Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants

Unravelling the Relacatib activity against the CTSK proteins causing pycnodysostosis: a molecular docking and dynamics approach

Pycnodysostosis is an atypical autosomal recessive condition of Lysosomal storage disorder that originated due to the deficit of the enzyme Cathepsin K which is vital for normal osteoclast action in bone resorption. Abnormal degradation of type 1 collagen and accumulation of toxic undigested collagen fibers in lysosomes of the osteoclast cells resulting in high bone density, brittle bones, and a short stature is caused in CTSK protein-carrying individuals. The broad aim of this study is to identify the most significant variant through various computational pipelines. This study was initiated by retrieving a total number of thirty-six variants from NCBI, HGMD, and UniProt databases, and the Y283C variant was found to be more significant by various standard computational tools. A structural investigation was performed to understand and gain a better knowledge about the interaction profile for the native (1BY8) and variant (Y283C) with Relacatib (a small-molecule drug that blocks the function of Cathepsin K, an enzyme that has been linked to osteoporosis, osteoarthritis, and other bone-degrading diseases). The interaction profile was analyzed using molecular docking. Relacatib (ligand) had an average binding affinity for both native (-7.16 kcal/mol) and Y283C (-6.76 kcal/mol). Finally, Molecular dynamics simulations were done in duplicates to recognize the variant (Y283C) activity of the protein structure against Relacatib for 100 ns. This study assists in comprehending the most pathogenic amino-acid variant, the ligand interaction with the protein structure, and paves the way for understanding the steadiness of the ligand with the native and selected significant amino-acid variant.Communicated by Ramaswamy H. Sarma.

A computational approach to analyzing the functional and structural impacts of Tripeptidyl-Peptidase 1 missense mutations in neuronal ceroid lipofuscinosis

Neuronal ceroid-lipofuscinosis (NCLs) are a group of severe neurodegenerative conditions, most likely present in infantile, late infantile, juvenile, and adult-onset forms. Their phenotypic characteristics comprise eyesight damage, reduced motor activity and cognitive function, and sometimes tend to die in the initial stage. In recent studies, NCLs have been categorized into at least 14 genetic collections (CLN1-14). CLN2 gene encodes Tripeptidyl peptidase 1 (TPP1), which affects late infantile-onset form. In this study, we retrieved a mutational dataset screening for TPP1 protein from various databases (ClinVar, UniProt, HGMD). Fifty-six missense mutants were enumerated with computational methods to perceive the significant mutants (G475R and G501C) and correlated with clinical and literature data. A structure-based screening method was initiated to understand protein-ligand interaction and dynamic simulation. The docking procedure was performed for the native (3EDY) and mutant (G473R and G501C) structures with Gemfibrozil (gem), which lowers the lipid level, decreases the triglycerides amount in the blood circulation, and controls hyperlipidemia. The Native had an interaction score of -5.57 kcal/mol, and the mutants had respective average binding scores of -6.24 (G473R) and - 5.17 (G501C) kcal/mol. Finally, molecular dynamics simulation showed that G473R and G501C mutants had better flexible and stable orientation in all trajectory analyses. Therefore, this work gives an extended understanding of both functional and structural levels of influence for the mutant form that leads to NCL disorder.

Choosing Variant Interpretation Tools for Clinical Applications: Context Matters

Pathogenicity predictors are computational tools that classify genetic variants as benign or pathogenic; this is currently a major challenge in genomic medicine. With more than fifty such predictors available, selecting the most suitable tool for clinical applications like genetic screening, molecular diagnostics, and companion diagnostics has become increasingly challenging. To address this issue, we have developed a cost-based framework that naturally considers the various components of the problem. This framework encodes clinical scenarios using a minimal set of parameters and treats pathogenicity predictors as rejection classifiers, a common practice in clinical applications where low-confidence predictions are routinely rejected. We illustrate our approach in four examples where we compare different numbers of pathogenicity predictors for missense variants. Our results show that no single predictor is optimal for all clinical scenarios and that considering rejection yields a different perspective on classifiers.

Computational approaches for predicting variant impact: An overview from resources, principles to applications

One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.

Comprehensive evaluation and efficient classification of BRCA1 RING domain missense substitutions

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.

