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Constitutive activation of NF-κB is a hallmark of the activated B cell–like (ABC) subtype of diffuse large B-cell lymphoma (DLBCL), owing to upstream signals from the B-cell receptor (BCR) and MYD88 pathways. The linear polyubiquitin chain assembly complex (LUBAC) attaches linear polyubiquitin chains to IκB kinase-γ, a necessary event in some pathways that engage NF-κB. Two germline polymorphisms affecting the LUBAC subunit RNF31 are rare among healthy individuals (∼1%) but enriched in ABC DLBCL (7.8%). These polymorphisms alter RNF31 α-helices that mediate binding to the LUBAC subunit RBCK1, thereby increasing RNF31–RBCK1 association, LUBAC enzymatic activity, and NF-κB engagement. In the BCR pathway, LUBAC associates with the CARD11–MALT1–BCL10 adapter complex and is required for ABC DLBCL viability. A stapled RNF31 α-helical peptide based on the ABC DLBCL–associated Q622L polymorphism inhibited RNF31–RBCK1 binding, decreased NF-κB activation, and killed ABC DLBCL cells, credentialing this protein–protein interface as a therapeutic target.Significance: We provide genetic, biochemical, and functional evidence that the LUBAC ubiquitin ligase is a therapeutic target in ABC DLBCL, the DLBCL subtype that is most refractory to current therapy. More generally, our findings highlight the role of rare germline-encoded protein variants in cancer pathogenesis. Cancer Discov; 4(4); 480–93. ©2014 AACR.See related commentary by Grumati and Dikic, p. 394This article is highlighted in the In This Issue feature, p. 377

PDF file 42K, Co-occurrence of RNF31 SNPs with other genetic lesions in ABC DLBCL cases

Supplementary Table 1 PDF file 53K, Enrichment of two rare SNPs among ABC DLBCL tumors

PDF file 124K, Involvement of LUBAC in CBM complex mediated NF-kappaB activation, related to main figure 3

PDF file 149K, RNF31 peptides internalized equivalently in ABC DLBCL cells

PDF file 73K, Constitutive linear ubiquitination of NEMO in ABC comparing to GCB DLBCL cells

PDF file 132K, Specificity of RNF31 stapled peptides in ABC DLBCL

PDF file 283K, RNF31 DNA sequence electropherograms for the region corresponding to the single nucleotide polymorphisms (SNPs)

Purpose:For patients with refractory/relapsed Hodgkin lymphoma (roughly 20% of total cases), few effective therapeutic options exist. Currently, brentuximab vedotin (BV), a drug-conjugated anti-CD30 antibody, is one of the most effective approved therapy agents for these patients. However, many patients do not achieve complete remission and ultimately develop BV-resistant disease, necessitating a more detailed understanding of the molecular circuitry that drives BV sensitivity and the mechanism of BV resistance.Experimental Design:Here, we established a ubiquitin regulator–focused CRISPR library screening platform in Hodgkin lymphoma and carried out a drug sensitization screen against BV to identify genes regulating BV treatment sensitivity.Results:Our CRISPR library screens revealed the ubiquitin-editing enzymes A20 and RBX1 as key molecule effectors that regulate BV sensitivity in Hodgkin lymphoma line L428. A20 negatively regulates NF-κB activity which is required to prevent BV cytotoxicity. In line with these results, the RNA-seq analysis of the BV-resistant single-cell clones demonstrated a consistent upregulation of NF-κB signature genes, as well as the ABC transporter gene ABCB1. Mechanically, NF-κB regulates BV treatment sensitivity through mediating ABCB1 expression. Targeting NF-κB activity synergized well with BV in killing Hodgkin lymphoma cell lines, augmented BV sensitivity, and overcame BV resistance in vitro and in Hodgkin lymphoma xenograft mouse models.Conclusions:Our identification of this previously unrecognized mechanism provides novel knowledge of possible BV responsiveness and resistance mechanisms in Hodgkin lymphoma, as well as leads to promising hypotheses for the development of therapeutic strategies to overcome BV resistance in this disease.

Supplementary Information. Including Supplemental Experimental Procedures, and Supplementary Figure 1-6.

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications such as companion diagnostics and prognostics. However, there is a lack of certified RNA reference materials and the corresponding reference datasets of differential expression for assessing the reliability of RNAseq for its intended use in detecting intrinsically small biological differences in clinical settings such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multiomics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two reference samples, providing "ground truth" for cross-platform and cross-lab proficiency test. Moreover, Quartet-sample-based quality metrics were developed for assessing the reliability of RNAseq technology in terms of intra-batch measurement and cross-batch data integration. The small intrinsic biological differences among the Quartet samples enabled sensitive assessment of performance of transcriptomic measurements and their cross-batch integration at the ratio level. The Quartet RNA reference materials combined with the ratio-based reference datasets can serve as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor–normal genomic DNA (gDNA) samples derived from a breast cancer cell line—which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations—and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible athttps://chinese-quartet.org.Graphical Abstract

