Use of Germline Genetic Variability for Prediction of Chemoresistance and Prognosis of Breast Cancer Patients

. 2018 Dec 12 ; 10 (12) : . [epub] 20181212

Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid30545124

Grantová podpora
15-25618A Agentura Pro Zdravotnický Výzkum České Republiky
1776218 Grantová Agentura, Univerzita Karlova

The aim of our study was to set up a panel for targeted sequencing of chemoresistance genes and the main transcription factors driving their expression and to evaluate their predictive and prognostic value in breast cancer patients. Coding and regulatory regions of 509 genes, selected from PharmGKB and Phenopedia, were sequenced using massive parallel sequencing in blood DNA from 105 breast cancer patients in the testing phase. In total, 18,245 variants were identified of which 2565 were novel variants (without rs number in dbSNP build 150) in the testing phase. Variants with major allele frequency over 0.05 were further prioritized for validation phase based on a newly developed decision tree. Using emerging in silico tools and pharmacogenomic databases for functional predictions and associations with response to cytotoxic therapy or disease-free survival of patients, 55 putative variants were identified and used for validation in 805 patients with clinical follow up using KASPTM technology. In conclusion, associations of rs2227291, rs2293194, and rs4376673 (located in ATP7A, KCNAB1, and DFFB genes, respectively) with response to neoadjuvant cytotoxic therapy and rs1801160 in DPYD with disease-free survival of patients treated with cytotoxic drugs were validated and should be further functionally characterized.

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Siegel R.L., Miller K.D., Jemal A. Cancer statistics, 2016. CA Cancer J. Clin. 2016;66:7–30. doi: 10.3322/caac.21332. PubMed DOI

Videira M., Reis R.L., Brito M.A. Deconstructing breast cancer cell biology and the mechanisms of multidrug resistance. Biochim. Biophys. Acta. 2014;1846:312–325. doi: 10.1016/j.bbcan.2014.07.011. PubMed DOI

Soucek P. Xenobiotics. In: Schwab M., editor. Encyclopedia of Cancer. 3rd ed. Springer Verlag; Berlin, Germany: 2015.

De Iuliis F., Salerno G., Taglieri L., Scarpa S. Are pharmacogenomic biomarkers an effective tool to predict taxane toxicity and outcome in breast cancer patients? Literature review. Cancer Chemother. Pharmacol. 2015;76:679–690. doi: 10.1007/s00280-015-2818-4. PubMed DOI

Szakács G., Paterson J.K., Ludwig J.A., Booth-Genthe C., Gottesman M.M. Targeting multidrug resistance in cancer. Nat. Rev. Drug Discov. 2006;5:219–234. doi: 10.1038/nrd1984. PubMed DOI

El-Gebali S., Bentz S., Hediger M., Anderle P. Solute carriers (SLCs) in cancer. Mol. Aspects Med. 2013;34:719–734. doi: 10.1016/j.mam.2012.12.007. PubMed DOI

Lemstrová R., Souček P., Melichar B., Mohelnikova-Duchonova B. Role of solute carrier transporters in pancreatic cancer: A review. Pharmacogenomics. 2014;15:1133–1145. doi: 10.2217/pgs.14.80. PubMed DOI

Mohelnikova-Duchonova B., Melichar B., Soucek P. FOLFOX/FOLFIRI pharmacogenetics: The call for a personalized approach in colorectal cancer therapy. World J. Gastroenterol. 2014;20:10316–10330. doi: 10.3748/wjg.v20.i30.10316. PubMed DOI PMC

Hlavata I., Mohelnikova-Duchonova B., Vaclavikova R., Liska V., Pitule P., Novak P., Bruha J., Vycital O., Holubec L., Treska V., et al. The role of ABC transporters in progression and clinical outcome of colorectal cancer. Mutagenesis. 2012;27:187–196. doi: 10.1093/mutage/ger075. PubMed DOI

