Implementation of Novel Molecular Biomarkers for Non-small Cell Lung Cancer in the Netherlands:How to Deal With Increasing Complexity

The diagnostic landscape of non-small cell lung cancer (NSCLC) is changing rapidly with the availability of novel treatments. Despite high-level healthcare in the Netherlands, not all patients with NSCLC are tested with the currently relevant predictive tumor markers that are necessary for optimal decision-making for today's available targeted or immunotherapy. An expert workshop on the molecular diagnosis of NSCLC involving pulmonary oncologists, clinical chemists, pathologists, and clinical scientists in molecular pathology was held in the Netherlands on December 10, 2018. The aims of the workshop were to facilitate cross-disciplinary discussions regarding standards of practice, and address recent developments and associated challenges that impact future practice. This paper presents a summary of the discussions and consensus opinions of the workshop participants on the initial challenges of harmonization of the detection and clinical use of predictive markers of NSCLC. A key theme identified was the need for broader and active participation of all stakeholders involved in molecular diagnostic services for NSCLC, including healthcare professionals across all disciplines, the hospitals and clinics involved in service delivery, healthcare insurers, and industry groups involved in diagnostic and treatment innovations. Such collaboration is essential to integrate different technologies into molecular diagnostics practice, to increase nationwide patient access to novel technologies, and to ensure consensus-preferred biomarkers are tested

Implementation of Novel Molecular Biomarkers for Non-small Cell Lung Cancer in the Netherlands: How to Deal With Increasing Complexity

The diagnostic landscape of non-small cell lung cancer (NSCLC) is changing rapidly with the availability of novel treatments. Despite high-level healthcare in the Netherlands, not all patients with NSCLC are tested with the currently relevant predictive tumor markers that are necessary for optimal decision-making for today's available targeted or immunotherapy. An expert workshop on the molecular diagnosis of NSCLC involving pulmonary oncologists, clinical chemists, pathologists, and clinical scientists in molecular pathology was held in the Netherlands on December 10, 2018. The aims of the workshop were to facilitate cross-disciplinary discussions regarding standards of practice, and address recent developments and associated challenges that impact future practice. This paper presents a summary of the discussions and consensus opinions of the workshop participants on the initial challenges of harmonization of the detection and clinical use of predictive markers of NSCLC. A key theme identified was the need for broader and active participation of all stakeholders involved in molecular diagnostic services for NSCLC, including healthcare professionals across all disciplines, the hospitals and clinics involved in service delivery, healthcare insurers, and industry groups involved in diagnostic and treatment innovations. Such collaboration is essential to integrate different technologies into molecular diagnostics practice, to increase nationwide patient access to novel technologies, and to ensure consensus-preferred biomarkers are tested

Extensive Evolutionary Changes in Regulatory Element Activity during Human Origins Are Associated with Altered Gene Expression and Positive Selection

Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS) sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium

BACKGROUND: Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands). METHODS: Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance. RESULTS: A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately. CONCLUSIONS: Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine

Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease

Alzheimer’s disease (AD) is a severe1 age-related neurodegenerative disorder characterized by accumulation of amyloid-β (Aβ) plaques and neurofibrillary tangles, synaptic and neuronal loss, and cognitive decline. Several genes have been implicated in AD, but chromatin state alterations during neurodegeneration remain uncharacterized. Here, we profile transcriptional and chromatin state dynamics across early and late pathology in the hippocampus of an inducible mouse model of AD-like neurodegeneration. We find a coordinated downregulation of synaptic plasticity genes and regulatory regions, and upregulation of immune response genes and regulatory regions, which are targeted by factors that belong to the ETS family of transcriptional regulators, including PU.1. Human regions orthologous to increasing-level enhancers show immune cell-specific enhancer signatures as well as immune cell expression quantitative trait loci (eQTL), while decreasing-level enhancer orthologs show fetal-brain-specific enhancer activity. Notably, AD-associated genetic variants are specifically enriched in increasing-level enhancer orthologs implicating immune processes in AD predisposition. Indeed, increasing enhancers overlap known AD loci lacking protein-altering variants and implicate additional loci that do not reach genome-wide significance. Our results reveal new insights into the mechanisms of neurodegeneration and establish the mouse as a useful model for functional studies of AD regulatory regions

HIV latency and integration site placement in five cell-based models

BACKGROUND: HIV infection can be treated effectively with antiretroviral agents, but the persistence of a latent reservoir of integrated proviruses prevents eradication of HIV from infected individuals. The chromosomal environment of integrated proviruses has been proposed to influence HIV latency, but the determinants of transcriptional repression have not been fully clarified, and it is unclear whether the same molecular mechanisms drive latency in different cell culture models. RESULTS: Here we compare data from five different in vitro models of latency based on primary human T cells or a T cell line. Cells were infected in vitro and separated into fractions containing proviruses that were either expressed or silent/inducible, and integration site populations sequenced from each. We compared the locations of 6,252 expressed proviruses to those of 6,184 silent/inducible proviruses with respect to 140 forms of genomic annotation, many analyzed over chromosomal intervals of multiple lengths. A regularized logistic regression model linking proviral expression status to genomic features revealed no predictors of latency that performed better than chance, though several genomic features were significantly associated with proviral expression in individual models. Proviruses in the same chromosomal region did tend to share the same expressed or silent/inducible status if they were from the same cell culture model, but not if they were from different models. CONCLUSIONS: The silent/inducible phenotype appears to be associated with chromosomal position, but the molecular basis is not fully clarified and may differ among in vitro models of latency

Expanded encyclopaedias of DNA elements in the human and mouse genomes

All data are available on the ENCODE data portal: www.encodeproject. org. All code is available on GitHub from the links provided in the methods section. Code related to the Registry of cCREs can be found at https:// github.com/weng-lab/ENCODE-cCREs. Code related to SCREEN can be found at https://github.com/weng-lab/SCREEN.© The Author(s) 2020. The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.This work was supported by grants from the NIH under U01HG007019, U01HG007033, U01HG007036, U01HG007037, U41HG006992, U41HG006993, U41HG006994, U41HG006995, U41HG006996, U41HG006997, U41HG006998, U41HG006999, U41HG007000, U41HG007001, U41HG007002, U41HG007003, U54HG006991, U54HG006997, U54HG006998, U54HG007004, U54HG007005, U54HG007010 and UM1HG009442