TP53_PROF: a machine learning model to predict impact of missense mutations in TP53

Correctly identifying the true driver mutations in a patient’s tumor is a major challenge in precision oncology. Most efforts address frequent mutations, leaving medium- and low-frequency variants mostly unaddressed. For TP53, this identification is crucial for both somatic and germline mutations, with the latter associated with the Li-Fraumeni syndrome (LFS), a multiorgan cancer predisposition. We present TP53_PROF (prediction of functionality), a gene specific machine learning model to predict the functional consequences of every possible missense mutation in TP53, integrating human cell- and yeast-based functional assays scores along with computational scores. Variants were labeled for the training set using well-defined criteria of prevalence in four cancer genomics databases. The model’s predictions provided accuracy of 96.5%. They were validated experimentally, and were compared to population data, LFS datasets, ClinVar annotations and to TCGA survival data. Very high accuracy was shown through all methods of validation. TP53_PROF allows accurate classification of TP53 missense mutations applicable for clinical practice. Our gene specific approach integrated machine learning, highly reliable features and biological knowledge, to create an unprecedented, thoroughly validated and clinically oriented classification model. This approach currently addresses TP53 mutations and will be applied in the future to other important cancer genes.

Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2, and HBB associated with haemoglobinopathies

Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework.

Prevalence of germline TP53 mutation among early onset middle eastern breast cancer patients

Background

The data on prevalence and clinical relevance of TP53 germline mutations in early onset Middle-Eastern breast cancer (BC) is limited.

Methods

We determined TP53 germline mutations in a cohort of 464 early onset BC patients from Saudi Arabia using capture sequencing based next generation sequencing.

Results

Germline TP53 pathogenic mutations were found in 1.5% (7/464) of early onset Saudi BC patients. A total of six pathogenic missense mutations, one stop gain mutation and two variants of uncertain significance (VUS) were detected in our cohort. No TP53 pathogenic mutations were detected among 463 healthy controls. TP53 mutations carriers were significantly more likely to have bilateral breast cancer (p = 0.0008). At median follow-up of 41 months, TP53 mutations were an unfavorable factor for overall survival in univariate analysis. All the patients carrying TP53 mutations were negative for BRCA1 and BRCA2 mutations. Majority of patients (85.7%; 6/7) carrying TP53 mutation had no family history suggestive of Li-Fraumeni Syndrome (LFS) or personal history of multiple LFS related tumors. Only one patient had a positive family history suggestive of LFS.

Conclusions

TP53 germline mutation screening detects a clinically meaningful risk of early onset BC from this ethnicity and should be considered in all early onset BC regardless of the family history of cancer, especially in young patients that are negative for BRCA mutations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13053-021-00206-w.

A Novel Germline TP53 Mutation in a Patient With Li-Fraumeni Syndrome: Resolving a Variant of Uncertain Significance

Increasing availability of genomic testing poses new challenges to clinicians, particularly where variant interpretation from commercial sources may be equivocal. The authors report a patient with recurrent rhabdomyosarcoma and subsequent bilateral breast cancer who was found to harbor a previously undescribed germline TP53 sequence alteration annotated by the commercial laboratory as a variant of uncertain significance. By investigating publicly available databases of aggregated normal germline and malignant somatic genomic sequences, the authors conclude that this missense variant, c.476C>T (p.A159V), is a novel, pathogenic Li-Fraumeni syndrome mutation and demonstrate the utility of these resources in clinical pediatric hematology and oncology practice.

Clinical and Functional Significance of TP53 Exon 4-Intron 4 Splice Junction Variants

Germline TP53 splicing variants are uncommon, and their clinical relevance is unknown. However, splice-altering variants at exon 4-intron 4 junctions are relatively enriched in pediatric adrenocortical tumors (ACT). Nevertheless, family histories of cancer compatible with classic Li-Fraumeni syndrome are rarely seen in these patients. We used conventional and in silico assays to determine protein stability, splicing, and transcriptional activity of 10 TP53 variants at exon 4-intron 4 junctions and analyzed their clinical correlates. We reviewed public databases that report the impact of TP53 variants in human cancer and examined individual reports, focusing on family history of cancer. TP53 exon 4-intron 4 junction germline variants were identified in 9 of 75 pediatric ACTs enrolled in the International Pediatric Adrenocortical Tumor Registry and Children's Oncology Group ARAR0332 study. An additional eight independent TP53 variants involving exon 4 splicing were identified in the Pediatric Cancer Genome Project (n = 5,213). These variants resulted in improper expression due to ineffective splicing, protein instability, altered subcellular localization, and loss of function. Clinical case review of carriers of TP53 exon 4-intron 4 junction variants revealed a high incidence of pediatric ACTs and atypical tumor types not consistent with classic Li-Fraumeni syndrome. Germline variants involving TP53 exon 4-intron 4 junctions are frequent in ACT and rare in other pediatric tumors. The collective impact of these germline TP53 variants on the fidelity of splicing, protein structure, and function must be considered in evaluating cancer susceptibility. IMPLICATIONS: Taken together, the data indicate that splice variants at TP53 codon 125 and surrounding bases differentially impacted p53 gene expression and function.

