Transcriptional regulation by methyltransferases and their role in the heart: highlighting novel emerging functionality

Methyltransferases are a superfamily of enzymes that transfer methyl groups to proteins, nucleic acids, and small molecules. Traditionally, these enzymes have been shown to carry out a specific modification (mono-, di-, or trimethylation) on a single, or limited number of, amino acid(s). The largest subgroup of this family, protein methyltransferases, target arginine and lysine side chains of histone molecules to regulate gene expression. Although there is a large number of functional studies that have been performed on individual methyltransferases describing their methylation targets and effects on biological processes, no analyses exist describing the spatial distribution across tissues or their differential expression in the diseased heart. For this review, we performed tissue profiling in protein databases of 199 confirmed or putative methyltransferases to demonstrate the unique tissue-specific expression of these individual proteins. In addition, we examined transcript data sets from human heart failure patients and murine models of heart disease to identify 40 methyltransferases in humans and 15 in mice, which are differentially regulated in the heart, although many have never been functionally interrogated. Lastly, we focused our analysis on the largest subgroup, that of protein methyltransferases, and present a newly emerging phenomenon in which 16 of these enzymes have been shown to play dual roles in regulating transcription by maintaining the ability to both activate and repress transcription through methyltransferase-dependent or -independent mechanisms. Overall, this review highlights a novel paradigm shift in our understanding of the function of histone methyltransferases and correlates their expression in heart disease.

Spatial tissue profiling by imaging-free molecular tomography

Genomics techniques are currently being adapted to provide spatially resolved omics profiling. However, the adaptation of each new method typically requires the setup of specific detection strategies or specialized instrumentation. A generic approach to spatially resolve different types of high throughput data is missing. Here, we describe an imaging-free framework to localize high throughput readouts within a tissue by combining compressive sampling and image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (STRP-seq) and validated this method with a transcriptome profiling of the murine brain. To verify the broad applicability of STRP-seq, we applied the technique on the brain of the Australian bearded dragon Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. Overall, the proposed framework constitutes a new approach that allows upgrading in a generic fashion conventional genomic assays to spatially resolved techniques.

Prospective Clinical Validation of the InVisionFirst-Lung Circulating Tumor DNA Assay for Molecular Profiling of Patients With Advanced Nonsquamous Non–Small-Cell Lung Cancer

PURPOSE Guidelines advocate molecular profiling in the evaluation of advanced non–small-cell lung cancer (NSCLC) and support the use of plasma circulating tumor DNA (ctDNA)-based profiling for patients with insufficient tissue. Thorough prospective clinical validation studies of next-generation sequencing (NGS)-based ctDNA assays are lacking. We report the multicentered prospective clinical validation of the InVision ctDNA assay in patients with advanced untreated NSCLC. METHODS A total of 264 patients with untreated advanced NSCLC were prospectively recruited, and their plasma was analyzed using a ctDNA NGS assay for detection of genomic alterations in 36 commonly mutated genes. Tumor tissue was available in 178 patients for molecular profiling for comparison with plasma profiling. The remaining 86 patients were included to compare ctDNA profiles in patients with and without tissue for profiling. RESULTS Concordance of InVisionFirst with matched tissue profiling was 97.8%, with 82.9% positive predictive value, 98.5% negative predictive value, 70.6% sensitivity, and 99.2% specificity. Considering specific alterations in eight genes that most influence patient management, the positive predictive value was 97.8%, with 97.1% negative predictive value, 73.9% sensitivity, and 99.8% specificity. Across the entire study, 48 patients with actionable alterations were identified by ctDNA testing compared with only 38 by tissue testing. ctDNA NGS reported either an actionable alteration or an alteration generally considered mutually exclusive for such actionable changes in 53% of patients. CONCLUSION The liquid biopsy NGS assay demonstrated excellent concordance with tissue profiling in this multicenter, prospective, clinical validation study, with sensitivity and specificity equivalent to Food and Drug Administration–approved single-gene ctDNA assays. The use of plasma-based molecular profiling using NGS led to the detection of 26% more actionable alterations compared with standard-of-care tissue testing in this study.