Genome Medicine最新文献

{"title":"Correction: Intricate interplay of CRISPR-Cas systems, anti-CRISPR proteins, and antimicrobial resistance genes in a globally successful multi-drug resistant Klebsiella pneumoniae clone.","authors":"Jianping Jiang, Astrid V Cienfuegos-Gallet, Tengfei Long, Gisele Peirano, Tingyu Chu, Johann D D Pitout, Barry N Kreiswirth, Liang Chen","doi":"10.1186/s13073-025-01436-6","DOIUrl":"10.1186/s13073-025-01436-6","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"13"},"PeriodicalIF":10.4,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11852811/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143491757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The landcape of Helicobacter pylori-mediated DNA breaks links bacterial genotoxicity to its oncogenic potential.","authors":"Hadas Sibony-Benyamini, Rose Jbara, Tania Shubash Napso, Layan Abu-Rahmoun, Daniel Vizenblit, Michal Easton-Mor, Shira Perez, Alexander Brandis, Tamar Leshem, Avi Peretz, Yaakov Maman","doi":"10.1186/s13073-025-01439-3","DOIUrl":"10.1186/s13073-025-01439-3","url":null,"abstract":"<p><strong>Background: </strong>Helicobacter pylori (H. pylori) infection is a significant risk factor for gastric cancer (GC) development. A growing body of evidence suggests a causal link between infection with H. pylori and increased DNA breakage in the host cells. While several mechanisms have been proposed for this damage, their relative impact on the overall bacterial genotoxicity is unknown. Moreover, the link between the formation of DNA damage following infection and the emergence of cancerous structural variants (SV) in the genome of infected cells remained unexplored.</p><p><strong>Methods: </strong>We constructed a high-resolution map of genomic H. pylori-induced recurrent break sites using the END-seq method on AGS human gastric cells before and after infection. We next applied END-seq to cycling and arrested cells to identify the role of DNA replication on break formation. Recurrent H. pylori-mediated break sites were further characterized by analyzing published RNA-seq, DRIP-seq, and GRO-seq data at these sites. γH2AX staining and comet assay were used for DNA breakage quantification. Liquid chromatography-mass spectrometry (LC-MS) assay was used to quantify cellular concentrations of dNTPs.</p><p><strong>Results: </strong>Our data indicated that sites of recurrent H. pylori-mediated DNA breaks are ubiquitous across cell types, localized at replication-related fragile sites, and their breakage is dependent on replication. Consistent with that, we found that H. pylori inflicts nucleotide depletion, and that rescuing the cellular nucleotide pool largely reduced H. pylori-induced DNA breaks. Intriguingly, we found that this genotoxic mechanism operates independently of H. pylori cag pathogenicity island (CagPAI) that encodes for the bacterial type 4 secretion system (T4SS), and its virulence factor, CagA, which was previously implicated in increasing DNA damage by downregulating the DNA damage response. Finally, we show that sites of recurrent H. pylori-mediated breaks coincide with chromosomal deletions observed in patients with intestinal-type GC and that this link potentially elucidates the persistent transcriptional alterations observed in cancer driver genes.</p><p><strong>Conclusions: </strong>Our findings indicate that dNTP depletion by H. pylori is a key component of its genotoxicity and suggest a link between H. pylori genotoxicity and its oncogenic potential.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"14"},"PeriodicalIF":10.4,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143491764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging flow cytometry-based cellular screening elucidates pathophysiology in individuals with Variants of Uncertain Significance.","authors":"Irena Josephina Johanna Muffels, Hans R Waterham, Giuseppina D'Alessandro, Guido Zagnoli-Vieira, Michael Sacher, Dirk J Lefeber, Celine Van der Vinne, Chaim M Roifman, Koen L I Gassen, Holger Rehmann, Desiree Y Van Haaften-Visser, Edward S S Nieuwenhuis, Stephen P Jackson, Sabine A Fuchs, Femke Wijk, Peter van Hasselt","doi":"10.1186/s13073-025-01433-9","DOIUrl":"10.1186/s13073-025-01433-9","url":null,"abstract":"<p><strong>Background: </strong>Deciphering variants of uncertain significance (VUS) represents a major diagnostic challenge, partially due to the lack of easy-to-use and versatile cellular readouts that aid the interpretation of pathogenicity and pathophysiology. To address this challenge, we propose a high-throughput screening of cellular functionality through an imaging flow cytometry (IFC)-based platform.</p><p><strong>Methods: </strong>Six assays to evaluate autophagic-, lysosomal-, Golgi- health, mitochondrial function, ER stress, and NF-κβ activity were developed in fibroblasts. Assay sensitivity was verified with compounds (N = 5) and positive control patients (N = 6). Eight healthy controls and 20 individuals with VUS were screened.</p><p><strong>Results: </strong>All molecular compounds and positive controls showed significant changes on their cognate assays, confirming assay sensitivity. Simultaneous screening of positive control patients on all six assays revealed distinct phenotypic profiles. In addition, individuals with VUS(es) in well-known disease genes showed distinct - but similar-phenotypic profiles compared to patients with pathogenic variants in the same gene.. For all individuals with VUSes in Genes of Uncertain Significance (GUS), we found one or more of six assays were significantly altered. Broadening the screening to an untargeted approach led to the identification of two clusters that allowed for the recognition of altered cell cycle dynamics and DNA damage repair defects. Experimental follow-up of the 'DNA damage repair defect cluster' led to the discovery of highly specific defects in top2cc release from double-strand DNA breaks in one of these individuals, harboring a VUS in the RAD54L2 gene.