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

A probabilistic graphical model for estimating selection coefficients of nonsynonymous variants from human population sequence data

Accurately predicting the effect of missense variants is important in discovering disease risk genes and clinical genetic diagnostics. Commonly used computational methods predict pathogenicity, which does not capture the quantitative impact on fitness in humans. We develop a method, MisFit, to estimate missense fitness effect using a graphical model. MisFit jointly models the effect at a molecular level ( d ) and a population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . We train it by maximizing probability of observed allele counts in 236,017 individuals of European ancestry. We show that s is informative in predicting allele frequency across ancestries and consistent with the fraction of de novo mutations in sites under strong selection. Further, s outperforms previous methods in prioritizing de novo missense variants in individuals with neurodevelopmental disorders. In conclusion, MisFit accurately predicts s and yields new insights from genomic data.

Structural biology in variant interpretation: Perspectives and practices from two studies

Structural biology offers a powerful lens through which to assess genetic variants by providing insights into their impact on clinically relevant protein structure and function. Due to the availability of new, user-friendly, web-based tools, structural analyses by wider audiences have become more mainstream. These new tools, including AlphaMissense and AlphaFold, have recently been in the limelight due to their initial success and projected future promise; however, the intricacies and limitations of using these tools still need to be disseminated to the more general audience that is likely to use them in variant analysis. Here, we expound on frameworks applying structural biology to variant interpretation by examining two accompanying articles. To this end, we explore the nuances of choosing the correct protein model, compare and contrast various structural approaches, and highlight both the advantages and limitations of employing structural biology in variant interpretation. Using two articles published in this issue of The American Journal of Human Genetics as a baseline, we focus on case studies in TP53 and BRCA1 to illuminate gene-specific differences in the applications of structural information, which illustrate the complexities inherent in this field. Additionally, we discuss the implications of recent advancements, such as AlphaFold, and provide practical guidance for researchers navigating variant interpretation using structural biology.

Oncogenic and teratogenic effects of Trp53Y217C, an inflammation-prone mouse model of the human hotspot mutant TP53Y220C

Missense 'hotspot' mutations localized in six p53 codons account for 20% of TP53 mutations in human cancers. Hotspot p53 mutants have lost the tumor suppressive functions of the wildtype protein, but whether and how they may gain additional functions promoting tumorigenesis remain controversial. Here, we generated Trp53Y217C, a mouse model of the human hotspot mutant TP53Y220C. DNA damage responses were lost in Trp53Y217C/Y217C (Trp53YC/YC) cells, and Trp53YC/YC fibroblasts exhibited increased chromosome instability compared to Trp53-/- cells. Furthermore, Trp53YC/YC male mice died earlier than Trp53-/- males, with more aggressive thymic lymphomas. This correlated with an increased expression of inflammation-related genes in Trp53YC/YC thymic cells compared to Trp53-/- cells. Surprisingly, we recovered only one Trp53YC/YC female for 22 Trp53YC/YC males at weaning, a skewed distribution explained by a high frequency of Trp53YC/YC female embryos with exencephaly and the death of most Trp53YC/YC female neonates. Strikingly, however, when we treated pregnant females with the anti-inflammatory drug supformin (LCC-12), we observed a fivefold increase in the proportion of viable Trp53YC/YC weaned females in their progeny. Together, these data suggest that the p53Y217C mutation not only abrogates wildtype p53 functions but also promotes inflammation, with oncogenic effects in males and teratogenic effects in females.

A probabilistic graphical model for estimating selection coefficient of nonsynonymous variants from human population sequence data

Accurately predicting the effect of missense variants is important in discovering disease risk genes and clinical genetic diagnostics. Commonly used computational methods predict pathogenicity, which does not capture the quantitative impact on fitness in humans. We developed a method, MisFit, to estimate missense fitness effect using a graphical model. MisFit jointly models the effect at a molecular level (𝑑) and a population level (selection coefficient, 𝑠), assuming that in the same gene, missense variants with similar 𝑑 have similar 𝑠. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that 𝑠 is informative in predicting allele frequency across ancestries and consistent with the fraction of de novo mutations in sites under strong selection. Further, 𝑠 outperforms previous methods in prioritizing de novo missense variants in individuals with neurodevelopmental disorders. In conclusion, MisFit accurately predicts 𝑠 and yields new insights from genomic data.

Establishment and characterization of novel patient-derived esophageal tumoroids with long-term cultivability

Esophageal cancer is an aggressive and fatal disease classified into two distinct histologic types: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). To develop novel therapeutic strategies, it is important to establish preclinical models of esophageal carcinoma. In this study, we successfully established three types of human esophageal cancer organoids (tumoroids) from surgical specimens for long-term culture. Two of the tumoroids were derived from ESCC and one from EAC, which arose from Barrett's esophagus. Whole-exome sequencing revealed that the tumoroids inherited genetic mutations from the parental tumors and patient-derived tumor xenografts closely mimicked the pathology of the original esophageal cancers. In addition to whole-exome analysis, copy number and immunohistochemical analyses demonstrated HER2 expression and amplification as well as HER3 expression and mutation in esophageal tumoroids derived from adenocarcinoma in Barrett's esophagus. HER2-targeting antibody-drug conjugates (ADCs), trastuzumab deruxtecan (T-DXd), and patritumab deruxtecan (P-DXd) effectively suppressed the viability of the tumoroids. Therefore, the establishment of esophageal tumoroids with long-term cultivability makes it possible to obtain reproducible basic data, including drug sensitivity studies, which are important for the development of personalized therapies and treatment strategies.

Mis-splicing drives loss of function of p53E224D point mutation

BACKGROUND

The tumor suppressor p53 (Trp53), also known as p53, is the most commonly mutated gene in cancer. Canonical p53 DNA damage response pathways are well characterized and classically thought to underlie the tumor suppressive effect of p53. Challenging this dogma, mouse models have revealed that p53-driven apoptosis and cell cycle arrest are dispensable for tumor suppression. Here, we investigated the inverse context of a p53 mutation predicted to drive the expression of canonical targets but is detected in human cancer.

METHODS

We established a novel mouse model with a single base pair mutation (GAG>GAT, p53E221D) in the DNA-Binding domain that has wild-type function in screening assays, but is paradoxically found in human cancer in Li-Fraumeni syndrome. Using mouse p53E221D and the analogous human p53E224D mutants, we evaluated expression, transcriptional activation, and tumor suppression in vitro and in vivo.

RESULTS

Expression of human p53E224D from cDNA translated to a fully functional p53 protein. However, p53E221D/E221D RNA transcribed from the endogenous locus is mis-spliced resulting in nonsense-mediated decay. Moreover, fibroblasts derived from p53E221D/E221D mice do not express a detectable protein product. Mice homozygous for p53E221D exhibited increased tumor penetrance and decreased life expectancy compared to p53WT/WT animals.

CONCLUSIONS

Mouse p53E221D and human p53E224D mutations lead to splice variation and a biologically relevant p53 loss of function in vitro and in vivo.