Hlaváč V., Brynychová V., Václavíková R., Ehrlichová M., Vrána D., Pecha V., Koževnikovová R., Trnková M., Gatěk J., Kopperová D., et al. The expression profile of ATP-binding cassette transporter genes in breast carcinoma. Pharmacogenomics. 2013;14:515–529. doi: 10.2217/pgs.13.26. PubMed DOI

Mohelnikova-Duchonova B., Brynychova V., Hlavac V., Kocik M., Oliverius M., Hlavsa J., Honsova E., Mazanec J., Kala Z., Melichar B., et al. The association between the expression of solute carrier transporters and the prognosis of pancreatic cancer. Cancer Chemother. Pharmacol. 2013;72:669–682. doi: 10.1007/s00280-013-2246-2. PubMed DOI

Mohelnikova-Duchonova B., Brynychova V., Oliverius M., Honsova E., Kala Z., Muckova K., Soucek P. Differences in transcript levels of ABC transporters between pancreatic adenocarcinoma and nonneoplastic tissues. Pancreas. 2013;42:707–716. doi: 10.1097/MPA.0b013e318279b861. PubMed DOI

Elsnerova K., Mohelnikova-Duchonova B., Cerovska E., Ehrlichova M., Gut I., Rob L., Skapa P., Hruda M., Bartakova A., Bouda J., et al. Gene expression of membrane transporters: Importance for prognosis and progression of ovarian carcinoma. Oncol. Rep. 2016;35:2159–2170. doi: 10.3892/or.2016.4599. PubMed DOI

Chang M.T., Asthana S., Gao S.P., Lee B.H., Chapman J.S., Kandoth C., Gao J., Socci N.D., Solit D.B., Olshen A.B., et al. Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity. Nat. Biotechnol. 2016;34:155–163. doi: 10.1038/nbt.3391. PubMed DOI PMC

Liang X., Vacher S., Boulai A., Bernard V., Baulande S., Bohec M., Bièche I., Lerebours F., Callens C. Targeted next-generation sequencing identifies clinically relevant somatic mutations in a large cohort of inflammatory breast cancer. Breast Cancer Res. 2018;20:88. doi: 10.1186/s13058-018-1007-x. PubMed DOI PMC

Ingelman-Sundberg M. Genetic polymorphisms of cytochrome P450 2D6 (CYP2D6): Clinical consequences, evolutionary aspects and functional diversity. Pharmacogenomics J. 2005;5:6–13. doi: 10.1038/sj.tpj.6500285. PubMed DOI

Barretina J., Caponigro G., Stransky N., Venkatesan K., Margolin A.A., Kim S., Wilson C.J., Lehár J., Kryukov G.V., Sonkin D., et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483:603–607. doi: 10.1038/nature11003. PubMed DOI PMC

Iorio F., Knijnenburg T.A., Vis D.J., Bignell G.R., Menden M.P., Schubert M., Aben N., Gonçalves E., Barthorpe S., Lightfoot H., et al. A Landscape of Pharmacogenomic Interactions in Cancer. Cell. 2016;166:740–754. doi: 10.1016/j.cell.2016.06.017. PubMed DOI PMC

Menden M.P., Casale F.P., Stephan J., Bignell G.R., Iorio F., McDermott U., Garnett M.J., Saez-Rodriguez J., Stegle O. The germline genetic component of drug sensitivity in cancer cell lines. Nat. Commun. 2018;9:3385. doi: 10.1038/s41467-018-05811-3. PubMed DOI PMC

Wang L., Ingle J., Weinshilboum R. Pharmacogenomic Discovery to Function and Mechanism: Breast Cancer as a Case Study. Clin. Pharmacol. Ther. 2018;103:243–252. doi: 10.1002/cpt.915. PubMed DOI PMC

Kozyra M., Ingelman-Sundberg M., Lauschke V.M. Rare genetic variants in cellular transporters, metabolic enzymes, and nuclear receptors can be important determinants of interindividual differences in drug response. Genet. Med. 2017;19:20–29. doi: 10.1038/gim.2016.33. PubMed DOI

