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The National Institutes of Health-US Food and Drug Administration Joint Leadership Council Next-Generation Sequencing and Radiomics Working Group was formed by the National Institutes of Health-Food and Drug Administration Joint Leadership Council to promote the development and validation of innovative next-generation sequencing tests, radiomic tools, and associated data analysis and interpretation enhanced by artificial intelligence and machine learning technologies. A 2-day workshop was held on September 29-30, 2021, to convene members of the scientific community to discuss how to overcome the "ground truth" gap that has frequently been acknowledged as 1 of the limiting factors impeding high-quality research, development, validation, and regulatory science in these fields. This report provides a summary of the resource gaps identified by the working group and attendees, highlights existing resources and the ways they can potentially be employed to accelerate growth in these fields, and presents opportunities to support next-generation sequencing and radiomic tool development and validation using technologies such as artificial intelligence and machine learning., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

On September 21, 2022, the FDA granted accelerated approval to selpercatinib (Retevmo, Eli Lilly and Company) for the treatment of adult patients with locally advanced or metastatic solid tumors with a rearranged during transfection (RET) gene fusion that have progressed on or following prior systemic treatment or who have no satisfactory alternative treatment options. The approval was based on data from Study LOXO-RET-17001 (LIBRETTO-001; NCT03157128), an international, non-randomized, multi-cohort clinical trial that included patients with advanced solid tumors harboring RET alterations. The overall response rate in 41 patients with locally advanced or metastatic RET fusion-positive solid tumors other than non-small cell lung cancer (NSCLC) or thyroid cancer was 44% [95% confidence interval (CI), 28%-60%], with median duration of response 24.5 months (95% CI, 9.2-not evaluable). Patients with 10 of 14 tumor types with a variety of fusion partners had objective responses, including patients with the following tumors: pancreatic adenocarcinoma, colorectal, salivary, unknown primary, breast, soft-tissue sarcoma, bronchial carcinoid, ovarian, small intestine, and cholangiocarcinoma. The recommendation for approval was supported by results from LIBRETTO-001 in patients with RET fusion-positive NSCLC and thyroid cancer, which formed the basis of prior approvals in these tumor types. The most common adverse reactions (>25%) were edema, diarrhea, fatigue, dry mouth, hypertension, abdominal pain, constipation, rash, nausea, and headache. This is the first tissue-agnostic approval of a RET-directed targeted therapy., (©2023 American Association for Cancer Research.)

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Sample mislabeling or misannotation has been a long-standing problem in scientific research, particularly prevalent in large-scale, multi-omic studies due to the complexity of multi-omic workflows. There exists an urgent need for implementing quality controls to automatically screen for and correct sample mislabels or misannotations in multi-omic studies. Here, we describe a crowdsourced precisionFDA NCI-CPTAC Multi-omics Enabled Sample Mislabeling Correction Challenge, which provides a framework for systematic benchmarking and evaluation of mislabel identification and correction methods for integrative proteogenomic studies. The challenge received a large number of submissions from domestic and international data scientists, with highly variable performance observed across the submitted methods. Post-challenge collaboration between the top-performing teams and the challenge organizers has created an open-source software, COSMO, with demonstrated high accuracy and robustness in mislabeling identification and correction in simulated and real multi-omic datasets., Competing Interests: S.Y. and J.Z. are employees of Sema4, a for-profit organization that promotes a healthcare through information-driven insights. R.P., H.F., and H.C. are employees of Sentieon Inc. A.C. is an employee of Bionamic AB. The other authors declare no competing interests., (© 2021 The Author(s).)

In the version of this article initially published online, two pairs of headings were switched with each other in Table 4: "Recall (PCR free)" was switched with "Recall (with PCR)," and "Precision (PCR free)" was switched with "Precision (with PCR)." The error has been corrected in the print, PDF and HTML versions of this article.

