Genes and Pathways Implicated in Tetralogy of Fallot Revealed by Ultra-Rare Variant Burden Analysis in 231 Genome Sequences.

Recent genome-wide studies of rare genetic variants have begun to implicate novel mechanisms for tetralogy of Fallot (TOF), a severe congenital heart defect (CHD). To provide statistical support for case-only data without parental genomes, we re-analyzed genome sequences of 231 individuals with TOF (n = 175) or related CHD. We adapted a burden test originally developed for de novo variants to assess ultra-rare variant burden in individual genes, and in gene-sets corresponding to functional pathways and mouse phenotypes, accounting for highly correlated gene-sets and for multiple testing. For truncating variants, the gene burden test confirmed significant burden in FLT4 (Bonferroni corrected p-value < 0.01). For missense variants, burden in NOTCH1 achieved genome-wide significance only when restricted to constrained genes (i.e., under negative selection, Bonferroni corrected p-value = 0.004), and showed enrichment for variants affecting the extracellular domain, especially those disrupting cysteine residues forming disulfide bonds (OR = 39.8 vs. gnomAD). Individuals with NOTCH1 ultra-rare missense variants, all with TOF, were enriched for positive family history of CHD. Other genes not previously implicated in CHD had more modest statistical support in gene burden tests. Gene-set burden tests for truncating variants identified a cluster of pathways corresponding to VEGF signaling (FDR = 0%), and of mouse phenotypes corresponding to abnormal vasculature (FDR = 0.8%); these suggested additional candidate genes not previously identified (e.g., WNT5A and ZFAND5). Results for the most promising genes were driven by the TOF subset of the cohort. The findings support the importance of ultra-rare variants disrupting genes involved in VEGF and NOTCH signaling in the genetic architecture of TOF, accounting for 11-14% of individuals in the TOF cohort. These proof-of-principle data indicate that this statistical methodology could assist in analyzing case-only sequencing data in which ultra-rare variants, whether de novo or inherited, contribute to the genetic etiopathogenesis of a complex disorder.

A three-gene DNA methylation biomarker accurately classifies early stage prostate cancer.

BACKGROUND: We identify and validate accurate diagnostic biomarkers for prostate cancer through a systematic evaluation of DNA methylation alterations. MATERIALS AND METHODS: We assembled three early prostate cancer cohorts (total patients = 699) from which we collected and processed over 1300 prostatectomy tissue samples for DNA extraction. Using real-time methylation-specific PCR, we measured normalized methylation levels at 15 frequently methylated loci. After partitioning sample sets into independent training and validation cohorts, classifiers were developed using logistic regression, analyzed, and validated. RESULTS: In the training dataset, DNA methylation levels at 7 of 15 genomic loci (glutathione S-transferase Pi 1 [GSTP1], CCDC181, hyaluronan, and proteoglycan link protein 3 [HAPLN3], GSTM2, growth arrest-specific 6 [GAS6], RASSF1, and APC) showed large differences between cancer and benign samples. The best binary classifier was the GAS6/GSTP1/HAPLN3 logistic regression model, with an area under these curves of 0.97, which showed a sensitivity of 94%, and a specificity of 93% after external validation. CONCLUSION: We created and validated a multigene model for the classification of benign and malignant prostate tissue. With false positive and negative rates below 7%, this three-gene biomarker represents a promising basis for more accurate prostate cancer diagnosis.

Reliability and performance of commercial RNA and DNA extraction kits for FFPE tissue cores.