Ritzel M.W., Ng A.M., Yao S.Y., Graham K., Loewen S.K., Smith K.M., Ritzel R.G., Mowles D.A., Carpenter P., Chen X.Z., et al. Molecular identification and characterization of novel human and mouse concentrative Na+-nucleoside cotransporter proteins (hCNT3 and mCNT3) broadly selective for purine and pyrimidine nucleosides (system cib) J. Biol. Chem. 2001;276:2914–2927. doi: 10.1074/jbc.M007746200. PubMed DOI

Khatri A., Williams B.W., Fisher J., Brundage R.C., Gurvich V.J., Lis L.G., Skubitz K.M., Dudek A.Z., Greeno E.W., Kratzke R.A., et al. SLC28A3 genotype and gemcitabine rate of infusion affect dFdCTP metabolite disposition in patients with solid tumours. Br. J. Cancer. 2014;110:304–312. doi: 10.1038/bjc.2013.738. PubMed DOI PMC

Visscher H., Ross C.J., Rassekh S.R., Sandor G.S., Caron H.N., van Dalen E.C., Kremer L.C., van der Pal H.J., Rogers P.C., Rieder M.J., et al. Validation of variants in SLC28A3 and UGT1A6 as genetic markers predictive of anthracycline-induced cardiotoxicity in children. Pediatr. Blood Cancer. 2013;60:1375–1381. doi: 10.1002/pbc.24505. PubMed DOI

Hertz D.L., Caram M.V., Kidwell K.M., Thibert J.N., Gersch C., Seewald N.J., Smerage J., Rubenfire M., Henry N.L., Cooney K.A., et al. Evidence for association of SNPs in ABCB1 and CBR3, but not RAC2, NCF4, SLC28A3 or TOP2B, with chronic cardiotoxicity in a cohort of breast cancer patients treated with anthracyclines. Pharmacogenomics. 2016;17:231–240. doi: 10.2217/pgs.15.162. PubMed DOI PMC

Park Y.H., Jung K.H., Im S.A., Sohn J.H., Ro J., Ahn J.H., Kim S.B., Nam B.H., Oh D.Y., Han S.W., et al. Phase III, multicenter, randomized trial of maintenance chemotherapy versus observation in patients with metastatic breast cancer after achieving disease control with six cycles of gemcitabine plus paclitaxel as first-line chemotherapy: KCSG-BR07-02. J. Clin. Oncol. 2013;31:1732–1739. doi: 10.1200/JCO.2012.45.2490. PubMed DOI

Okazaki T., Javle M., Tanaka M., Abbruzzese J.L., Li D. Single nucleotide polymorphisms of gemcitabine metabolic genes and pancreatic cancer survival and drug toxicity. Clin. Cancer Res. 2010;16:320–329. doi: 10.1158/1078-0432.CCR-09-1555. PubMed DOI PMC

Mei S., Li X., Gong X., Yang L., Zhou H., Liu Y., Zhou A., Zhu L., Zhang X., Zhao Z. LC-MS/MS Analysis of Erythrocyte Thiopurine Nucleotides and Their Association with Genetic Variants in Patients with Neuromyelitis Optica Spectrum Disorders Taking Azathioprine. Ther. Drug Monit. 2017;39:5–12. doi: 10.1097/FTD.0000000000000362. PubMed DOI

Van Kuilenburg A.B. Dihydropyrimidine dehydrogenase and the efficacy and toxicity of 5-fluorouracil. Eur. J. Cancer. 2004;40:939–950. doi: 10.1016/j.ejca.2003.12.004. PubMed DOI

Ruzzo A., Graziano F., Galli F., Rulli E., Lonardi S., Ronzoni M., Massidda B., Zagonel V., Pella N., Mucciarini C., et al. Dihydropyrimidine dehydrogenase pharmacogenetics for predicting fluoropyrimidine-related toxicity in the randomised, phase III adjuvant TOSCA trial in high-risk colon cancer patients. Br. J. Cancer. 2017;117:1269–1277. doi: 10.1038/bjc.2017.289. PubMed DOI PMC