Skin cancer is the commonly found type, which contributes to 40% of whole cancer incidences worldwide. Dieckol is an active compound occurs in the marine algae with many biological benefits. In this exploration, we intended to investigate the therapeutic potency of dieckol against the 7,12-dimethylbenz(a)anthracene (DMBA)-triggered skin carcinogenesis in mice. The skin cancer was stimulated to the animals via injecting the 25 μg of DMBA in 100 μL of acetone in shaved dorsal portion along with the 30 mg/kg of dieckol supplementation for 25 week. The antioxidant enzymes and phase-I and -II detoxifying enzymes in the test animals were inspected via standard protocols. Pro-inflammatory markers (IL-6, IL-1β, and TNF-α) level was examined via ELISA kits and the expression of inflammatory molecular markers like p-NF-ƙB, IƙBα and p-IƙBα were studied through western blotting. The expression status of pro- and anti-apoptotic proteins (p53, Bax, Bcl-2, caspase-3, caspase-9, COX-2, TGF-β1) was investigated via real-time polymerase chain reaction (RT-PCR). Our results revealed that the 30 mg/kg of dieckol supplementation noticeably regained the body and liver weight and also diminished the tumor incidence in the DMBA-incited animals. Dieckol treatment exhibited an enhanced antioxidants (SOD, CAT, GPx, and GSH) and reduced phase-I enzymes Cyt-p450 and Cyt-b5 in the DMBA-induced animals. Dieckol also diminished the pro-inflammatory modulators like IL-6, IL-1β and TNF-α. Western blotting result evidenced that the dieckol was inhibited the IƙB/NF-ƙB signaling pathway. RT-PCR study proved the enhanced expression of pro-apoptotic protein (p53, Bax, caspase-3 and -9) in the dieckol treated animals. Histological study also confirmed the therapeutic benefits of Dieckol. Altogether with these findings, it was clear that the dieckol has appreciably allayed the DMBA activated skin tumorigenesis in the mice and it could be a promising agent to treat the human skin cancer in future.

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study. A comprehensive comparison of 20 single-cell RNA-seq datasets derived from the two cell lines analyzed using six preprocessing pipelines, eight normalization methods and seven batch-correction algorithms derived from four different sequencing platforms at different centers.

Aberrant activation of NF-κB is the most striking oncogenic mechanism in B-cell lymphoma; however, its role in anaplastic large cell lymphomas (ALCL) has not been fully established and its activation mechanism(s) remain unclear. Using ALCL cell line models, we revealed the supporting roles for NFKB2 and the NIK pathway in some ALCL lines. To investigate the detailed activation mechanisms for this oncogenic pathway, we performed specifically designed alternative NF-κB reporter CRISPR screens followed by the RNA-seq analysis, which led us to identify STAT3 as the major mediator for NIK-dependent NF-κB activation in ALCL. Consistently, p-STAT3 level was correlated with NFKB2 nuclear accumulation in primary clinical samples. Mechanistically, we found that in NIK-positive ALK- ALCL cells, common JAK/STAT3 mutations promote transcriptional activity of STAT3 which directly regulates NFKB2 and CD30 expression. Endogenous expression of CD30 induces constitutive NF-κB activation through binding and degrading of TRAF3. In ALK+ ALCL, the CD30 pathway is blocked by the NPM-ALK oncoprotein, but STAT3 activity and resultant NFKB2 expression can still be induced by NPM-ALK, leading to minimal alternative NF-κB activation. Our data suggest combined NIK and JAK inhibitor therapy could benefit patients with NIK-positive ALK- ALCL carrying JAK/STAT3 somatic mutations.

Based on a detailed case study of the socialist transformation of the Shanghai Great World Amusement Centre (Dashijie), this article documents state-building efforts during the early years of the People's Republic of China (PRC). Between 1950 and 1958, the Communist regime incrementally transformed the power configuration within Dashijie, promoting dramatic changes in its personnel, institutional structures, drama performances, and physical space. Over the course of this process, Dashijie seemed to become a ‘loftier’ cultural organization in accordance with the aims of its transformation. This transfigured Dashijie, however, fell out of favour with the people of Shanghai. This multifaceted transformation process reflects considerable state capacities on the one hand and illustrates the complexity of state capacities—their unevenness and the limitations of a strong state—on the other. The complexity of state capacities thus shaped and was embedded in the process and outcome of this socialist cultural transformation. Since the Chinese state is once again making strenuous efforts at culture-building, an overview of cultural transformation in the early PRC era has important contemporary implications.

BackgroundReproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS.ResultsTo dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×.ConclusionsOur findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies., Measurement(s)Somatic Mutation AnalysisTechnology Type(s)whole genome sequencing • Whole Exome SequencingFactor Type(s)sequencing platform • sample prepration • library preparation • bioinformatics methodSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16713655

Background Accurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly. Results To address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies. Conclusions The dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

The Tibetan Plateau (TP) is a key area affecting forecasts of weather and climate in China and occurrences of extreme weather and climate events over the world. The China Meteorological Administration, the National Natural Science Foundation of China, and the Chinese Academy of Sciences jointly initiated the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-III) in 2013, with an 8–10-yr implementation plan. Since its preliminary field measurements conducted in 2013, routine automatic sounding systems have been deployed at Shiquanhe, Gaize, and Shenzha stations in western TP, where no routine sounding observations were available previously. The observational networks for soil temperature and soil moisture in the central and western TP have also been established. Meanwhile, the plateau-scale and regional-scale boundary layer observations, cloud-precipitation microphysical observations with multiple radars and aircraft campaigns, and tropospheric-stratospheric air composition observations at multiple sites, were performed. The results so far show that the turbulent heat exchange coefficient and sensible heat flux are remarkably lower than the earlier estimations at grassland, meadow, and bare soil surfaces of the central and western TP. Climatologically, cumulus clouds over the main body of the TP might develop locally instead of originating from the cumulus clouds that propagate northward from South Asia. The TIPEX-III observations up to now also reveal diurnal variations, macro- and microphysical characteristics, and water-phase transition mechanisms, of cumulus clouds at Naqu station. Moreover, TIPEX-III related studies have proposed a maintenance mechanism responsible for the Asian “atmospheric water tower” and demonstrated the effects of the TP heating anomalies on African, Asian, and North American climates. Additionally, numerical modeling studies show that the Γ distribution of raindrop size is more suitable for depicting the TP raindrop characteristics compared to the M-P distribution, the overestimation of sensible heat flux can be reduced via modifying the heat transfer parameterization over the TP, and considering climatic signals in some key areas of the TP can improve the skill for rainfall forecast in the central and eastern parts of China. Furthermore, the TIPEX-III has been promoting the technology in processing surface observations, soundings, and radar observations, improving the quality of satellite retrieved soil moisture and atmospheric water vapor content products as well as high-resolution gauge-radar-satellite merged rainfall products, and facilitating the meteorological monitoring, forecasting, and data sharing operations.

Background Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed. Methods We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs. Results The conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected). Conclusion A significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome. Electronic supplementary material The online version of this article (10.1186/s12859-019-2620-0) contains supplementary material, which is available to authorized users.

The use of personalized genome assembly as a reference for detecting the full spectrum of somatic events from cancers has long been advocated but never been systematically investigated. Here we address the critical need of assessing the accuracy of somatic mutation detection using personalized genome assembly versus the standard human reference assembly (i.e. GRCh38). We first obtained massive whole genome sequencing data using multiple sequencing technologies, and then performed de novo assembly of the first tumor-normal paired genomes, both nuclear and mitochondrial, derived from the same donor with triple negative breast cancer. Compared to standard human reference assembly, the haplotype phased chromosomal-scale personalized genome was best demonstrated with individual specific haplotypes for some complex regions and medical relevant genes. We then used this well-assembled personalized genome as a reference for read mapping and somatic variant discovery. We showed that the personalized genome assembly results in better alignments of sequencing reads and more accurate somatic mutation calls. Direct comparison of mitochondrial genomes led to discovery of unreported nonsynonymous somatic mutations. Our findings provided a unique resource and proved the necessity of personalized genome assembly as a reference in improving somatic mutation detection at personal genome level not only for breast cancer reference samples, but also potentially for other cancers.

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies. Background & Summary The NGS technology has become a powerful tool for precision medicine. More researchers and clinicians are utilizing NGS to identify clinically actionable mutations in cancer patients and to establish targeted therapies for patients based on the patient’s genetic makeup or genetic variants of their tumor1, there is a critical need to have a full understanding of the many different variables affecting the NGS analysis output. The rapid growing number of sample processing protocols, library preparation methods, sequencing platforms, and bioinformatics pipelines to detect mutations in cancer genome, presents great technical challenges for the accuracy and reproducibility of utilizing NGS for cancer genome mutation detections. To investigate how these experimental and analytical elements may affect mutation detection accuracy, recently we carried out a comprehensive benchmarking study using both whole-genome (WGS) and whole-exome sequencing (WES) data sets generated from two well-characterized reference samples: a human breast cancer cell line (HCC1395) and a B lymphocytes cell line (HCC1395BL) derived from the same donor (NBT-RS47789). We generated WGS and WES data using various NGS library preparation protocols, seven NGS platforms at six centers (NBT-A46164B).

Copy number variation (CNV) is a common type of mutation that often drives cancer progression. With advances in next-generation sequencing (NGS), CNVs can be detected in a detailed manner via newly developed computational tools but quality of such CNV calls has not been carefully evaluated. We analyzed CNV calls reported by 6 cutting-edge callers for 91 samples which were derived from the same cancer cell line, prepared and sequenced by varying the following factors: type of tissue sample (Fresh vs. Formalin Fixed Paraffin Embedded (FFPE)), library DNA amount, tumor purity, sequencing platform (Whole-Genome Sequencing (WGS) versus Whole-Exome Sequencing (WES)), and sequencing coverage. We found that callers greatly determined the pattern of CNV calls. Calling quality was drastically impaired by low purity (