 kDa) protein levels across three thaws ranging had p<0.05 ranging from 0.02 to 1.6×10−6 and a mixed effect p-value of 1.55×10−7 (c).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3974641&req=5

pgen-1004192-g001: Protein levels regressed against four cytotoxicity phenotypes using fixed effect or mixed effect models representing the three biological replicates.We analyzed 441 protein levels against 5 µM cisplatin induced apoptosis and cytotoxicity and 12.5 nM paclitaxel apoptosis and cytotoxicity using both fixed effect and mixed effect modeling (a). The Y-axis represents the total number of protein-drug phenotype (A, apoptosis and C, cytotoxicity) correlations (p<0.05) using fixed effect (medium grey) or mixed effect (light grey) or those that showed a correlation for both methods (dark grey). Five micromolar cisplatin induced caspase activity correlated with WHSC1 protein levels demonstrates strong association (p = 0.009) using the fixed effect, whereas the individual thaw association reveals no association from the third thaw, resulting in a greater than p>0.05 MEM result (b). Five micromolar cisplatin-induced caspase activity correlated with STAT3A (∼90 kDa) protein levels across three thaws ranging had p<0.05 ranging from 0.02 to 1.6×10−6 and a mixed effect p-value of 1.55×10−7 (c).
Mentions: Prior to our global analysis, a pilot study consisting of three independent biological replicates of six cell lines demonstrated significant variation not only among protein levels from different individuals, but also among cells thawed and propagated independently from the same individual. Based on a significant thaw effect explaining 3.75% of global protein expression variation (p = 0.01, F test), we measured baseline, steady-state protein levels from three independent thaws (thawed simultaneously) from each of 68 unrelated YRI LCLs to have a more accurate estimate of inter-individual variation in protein expression. These measurements were evaluated with both fixed effect (by averaging the three thaws) and mixed effect (by incorporating a random thaw effect per individual) models. Mixed effect modeling (MEM) allowed us to gain additional power from multiple measurements compared with simply averaging across the biological replicates in a linear model (Figure 1a). Relationships identified by fixed effect that had conflicting trends (i.e. positive and negative associations) across biological replicates were more likely to be false positives (Figure 1b) than the observations that were reproducible by MEM (across biological replicates) (Figure 1c); we therefore considered the MEM to be the more robust approach and used this method for all subsequent estimates of protein-drug associations.

Bottom Line: Annotating and interpreting the results of genome-wide association studies (GWAS) remains challenging.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).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.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, The University of Chicago, Chicago, Illinois, United States of America.

ABSTRACT
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.

Show MeSH