Evidence is strengthening for the morphological evaluation of tumor infiltrating lymphocytes (TILs) in breast cancer. Herein, the concepts for TILs assessment are laid out by pathologists to ...facilitate their wider evaluation and consistent interpretation. The goal of this article is to promote the evaluation of TILs as a biomarker in research, clinical trial settings and day-to-day practice.
The morphological evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is gaining momentum as evidence strengthens for the clinical relevance of this immunological biomarker. Accumulating evidence suggests that the extent of lymphocytic infiltration in tumor tissue can be assessed as a major parameter by evaluation of hematoxylin and eosin (H&E)-stained tumor sections. TILs have been shown to provide prognostic and potentially predictive value, particularly in triple-negative and human epidermal growth factor receptor 2-overexpressing BC.
A standardized methodology for evaluating TILs is now needed as a prerequisite for integrating this parameter in standard histopathological practice, in a research setting as well as in clinical trials. This article reviews current data on the clinical validity and utility of TILs in BC in an effort to foster better knowledge and insight in this rapidly evolving field, and to develop a standardized methodology for visual assessment on H&E sections, acknowledging the future potential of molecular/multiplexed approaches.
The methodology provided is sufficiently detailed to offer a uniformly applied, pragmatic starting point and improve consistency and reproducibility in the measurement of TILs for future studies.
With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding ...accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: “Definitive,” “Strong,” “Moderate,” “Limited,” “No Reported Evidence,” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.
Abstract
BACKGROUND
Human male infertility has a notable genetic component, including well-established diagnoses such as Klinefelter syndrome, Y-chromosome microdeletions and monogenic causes. ...Approximately 4% of all infertile men are now diagnosed with a genetic cause, but a majority (60–70%) remain without a clear diagnosis and are classified as unexplained. This is likely in large part due to a delay in the field adopting next-generation sequencing (NGS) technologies, and the absence of clear statements from field leaders as to what constitutes a validated cause of human male infertility (the current paper aims to address this). Fortunately, there has been a significant increase in the number of male infertility NGS studies. These have revealed a considerable number of novel gene–disease relationships (GDRs), which each require stringent assessment to validate the strength of genotype–phenotype associations. To definitively assess which of these GDRs are clinically relevant, the International Male Infertility Genomics Consortium (IMIGC) has identified the need for a systematic review and a comprehensive overview of known male infertility genes and an assessment of the evidence for reported GDRs.
OBJECTIVE AND RATIONALE
In 2019, the first standardised clinical validity assessment of monogenic causes of male infertility was published. Here, we provide a comprehensive update of the subsequent 1.5 years, employing the joint expertise of the IMIGC to systematically evaluate all available evidence (as of 1 July 2020) for monogenic causes of isolated or syndromic male infertility, endocrine disorders or reproductive system abnormalities affecting the male sex organs. In addition, we systematically assessed the evidence for all previously reported possible monogenic causes of male infertility, using a framework designed for a more appropriate clinical interpretation of disease genes.
SEARCH METHODS
We performed a literature search according to the PRISMA guidelines up until 1 July 2020 for publications in English, using search terms related to ‘male infertility’ in combination with the word ‘genetics’ in PubMed. Next, the quality and the extent of all evidence supporting selected genes were assessed using an established and standardised scoring method. We assessed the experimental quality, patient phenotype assessment and functional evidence based on gene expression, mutant in-vitro cell and in-vivo animal model phenotypes. A final score was used to determine the clinical validity of each GDR, across the following five categories: no evidence, limited, moderate, strong or definitive. Variants were also reclassified according to the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines and were recorded in spreadsheets for each GDR, which are available at imigc.org.
OUTCOMES
The primary outcome of this review was an overview of all known GDRs for monogenic causes of human male infertility and their clinical validity. We identified a total of 120 genes that were moderately, strongly or definitively linked to 104 infertility phenotypes.
WIDER IMPLICATIONS
Our systematic review curates all currently available evidence to reveal the strength of GDRs in male infertility. The existing guidelines for genetic testing in male infertility cases are based on studies published 25 years ago, and an update is far overdue. The identification of 104 high-probability ‘human male infertility genes’ is a 33% increase from the number identified in 2019. The insights generated in the current review will provide the impetus for an update of existing guidelines, will inform novel evidence-based genetic testing strategies used in clinics, and will identify gaps in our knowledge of male infertility genetics. We discuss the relevant international guidelines regarding research related to gene discovery and provide specific recommendations to the field of male infertility. Based on our findings, the IMIGC consortium recommend several updates to the genetic testing standards currently employed in the field of human male infertility, most important being the adoption of exome sequencing, or at least sequencing of the genes validated in this study, and expanding the patient groups for which genetic testing is recommended.
