Update on molecular companion diagnostics - a future in personalized medicine beyond Sanger sequencing

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Accurate Detection of Multiple Tumor Mutations in Formalin-Fixed Paraffin-Embedded Tissues by Coupling Sequence Artifacts Elimination and Mutation Enrichment With MeltArray

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary source of DNA for companion diagnostics (CDx) of cancers. Degradation of FFPE tissue DNA and inherent tumor heterogeneity constitute serious challenges in current CDx assays. To address these limitations, we introduced sequence artifact elimination and mutation enrichment to MeltArray, a highly multiplexed PCR approach, to establish an integrated protocol that provides accuracy, ease of use, and rapidness. Using PIK3CA mutations as a model, we established a MeltArray protocol that could eliminate sequence artifacts completely and enrich mutations from 23.5- to 59.4-fold via a single-reaction pretreatment step comprising uracil-DNA-glycosylase excision and PCR clamping. The entire protocol could identify 13 PIK3CA hotspot mutations of 0.05% to 0.5% mutant allele fractions within 5 hours. Evaluation of 106 breast cancer and 40 matched normal FFPE tissue samples showed that all 47 PIK3CA mutant samples were from the cancer tissue, and no false-positive results were detected in the normal samples. Further evaluation of 105 colorectal and 40 matched normal FFPE tissue samples revealed that 11 PIK3CA mutants were solely from the cancer sample. The detection results of our protocol were consistent with those of the droplet digital PCR assays that underwent sequence artifact elimination. Of the 60 colorectal samples with next-generation sequencing results, the MeltArray protocol detected 2 additional mutant samples with low mutant allele fractions. We conclude that the new protocol provides an improved alternative to current CDx assays for detecting tumor mutations in FFPE tissue DNA.

Cell-free DNA approaches for cancer early detection and interception

Rapid advancements in the area of early cancer detection have brought us closer to achieving the goals of finding cancer early enough to treat or cure it, while avoiding harms of overdiagnosis. We evaluate progress in the development of early cancer detection tests in the context of the current principles for cancer screening. We review cell-free DNA (cfDNA)-based approaches using mutations, methylation, or fragmentomes for early cancer detection. Lastly, we discuss the challenges in demonstrating clinical utility of these tests before integration into routine clinical care.

Multimodal data fusion for cancer biomarker discovery with deep learning

Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.

Companion Diagnostics: State of the Art and New Regulations

Companion diagnostics (CDx) hail promise of improving the drug development process and precision medicine. However, there are various challenges involved in the clinical development and regulation of CDx, which are considered high-risk in vitro diagnostic medical devices given the role they play in therapeutic decision-making and the complications they may introduce with respect to their sensitivity and specificity. The European Union (E.U.) is currently in the process of bringing into effect in vitro Diagnostic Medical Devices Regulation (IVDR). The new Regulation is introducing a wide range of stringent requirements for scientific validity, analytical and clinical performance, as well as on post-market surveillance activities throughout the lifetime of in vitro diagnostics (IVD). Compliance with General Safety and Performance Requirements (GSPRs) adopts a risk-based approach, which is also the case for the new classification system. This changing regulatory framework has an impact on all stakeholders involved in the IVD Industry, including Authorized Representatives, Distributors, Importers, Notified Bodies, and Reference Laboratories and is expected to have a significant effect on the development of new CDx.