The Impact of Digital Transformation on Blood Donation and Donor Characteristics.

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.

Biomarker Discovery in Rare Malignancies: Development of a miRNA Signature for RDEB-cSCC.

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.

Machine learning-based prediction of fainting during blood donations using donor properties and weather data as features.

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.

New Aspects of the Virus Life Cycle and Clinical Utility of Next Generation Sequencing based HIV-1 Resistance Testing in the Genomic, the Proviral, and the Viral Reservoir of Peripheral Blood Mononuclear Cells.

BACKGROUND: Typically, genotypic resistance testing is recommended at the start of antiretroviral therapy and is even mandatory in cases of virologic failure. The material of choice is plasma viral RNA. However, in patients with low viremia (viral load < 500 copies/ml), resistance testing by population-based sequencing is very difficult. OBJECTIVE: Therefore, we aimed to investigate whether next generation sequencing (NGS) from proviral DNA and RNA could be an alternative. MATERIAL AND METHODS: EDTA blood samples (n = 36) from routine clinical viral load testing were used for the study. Viral loads ranged from 96 to 390,000 copies/mL, with 100% of samples having low viremia. Distribution of subtypes; A (n = 2), B (n = 16), C (n = 4), D (n = 2), G (1), CRF02 AG (n = 5), CRF01 AE (n = 5), undefined/mixed (n = 4). The extracted consensus sequences were uploaded to the Stanford HIV Drug Resistance Data Base and Geno2pheno for online analysis of drug resistance mutations and resistance factors. RESULTS: A total of 2476 variants or drug resistance mutations (DRMs) were detected with Sanger sequencing, compared with 2892 variants with NGS. An average of 822/1008 variants were identified in plasma viral RNA by Sanger or NGS sequencing, 834/956 in cellular viral RNA, and 820/928 in cellular viral DNA. CONCLUSION: Both methods are well suited for the detection of HIV substitutions or drug resistance mutations. Our results suggest that cellular RNA or cellular viral DNA is an informative alternative to plasma viral RNA for variant detection in patients with low viremia, as shown by the high correlation of variants in the different viral pools. We show that by using UDS, a plus of two DRMs per patient becomes visible, which can make a big difference in the assessment of the expected resistance behavior of the virus.

A cancer stem cell-like phenotype is associated with miR-10b expression in aggressive squamous cell carcinomas.

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.

High-Throughput Sequencing of the Major Histocompatibility Complex following Targeted Sequence Capture.

The Human Major Histocompatibility Complex (MHC) is a highly polymorphic region full of immunoregulatory genes. The MHC codes for the human leukocyte antigens (HLA), proteins that present on the cellular surface and that are involved in self-non-self recognition. For matching donors and recipients for organ and stem-cell transplants it is important to know an individual's HLA haplotype determinable in this region. Now, as next-generation sequencing (NGS) platforms mature and become more and more accepted as a standard method, NGS applications have spread from research laboratories to the clinic, where they provide valid genetic insights. Here, we describe a cost-effective microarray-based sequence capture, enrichment, and NGS sequencing approach to characterize MHC haplotypes. Using this approach, ~4 MB of MHC sequence for four DNA samples (donor, recipient and the parents of the recipient) were sequenced in parallel in one NGS instrument run. We complemented this approach using microarray-based genome-wide SNP analysis. Taken together, the use of recently developed tools and protocols for sequence capture and massively parallel sequencing allows for detailed MHC analysis and donor-recipient matching.

cFinder: definition and quantification of multiple haplotypes in a mixed sample.

BACKGROUND: 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. RESULTS: 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 (R(2) = 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/. CONCLUSIONS: 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.

Mutation Analysis of Nine Chordoma Specimens by Targeted Next-Generation Cancer Panel Sequencing.

BACKGROUND: Chordoma is a rare primary malignant bone tumour. Treatment options are mainly restricted to surgical excision, since chordomas are largely resistant to conventional ionising radiation and chemotherapy. Thus, there is a strong need to gain more thorough insights into the molecular biology and genetics of chordoma to allow for the development of new therapeutic options. We performed an ultra-deep sequencing analysis to find novel mutations in cancer associated genes in chordomas to date unseen with Sanger sequencing. MATERIAL AND METHODS: Nine chordomas (skull base (n=3), mobile spine (n=4), and sacrum/coccyx (n=2) were screened for mutations in 48 cancer genes using the Hot Spot Cancer Panel (Illumina). All putative mutations were compared against multiple databases (e.g. NCBI, COSMIC, PolyPhen, EGB, SIFT) and published Copy Number Variation (CNV) data for chordoma. RESULTS: Our results showed mutations with a frequency above 5% in tumorsuppressor- and onco-genes, revealing new possible driver genes for chordomas. We detected three different variants accounting for 11 point mutations in three cancer associated genes (KIT, KDR and TP53). None of the detected mutations was found in all samples investigated. However, all genes affected interact or are connected in pathway analysis. There were no correlations to already reported CNVs in the samples analysed. CONCLUSIONS: We identified mutations in the associated genes KIT, KDR, and TP53. These mutations have been described previously and have been predicted to be tolerated. Further results on a larger series are warranted. The driver mechanisms of chordoma still have to be identified.

Introduction of the hybcell-based compact sequencing technology and comparison to state-of-the-art methodologies for KRAS mutation detection.