</p><p><strong>Conclusions: </strong>Our high-throughput IFC-based platform simplifies the process of identifying VUS pathogenicity through six assays and allows for the recognition of useful pathophysiological markers that structure follow-up experiments, thereby representing a novel valuable tool for precise functional diagnostics in genomics.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"12"},"PeriodicalIF":10.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143370749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twins as global learning health and disease models for preventive and personalized medicine.","authors":"Xinxiu Li, Joseph Loscalzo, A K M Firoj Mahmud, Dina Mansour Aly, Andrey Rzhetsky, Marinka Zitnik, Mikael Benson","doi":"10.1186/s13073-025-01435-7","DOIUrl":"10.1186/s13073-025-01435-7","url":null,"abstract":"<p><p>Ineffective medication is a major healthcare problem causing significant patient suffering and economic costs. This issue stems from the complex nature of diseases, which involve altered interactions among thousands of genes across multiple cell types and organs. Disease progression can vary between patients and over time, influenced by genetic and environmental factors. To address this challenge, digital twins have emerged as a promising approach, which have led to international initiatives aiming at clinical implementations. Digital twins are virtual representations of health and disease processes that can integrate real-time data and simulations to predict, prevent, and personalize treatments. Early clinical applications of DTs have shown potential in areas like artificial organs, cancer, cardiology, and hospital workflow optimization. However, widespread implementation faces several challenges: (1) characterizing dynamic molecular changes across multiple biological scales; (2) developing computational methods to integrate data into DTs; (3) prioritizing disease mechanisms and therapeutic targets; (4) creating interoperable DT systems that can learn from each other; (5) designing user-friendly interfaces for patients and clinicians; (6) scaling DT technology globally for equitable healthcare access; (7) addressing ethical, regulatory, and financial considerations. Overcoming these hurdles could pave the way for more predictive, preventive, and personalized medicine, potentially transforming healthcare delivery and improving patient outcomes.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"11"},"PeriodicalIF":10.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806862/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143370695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics uncovers immune-modulatory molecules in plasma contributing to resistance exercise-ameliorated locomotor disability after incomplete spinal cord injury.","authors":"Ren Zhou, Jibao Chen, Yunhan Tang, Chuijin Wei, Ping Yu, Xinmei Ding, Li'ao Zhu, Jiajia Yao, Zengqiang Ouyang, Jing Qiao, Shumin Xiong, Liaoliao Dong, Tong Yin, Haiqing Li, Ye Feng, Lin Cheng","doi":"10.1186/s13073-025-01434-8","DOIUrl":"10.1186/s13073-025-01434-8","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Exercise rehabilitation therapy has garnered widespread recognition for its beneficial effects on the restoration of locomotor function in individuals with spinal cord injury (SCI). Notably, resistance exercise has demonstrated significant improvements in muscle strength, coordination, and overall functional recovery. However, to optimize clinical management and mimic exercise-like effects, it is imperative to obtain a comprehensive understanding of the molecular alterations that underlie these positive effects.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a randomized controlled clinical trial investigating the effects of resistance exercise therapy for incomplete SCI. We integrated the analysis of plasma proteomics and peripheral blood mononuclear cells (PBMC) transcriptomics to explore the molecular and cellular changes induced by resistance exercise. Subsequently, we established a weight-loaded ladder-climbing mouse model to mimic the physiological effects of resistance exercise, and we analyzed the plasma proteome and metabolome, as well as the transcriptomes of PBMC and muscle tissue. Lastly, to confirm the transmissibility of the neuroprotective effects induced by resistance exercise, we intravenously injected plasma obtained from exercised male mice into SCI female mice during the non-acute phase.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Plasma proteomic and PBMC transcriptomic profiling underscored the notable involvement of the complement pathways and humoral immune response in the process of restoring locomotor function following SCI in the human trial. Moreover, it was emphasized that resistance exercise interventions could effectively modulate these pathways. Through employing plasma proteomic profiling and transcriptomic profiling of PBMC and muscle tissues in mice, our study revealed immunomodulatory responses that parallel those observed in human trials. In addition, our analysis of plasma metabolomics revealed an enhancement in lipid metabolism following resistance exercise. We observed that resistance exercise plasma exhibited significant effects in ameliorating locomotor disability after SCI via reducing demyelination and inhibiting neuronal apoptosis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our investigation elucidates the molecular alterations associated with resistance exercise therapy promoting recovery of locomotor function following incomplete SCI. Moreover, we demonstrate the direct neuroprotective effects delivered via exercise plasma injection, which facilitates spinal cord repair. Mechanistically, the comprehensive multi-omics analysis involving both human and mice reveals that the principal constituents responsible for the observed neuroprotective effects within the plasma are predominantly immunoregulatory factors, warranting further experimental validation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Trial registration: &lt;/strong&gt;The study was retrospectively registered on 17 July, 2024, in Chinese Clinical Trial Registry (No.