Norbert Niklas

Machine learning has been proven to be a powerful tool in the identification of diagnostic tumor biomarkers but is often impeded in rare cancers due to small patient numbers. In patients suffering from recessive dystrophic epidermolysis bullosa (RDEB), early-in-life development of particularly aggressive cutaneous squamous-cell carcinomas (cSCCs) represents a major threat and timely detection is crucial to facilitate prompt tumor excision. As miRNAs have been shown to hold great potential as liquid biopsy markers, we characterized miRNA signatures derived from cultured primary cells specific for the potential detection of tumors in RDEB patients. To address the limitation in RDEB-sample accessibility, we analyzed the similarity of RDEB miRNA profiles with other tumor entities derived from the Cancer Genome Atlas (TCGA) repository. Due to the similarity in miRNA expression with RDEB-SCC, we used HN-SCC data to train a tumor prediction model. Three models with varying complexity using 33, 10 and 3 miRNAs were derived from the elastic net logistic regression model. The predictive performance of all three models was determined on an independent HN-SCC test dataset (AUC-ROC: 100%, 83% and 96%), as well as on cell-based RDEB miRNA-Seq data (AUC-ROC: 100%, 100% and 91%). In addition, the ability of the models to predict tumor samples based on RDEB exosomes (AUC-ROC: 100%, 93% and 100%) demonstrated the potential feasibility in a clinical setting. Our results support the feasibility of this approach to identify a diagnostic miRNA signature, by exploiting publicly available data and will lay the base for an improvement of early RDEB-SCC detection.

Introduction: The management of an adequate donor pool is a constant and challenging task for blood centers in order to provide blood supply. New methods are required to streamline processes and attract (new) donors on a sustained basis. We present a digitalization method without media disruption and show the impact on our donors and their behavior. Methods: We designed and created a blood donation app that is fully compliant to all regulations and conforms to donor expectations. The presented digitalization serves the donor from preparation before the donation (health questionnaire) until completion of laboratory testing (medical report). Many other features are included and continuously attract donors to engage with the blood donation topic. Results: Eighteen months after the launch of our app, there are already 45,000 users. The digital questionnaire reduced the number of deferrals by 31.9% compared to the conventional paper questionnaire. Digital adopters show a significantly shorter donation interval (193 days compared to 316 days). In-app incentives include identification card, rapid laboratory testing results (time-to-results are two business days for 95%), and collection of badges among others. Conclusion: The presented method has changed our donor pool. Besides that, medical staff benefits from the automated process that allows focusing on the donor and their admission. On the other hand, the app has become a valid tool to manage our donor pool and attract first-time and young donors.

Background and objectives: Fainting is a well-known side effect of blood donation. Such adverse experiences can diminish the return rate for further blood donations. Identifying factors associated with fainting could help prevent adverse incidents during blood donation. Materials and methods: Data of 85,040 blood donations from whole blood and apheresis donors within four consecutive years were included in this retrospective study. Seven different machine learning models (random forests, artificial neural networks, XGradient Boosting, AdaBoost, logistic regression, K nearest neighbors, and support vector machines) for predicting fainting during blood donation were established. The used features derived from the data obtained from the questionnaire every donor has to fill in before the donation and weather data of the day of the donation. Results: One thousand seven hundred fifteen fainting reactions were observed in 228 846 blood donations from 88,003 donors over a study period of 48 months. Similar values for all machine learning algorithms investigated for NPV, PPV, AUC, and F1-score were obtained. In general, NPV was above 0.996, whereas PPV was below 0.03. AUC and F1-score were close to 0.9 for all models. Essential features predicting fainting during blood donation were systolic and diastolic blood pressure and ambient temperature, humidity, and barometric pressure. Conclusion: Machine-learning algorithms can establish prediction models of fainting in blood donors. These new tools can reduce adverse reactions during blood donation and improve donor safety and minimize negative associations relating to blood donation.