Clinicopathologic Features of Breast Tumors in Germline TP53 Variant-Associated Li-Fraumeni Syndrome

We present one of the largest cohorts of TP53 -pathogenic germline variants (PGVs) associated with patients with Li-Fraumeni syndrome (n = 82) with breast tumors (19 to 76 y; median age: 35). Most had missense variants (77%), followed by large gene rearrangements (LGRs; 12%), truncating (6%), and splice-site (5%) variants. Twenty-one unique germline missense variants were found, with hotspots at codons 175, 181, 245, 248, 273, 334, and 337. Of 100 total breast tumors, 63% were invasive (mostly ductal), 30% pure ductal carcinoma in situ, 4% fibroepithelial lesions, and 3% with unknown histology. Unlike BRCA -associated tumors, approximately half of the breast cancers exhibited HER2 -positivity, of which ~50% showed estrogen receptor coexpression. Pathology slides were available for review for 61 tumors (44 patients), and no significant correlation between the type of TP53 PGVs and histologic features was noted. High p53 immunohistochemistry expression (>50%) was seen in 67% of tumors tested (mostly missense variant). Null pattern (<1% cells) was seen in 2 (LGR and splicing variants carriers). Surprisingly, 2 tumors from patients with an LGR and 1 tumor from a patient with a truncating variant showed p53 overexpression (>50%). The subset of patients with the Brazilian p.R337H variant presented at a higher age than those with non-p.R337H variant (46 vs 35 y) though statistically insignificant ( P = 0.071) due to an imbalance in the sample size, and were uniquely negative for HER2 -overexpressing tumors. To conclude, breast cancer in carriers of TP53 PGVs has some unique clinicopathological features that suggest differential mechanisms of tumor formation. p53 immunohistochemistry cannot be used as a surrogate marker to identify germline TP53 -mutated breast cancers.

Deciphering the significance of p53 mutant proteins

Mutations in the p53 gene compromise its role as guardian of genomic integrity, yielding predominantly missense p53 mutant proteins. The gain-of-function hypothesis has long suggested that these mutant proteins acquire new oncogenic properties; however, recent studies challenge this notion, indicating that targeting these mutants may not impact the fitness of cancer cells. Mounting evidence indicates that tumorigenesis involves a cooperative interplay between driver mutations and cellular state, influenced by developmental stage, external insults, and tissue damage. Consistently, the behavior and properties of p53 mutants are altered by the context. This article aims to provide a balanced summary of the evolving evidence regarding the contribution of p53 mutants in the biology of cancer while contemplating alternative frameworks to decipher the complexity of p53 mutants within their physiological contexts.

Unveiling the prognostic value of ARID3A in breast cancer through bioinformatic analysis

Objective

Identifying reliable prognostic markers for breast cancer is crucial for improving survival rates and reducing mortality. Recent studies highlight the AT-rich interactive domain-containing protein (ARID) family, particularly ARID3A, as influential in cancer progression, though its specific role in breast cancer remains unclear. This study investigates ARID3A's expression, prognostic relevance, clinicopathological correlations, co-expression profiles, and protein-protein interactions in breast cancer.

Methods

ARID3A mRNA and protein expression levels were analyzed using UALCAN, GEPIA databases, and immunohistochemistry from our hospital samples. Clinical prognostic parameters and survival data were examined through bioinformatics tools, including GEPIA, Bc-GenExMiner, and BEST. Subtype-specific expression and co-expression, particularly with REXO1, were evaluated using LinkedOmics, TIMER, and bc-GenExMiner. Functional enrichment analysis was conducted via LinkedOmics. Protein-protein interactions (PPI) were established using GeneMANIA and STRING, with validation through molecular docking using Cluspro.

Results

Elevated ARID3A expression was associated with poor prognosis in breast cancer, particularly in Luminal and HER2-positive subtypes. A positive correlation with REXO1 was identified, and enrichment analysis emphasized ARID3A's involvement in immune-related pathways, such as "interferon gamma production" and "primary immunodeficiency." PPI network and docking studies identified TP53 as a potential binding partner, suggesting a novel interaction influencing tumor progression.

Conclusion

These findings indicate that ARID3A may serve as a prognostic biomarker and therapeutic target in breast cancer, providing insights into its involvement in oncogenic pathways and interactions, particularly with TP53, that may drive cancer development and progression.

Epithelial competition determines gene therapy potential to suppress Fanconi Anemia oral cancer risk

Fanconi Anemia (FA) is a heritable syndrome characterized by DNA damage repair deficits, frequent malformations and a significantly elevated risk of bone marrow failure, leukemia, and mucosal head and neck squamous cell carcinomas (HNSCC). Hematopoietic stem cell gene therapy can prevent marrow failure and lower leukemia risk, but mucosal gene therapy to lower HNSCC risk remains untested. Major knowledge gaps include an incomplete understanding of how rapidly gene-corrected cellular lineages could spread through the oral epithelium, and which delivery parameters are critical for ensuring efficient gene correction. To answer these questions, we extended an agent-based model of the oral epithelium to include the delivery of gene correction in situ to FA cells and the competitive dynamics between cellular lineages with and without gene correction. We found that only gene-corrected lineages with substantial proliferative advantages (probability of resisting displacement out of the basal layer ≥ 0.1) could spread on clinically relevant timelines, and that these lineages were initially at high risk of loss in the generations following correction. Delivering gene correction to many cells minimizes the risk of loss, while delivery to many distinct locations within a tissue maximizes the rate of spread. To determine the impact of mucosal gene therapy in preventing the clonal expansion of pre-cancerous mutations, we compared the expected burden of T P 53 mutations in simulated tissue sections with and without gene correction. We found that when FA cells have elevated genome instability or a T P 53 -dependent proliferative advantage, gene correction can substantially reduce the accumulation of pro-tumorigenic mutations. This model illustrates the power of computational frameworks to identify critical determinants of therapeutic success to enable experimental optimization and support novel and effective gene therapy applications.

TP53: the unluckiest of genes?

The transcription factor p53 plays a key role in the cellular defense against cancer development. It is inactivated in virtually every tumor, and in every second tumor this inactivation is due to a mutation in the TP53 gene. In this perspective, we show that this diverse mutational spectrum is unique among all other cancer-associated proteins and discuss what drives the selection of TP53 mutations in cancer. We highlight that several factors conspire to make the p53 protein particularly vulnerable to inactivation by the mutations that constantly plague our genome. It appears that the TP53 gene has emerged as a victim of its own evolutionary past that shaped its structure and function towards a pluripotent tumor suppressor, but came with an increased structural fragility of its DNA-binding domain. TP53 loss of function - with associated dominant-negative effects - is the main mechanism that will impair TP53 tumor suppressive function, regardless of whether a neomorphic phenotype is associated with some of these variants.

Exploring the role of splicing in TP53 variant pathogenicity through predictions and minigene assays

BACKGROUND

TP53 variant classification benefits from the availability of large-scale functional data for missense variants generated using cDNA-based assays. However, absence of comprehensive splicing assay data for TP53 confounds the classification of the subset of predicted missense and synonymous variants that are also predicted to alter splicing. Our study aimed to generate and apply splicing assay data for a prioritised group of 59 TP53 predicted missense or synonymous variants that are also predicted to affect splicing by either SpliceAI or MaxEntScan.

METHODS

We conducted splicing analyses using a minigene construct containing TP53 exons 2 to 9 transfected into human breast cancer SKBR3 cells, and compared results against different splice prediction methods, including correlation with the SpliceAI-10k calculator. We additionally applied the splicing results for TP53 variant classification using an approach consistent with the ClinGen Sequence Variant Interpretation Splicing Subgroup recommendations.

