Genome-wide analysis reveals genomic diversity and signatures of selection in Qinchuan beef cattle.

BACKGROUND: Indigenous Chinese cattle have abundant genetic diversity and a long history of artificial selection, giving local breeds advantages in adaptability, forage tolerance and resistance. The detection of selective sweeps and comparative genome analysis of selected breeds and ancestral populations provide a basis for understanding differences among breeds and for the identification and utilization of candidate genes. We investigated genetic diversity, population structure, and signatures of selection using genome-wide sequencing data for a new breed of Qinchuan cattle (QNC, n = 21), ancestral Qinchuan cattle (QCC, n = 20), and Zaosheng cattle (ZSC, n = 19). RESULTS: A population structure analysis showed that the ancestry components of QNC and ZSC were similar. In addition, the QNC and ZSC groups showed higher proportions of European taurine ancestry than that of QCC, and this may explain the larger body size of QNC, approaching that of European cattle under long-term domestication and selection. A neighbor-joining tree revealed that QCC individuals were closely related, whereas QNC formed a distinct group. To search for signatures of selection in the QNC genome, we evaluated nucleotide diversity (θπ), the fixation index (FST) and Tajima's D. Overlapping selective sweeps were enriched for one KEGG pathway, the apelin signaling pathway, and included five candidate genes (MEF2A, SMAD2, CAMK4, RPS6, and PIK3CG). We performed a comprehensive review of genomic variants in QNC, QCC, and ZSC using whole-genome sequencing data. QCC was rich in novel genetic diversity, while diversity in QNC and ZSC cattle was reduced due to strong artificial selection, with divergence from the original cattle. CONCLUSIONS: We identified candidate genes associated with production traits. These results support the success of selective breeding and can guide further breeding and resource conservation of Qinchuan cattle.

Prospective of Mitochondrial DNA Variations in Cancer on Genomic Medicine.

Mitochondrial DNA (mtDNA) has emerged as a pivotal component in understanding the etiology and susceptibility of cancer. A recent study by Chen and colleagues delineated the germline genetic effect of mtDNA single-nucleotide polymorphisms (SNP) and haplogroups across pan-cancer risk. They identified a subset of mtSNPs and the corresponding risk score, as well as haplogroups A and M7 alongside their genetic interactions, conferring a protective effect against various cancers. These findings underscored the value of mtDNA variations as biomarkers for cancer etiology and as tools for cancer risk stratification. Future investigations are encouraged to integrate comprehensive omics data of genomics, transcriptomics, proteomics, and metabolomics, etc., from nuclear DNA with mtDNA variations, alongside single-cell and spatial technologies, to unravel the tumor mechanism and identify the drug targets. Moreover, the incorporation of polygenic risk score, that included mtDNA variations with both rare and common frequencies, and liquid biopsy-based biomarkers would enhance the predictive performance of cancer risk assessment and refine the risk stratification of population-based cancer screening. This commentary advocates for the validation across diverse populations to harness the full potential of mitochondrial genomics, and ultimately paves the prospective way for advancements in personalized cancer therapeutics and prevention strategies. See related article by Chen and colleagues, Cancer Epidemiol Biomarkers Prev 2024;33:381-8.

Insights into the genomic traits of Yersinia frederiksenii, Yersinia intermedia and Yersinia kristensenii isolated from diverse sources in Brazil.

Yersinia is an important genus comprising foodborne, zoonotic and pathogenic bacteria. On the other hand, species of the so-called group Yersinia enterocolitica-like are understudied and mostly characterized as non-pathogenic, despite of some reports of human infections. The present study aimed to provide genomic insights of Yersinia frederiksenii (YF), Yersinia intermedia (YI) and Yersinia kristensenii (YK) isolated worldwide. A total of 22 YF, 20 YI and 14 YK genomes were searched for antimicrobial resistance genes, plasmids, prophages, and virulence factors. Their phylogenomic relatedness was analyzed by Gegenees and core-genome multi-locus sequence typing. Beta-lactam resistance gene blaTEM-116 and five plasmids replicons (pYE854, ColRNAI, ColE10, Col(pHAD28) and IncN3) were detected in less than five genomes. A total of 59 prophages, 106 virulence markers of the Yersinia genus, associated to adherence, antiphagocytosis, exoenzymes, invasion, iron uptake, proteases, secretion systems and the O-antigen, and virulence factors associated to other 20 bacterial genera were detected. Phylogenomic analysis revealed high inter-species distinction and four highly diverse YF clusters. In conclusion, the results obtained through the analyses of YF, YI and YK genomes suggest the virulence potential of these strains due to the broad diversity and high frequency of prophages and virulence factors found. Phylogenetic analyses were able to correctly distinguish these closely related species and show the presence of different genetic subgroups. These data contributed for a better understanding of YF, YI and YK virulence-associated features and global genetic diversity, and reinforced the need for better characterization of these Y. enterocolitica-like species considered non-pathogenic.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

