A Systematic p53 Mutation Library Links Differential Functional Impact to Cancer Mutation Pattern and Evolutionary Conservation

The Diverse Functions of Mutant 53, Its Family Members and Isoforms in Cancer

The p53 family of proteins has grown substantially over the last 40 years. It started with p53, then p63, p73, isoforms and mutants of these proteins. The function of p53 as a tumour suppressor has been thoroughly investigated, but the functions of all isoforms and mutants and the interplay between them are still poorly understood. Mutant p53 proteins lose p53 function, display dominant-negative (DN) activity and display gain-of-function (GOF) to varying degrees. GOF was originally attributed to mutant p53′s inhibitory function over the p53 family members p63 and p73. It has become apparent that this is not the only way in which mutant p53 operates as a large number of transcription factors that are not related to p53 are activated on mutant p53 binding. This raises the question to what extent mutant p53 binding to p63 and p73 plays a role in mutant p53 GOF. In this review, we discuss the literature around the interaction between mutant p53 and family members, including other binding partners, the functional consequences and potential therapeutics.

Statin therapy: does sex matter?

OBJECTIVE

Statins are a class of drugs that competitively bind to the active site of HMG-CoA reductase enzyme, thereby inhibiting the initial steps in cholesterol synthesis. Originally approved for use in lowering serum cholesterol, a risk factor for developing atherosclerosis and coronary heart disease, statins have subsequently been noted to have myriad extrahepatic effects, including potential effects on cognition, diabetes, breast cancer, bone, and muscle. This narrative review assesses the current state of the science regarding the risks and benefits of statin therapy in women to identify areas where additional research is needed.

METHODS

Basic and clinical studies were identified by searching PubMed with particular attention to inclusion of female animals, women, randomized controlled trials, and sex-specific analyses.

RESULTS

Statin therapy is generally recommended to reduce the risk of cardiovascular disease. None of the current clinical guidelines, however, offer sex-specific recommendations for women due to lack of understanding of sex differences and underlying mechanisms of disease processes. In addition, conclusions regarding efficacy of treatments do not consider lipid solubility for the drug, dosing, duration of treatment, interactions with estrogen, or comorbidities. Pleiotropic effects of statins are often derived from secondary analysis of studies with cardiovascular events as primary outcomes.

CONCLUSIONS

Many of the trials that have established the efficacy and safety of statins were conducted predominantly or entirely in men, with results extrapolated to women. Additional research is needed to guide clinical recommendations specific to women. : Video Summary:http://links.lww.com/MENO/A462.

Inactivation of Mdm2 restores apoptosis proficiency of cooperativity mutant p53 in vivo

TP53 mutations are found in 50% of all cancers and mutated TP53 status is considered poor for treatment. However, some TP53 mutations exhibit only partial loss-of-function (LOF), meaning they retain residual transcriptional and non-transcriptional activities that are potentially beneficial for therapy. Earlier we have characterized a knock-in mouse model for the partial LOF mutant Trp53^E177R (p53RR). Reduced DNA binding cooperativity of this mutant led to the loss of p53-dependent apoptosis, while p53 functions in cell cycle control, senescence, metabolism, and antioxidant defense remained intact. Concomitantly, tumor suppression was evident but strongly compromised compared to wild-type mice. Here we used the Trp53^E177R mouse as a model to investigate whether residual functions of mutant p53 can be engaged to induce cell death, which is considered the most desirable outcome of tumor therapy. We made use of Mdm2 knock-out in developing embryos as a sensitive tool for detecting remaining p53 activities. Genetic ablation of Mdm2 led to embryonic lethality in Trp53^E177R/E177R homozygotes at days 9.5-11.5. This effect was not rescued by concomitant p21-knockout, indicating its independence of p21-mediated cell cycle arrest. Instead, immunohistochemical analysis showed widespread apoptosis in tissues of defective embryos accompanied by persistent accumulation of p53RR protein. This led to partial restoration of the mutant's proficiency in transcriptional induction of the pro-apoptotic genes Bbc3 (Puma) and Bax. These data indicate that increased quantity can compensate for qualitative defects of p53 mutants and suggest that Mdm2-targeting (potentially in combination with other drugs) might be effective against cells bearing p53 partial LOF mutants.

MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect

Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB ( https://www.mavedb.org ), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

Loss of p53 function at late stages of tumorigenesis confers ARF-dependent vulnerability to p53 reactivation therapy

Mouse studies demonstrating regression of p53-null tumors following reinstatement of functional p53 have fueled the development of p53 reactivating drugs. However, successful p53 reactivation responses have only been formally demonstrated in tumor models where p53 inactivation served as the initiating event. Our study provides the first proof-of-principle evidence that p53 inactivation at late stages of tumorigenesis can also generate a vulnerability to p53 reactivation. However, this is dependent on intact ARF function highlighting ARF as a potential biomarker for p53 reactivation responses in tumors with late-stage p53 inactivation. It furthermore suggests the use of Mdm2 inhibitors as ARF mimetics for sensitizing ARF-deficient tumors to p53-reactivating drugs.

Cancer development is driven by activated oncogenes and loss of tumor suppressors. While oncogene inhibitors have entered routine clinical practice, tumor suppressor reactivation therapy remains to be established. For the most frequently inactivated tumor suppressor p53, genetic mouse models have demonstrated regression of p53-null tumors upon p53 reactivation. While this was shown in tumor models driven by p53 loss as the initiating lesion, many human tumors initially develop in the presence of wild-type p53, acquire aberrations in the p53 pathway to bypass p53-mediated tumor suppression, and inactivate p53 itself only at later stages during metastatic progression or therapy. To explore the efficacy of p53 reactivation in this scenario, we used a reversibly switchable p53 (p53ER^TAM) mouse allele to generate Eµ-Myc–driven lymphomas in the presence of active p53 and, after full lymphoma establishment, switched off p53 to model late-stage p53 inactivation. Although these lymphomas had evolved in the presence of active p53, later loss and subsequent p53 reactivation surprisingly activated p53 target genes triggering massive apoptosis, tumor regression, and long-term cure of the majority of animals. Mechanistically, the reactivation response was dependent on Cdkn2a/p19Arf, which is commonly silenced in p53 wild-type lymphomas, but became reexpressed upon late-stage p53 inactivation. Likewise, human p53 wild-type tumor cells with CRISPR-engineered switchable p53ER^TAM alleles responded to p53 reactivation when CDKN2A/p14ARF function was restored or mimicked with Mdm2 inhibitors. Together, these experiments provide genetic proof of concept that tumors can respond, in an ARF-dependent manner, to p53 reactivation even if p53 inactivation has occurred late during tumor evolution.

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): a cloud-based platform for curating and classifying germline variants

Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

Relating evolutionary selection and mutant clonal dynamics in normal epithelia

Cancer develops from mutated cells in normal tissues. Whether somatic mutations alter normal cell dynamics is key to understanding cancer risk and guiding interventions to reduce it. An analysis of the first incomplete moment of size distributions of clones carrying cancer-associated mutations in normal human eyelid skin gives a good fit with neutral drift, arguing mutations do not affect cell fate. However, this suggestion conflicts with genetic evidence in the same dataset that argues for strong positive selection of a subset of mutations. This implies cells carrying these mutations have a competitive advantage over normal cells, leading to large clonal expansions within the tissue. In the normal epithelium, clone growth is constrained by the limited size of the proliferating compartment and competition with surrounding cells. We show that if these factors are taken into account, the first incomplete moment of the clone size distribution is unable to exclude non-neutral behaviour. Furthermore, experimental factors can make a non-neutral clone size distribution appear neutral. We validate these principles with a new experimental dataset showing that when experiments are appropriately designed, the first incomplete moment can be a useful indicator of non-neutral competition. Finally, we discuss the complex relationship between mutant clone sizes and genetic selection.

