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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

The COVID-19 pandemic provides an urgent example where a gap exists between availability of state-of-the-art diagnostics and current needs. As assay protocols and primer sequences become widely known, many laboratories perform diagnostic tests using methods such as RT-PCR or reverse transcription loop mediated isothermal amplification (RT-LAMP). Here, we report an RT-LAMP isothermal assay for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and demonstrate the assay on clinical samples using a simple and accessible point-of-care (POC) instrument. We characterized the assay by dipping swabs into synthetic nasal fluid spiked with the virus, moving the swab to viral transport medium (VTM), and sampling a volume of the VTM to perform the RT-LAMP assay without an RNA extraction kit. The assay has a limit of detection (LOD) of 50 RNA copies per μL in the VTM solution within 30 min. We further demonstrate our assay by detecting SARS-CoV-2 viruses from 20 clinical samples. Finally, we demonstrate a portable and real-time POC device to detect SARS-CoV-2 from VTM samples using an additively manufactured three-dimensional cartridge and a smartphone-based reader. The POC system was tested using 10 clinical samples, and was able to detect SARS-CoV-2 from these clinical samples by distinguishing positive samples from negative samples after 30 min. The POC tests are in complete agreement with RT-PCR controls. This work demonstrates an alternative pathway for SARS-CoV-2 diagnostics that does not require conventional laboratory infrastructure, in settings where diagnosis is required at the point of sample collection.

Background: Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed. Methods: Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared. Results: Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number’ status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk’ group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves. Conclusions: Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Key Points Clinical molecular genetic testing is transforming personalized medicine and is appropriate for a range of applications, such as rare disease diagnostics and predictive testing for common disorders. Whole-exome and whole-genome sequencing may become a first-line clinical test for some naive diagnostic cases, but classic genetic tests will continue to be used for the high analytical sensitivity of specific defects and for the confirmation of genome findings. There remains no single test to detect the wide array of genetic defects that may be inherited or arise de novo ; clinical diagnostics requires multiple approaches to determine a causal genetic defect. Although genome sequencing may transform diagnostic approaches in large academic medical centres, access to expensive and sophisticated tests are not universal. Genetic testing must be available globally through validated simple technologies for molecular diagnostics (such as direct PCR, linkage analysis or multiplex ligation-dependent probe amplification). The greatest challenge to clinical genomics is the reliable interpretation of the multiple and novel variants found through genome sequencing. Pathogenicity of genetic variants can be examined with bioinformatics prediction approaches, protein stability studies, transcriptional activity studies and allele- and/or gene-specific animal models. As broader genomic information becomes available to providers and patients, partnerships will develop to convey patient-centred data, including incidental findings. The regulatory environment must adapt to the coming volume of genomic information to maximize benefit to patients and health-care systems and to match the expectations of the patient population with regard to these technologies. The authors review current technologies for clinical genetic testing. Moves are being made towards whole-genome and whole-exome sequencing in the clinic, although other technologies will continue to be of value. Genomic technologies are reaching the point of being able to detect genetic variation in patients at high accuracy and reduced cost, offering the promise of fundamentally altering medicine. Still, although scientists and policy advisers grapple with how to interpret and how to handle the onslaught and ambiguity of genome-wide data, established and well-validated molecular technologies continue to have an important role, especially in regions of the world that have more limited access to next-generation sequencing capabilities. Here we review the range of methods currently available in a clinical setting as well as emerging approaches in clinical molecular diagnostics. In parallel, we outline implementation challenges that will be necessary to address to ensure the future of genetic medicine.