An updated quantitative model to classify missense variants in the TP53 gene: A novel multifactorial strategy

Multigene panel testing has led to an increase in the number of variants of uncertain significance identified in the TP53 gene, associated with Li-Fraumeni syndrome. We previously developed a quantitative model for predicting the pathogenicity of P53 missense variants based on the combination of calibrated bioinformatic information and somatic to germline ratio. Here, we extended this quantitative model for the classification of P53 predicted missense variants by adding new pieces of evidence (personal and family history parameters, loss-of-function results, population allele frequency, healthy individual status by age 60, and breast tumor pathology). We also annotated which missense variants might have an effect on splicing based on bioinformatic predictions. This updated model plus annotation led to the classification of 805 variants into a clinically relevant class, which correlated well with existing ClinVar classifications, and resolved a large number of conflicting and uncertain classifications. We propose this model as a reliable approach to TP53 germline variant classification and emphasize its use in contributing to optimize TP53-specific ACMG/AMP guidelines.

Targeted Sequencing of Sorted Esophageal Adenocarcinoma Cells Unveils Known and Novel Mutations in the Separated Subpopulations

INTRODUCTION

Our study aimed at investigating tumor heterogeneity in esophageal adenocarcinoma (EAC) cells regarding clinical outcomes.

METHODS

Thirty-eight surgical EAC cases who underwent gastroesophageal resection with lymph node dissection in 3 university centers were included. Archival material was analyzed via high-throughput cell sorting technology and targeted sequencing of 63 cancer-related genes. Low-pass sequencing and immunohistochemistry (IHC) were used to validate the results.

RESULTS

Thirty-five of 38 EACs carried at least one somatic mutation that was absent in the stromal cells; 73.7%, 10.5%, and 10.5% carried mutations in tumor protein 53, cyclin dependent kinase inhibitor 2A, and SMAD family member 4, respectively. In addition, 2 novel mutations were found for hepatocyte nuclear factor-1 alpha in 2 of 38 cases. Tumor protein 53 gene abnormalities were more informative than p53 IHC. Conversely, loss of SMAD4 was more frequently noted with IHC (53%) and was associated with a higher recurrence rate (P = 0.015). Only through cell sorting we were able to detect the presence of hyperdiploid and pseudodiploid subclones in 7 EACs that exhibited different mutational loads and/or additional copy number amplifications, indicating the high genetic heterogeneity of these cancers.

DISCUSSION

Selective cell sorting allowed the characterization of multiple molecular defects in EAC subclones that were missed in a significant number of cases when whole-tumor samples were analyzed. Therefore, this approach can reveal subtle differences in cancer cell subpopulations. Future studies are required to investigate whether these subclones are responsible for treatment response and disease recurrence.

Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene

Infrequent and rare genetic variants in the human population vastly outnumber common ones. Although they may contribute significantly to the genetic basis of a disease, these seldom-encountered variants may also be miss-identified as pathogenic if no correct references are available. Somatic and germline TP53 variants are associated with multiple neoplastic diseases, and thus have come to serve as a paradigm for genetic analyses in this setting. We searched 14 independent, globally distributed datasets and recovered TP53 SNPs from 202,767 cancer-free individuals. In our analyses, 19 new missense TP53 SNPs, including five novel variants specific to the Asian population, were recurrently identified in multiple datasets. Using a combination of in silico, functional, structural, and genetic approaches, we showed that none of these variants displayed loss of function compared to the normal TP53 gene. In addition, classification using ACMG criteria suggested that they are all benign. Considered together, our data reveal that the TP53 coding region shows far more polymorphism than previously thought and present high ethnic diversity. They furthermore underline the importance of correctly assessing novel variants in all variant-calling pipelines associated with genetic diagnoses for cancer.

Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants

Germline pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a cancer predisposition disorder inherited in an autosomal dominant pattern associated with a high risk of malignancy, including early-onset breast cancers, sarcomas, adrenocortical carcinomas, and brain tumors. Intense cancer surveillance for individuals with TP53 germline pathogenic variants is associated with reduced cancer-related mortality. Accurate and consistent classification of germline variants across clinical and research laboratories is important to ensure appropriate cancer surveillance recommendations. Here, we describe the work performed by the Clinical Genome Resource TP53 Variant Curation Expert Panel (ClinGen TP53 VCEP) focused on specifying the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification to the TP53 gene. Specifications were developed for 20 ACMG/AMP criteria, while nine were deemed not applicable. The original strength level for the 10 criteria was also adjusted due to current evidence. Use of TP53-specific guidelines and sharing of clinical data among experts and clinical laboratories led to a decrease in variants of uncertain significance from 28% to 12% compared with the original guidelines. The ClinGen TP53 VCEP recommends the use of these TP53-specific ACMG/AMP guidelines as the standard strategy for TP53 germline variant classification.

Blood functional assay for rapid clinical interpretation of germline TP53 variants

BACKGROUND

The interpretation of germline TP53 variants is critical to ensure appropriate medical management of patients with cancer and follow-up of variant carriers. This interpretation remains complex and is becoming a growing challenge considering the exponential increase in TP53 tests. We developed a functional assay directly performed on patients' blood.

METHODS

Peripheral blood mononuclear cells were cultured, activated, exposed to doxorubicin and the p53-mediated transcriptional response was quantified using reverse transcription-multiplex ligation probe amplification and RT-QMPSF assays, including 10 p53 targets selected from transcriptome analysis, and two amplicons to measure p53 mRNA levels. We applied this blood functional assay to 77 patients addressed for TP53 analysis.

RESULTS

In 51 wild-type TP53 individuals, the mean p53 functionality score was 12.7 (range 7.5-22.8). Among eight individuals harbouring likely pathogenic or pathogenic variants, the scores were reduced (mean 4.8, range 3.1-7.1), and p53 mRNA levels were reduced in patients harbouring truncating variants. We tested 14 rare unclassified variants (p.(Pro72His), p.(Gly105Asp), p.(Arg110His), p.(Phe134Leu), p.(Arg158Cys), p.(Pro191Arg), p.(Pro278Arg), p.(Arg283Cys), p.(Leu348Ser), p.(Asp352Tyr), p.(Gly108_Phe109delinsVal), p.(Asn131del), p.(Leu265del), c.-117G>T) and 12 yielded functionally abnormal scores. Remarkably, the assay revealed that the c.*1175A>C polymorphic variant within TP53 poly-adenylation site can impact p53 function with the same magnitude as a null variant, when present on both alleles, and may act as a modifying factor in pathogenic variant carriers.

CONCLUSION

This blood p53 assay should therefore be a useful tool for the rapid clinical classification of germline TP53 variants and detection of non-coding functional variants.

TP53 variants of uncertain significance: increasing challenges in variant interpretation and genetic counseling

Li-Fraumeni syndrome (LFS) and Li-Fraumeni Like (LFL) are autosomal dominant cancer predisposition syndromes caused by pathogenic germline variants in the TP53 gene. Recent studies have shown that the incorporation of next-generation sequencing by using multigene panels in clinical practice has resulted in the frequent identification of variants of uncertain significance (VUS). Given that there is no established medical management for VUS carriers, the identification of these variants may cause confusion and anxiety for both patients and practitioners. Herein, we aimed to verify VUS frequency and review VUS classification and interpretation in 1844 patients submitted for comprehensive germline TP53 testing independent of clinical criteria. Variant characterization was done assessing clinical information whenever available, variant frequency in population databases, pathogenicity predictions using in silico tools and previous functional studies. All variants were classified based on the guidelines proposed by the American College of Medical Genetics and Genomics (2015) and by the Sherloc framework (2017). Of the twelve VUS (0.65%) identified in TP53, two were classified as likely pathogenic and two were classified as likely benign after re-evaluation, potentially resulting in significant management modification for the proband and relatives. This report cases highlights the challenges and impact of TP53 variant interpretation especially when there is no clear LFS/LFL phenotype.

Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort

Purpose

Genetic testing of individuals often results in identification of genomic variants of unknown significance (VUS). Multiple lines of evidence are used to help determine the clinical significance of these variants.

Methods

We analyzed ~138,000 individuals tested by multigene panel testing (MGPT). We used logistic regression to predict carrier status based on personal and family history of cancer. This was applied to 4644 tested individuals carrying 2383 BRCA1/2 variants to calculate likelihood ratios informing pathogenicity for each. Heterogeneity tests were performed for specific classes of variants defined by in silico predictions.

Results

Twenty-two variants labeled as VUS had odds of >10:1 in favor of pathogenicity. The heterogeneity analysis found that among variants in functional domains that were predicted to be benign by in silico tools, a significantly higher proportion of variants were estimated to be pathogenic than previously indicated; that missense variants outside of functional domains should be considered benign; and that variants predicted to create de novo donor sites were also largely benign.