Comparative Genomics and Characterization of Shigella flexneri Isolated from Urban Wastewater.

Shigella species are a group of highly transmissible Gram-negative pathogens. Increasing reports of infection with extensively drug-resistant varieties of this stomach bug has convinced the World Health Organization to prioritize Shigella for novel therapeutic interventions. We herein coupled the whole-genome sequencing of a natural isolate of Shigella flexneri with a pangenome ana-lysis to characterize pathogen genomics within this species, which will provide us with an insight into its existing genomic diversity and highlight the root causes behind the emergence of quick vaccine escape variants. The isolated novel strain of S. flexneri contained ~4,500 protein-coding genes, 57 of which imparted resistance to antibiotics. A comparative pan-genomic ana-lysis revealed genomic variability of ~64%, the shared conservation of core genes in central metabolic processes, and the enrichment of unique/accessory genes in virulence and defense mechanisms that contributed to much of the observed antimicrobial resistance (AMR). A pathway ana-lysis of the core genome mapped 22 genes to 2 antimicrobial resistance pathways, with the bulk coding for multidrug efflux pumps and two component regulatory systems that are considered to work synergistically towards the development of resistance phenotypes. The prospective evolvability of Shigella species as witnessed by the marked difference in genomic content, the strain-specific essentiality of unique/accessory genes, and the inclusion of a potent resistance mechanism within the core genome, strengthens the possibility of novel serotypes emerging in the near future and emphasizes the importance of tracking down genomic diversity in drug/vaccine design and AMR governance.

Genomic profiling informs therapies and prognosis for patients with hepatocellular carcinoma in clinical practice.

Hepatocellular carcinoma (HCC) genomic research has discovered actionable genetic changes that might guide treatment decisions and clinical trials. Nonetheless, due to a lack of large-scale multicenter clinical validation, these putative targets have not been converted into patient survival advantages. So, it's crucial to ascertain whether genetic analysis is clinically feasible, useful, and whether it can be advantageous for patients. We sequenced tumour tissue and blood samples (as normal controls) from 111 Chinese HCC patients at Qingdao University Hospital using the 508-gene panel and the 688-gene panel, respectively. Approximately 95% of patients had gene variations related to targeted treatment, with 50% having clinically actionable mutations that offered significant information for targeted therapy. Immune cell infiltration was enhanced in individuals with TP53 mutations but decreased in patients with CTNNB1 and KMT2D mutations. More notably, we discovered that SPEN, EPPK1, and BRCA2 mutations were related to decreased median overall survival, although MUC16 mutations were not. Furthermore, we found mutant MUC16 as an independent protective factor for the prognosis of HCC patients after curative hepatectomy. In conclusion, this study connects genetic abnormalities to clinical practice and potentially identifies individuals with poor prognoses who may benefit from targeted treatment or immunotherapy.

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies.

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is usually required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low read depth; (2) most of the benefit of short-read polishing occurs by 25× depth; (3) Polypolish-careful almost never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5×), Polypolish-careful and Pypolca-careful when depth is low (5-25×), and Polypolish-default and Pypolca-careful when depth is sufficient (>25×).

European Autism GEnomics Registry (EAGER): protocol for a multicentre cohort study and registry.