This study was designed to test the upper limits of the Rey-15’s classification accuracy in cognitively intact university students and clinical patients. A brief battery of neuropsychological tests ...was administered to all participants. Students were randomly assigned to either the control ( n = 80) or experimental malingering ( n = 59) condition. Invalid performance in patients ( n = 52) was psychometrically defined. The classification accuracy of the Rey-15 (original free recall and the combination score including the recognition trial developed by Boone et al., 2002) was computed across a range of cutoffs. A free recall ≤ 13 and combination score ≤ 25 produced a good combination of sensitivity (.41–.70) and specificity (.90–.94) among students. The highest cutoff to reach .90 specificity in clinical patients was free recall ≤ 11 and combination score ≤ 23, at .38–.56 sensitivity. Results confirmed the previous reports that more liberal alternative cutoffs maintain adequate specificity. Cutoffs can be raised even further in cognitively intact examinees. The introduction of the recognition trial provided a significant boost to the instrument’s classification accuracy. The Rey-15 remains a cost-effective and clinically useful test in both clinical and research settings. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: journal abstract)
Aim
The Structured Clinical Interview for the DSM is one of the most used diagnostic instruments in clinical research worldwide. The current Clinician Version of the instrument (SCID‐5‐CV) has not ...yet been assessed in respect to its psychometric qualities. We aimed to assess the clinical validity and different reliability indicators (interrater test–retest, joint interview, face‐to‐face vs telephone application) of the SCID‐5‐CV in a large sample of 180 non‐prototypical and psychiatric patients based on interviews conducted by raters with different levels of clinical experience.
Methods
The SCID‐5‐CV was administered face‐to‐face and by telephone by 12 psychiatrists/psychologists who took turns as raters and observers. Clinical diagnoses were established according to DSM‐5 criteria and the longitudinal, expert, all data (LEAD) procedure. We calculated the percentage of agreement, diagnostic sensitivity and specificity, and the level of agreement (kappa) for diagnostic categories and specific diagnoses.
Results
The percentage of positive agreement between the interview and clinical diagnoses ranged between 73% and 97% and the diagnostic sensitivity/specificity were >0.70. In the joint interview, the levels of positive agreement were high (>75%) and kappa levels were >0.70 for most diagnoses. The values were less expressive, but still adequate, for interrater test–retest interviews.
Conclusion
The SCID‐5‐CV presented excellent reliability and high specificity as assessed with different methods. The clinical validity of the instrument was also confirmed, which supports its use in daily clinical practice. We highlight the adequacy of the instrument to be used via telephone and the need for careful use by professionals with little experience in psychiatric clinical practice.
Abstract
STUDY QUESTION
Which genes are confidently linked to human monogenic male infertility?
SUMMARY ANSWER
Our systematic literature search and clinical validity assessment reveals that a total ...of 78 genes are currently confidently linked to 92 human male infertility phenotypes.
WHAT IS KNOWN ALREADY
The discovery of novel male infertility genes is rapidly accelerating with the availability of next-generating sequencing methods, but the quality of evidence for gene-disease relationships varies greatly. In order to improve genetic research, diagnostics and counseling, there is a need for an evidence-based overview of the currently known genes.
STUDY DESIGN, SIZE, DURATION
We performed a systematic literature search and evidence assessment for all publications in Pubmed until December 2018 covering genetic causes of male infertility and/or defective male genitourinary development.
PARTICIPANTS/MATERIALS, SETTING, METHODS
Two independent reviewers conducted the literature search and included papers on the monogenic causes of human male infertility and excluded papers on genetic association or risk factors, karyotype anomalies and/or copy number variations affecting multiple genes. Next, the quality and the extent of all evidence supporting selected genes was weighed by a standardized scoring method and used to determine the clinical validity of each gene-disease relationship as expressed by the following six categories: no evidence, limited, moderate, strong, definitive or unable to classify.
MAIN RESULTS AND THE ROLE OF CHANCE
From a total of 23 526 records, we included 1337 publications about monogenic causes of male infertility leading to a list of 521 gene-disease relationships. The clinical validity of these gene-disease relationships varied widely and ranged from definitive (n = 38) to strong (n = 22), moderate (n = 32), limited (n = 93) or no evidence (n = 160). A total of 176 gene-disease relationships could not be classified because our scoring method was not suitable.
LARGE SCALE DATA
Not applicable.
LIMITATIONS, REASONS FOR CAUTION
Our literature search was limited to Pubmed.
WIDER IMPLICATIONS OF THE FINDINGS
The comprehensive overview will aid researchers and clinicians in the field to establish gene lists for diagnostic screening using validated gene-disease criteria and help to identify gaps in our knowledge of male infertility. For future studies, the authors discuss the relevant and important international guidelines regarding research related to gene discovery and provide specific recommendations for the field of male infertility.
