Comprehensive Genomic Profiling (CGP) is a method of cancer diagnosis and prognosis that uses genomic information to determine treatment plans. CGP is an important tool in cancer care, given that cancer is the second leading cause of death in the US and is understood to be a disease of the genome. Assessing the clinical utility of CGP is complex given the increasing number of genomic markers it identifies, resulting in challenges for US healthcare payers who have to navigate these complexities in their coverage policies.

Evaluating CGP on a gene-by-gene basis is not sustainable, and coverage policies are gradually shifting to consider CGP as a holistic process, despite the challenges posed by the expanding number of genes included and a dynamic evidence base. There is also a need for alternative evidence models to demonstrate the value of CGP, including real-world data and value-based models of evidence. This may foster better collaboration between payors, health systems, biopharma, patient advocates, and other stakeholders throughout the healthcare system.

This white paper explores the evolving dialogue around CGP between payers, health systems, biopharma, patient advocates, and other stakeholders, including the complexities of assessing the clinical utility of large cancer panels and new models to demonstrate the value of comprehensive testing.

Whole-exome sequencing (WES) is a cost-effective method for translational cancer research, as it enables the detection of rare gene variations and the discovery of new cancer biomarkers. Despite the significant contributions of genome-wide association studies, linkage analysis, and candidate gene mutation screening approaches to understanding hereditary cancers, over 50 percent of hereditary cancer risk remains unexplained, implying the need for further investigation into rarer genetic susceptibility alleles. WES provides a comprehensive approach to uncovering missing heritability in hereditary cancers, helping to determine if the majority of missing heritability is due to rare genetic variants. WES analysis poses challenges in variant interpretation, which may lead to missing important variants if not done properly. QIAGEN Digital Insights offers QCI Interpret Translational, a comprehensive tool that translates raw sequencing data into meaningful, interpretable results. This application note from Qiagen explains how this next-generation sequencing (NGS) variant assessment software solution enables rapid, evidence-powered variant annotation, filtering, and triage for human exome, genome, and large cohort sequencing data. By addressing the challenges of WES analysis, this tool empowers researchers to decipher which detected variants have functional significance and which are irrelevant to the phenotype in question.

Long-read sequencing technology has enabled the detection and characterization of structural variations (SVs) at a higher resolution than ever before, including deletions, insertions, duplications, inversions, and translocations, with significant impacts on gene expression and disease development. The technology generates tens of thousands of base pair-long reads, allowing for the detection of larger SVs that may be missed by short-read sequencing. Although challenges such as the high error rate remain, the benefits of haplotype-resolved assemblies and accurate detection of SVs have already led to new insights into the genomic basis of diseases such as cancer, autism, and schizophrenia. Long-read sequencing has the potential to greatly improve our understanding of health and disease.

This white paper from Geneyx introduces the use of long-read sequencing for the detection of structural variants, the technologies behind long-read sequencing, the performance characteristics of long-read sequencing for structural variant detection, and the advantages of long reads for understanding genomic diversity and disease.

Pharmacogenomics (PGx) is a field of medicine that studies the association between genetic variations and drug metabolism. PGx provides valuable insights into how individuals metabolize drugs, which can impact the effectiveness of medications and increase the risk of side effects. The adoption of PGx in clinical and diagnostic environments is gaining traction as knowledgebases and novel genetic insights continue to improve.

This white paper from Geneyx describes pharmacogenomics, gives examples of genes that impact drug metabolism, discusses the accuracy of PGx tests and the value of testing, gives examples of PGx applications in clinical practice, and discusses PGx in drug discovery and development.

This white paper from Geneyx describes the importance of genetic screening, types of inherited genetic disorders, genetic testing methods used for carrier screening, ethical issues surrounding carrier screening, and future directions.

Numerous clinical decision support systems and knowledgebases have been developed to assist variant scientists and laboratory directors with the task of variant classification. These private and commercially available systems utilize varying degrees of software automation and manually curated literature to provide variant assessment and therapy matching for clinicians. The body of literature that must be accessed to deliver accurate variant interpretation is vast and there is debate in the field as to the most accurate and efficient approach.

This white paper from Qiagen describes a study demonstrating that clinical decision support tools can help to reliably streamline and standardize somatic variant interpretation and address the high degree of variability among experts in somatic clinical interpretation.

The new era of personalized health relies on data to guide more personalized patient treatments, therapeutics, diagnostics, and patient care. Across clinical and research disciplines, leading healthcare and life sciences organizations are combining varying data modalities to increase the accuracy of diagnoses, reduce turnaround times, and ultimately improve patient outcomes.

This white paper from Amazon Web Services presents case studies in which companies, hospitals, and organizations partnered with AWS for Health to unify analysis of various forms of medical and omics data and help researchers and clinicians generate new insights and offer more personalized care.

This white paper from PINC AI discusses the causes of health inequities and how equity may be advanced through innovative and collaborative solutions that address the underlying systemic issues that contribute to inequities, and it describes a case study in which PINC AI collaborated with Henry Ford Health to develop solutions.