The detection of KRAS mutations in codons 12 and 13 is critical for anti-EGFR therapy strategies; however, only those methodologies with high sensitivity, specificity, and accuracy as well as the best cost and turnaround balance are suitable for routine daily testing. Here we compared the performance of compact sequencing using the novel hybcell technology with 454 next-generation sequencing (454-NGS), Sanger sequencing, and pyrosequencing, using an evaluation panel of 35 specimens. A total of 32 mutations and 10 wild-type cases were reported using 454-NGS as the reference method. Specificity ranged from 100% for Sanger sequencing to 80% for pyrosequencing. Sanger sequencing and hybcell-based compact sequencing achieved a sensitivity of 96%, whereas pyrosequencing had a sensitivity of 88%. Accuracy was 97% for Sanger sequencing, 85% for pyrosequencing, and 94% for hybcell-based compact sequencing. Quantitative results were obtained for 454-NGS and hybcell-based compact sequencing data, resulting in a significant correlation (r = 0.914). Whereas pyrosequencing and Sanger sequencing were not able to detect multiple mutated cell clones within one tumor specimen, 454-NGS and the hybcell-based compact sequencing detected multiple mutations in two specimens. Our comparison shows that the hybcell-based compact sequencing is a valuable alternative to state-of-the-art methodologies used for detection of clinically relevant point mutations.

Qualifying high-throughput immune repertoire sequencing.

Diversity of B and T cell receptors, achieved by gene recombination and somatic hypermutation, allows the immune system for recognition and targeted reaction against various threats. Next-generation sequencing for assessment of a cell's gene composition and variation makes deep analysis of one individual's immune spectrum feasible. An easy to apply but detailed analysis and visualization strategy is necessary to process all sequences generated. We performed sequencing utilizing the 454 system for CLL and control samples, utilized the IMGT database and applied the presented analysis tools. With the applied protocol, malignant clones are found and characterized, mutational status compared to germline identity is elaborated in detail showing that the CLL mutation status is not as monoclonal as generally thought. On the other hand, this strategy is not solely applicable to the 454 sequencing system but can easily be transferred to any other next-generation sequencing platform.

Routine performance and errors of 454 HLA exon sequencing in diagnostics.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Rapid, scalable and highly automated HLA genotyping using next-generation sequencing: a transition from research to diagnostics.

BACKGROUND: 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. RESULTS: A validation panel of 173 clinical and proficiency testing samples was analysed, demonstrating 100% concordance to the reference method. From a total of 1,273 loci we were able to generate 1,241 (97.3%) initial successful typings. The mean ambiguity reduction for the analysed loci was 93.5%. Allele assignment including intronic sequences showed an improved resolution (99.2%) of non-expressed HLA alleles. CONCLUSION: We provide a powerful HLA typing protocol offering a short turnaround time of only two days, a fully integrated workflow and most importantly a high degree of typing reliability. The presented automated assay is flexible and can be scaled by specific primer compilations and the use of different 454 sequencing systems. The workflow was successfully validated according to the policies of the European Federation for Immunogenetics. Next-generation sequencing seems to become one of the new methods in the field of Histocompatibility.

Human immunodeficiency virus type 1 drug resistance testing: Evaluation of a new ultra-deep sequencing-based protocol and comparison with the TRUGENE HIV-1 Genotyping Kit.

Genotypic HIV-1 drug resistance testing with standard Sanger sequencing is limited to the detection of mutations with >20% prevalence. A new protocol for variant detection of protease and reverse transcriptase genes of HIV-1 genotype B samples with ultra-deep sequencing on the GS-FLX sequencer (Roche 454 Life Sciences, Branford, CT) was evaluated. The new technology was compared with the standard Sanger sequencing method. For accuracy testing, genotype B samples obtained from proficiency panels were examined with ultra-deep sequencing. Reproducibility was determined by repeat GS-FLX sequencing of 21 clinical samples. Clinical performance was evaluated with 44 samples and the results were compared to the TRUGENE HIV-1 Genotyping Kit (Siemens Healthcare Diagnostics, Tarrytown, NY). Sequences generated with both protocols were analyzed using the Stanford University HIV drug resistance database. When accuracy was tested, 316 of 317 mutation codons included in the analysis of proficiency panels could be identified correctly with ultra-deep sequencing. Reproducibility testing resulted in a correlation value of R(2)=0.969. Analysis of 44 routine clinical samples with the Stanford University HIV drug resistance database revealed a total number of 269 and 171 mutations by the ultra-deep and standard Sanger sequencing, respectively. Drug resistance interpretations showed differences for 11 samples. With ultra-deep sequencing, total time to result was four times longer in comparison to standard Sanger sequencing. Manual work was increased significantly using the new protocol. The ultra-deep sequencing protocol showed good accuracy and reproducibility. However, automation and shorter time to obtain results are essential for use in the routine diagnostic laboratory.

Sequence capture and next generation resequencing of the MHC region highlights potential transplantation determinants in HLA identical haematopoietic stem cell transplantation.

How cells coordinate the immune system activities is important for potentially life-saving organ or stem cell transplantations. Polymorphic immunoregulatory genes, many of them located in the human major histocompatibility complex, impact the process and assure the proper execution of tolerance-versus-activity mechanisms. In haematopoietic stem cell transplantation, on the basis of fully human leukocyte antigen (HLA)-matched donor-recipient pairs, adverse effects like graft versus leukaemia and graft versus host are observed and difficult to handle. So far, high-resolution HLA typing was performed with Sanger sequencing, but for methodological reasons information on additional immunocompetent major histocompatibility complex loci has not been revealed. Now, we have used microarray sequence capture and targeted enrichment combined with next generation pyrosequencing for 3.5 million base pair human major histocompatibility complex resequencing in a clinical transplant setting and describe 3025 variant single nucleotide polymorphisms, insertions and deletions among recipient and donor in a single sequencing experiment. Taken together, the presented data show that sequence capture and massively parallel pyrosequencing can be used as a new tool for risk assessment in the setting of allogeneic stem cell transplantation.