The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic variants. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Lentiviral vectors (LV) have proven to be powerful tools for stable gene delivery in both dividing and non-dividing cells. Approval of these LVs for use in clinical applications has been achieved by improvements in LV design. Critically important characteristics concerning quality control are LV titer quantification and the detection of impurities. However, increasing evidence concerning high variability in titration assays indicates poor harmonization of the methods undertaken to date. In this study, we developed a direct reverse transcription droplet digital PCR (Direct RT-ddPCR) approach without RNA extraction and purification for estimation of LV titer and RNA genome integrity. The RNA genome integrity was assessed by RT-ddPCR assays targeted to four distant regions of the LV genome. Results of the analyses showed that direct RT-ddPCR without RNA extraction and purification performs similarly to RT-ddPCR on purified RNA from 3 different LV samples, in terms of robustness and assay variance. Interestingly, these RNA titer results were comparable to physical titers by p24 antigen ELISA (enzyme-linked immunosorbent assay). Moreover, we confirmed the partial degradation or the incomplete RNA genomes in the prepared 3 LV samples. These results may partially explain the discrepancy of the LV particle titers to functional titers. This work not only demonstrates the feasibility of direct RT-ddPCR in determining LV titers, but also provides a method that can be easily adapted for RNA integrity assessment.

The National Institute of Standards and Technology (NIST) is developing analytical methods to characterize extracellular vesicles (EVs) to support the urgent need for standardized EV reference materials (RMs). This study used orthogonal techniques, cryogenic electron microscopy (Cryo-EM), particle tracking analysis (PTA), asymmetrical flow field-flow fractionation (AF⁴), and microfluidic resistive pulse sensing (MRPS), to evaluate particle size distributions (PSDs) and particle number concentrations (PNCs) of human mesenchymal stem cells (MSCs) and LNCaP prostate cancer cell EVs. Proteomic profiles were assessed by mass spectrometry (MS), and microRNA (miRNA) content of LNCaP EVs was evaluated by small RNA-seq at two independent laboratories. A commercial green fluorescent protein exosome served as a control, except in Cryo-EM, proteomic, and miRNA analyses. Cryo-EM, regarded as the gold standard for morphological resolution, served as PSD reference. PSDs from all methods skewed larger than Cryo-EM, with MRPS closest, AF⁴ most divergent, and PTA intermediate with broader distributions. All techniques reported broad PSDs (30 nm to >350 nm) with PNCs decreasing with increasing particle size, except for AF⁴. Quantitative discrepancies in PNCs reached up to two orders of magnitude across methods and cell sources. MS identified global and EV-specific proteins, including syntenin-1 and tetraspanins CD9, CD63, and CD81. RNA-seq revealed notable inter-laboratory variation. These findings highlight the variability across measurement platforms and emphasize the need for reproducible methods to support NIST’s mission of developing reliable EV reference materials.

While lentiviral vectors have played a critical role in the emergence of gene-modified cell therapies, safety concerns remain regarding potential insertional mutagenesis. Regulatory authorities strongly recommend risk assessment and management of vector copy numbers (VCNs), integration profiles, and integration sites in the lentivirus-based cell and gene therapy products. However, accurately measuring these parameters remains a significant challenge due to the lack of standardized methodologies and VCN reference materials (RMs). Toward this challenge, we conducted an interlaboratory study on NIST candidate RMs for VCN measurements. The candidate RMs comprise five human genomic DNA samples or fixed cells from clonal Jurkat cell lines with defined VCNs ranging from 0 to 4. All 12 study participants were able to identify the VCN in the five blinded samples using quantitative PCR (qPCR), digital PCR (dPCR), or next generation sequencing (NGS) assays. Consensus value of VCN and integration sites in these candidate RMs were achieved. The fixed clonal VCN cells were also used to evaluate an emerging imaging-based technology called molecular combing. This interlaboratory assessment demonstrated the utility, commutability, and suitability of the NIST VCN candidate RMs for quality assurance and improved confidence in VCN, integration profile, and integration site measurements.

Summary: Genomic changes are central to cancer, so sequencing is essential for understanding tumor evolution and advancing precision medicine, but resolving somatic variants and methylation is challenging in regions with repeats, reference gaps, and germline variants. ^1–4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage, broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. ⁵ The tumor assembly recapitulates all 35 chromosomes observed by karyotyping, including translocation-induced hybrid chromosomes containing dynamic dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single derivative chromosome, and centromeric satellite tandem duplications up to 136 kbp. Our tumor-normal assembly-based benchmark expands previous multi-technology ensemble benchmark approaches, adding >8,000 somatic small variants altering ∼40 kbp and 149 somatic SVs altering 939 kbp, including 2,764 small variants and 126 SVs not represented on GRCh38. Additionally, 5,111 somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures. Most source-resolved somatic LINE insertions originate from two non-reference germline LINE insertions with accessible promoter elements. These assemblies demonstrate that centromeric, acrocentric, telomeric, and other polymorphic regions, conventionally excluded from analysis, harbor extensive somatic and epigenetic changes and provide curated paired tumor-normal benchmarks to advance algorithms for repetitive regions of cancer genomes.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line (HG008-T) and matched normal cells from duodenal tissue (HG008-N-D) and pancreatic tissue (HG008-N-P). The data come from thirteen whole genome measurement technologies: Illumina paired-end, Element standard and long insert, Ultima UG100, PacBio (HiFi and Onso), Oxford Nanopore (standard and ultra-long), Bionano Optical Mapping, Arima and Phase Genomics Hi-C, G-banded karyotyping, directional genomic hybridization, and BioSkryb Genomics single-cell ResolveDNA. Most tumor data is from a large homogenous batch of non-viable cells after 23 passages of the primary tumor cells, along with some data from different passages to enable an initial understanding of genomic instability. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. In addition, extensive data from two different normal tissues from the same individual can enable understanding of mosaicism. Long reads also contain methylation tags for epigenetic analyses. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.