RESULTS

Aberrant transcript profile consistent with loss of function, and for which a PVS1 (RNA) code would be assigned, was observed for 42 (71%) of prioritised variants, of which aberrant transcript expression was over 50% for 26 variants, and over 80% for 15 variants. Data supported the use of SpliceAI ≥ 0.2 cutoff for predicted splicing impact of TP53 variants. Prediction of aberration types using SpliceAI-10k calculator generally aligned with the corresponding assay results, though maximum SpliceAI score did not accurately predict level of aberrant expression. Application of the observed splicing results was used to reclassify 27/59 (46%) test variants as (likely) pathogenic or (likely) benign.

CONCLUSIONS

In conclusion, this study enhances the integration of splicing predictions and provides splicing assay data for exonic variants to support TP53 germline classification.

Mutation impact on mRNA versus protein expression across human cancers

BACKGROUND

Cancer mutations are often assumed to alter proteins, thus promoting tumorigenesis. However, how mutations affect protein expression-in addition to gene expression-has rarely been systematically investigated. This is significant as mRNA and protein levels frequently show only moderate correlation, driven by factors such as translation efficiency and protein degradation. Proteogenomic datasets from large tumor cohorts provide an opportunity to systematically analyze the effects of somatic mutations on mRNA and protein abundance and identify mutations with distinct impacts on these molecular levels.

RESULTS

We conduct a comprehensive analysis of mutation impacts on mRNA- and protein-level expressions of 953 cancer cases with paired genomics and global proteomic profiling across 6 cancer types. Protein-level impacts are validated for 47.2% of the somatic expression quantitative trait loci (seQTLs), including CDH1 and MSH3 truncations, as well as other mutations from likely "long-tail" driver genes. Devising a statistical pipeline for identifying somatic protein-specific QTLs (spsQTLs), we reveal several gene mutations, including NF1 and MAP2K4 truncations and TP53 missenses showing disproportional influence on protein abundance not readily explained by transcriptomics. Cross-validating with data from massively parallel assays of variant effects (MAVE), TP53 missenses associated with high tumor TP53 proteins are more likely to be experimentally confirmed as functional.

CONCLUSION

This study reveals that somatic mutations can exhibit distinct impacts on mRNA and protein levels, underscoring the necessity of integrating proteogenomic data to comprehensively identify functionally significant cancer mutations. These insights provide a framework for prioritizing mutations for further functional validation and therapeutic targeting.

Cancer risk in carriers of TP53 germline variants grouped into different functional categories

Li-Fraumeni syndrome is a cancer predisposition syndrome caused by pathogenic TP53 germline variants; it is associated with a high lifelong cancer risk. We analyzed the German Li-Fraumeni syndrome registry, which contains data on 304 individuals. Cancer phenotypes were correlated with variants grouped according to their ability to transactivate target genes in a yeast assay using a traditional (nonfunctional, partially functional) and a novel (clusters A, B, and C) classification of variants into different groups. Partially functional and cluster B or C variants were enriched in patients who did not meet clinical testing criteria. Time to first malignancy was longer in carriers of partially functional variants (hazard ratio = 0.38, 95% CI = 0.22 to 0.66). Variants grouped within cluster B (hazard ratio = 0.45, 95% CI = 0.28 to 0.71) or C (hazard ratio = 0.34, 95% CI = 0.19 to 0.62) were associated with later cancer onset than NULL variants. These findings can be used to risk-stratify patients and inform care.

Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations

The mutational landscape of TP53, a tumor suppressor mutated in about half of all cancers, includes over 2,000 known missense mutations. To fully leverage TP53 mutation status for personalized medicine, a thorough understanding of the functional diversity of these mutations is essential. We conducted a deep mutational scan using saturation genome editing with CRISPR-mediated homology-directed repair to engineer 9,225 TP53 variants in cancer cells. This high-resolution approach, covering 94.5% of all cancer-associated TP53 missense mutations, precisely mapped the impact of individual mutations on tumor cell fitness, surpassing previous deep mutational scan studies in distinguishing benign from pathogenic variants. Our results revealed even subtle loss-of-function phenotypes and identified promising mutants for pharmacological reactivation. Moreover, we uncovered the roles of splicing alterations and nonsense-mediated messenger RNA decay in mutation-driven TP53 dysfunction. These findings underscore the power of saturation genome editing in advancing clinical TP53 variant interpretation for genetic counseling and personalized cancer therapy.

A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening

Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable editing efficiencies have complicated application of the approach to high-throughput functional genomics. Here we assembled a prime editing platform capable of high-efficiency substitution editing suitable for functional interrogation of small genetic variants. We benchmarked this platform for pooled, loss-of-function screening using a library of ~240,000 engineered prime editing guide RNAs (epegRNAs) targeting ~17,000 codons with 1-3 bp substitutions. Comparing the abundance of these epegRNAs across screen samples identified negative selection phenotypes for 7,996 nonsense mutations targeted to 1,149 essential genes and for synonymous mutations that disrupted splice site motifs at 3' exon boundaries. Rigorous evaluation of codon-matched controls demonstrated that these phenotypes were highly specific to the intended edit. Altogether, we established a prime editing approach for multiplexed, functional characterization of genetic variants with simple readouts.

Detection of clinically relevant variants in the TP53 gene below 10% allelic frequency: A multicenter study by ERIC, the European Research Initiative on CLL

In chronic lymphocytic leukemia, the reliability of next-generation sequencing (NGS) to detect TP53 variants ≤10% allelic frequency (low-VAF) is debated. We tested the ability to detect 23 such variants in 41 different laboratories using their NGS method of choice. The sensitivity was 85.6%, 94.5%, and 94.8% at 1%, 2%, and 3% VAF cut-off, respectively. While only one false positive (FP) result was reported at >2% VAF, it was more challenging to distinguish true variants <2% VAF from background noise (37 FPs reported by 9 laboratories). The impact of low-VAF variants on time-to-second-treatment (TTST) and overall survival (OS) was investigated in a series of 1092 patients. Among patients not treated with targeted agents, patients with low-VAF TP53 variants had shorter TTST and OS versus wt-TP53 patients, and the relative risk of second-line treatment or death increased continuously with increasing VAF. Targeted therapy in ≥2 line diminished the difference in OS between patients with low-VAF TP53 variants and wt-TP53 patients, while patients with high-VAF TP53 variants had inferior OS compared to wild type-TP53 cases. Altogether, NGS-based approaches are technically capable of detecting low-VAF variants. No strict threshold can be suggested from a technical standpoint, laboratories reporting TP53 mutations should participate in a standardized validation set-up. Finally, whereas low-VAF variants affected outcomes in patients receiving chemoimmunotherapy, their impact on those treated with novel therapies remains undetermined. Our results pave the way for the harmonized and accurate TP53 assessment, which is indispensable for elucidating the role of TP53 mutations in targeted treatment.

Clustering of TP53 variants into functional classes correlates with cancer risk and identifies different phenotypes of Li-Fraumeni syndrome

Li-Fraumeni syndrome (LFS) is a heterogeneous predisposition to an individually variable spectrum of cancers caused by pathogenic TP53 germline variants. We used a clustering method to assign TP53 missense variants to classes based on their functional activities in experimental assays assessing biological p53 functions. Correlations with LFS phenotypes were analyzed using the public germline TP53 mutation database and validated in three LFS clinical cohorts. Class A carriers recapitulated all phenotypic traits of fully penetrant LFS, whereas class B carriers showed a slightly less penetrant form dominated by specific cancers, consistent with the notion that these classes identify variants with distinct functional properties. Class C displayed a lower lifetime cancer risk associated with attenuated LFS features, consistent with the notion that these variants have hypomorphic features. Class D carriers showed low lifetime cancer risks inconsistent with LFS definitions. This classification of TP53 variants provides insights into structural/functional features causing pathogenicity.