Henricks L.M., Lunenburg C.A.T.C., de Man F.M., Meulendijks D., Frederix G.W.J., Kienhuis E., Creemers G.J., Baars A., Dezentjé V.O., Imholz A.L.T., et al. DPYD genotype-guided dose individualisation of fluoropyrimidine therapy in patients with cancer: A prospective safety analysis. Lancet Oncol. 2018 doi: 10.1016/S1470-2045(18)30686-7. PubMed DOI

Li T., Peng J., Zeng F., Zhang K., Liu J., Li X., Ouyang Q., Wang G., Wang L., Liu Z., et al. Association between polymorphisms in CTR1, CTR2, ATP7A, and ATP7B and platinum resistance in epithelial ovarian cancer. Int. J. Clin. Pharmacol. Ther. 2017;55:774–780. doi: 10.5414/CP202907. PubMed DOI

Maurano M.T., Humbert R., Rynes E., Thurman R.E., Haugen E., Wang H., Reynolds A.P., Sandstrom R., Qu H., Brody J., et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337:1190–1195. doi: 10.1126/science.1222794. PubMed DOI PMC

Hlaváč V., Brynychová V., Václavíková R., Ehrlichová M., Vrána D., Pecha V., Trnková M., Kodet R., Mrhalová M., Kubáčková K., et al. The role of cytochromes p450 and aldo-keto reductases in prognosis of breast carcinoma patients. Medicine. 2014;93:e255. doi: 10.1097/MD.0000000000000255. PubMed DOI PMC

Bagheri F., Safarian S., Eslaminejad M.B., Sheibani N. Sensitization of breast cancer cells to doxorubicin via stable cell line generation and overexpression of DFF40. Biochem. Cell Biol. 2015;93:604–610. doi: 10.1139/bcb-2015-0007. PubMed DOI PMC

Bagheri F., Safarian S., Eslaminejad M.B., Sheibani N. Stable overexpression of DNA fragmentation factor in T-47D cells: Sensitization of breast cancer cells to apoptosis in response to acetazolamide and sulfabenzamide. Mol. Biol. Rep. 2014;41:7387–7394. doi: 10.1007/s11033-014-3626-3. PubMed DOI PMC

Fadista J., Oskolkov N., Hansson O., Groop L. LoFtool: A gene intolerance score based on loss-of-function variants in 60 706 individuals. Bioinformatics. 2017;33:471–474. doi: 10.1093/bioinformatics/btv602. PubMed DOI

McDonagh E.M., Whirl-Carrillo M., Garten Y., Altman R.B., Klein T.E. From pharmacogenomic knowledge acquisition to clinical applications: The PharmGKB as a clinical pharmacogenomic biomarker resource. Biomark. Med. 2011;5:795–806. doi: 10.2217/bmm.11.94. PubMed DOI PMC

Smirnov P., Kofia V., Maru A., Freeman M., Ho C., El-Hachem N., Adam G.A., Ba-Alawi W., Safikhani Z., Haibe-Kains B. PharmacoDB: An integrative database for mining in vitro anticancer drug screening studies. Nucleic Acids Res. 2018;46:D994–D1002. doi: 10.1093/nar/gkx911. PubMed DOI PMC

Ingelman-Sundberg M., Mkrtchian S., Zhou Y., Lauschke V.M. Integrating rare genetic variants into pharmacogenetic drug response predictions. Hum. Genom. 2018;12:26. doi: 10.1186/s40246-018-0157-3. PubMed DOI PMC

Gerek N.Z., Liu L., Gerold K., Biparva P., Thomas E.D., Kumar S. Evolutionary Diagnosis of non-synonymous variants involved in differential drug response. BMC Med. Genom. 2015;8(Suppl. 1):S6. doi: 10.1186/1755-8794-8-S1-S6. PubMed DOI PMC

Ghosh R., Oak N., Plon S.E. Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines. Genome Biol. 2017;18:225. doi: 10.1186/s13059-017-1353-5. PubMed DOI PMC