Conclusion

The evidence presented here supports the use of personal and family history from MGPT in the classification of VUS and will be integrated into ongoing efforts to provide large-scale multifactorial classification.

p53 major hotspot variants are associated with poorer prognostic features in hereditary cancer patients

TP53 pathogenic germline variation is associated with the multi-cancer predisposition Li-Fraumeni syndrome (LFS). Next-generation sequencing and multigene panel testing are highlighting variability in the clinical presentation of patients with TP53 positive results. We aimed to investigate if the p53 variants considered as major hotspots at both germline and somatic levels (p.Arg175His, p.Gly245Asp, p.Gly245Ser, p.Arg248Gln, p.Arg248Trp, p.Arg273Cys, p.Arg273His, and p.Arg282Trp) were associated with poorer prognostic features compared to other pathogenic missense variants in the DNA-binding domain. To do so, we assessed clinical features from 1025 carriers of germline TP53 pathogenic variants (749 probands and 276 relatives) from three independent datasets (IARC TP53 Database, Ambry Single Gene Testing, and Ambry Multigene Panel Testing). We observed that, compared to carriers of non-hotspot germline variants, individuals that carried a hotspot germline variant were more likely to present with a Classic LFS phenotype, earlier age of first breast cancer onset, and shorter time to diagnosis to any cancer. Further studies with larger datasets addressing differences in cancer phenotypes by genotype are thus needed to replicate our findings and consider variant effect and position, towards future personalized clinical management of pathogenic variant carriers.

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.

A quantitative model to predict pathogenicity of missense variants in the TP53 gene

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.

Distinct mutation spectrum, clinical outcome and therapeutic responses of typical complex/monosomy karyotype acute myeloid leukemia carrying TP53 mutations

The present study aimed to define a subtype of complex/monosomal karyotype (CK/MK) acute myeloid leukemia (AML) by its distinct clinical features, p53 signaling and responses to p53 targeting agents. Ninety-eight young adults (range: 21-60 years; median: 49 years) with CK/MK AML were studied. They received standard induction, consolidation and allogeneic hematopoietic stem cell transplantation from siblings or matched unrelated donors if available. Chromosomal abnormalities most commonly affected chromosome 5 (30%), 7 (22%) and 17 (21%). Next generation sequencing of a 54-myeloid gene panel were available in 76 patients. Tumor protein 53 (TP53) mutations were most common (49%) and associated with the presence of -5/5q- (P < .001) and -17/17p- (P < .001), but not -7/7q- (P = .370). This "typical" CK/MK AML subtype was associated with significantly lower presenting white cell counts, higher number of karyotypic abnormalities, and inferior leukemia-free and overall survivals, compared with CK/MK AML without the typical features. Blood or bone marrow samples from typical CK/MK AML patients showed defective p53 signaling upon induction by etoposide. In vitro drug sensitivity analysis showed that they were sensitive to APR-246 that targeted mutant p53, but resistant to MDM2 antagonist MI-77301. Novel therapeutic strategies targeting TP53 mutations in CK/MK AML should be developed and tested in clinical trials.

Current review of TP53 pathogenic germline variants in breast cancer patients outside Li-Fraumeni syndrome

Pathogenic germline variants in TP53 predispose carriers to the multi-cancer Li-Fraumeni syndrome (LFS). Widespread multigene panel testing is identifying TP53 pathogenic variants in breast cancer patients outside the strict clinical criteria recommended for LFS testing. We aimed to assess frequency and clinical implications of TP53 pathogenic variants in breast cancer cohorts ascertained outside LFS. Classification of TP53 germline variants reported in 59 breast cancer studies, and publicly available population control sets was reviewed and identified evidence for misclassification of variants. TP53 pathogenic variant frequency was determined for: breast cancer studies grouped by ascertainment characteristics; breast cancer cohorts undergoing panel testing; and population controls. Early age of breast cancer onset, regardless of family history or BRCA1/BRCA2 previous testing, had the highest pick-up rate for TP53 carriers. Patients at risk of hereditary breast cancer unselected for features of LFS carried TP53 pathogenic variants at a frequency comparable to that of other non-BRCA1/2 breast cancer predisposing genes, and ∼threefold more than reported in population controls. These results have implications for the implementation of TP53 testing in broader clinical settings, and suggest urgent need to investigate cancer risks associated with TP53 pathogenic variants in individuals outside the LFS spectrum.