Genes associated with hereditary breast and ovarian cancer (HBOC) and colorectal cancer (CRC) predisposition have been shown to play a role in pancreatic cancer susceptibility. Growing evidence ...suggests that pancreatic cancer may be useful as a sentinel cancer to identify families that could benefit from HBOC or CRC surveillance, but to date pancreatic cancer is only considered an indication for genetic testing in the context of additional family history.
Preliminary data generated at the Huntsman Cancer Hospital (HCH) included variants identified on a custom 34-gene panel or 59-gene panel including both known HBOC and CRC genes for respective sets of 66 and 147 pancreatic cancer cases, unselected for family history. Given the strength of preliminary data and corresponding literature, 61 sequential pancreatic cancer cases underwent a custom 14-gene clinical panel. Sequencing data from HCH pancreatic cancer cases, pancreatic cancer cases of the Cancer Genome Atlas (TCGA), and an unselected pancreatic cancer screen from the Mayo Clinic were combined in a meta-analysis to estimate the proportion of carriers with pathogenic and high probability of pathogenic variants of uncertain significance (HiP-VUS).
Approximately 8.6% of unselected pancreatic cancer cases at the HCH carried a variant with potential HBOC or CRC screening recommendations. A meta-analysis of unselected pancreatic cancer cases revealed that approximately 11.5% carry a pathogenic variant or HiP-VUS.
With the inclusion of both HBOC and CRC susceptibility genes in a panel test, unselected pancreatic cancer cases act as a useful sentinel cancer to identify asymptomatic at-risk relatives who could benefit from relevant HBOC and CRC surveillance measures.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
BRCA1 is a high-risk susceptibility gene for breast and ovarian cancer. Pathogenic protein-truncating variants are scattered across the open reading frame, but all known missense substitutions that ...are pathogenic because of missense dysfunction are located in either the amino-terminal RING domain or the carboxy-terminal BRCT domain. Heterodimerization of the BRCA1 and BARD1 RING domains is a molecularly defined obligate activity. Hence, we tested every BRCA1 RING domain missense substitution that can be created by a single nucleotide change for heterodimerization with BARD1 in a mammalian two-hybrid assay. Downstream of the laboratory assay, we addressed three additional challenges: assay calibration, validation thereof, and integration of the calibrated results with other available data, such as computational evidence and patient/population observational data to achieve clinically applicable classification. Overall, we found that 15%–20% of BRCA1 RING domain missense substitutions are pathogenic. Using a Bayesian point system for data integration and variant classification, we achieved clinical classification of 89% of observed missense substitutions. Moreover, among missense substitutions not present in the human observational data used here, we find an additional 45 with concordant computational and functional assay evidence in favor of pathogenicity plus 223 with concordant evidence in favor of benignity; these are particularly likely to be classified as likely pathogenic and likely benign, respectively, once human observational data become available.
Germline pathogenic variants in the TP53 gene cause Li‐Fraumeni syndrome, a condition that predisposes individuals to a wide range of cancer types. Identification of individuals carrying a
TP53 ...pathogenic variant is linked to clinical management decisions, such as the avoidance of radiotherapy and use of high‐intensity screening programs. The aim of this study was to develop an evidence‐based quantitative model that integrates independent in silico data (Align‐GVGD and BayesDel) and somatic to germline ratio (SGR), to assign pathogenicity to every possible missense variant in the
TP53 gene. To do this, a likelihood ratio for pathogenicity (LR) was derived from each component calibrated using reference sets of assumed pathogenic and benign missense variants. A posterior probability of pathogenicity was generated by combining LRs, and algorithm outputs were validated using different approaches. A total of 730
TP53 missense variants could be assigned to a clinically interpretable class. The outputs of the model correlated well with existing clinical information, functional data, and ClinVar classifications. In conclusion, these quantitative outputs provide the basis for individualized assessment of cancer risk useful for clinical interpretation. In addition, we propose the value of the novel SGR approach for use within the ACMG/AMP guidelines for variant classification.
Germline pathogenic missense variants in the TP53 gene predispose individuals to a wide range of cancer types but are often difficult to interpret. The output from in silico tools and an analysis of the relationship between reported somatic and germline variants in the IARC
TP53 database were used to construct a quantitative model of variant pathogenicity. The model was validated against a range of existing data and used to generate clinically interpretable classifications for 730 unique
TP53 missense variants.
Prediction of the biological effect of missense substitutions has become important because they are often observed in known or candidate disease susceptibility genes. In this paper, we carried out a ...3-step analysis of 1514 missense substitutions in the DNA-binding domain (DBD) of TP53, the most frequently mutated gene in human cancers. First, we calculated two types of conservation scores based on a TP53 multiple sequence alignment (MSA) for each substitution: (i) Grantham Variation (GV), which measures the degree of biochemical variation among amino acids found at a given position in the MSA; (ii) Grantham Deviation (GD), which reflects the ‘biochemical distance’ of the mutant amino acid from the observed amino acid at a particular position (given by GV). Second, we used a method that combines GV and GD scores, Align-GVGD, to predict the transactivation activity of each missense substitution. We compared our predictions against experimentally measured transactivation activity (yeast assays) to evaluate their accuracy. Finally, the prediction results were compared with those obtained by the program Sorting Intolerant from Tolerant (SIFT) and Dayhoff's classification. Our predictions yielded high prediction accuracy for mutants showing a loss of transactivation (∼88% specificity) with lower prediction accuracy for mutants with transactivation similar to that of the wild-type (67.9 to 71.2% sensitivity). Align-GVGD results were comparable to SIFT (88.3 to 90.6% and 67.4 to 70.3% specificity and sensitivity, respectively) and outperformed Dayhoff's classification (80 and 40.9% specificity and sensitivity, respectively). These results further demonstrate the utility of the Align-GVGD method, which was previously applied to BRCA1. Align-GVGD is available online at http://agvgd.iarc.fr.
Functional assays that assess mRNA splicing can be used in interpretation of the clinical significance of sequence variants, including the Lynch syndrome-associated mismatch repair (MMR) genes. The ...purpose of this study was to investigate the contribution of splicing assay data to the classification of MMR gene sequence variants. We assayed mRNA splicing for 24 sequence variants in
,
, and
, including 12 missense variants that were also assessed using a cell-free
MMR activity (CIMRA) assay. Multifactorial likelihood analysis was conducted for each variant, combining CIMRA outputs and clinical data where available. We collated these results with existing public data to provide a dataset of splicing assay results for a total of 671 MMR gene sequence variants (328 missense/in-frame indel), and published and unpublished repair activity measurements for 154 of these variants. There were 241 variants for which a splicing aberration was detected: 92 complete impact, 33 incomplete impact, and 116 where it was not possible to determine complete versus incomplete splicing impact. Splicing results mostly aided in the interpretation of intronic (72%) and silent (92%) variants and were the least useful for missense substitutions/in-frame indels (10%). MMR protein functional activity assays were more useful in the analysis of these exonic variants but by design they were not able to detect clinically important splicing aberrations identified by parallel mRNA assays. The development of high throughput assays that can quantitatively assess impact on mRNA transcript expression and protein function in parallel will streamline classification of MMR gene sequence variants.
Individuals with multiple primary melanomas have rates of germline CDKN2A pathogenic variants of 3%-18%, and are also frequent carriers of variants in the melanocortin-1 receptor. Few patients with ...numerous (≥3) primary melanomas have been studied with respect to these or other potential germline pathogenic variants. We investigated 46 patients with ≥3 primary melanomas (3, n = 17; 4, n = 14; 5-14, n = 15) to determine if higher rates of germline pathogenic variants of CDKN2A, MC1R, or other cancer genes could explain their extreme melanoma phenotype. Most (43/46, 93%) patients had variants in MC1R and 11/46 (24%) had CDKN2A pathogenic variants, but only male sex and having two variants in MC1R correlated with increasing number of melanomas. Panel screening of 56 other cancer predisposition genes did not reveal other germline pathogenic variants associated with melanoma (CDK4, BAP1, POT1), although pathogenic variants in TP53, CHEK2, and BRCA2 were present in three separate patients and some patients had variants of uncertain significance. In summary, targeted germline sequencing of patients with ≥3 primary melanomas revealed a high rate of pathogenic variants in CDKN2A and other known cancer genes. Although further investigation of these pathogenic variants and variants of uncertain significance is needed, these results support cancer gene panel testing in individuals diagnosed with ≥3 melanomas.
The 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification publication established a standard employed internationally to guide ...laboratories in variant assessment. Those recommendations included both pathogenic (PP1) and benign (BS4) criteria for evaluating the inheritance patterns of variants, but details of how to apply those criteria at appropriate evidence levels were sparse. Several publications have since attempted to provide additional guidance, but anecdotally, this issue is still challenging. Additionally, it is not clear that those prior efforts fully distinguished disease-gene identification considerations from variant pathogenicity considerations nor did they address autosomal-recessive and X-linked inheritance. Here, we have taken a mixed inductive and deductive approach to this problem using real diseases as examples. We have developed a practical heuristic for genetic co-segregation evidence and have also determined that the specific phenotype criterion (PP4) is inseparably coupled to the co-segregation criterion. We have also determined that negative evidence at one locus constitutes positive evidence for other loci for disorders with locus heterogeneity. Finally, we provide a points-based system for evaluating phenotype and co-segregation as evidence types to support or refute a locus and show how that can be integrated into the Bayesian framework now used for variant classification and consistent with the 2015 guidelines.
The 2015 ACMG/AMP variant classification recommendations included pathogenic (PP1) and benign (BS4) criteria for co-segregation, but details for using them were sparse. We developed a points-based co-segregation heuristic and integrated the specific phenotype criterion (PP4). We also show that negative evidence at one locus constitutes positive evidence for other loci.
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