Standardized benchmarking approaches are required to assess the accuracy of variants called from sequence data. Although variant-calling tools and the metrics used to assess their performance continue to improve, important challenges remain. Here, as part of the Global Alliance for Genomics and Health (GA4GH), we present a benchmarking framework for variant calling. We provide guidance on how to match variant calls with different representations, define standard performance metrics, and stratify performance by variant type and genome context. We describe limitations of high-confidence calls and regions that can be used as truth sets (for example, single-nucleotide variant concordance of two methods is 99.7% inside versus 76.5% outside high-confidence regions). Our web-based app enables comparison of variant calls against truth sets to obtain a standardized performance report. Our approach has been piloted in the PrecisionFDA variant-calling challenges to identify the best-in-class variant-calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and evaluating the results.

A national workgroup convened by the Centers for Disease Control and Prevention identified principles and made recommendations for standardizing the description of sequence data contained within the variant file generated during the course of clinical next-generation sequence analysis for diagnosing human heritable conditions. The specifications for variant files were initially developed to be flexible with regard to content representation to support a variety of research applications. This flexibility permits variation with regard to how sequence findings are described and this depends, in part, on the conventions used. For clinical laboratory testing, this poses a problem because these differences can compromise the capability to compare sequence findings among laboratories to confirm results and to query databases to identify clinically relevant variants. To provide for a more consistent representation of sequence findings described within variant files, the workgroup made several recommendations that considered alignment to a common reference sequence, variant caller settings, use of genomic coordinates, and gene and variant naming conventions. These recommendations were considered with regard to the existing variant file specifications presently used in the clinical setting. Adoption of these recommendations is anticipated to reduce the potential for ambiguity in describing sequence findings and facilitate the sharing of genomic data among clinical laboratories and other entities., (Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Next-generation sequencing technologies are fueling a wave of new diagnostic tests. Progress on a key set of nine research challenge areas will help generate the knowledge required to advance effectively these diagnostics to the clinic., (Copyright © 2016, American Association for the Advancement of Science.)

Issues associated with the translation of complex proteomic biomarkers from discovery to clinical diagnostics have been widely discussed among academic researchers, government agencies, as well as assay and instrumentation manufacturers. Here, we provide an overview of the regulatory framework and type of information that is typically required in order to evaluate in vitro diagnostic tests regulated by the Office of In Vitro Diagnostic Device Evaluation and Safety (OIVD) at the US Food and Drug Administration (FDA), with the focus on some of the issues specific to protein-based complex tests. Technological points pertaining to mass spectrometry platforms and assessment of potential concerns important for assurance of safety and effectiveness of this type of assays when introduced into clinical diagnostic use, as well as general approaches for evaluating the performance of these devices, are discussed., (Published by Elsevier B.V.)

This article highlights a current US FDA perspective concerning the use of biomarker-based diagnostics for personalized medicine. Specifically, current biomarkers that have application for improving the benefit/risk profile of already approved drugs are discussed. The success of biomarkers for use in personalized medicine depends on many factors, including proper evaluation of the usefulness of the biomarker for assessing the event of interest, and the safety and effectiveness of the diagnostic device used to measure the biomarker, which includes appropriate analytical and clinical validation. These points along with the many regulatory concerns regarding co-labeling of drugs and devices and future aspects, such as co-development, will be discussed in this regulatory science focus.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Clinical proteomics has the potential to enable the early detection of cancer through the development of multiplex assays that can inform clinical decisions. However, there has been some uncertainty among translational researchers and developers as to the specific analytical measurement criteria needed to validate protein-based multiplex assays. To begin to address the causes of this uncertainty, a day-long workshop titled "Interagency Oncology Task Force Molecular Diagnostics Workshop" was held in which members of the proteomics and regulatory communities discussed many of the analytical evaluation issues that the field should address in development of protein-based multiplex assays for clinical use. This meeting report explores the issues raised at the workshop and details the recommendations that came out of the day's discussions, such as a workshop summary discussing the analytical evaluation issues that specific proteomic technologies should address when seeking US Food and Drug Administration approval.