Mutations in BRCA1 and BRCA2 tumor-suppressor genes account for a significant portion of hereditary breast and ovarian cancer cases. Among them, large genomic rearrangements (LGRs) involving a loss or gain of partial complete BRCA exon(s) are responsible for up to 27 percent of all BRCA disease-causing mutations identified. However, these LGRs are frequently missed using both PCR-based methods and targeted NGS assays.

Given the difficulty in detecting LGRs, there is a need for a comprehensive BRCA1/2 testing algorithm including reference materials that incorporate pathogenic BRCA1/2 LGRs to support NGS assays that identify these mutations at both germline and somatic levels. Clinical studies have demonstrated that pathogenic BRCA1/2 mutations sensitized patients to platinum-based chemotherapy and PARP inhibitors. Current guidelines increasingly recommend BRCA testing in management and therapy selection. Accurate detection of BRCA1 or BRCA2 pathogenic variants is therefore critical in breast and ovarian cancer therapy as well as clinical management of disease including patients who are eligible for new PARP inhibitors.

This poster from LGC SeraCare describes the development and validation of reference material to support BRCA1 and BRCA2 gene testing, the first to include 10 LGRs, which will be useful in evaluating the ability to detect challenging LGRs and support PARP inhibitor treatment of patients with breast and ovarian cancers.

Epigenetic modifications such as methylation influence cellular differentiation and gene expression. Liquid biopsies are starting to screen for cancer-derived DNA by looking for unexpected epigenetic modifications in circulating cell-free DNA (ccfDNA) that could also be used to assign a tissue of origin to the cancer to direct confirmatory diagnostic procedures. However, because of the low abundance of ccfDNA, obtaining sufficient amounts for assay development, validation, and proficiency testing are difficult. Furthermore, methods of analyzing the epigenetic modifications, such as bisulfite conversion, can damage a significant fraction of the input material; but, failing to carry them out to completion can result in an overestimation of methylation. This makes method optimization very important.

This poster from LGC SeraCare describes the creation and validation of circulating cell-free DNA reference materials with defined amounts of methylation to address the challenges associated with assessing the methylation of circulating cell-free DNA.

Homologous recombination deficiency (HRD) arises due to a defect in DNA repair and serves as an important therapeutic biomarker. NGS assays that measure HRD status via genomic instability are used to stratify ovarian and breast cancer patients and determine eligibility for clinical trials as well as PARP inhibitor and platinum-based therapies. Testing is performed on FFPE biopsied tissue, and, despite the challenges of this sample type and the complexity of analysis, there are currently no commercially available HRD reference materials that enable standardization between assays.

This poster from LGC SeraCare describes the development and validation of reference materials to aid in developing and validating NGS-based HRD assays and for quality control monitoring of genomic instability scores.

Advances in next-generation sequencing are enabling larger panel sizes and increased sensitivities for liquid biopsies. These advances lead to a need for patient-like reference materials with more clinically relevant alterations at lower levels than before. To address this need, LGC SeraCare generated novel circulating tumor DNA (ctDNA) reference materials that combine much of the content of Seraseq ctDNA reference materials and add additional variants and copy number alterations. Because limits of detection of individual mutations are now at or below 0.2 percent variant allele frequency in some ctDNA assays, SeraCare also reduced the lowest VAF from 0.1 percent to 0.01 percent.

This poster from LGC SeraCare provides data on the initial testing of new circulating tumor DNA reference materials that incorporate updated clinically relevant alterations and copy number variants with the lowest variant allele frequency reduced from 0.1 percent to 0.01 percent to accommodate larger NGS panels with increased sensitivities.

Myeloid malignancies are characterized by excessive proliferation, abnormal self-renewal, and differentiation defects of hematopoietic stem cells and myeloid progenitor cells. The detection of these types of malignancies using traditional procedures by obtaining bone marrow samples is invasive and risky. Hence, liquid biopsy-based methods are in high demand to monitor and detect new cases of blood cancer.

This poster from LGC SeraCare summarizes the development of ctDNA myeloid reference materials — a purified mix of 25 myeloid DNA variants that were blended against a wild-type background — for the development, validation, and clinical application of targeted NGS assays as well as digital PCR-based assays that analyze for myeloid diseases in cancer patients.

Predictive biomarkers help to identify tumors that are most likely to benefit from a specific treatment and spare patients from toxic effects of ineffective therapies. Both genetic mutations and protein levels in diseased tissues are examples of predictive biomarkers, yet few platforms enable the simultaneous evaluation of both RNA and protein.

The GeoMx Digital Spatial Profiler (DSP) from NanoString provides morphological context in spatial transcriptomics and spatial proteomics experiments for immuno-oncology research. The GeoMx DSP platform can investigate novel biomarkers in tissue samples because it offers digital profiling of protein and RNA analytes on the same slide.

This application note from Canopy Biosciences, a Center of Excellence for NanoString services, outlines a recent study that used the GeoMx DSP to investigate novel biomarkers associated with beneficial PD-1 therapy in formalin-fixed, paraffin-embedded samples from patients with non-small cell lung cancer.

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.