Xpert MTB/RIF Ultra (Xpert Ultra) might have higher sensitivity than its predecessor, Xpert MTB/RIF (Xpert), but its role in tuberculous meningitis diagnosis is uncertain. We aimed to compare Xpert Ultra with Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. In this prospective, randomised, diagnostic accuracy study, adults (≥16 years) with suspected tuberculous meningitis from a single centre in Vietnam were randomly assigned to cerebrospinal fluid testing by either Xpert Ultra or Xpert at baseline and, if treated for tuberculous meningitis, after 3–4 weeks of treatment. Test performance (sensitivity, specificity, and positive and negative predictive values) was calculated for Xpert Ultra and Xpert and compared against clinical and mycobacterial culture reference standards. Analyses were done for all patients and by HIV status. Between Oct 16, 2017, and Feb 10, 2019, 205 patients were randomly assigned to Xpert Ultra (n=103) or Xpert (n=102). The sensitivities of Xpert Ultra and Xpert for tuberculous meningitis diagnosis against a reference standard of definite, probable, and possible tuberculous meningitis were 47·2% (95% CI 34·4–60·3; 25 of 53 patients) for Xpert Ultra and 39·6% (27·6–53·1; 21 of 53) for Xpert (p=0·56); specificities were 100·0% (95% CI 92·0–100·0; 44 of 44) and 100·0% (92·6–100·0; 48 of 48), respectively. In HIV-negative patients, the sensitivity of Xpert Ultra was 38·9% (24·8–55·1; 14 of 36) versus 22·9% (12·1–39·0; eight of 35) by Xpert (p=0·23). In HIV co-infected patients, the sensitivities were 64·3% (38·8–83·7; nine of 14) for Xpert Ultra and 76·9% (49·7–91·8; ten of 13) for Xpert (p=0·77). Negative predictive values were 61·1% (49·6–71·5) for Xpert Ultra and 60·0% (49·0–70·0) for Xpert. Against a reference standard of mycobacterial culture, sensitivities were 90·9% (72·2–97·5; 20 of 22 patients) for Xpert Ultra and 81·8% (61·5–92·7; 18 of 22) for Xpert (p=0·66); specificities were 93·9% (85·4–97·6; 62 of 66) and 96·9% (89·5–91·2; 63 of 65), respectively. Six (22%) of 27 patients had a positive test by Xpert Ultra after 4 weeks of treatment versus two (9%) of 22 patients by Xpert. Xpert Ultra was not statistically superior to Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. A negative Xpert Ultra or Xpert test does not rule out tuberculous meningitis. New diagnostic strategies are urgently required. Wellcome Trust and the Foundation for Innovative New Diagnostics.

Background: Functional microRNAs (miRNAs) in exosomes have been recognised as potential stable biomarkers in cancers. The aim of this study is to identify specific miRNAs in exosome as serum biomarkers for the early detection of recurrence in human colorectal cancer (CRC). Methods: Serum samples were sequentially obtained from six patients with and without recurrent CRC. The miRNAs were purified from exosomes, and miRNA microarray analysis was performed. The miRNA expression profiles and copy number aberrations were explored using microarray and array CGH analyses in 124 CRC tissues. Then, we validated exosomal miRNAs in 2 serum sample sets (90 and 209 CRC patients) by quantitative real-time RT–PCR. Results: Exosomal miR-17-92a cluster expression level in serum was correlated with the recurrence of CRC. Exosomal miR-19a expression levels in serum were significantly increased in patients with CRC as compared with healthy individuals with gene amplification. The CRC patients with high exosomal miR-19a expression showed poorer prognoses than the low expression group ( P <0.001). Conclusions: Abundant expression of exosomal miR-19a in serum was identified as a prognostic biomarker for recurrence in CRC patients.

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:Tumour budding has been reported as a promising prognostic marker in many cancers. This meta-analysis assessed the prognostic value of tumour budding in oral squamous cell carcinoma (OSCC).Methods:We searched OvidMedline, PubMed, Scopus and Web of Science for articles that studied tumour budding in OSCC. We used reporting recommendations for tumour marker (REMARK) criteria to evaluate the quality of studies eligible for meta-analysis.Results:A total of 16 studies evaluated the prognostic value of tumour budding in OSCC. The meta-analysis showed that tumour budding was significantly associated with lymph node metastasis (odds ratio=7.08, 95% CI=1.75-28.73), disease-free survival (hazard ratio=1.83, 95% CI=1.34-2.50) and overall survival (hazard ratio=1.88, 95% CI=1.25-2.82).Conclusions:Tumour budding is a simple and reliable prognostic marker for OSCC. Evaluation of tumour budding could facilitate personalised management of OSCC.

