Cancer Variant Interpretation Group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network.

Advances in technology have led to a massive expansion in the capacity for genomic analysis, with a commensurate fall in costs. The clinical indications for genomic testing have evolved markedly; the volume of clinical sequencing has increased dramatically; and the range of clinical professionals involved in the process has broadened. There is general acceptance that our early dichotomous paradigms of variants being pathogenic-high risk and benign-no risk are overly simplistic. There is increasing recognition that the clinical interpretation of genomic data requires significant expertise in disease-gene-variant associations specific to each disease area. Inaccurate interpretation can lead to clinical mismanagement, inconsistent information within families and misdirection of resources. It is for this reason that 'national subspecialist multidisciplinary meetings' (MDMs) for genomic interpretation have been articulated as key for the new NHS Genomic Medicine Service, of which Cancer Variant Interpretation Group UK (CanVIG-UK) is an early exemplar. CanVIG-UK was established in 2017 and now has >100 UK members, including at least one clinical diagnostic scientist and one clinical cancer geneticist from each of the 25 regional molecular genetics laboratories of the UK and Ireland. Through CanVIG-UK, we have established national consensus around variant interpretation for cancer susceptibility genes via monthly national teleconferenced MDMs and collaborative data sharing using a secure online portal. We describe here the activities of CanVIG-UK, including exemplar outputs and feedback from the membership

Identification of reduced host transcriptomic signatures for tuberculosis disease and digital PCR-based validation and quantification

Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.Immunogenetics and cellular immunology of bacterial infectious disease

Identification of Reduced Host Transcriptomic Signatures for Tuberculosis Disease and Digital PCR-Based Validation and Quantification.

Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology

Molecular techniques for the personalised management of patients with chronic myeloid leukaemia.

Chronic myeloid leukemia (CML) is the paradigm for targeted cancer therapy. RT-qPCR is the gold standard for monitoring response to tyrosine kinase-inhibitor (TKI) therapy based on the reduction of blood or bone marrow BCR-ABL1. Some patients with CML and very low or undetectable levels of BCR-ABL1 transcripts can stop TKI-therapy without CML recurrence. However, about 60 percent of patients discontinuing TKI-therapy have rapid leukaemia recurrence. This has increased the need for more sensitive and specific techniques to measure residual CML cells. The clinical challenge is to determine when it is safe to stop TKI-therapy. In this review we describe and critically evaluate the current state of CML clinical management, different technologies used to monitor measurable residual disease (MRD) focus on comparingRT-qPCR and new methods entering clinical practice. We discuss advantages and disadvantages of new methods

Impaired cellular and humoral immunity is a feature of Diamond‐Blackfan anaemia; experience of 107 unselected cases in the United Kingdom

Diamond‐Blackfan anaemia (DBA) is a rare bone marrow failure syndrome characterised by anaemia, congenital anomalies and cancer predisposition. Although infections are the second leading cause of mortality in non‐transplanted patients, immune function is largely unexplored. We identified quantitative deficits in serum immunoglobulins and/or circulating T, natural killer and B lymphocytes in 59 of 107 unselected patients (55·1%) attending our centre over a 7‐year period. Immune abnormalities were independent of ribosomal protein genotype and arose in both steroid‐treated and steroid‐untreated patients. In summary, these data highlight the high prevalence and spectrum of infections and immune defects in DBA

Impaired cellular and humoral immunity is a feature of Diamond‐Blackfan anaemia; experience of 107 unselected cases in the United Kingdom

Diamond‐Blackfan anaemia (DBA) is a rare bone marrow failure syndrome characterised by anaemia, congenital anomalies and cancer predisposition. Although infections are the second leading cause of mortality in non‐transplanted patients, immune function is largely unexplored. We identified quantitative deficits in serum immunoglobulins and/or circulating T, natural killer and B lymphocytes in 59 of 107 unselected patients (55·1%) attending our centre over a 7‐year period. Immune abnormalities were independent of ribosomal protein genotype and arose in both steroid‐treated and steroid‐untreated patients. In summary, these data highlight the high prevalence and spectrum of infections and immune defects in DBA