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Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia
Linköping University, Department of Medical and Health Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences.
Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden / School of Engineering and Natural Sciences, University of Iceland, Reykjavík, Iceland.
Linköping University, Department of Medical and Health Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences.
Science for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden.
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2019 (English)In: The Pharmacogenomics Journal, ISSN 1470-269X, E-ISSN 1473-1150Article in journal (Refereed) Epub ahead of print
Abstract [en]

Chemotherapy-induced myelosuppression, including thrombocytopenia, is a recurrent problem during cancer treatments that may require dose alterations or cessations that could affect the antitumor effect of the treatment. To identify genetic markers associated with treatment-induced thrombocytopenia, we whole-exome sequenced 215 non-small cell lung cancer patients homogeneously treated with gemcitabine/carboplatin. The decrease in platelets (defined as nadir/baseline) was used to assess treatment-induced thrombocytopenia. Association between germline genetic variants and thrombocytopenia was analyzed at single-nucleotide variant (SNV) (based on the optimal false discovery rate, the severity of predicted consequence, and effect), gene, and pathway levels. These analyses identified 130 SNVs/INDELs and 25 genes associated with thrombocytopenia (P-value < 0.002). Twenty-three SNVs were validated in an independent genome-wide association study (GWAS). The top associations include rs34491125 in JMJD1C (P-value = 9.07 × 10−5), the validated variants rs10491684 in DOCK8 (P-value = 1.95 × 10−4), rs6118 in SERPINA5 (P-value = 5.83 × 10−4), and rs5877 in SERPINC1 (P-value = 1.07 × 10−3), and the genes CAPZA2 (P-value = 4.03 × 10−4) and SERPINC1 (P-value = 1.55 × 10−3). The SNVs in the top-scoring pathway “Factors involved in megakaryocyte development and platelet production” (P-value = 3.34 × 10−4) were used to construct weighted genetic risk score (wGRS) and logistic regression models that predict thrombocytopenia. The wGRS predict which patients are at high or low toxicity risk levels, for CTCAE (odds ratio (OR) = 22.35, P-value = 1.55 × 10−8), and decrease (OR = 66.82, P-value = 5.92 × 10−9). The logistic regression models predict CTCAE grades 3–4 (receiver operator characteristics (ROC) area under the curve (AUC) = 0.79), and large decrease (ROC AUC = 0.86). We identified and validated genetic variations within hematopoiesis-related pathways that provide a solid foundation for future studies using genetic markers for predicting chemotherapy-induced thrombocytopenia and personalizing treatments.

Place, publisher, year, edition, pages
2019.
National Category
Cancer and Oncology Medical Genetics Pharmacology and Toxicology Medicinal Chemistry
Identifiers
URN: urn:nbn:se:liu:diva-162137DOI: 10.1038/s41397-019-0099-8OAI: oai:DiVA.org:liu-162137DiVA, id: diva2:1371541
Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2019-11-20Bibliographically approved
In thesis
1. Pharmacogenetic biomarkers for chemotherapy-induced adverse drug reactions
Open this publication in new window or tab >>Pharmacogenetic biomarkers for chemotherapy-induced adverse drug reactions
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cancer is a serious disease expected to be the world-leading cause of death in the 21st century. The use of harsh chemotherapies is motivated and accepted but, unfortunately, is often accompanied by severe toxicity and adverse drug reactions (ADRs). These occur because the classical chemotherapies’ common modes of action effectively kill and/or reduce the growth rate not only of tumour cells, but also of many other rapidly dividing healthy cells in the body. There are also considerable interindividual differences in ADRs, even between patients with similar cancers and disease stage treated with equal doses; some experience severe to life-threatening ADRs after one dose, leading to treatment delays, adjustments, or even discontinuation resulting in suboptimal treatment, while others remain unaffected through all treatment cycles. Being able to predict which patients are at high or low risk of ADRs, and to adjust doses accordingly before treatment, would probably decrease toxicity and patient suffering while also increasing treatment tolerability and effects. In this thesis, we have used next-generation sequencing (NGS) and bioinformatics for the prediction of myelosuppressive ADRs in lung and ovarian cancer patients treated with gemcitabine/carboplatin and paclitaxel/carboplatin.

Paper I shows that ABCB1 and CYP2C8 genotypes have small effects inadequate for stratification of paclitaxel/carboplatin toxicity. This supports the transition to whole-exome sequencing (WES) and whole-genome sequencing (WGS). Papers II and IV, respectively, use WES and WGS, and demonstrate that genetic variation in or around genes involved in blood cell regulation and proliferation, or genes differentially expressed at chemotherapy exposure, can be used in polygenic prediction models for stratification of gemcitabine/carboplatininduced myelosuppression. Paper III reassuringly shows that WES and WGS are concordant and mostly yield comparable genotypes across the exome. Paper V proves that single-cell RNA sequencing of hematopoietic stem cells is a feasible method for elucidating differential transcriptional effects induced as a response to in vitro chemotherapy treatment.

In conclusion, our results supports the transition to genome-wide approaches using WES, WGS, and RNA sequencing to establish polygenic models that combine effects of multiple pharmacogenetic biomarkers for predicting chemotherapy-induced ADRs. This approach could be applied to improve risk stratification and our understanding of toxicity and ADRs related to other drugs and diseases. We hope that our myelosuppression prediction models can be refined and validated to facilitate personalized treatments, leading to increased patient wellbeing and quality of life.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 74
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1700
National Category
Cancer and Oncology Pharmacology and Toxicology Medicinal Chemistry Medical Genetics
Identifiers
urn:nbn:se:liu:diva-162138 (URN)10.3384/diss.diva-162138 (DOI)9789176850046 (ISBN)
Public defence
2019-12-20, Hasselquistsalen, Campus US, Linköping, 09:15 (Swedish)
Opponent
Supervisors
Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2019-12-12Bibliographically approved

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Björn, NiclasSvedberg, AnnaGréen, Henrik

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