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Article ; Online: Validation of transcriptome signature reversion for drug repurposing in oncology.

Koudijs, Karel K M / Böhringer, Stefan / Guchelaar, Henk-Jan

2022 Volume 24, Issue 1

Abstract: Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types. TSR relies on the assumption that a drug that can revert ... ...

Abstract	Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types. TSR relies on the assumption that a drug that can revert gene expression changes induced by a disease back to original, i.e. healthy, levels is likely to be therapeutically active in treating the disease. Here, we aimed to validate the concept of TSR using the PRISM repurposing data set, which is-as of writing-the largest pharmacogenomic data set. The predictive utility of the TSR approach as it has currently been used appears to be much lower than previously reported and is completely nullified after the drug gene expression signatures are adjusted for the general anti-proliferative downstream effects of drug-induced decreased cell viability. Therefore, TSR mainly relies on generic anti-proliferative drug effects rather than on targeting cancer pathways specifically upregulated in tumor types.
MeSH term(s)	Humans ; Transcriptome ; Drug Repositioning ; Gene Expression Profiling ; Neoplasms/drug therapy ; Neoplasms/genetics ; Medical Oncology
Language	English
Publishing date	2022-12-12
Publishing country	England
Document type	Journal Article
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbac490
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Article ; Online: A Genome-Wide Association Study of Endoxifen Serum Concentrations and Adjuvant Tamoxifen Efficacy in Early-Stage Breast Cancer Patients.

Sanchez-Spitman, Anabel Beatriz / Böhringer, Stefan / Dezentjé, Vincent Olaf / Gelderblom, Hans / Swen, Jesse Joachim / Guchelaar, Henk-Jan

Clinical pharmacology and therapeutics

2024

Abstract: Tamoxifen is part of the standard of care of endocrine therapy for adjuvant treatment of breast cancer. However, survival outcomes with tamoxifen are highly variable. The concentration of endoxifen, the 30-100 times more potent metabolite of tamoxifen ... ...

Abstract	Tamoxifen is part of the standard of care of endocrine therapy for adjuvant treatment of breast cancer. However, survival outcomes with tamoxifen are highly variable. The concentration of endoxifen, the 30-100 times more potent metabolite of tamoxifen and bioactivated by the CYP2D6 enzyme, has been described as the most relevant metabolite of tamoxifen metabolism. A genome-wide association study (GWAS) was performed with the objective to identify genetic polymorphisms associated with endoxifen serum concentration levels and clinical outcome in early-stage breast cancer patients receiving tamoxifen. A GWAS was conducted in 608 women of the CYPTAM study (NTR1509/PMID: 30120701). Germline DNA and clinical and survival characteristics were readily available. Genotyping was performed on Infinium Global Screening Array (686,082 markers) and single nucleotide polymorphism (SNP) imputation by using 1000 Genomes. Relapse-free survival during tamoxifen (RFSt) was defined the primary clinical outcome. Endoxifen serum concentration was analyzed as a continuous variable. Several genetic variants reached genome-wide significance (P value: ≤5 × 10
Language	English
Publishing date	2024-03-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	123793-7
ISSN	1532-6535 ; 0009-9236
ISSN (online)	1532-6535
ISSN	0009-9236
DOI	10.1002/cpt.3255
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Article ; Online: The PREPARE study: benefits of pharmacogenetic testing are unclear - Authors' reply.

Swen, Jesse J / Manson, Lisanne E N / Böhringer, Stefan / Pirmohamed, Munir / Guchelaar, Henk-Jan

Lancet (London, England)

2023 Volume 401, Issue 10391, Page(s) 1851–1852

MeSH term(s)	Humans ; Pharmacogenomic Testing ; Genetic Testing ; Pharmacogenetics
Language	English
Publishing date	2023-06-02
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	3306-6
ISSN	1474-547X ; 0023-7507 ; 0140-6736
ISSN (online)	1474-547X
ISSN	0023-7507 ; 0140-6736
DOI	10.1016/S0140-6736(23)00852-8
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Article ; Online: Choosing and changing the analysis scale in non-inferiority trials with a binary outcome.

