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- In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing. - To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update. - The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations. - Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline. - The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes ( ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to \"rule in\" targetable mutations when tissue is limited or hard to obtain.

Glioblastoma multiforme (GBM) is the most common and malignant type of primary brain tumor in adults. Despite important advances in understanding the molecular pathogenesis and biology of this tumor in the past decade, the prognosis for GBM patients remains poor. GBM is characterized by aggressive biological behavior and high degrees of inter-tumor and intra-tumor heterogeneity. Increased understanding of the molecular and cellular heterogeneity of GBM may not only help more accurately define specific subgroups for precise diagnosis but also lay the groundwork for the successful implementation of targeted therapy. Herein, we systematically review the key achievements in the understanding of GBM molecular pathogenesis, mechanisms, and biomarkers in the past decade. We discuss the advances in the molecular pathology of GBM, including genetics, epigenetics, transcriptomics, and signaling pathways. We also review the molecular biomarkers that have potential clinical roles. Finally, new strategies, current challenges, and future directions for discovering new biomarkers and therapeutic targets for GBM will be discussed.

Similar to other malignancies, TCGA network efforts identified the detailed genomic picture of skin melanoma, laying down the basis of molecular classification. On the other hand, genome-wide association studies discovered the genetic background of the hereditary melanomas and the susceptibility genes. These genetic studies helped to fine-tune the differential diagnostics of malignant melanocytic lesions, using either FISH tests or the myPath gene expression signature. Although the original genomic studies on skin melanoma were mostly based on primary tumors, data started to accumulate on the genetic diversity of the progressing disease. The prognostication of skin melanoma is still based on staging but can be completed with gene expression analysis (DecisionDx). Meanwhile, this genetic knowledge base of skin melanoma did not turn to the expected wide array of target therapies, except the BRAF inhibitors. The major breakthrough of melanoma therapy was the introduction of immune checkpoint inhibitors, which showed outstanding efficacy in skin melanoma, probably due to their high immunogenicity. Unfortunately, beyond BRAF, KIT mutations and tumor mutation burden, no clinically validated predictive markers exist in melanoma, although several promising biomarkers have been described, such as the expression of immune-related genes or mutations in the IFN-signaling pathway. After the initial success of either target or immunotherapies, sooner or later, relapses occur in the majority of patients, due to various induced genetic alterations, the diagnosis of which could be developed to novel predictive genetic markers.

CRISPR-based nucleic acid detection assays offer a potent and dependable tool in modern nucleic acid detection, owing to their high specificity, rapidity, sensitivity, ease of use, and broad applicability.The combination of the CRISPR system and nucleic acid amplification technology has transformed the modern biomedical landscape, markedly augmenting the specificity of nucleic acid amplification, thereby advancing the field of precision medicine.The one-pot nucleic acid detection assay based on the CRISPR system realizes the integration of nucleic acid amplification and CRISPR detection into a single reaction tube, which not only simplifies the experimental operations but also significantly reduces the risk of aerosol contamination. The integration of nucleic acid amplification (NAA) with the CRISPR detection system has led to significant advancements and opportunities for development in molecular diagnostics. Nevertheless, the incompatibility between CRISPR cleavage and NAA has significantly impeded the commercialization of this technology. Currently, several one-pot detection strategies based on CRISPR systems have been devised to address concerns regarding aerosol contamination risk and operational complexity associated with step-by-step detection as well as the sensitivity limitation of conventional one-pot methods. In this review, we provide a comprehensive introduction and outlook of the various solutions of the one-pot CRISPR assay for practitioners who are committed to developing better CRISPR nucleic acid detection technologies to promote the progress of molecular diagnostics. The integration of nucleic acid amplification (NAA) with the CRISPR detection system has led to significant advancements and opportunities for development in molecular diagnostics. Nevertheless, the incompatibility between CRISPR cleavage and NAA has significantly impeded the commercialization of this technology. Currently, several one-pot detection strategies based on CRISPR systems have been devised to address concerns regarding aerosol contamination risk and operational complexity associated with step-by-step detection as well as the sensitivity limitation of conventional one-pot methods. In this review, we provide a comprehensive introduction and outlook of the various solutions of the one-pot CRISPR assay for practitioners who are committed to developing better CRISPR nucleic acid detection technologies to promote the progress of molecular diagnostics.