As a part of ongoing efforts of the NCI-FDA Interagency Oncology Task Force subcommittee on molecular diagnostics, members of the Clinical Proteomic Technology Assessment for Cancer program of the National Cancer Institute have submitted 2 protein-based multiplex assay descriptions to the Office of In Vitro Diagnostic Device Evaluation and Safety, US Food and Drug Administration. The objective was to evaluate the analytical measurement criteria and studies needed to validate protein-based multiplex assays. Each submission described a different protein-based platform: a multiplex immunoaffinity mass spectrometry platform for protein quantification, and an immunological array platform quantifying glycoprotein isoforms. Submissions provided a mutually beneficial way for members of the proteomics and regulatory communities to identify the analytical issues that the field should address when developing protein-based multiplex clinical assays.

The use of in vitro tests to detect and measure biomarkers will be central to the realization of personalized medicine. The importance of proper biomarker test development processes cannot be overemphasized; whether the test is being used as part of drug development or ultimately for use as a companion diagnostic, if the test result is to be meaningful, the test analytical performance must be well characterized and reliable. This article will outline important design issues and special analytical validation issues to consider when developing and assessing an in vitro diagnostic test system for use in pharmacogenetic and pharmacogenomic studies. Of particular importance is understanding that good analytical performance is a result of a well-coordinated analytical system specifically designed to provide quality results.:, (© Published by Elsevier Ltd.)

The use of in vitro tests to detect and measure biomarkers provides promising avenues for development of new and better drugs, and will be central to the realization of personalized medicine. The importance of proper biomarker test assessment cannot be overemphasized. Whether the test is being used as part of drug development or ultimately used as a companion diagnostic, if the test result is to be meaningful, the test analytical performance must be well characterized. This article will outline important analytical validation issues to consider when developing and assessing an in vitro diagnostic test system for use in pharmacogenetic and pharmacogenomic studies.:, (© Published by Elsevier Ltd.)

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

The US Food and Drug Administration (FDA) encourages the development of new technologies such as microarrays which may improve and streamline assessments of safety and the effectiveness of medical products for the benefit of public health. The FDA anticipates that these new technologies may offer the potential for more effective approaches to medical treatment and disease prevention and management. This paper discusses issues associated with the translation of nucleic acid microarray-based devices from basic research and target discovery to in vitro clinical diagnostic use, which the Office of In Vitro Diagnostic Device Evaluation and Safety in the Center for Devices and Radiological Health foresees will be important for assurance of safety and effectiveness of these types of devices. General technological points, assessment of potential concerns for transitioning microarrays into clinical diagnostic use and approaches for evaluating the performance of these types of devices will be discussed.

Complete laminin alpha2 (LAMA2) deficiency causes approximately half of congenital muscular dystrophy (CMD) cases. Many loss-of-function mutations have been reported in these severe, neonatal-onset patients, but only single missense mutations have been found in milder CMD with partial laminin alpha2 deficiency. Here, we studied nine patients diagnosed with CMD who showed abnormal white-matter signal at brain MRI and partial deficiency of laminin alpha2 on immunofluorescence of muscle biopsy. We screened the entire 9.5 kb laminin alpha2 mRNA from patient muscle biopsy by direct capillary automated sequencing, single strand conformational polymorphism (SSCP), or denaturing high performance liquid chromatography (DHPLC) of overlapping RT-PCR products followed by direct sequencing of heteroduplexes. We identified laminin alpha2 sequence changes in six of nine CMD patients. Each of the gene changes identified, except one, was novel, including three missense changes and two splice-site mutations. The finding of partial laminin alpha2 deficiency by immunostaining is not specific for laminin alpha2 gene mutation carriers, with only two patients (22%) showing clear causative mutations, and an additional three patients (33%) showing possible mutations. The clinical presentation and disease progression was homogeneous in the laminin alpha2-mutation positive and negative CMD patients., (Copyright 2003 Wiley-Liss, Inc.)

