| 1. |
- Björn, Niclas, 1990-
(författare)
-
Pharmacogenetic biomarkers for chemotherapy-induced adverse drug reactions
- 2019
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
|
|
| 2. |
- Björn, Niclas, 1990-, et al.
(författare)
-
Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients
- 2020
-
Ingår i: npj Systems Biology and Applications. - : Nature Publishing Group. - 2056-7189. ; 6:1
-
Tidskriftsartikel (refereegranskat)abstract
- Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.
|
|