INTRODUCTION: Autism is a common neurodevelopmental condition with a complex genetic aetiology that includes contributions from monogenic and polygenic factors. Many autistic people have unmet healthcare needs that could be served by genomics-informed research and clinical trials. The primary aim of the European Autism GEnomics Registry (EAGER) is to establish a registry of participants with a diagnosis of autism or an associated rare genetic condition who have undergone whole-genome sequencing. The registry can facilitate recruitment for future clinical trials and research studies, based on genetic, clinical and phenotypic profiles, as well as participant preferences. The secondary aim of EAGER is to investigate the association between mental and physical health characteristics and participants' genetic profiles. METHODS AND ANALYSIS: EAGER is a European multisite cohort study and registry and is part of the AIMS-2-TRIALS consortium. EAGER was developed with input from the AIMS-2-TRIALS Autism Representatives and representatives from the rare genetic conditions community. 1500 participants with a diagnosis of autism or an associated rare genetic condition will be recruited at 13 sites across 8 countries. Participants will be given a blood or saliva sample for whole-genome sequencing and answer a series of online questionnaires. Participants may also consent to the study to access pre-existing clinical data. Participants will be added to the EAGER registry and data will be shared externally through established AIMS-2-TRIALS mechanisms. ETHICS AND DISSEMINATION: To date, EAGER has received full ethical approval for 11 out of the 13 sites in the UK (REC 23/SC/0022), Germany (S-375/2023), Portugal (CE-085/2023), Spain (HCB/2023/0038, PIC-164-22), Sweden (Dnr 2023-06737-01), Ireland (230907) and Italy (CET_62/2023, CEL-IRCCS OASI/24-01-2024/EM01, EM 2024-13/1032 EAGER). Findings will be disseminated via scientific publications and conferences but also beyond to participants and the wider community (eg, the AIMS-2-TRIALS website, stakeholder meetings, newsletters).

Morphological, Metabolomic and Genomic Evidences on Drought Stress Protective Functioning of the Endophyte Bacillus safensis Ni7.

The metabolomic and genomic characterization of an endophytic Bacillus safensis Ni7 was carried out in this study. This strain has previously been isolated from the xerophytic plant Nerium indicum L. and reported to enhance the drought tolerance in Capsicum annuum L. seedlings. The effects of drought stress on the morphology, biofilm production, and metabolite production of B. safensis Ni7 are analyzed in the current study. From the results obtained, the organism was found to have multiple strategies such as aggregation and clumping, robust biofilm production, and increased production of surfactin homologues under the drought induced condition when compared to non-stressed condition. Further the whole genome sequencing (WGS) based analysis has demonstrated B. safensis Ni7 to have a genome size of 3,671,999 bp, N50 value of 3,527,239, and a mean G+C content of 41.58%. Interestingly the organism was observed to have the presence of various stress-responsive genes (13, 20U, 16U,160, 39, 17M, 18, 26, and ctc) and genes responsible for surfactin production (srfAA, srfAB, srfAC, and srfAD), biofilm production (epsD, epsE, epsF, epsG, epsH, epsI, epsK, epsL, epsM, epsN, and pel), chemotaxis (cheB_1, cheB_2, cheB_3, cheW_1, cheW_2 cheR, cheD, cheC, cheA, cheY, cheV, and cheB_4), flagella synthesis (flgG_1, flgG_2, flgG_3, flgC, and flgB) as supportive to the drought tolerance. Besides these, the genes responsible for plant growth promotion (PGP), including the genes for nitrogen (nasA, nasB, nasC, nasD, and nasE) and sulfur assimilation (cysL_1&L_2, cysI) and genes for phosphate solubilization (phoA, phoP_1& phoP_2, and phoR) could also be predicted. Along with the same, the genes for catalase, superoxide dismutase, protein homeostasis, cellular fitness, osmoprotectants production, and protein folding could also be predicted from its WGS data. Further pan-genome analysis with plant associated B. safensis strains available in the public databases revealed B. safensis Ni7 to have the presence of a total of 5391 gene clusters. Among these, 3207 genes were identified as core genes, 954 as shell genes and 1230 as cloud genes. This variation in gene content could be taken as an indication of evolution of strains of Bacillus safensis as per specific conditions and hence in the case of B. safensis Ni7 its role in habitat adaptation of plant is well expected. This diversity in endophytic bacterial genes may attribute its role to support the plant system to cope up with stress conditions. Overall, the study provides genomic evidence on Bacillus safensis Ni7 as a stress alleviating microbial partner in plants.