Role of artificial intelligence in cancer detection using protein p53: A Review

Normal cell development and prevention of tumor formation rely on the tumor-suppressor protein p53. This crucial protein is produced from the Tp53 gene, which encodes the p53 protein. The p53 protein plays a vital role in regulating cell growth, DNA repair, and apoptosis (programmed cell death), thereby maintaining the integrity of the genome and preventing the formation of tumors. Since p53 was discovered 43 years ago, many researchers have clarified its functions in the development of tumors. With the support of the protein p53 and targeted artificial intelligence modeling, it will be possible to detect cancer and tumor activity at an early stage. This will open up new research opportunities. In this review article, a comprehensive analysis was conducted on different machine learning techniques utilized in conjunction with the protein p53 to predict and speculate cancer. The study examined the types of data incorporated and evaluated the performance of these techniques. The aim was to provide a thorough understanding of the effectiveness of machine learning in predicting and speculating cancer using the protein p53.

Clinical Relevance of TP53 Mutation and Its Characteristics in Breast Cancer with Long-Term Follow-Up Date

BACKGROUND

The TP53 mutation is one of the most frequently identified mutations in human cancers and is typically associated with a poor prognosis. However, there are conflicting findings regarding its impact. We aimed to clarify the clinical relevance of TP53 mutations across all breast cancer subtypes and treatments utilizing long-term follow-up data.

METHODS

We retrospectively identified the data of breast cancer patients who underwent TP53 mutation testing. Stratified log-rank tests and Cox regression analysis were performed to compare oncologic outcomes based on TP53 mutation status and the characteristics of these mutations, including types and locations. Mutations in exons 5-9 were identified using polymerase chain reaction-denaturing high-performance liquid chromatography (PCR-DHPLC) and direct sequencing.

RESULTS

Between January 2007 and December 2015, 650 breast cancer patients underwent TP53 mutation testing in Gangnam Severance Hospital. The TP53 mutations were identified in 172 patients (26.5%), with 34 (19.8%) exhibiting missense hotspot mutations. Patients with TP53 mutations (TP53-mutated group) had worse prognosis, demonstrated by a 10-year recurrence-free survival (RFS) rate of 83.5% compared to 86.6% in patients without mutations (HR, 1.67; p = 0.026) and a 10-year overall survival (OS) rate of 88.1% versus 91.0% (HR, 3.02; p = 0.003). However, subgroup analyses within the TP53-mutated group did not reveal significant differences in oncologic outcomes based on mutation types and locations.

CONCLUSIONS

Our findings establish that TP53 mutations are linked to poorer oncologic outcomes in breast cancer across all subtypes. Yet, within the TP53-mutated group, the specific characteristics of TP53 mutations do not influence oncologic outcomes.

Sequence modeling and design from molecular to genome scale with Evo

The genome is a sequence that encodes the DNA, RNA, and proteins that orchestrate an organism's function. We present Evo, a long-context genomic foundation model with a frontier architecture trained on millions of prokaryotic and phage genomes, and report scaling laws on DNA to complement observations in language and vision. Evo generalizes across DNA, RNA, and proteins, enabling zero-shot function prediction competitive with domain-specific language models and the generation of functional CRISPR-Cas and transposon systems, representing the first examples of protein-RNA and protein-DNA codesign with a language model. Evo also learns how small mutations affect whole-organism fitness and generates megabase-scale sequences with plausible genomic architecture. These prediction and generation capabilities span molecular to genomic scales of complexity, advancing our understanding and control of biology.

Germline Variant Spectrum in Southern Italian High-Risk Hereditary Breast Cancer Patients: Insights from Multi-Gene Panel Testing

Hereditary breast cancer accounts for 5-10% of all cases, with pathogenic variants in BRCA1/2 and other susceptibility genes playing a crucial role. This study elucidates the prevalence and spectrum of germline variants in 13 cancer predisposition genes among high-risk hereditary breast cancer patients from Southern Italy. We employed next-generation sequencing (NGS) to analyze 254 individuals selected through genetic counseling. Pathogenic or likely pathogenic variants were identified in 13% (34/254) of patients, with 54% of these variants occurring in non-BRCA1/2 genes. Notably, we observed a recurrent BRCA1 c.4964_4982del founder mutation, underscoring the importance of population-specific genetic screening. The spectrum of variants extended beyond BRCA1/2 to include PALB2, ATM, TP53, CHEK2, and RAD51C, highlighting the genetic heterogeneity of breast cancer susceptibility. Variants of uncertain significance were detected in 20% of patients, emphasizing the ongoing challenge of variant interpretation in the era of multi-gene panel testing. These findings not only enhance our understanding of the genetic landscape of breast cancer in Southern Italy but also provide a foundation for developing more targeted, population-specific approaches to genetic testing and counseling, ultimately contributing to the advancement of precision medicine in oncology.

TP53 mutations in myeloid neoplasms: implications for accurate laboratory detection, diagnosis, and treatment

Genetic alterations that affect the function of p53 tumor suppressor have been extensively investigated in myeloid neoplasms, revealing their significant impact on disease progression, treatment response, and patient outcomes. The identification and characterization of TP53 mutations play pivotal roles in subclassifying myeloid neoplasms and guiding treatment decisions. Starting with the presentation of a typical case, this review highlights the complicated nature of genetic alterations involving TP53 and provides a comprehensive analysis of TP53 mutations and other alterations in myeloid neoplasms. Currently available methods used in clinical laboratories to identify TP53 mutations are discussed, focusing on the importance of establishing a robust testing protocol within clinical laboratories to ensure the delivery of accurate and reliable results. The treatment implications of TP53 mutations in myeloid neoplasms and clinical trial options are reviewed. Ultimately, we hope that this review provides valuable insights into the patterns of TP53 alterations in myeloid neoplasms and offers guidance to establish practical laboratory testing protocols to support the best practices of precision oncology.