Juvenile dermatomyositis (JDM), the most common pediatric inflammatory myopathy, is a systemic vasculopathy affecting young children. Epidemiology studies documenting an antecedent illness in the 3 mo before the first definite symptom (rash and/or weakness) of JDM are supported by immunologic data that suggest that the disease pathophysiology is Ag driven. The purpose of this study was to compare the gene expression profiles in muscle biopsies of four untreated DQA1*0501(+) JDM children with profiles from children with a known necrotizing myopathy (Duchenne muscular dystrophy), as well as an in vitro antiviral model (NF90), and healthy pediatric controls. Nearly half (47%) of the dysregulated genes in JDM were associated with the immune response. In particular, increased expression of IFN-alphabeta-inducible genes 6-16, myxovirus resistance protein p78, latent cytosolic transcription factor, LMP2, and TAP1 was observed. This profile is consistent with an IFN-alphabeta transcription cascade seen in the in vitro viral resistance model. The IFN-alphabeta-inducible profile was superimposed on transcription profiles reflective of myofiber necrosis and regeneration shared with Duchenne muscular dystrophy. Expressed genes were confirmed by quantitative real-time PCR (6-16), immunofluorescence (thrombospondin 4), and immunolocalization (IFN-gamma, p21). We hypothesize that these data support a model of Ag (?viral) induction of an apparent autoimmune disease based on dynamic interaction between the muscle, vascular, and immune systems in the genetically susceptible (DQA1*0501(+)) child.

Primary merosin-deficient congenital muscular dystrophy (CMD) is a severe form of congenital muscular disorder which is caused by mutations in the laminin alpha2 chain gene (LAMA2). The disease is characterized by marked dystrophic changes in skeletal muscles during early infancy, while little is known about the pathological process of the muscle fiber degeneration. Here, we report the immunohistochemical analysis of skeletal muscle in ten patients with primary merosin-deficient CMD using a panel of molecular markers for skeletal muscle proteins, cellular necrosis, and apoptosis. In the youngest patient (a 52 day old baby), prominent massive muscle cell degeneration occurred in association with the deposition of the C5-9 complement membrane attack complex (MAC). Most of the MAC-positive muscle fibers showed a severely deranged immunoreaction to dystrophin, dystroglycans, and other sarcolemmal proteins. In addition, we found scattered positive signals for apoptosis. Similar but milder changes were also observed in six other patients younger than 1 year. In the patients older than 3 years, muscle fibers positive for MAC and apoptotic signals were barely detectable. These findings imply that massive muscle fiber degeneration occurs in the very early stage of merosin-deficient CMD and may contribute to the severe dystrophic changes in muscle from early infancy.

The normal tissue tropism of adeno-associated virus (AAV) is poorly defined, although the majority of humans test seropositive for this virus. Eighty-five muscle biopsy specimens were tested for AAV genomes; AAV DNA was identified in 17% of normal and 10% of Duchenne muscular dystrophy muscle biopsy specimens, but in only 3% of peripheral blood samples. AAV genomes were absent from all 37 muscle biopsy specimens from patients with myositis tested. Muscle is a major target organ for AAV, and infection is associated with autoimmune disease of muscle.

The effect of gamma-1,2,3,4,5,6-hexachlorocyclohexane (lindane), 2-chloro-4-ethylamino-6-isopropylamino-s-triazine (atrazine) and 2-methylthio-4,6-bis-isopropylamino-s-triazine (prometryne) on the formation of a specific oestradiol-receptor complex in the rat uterus cytosol has been examined in vitro and in vivo. Both in vitro and in vivo, the pesticides significantly (P < 0.001) inhibited the formation of the complex in the rat uterus cytosol. The decrease in the number of free specific binding sites on the receptors was determined. The affinity of binding was not modified under the influence of pesticides, and the Kd value was of the same order of magnitude (10(-9) M). The inhibition was found to be fully non-competitive.