Advancing NGS quality control to enable measurement of actionable mutations in circulating tumor DNA.

The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation.

RNA Immune Signatures from Pan-Cancer Analysis Are Prognostic for High-Grade Serous Ovarian Cancer and Other Female Cancers.

Immune cell infiltrates within the tumor microenvironment can influence treatment response and outcome in several cancers. In this study, we developed RNA-based immune signatures from pan-cancer analysis that could serve as potential markers across tumor types and tested them for association with outcome in high-grade serous ovarian cancer (HGSOC) and other female cancers. Pan-cancer RNA-Seq cluster analysis of immune-related gene expression profiles in The Cancer Genome Atlas (TCGA) from 29 different solid tumors (4446 specimens) identified distinct but concordant gene signatures.

Increased expression of neurotensin in high grade serous ovarian carcinoma with evidence of serous tubal intraepithelial carcinoma.

High grade serous ovarian carcinoma (HGSC) without identifiable serous tubal intraepithelial carcinoma (STIC) within the fallopian tube (FT) occurs in approximately 50% of patients. The objective of this study was to use a multisite tumor sampling approach to study HGSC with and without STIC. RNAseq analysis of HGSC samples collected from multiple sites e.

Tumor mutational burden is a determinant of immune-mediated survival in breast cancer.

Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively).

Clonal lineage of high grade serous ovarian cancer in a patient with neurofibromatosis type 1.

Neurofibromatosis type 1 (NF1) is caused by mutations in the gene encoding neurofibromin, which negatively regulates Ras signaling. NF1 patients have an increased risk of developing early onset breast cancer, however, the association between NF1 and high grade serous ovarian cancer (HGSOC) is unclear. Since most NF1-related tumors exhibit early biallelic inactivation of , we evaluated the evolution of genetic alterations in HGSOC in an NF1 patient.

A B-Cell Gene Signature Correlates With the Extent of Gluten-Induced Intestinal Injury in Celiac Disease.

Background & Aims: Celiac disease (CeD) provides an opportunity to study autoimmunity and the transition in immune cells as dietary gluten induces small intestinal lesions.

Methods: Seventy-three celiac disease patients on a long-term, gluten-free diet ingested a known amount of gluten daily for 6 weeks. A peripheral blood sample and intestinal biopsy specimens were taken before and 6 weeks after initiating the gluten challenge.

Blood-Borne RNA Correlates with Disease Activity and IFN-Stimulated Gene Expression in Systemic Lupus Erythematosus.

The loss of tolerance and the presence of circulating autoantibodies directed against nuclear Ags is the hallmark of systemic lupus erythematosus (SLE). Many of these Ags are complexed with short, noncoding RNAs, such as U1 and Y1. The amount of U1 and Y1 RNA complexed with SLE patient Abs and immune complexes was measured in a cross-section of 228 SLE patients to evaluate the role of these RNA molecules within the known biochemical framework of SLE.

Expression profile of COL2A1 and the pseudogene SLC6A10P predicts tumor recurrence in high-grade serous ovarian cancer.

Tumor recurrence, following initial response to adjuvant chemotherapy, is a major problem in women with high-grade serous ovarian cancer (HGSOC). Microarray analysis of primary tumors has identified genes that may be useful in risk stratification/overall survival, but are of limited value in predicting the >70% rate for tumor recurrence. In this study, we performed RNA-Seq analysis of primary and recurrent HGSOC to first identify unique differentially expressed genes.

A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages.

The rat has been used extensively as a model for evaluating chemical toxicities and for understanding drug mechanisms. However, its transcriptome across multiple organs, or developmental stages, has not yet been reported. Here we show, as part of the SEQC consortium efforts, a comprehensive rat transcriptomic BodyMap created by performing RNA-Seq on 320 samples from 11 organs of both sexes of juvenile, adolescent, adult and aged Fischer 344 rats.

Dysregulation of the epigenome in triple-negative breast cancers: basal-like and claudin-low breast cancers express aberrant DNA hypermethylation.

A subset of human breast cancer cell lines exhibits aberrant DNA hypermethylation that is characterized by hyperactivity of the DNA methyltransferase enzymes, overexpression of DNMT3b, and concurrent methylation-dependent silencing of numerous epigenetic biomarker genes. The objective of this study was to determine if this aberrant DNA hypermethylation (i) is found in primary breast cancers, (ii) is associated with specific breast cancer molecular subtypes, and (iii) influences patient outcomes. Analysis of epigenetic biomarker genes (CDH1, CEACAM6, CST6, ESR1, GNA11, MUC1, MYB, SCNN1A, and TFF3) identified a gene expression signature characterized by reduced expression levels or loss of expression among a cohort of primary breast cancers.

Technical reproducibility of genotyping SNP arrays used in genome-wide association studies.

During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods.

Comparison of comparative genomic hybridization technologies across microarray platforms.

In the 2007 Association of Biomolecular Resource Facilities Microarray Research Group project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation was analyzed using circular binary segmentation (CBS) analysis of log ratio scores from four independently assessed hybridizations of each platform.

Learning from microarray interlaboratory studies: measures of precision for gene expression.

Background: The ability to demonstrate the reproducibility of gene expression microarray results is a critical consideration for the use of microarray technology in clinical applications. While studies have asserted that microarray data can be "highly reproducible" under given conditions, there is little ability to quantitatively compare amongst the various metrics and terminology used to characterize and express measurement performance. Use of standardized conceptual tools can greatly facilitate communication among the user, developer, and regulator stakeholders of the microarray community.

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.

Background: Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature.

DNMT3b overexpression contributes to a hypermethylator phenotype in human breast cancer cell lines.

Background: DNA hypermethylation events and other epimutations occur in many neoplasms, producing gene expression changes that contribute to neoplastic transformation, tumorigenesis, and tumor behavior. Some human cancers exhibit a hypermethylator phenotype, characterized by concurrent DNA methylation-dependent silencing of multiple genes. To determine if a hypermethylation defect occurs in breast cancer, the expression profile and promoter methylation status of methylation-sensitive genes were evaluated among breast cancer cell lines.

DNA methylation-dependent epigenetic regulation of gene expression in MCF-7 breast cancer cells.

To identify epigenetically-regulated genes in breast cancer, MCF-7 cells were exposed to 250 nM 5-aza or 5-aza + 50 nM TSA for three weeks followed by a five week recovery period after treatment withdrawal and gene expression patterns were examined by microarray analysis. We identified 20 genes that are associated with a > or = 2-fold increase in expression in response to the demethylating treatment but returned to control levels after treatment withdrawal. RT-PCR verified that the genes identified were expressed at low or undetectable levels in control MCF-7 cells, but increased expression in treated cells.

DNA methylation-dependent silencing of CST6 in human breast cancer cell lines.

Cystatin M (CST6) is a candidate breast cancer tumor suppressor that is expressed in normal and premalignant breast epithelium, but not in metastatic breast cancer cell lines. CST6 is subject to epigenetic silencing in MCF-7 breast cancer cells related to methylation of the CpG island that encompasses the CST6 proximal promoter region and exon 1. In the current study, CST6 CpG island methylation and expression status was examined in a panel of breast cancer cell lines.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues.

Using RNA sample titrations to assess microarray platform performance and normalization techniques.

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples.