Sorafenib as a feasible therapeutic option in haemophiliacs with hepatocellular carcinoma

hepatocellular carcinoma, haemophilia, treatmen

clinical and psychometric validation of the bresas questionnaire for symptom assessment among breast cancer survivors

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Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report.

The vocabulary currently used to describe genetic variants and their consequences reflects many years of studying and discovering monogenic disease with high penetrance. With the recent rapid expansion of genetic testing brought about by wide availability of high-throughput massively parallel sequencing platforms, accurate variant interpretation has become a major issue. The vocabulary used to describe single genetic variants in silico, in vitro, in vivo and as a contributor to human disease uses terms in common, but the meaning is not necessarily shared across all these contexts. In the setting of cancer genetic tests, the added dimension of using data from genetic sequencing of tumour DNA to direct treatment is an additional source of confusion to those who are not experienced in cancer genetics. The language used to describe variants identified in cancer susceptibility genetic testing typically still reflects an outdated paradigm of Mendelian inheritance with dichotomous outcomes. Cancer is a common disease with complex genetic architecture; an improved lexicon is required to better communicate among scientists, clinicians and patients, the risks and implications of genetic variants detected. This review arises from a recognition of, and discussion about, inconsistencies in vocabulary usage by members of the ENIGMA international multidisciplinary consortium focused on variant classification in breast-ovarian cancer susceptibility genes. It sets out the vocabulary commonly used in genetic variant interpretation and reporting, and suggests a framework for a common vocabulary that may facilitate understanding and clarity in clinical reporting of germline genetic tests for cancer susceptibility

Conversation analysis and online interaction

At the same time as Harvey Sacks was developing conversation analysis (CA), at the same institution a young graduate student attempted to type the word “login” into a computer; this message would then be sent to another computer in a different lab. Unfortunately the system crashed after the letters ‘L’ and ‘O’ were sent, and so the first word to be sent via the internet (or at least the pre-cursor to it) was ‘LO’ or perhaps, if we want to read it as such, ‘hello’. The fact that the first message sent via the ‘internet’ was, somewhat accidentally, a standard greeting is a foreshadowing of the fact that the internet has become a predominantly interactional medium. Online communication has grown exponentially since that first message. There are currently an estimated 269 billion e-mails, 55 billion Whatsapp messages, over 9.5 billion Instagram photos and videos, and around 500 million tweets sent per day. Online interaction is a worldwide phenomenon, with users of Chinese social media site, Weibo, sending over 100 million messages each day and about 38 billion messages sent every day on WeChat, the Chinese instant messaging service. As conversation analysts are interested in interaction as the primordial site of sociality, the internet is an enormous and ever-growing site of interaction, and as such should be a clear focus for exploring social life. This review provides an overview of what we already know from studies of CA and online interaction. It will argue that going forward there should be more impetus to explore this area of interaction, not only in its own right but also for what it tells us about human interaction more generally. This paper will show how CA can offer real insight into the organization of online interaction, particularly in relation to the potential affordances and constraints of the interaction

The BRCA2 c.68-7T > A variant is not pathogenic : A model for clinical calibration of spliceogenicity

Although the spliceogenic nature of the BRCA2 c.68-7T > A variant has been demonstrated, its association with cancer risk remains controversial. In this study, we accurately quantified by real-time PCR and digital PCR (dPCR), the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case-control analysis in 83,636 individuals. Co-occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5-fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68-7T > A allele of approximately 20%. The posterior probability of pathogenicity was 7.44x10(-115). There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86-1.24) nor for a deleterious effect of the variant when co-occurring with pathogenic variants. Our data provide for the first time robust evidence of the nonpathogenicity of the BRCA2 c.68-7T > A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants.Peer reviewe

The BRCA2 c.68-7T > A variant is not pathogenic: A model for clinical calibration of spliceogenicity.

Although the spliceogenic nature of the BRCA2 c.68-7T>A variant has been demonstrated, its association with cancer risk remains ontroversial. In this study, we accurately quantified by real-time PCR and digital PCR the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case-control analysis in 83,636 individuals. Co-occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5-fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68-7T>A allele of approximately 20%. The posterior probability of pathogenicity was 7.44 x 10-115. There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86-1.24), nor for a deleterious effect of the variant when co-occurring with pathogenic variants. Our data provide for the first time robust evidence of the non-pathogenicity of the BRCA2 c.68-7T>A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe