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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.

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.

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.

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.

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.

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 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.

The evolution of cellular pathology as a specialty has always been driven by technological developments and the clinical relevance of incorporating novel investigations into diagnostic practice. In recent years, the molecular characterisation of cancer has become of crucial relevance in patient treatment both for predictive testing and subclassification of certain tumours. Much of this has become possible due to the availability of next-generation sequencing technologies and the whole-genome sequencing of tumours is now being rolled out into clinical practice in England via the 100 000 Genome Project. The effective integration of cellular pathology reporting and genomic characterisation is crucial to ensure the morphological and genomic data are interpreted in the relevant context, though despite this, in many UK centres molecular testing is entirely detached from cellular pathology departments. The CM-Path initiative recognises there is a genomics knowledge and skills gap within cellular pathology that needs to be bridged through an upskilling of the current workforce and a redesign of pathology training. Bridging this gap will allow the development of an integrated ‘morphomolecular pathology’ specialty, which can maintain the relevance of cellular pathology at the centre of cancer patient management and allow the pathology community to continue to be a major influence in cancer discovery as well as playing a driving role in the delivery of precision medicine approaches. Here, several alternative models of pathology training, designed to address this challenge, are presented and appraised.

The continuing evolution of treatment options in thoracic oncology requires the pathologist to regularly update diagnostic algorithms for management of tumor samples. It is essential to decide on the best way to use tissue biopsies, cytological samples, as well as liquid biopsies to identify the different mandatory predictive biomarkers of lung cancers in a short turnaround time. However, biological resources and laboratory member workforce are limited and may be not sufficient for the increased complexity of molecular pathological analyses and for complementary translational research development. In this context, the surgical pathologist is the only one who makes the decisions whether or not to send specimens to immunohistochemical and molecular pathology platforms. Moreover, the pathologist can rapidly contact the oncologist to obtain a new tissue biopsy and/or a liquid biopsy if he/she considers that the biological material is not sufficient in quantity or quality for assessment of predictive biomarkers. Inadequate control of algorithms and sampling workflow may lead to false negative, inconclusive, and incomplete findings, resulting in inappropriate choice of therapeutic strategy and potentially poor outcome for patients. International guidelines for lung cancer treatment are based on the results of the expression of different proteins and on genomic alterations. These guidelines have been established taking into consideration the best practices to be set up in clinical and molecular pathology laboratories. This review addresses the current predictive biomarkers and algorithms for use in thoracic oncology molecular pathology as well as the central role of the pathologist, notably in the molecular tumor board and her/his participation in the treatment decision-making. The perspectives in this setting will be discussed.