Advances in precision medicine are transforming cancer diagnosis and treatment. The potential to detect and monitor both solid tumors and blood cancers has spurred aggressive research programs around the world. Liquid biopsy – the analysis of short nucleic acid fragments (150–500 bp) in blood – provides researchers with a unique opportunity to identify and define signatures for specific tumor types. These circulating free DNA (cfDNA) fragments not only offer the potential for earlier detection and diagnosis, but can also measure therapeutic effectiveness and inform treatment decisions.
Cancers present complex biological pathways that vary across tumor types and patients, and not all tumors respond equally to treatment. For example, therapies targeting pathways in highly proliferative or resistant tumors are more efficient and effective. Personalized genomics has therefore opened a groundbreaking path for molecular diagnostics in oncology.
With increasing numbers of diagnostic assays entering the lab, our need to evaluate these tests’ performance is greater than ever – and appropriate controls are essential to calibration, standardization, and routine quality control.
Reference standards used in molecular tests should be well-characterized, stable, homogenous, and mimic the properties intended for use in analytical measurements. Clinical tests aimed at detecting genetic variations by next-generation sequencing (NGS) can introduce errors at various stages of the workflow, from sample preparation to bioinformatic analysis. To support the use of such comprehensive assays and ensure their accuracy, we must use reference standards that closely represent patient samples at each stage of the process.
That’s where cell line-derived controls come in. Cell line-derived materials offer the complexity of the human genome and, when processed into different formats representing a patient sample analyte, serve as a commutable and renewable source of biological controls for assay development and R&D studies. They are comprehensive and, when sufficiently characterized, help establish analytical sensitivity in both quantitative and qualitative measurements.
Every clinical test needs robust controls to ensure reliable results and accurate diagnosis. In lung cancer, for instance, therapeutics tackle at least 10 different disease drivers and elements of the disease pathway – so it’s clear that we need new assays to characterize specific cancer types and ensure each patient receives the best possible treatment for their disease. In addition, when studying rare cancers or novel biomarkers, it can be a challenge to obtain reliable, reproducible controls from patient samples. In both cases, cell line-derived reference standards offer a consistent, accurate, affordable way to design these assays.
Tumor DNA shed into blood constitutes a small fraction of the total cfDNA population, but is proving an important noninvasive biomarker in early cancer diagnosis, progression, and remission. However, the variant allele frequencies (VAFs) of tumor-specific mutations can be much lower in the cfDNA population compared to primary tumors – so accurate detection of low-level (1–10 percent) VAFs in cfDNA requires analytical tools with higher sensitivity and specificity. Careful consideration of the preanalytical workflow, which includes sample collection, storage, and nucleic acid isolation, is also critical to cfDNA quality and quantity. Appropriate quality controls for each step of the workflow reduce errors, aid in calibration to achieve higher purity and quality of extracted cfDNA, and facilitate accurate detection of low-frequency alleles.
Cell line-derived DNA, like patient samples, is genomically complex and thus offers an advantage over synthetic reference materials. It’s also preferable to non-renewable, non-reproducible patient-derived samples. DNA from cell lines can be processed into smaller fragments corresponding to cfDNA fragment profiles and, when well-characterized for physical properties like quality, purity, quantity, and average size, can be used as controls for preanalytical workflows. Genetic profiling of cell line-derived cfDNA can be useful for developing quality controls to validate mutations and their respective allele frequencies in analytical assays. As the medical community increasingly uses NGS assays to inform diagnosis, prognosis, and treatment, cell line-derived controls will be essential to maximizing their utility and effectiveness in improving patient care.
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