Cancer biomarker studies often require nucleic acid extraction from limited amounts of formalin-fixed, paraffin-embedded (FFPE) tissues, such as histologic sections or needle cores. A major challenge is low quantity and quality of extracted nucleic acids, which can limit our ability to perform genetic analyses, and have a significant influence on overall study design. This study was aimed at identifying the most reliable and reproducible method of obtaining sufficient high-quality nucleic acids from FFPE tissues. We compared the yield and quality of nucleic acids from 0.6-mm FFPE prostate tissue cores across 16 DNA and RNA extraction protocols, using 14 commercially available kits. Nucleic acid yield was determined by fluorometry, and quality was determined by spectrophotometry. All protocols yielded nucleic acids in quantities that are compatible with downstream molecular applications. However, the protocols varied widely in the quality of the extracted RNA and DNA. Four RNA and five DNA extraction protocols, including protocols from two kits for dual-extraction of RNA and DNA from the same tissue source, were prioritized for further quality assessment based on the yield and purity of their products. Specifically, their compatibility with downstream reactions was assessed using both NanoString nCounter gene expression assays and reverse-transcriptase real-time PCR for RNA, and methylation-specific PCR assays for DNA. The kit deemed most suitable for FFPE tissue was the AllPrep kit by Qiagen because of its yield, quality, and ability to purify both RNA and DNA from the same sample, which would be advantageous in biomarker studies.

Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction.

Formalin-fixed paraffin embedded tissue (FFPET) represents a valuable, well-annotated substrate for molecular investigations. The utility of FFPET in molecular analysis is complicated both by heterogeneous tissue composition and low yields when extracting nucleic acids. A literature search revealed a paucity of protocols addressing these issues, and none that showed a validated method for simultaneous extraction of RNA and DNA from regions of interest in FFPET. This method addresses both issues. Tissue specificity was achieved by mapping cancer areas of interest on microscope slides and transferring annotations onto FFPET blocks. Tissue cores were harvested from areas of interest using 0.6 mm microarray punches. Nucleic acid extraction was performed using a commercial FFPET extraction system, with modifications to homogenization, deparaffinization, and Proteinase K digestion steps to improve tissue digestion and increase nucleic acid yields. The modified protocol yields sufficient quantity and quality of nucleic acids for use in a number of downstream analyses, including a multi-analyte gene expression platform, as well as reverse transcriptase coupled real time PCR analysis of mRNA expression, and methylation-specific PCR (MSP) analysis of DNA methylation.

Quantitative assessment of the sensitivity of various commercial reverse transcriptases based on armored HIV RNA.

BACKGROUND: The in-vitro reverse transcription of RNA to its complementary DNA, catalyzed by the enzyme reverse transcriptase, is the most fundamental step in the quantitative RNA detection in genomic studies. As such, this step should be as analytically sensitive, efficient and reproducible as possible, especially when dealing with degraded or low copy RNA samples. While there are many reverse transcriptases in the market, all claiming to be highly sensitive, there is need for a systematic independent comparison of their applicability in quantification of rare RNA transcripts or low copy RNA, such as those obtained from archival tissues. METHODOLOGY/PRINCIPAL FINDINGS: We performed RT-qPCR to assess the sensitivity and reproducibility of 11 commercially available reverse transcriptases in cDNA synthesis from low copy number RNA levels. As target RNA, we used a serially known number of Armored HIV RNA molecules, and observed that 9 enzymes we tested were consistently sensitive to ∼1,000 copies, seven of which were sensitive to ∼100 copies, while only 5 were sensitive to ∼10 RNA template copies across all replicates tested. Despite their demonstrated sensitivity, these five best performing enzymes (Accuscript, HIV-RT, M-MLV, Superscript III and Thermoscript) showed considerable variation in their reproducibility as well as their overall amplification efficiency. Accuscript and Superscript III were the most sensitive and consistent within runs, with Accuscript and Superscript II ranking as the most reproducible enzymes between assays. CONCLUSIONS/SIGNIFICANCE: We therefore recommend the use of Accuscript or Superscript III when dealing with low copy number RNA levels, and suggest purification of the RT reactions prior to downstream applications (eg qPCR) to augment detection. Although the results presented in this study were based on a viral RNA surrogate, and applied to nucleic acid lysates derived from archival formalin-fixed paraffin embedded tissue, their relative performance on RNA obtained from other tissue types may vary, and needs future evaluation.