Li, Zhong / Quartagno, Matteo / Böhringer, Stefan / van Geloven, Nan

Clinical trials (London, England)

2021 Volume 19, Issue 1, Page(s) 14–21

Abstract: Background: The size of the margin strongly influences the required sample size in non-inferiority and equivalence trials. What is sometimes ignored, however, is that for trials with binary outcomes, the scale of the margin - risk difference, risk ratio ...

Abstract	Background: The size of the margin strongly influences the required sample size in non-inferiority and equivalence trials. What is sometimes ignored, however, is that for trials with binary outcomes, the scale of the margin - risk difference, risk ratio or odds ratio - also has a large impact on power and thus on sample size requirement. When considering several scales at the design stage of a trial, these sample size consequences should be taken into account. Sometimes, changing the scale may be needed at a later stage of a trial, for example, when the event proportion in the control arm turns out different from expected. Also after completion of a trial, a switch to another scale is sometimes made, for example, when using a regression model in a secondary analysis or when combining study results in a meta-analysis that requires unifying scales. The exact consequences of such switches are currently unknown. Methods and results: This article first outlines sample size consequences for different choices of analysis scale at the design stage of a trial. We add a new result on sample size requirement comparing the risk difference scale with the risk ratio scale. Then, we study two different approaches to changing the analysis scale after the trial has commenced: (1) mapping the original non-inferiority margin using the event proportion in the control arm that was anticipated at the design stage or (2) mapping the original non-inferiority margin using the observed event proportion in the control arm. We use simulations to illustrate consequences on type I and type II error rates. Methods are illustrated on the INES trial, a non-inferiority trial that compared single birth rates in subfertile couples after different fertility treatments. Our results demonstrate large differences in required sample size when choosing between risk difference, risk ratio and odds ratio scales at the design stage of non-inferiority trials. In some cases, the sample size requirement is twice as large on one scale compared with another. Changing the scale after commencing the trial using anticipated proportions mainly impacts type II error rate, whereas switching using observed proportions is not advised due to not maintaining type I error rate. Differences were more pronounced with larger margins. Conclusions: Trialists should be aware that the analysis scale can have large impact on type I and type II error rates in non-inferiority trials.
MeSH term(s)	Clinical Trials as Topic ; Humans ; Odds Ratio ; Research Design ; Sample Size
Language	English
Publishing date	2021-10-24
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2138796-5
ISSN	1740-7753 ; 1740-7745
ISSN (online)	1740-7753
ISSN	1740-7745
DOI	10.1177/17407745211053790
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Article: Genotyping for HLA risk alleles versus patch tests to diagnose anti-seizure medication induced cutaneous adverse drug reactions.

Manson, Lisanne E N / Chan, Patricia C Y / Böhringer, Stefan / Guchelaar, Henk-Jan

Frontiers in pharmacology

2022 Volume 13, Page(s) 1061419

Abstract: Aim: ...

Abstract	Aim:
Language	English
Publishing date	2022-11-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2022.1061419
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Article: IGF1 and Insulin Receptor Single Nucleotide Variants Associated with Response in HER2-Negative Breast Cancer Patients Treated with Neoadjuvant Chemotherapy with or without a Fasting Mimicking Diet (BOOG 2013-04 DIRECT Trial).

de Gruil, Nadia / Böhringer, Stefan / de Groot, Stefanie / Pijl, Hanno / Kroep, Judith R / Swen, Jesse J

Cancers

2023 Volume 15, Issue 24

Abstract: Aim: We aimed to investigate associations between : Methods: Germline DNA from 113 patients was tested for 17 systematically selected candidate SNVs in : Results: IGF1R: Conclusions: ... ...

Abstract	Aim: We aimed to investigate associations between Methods: Germline DNA from 113 patients was tested for 17 systematically selected candidate SNVs in Results: IGF1R Conclusions: The
Language	English
Publishing date	2023-12-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers15245872
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Article ; Online: Haplotype reconstruction for genetically complex regions with ambiguous genotype calls: Illustration by the KIR gene region.

van der Burg, Lars L J / de Wreede, Liesbeth C / Baldauf, Henning / Sauter, Jürgen / Schetelig, Johannes / Putter, Hein / Böhringer, Stefan

Genetic epidemiology

2023 Volume 48, Issue 1, Page(s) 3–26

Abstract: Advances in DNA sequencing technologies have enabled genotyping of complex genetic regions exhibiting copy number variation and high allelic diversity, yet it is impossible to derive exact genotypes in all cases, often resulting in ambiguous genotype ... ...

