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Björn, Niclas
Publications (4 of 4) Show all publications
Björn, N., Sigurgeirsson, B., Svedberg, A., Pradhananga, S., Brandén, E., Koyi, H., . . . Gréen, H. (2020). Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia. The Pharmacogenomics Journal, 20(2), 179-191
Open this publication in new window or tab >>Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia
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2020 (English)In: The Pharmacogenomics Journal, ISSN 1470-269X, E-ISSN 1473-1150, Vol. 20, no 2, p. 179-191Article in journal (Refereed) Published
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
Nature Publishing Group, 2020
National Category
Cancer and Oncology Medical Genetics Pharmacology and Toxicology Medicinal Chemistry
urn:nbn:se:liu:diva-162137 (URN)10.1038/s41397-019-0099-8 (DOI)000521728100003 ()

Funding agencies:  Swedish Cancer SocietySwedish Cancer Society; Swedish Research CouncilSwedish Research Council; ALF grants Region ostergotland; Radiumhemmet; Marcus Borgstroms stiftelse; Spanish Ministry of Economy and Competitiveness [SAF2015-64850-R]; Science for Life 

Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2020-04-10Bibliographically approved
Björn, N., Jakobsen, I., Lotfi, K. & Gréen, H. (2020). Single-Cell RNA Sequencing of Hematopoietic Stem and Progenitor Cells Treated with Gemcitabine and Carboplatin.. Genes, 11(5), Article ID E549.
Open this publication in new window or tab >>Single-Cell RNA Sequencing of Hematopoietic Stem and Progenitor Cells Treated with Gemcitabine and Carboplatin.
2020 (English)In: Genes, ISSN 2073-4425, E-ISSN 2073-4425, Vol. 11, no 5, article id E549Article in journal (Refereed) Published
Abstract [en]

Treatments that include gemcitabine and carboplatin induce dose-limiting myelosuppression. The understanding of how human bone marrow is affected on a transcriptional level leading to the development of myelosuppression is required for the implementation of personalized treatments in the future. In this study, we treated human hematopoietic stem and progenitor cells (HSPCs) harvested from a patient with chronic myelogenous leukemia (CML) with gemcitabine/carboplatin. Thereafter, scRNA-seq was performed to distinguish transcriptional effects induced by gemcitabine/carboplatin. Gene expression was calculated and evaluated among cells within and between samples compared to untreated cells. Cell cycle analysis showed that the treatments effectively decrease cell proliferation, indicated by the proportion of cells in the G2M-phase dropping from 35% in untreated cells to 14.3% in treated cells. Clustering and t-SNE showed that cells within samples and between treated and untreated samples were affected differently. Enrichment analysis of differentially expressed genes showed that the treatments influence KEGG pathways and Gene Ontologies related to myeloid cell proliferation/differentiation, immune response, cancer, and the cell cycle. The present study shows the feasibility of using scRNA-seq and chemotherapy-treated HSPCs to find genes, pathways, and biological processes affected among and between treated and untreated cells. This indicates the possible gains of using single-cell toxicity studies for personalized medicine.

adverse drug reactions, carboplatin, gemcitabine, hematopoietic stem and progenitor cells, myelosuppression, single-cell RNA sequencing, toxicity
National Category
Cell and Molecular Biology
urn:nbn:se:liu:diva-165784 (URN)10.3390/genes11050549 (DOI)32422951 (PubMedID)
Available from: 2020-05-25 Created: 2020-05-25 Last updated: 2020-05-25
Björn, N. (2019). Pharmacogenetic biomarkers for chemotherapy-induced adverse drug reactions. (Doctoral dissertation). Linköping: Linköping University Electronic Press
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
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1700
National Category
Cancer and Oncology Pharmacology and Toxicology Medicinal Chemistry Medical Genetics
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)
Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2020-05-25Bibliographically approved
Björn, N., Pradhananga, S., Sigurgeirsson, B., Lundberg, J., Green, H. & Sahlén, P. (2018). Comparison of Variant Calls from Whole Genome and Whole Exome Sequencing Data Using Matched Samples. Journal of Next Generation Sequencing & Applications, 5(1), 1-8
Open this publication in new window or tab >>Comparison of Variant Calls from Whole Genome and Whole Exome Sequencing Data Using Matched Samples
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2018 (English)In: Journal of Next Generation Sequencing & Applications, ISSN 2469-9853, Vol. 5, no 1, p. 1-8Article in journal (Refereed) Published
Abstract [en]

Whole exome sequencing (WES) has been extensively used in genomic research. As sequencing costs decline it is being replaced by whole genome sequencing (WGS) in large-scale genomic studies, but more comparative information on WES and WGS datasets would be valuable. Thus, we have extensively compared variant calls obtained from WGS and WES of matched germline DNA samples from 96 lung cancer patients. WGS provided more homogeneous coverage with higher genotyping quality, and identified more variants, than WES, regardless of exome coverage depth. It also called more reference variants, reflecting its power to call rare variants, and more heterozygous variants that met applied quality criteria, indicating that WGS is less prone to allelic drop outs. However, increasing WES coverage reduced the discrepancy between the WES and WGS results. We believe that as sequencing costs further decline WGS will become the method of choice even for research confined to the exome.

Whole genome sequencing; Whole exome sequencing; Coverage; Depth; Genotyping quality; Discordant; Concordant; Variant calls; Single-nucleotide variants
National Category
Medical Genetics
urn:nbn:se:liu:diva-155840 (URN)

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Available from: 2019-03-28 Created: 2019-03-28 Last updated: 2019-11-20Bibliographically approved

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