Clinical and genetic characteristics of carriers of the TP53 c.541C > T, p.Arg181Cys pathogenic variant causing hereditary cancer in patients of Arab-Muslim descent

TP53 pathogenic variants cause Li-Fraumeni syndrome (LFS), with some variants causing an attenuated phenotype. Herein, we describe the clinical phenotype and genetic characteristics of carriers of NM_000546.6 (TP53): c.541C > T, (p.Arg181Cys) treated at Hadassah Medical Center. We retrospectively examined our genetic databases to identify all carriers of TP53 p.Arg181Cys. We reached out to carriers and their relatives and collected clinical and demographic data, lifestyle factors, carcinogenic exposures as well as additional blood samples for genetic testing and whole exome sequencing. Between 2005 and 2022 a total of 2875 cancer patients underwent genetic testing using genetic panels, whole exome sequencing or targeted TP53 assays. A total of 30 cancer patients, all of Arab-Muslim descent, were found to be carriers of TP53 p.Arg181Cys, the majority from Jerusalem and Hebron, two of which were homozygous for the variant. Carriers were from 24 distinct families of them, 15 families (62.5%) met updated Chompret criteria for LFS. Median age of diagnosis was 35 years-old (range 1-69) with cancers characteristic of LFS (16 Breast cancer; 6 primary CNS tumors; 3 sarcomas) including 4 children with choroid plexus carcinoma, medulloblastoma, or glioblastoma. A total of 21 healthy carriers of TP53 p.Arg181Cys were identified at a median age of 39 years-old (range 2-54)-19 relatives and 2 additional pediatric non-cancer patients, in which the finding was incidental. We report a shared haplotype of 350kb among carriers, limited co-morbidities and low BMI in both cancer patients and healthy carriers. There were no demographic factors or carcinogenic exposures unique to carriers who developed malignancy. Upon exome analysis no other known pathogenic variants in cancer predisposing genes were identified. TP53 p.Arg181Cys is a founder pathogenic variant predominant to the Arab-Muslim population in Jerusalem and Hebron, causing attenuated-LFS. We suggest strict surveillance in established carriers and encourage referral to genetic testing for all cancer patients of Arab-Muslim descent in this region with LFS-associated malignancies as well as family members of established carriers.

Overall survival in TP53-mutated AML and MDS

TP53 mutations in patients with AML and MDS frequently portend a poor prognosis, related to both p53 allele status and blast count. In 2022, the ICC and WHO released updated guidelines for classifying p53-mutated AML/MDS. The characteristics of p53 mutations, their associated co-mutations, and their effects on overall survival (OS) are not known in the context of these new guidelines. A retrospective chart review was undertaken for all patients with AML or MDS and at least one TP53 mutation detected on next generation sequencing (NGS) at Yale New Haven Hospital from 2015 to 2023. All patients (N = 210) met criteria for one of the 5 diagnostic classes based on WHO and ICC guidelines. Kaplan-Meier curves with associated log-rank testing and Cox proportional hazards model quantified the effects of clinical and molecular data on survival. Multi-hit pathogenic mutations were related to poorer OS in MDS but not AML using either the WHO (p = .02) or the ICC (p = .01) diagnostic criteria. The most significant predictors of OS in the sample overall were platelet count < 50 K (HR: 2.01, 95% CI [1.47, 2.75], p < .001) and TP53 VAF ≤ 40% (HR: 0.68, 95% CI[0.50, 0.91], p = .01). Blast count ranges, complex karyotype, and p53 mutation type or location, showed no association with OS. In our cohort defined by the 2022 ICC and WHO criteria, VAF and thrombocytopenia, rather than blast count or p53 mutation features, significantly predicted OS. These results speak to each criteria's ability to identify cases of similarly aggressive disease biology and prognosis.

Targeting mutant p53: a key player in breast cancer pathogenesis and beyond

The p53 mutation is the most common genetic mutation associated with human neoplasia. TP53 missense mutations, which frequently arise early in breast cancer, are present in over thirty percent of breast tumors. In breast cancer, p53 mutations are linked to a more aggressive course of the disease and worse overall survival rates. TP53 mutations are mostly seen in triple-negative breast cancer, a very diverse kind of the disease. The majority of TP53 mutations originate in the replacement of individual amino acids within the p53 protein's core domain, giving rise to a variety of variations referred to as "mutant p53s." In addition to gaining carcinogenic qualities through gain-of-function pathways, these mutants lose the typical tumor-suppressive features of p53 to variable degrees. The gain-of-function impact of stabilized mutant p53 causes tumor-specific dependency and resistance to therapy. P53 is a prospective target for cancer therapy because of its tumor-suppressive qualities and the numerous alterations that it experiences in tumors. Phenotypic abnormalities in breast cancer, notably poorly differentiated basal-like tumors are frequently linked to high-grade tumors. By comparing data from cell and animal models with clinical outcomes in breast cancer, this study investigates the molecular mechanisms that convert gene alterations into the pathogenic consequences of mutant p53's tumorigenic activity. The study delves into current and novel treatment approaches aimed at targeting p53 mutations, taking into account the similarities and differences in p53 regulatory mechanisms between mutant and wild-type forms, as well.

FGFR3 alterations in bladder cancer: Sensitivity and resistance to targeted therapies

In this review, we revisit the pivotal role of fibroblast growth factor receptor 3 (FGFR3) in bladder cancer (BLCA), underscoring its prevalence in both non-muscle-invasive and muscle-invasive forms of the disease. FGFR3 mutations in up to half of BLCAs play a well-established role in tumorigenesis, shaping distinct tumor initiation patterns and impacting the tumor microenvironment (TME). Emphasizing the importance of considering epithelial-mesenchymal transition profile and TME status, we revisit their relevance in predicting responses to immune checkpoint inhibitors in FGFR3-mutated BLCAs. This writing highlights the initially promising yet transient efficacy of the FGFR inhibitor Erdafitinib on FGFR3-mutated BLCA, stressing the pressing need to unravel resistance mechanisms and identify co-targets for future combinatorial studies. A thorough analysis of recent preclinical and clinical evidence reveals resistance mechanisms, including secondary mutations, epigenetic alterations in pathway effectors, phenotypic heterogeneity, and population-specific variations within FGFR3 mutational status. Lastly, we discuss the potential of combinatorial treatments and concepts like synthetic lethality for discovering more effective targeted therapies against FGFR3-mutated BLCA.

Understanding large scale sequencing datasets through changes to protein folding

The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.

Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis

Clonal hematopoiesis (CH) is a phenomenon of clonal expansion of hematopoietic stem cells driven by somatic mutations affecting certain genes. Recently, CH has been linked to the development of hematologic malignancies, cardiovascular diseases, and other conditions. Although the most frequently mutated CH driver genes have been identified, a systematic landscape of the mutations capable of initiating this phenomenon is still lacking. In this study, we trained machine learning models for 12 of the most recurrent CH genes to identify their driver mutations. These models outperform expert-curated rules based on prior knowledge of the function of these genes. Moreover, their application to identify CH driver mutations across almost half a million donors of the UK Biobank reproduces known associations between CH driver mutations and age, and the prevalence of several diseases and conditions. We thus propose that these models support the accurate identification of CH across healthy individuals. Significance: We developed and validated gene-specific machine learning models to identify CH driver mutations, showing their advantage with respect to expert-curated rules. These models can support the identification and clinical interpretation of CH mutations in newly sequenced individuals. See related commentary by Arends and Jaiswal, p. 1581.

Breast Carcinoma With Tubulopapillary Features Has a Distinct Immunophenotypic and Molecular Signature: A Report of Two Tumors and Literature Review

Breast carcinoma with tubulopapillary features is a newly described entity associated with poor prognosis with only 14 tumors reported in the literature. We report 2 additional tumors and identify novel immunohistochemical and molecular features of the tumor. The first tumor was from a 72-year-old woman with nonmetastatic breast carcinoma and the second was from a 32-year-old woman with metastatic breast carcinoma who received neoadjuvant therapy. Both tumors had high-grade nuclear features with a distinctive morphology characterized by infiltrating open glands with intratubular papillary and micropapillary projections in >90% of the invasive carcinoma. In addition to the usual predictors of aggressive behavior, both tumors showed a high expression of p16 and SOX10, which has not been previously described. Targeted tumor sequencing revealed pathogenic variants of TP53 in both tumors, in agreement with previous reports. Prior studies have shown a correlation between p16 and SOX10 expression with high-grade features and worse prognosis; typically seen in triple-negative carcinomas as demonstrated in both of our tumors. However, not all reported tumors of breast carcinoma with tubulopapillary features have demonstrated a triple-negative profile as there are a few reports of tumors with estrogen receptor and/or human epidermal growth factor 2 expression. Due to their distinct morphologic and molecular characteristics, breast carcinoma with tubulopapillary features may represent a new breast cancer histologic subtype.

Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification

As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings. Here, we describe a framework for generating, validating and incorporating data from MAVEs into a semi-quantitative variant classification method applied to clinical genetic testing. Using single-cell gene expression measurements, cellular evidence models were built to assess the effects of DNA variation in 44 genes of clinical interest. This framework was also applied to models for an additional 22 genes with previously published MAVE datasets. In total, modeling data was incorporated from 24 genes into our variant classification method. These data contributed evidence for classifying 4043 observed variants in over 57,000 individuals. Genetic testing laboratories are uniquely positioned to generate, analyze, validate, and incorporate evidence from high-throughput functional data and ultimately enable the use of these data to provide definitive clinical variant classifications for more patients.

Germline NGS targeted analysis in adult patients with sporadic adrenocortical carcinoma

BACKGROUND

Adrenocortical carcinoma (ACC) is a rare cancer that arises sporadically or due to hereditary syndromes. Data on germline variants (GVs) in sporadic ACC are limited. Our aim was to characterize GVs of genes potentially related to adrenal diseases in 150 adult patients with sporadic ACC.

METHODS

This was a retrospective analysis of stage I-IV ACC patients with sporadic ACC from two reference centers for ACC in Italy. Patients were included in the analysis if they had confirmed diagnosis of ACC, a frozen peripheral blood sample and complete clinical and follow-up data. Next generation sequencing technology was used to analyze the prevalence of GVs in a custom panel of 17 genes belonging to either cancer-predisposition genes or adrenocortical-differentiation genes categories.

RESULTS

We identified 18 GVs based on their frequency, enrichment and predicted functional characteristics. We found six pathogenic (P) or likely pathogenic (LP) variants in ARMC5, CTNNB1, MSH2, PDE11A and TP53 genes; and twelve variants lacking evidence of pathogenicity. New unique P/LP variants were identified in TP53 (p.G105D) and, for the first time, in ARMC5 (p.P731R). The presence of P/LP GVs was associated with reduced survival outcomes and had a significant and independent impact on both progression-free survival and overall survival.

CONCLUSIONS

GVs were present in 6.7 % of patients with sporadic ACC, and we identified novel variants of ARMC5 and TP53. These findings may improve understanding of ACC pathogenesis and enable genetic counseling of patients and their families.

Bioinformatic Identification of TP53 Gene Mutation Hotspots in Colorectal Cancer

Mutations and inactivation of the TP53 gene are frequently observed in various types of malignancies. Precise knowledge of the genetic structure and detection of mutation hotspots are crucial, as these indicate a high probability of developing cancer. The aim of our study was to perform the bioinformatic detection of mutation hotspots in the TP53 gene in patients diagnosed with malignant colon neoplasms using self-developed software (version 1). We compared TP53 gene sequences from 50 healthy individuals with those from 50 patients diagnosed with colorectal carcinoma. Of the 50 samples from cancer patients, the most frequent mutations were observed in exons 5 and 8 (12 mutations per exon) and gene sequences of 12 samples, which differed from those of the 50 samples from healthy individuals. Based on our results, the distribution of mutations in the TP53 gene structure was not even across different exons. By comparing the gene sequences of healthy individuals with those of colon cancer samples, we conclude that structural changes occurring in similar gene regions are not associated with increases in susceptibility to malignancies in every case, namely, that the pathological mechanism is multifactorial.

Canonical and non-canonical functions of p53 isoforms: potentiating the complexity of tumor development and therapy resistance

Full-length p53 (p53α) plays a pivotal role in maintaining genomic integrity and preventing tumor development. Over the years, p53 was found to exist in various isoforms, which are generated through alternative splicing, alternative initiation of translation, and internal ribosome entry site. p53 isoforms, either C-terminally altered or N-terminally truncated, exhibit distinct biological roles compared to p53α, and have significant implications for tumor development and therapy resistance. Due to a lack of part and/or complete C- or N-terminal domains, ectopic expression of some p53 isoforms failed to induce expression of canonical transcriptional targets of p53α like CDKN1A or MDM2, even though they may bind their promoters. Yet, p53 isoforms like Δ40p53α still activate subsets of targets including MDM2 and BAX. Furthermore, certain p53 isoforms transactivate even novel targets compared to p53α. More recently, non-canonical functions of p53α in DNA repair and of different isoforms in DNA replication unrelated to transcriptional activities were discovered, amplifying the potential of p53 as a master regulator of physiological and tumor suppressor functions in human cells. Both regarding canonical and non-canonical functions, alternative p53 isoforms frequently exert dominant negative effects on p53α and its partners, which is modified by the relative isoform levels. Underlying mechanisms include hetero-oligomerization, changes in subcellular localization, and aggregation. These processes ultimately influence the net activities of p53α and give rise to diverse cellular outcomes. Biological roles of p53 isoforms have implications for tumor development and cancer therapy resistance. Dysregulated expression of isoforms has been observed in various cancer types and is associated with different clinical outcomes. In conclusion, p53 isoforms have expanded our understanding of the complex regulatory network involving p53 in tumors. Unraveling the mechanisms underlying the biological roles of p53 isoforms provides new avenues for studies aiming at a better understanding of tumor development and developing therapeutic interventions to overcome resistance.

BRCA1 Intragenic Duplication Combined with a Likely Pathogenic TP53 Variant in a Patient with Triple-Negative Breast Cancer: Clinical Risk and Management

For patients with hereditary breast and ovarian cancer, the probability of carrying two pathogenic variants (PVs) in dominant cancer-predisposing genes is rare. Using targeted next-generation sequencing (NGS), we investigated a 49-year-old Caucasian woman who developed a highly aggressive breast tumor. Our analyses identified an intragenic germline heterozygous duplication in BRCA1 with an additional likely PV in the TP53 gene. The BRCA1 variant was confirmed by multiplex ligation probe amplification (MLPA), and genomic breakpoints were characterized at the nucleotide level (c.135-2578_442-1104dup). mRNA extracted from lymphocytes was amplified by RT-PCR and then Sanger sequenced, revealing a tandem duplication r.135_441dup; p.(Gln148Ilefs*20). This duplication results in the synthesis of a truncated and, most likely, nonfunctional protein. Following functional studies, the TP53 exon 5 c.472C > T; p.(Arg158Cys) missense variant was classified as likely pathogenic by the Li-Fraumeni Syndrome (LFS) working group. This type of unexpected association will be increasingly identified in the future, with the switch from targeted BRCA sequencing to hereditary breast and ovarian cancer (HBOC) panel sequencing, raising the question of how these patients should be managed. It is therefore important to record and investigate these rare double-heterozygous genotypes.