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.

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.

A Gain-of-Function p53-Mutant Oncogene Promotes Cell Fate Plasticity and Myeloid Leukemia through the Pluripotency Factor FOXH1

Mutations in the TP53 tumor suppressor gene are common in many cancer types, including the acute myeloid leukemia (AML) subtype known as complex karyotype AML (CK-AML). Here, we identify a gain-of-function (GOF) Trp53 mutation that accelerates CK-AML initiation beyond p53 loss and, surprisingly, is required for disease maintenance. The Trp53^R172H mutation (TP53^R175H in humans) exhibits a neomorphic function by promoting aberrant self-renewal in leukemic cells, a phenotype that is present in hematopoietic stem and progenitor cells (HSPC) even prior to their transformation. We identify FOXH1 as a critical mediator of mutant p53 function that binds to and regulates stem cell-associated genes and transcriptional programs. Our results identify a context where mutant p53 acts as a bona fide oncogene that contributes to the pathogenesis of CK-AML and suggests a common biological theme for TP53 GOF in cancer. SIGNIFICANCE: Our study demonstrates how a GOF p53 mutant can hijack an embryonic transcription factor to promote aberrant self-renewal. In this context, mutant Trp53 functions as an oncogene to both initiate and sustain myeloid leukemia and suggests a potential convergent activity of mutant Trp53 across cancer types.This article is highlighted in the In This Issue feature, p. 813.

Mutation Hotspots in the β-Catenin Gene: Lessons from the Human Cancer Genome Databases

Mutations in the β-catenin gene (CTNNB1) have been implicated in the pathogenesis of some cancers. The recent development of cancer genome databases has facilitated comprehensive and focused analyses on the mutation status of cancer-related genes. We have used these databases to analyze the CTNNB1 mutations assembled from different tumor types. High incidences of CTNNB1 mutations were detected in endometrial, liver, and colorectal cancers. This finding agrees with the oncogenic role of aberrantly activated β-catenin in epithelial cells. Elevated frequencies of missense mutations were found in the exon 3 of CTNNB1, which is responsible for encoding the regulatory amino acids at the N-terminal region of the protein. In the case of metastatic colorectal cancers, inframe deletions were revealed in the region spanning exon 3. Thus, exon 3 of CTNNB1 can be considered to be a mutation hotspot in these cancers. Since the N-terminal region of the β-catenin protein forms a flexible structure, many questions arise regarding the structural and functional impacts of hotspot mutations. Clinical identification of hotspot mutations could provide the mechanistic basis for an oncogenic role of mutant β-catenin proteins in cancer cells. Furthermore, a systematic understanding of tumor-driving hotspot mutations could open new avenues for precision oncology.

Functional characterization of the p53 "mutome"

Phenotypic characterization of mutations in the tumor protein p53 (TP53) gene has so far focused on a handful of relatively frequent "hotspot" mutations, accounting for only ~ 30% of cases. We expanded the scope and quantitatively measured the impact of thousands of distinct TP53 mutations in vitro and in vivo, providing insights into the connections between structure, function, evolutionary conservation and clinical impact.

Multiplexed assays of variant effects contribute to a growing genotype-phenotype atlas

Given the constantly improving cost and speed of genome sequencing, it is reasonable to expect that personal genomes will soon be known for many millions of humans. This stands in stark contrast with our limited ability to interpret the sequence variants which we find. Although it is, perhaps, easiest to interpret variants in coding regions, knowledge of functional impact is unknown for the vast majority of missense variants. While many computational approaches can predict the impact of coding variants, they are given a little weight in the current guidelines for interpreting clinical variants. Laboratory assays produce comparatively more trustworthy results, but until recently did not scale to the space of all possible mutations. The development of deep mutational scanning and other multiplexed assays of variant effect has now brought feasibility of this endeavour within view. Here, we review progress in this field over the last decade, break down the different approaches into their components, and compare methodological differences.