Whole-genome sequencing reveals genomic diversity and selection signatures in Xia'nan cattle.

BACKGROUND: The crossbreeding of specialized beef cattle breeds with Chinese indigenous cattle is a common method of genetic improvement. Xia'nan cattle, a crossbreed of Charolais and Nanyang cattle, is China's first specialized beef cattle breed with independent intellectual property rights. After more than two decades of selective breeding, Xia'nan cattle exhibit a robust physique, good environmental adaptability, good tolerance to coarse feed, and high meat production rates. This study analyzed the population genetic structure, genetic diversity, and genomic variations of Xia'nan cattle using whole-genome sequencing data from 30 Xia'nan cattle and 178 published cattle genomic data. RESULT: The ancestry estimating composition analysis showed that the ancestry proportions for Xia'nan cattle were mainly Charolais with a small amount of Nanyang cattle. Through the genetic diversity studies (nucleotide diversity and linkage disequilibrium decay), we found that the genomic diversity of Xia'nan cattle is higher than that of specialized beef cattle breeds in Europe but lower than that of Chinese native cattle. Then, we used four methods to detect genome candidate regions influencing the excellent traits of Xia'nan cattle. Among the detected results, 42 genes (θπ and CLR) and 131 genes (FST and XP-EHH) were detected by two different detection strategies. In addition, we found a region in BTA8 with strong selection signals. Finally, we conducted functional annotation on the detected genes and found that these genes may influence body development (NR6A1), meat quality traits (MCCC1), growth traits (WSCD1, TMEM68, MFN1, NCKAP5), and immunity (IL11RA, CNTFR, CCL27, SLAMF1, SLAMF7, NAA35, and GOLM1). CONCLUSION: We elucidated the genomic features and population structure of Xia'nan cattle and detected some selection signals in genomic regions potentially associated with crucial economic traits in Xia'nan cattle. This research provided a basis for further breeding improvements in Xia'nan cattle and served as a reference for genetic enhancements in other crossbreed cattle.

Assessment of the pathogen genomics landscape highlights disparities and challenges for effective AMR Surveillance and outbreak response in the East African community.

The East African Community (EAC) grapples with many challenges in tackling infectious disease threats and antimicrobial resistance (AMR), underscoring the importance of regional and robust pathogen genomics capacities. However, a significant disparity exists among EAC Partner States in harnessing bacterial pathogen sequencing and data analysis capabilities for effective AMR surveillance and outbreak response. This study assesses the current landscape and challenges associated with pathogen next-generation sequencing (NGS) within EAC, explicitly focusing on World Health Organization (WHO) AMR-priority pathogens. The assessment adopts a comprehensive approach, integrating a questionnaire-based survey amongst National Public Health Laboratories (NPHLs) with an analysis of publicly available metadata on bacterial pathogens isolated in the EAC countries. In addition to the heavy reliance on third-party organizations for bacterial NGS, the findings reveal a significant disparity among EAC member States in leveraging bacterial pathogen sequencing and data analysis. Approximately 97% (n = 4,462) of publicly available high-quality bacterial genome assemblies of samples collected in the EAC were processed and analyzed by external organizations, mainly in Europe and North America. Tanzania led in-country sequencing efforts, followed by Kenya and Uganda. The other EAC countries had no publicly available samples or had all their samples sequenced and analyzed outside the region. Insufficient local NGS sequencing facilities, limited bioinformatics expertise, lack of adequate computing resources, and inadequate data-sharing mechanisms are among the most pressing challenges that hinder the EAC's NPHLs from effectively leveraging pathogen genomics data. These insights emphasized the need to strengthen microbial pathogen sequencing and data analysis capabilities within the EAC to empower these laboratories to conduct pathogen sequencing and data analysis independently. Substantial investments in equipment, technology, and capacity-building initiatives are crucial for supporting regional preparedness against infectious disease outbreaks and mitigating the impact of AMR burden. In addition, collaborative efforts should be developed to narrow the gap, remedy regional imbalances, and harmonize NGS data standards. Supporting regional collaboration, strengthening in-country genomics capabilities, and investing in long-term training programs will ultimately improve pathogen data generation and foster a robust NGS-driven AMR surveillance and outbreak response in the EAC, thereby supporting global health initiatives.