P53 Gene as a Promising Biomarker and Potential Target for the Early Diagnosis of Reproductive Cancers

One of the crucial aspects of cancer research is diagnosis with specificity and accuracy. Early cancer detection mostly helps make appropriate decisions regarding treatment and metastasis. The well-studied transcription factor tumor suppressor protein p53 is essential for maintaining genetic integrity. p53 is a key tumor suppressor that recognizes the carcinogenic biological pathways and eradicates them by apoptosis. A wide range of carcinomas, especially gynecological such as ovarian, cervical, and endometrial cancers, frequently undergo TP53 gene mutations. This study evaluates the potential of the p53 gene as a biological marker for the diagnosis of reproductive system neoplasms. Immunohistochemistry of p53 is rapid, easy to accomplish, cost-effective, and preferred by pathologists as a surrogate for the analysis of TP53 mutation. Thus, this review lays a groundwork for future efforts to develop techniques using p53 for the early diagnosis of cancer.

TP53-mutated acute myeloid leukemia and myelodysplastic syndrome: biology, treatment challenges, and upcoming approaches

Improved understanding of TP53 biology and the clinicopathological features of TP53-mutated myeloid neoplasms has led to the recognition of TP53-mutated acute myeloid leukemia/myelodysplastic syndrome (TP53m AML/MDS) as a unique entity, characterized by dismal outcomes following conventional therapies. Several clinical trials have investigated combinations of emerging therapies for these patients with the poorest molecular prognosis among myeloid neoplasms. Although some emerging therapies have shown improvement in overall response rates, this has not translated into better overall survival, hence the notion that p53 remains an elusive target. New therapeutic strategies, including novel targeted therapies, immune checkpoint inhibitors, and monoclonal antibodies, represent a shift away from cytotoxic and hypomethylating-based therapies, towards approaches combining non-immune and novel immune therapeutic strategies. The triple combination of azacitidine and venetoclax with either magrolimab or eprenetapopt have demonstrated safety in early trials, with phase III trials currently underway, and promising interim clinical results. This review compiles background on TP53 biology, available and emerging therapies along with their mechanisms of action for the TP53m disease entity, current treatment challenges, and recently published data and status of ongoing clinical trials for TP53m AML/MDS.

A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening

Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable editing efficiencies have complicated application of the approach to high-throughput functional genomics. Leveraging several recent advances, we assembled a prime editing platform capable of high-efficiency substitution editing across a set of engineered prime editing guide RNAs (epegRNAs) and corresponding target sequences (80% median intended editing). Then, using a custom library of 240,000 epegRNAs targeting >17,000 codons with 175 different substitution types, we benchmarked our platform for functional interrogation of small substitution variants (1-3 nucleotides) targeted to essential genes. Resulting data identified negative growth phenotypes for nonsense mutations targeted to ~8,000 codons, and comparing those phenotypes to results from controls demonstrated high specificity. We also observed phenotypes for synonymous mutations that disrupted splice site motifs at 3' exon boundaries. Altogether, we establish and benchmark a high-throughput prime editing approach for functional characterization of genetic variants with simple readouts from multiplexed experiments.

Phase I Study of ORIC-101, a Glucocorticoid Receptor Antagonist, in Combination with Enzalutamide in Patients with Metastatic Castration-resistant Prostate Cancer Progressing on Enzalutamide

PURPOSE

Increased glucocorticoid receptor (GR) signaling is a proposed compensatory mechanism of resistance to androgen receptor (AR) inhibition in metastatic castration-resistant prostate cancer (mCRPC). ORIC-101 is a potent and selective orally-bioavailable GR antagonist.

PATIENTS AND METHODS

Safety, pharmacokinetic/pharmacodynamic, and antitumor activity of ORIC-101 in combination with enzalutamide were studied in patients with mCRPC progressing on enzalutamide. ORIC-101 doses ranging from 80 to 240 mg once daily were tested in combination with enzalutamide 160 mg once daily. Pharmacokinetics/pharmacodynamics was assessed after a single dose and at steady state. Disease control rate (DCR) at 12 weeks was evaluated at the recommended phase 2 dose (RP2D).

RESULTS

A total of 41 patients were enrolled. There were no dose-limiting toxicities and the RP2D was selected as 240 mg of ORIC-101 and 160 mg of enzalutamide daily. At the RP2D, the most common treatment-related adverse events were fatigue (38.7%), nausea (29.0%), decreased appetite (19.4%), and constipation (12.9%). Pharmacokinetic/pharmacodynamic data confirmed ORIC-101 achieved exposures necessary for GR target engagement. Overall, for 31 patients treated at the RP2D, there was insufficient clinical benefit based on DCR (25.8%; 80% confidence interval: 15.65-38.52) which did not meet the prespecified target rate, leading to termination of the study. Exploratory subgroup analyses based on baseline GR expression, presence of AR resistance variants, and molecular features of aggressive variant prostate cancer suggested possible benefit in patients with high GR expression and no other resistance markers, although this would require confirmation.

CONCLUSIONS

Although the combination of ORIC-101 and enzalutamide demonstrated an acceptable tolerability profile, GR target inhibition with ORIC-101 did not produce clinical benefit in men with metastatic prostate cancer resistant to enzalutamide.

ERK pathway agonism for cancer therapy: evidence, insights, and a target discovery framework

At least 40% of human cancers are associated with aberrant ERK pathway activity (ERKp). Inhibitors targeting various effectors within the ERKp have been developed and explored for over two decades. Conversely, a substantial body of evidence suggests that both normal human cells and, notably to a greater extent, cancer cells exhibit susceptibility to hyperactivation of ERKp. However, this vulnerability of cancer cells remains relatively unexplored. In this review, we reexamine the evidence on the selective lethality of highly elevated ERKp activity in human cancer cells of varying backgrounds. We synthesize the insights proposed for harnessing this vulnerability of ERK-associated cancers for therapeutical approaches and contextualize these insights within established pharmacological cancer-targeting models. Moreover, we compile the intriguing preclinical findings of ERK pathway agonism in diverse cancer models. Lastly, we present a conceptual framework for target discovery regarding ERKp agonism, emphasizing the utilization of mutual exclusivity among oncogenes to develop novel targeted therapies for precision oncology.

A pan-cancer analysis of the oncogenic and immunological roles of transglutaminase 1 (TGM1) in human cancer

BACKGROUND

There is currently a limited number of studies on transglutaminase type 1 (TGM1) in tumors. The objective of this study is to perform a comprehensive analysis across various types of cancer to determine the prognostic significance of TGM1 in tumors and investigate its role in the immune environment.

METHOD

Pan-cancer and mutational data were retrieved from the TCGA database and analyzed using R (version 3.6.4) and its associated software package. The expression difference and prognosis of TGM1 were examined, along with its correlation with tumor heterogeneity, stemness, mutation landscape, and RNA modification. Additionally, the relationship between TGM1 expression and tumor immunity was investigated using the TIMER method.

RESULTS

TGM1 is expressed differently in various tumors and normal samples and is associated with the overall survival and progression-free time of KIRC, ACC, SKCM, LIHC, and STES. In LICH, we found a negative correlation between TGM1 expression and 6 indicators of tumor stemness. The mutation frequencies of BLCA, LIHC, and KIRC were 1.7%, 0.3%, and 0.3% respectively. In BLCA and BRCA, there was a significant correlation between TGM1 expression and the infiltration of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells.

CONCLUSION

TGM1 has the potential to serve as both a prognostic marker and a drug target.