STUDY FUNDING/COMPETING INTEREST(S)
This work was supported by a VICI grant from The Netherlands Organization for Scientific Research (918-15-667 to J.A.V.), the Royal Society, and Wolfson Foundation (WM160091 to J.A.V.) as well as an investigator award in science from the Wellcome Trust (209451 to J.A.V.).
PROSPERO REGISTRATION NUMBER
None.
Despite the rapid uptake of multigene panel testing (MGPT) for hereditary cancer predisposition, there is limited guidance surrounding indications for testing and genes to include.
To inform the ...clinical approach to hereditary cancer MGPT, we comprehensively evaluated 32 cancer predisposition genes by assessing phenotype-specific pathogenic variant (PV) frequencies, cancer risk associations, and performance of genetic testing criteria in a cohort of 165,000 patients referred for MGPT.
We identified extensive genetic heterogeneity surrounding predisposition to cancer types commonly referred for germline testing (breast, ovarian, colorectal, uterine/endometrial, pancreatic, and melanoma). PV frequencies were highest among patients with ovarian cancer (13.8%) and lowest among patients with melanoma (8.1%). Fewer than half of PVs identified in patients meeting testing criteria for only BRCA1/2 or only Lynch syndrome occurred in the respective genes (33.1% and 46.2%). In addition, 5.8% of patients with PVs in BRCA1/2 and 26.9% of patients with PVs in Lynch syndrome genes did not meet respective testing criteria.
Opportunities to improve upon identification of patients at risk for hereditary cancer predisposition include revising BRCA1/2 and Lynch syndrome testing criteria to include additional clinically actionable genes with overlapping phenotypes and relaxing testing criteria for associated cancers.
The prognostic role of circulating tumor cells (CTCs) has been clearly demonstrated in many types of cancer. However, their roles in diagnostic and treatment strategies remain to be defined. In this ...review, we present an overview of the current clinical validity of CTCs in nonmetastatic and metastatic cancer, and the main studies or concepts investigating the clinical utility of CTCs. In particular, we focus on breast, lung, colorectal, and prostate cancer. Two major topics concerning the clinical utility of CTC are discussed: treatment based on CTC count or CTC variations, and treatment based on the molecular characteristics of CTCs. Although some of these studies are inconclusive, many are still ongoing, and their results could help to define the role of CTCs in the management of cancers. A summary of published or ongoing phase II‐III trials is also presented.
This review article discusses the clinical utility of circulating tumor cells (CTCs) in various settings of screening and treatment of non‐metastatic and metastatic tumors. Two major aspects are considered, namely i) treatment based on CTC count or CTC variations, and ii) treatment based on the molecular characteristics of CTCs. A summary of published or ongoing phase II‐III trials with CTCs is also presented.
•Pharmacogenomics (PGx) can be used to identify gene-drug interactions (GDI)•PGx tests or single-gene guidelines are often used to guide prescribing based on GDI•Only the PGx test predicted variation ...in outcomes for patients with depression•Both single-gene guidelines and the PGx test predicted medication blood levels•The combinatorial PGx test was a better predictor than the single-gene guidelines
We evaluated the clinical validity of a combinatorial pharmacogenomic test and single-gene Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines against patient outcomes and medication blood levels to assess their ability to inform prescribing in major depressive disorder (MDD).
This is a secondary analysis of the Genomics Used to Improve DEpression Decisions (GUIDED) randomized-controlled trial, which included patients with a diagnosis of MDD, and ≥1 prior medication failure. The ability to predict increased/decreased medication metabolism was validated against blood levels at screening (adjusted for age, sex, smoking status). The ability of predicted gene-drug interactions (pharmacogenomic test) or therapeutic recommendations (single-gene guidelines) to predict patient outcomes was validated against week 8 outcomes (17-item Hamilton Depression Rating Scale; symptom improvement, response, remission). Analyses were performed for patients taking any eligible medication (outcomes N=1,022, blood levels N=1,034) and the subset taking medications with single-gene guidelines (outcomes N=584, blood levels N=372). The combinatorial pharmacogenomic test was the only significant predictor of patient outcomes. Both the combinatorial pharmacogenomic test and single-gene guidelines were significant predictors of blood levels for all medications when evaluated separately; however, only the combinatorial pharmacogenomic test remained significant when both were included in the multivariate model. There were no substantial differences when all medications were evaluated or for the subset with single-gene guidelines. Overall, this evaluation of clinical validity demonstrates that the combinatorial pharmacogenomic test was a superior predictor of patient outcomes and medication blood levels when compared with guidelines based on individual genes.
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