A versatile, rapid Agrobacterium-mediated transient expression system for functional genomics studies in cannabis seedling.

MAIN CONCLUSION: We have developed and optimized a rapid, versatile Agrobacterium-mediated transient expression system for cannabis seedlings that can be used in functional genomics studies of both hemp-type and drug-type cannabis. Cannabis (Cannabis sativa L.) holds great promise in the medical and food industries due to its diverse chemical composition, including specialized cannabinoids. However, the study of key genes involved in various biological processes, including secondary metabolite biosynthesis, has been hampered by the lack of efficient in vivo functional analysis methods. Here, we present a novel, short-cycle, high-efficiency transformation method for cannabis seedlings using Agrobacterium tumefaciens. We used the RUBY reporter system to monitor transformation results without the need for chemical treatments or specialized equipment. Four strains of A. tumefaciens (GV3101, EHA105, LBA4404, and AGL1) were evaluated for transformation efficiency, with LBA4404 and AGL1 showing superior performance. The versatility of the system was further demonstrated by successful transformation with GFP and GUS reporter genes. In addition, syringe infiltration was explored as an alternative to vacuum infiltration, offering simplicity and efficiency for high-throughput applications. Our method allows rapid and efficient in vivo transformation of cannabis seedlings, facilitating large-scale protein expression and high-throughput characterization studies.

Genomic insights into novel Erwinia bacteriophages: unveiling their Henunavirus membership and host infection strategies.

Erwinia amylovora, the primary causative agent of blight disease in rosaceous plants, poses a significant threat to agricultural yield worldwide, with limited effective countermeasures. The emergence of sustainable alternative agents such as bacteriophages is a promising solution for fire blight that specifically targets Erwinia. In this study, we isolated pEp_SNUABM_01 and pEa_SNUABM_55 from a South Korean apple orchard soil, analyzed their genomic DNA sequences, and performed a comprehensive comparative analysis of Hena1 in four distinct sections. This study aimed to unveil distinctive features of these phages, with a focus on host recognition, which will provide valuable insights into the evolution and characteristics of Henunavirus bacteriophages that infect plant pathogenic Erwinia spp. By elucidating the distinct genomic features of these phages, particularly in terms of host recognition, this study lays a foundation for their potential application in mitigating the risks associated with fire blight in Rosaceae plants on a global scale.

Accelerating 3D genomics data analysis with Microcket.

The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .

Bioinformatics for Dentistry: A secondary database for the genetics of tooth development.

Genes strictly regulate the development of teeth and their surrounding oral structures. Alteration of gene regulation leads to tooth disorders and developmental anomalies in tooth, oral, and facial regions. With the advancement of gene sequencing technology, genomic data is rapidly increasing. However, the large sets of genomic and proteomic data related to tooth development and dental disorders are currently dispersed in many primary databases and literature, making it difficult for users to navigate, extract, study, or analyze. We have curated the scattered genetic data on tooth development and created a knowledgebase called 'Bioinformatics for Dentistry' (https://dentalbioinformatics.com/). This database compiles genomic and proteomic data on human tooth development and developmental anomalies and organizes them according to their roles in different stages of tooth development. The database is built by systemically curating relevant data from the National Library of Medicine (NCBI) GenBank, OMIM: Online Mendelian Inheritance in Man, AlphaFold Protein Structure Database, Reactome pathway knowledgebase, Wiki Pathways, and PubMed. The accuracy of the included data was verified from supporting primary literature. Upon data curation and validation, a simple, easy-to-navigate browser interface was created on WordPress version 6.3.2, with PHP version 8.0. The website is hosted in a cloud hosting service to provide fast and reliable data transfer rate. Plugins are used to ensure the browser's compatibility across different devices. Bioinformatics for Dentistry contains four embedded filters for complex and specific searches and free-text search options for quick and simple searching through the datasets. Bioinformatics for Dentistry is made freely available worldwide, with the hope that this knowledgebase will improve our understanding of the complex genetic regulation of tooth development and will open doors to research initiatives and discoveries. This database will be expanded in the future by incorporating resources and built-in sequence analysis tools, and it will be maintained and updated annually.

