Whole-exome sequencing enables the discovery and assessment of genetic variations linked to rare or complex diseases and is a key tool for the diagnosis of genetic disease, population genome studies, and tumor-normal sequencing protocols used in precision oncology. Although the exome only represents about one percent of the human genome, mutations in these protein-coding regions are highly associated with disease. New advancements in next-generation sequencing and artificial intelligence technologies now allow research beyond clinical diagnosis as WES can also help inform and improve drug discovery, personalized medicine, and reproductive health.

This application note from Singular Genomics presents whole-exome sequencing data generated using the G4, a novel benchtop sequencing platform that enables cost-efficient delivery of eight to 64 exome samples in 16 to 19 hours and fits into existing whole-exome sequencing and analysis workflows.

This application note from Singular Genomics presents RNA sequencing data from the novel G4 Sequencing Platform, which is compatible with existing upstream RNA-seq library prep kits and outputs FASTQ files compatible with existing bioinformatic pipelines, showing the platform to deliver accurate data correlated with the industry standard benchtop sequencer.

Despite its success, current limitations of NGS systems include long analysis times, labor-intensive protocols, extensive sample batching requirements for cost-effective use, and limited choice in instrumentation. There is a need for new DNA sequencing platforms that combine high accuracy, speed, and flexible throughput to provide timely results and cost-effective operation for research and clinical applications.

This technical report from Singular Genomics presents whole-genome sequencing data of a reference human genome, cell line NA12878 from the CEPH Utah Reference collection, using the G4, a new NGS platform from Singular Genomics designed to enable accurate sequencing and faster results to advance the state of the art in clinical and basic research.

Aberrant DNA methylation patterns found in cancer tissue are seen as the first and most persistent phenotypic expression biomarkers. Consequently, there is a major translational research effort to advance cell-free assay technologies for early cancer screening and for clinical diagnostics to support patient monitoring and treatment. However, accurate and precise measurement of methylated DNA markers across the genome or for specific genes that are found in plasma is technically complex and not yet standardized.

This webinar brings together a panel of academic, clinical, and industry experts in the field of methylated DNA testing who will discuss the promises and challenges of early cancer screening. The panel will discuss tissue plasma concordance, preanalytical variables, accurate measurement of methylated and unmethylated DNA, and the use of reference materials to help standardization. 

Our panelists on this session will be Dennis Lo, MD, PhD, Director at the Li Ka Shing Institute of Health Sciences and Li Ka Shing Professor of Medicine at The Chinese University of Hong Kong, Jimmy Lin, MD, PhD, MHS, Chief Scientific Officer at Freenome Company and Yves Konigshofer, PhD, Director of Technology Development at LGC Clinical Diagnostics.

No two cancer patients are the same. Some patients have yet to undergo any treatments, while others have failed multiple lines of treatment. However, no matter what journey a patient has been through, their medical history can impact their eligibility for further treatment opportunities. To avoid recommending patients to clinical trials or therapies they may not be eligible for, GenomOncology includes all prior intervention eligibility data, along with clinical and biomarker data, in its automated treatment matching and identification process.

In this on-demand webinar from GenomOncology, speakers discuss the importance of prior medical interventions in precision oncology, how GenomOncology’s solutions utilize patients’ prior medical interventions and clinical history within its treatment matching algorithm, and a patient case study.

This application note from Tecan presents data supporting the use of the MagicPrep NGS system, which combines automation, software, scripts, reagents, and consumables into a simplified workflow to generate libraries for Illumina sequencing platforms.

For research use only. Not for use in diagnostic procedures.

Large-scale proteomics studies are being increasingly applied to detect and characterize differential protein expression patterns in health and disease. Proteomics has the potential to provide crucial insights for biomarker discovery and drug development. In fact, proteins are the primary target of nearly all drugs currently in development. However, conventional proteomics assays are constrained by a lack of sensitivity, particularly for low abundance proteins, and the inability to detect proteins over a wide range of concentrations. Sensitivity is key for analyzing plasma and serum samples in which only 22 proteins make up approximately 99 percent of the total protein mass, with protein concentrations spanning over 10 orders of magnitude.

This technical note from Olink outlines a protocol to detect thousands of proteins representing major biological pathways simultaneously with high sensitivity and specificity using Olink Explore, a high-throughput protein biomarker discovery platform based on Olink’s Proximity Extension Assay (PEA) technology coupled with NGS readout.

Achieving the goal of precision medicine and more targeted therapeutics will require the use of systems biology approaches to understand the molecular mechanisms at work within the human body. This trend is already apparent in scientific research, with more scientists beginning to use multiomics studies to better understand diseases and to help develop the drugs needed to treat them. To this end, the integration of data from high-throughput proteomics technologies is essential, as proteins best represent individual phenotypes and the effects of environmental and lifestyle factors. In other words, proteins best reflect real-time biology, which is key in developing precision medicine.

This e-book from Olink discusses the integration of proteomics data in multiomics, focusing on how combining genetic data with proteomics help researchers identify proteins that cause disease, how proteomics adds value to multiomics studies on complex diseases, and the future of proteomics in multiomics research.

This white paper from Qiagen discusses use cases for employing QCI Interpret for Oncology clinical decision support software to annotate and interpret co-mutations, genomic changes in associated pathways that may elicit complementary effects and may provide prognostic and predictive value.

This white paper from Qiagen describes tracking ERBB2-targeted therapies using COSMIC Actionability, a feature within the Catalogue of Somatic Mutations in Cancer that indicates the availability of drugs that target mutations in cancer and tracks the progress of clinical studies towards making new drugs available.

This white paper from Qiagen describes the PRKD1 gene and its role in head and neck cancers, as well as how COSMIC, the Catalogue of Somatic Mutations in Cancer, can be used to explore mutations in PRKD1 and other genes related to head and neck cancer.

Genomic reference material (RM) for next-generation sequencing (NGS) has been widely utilized in clinical diagnosis, NGS product development, and patient selection for clinical trials or treatments. To better serve these purposes, RM is expected to have precise allele frequencies (AFs) for all variants contained within. Several methods have been used to quantify AFs during RM development, including droplet digital PCR (dPCR) and NGS. At LGC Clinical Diagnostics, dPCR has been chosen to quantify and finalize the AFs in our genomic RMs because of its proven sensitivity, ease of use, accuracy, and low cost. Customers report consistent satisfaction with the RMs and associated AFs claimed, but as yet, data directly comparing the two technologies are limited.

This white paper from LGC SeraCare describes a study that analyzed data from two different types of genomic reference materials and demonstrates that next-generation sequencing shows a high level of concordance to variant calls generated with droplet digital PCR as the precise allele frequency-defining method.

This case study from Qiagen describes how clinical laboratory geneticists at the Institute for Oncology and Radiology of Serbia use the Human Somatic Mutation Database, or HSMD, which contains curated genomic content relevant to solid tumors and hematological malignancies.

Despite incredible advances in genomics, the NGS data interpretation workflow for hereditary diseases remains challenging. The field is rapidly evolving, and novel findings are uncovered daily, resulting in thousands of new articles on human genetic variants being added each week to PubMed. For genetic testing labs, missing even one article among millions can mean the difference between a diagnosis or an inconclusive result.

This on-demand webinar from Qiagen shows, through a series of use cases, how to maximize the diagnostic yield of hereditary disorders with QCI Interpret, a clinical decision support platform that can streamline the interpretation workflow using a comprehensive collection of up-to-date, manually curated molecular knowledge and bibliography evidence.

In this webinar, you will:

• Learn about QCI Interpret’s analysis and interpretation workflow for hereditary diseases using targeted and extended gene panels, including WES/WGS.
• View demonstrations of unique features in QCI Interpret, including how to input symptoms relevant to a case and receive relationships to candidate diseases and mutated genes using the Phenotype Network Analysis feature.
• Learn how QCI Interpret supports CNV interpretation and reporting with bibliographic coverage of over 60,000 CNV case reports.

Next-generation sequencing (NGS) has revealed comprehensive genomic tumor profiles and showed that the presence of a single somatic mutation can be insufficient to implicate a gene in the development of cancer. While initial studies of somatic mutations focused on the impact of single mutations, researchers are now investigating the cooperative effects induced by multiple mutations arising simultaneously in one tumor. The event of multiple mutations emerging concurrently is referred to as co-mutation or mutation co-occurrence. Co-mutations have been investigated in many tumor types, and studies have suggested that co-mutations might be a core determinant of oncogene-driven cancers.

This white paper from Qiagen presents use cases in acute myeloid leukemia and glioma demonstrating the importance of adequately annotating and interpreting co-mutations in human cancers, and how the presence of co-occurring mutations can inform diagnosis, prognosis, and therapy options.