Vaclavikova R., Ehrlichova M., Hlavata I., Pecha V., Kozevnikovova R., Trnkova M., Adamek J., Edvardsen H., Kristensen V.N., Gut I., et al. Detection of frequent ABCB1 polymorphisms by high-resolution melting curve analysis and their effect on breast carcinoma prognosis. Clin. Chem. Lab. Med. 2012;50:1999–2007. doi: 10.1515/cclm-2012-0103. PubMed DOI

Therasse P., Arbuck S.G., Eisenhauer E.A., Wanders J., Kaplan R.S., Rubinstein L., Verweij J., Van Glabbeke M., van Oosterom A.T., Christian M.C., et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl. Cancer Inst. 2000;92:205–216. doi: 10.1093/jnci/92.3.205. PubMed DOI

Topić E., Gluhak J. Isolation of restrictible DNA. Eur. J. Clin. Chem. Clin. Biochem. 1991;29:327–330. PubMed

Soucek P., Hlavac V., Elsnerova K., Vaclavikova R., Kozevnikovova R., Raus K. Whole exome sequencing analysis of ABCC8 and ABCD2 genes associating with clinical course of breast carcinoma. Physiol. Res. 2015;64(Suppl. 4):S549–S557. PubMed

Lhota F., Zemankova P., Kleiblova P., Soukupova J., Vocka M., Stranecky V., Janatova M., Hartmannova H., Hodanova K., Kmoch S., et al. Hereditary truncating mutations of DNA repair and other genes in BRCA1/BRCA2/PALB2-negatively tested breast cancer patients. Clin. Genet. 2016;90:324–333. doi: 10.1111/cge.12748. PubMed DOI

Li H. Toward better understanding of artifacts in variant calling from high-coverage samples. Bioinformatics. 2014;30:2843–2851. doi: 10.1093/bioinformatics/btu356. PubMed DOI PMC

Van der Auwera G.A., Carneiro M.O., Hartl C., Poplin R., Del Angel G., Levy-Moonshine A., Jordan T., Shakir K., Roazen D., Thibault J., et al. From FastQ data to high confidence variant calls: The Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinform. 2013;43:11–33. PubMed PMC

Wang K., Li M., Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164. doi: 10.1093/nar/gkq603. PubMed DOI PMC

McLaren W., Gil L., Hunt S.E., Riat H.S., Ritchie G.R., Thormann A., Flicek P., Cunningham F. The Ensembl Variant Effect Predictor. Genome Biol. 2016;17:122. doi: 10.1186/s13059-016-0974-4. PubMed DOI PMC

Dong C., Wei P., Jian X., Gibbs R., Boerwinkle E., Wang K., Liu X. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. Hum. Mol. Genet. 2015;24:2125–2137. doi: 10.1093/hmg/ddu733. PubMed DOI PMC

Grimm D.G., Azencott C.A., Aicheler F., Gieraths U., MacArthur D.G., Samocha K.E., Cooper D.N., Stenson P.D., Daly M.J., Smoller J.W., et al. The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity. Hum. Mutat. 2015;36:513–523. doi: 10.1002/humu.22768. PubMed DOI PMC

Boyle A.P., Hong E.L., Hariharan M., Cheng Y., Schaub M.A., Kasowski M., Karczewski K.J., Park J., Hitz B.C., Weng S., et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–1797. doi: 10.1101/gr.137323.112. PubMed DOI PMC

Bodea C.A., Mitchell A.A., Bloemendal A., Day-Williams A.G., Runz H., Sunyaev S.R. PINES: Phenotype-informed tissue weighting improves prediction of pathogenic noncoding variants. Genome Biol. 2018;19:173. doi: 10.1186/s13059-018-1546-6. PubMed DOI PMC

Huang L.H., He Q.S., Liu K., Cheng J., Zhong M.D., Chen L.S., Yao L.X., Ji Z.L. ADReCS-Target: Target profiles for aiding drug safety research and application. Nucleic Acids Res. 2018;46:D911–D917. doi: 10.1093/nar/gkx899. PubMed DOI PMC

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