The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

This article reviews the histologic and molecular characterization of gliomas, including the new “integrated diagnoses” of the World Health Organization Classification, 2016 edition. The entities reviewed within include diffuse gliomas (astrocytoma, oligodendroglioma, glioblastoma), as well as circumscribed and low-grade gliomas (angiocentric glioma, pilocytic astrocytoma, subependymal giant cell astrocytoma, pleomorphic xanthoastrocytoma, pilomyxoid astrocytoma, ependymoma, myxopapillary ependymoma, and subependymoma). Diagnostic, prognostic, and predictive biomarkers are discussed for each entity. We review how molecular testing for IDH1 and ATRX and detection of chromosome 1p/19q codeletion can be used to categorize glioblastomas as IDH-wildtype or IDH-mutant, and lower grade diffuse gliomas into three molecular groups that correlate better with patient outcomes than histologic subtyping. Pediatric diffuse gliomas are highlighted, including diffuse midline glioma, H3 K27M-mutant, and inherited germline mutations that predispose to pediatric gliomas. The utility of genomic profiling of certain gliomas is discussed, including identifying candidates for experimental therapies. This review is meant to be a concise summary of glioma characterization for the practicing pathologist.

Genomics and genome technology is having, and continues to have, a major impact on all areas of bioscience research providing insights into the key area of molecular mechanisms of cells in health and disease. This is causing a profound effect on biomedical science and is accelerating the development of new diagnostic applications. This book provides a timely, graduate level introduction to the fast-paced area of genomics and clinical diagnostic technologies and introduces the concept of applications based on this area. The initial chapters focus on principal molecular technologies that underpin the information in the later chapters. In addition to introductory areas of nucleic acids and techniques in molecular biology, bioinformatics and proteomics, other key diagnostic areas such as the use of immunological reagents are covered. The later chapters provide more specialised examples of currently used diagnostic technologies and insights into selected key diagnostic challenges including specific examples of molecular microbial diagnostics and molecular biomarkers in oncology. The running themes through the chapters provides an insight into current and future perspectives in this rapidly evolving field.

Background. Blood culture-negative endocarditis (BCNE) may account for up to 31% of all cases of endocarditis. Methods. We used a prospective, multimodal strategy incorporating serological, molecular, and histopathological assays to investigate specimens from 819 patients suspected of having BCNE. Results. Diagnosis of endocarditis was first ruled out for 60 patients. Among 759 patients with BCNE, a causative microorganism was identified in 62.7%, and a noninfective etiology in 2.5%. Blood was the most useful specimen, providing a diagnosis for 47.7% of patients by serological analysis (mainly Q fever and Bartonella infections). Broad-range polymerase chain reaction (PCR) of blood and Bartonella-specific Western blot methods diagnosed 7 additional cases. PCR of valvular biopsies identified 109 more etiologies, mostly streptococci, Tropheryma whipplei, Bartonella species, and fungi. Primer extension enrichment reaction and autoimmunohistochemistry identified a microorganism in 5 additional patients. No virus or Chlamydia species were detected. A noninfective cause of endocarditis, particularly neoplasic or autoimmune disease, was determined by histological analysis or by searching for antinuclear antibodies in 19 (2.5%) of the patients. Our diagnostic strategy proved useful and sensitive for BCNE workup. Conclusions. We highlight the major role of zoonotic agents and the underestimated role of noninfective diseases in BCNE. We propose serological analysis for Coxiella burnetii and Bartonella species, detection of antinuclear antibodies and rheumatoid factor as first-line tests, followed by specific PCR assays for T. whipplei, Bartonella species, and fungi in blood. Broad-spectrum 16S and 18S ribosomal RNA PCR may be performed on valvular biopsies, when available.

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

The purpose of the study was to implement and prospectively evaluate the outcomes of a rapid genomic diagnosis program at two pediatric tertiary centers. Rapid singleton whole-exome sequencing (rWES) was performed in acutely unwell pediatric patients with suspected monogenic disorders. Laboratory and clinical barriers to implementation were addressed through continuous multidisciplinary review of process parameters. Diagnostic and clinical utility and cost-effectiveness of rWES were assessed. Of 40 enrolled patients, 21 (52.5%) received a diagnosis, with median time to report of 16 days (range 9–109 days). A result was provided during the first hospital admission in 28 of 36 inpatients (78%). Clinical management changed in 12 of the 21 diagnosed patients (57%), including the provision of lifesaving treatment, avoidance of invasive biopsies, and palliative care guidance. The cost per diagnosis was AU$13,388 (US$10,453). Additional cost savings from avoidance of planned tests and procedures and reduced length of stay are estimated to be around AU$543,178 (US$424,101). The clear relative advantage of rWES, joint clinical and laboratory leadership, and the creation of a multidisciplinary “rapid team” were key to successful implementation. Rapid genomic testing in acute pediatrics is not only feasible but also cost-effective, and has high diagnostic and clinical utility. It requires a whole-of-system approach for successful implementation.