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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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Identification of a protein quantitative trait locus relevant for paclitaxel-induced apoptosis.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.
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pgen-1004192-g003: Identification of a protein quantitative trait locus relevant for paclitaxel-induced apoptosis.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.

Mentions: Upon evaluation of all proteins with a genome-wide significant pQTL, we identified one protein that was also associated with paclitaxel-induced apoptosis. The trans pQTL on chromosome 16, rs6834, was significantly correlated (p = 2.66×10−15) with death inducer-obliterator 1 (DIDO1) protein levels (Figure 3a). DIDO1 was in cluster 3 (Figure 2c), indicating that increased baseline levels conferred greater cellular sensitivity to both chemotherapeutic agents. DIDO1 protein levels were significantly correlated with paclitaxel-induced apoptosis (p = 0.01 r2 = 0.02; Figure 3b). However, the DIDO1 pQTL was not significantly associated with paclitaxel-induced apoptosis (p = 0.25, Figure 3c). Despite the lack of statistical significance (likely because of small sample size), the directionality was consistent with the observed protein relationship: cells containing two C alleles had lower levels of DIDO1 and lower paclitaxel-induced caspase 3/7 activation. DIDO1 mRNA levels were not associated with paclitaxel apoptosis (p>0.05), suggesting that this relationship was protein-specific.


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)

Identification of a protein quantitative trait locus relevant for paclitaxel-induced apoptosis.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.
© Copyright Policy
Related In: Results  -  Collection

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

pgen-1004192-g003: Identification of a protein quantitative trait locus relevant for paclitaxel-induced apoptosis.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.
Mentions: Upon evaluation of all proteins with a genome-wide significant pQTL, we identified one protein that was also associated with paclitaxel-induced apoptosis. The trans pQTL on chromosome 16, rs6834, was significantly correlated (p = 2.66×10−15) with death inducer-obliterator 1 (DIDO1) protein levels (Figure 3a). DIDO1 was in cluster 3 (Figure 2c), indicating that increased baseline levels conferred greater cellular sensitivity to both chemotherapeutic agents. DIDO1 protein levels were significantly correlated with paclitaxel-induced apoptosis (p = 0.01 r2 = 0.02; Figure 3b). However, the DIDO1 pQTL was not significantly associated with paclitaxel-induced apoptosis (p = 0.25, Figure 3c). Despite the lack of statistical significance (likely because of small sample size), the directionality was consistent with the observed protein relationship: cells containing two C alleles had lower levels of DIDO1 and lower paclitaxel-induced caspase 3/7 activation. DIDO1 mRNA levels were not associated with paclitaxel apoptosis (p>0.05), suggesting that this relationship was protein-specific.

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