1. |
- Fang, Li Tai, et al.
(author)
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Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
- 2021
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In: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1151-1160
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Journal article (peer-reviewed)abstract
- Tumor-normal paired DNA samples from a breast cancer cell line and a matched lymphoblastoid cell line enable calibration of clinical sequencing pipelines and benchmarking 'tumor-only' or 'matched tumor-normal' analyses. 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.
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2. |
- Foox, Jonathan, et al.
(author)
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The SEQC2 epigenomics quality control (EpiQC) study
- 2021
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In: Genome Biology. - : BioMed Central (BMC). - 1465-6906 .- 1474-760X. ; 22:1
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Journal article (peer-reviewed)abstract
- BackgroundCytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA’s Epigenomics Quality Control Group.ResultsEach sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.ConclusionsThe data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.
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3. |
- Gyllensten, Ulf B., et al.
(author)
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Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
- 2022
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In: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
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Journal article (peer-reviewed)abstract
- Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4-7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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4. |
- Kuci Emruli, Venera, et al.
(author)
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Identification of a serum biomarker signature associated with metastatic prostate cancer
- 2021
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In: Proteomics - Clinical Applications. - : Wiley. - 1862-8346 .- 1862-8354. ; 15:2-3
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Journal article (peer-reviewed)abstract
- Purpose: Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease. Experimental design: In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray. Results: A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified. Conclusions and clinical relevance: The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.
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5. |
- Lysenkova Wiklander, Mariya, et al.
(author)
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Genomic, transcriptomic and epigenomic sequencing data of the B-cell leukemia cell line REH
- 2023
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In: BMC Research Notes. - : BioMed Central (BMC). - 1756-0500. ; 16:1
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Journal article (peer-reviewed)abstract
- ObjectivesThe aim of this data paper is to describe a collection of 33 genomic, transcriptomic and epigenomic sequencing datasets of the B-cell acute lymphoblastic leukemia (ALL) cell line REH. REH is one of the most frequently used cell lines for functional studies of pediatric ALL, and these data provide a multi-faceted characterization of its molecular features. The datasets described herein, generated with short- and long-read sequencing technologies, can both provide insights into the complex aberrant karyotype of REH, and be used as reference datasets for sequencing data quality assessment or for methods development.Data descriptionThis paper describes 33 datasets corresponding to 867 gigabases of raw sequencing data generated from the REH cell line. These datasets include five different approaches for whole genome sequencing (WGS) on four sequencing platforms, two RNA sequencing (RNA-seq) techniques on two different sequencing platforms, DNA methylation sequencing, and single-cell ATAC-sequencing.
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6. |
- Verardo, Damiano, et al.
(author)
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Fluorescence Signal Enhancement in Antibody Microarrays Using Lightguiding Nanowires
- 2021
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In: Nanomaterials. - : MDPI AG. - 2079-4991. ; 11:1, s. 1-11
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Journal article (peer-reviewed)abstract
- Fluorescence-based detection assays play an essential role in the life sciences and medicine. To offer better detection sensitivity and lower limits of detection (LOD), there is a growing need for novel platforms with an improved readout capacity. In this context, substrates containing semiconductor nanowires may offer significant advantages, due to their proven light-emission enhancing, waveguiding properties, and increased surface area. To demonstrate and evaluate the potential of such nanowires in the context of diagnostic assays, we have in this work adopted a well-established single-chain fragment antibody-based assay, based on a protocol previously designed for biomarker detection using planar microarrays, to freestanding, SiO2-coated gallium phosphide nanowires. The assay was used for the detection of protein biomarkers in highly complex human serum at high dilution. The signal quality was quantified and compared with results obtained on conventional flat silicon and plastic substrates used in the established microarray applications. Our results show that using the nanowire-sensor platform in combination with conventional readout methods, improves the signal intensity, contrast, and signal-to-noise by more than one order of magnitude compared to flat surfaces. The results confirm the potential of lightguiding nanowires for signal enhancement and their capacity to improve the LOD of standard diagnostic assays.
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7. |
- Xiao, Wenming, et al.
(author)
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Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing
- 2021
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In: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1141-1150
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Journal article (peer-reviewed)abstract
- Recommendations are given on optimal read coverage and selection of calling algorithm to maximize the reproducibility of cancer mutation detection in whole-genome or whole-exome sequencing. 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.
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8. |
- Zhao, Yongmei, et al.
(author)
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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
- 2021
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- 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.
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