Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.

As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings. Here, we describe a framework for generating, validating and incorporating data from MAVEs into a semi-quantitative variant classification method applied to clinical genetic testing. Using single-cell gene expression measurements, cellular evidence models were built to assess the effects of DNA variation in 44 genes of clinical interest. This framework was also applied to models for an additional 22 genes with previously published MAVE datasets. In total, modeling data was incorporated from 24 genes into our variant classification method. These data contributed evidence for classifying 4043 observed variants in over 57,000 individuals. Genetic testing laboratories are uniquely positioned to generate, analyze, validate, and incorporate evidence from high-throughput functional data and ultimately enable the use of these data to provide definitive clinical variant classifications for more patients.

High-throughput sequencing technologies.

The human genome sequence has profoundly altered our understanding of biology, human diversity, and disease. The path from the first draft sequence to our nascent era of personal genomes and genomic medicine has been made possible only because of the extraordinary advancements in DNA sequencing technologies over the past 10 years. Here, we discuss commonly used high-throughput sequencing platforms, the growing array of sequencing assays developed around them, as well as the challenges facing current sequencing platforms and their clinical application.

Simul-seq: combined DNA and RNA sequencing for whole-genome and transcriptome profiling.

Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. Here, we introduce Simul-seq, a technique for the production of high-quality whole-genome and transcriptome sequencing libraries from small quantities of cells or tissues. We apply the method to laser-capture-microdissected esophageal adenocarcinoma tissue, revealing a highly aneuploid tumor genome with extensive blocks of increased homozygosity and corresponding increases in allele-specific expression. Among this widespread allele-specific expression, we identify germline polymorphisms that are associated with response to cancer therapies. We further leverage this integrative data to uncover expressed mutations in several known cancer genes as well as a recurrent mutation in the motor domain of KIF3B that significantly affects kinesin-microtubule interactions. Simul-seq provides a new streamlined approach for generating comprehensive genome and transcriptome profiles from limited quantities of clinically relevant samples.

DNMT1 maintains progenitor function in self-renewing somatic tissue.

Progenitor cells maintain self-renewing tissues throughout life by sustaining their capacity for proliferation while suppressing cell cycle exit and terminal differentiation. DNA methylation provides a potential epigenetic mechanism for the cellular memory needed to preserve the somatic progenitor state through repeated cell divisions. DNA methyltransferase 1 (DNMT1) maintains DNA methylation patterns after cellular replication. Although dispensable for embryonic stem cell maintenance, the role for DNMT1 in maintaining the progenitor state in constantly replenished somatic tissues, such as mammalian epidermis, is unclear. Here we show that DNMT1 is essential for epidermal progenitor cell function. DNMT1 protein was found enriched in undifferentiated cells, where it was required to retain proliferative stamina and suppress differentiation. In tissue, DNMT1 depletion led to exit from the progenitor cell compartment, premature differentiation and eventual tissue loss. Genome-wide analysis showed that a significant portion of epidermal differentiation gene promoters were methylated in self-renewing conditions but were subsequently demethylated during differentiation. Furthermore, UHRF1 (refs 9, 10), a component of the DNA methylation machinery that targets DNMT1 to hemi-methylated DNA, is also necessary to suppress premature differentiation and sustain proliferation. In contrast, Gadd45A and B, which promote active DNA demethylation, are required for full epidermal differentiation gene induction. These data demonstrate that proteins involved in the dynamic regulation of DNA methylation patterns are required for progenitor maintenance and self-renewal in mammalian somatic tissue.

Use of conditionally active ras fusion proteins to study epidermal growth, differentiation, and neoplasia.

Ras proteins are membrane-bound GTPases that play a central role in transmitting signals from the cell surface to the nucleus and affect a wide array of biological processes. The overall cellular response to Ras activation varies with cell type, experimental conditions, signal strength, and signal duration. Most current studies, however, rely on expression of constitutively active protein to study Ras function and thus ignore temporal variables, as well as signal strength. These experiments may provide contradictory results, as seen in the case of epidermal keratinocytes. In this setting, Ras has been shown to both promote and oppose proliferation and differentiation. By providing control over timing, duration, and signal magnitude, conditional systems allow for more precise investigation of the role of Ras in carcinogenesis, as well as normal cellular physiology. This chapter focuses on use of a ligand-responsive steroid hormone receptor fusion of Ras, ER-Ras, to study aspects of cellular transformation in epidermal keratinocytes.

Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations.

Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼ 15% of specific tumor types. SMRs demonstrate spatial clustering of alterations in molecular domains and at interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated across tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest that mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally agnostic driver identification.

Recurrent somatic mutations in regulatory regions of human cancer genomes.

Aberrant regulation of gene expression in cancer can promote survival and proliferation of cancer cells. Here we integrate whole-genome sequencing data from The Cancer Genome Atlas (TCGA) for 436 patients from 8 cancer subtypes with ENCODE and other regulatory annotations to identify point mutations in regulatory regions. We find evidence for positive selection of mutations in transcription factor binding sites, consistent with these sites regulating important cancer cell functions. Using a new method that adjusts for sample- and genomic locus-specific mutation rates, we identify recurrently mutated sites across individuals with cancer. Mutated regulatory sites include known sites in the TERT promoter and many new sites, including a subset in proximity to cancer-related genes. In reporter assays, two new sites display decreased enhancer activity upon mutation. These data demonstrate that many regulatory regions contain mutations under selective pressure and suggest a greater role for regulatory mutations in cancer than previously appreciated.

Modeling inducible human tissue neoplasia identifies an extracellular matrix interaction network involved in cancer progression.

To elucidate mechanisms of cancer progression, we generated inducible human neoplasia in three-dimensionally intact epithelial tissue. Gene expression profiling of both epithelia and stroma at specific time points during tumor progression revealed sequential enrichment of genes mediating discrete biologic functions in each tissue compartment. A core cancer progression signature was distilled using the increased signaling specificity of downstream oncogene effectors and subjected to network modeling. Network topology predicted that tumor development depends on specific extracellular matrix-interacting network hubs. Blockade of one such hub, the beta1 integrin subunit, disrupted network gene expression and attenuated tumorigenesis in vivo. Thus, integrating network modeling and temporal gene expression analysis of inducible human neoplasia provides an approach to prioritize and characterize genes functioning in cancer progression.

Intracellular delivery of functional proteins via decoration with transporter peptides.

Despite numerous attractive intracellular targets, protein therapeutics have been principally confined to the extracellular space due to the lack of a straightforward way to deliver functional polypeptides to the cell interior. Peptide sequences facilitating intracellular protein delivery have been identified; however, current strategies to apply them require problematic steps, such as generation of new in-frame fusion proteins, covalent chemical conjugation, and denaturation. We have developed a new approach to protein transfer into cells and tissues that relies on single-step decoration by cysteine-flanked, arginine-rich transporter peptides. This approach facilitated cell and tissue delivery of a variety of functional proteins, including antibodies and enzymes. Decoration with transporter peptides thus provides an attractive general means of intracellular delivery of functional proteins in vitro and in tissue.