Abstract	Advances in DNA sequencing technologies have enabled genotyping of complex genetic regions exhibiting copy number variation and high allelic diversity, yet it is impossible to derive exact genotypes in all cases, often resulting in ambiguous genotype calls, that is, partially missing data. An example of such a gene region is the killer-cell immunoglobulin-like receptor (KIR) genes. These genes are of special interest in the context of allogeneic hematopoietic stem cell transplantation. For such complex gene regions, current haplotype reconstruction methods are not feasible as they cannot cope with the complexity of the data. We present an expectation-maximization (EM)-algorithm to estimate haplotype frequencies (HTFs) which deals with the missing data components, and takes into account linkage disequilibrium (LD) between genes. To cope with the exponential increase in the number of haplotypes as genes are added, we add three components to a standard EM-algorithm implementation. First, reconstruction is performed iteratively, adding one gene at a time. Second, after each step, haplotypes with frequencies below a threshold are collapsed in a rare haplotype group. Third, the HTF of the rare haplotype group is profiled in subsequent iterations to improve estimates. A simulation study evaluates the effect of combining information of multiple genes on the estimates of these frequencies. We show that estimated HTFs are approximately unbiased. Our simulation study shows that the EM-algorithm is able to combine information from multiple genes when LD is high, whereas increased ambiguity levels increase bias. Linear regression models based on this EM, show that a large number of haplotypes can be problematic for unbiased effect size estimation and that models need to be sparse. In a real data analysis of KIR genotypes, we compare HTFs to those obtained in an independent study. Our new EM-algorithm-based method is the first to account for the full genetic architecture of complex gene regions, such as the KIR gene region. This algorithm can handle the numerous observed ambiguities, and allows for the collapsing of haplotypes to perform implicit dimension reduction. Combining information from multiple genes improves haplotype reconstruction.
MeSH term(s)	Humans ; Haplotypes ; DNA Copy Number Variations ; Gene Frequency ; Models, Genetic ; Genotype
Language	English
Publishing date	2023-10-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	605785-8
ISSN	1098-2272 ; 0741-0395
ISSN (online)	1098-2272
ISSN	0741-0395
DOI	10.1002/gepi.22538
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Article: Quantification of Facial Traits.

Böhringer, Stefan / de Jong, Markus A

Frontiers in genetics

2019 Volume 10, Page(s) 397

Abstract: Measuring facial traits by quantitative means is a prerequisite to investigate epidemiological, clinical, and forensic questions. This measurement process has received intense attention in recent years. We divided this process into the registration of ... ...

Abstract	Measuring facial traits by quantitative means is a prerequisite to investigate epidemiological, clinical, and forensic questions. This measurement process has received intense attention in recent years. We divided this process into the registration of the face, landmarking, morphometric quantification, and dimension reduction. Face registration is the process of standardizing pose and landmarking annotates positions in the face with anatomic description or mathematically defined properties (pseudolandmarks). Morphometric quantification computes pre-specified transformations such as distances.
Language	English
Publishing date	2019-05-24
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2019.00397
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Article ; Online: Influence of batch effect correction methods on drug induced differential gene expression profiles.

Zhou, Wei / Koudijs, Karel K M / Böhringer, Stefan

BMC bioinformatics

2019 Volume 20, Issue 1, Page(s) 437

Abstract: Background: Batch effects were not accounted for in most of the studies of computational drug repositioning based on gene expression signatures. It is unknown how batch effect removal methods impact the results of signature-based drug repositioning. ... ...

