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Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays., (Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

This multi-institutional study was undertaken to evaluate interrater reliability of the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines for interpretation and reporting of oncology sequence variants and to assess current practices and perceptions surrounding these guidelines. Fifty-one variants were distributed to 20 participants from 10 institutions for classification using the new guidelines. Agreement was assessed using chance-corrected agreement (Cohen κ). κ was 0.35. To evaluate if data sharing could help resolve disagreements, a summary of variant classifications and additional information about each variant were distributed to all participants. κ improved to 0.7 after the original classifications were revised. Participants were invited to take a web-based survey regarding their perceptions of the guidelines. Only 20% (n = 3) of the survey respondents had prior experience with the guidelines in clinical practice. The main perceived barriers to guideline implementation included the complexity of the guidelines, discordance between clinical actionability and pathobiologic relevance, lack of familiarity with the new classifications, and uncertainty when applying criteria to potential germline variants. This study demonstrates noteworthy discordances between pathologists for variant classification in solid tumors when using the 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists guidelines. These findings highlight potential areas for clarification/refinement before mainstream clinical adoption., (Copyright © 2020 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

This commentary highlights the article by Blidner et al that describes a novel assay for detection of chimeric RNAs from gene fusions and exon-skipping events in non-small-cell lung cancer., (Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Lack of reliable reference samples containing different mutations of interest across large sets of disease-relevant loci limits the extensive validation clinical next-generation sequencing (NGS) assays and their associated bioinformatics pipelines. Herein, we have generated a publicly available, highly flexible tool, in silico Mutator (insiM), to introduce point mutations, insertions, deletions, and duplications of any size into real data sets of amplicon-based or hybrid-capture NGS assays. insiM accepts an alignment file along with target territory and produces paired-end FASTQ files containing specified mutations via modification of original sequencing reads. Mutant signal is, thus, generated within the context of existing real-world data to most closely mimic assay performance. Resulting files may then be passed through the assay's bioinformatics pipeline to assist with assay/bioinformatics validation and to identify performance gaps in detection. To establish the basic functionality of the software, a series of simulation experiments with varying mutation types, sizes, and allele frequencies were performed across the entire clinical territory of hybrid-capture and amplicon-based clinical assays developed at The University of Chicago. This work demonstrates the utility of insiM as a supplementary tool during the validation of an NGS assay's bioinformatics pipeline., (Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Next-generation sequencing (NGS) diagnostic assays increasingly are becoming the standard of care in oncology practice. As the scale of an NGS laboratory grows, management of these assays requires organizing large amounts of information, including patient data, laboratory processes, genomic data, as well as variant interpretation and reporting. Although several Laboratory Information Systems and/or Laboratory Information Management Systems are commercially available, they may not meet all of the needs of a given laboratory, in addition to being frequently cost-prohibitive. Herein, we present the System for Informatics in the Molecular Pathology Laboratory (SIMPL), a free and open-source Laboratory Information System/Laboratory Information Management System for academic and nonprofit molecular pathology NGS laboratories, developed at the Genomic and Molecular Pathology Division at the University of Chicago Medicine. SIMPL was designed as a modular end-to-end information system to handle all stages of the NGS laboratory workload from test order to reporting. We describe the features of SIMPL, its clinical validation at University of Chicago Medicine, and its installation and testing within a different academic center laboratory (University of Colorado), and we propose a platform for future community co-development and interlaboratory data sharing., (Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)