Background: Cutaneous squamous cell carcinomas (cSCC) are the primary cause of premature deaths in patients suffering from the rare skin-fragility disorder recessive dystrophic epidermolysis bullosa (RDEB), which is in marked contrast to the rarely metastasizing nature of these carcinomas in the general population. This remarkable difference is attributed to the frequent development of chronic wounds caused by impaired skin integrity. However, the specific molecular and cellular changes to malignancy, and whether there are common players in different types of aggressive cSCCs, remain relatively undefined. Methods: MiRNA expression profiling was performed across various cell types isolated from skin and cSCCs. Microarray results were confirmed by qPCR and by an optimized in situ hybridization protocol. Functional impact of overexpression or knock-out of a dysregulated miRNA was assessed in migration and 3D-spheroid assays. Sample-matched transcriptome data was generated to support the identification of disease relevant miRNA targets. Results: Several miRNAs were identified as dysregulated in cSCCs compared to control skin. These included the metastasis-linked miR-10b, which was significantly upregulated in primary cell cultures and in archival biopsies. At the functional level, overexpression of miR-10b conferred the stem cell-characteristic of 3D-spheroid formation capacity to keratinocytes. Analysis of miR-10b downstream effects identified a novel putative target of miR-10b, the actin- and tubulin cytoskeleton-associated protein DIAPH2. Conclusion: The discovery that miR-10b mediates an aspect of cancer stemness – that of enhanced tumor cell adhesion, known to facilitate metastatic colonization – provides an important avenue for future development of novel therapies targeting this metastasis-linked miRNA.

Background: Cutaneous squamous cell carcinomas (cSCC) are the primary cause of premature deaths in patients suffering from the rare skin-fragility disorder recessive dystrophic epidermolysis bullosa, which is in marked contrast to the rarely metastasizing nature of these carcinomas in the general population. This remarkable difference is attributed to the frequent development of chronic wounds caused by an impaired skin integrity. However, the specific molecular and cellular changes to malignancy, and whether there are common players in different types of aggressive cSCCs, remain relatively undefined.Methods: MiRNA expression profiling was performed across various cell types isolated from skin and cSCCs. Microarray results were confirmed by qPCR and by an optimizedin situhybridization protocol. Functional impact of overexpression of a dysregulated miRNA was assessed in migration and 3D spheroid assays. Sample-matched transcriptome data was generated to support the identification of disease relevant miRNA targets.Results: Several miRNAs were identified as dysregulated in cSCCs as compared to controls. These included the metastasis-linked miR-10b, which was significantly upregulated in primary cell cultures and in archival biopsies. At the functional level, overexpression of miR-10b conferred the stem cell-characteristic of 3D-spheroid formation capacity to keratinocytes, and impaired their mobility. Analysis of miR-10b downstream effects identified a novel putative target of miR-10b, the actin- and tubulin cytoskeleton-associated protein DIAPH2.Conclusion: The discovery that miR-10b confers an aspect of cancer stemness – that of enhanced tumor cell adhesion, known to facilitate metastatic colonization - provides an important avenue for future development of novel therapies targeting this metastasis-linked miRNA.

Next-generation sequencing allows for determining the genetic composition of a mixed sample. For instance, when performing resistance testing for BCR-ABL1 it is necessary to identify clones and define compound mutations; together with an exact quantification this may complement diagnosis and therapy decisions with additional information. Moreover, that applies not only to oncological issues but also determination of viral, bacterial or fungal infection. The efforts to retrieve multiple haplotypes (more than two) and proportion information from data with conventional software are difficult, cumbersome and demand multiple manual steps. Therefore, we developed a tool called cFinder that is capable of automatic detection of haplotypes and their accurate quantification within one sample. BCR-ABL1 samples containing multiple clones were used for testing and our cFinder could identify all previously found clones together with their abundance and even refine some results. Additionally, reads were simulated using GemSIM with multiple haplotypes, the detection was very close to linear (R2 = 0.96). Our aim is not to deduce haploblocks over statistics, but to characterize one sample’s composition precisely. As a result the cFinder reports the connections of variants (haplotypes) with their readcount and relative occurrence (percentage). Download is available at http://sourceforge.net/projects/cfinder/ . Our cFinder is implemented in an efficient algorithm that can be run on a low-performance desktop computer. Furthermore, it considers paired-end information (if available) and is generally open for any current next-generation sequencing technology and alignment strategy. To our knowledge, this is the first software that enables researchers without extensive bioinformatic support to designate multiple haplotypes and how they constitute to a sample.