Background: Upper digestive endoscopy with biopsy and histopathological evaluation of the biopsy material is the standard method for diagnosing gastric cancer (GC). However, this procedure may not be widely available for screening in the developing world, whereas in developed countries endoscopy is frequently used without major clinical gain. There is a high demand for a simple and non-invasive test for selecting the individuals at increased risk that should undergo the endoscopic examination. Here, we studied the feasibility of a nanomaterial-based breath test for identifying GC among patients with gastric complaints. Methods: Alveolar exhaled breath samples from 130 patients with gastric complaints (37 GC/32 ulcers / 61 less severe conditions) that underwent endoscopy/biopsy were analyzed using nanomaterial-based sensors. Predictive models were built employing discriminant factor analysis (DFA) pattern recognition, and their stability against possible confounding factors (alcohol/tobacco consumption; Helicobacter pylori ) was tested. Classification success was determined (i) using leave-one-out cross-validation and (ii) by randomly blinding 25% of the samples as a validation set. Complementary chemical analysis of the breath samples was performed using gas chromatography coupled with mass spectrometry. Results: Three DFA models were developed that achieved excellent discrimination between the subpopulations: (i) GC vs benign gastric conditions, among all the patients (89% sensitivity; 90% specificity); (ii) early stage GC (I and II) vs late stage (III and IV), among GC patients (89% sensitivity; 94% specificity); and (iii) ulcer vs less severe, among benign conditions (84% sensitivity; 87% specificity). The models were insensitive against the tested confounding factors. Chemical analysis found that five volatile organic compounds (2-propenenitrile, 2-butoxy-ethanol, furfural, 6-methyl-5-hepten-2-one and isoprene) were significantly elevated in patients with GC and/or peptic ulcer, as compared with less severe gastric conditions. The concentrations both in the room air and in the breath samples were in the single p.p.b. v range, except in the case of isoprene. Conclusion: The preliminary results of this pilot study could open a new and promising avenue to diagnose GC and distinguish it from other gastric diseases. It should be noted that the applied methods are complementary and the potential marker compounds identified by gas-chromatography/mass spectrometry are not necessarily responsible for the differences in the sensor responses. Although this pilot study does not allow drawing far-reaching conclusions, the encouraging preliminary results presented here have initiated a large multicentre clinical trial to confirm the observed patterns for GC and benign gastric conditions.

Background: PD-L1 (programmed cell death 1 ligand 1) on tumour cells suppresses host immunity through binding to its receptor PD-1 on lymphocytes, and promotes peritoneal dissemination in mouse models of ovarian cancer. However, how PD-L1 expression is regulated in ovarian cancer microenvironment remains unclear. Methods: The number of CD8-positive lymphocytes and PD-L1 expression in tumour cells was assessed in ovarian cancer clinical samples. PD-L1 expression and tumour progression in mouse models under conditions of altering IFN- γ signals was assessed. Results: The number of CD8-positive cells in cancer stroma was very high in peritoneally disseminated tumours, and was strongly correlated to PD-L1 expression on the tumour cells ( P <0.001). In mouse models, depleting IFNGR1 (interferon- γ receptor 1) resulted in lower level of PD-L1 expression in tumour cells, increased the number of tumour-infiltrating CD8-positive lymphocytes, inhibition of peritoneal disseminated tumour growth and longer survival ( P =0.02). The injection of IFN- γ into subcutaneous tumours induced PD-L1 expression and promoted tumour growth, and PD-L1 depletion completely abrogated tumour growth caused by IFN- γ injection ( P =0.01). Conclusions: Interferon- γ secreted by CD8-positive lymphocytes upregulates PD-L1 on ovarian cancer cells and promotes tumour growth. The lymphocyte infiltration and the IFN- γ status may be the key to effective anti-PD-1 or anti-PD-L1 therapy in ovarian cancer.