High-throughput evaluation of genetic variants with prime editing sensor libraries

Tumor genomes often harbor a complex spectrum of single nucleotide alterations and chromosomal rearrangements that can perturb protein function. Prime editing has been applied to install and evaluate genetic variants, but previous approaches have been limited by the variable efficiency of prime editing guide RNAs. Here we present a high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites to quantitatively assess the functional impact of endogenous genetic variants. We screen over 1,000 endogenous cancer-associated variants of TP53-the most frequently mutated gene in cancer-to identify alleles that impact p53 function in mechanistically diverse ways. We find that certain endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein-protein interactions, and establish a framework for studying genetic variants in their endogenous sequence context at scale.

Primary vulvar adenocarcinoma of intestinal type: Report of two cases showing molecular similarity with colorectal adenocarcinoma

Primary vulvar adenocarcinoma is a particularly rare tumor with poorly understood histogenesis and unclear clinical characteristics and prognosis. Vulvar adenocarcinoma of intestinal type (VAIt) is a very uncommon subtype of primary vulvar adenocarcinoma and only 27 cases have been described in the literature in the past. Of these cases, two have been described as human papillomavirus (HPV)-associated VAIt. The current report presents two additional cases of primary VAIt showing variants in the KRAS, TP53, and DPYD genes and no evidence of HPV DNA by real-time polymerase chain reaction (RT-PCR). Next-generation sequencing (NGS) revealed TP53 pathogenic variants in both cases, but only one case had aberrant p53 protein immunohistochemical characteristics. KRAS and DPYD mutations were identified separately in the two cases. Due to their capacity to imitate the spread of more prevalent gastrointestinal carcinomas, these tumors may present diagnostic issues. Additional cases can contribute to a better understanding of the pathophysiology and prognosis of VAIt.

Understanding the prion-like behavior of mutant p53 proteins in triple-negative breast cancer pathogenesis: The current therapeutic strategies and future directions

Breast cancer (BC) is viewed as a significant public health issue and is the primary cause of cancer-related deaths among women worldwide. Triple-negative breast cancer (TNBC) is a particularly aggressive subtype that predominantly affects young premenopausal women. The tumor suppressor p53 playsa vital role in the cellular response to DNA damage, and its loss or mutations are commonly present in many cancers, including BC. Recent evidence suggests that mutant p53 proteins can aggregate and form prion-like structures, which may contribute to the pathogenesis of different types of malignancies, such as BC. This review provides an overview of BC molecular subtypes, the epidemiology of TNBC, and the role of p53 in BC development. We also discuss the potential implications of prion-like aggregation in BC and highlight future research directions. Moreover, a comprehensive analysis of the current therapeutic approaches targeting p53 aggregates in BC treatment is presented. Strategies including small molecules, chaperone inhibitors, immunotherapy, CRISPR-Cas9, and siRNA are discussed, along with their potential benefits and drawbacks. The use of these approaches to inhibit p53 aggregation and degradation represents a promising target for cancer therapy. Future investigations into the efficacy of these approaches against various p53 mutations or binding to non-p53 proteins should be conducted to develop more effective and personalized therapies for BC treatment.

BRCA1, BRCA2, and TP53 germline and somatic variants and clinicopathological characteristics of Brazilian patients with epithelial ovarian cancer

BACKGROUND

Approximately 3/4 of ovarian cancers are diagnosed in advanced stages, with the high-grade epithelial ovarian carcinoma (EOC) accounting for 90% of the cases. EOC present high genomic instability and somatic loss-of-function variants in genes associated with homologous recombination mutational repair pathway (HR), such as BRCA1 and BRCA2, and in TP53. The identification of germline variants in HR genes in EOC is relevant for treatment of platinum resistant tumors and relapsed tumors with therapies based in synthetic lethality such as PARP inhibitors. Patients with somatic variants in HR genes may also benefit from these therapies. In this work was analyzed the frequency of somatic variants in BRCA1, BRCA2, and TP53 in an EOC cohort of Brazilian patients, estimating the proportion of variants in tumoral tissue and their association with progression-free survival and overall survival.

METHODS

The study was conducted with paired blood/tumor samples from 56 patients. Germline and tumoral sequences of BRCA1, BRCA2, and TP53 were obtained by massive parallel sequencing. The HaplotypeCaller method was used for calling germline variants, and somatic variants were called with Mutect2.

RESULTS

A total of 26 germline variants were found, and seven patients presented germline pathogenic or likely pathogenic variants in BRCA1 or BRCA2. The analysis of tumoral tissue identified 52 somatic variants in 41 patients, being 43 somatic variants affecting or likely affecting protein functionality. Survival analyses showed that tumor staging was associated with overall survival (OS), while the presence of somatic mutation in TP53 was not associated with OS or progression-free survival.

CONCLUSION

Frequency of pathogenic or likely pathogenic germline variants in BRCA1 and BRCA2 (12.5%) was lower in comparison with other studies. TP53 was the most altered gene in tumors, with 62.5% presenting likely non-functional or non-functional somatic variants, while eight 14.2% presented likely non-functional or non-functional somatic variants in BRCA1 or BRCA2.

Pharmacological reactivation of p53 in the era of precision anticancer medicine

p53, which is encoded by the most frequently mutated gene in cancer, TP53, is an attractive target for novel cancer therapies. Despite major challenges associated with this approach, several compounds that either augment the activity of wild-type p53 or restore all, or some, of the wild-type functions to p53 mutants are currently being explored. In wild-type TP53 cancer cells, p53 function is often abrogated by overexpression of the negative regulator MDM2, and agents that disrupt p53-MDM2 binding can trigger a robust p53 response, albeit potentially with induction of p53 activity in non-malignant cells. In TP53-mutant cancer cells, compounds that promote the refolding of missense mutant p53 or the translational readthrough of nonsense mutant TP53 might elicit potent cell death. Some of these compounds have been, or are being, tested in clinical trials involving patients with various types of cancer. Nonetheless, no p53-targeting drug has so far been approved for clinical use. Advances in our understanding of p53 biology provide some clues as to the underlying reasons for the variable clinical activity of p53-restoring therapies seen thus far. In this Review, we discuss the intricate interactions between p53 and its cellular and microenvironmental contexts and factors that can influence p53's activity. We also propose several strategies for improving the clinical efficacy of these agents through the complex perspective of p53 functionality.

A machine learning and directed network optimization approach to uncover TP53 regulatory patterns

TP53, the Guardian of the Genome, is the most frequently mutated gene in human cancers and the functional characterization of its regulation is fundamental. To address this we employ two strategies: machine learning to predict the mutation status of TP53 from transcriptomic data, and directed regulatory networks to reconstruct the effect of mutations on the transcipt levels of TP53 targets. Using data from established databases (Cancer Cell Line Encyclopedia, The Cancer Genome Atlas), machine learning could predict the mutation status, but not resolve different mutations. On the contrary, directed network optimization allowed to infer the TP53 regulatory profile across: (1) mutations, (2) irradiation in lung cancer, and (3) hypoxia in breast cancer, and we could observe differential regulatory profiles dictated by (1) mutation type, (2) deleterious consequences of the mutation, (3) known hotspots, (4) protein changes, (5) stress condition (irradiation/hypoxia). This is an important first step toward using regulatory networks for the characterization of the functional consequences of mutations, and could be extended to other perturbations, with implications for drug design and precision medicine.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.