Next-generation sequencing (NGS) has changed genomics significantly. More and more applications strive for sequencing with different platforms. Now, in 2012, after a decade of development and evolution, NGS has been accepted for a variety of research fields. Determination of sequencing errors is essential in order to follow next-generation sequencing beyond research use only. This study describes the overall 454 system performance of using multiple GS Junior runs with an in-house established and validated diagnostic assay for human leukocyte antigen (HLA) exon sequencing. Based on this data, we extracted, evaluated and characterized errors and variants of 60 HLA loci per run with respect to their adjacencies. We determined an overall error rate of 0.18% in a total of 118,484,408 bases. 31.3% of all reads analyzed (n=349,503) contain one or more errors. The largest group are deletions that account for 50% of the errors. Incorrect bases are not distributed equally along sequences and tend to be more frequent at sequence ends. Certain sequence positions in the middle or at the beginning of the read accumulate errors. Typically, the corresponding quality score at the actual error position is lower than the adjacent scores. Here we present the first error assessment in a human next-generation sequencing diagnostics assay in an amplicon sequencing approach. Improvements of sequence quality and error rate that have been made over the years are evident and it is shown that both have now reached a level where diagnostic applications become feasible. Our presented data are better than previously published error rates and we can confirm and quantify the often described relation of homopolymers and errors. Nevertheless, a certain depth of coverage is needed, in particular with challenging areas of the sequencing target. Furthermore, the usage of error correcting tools is not essential but might contribute towards the capacity and efficiency of a sequencing run.

Human leukocyte antigen matching at allelic resolution is proven clinically significant in hematopoietic stem cell transplantation, lowering the risk of graft-versus-host disease and mortality. However, due to the ever growing HLA allele database, tissue typing laboratories face substantial challenges. In light of the complexity and the high degree of allelic diversity, it has become increasingly difficult to define the classical transplantation antigens at high-resolution by using well-tried methods. Thus, next-generation sequencing is entering into diagnostic laboratories at the perfect time and serving as a promising tool to overcome intrinsic HLA typing problems. Therefore, we have developed and validated a scalable automated HLA class I and class II typing approach suitable for diagnostic use.

Background and Objectives  The application of a commercial available microcolumn system for ABO/RH determination lead to irregular results in CDE typing of seemingly D‐ blood samples. In this study, we introduce a comprehensive serological and molecular work‐up of a novel haplotype carrying the RHD*weak 4.3 in combination with an aberrant RHCE*ce.Materials and Methods  The molecular background was characterized by RHD and RHCE‐specific DNA sequencing, RHD cDNA sequencing and RHD zygosity testing. Haplotype‐specific extraction and inheritance analysis were initiated to determine the linkage of the polymorphisms. The genetic admixture was studied by whole genome SNP array analysis. Serology was done using commercial available standard techniques and by in‐house sera likewise.Results  All samples (n = 29) were shown to harbour an altered RHD(T201R, F223V, P291R) allele known as RHD*weak 4.3 associated with a RHCE*ce(W16C, A36T, L245V) gene formation, expressing C^X and VS. Both anti‐C^X and anti‐V/VS were detected as contaminating antibodies in a commercial available microcolumn system for ABO/RH determination accounting for the positive results in CDE typing. Compared with other population data, the samples were clearly identified as Caucasian.Conclusion  The RHD*weak 4.3 allele with markedly reduced antigen D expression was shown to be associated with an altered RHCE gene formation leading to the expression of C^X and VS. Its frequency was estimated 1 in 854 among apparently D‐ Upper Austrian blood donors.