Revisiting Cardiac Biology in the Era of Single Cell and Spatial Omics.

Throughout our lifetime, each beat of the heart requires the coordinated action of multiple cardiac cell types. Understanding cardiac cell biology, its intricate microenvironments, and the mechanisms that govern their function in health and disease are crucial to designing novel therapeutical and behavioral interventions. Recent advances in single-cell and spatial omics technologies have significantly propelled this understanding, offering novel insights into the cellular diversity and function and the complex interactions of cardiac tissue. This review provides a comprehensive overview of the cellular landscape of the heart, bridging the gap between suspension-based and emerging in situ approaches, focusing on the experimental and computational challenges, comparative analyses of mouse and human cardiac systems, and the rising contextualization of cardiac cells within their niches. As we explore the heart at this unprecedented resolution, integrating insights from both mouse and human studies will pave the way for novel diagnostic tools and therapeutic interventions, ultimately improving outcomes for patients with cardiovascular diseases.

The evolution of thermogenesis in mammals.

Comparative genomics elucidates the steps enabling heat production in fat tissue.

Prevalence of Potentially Pathogenic Germline Variants Among Adult Patients in the Philippines With Solid Malignancies Who Underwent Tumor Genomic Profiling.

PURPOSE: In high-income countries, 2%-10% of tumor genomic profiling (TGP) reports reveal incidental pathogenic germline variants. A third of these patients would not qualify for genetic testing on the basis of current guidelines. Our study determined the prevalence of potentially pathogenic germline variants (PPGVs) in TGP results of adult patients with solid malignancies in the Philippines. METHODS: Annotated reports of patients with solid cancers who underwent TGP using FoundationOne or FoundationOne Heme between January 2021 and July 2023 were reviewed. PPGV criteria include having a variant allele frequency of >30% and were categorized as (1) high penetrance gene (HP), founder variant (FV), or variant associated with clinical presentation (VA). Pathogenicity was crosschecked through the ClinVar database. RESULTS: Of 446 patients, 13 PPGV variants were found in 50 (11.2%) patients at a median age of 60.5 years. Of them, 28 (56%) had HP (BRCA1, BRCA2, MSH2, MSH6, MLH1, RAD51C, RAD51D), 25 (50%) patients had VA (APC, SMAD4, CDH1, CDKN2A, PTEN), and two patients with lung cancer had a FV (EGFR p.Thr790Met). Six patients had more than one PPGV. PPGVs were primarily found in patients with colorectal (42% of 50 patients with PPGVs), breast (16%), ovarian (6%), and lung (6%) cancer (P < .001). HP genes were mostly found in female patients (71.4%; P = .03). CONCLUSION: With a PPGV prevalence of 11% in this study, it is important to recognize PPGVs as it can prompt genetic counseling and confirmatory germline testing.

Genomic profiles of Japanese patients with vulvar squamous cell carcinoma.

The incidence of vulvar carcinoma varies by race; however, it is a rare disease, and its genomic profiles remain largely unknown. This study examined the characteristics of vulvar squamous cell carcinoma (VSCC) in Japanese patients, focusing on genomic profiles and potential racial disparities. The study included two Japanese groups: the National Cancer Center Hospital (NCCH) group comprised 19 patients diagnosed between 2015 and 2023, and the Center for Cancer Genomics and Advanced Therapeutics group comprised 29 patients diagnosed between 2019 and 2022. Somatic mutations were identified by targeted or panel sequencing, and TP53 was identified as the most common mutation (52-81%), followed by HRAS (7-26%), CDKN2A (21-24%), and PIK3CA (5-10%). The mutation frequencies, except for TP53, were similar to those of Caucasian cohorts. In the NCCH group, 16 patients of HPV-independent tumors were identified by immunohistochemistry and genotyping. Univariate analysis revealed that TP53-mutated patients were associated with a poor prognosis (log-rank test, P = 0.089). Japanese VSCC mutations resembled those of Caucasian vulvar carcinomas, and TP53 mutations predicted prognosis regardless of ethnicity. The present findings suggest potential molecular-targeted therapies for select VSCC patients.