Abstract	Background: Batch effects were not accounted for in most of the studies of computational drug repositioning based on gene expression signatures. It is unknown how batch effect removal methods impact the results of signature-based drug repositioning. Herein, we conducted differential analyses on the Connectivity Map (CMAP) database using several batch effect correction methods to evaluate the influence of batch effect correction methods on computational drug repositioning using microarray data and compare several batch effect correction methods. Results: Differences in average signature size were observed with different methods applied. The gene signatures identified by the Latent Effect Adjustment after Primary Projection (LEAPP) method and the methods fitted with Linear Models for Microarray Data (limma) software demonstrated little agreement. The external validity of the gene signatures was evaluated by connectivity mapping between the CMAP database and the Library of Integrated Network-based Cellular Signatures (LINCS) database. The results of connectivity mapping indicate that the genes identified were not reliable for drugs with total sample size (drug + control samples) smaller than 40, irrespective of the batch effect correction method applied. With total sample size larger than 40, the methods correcting for batch effects produced significantly better results than the method with no batch effect correction. In a simulation study, the power was generally low for simulated data with sample size smaller than 40. We observed best performance when using the limma method correcting for two principal components. Conclusion: Batch effect correction methods strongly impact differential gene expression analysis when the sample size is large enough to contain sufficient information and thus the downstream drug repositioning. We recommend including two or three principal components as covariates in fitting models with limma when sample size is sufficient (larger than 40 drug and controls combined).
MeSH term(s)	Computational Biology/methods ; Computer Simulation ; Databases, Factual ; Drug Repositioning ; Humans ; Pharmaceutical Preparations/metabolism ; Principal Component Analysis ; Sample Size ; Transcriptome
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2019-08-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-019-3028-6
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Article ; Online: The impact of autoantibodies on the efficacy of biological disease-modifying anti-rheumatic drugs in rheumatoid arthritis: meta-analysis of randomized controlled trials.

Takase-Minegishi, Kaoru / Böhringer, Stefan / Nam, Jackie L / Kaneko, Yuko / Behrens, Frank / Saevarsdottir, Saedis / Detert, Jacqueline / Leirisalo-Repo, Marjatta / van der Heijde, Désirée / Landewé, Robert / Ramiro, Sofia / van der Woude, Diane

Rheumatology (Oxford, England)

2024

Abstract: Objective: To investigate the efficacy of bDMARDs in patients with RA with RF/ACPA compared with patients without these autoantibodies.: Methods: Previous systematic literature reviews performed by EULAR RA management task forces were searched for ... ...

Abstract	Objective: To investigate the efficacy of bDMARDs in patients with RA with RF/ACPA compared with patients without these autoantibodies. Methods: Previous systematic literature reviews performed by EULAR RA management task forces were searched for qualifying RCTs. RCTs investigating the efficacy of bDMARDs and including both autoantibody-positive (≤80% of total population) and -negative RA patients were eligible. For trials comparing bDMARD+csDMARD vs csDMARD, relative risks (RR) comparing two groups (RF + vs RF-, ACPA+ vs ACPA-) were calculated for efficacy outcomes for each arm. Subsequently, relative risk ratios (RRRs) were computed, as the ratio of RR of the bDMARD-arm and the RR from the non-bDMARD-arm. Pooled effects were obtained with random effect meta-analyses. Results: Data from 28 eligible RCTs were analyzed, pooling 23 studies in three subgroups: 6 including csDMARD-naïve patients, 14 csDMARD-IR, and 3 TNFi-IR patients. In csDMARD-naïve and csDMARD-IR patients, seropositivity was not associated with a better response to bDMARDs: pooled 6-month ACR20 RRRs 1.02 (0.88-1.18) and 1.09 (0.90-1.32), respectively. Other outcomes showed no difference between groups either. In TNFi-IR patients, based on 3 trials, the 6-month ACR20 RRR was 2.28 (1.31-3.95), favoring efficacy in seropositive patients. Other outcomes mostly showed no significant difference between the groups. Based on the mode of action, efficacy was comparable between RF-positive and RF-negative patients for both TNFi and non-TNFi treatment and also for the individual bDMARDs. Conclusion: The effect of bDMARDs is generally comparable in patients with and without RF/ACPA, regardless of the patient population, the mechanism of action or individual drug used.
Language	English
Publishing date	2024-02-16
Publishing country	England
Document type	Journal Article
ZDB-ID	1464822-2
ISSN	1462-0332 ; 1462-0324
ISSN (online)	1462-0332
ISSN	1462-0324
DOI	10.1093/rheumatology/keae113
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