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"10"},"PeriodicalIF":10.4,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11796186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intricate interplay of CRISPR-Cas systems, anti-CRISPR proteins, and antimicrobial resistance genes in a globally successful multi-drug resistant Klebsiella pneumoniae clone.","authors":"Jianping Jiang, Astrid V Cienfuegos-Gallet, Tengfei Long, Gisele Peirano, Tingyu Chu, Johann D D Pitout, Barry N Kreiswirth, Liang Chen","doi":"10.1186/s13073-025-01428-6","DOIUrl":"10.1186/s13073-025-01428-6","url":null,"abstract":"<p><strong>Background: </strong>Klebsiella pneumoniae is one of the most prevalent pathogens responsible for multiple infections in healthcare settings and the community. K. pneumoniae CG147, primarily including ST147 (the founder ST), ST273, and ST392, is one of the most globally successful MDR clone linked to various carbapenemases.</p><p><strong>Methods: </strong>One hundred and one CG147 strains were sequenced and additional 911 publicly available CG147 genome sequences were included for analysis. The molecular epidemiology, population structure, and time phylogeny were investigated. The virulome, resistome, and mobilome were analyzed, and the recombination in the capsular region was studied. The CRISPR-Cas and anti-CRISPR were identified. The interplay between CRISPR-Cas, anti-CRISPR, and carbapenemase-encoding plasmids was analyzed and experimentally validated.</p><p><strong>Results: </strong>We analyzed 1012 global CG147 genomes, with 80.4% encoding at least one carbapenemase (NDM [529/1012, 52.3%], OXA-48-like [182/1012, 17.7%], and KPC [105/1012, 10.4%]). Surprisingly, almost all CG147 strains (99.7%, 1009/1,012) harbor a chromosomal type I-E CRISPR-Cas system, with 41.8% (423/1012) containing an additional plasmid-borne type IV-A3 CRISPR-Cas system, and both target IncF plasmids, e.g., the most prevalent KPC-encoding pKpQIL-like plasmids. We found the presence of IV-A3 CRISPR-Cas system showed a negative correlation with the presence of KPC. Interestingly, a prophage-encoding anti-CRISPR AcrIE8.1 and a plasmid-borne anti-CRISPR AcrIE9.2 were detected in 40.1% (406/1012) and 54.2% (548/1012) of strains, respectively, which displayed positive correlations with the presence of a carbapenemase. Plasmid transfer experiments confirmed that the I-E and IV-A3 CRISPR-Cas systems significantly decreased (p < 0.001) KPC-encoding pKpQIL plasmid conjugation frequencies, while the AcrIE8.1 and AcrIE9.2 significantly increased (p < 0.001) pKpQIL conjugation frequencies and protected plasmids from elimination by CRISPR-Cas I-E system.</p><p><strong>Conclusions: </strong>Our results indicated a complex interplay between CRISPR-Cas, anti-CRISPR, and mobile genetic elements that shape the evolution of CG147. Our findings advance the understanding of multi-drug resistance mechanisms and will aid in preventing the emergence of future MDR clones.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"9"},"PeriodicalIF":10.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11781037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143065216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission.","authors":"Benjamin Sobkowiak, Patrick Cudahy, Melanie H Chitwood, Taane G Clark, Caroline Colijn, Louis Grandjean, Katharine S Walter, Valeriu Crudu, Ted Cohen","doi":"10.1186/s13073-025-01430-y","DOIUrl":"10.1186/s13073-025-01430-y","url":null,"abstract":"<p><strong>Background: </strong>Mixed infection with multiple strains of the same pathogen in a single host can present clinical and analytical challenges. Whole genome sequence (WGS) data can identify signals of multiple strains in samples, though the precision of previous methods can be improved. Here, we present MixInfect2, a new tool to accurately detect mixed samples from Mycobacterium tuberculosis short-read WGS data. We then evaluate three approaches for reconstructing the underlying mixed constituent strain sequences. This allows these samples to be included in downstream analysis to gain insights into the epidemiology and transmission of mixed infections.</p><p><strong>Methods: </strong>We employed a Gaussian mixture model to cluster allele frequencies at mixed sites (hSNPs) in each sample to identify signals of multiple strains. Building upon our previous tool, MixInfect, we increased the accuracy of classifying in vitro mixed samples through multiple improvements to the bioinformatic pipeline. Major and minor proportion constituent strains were reconstructed using three approaches and assessed by comparing the estimated sequence to the known constituent strain sequence. Lastly, mixed infections in a real-world Mycobacterium tuberculosis population from Moldova were detected with MixInfect2 and clusters of recent transmission that included major and minor constituent strains were built.</p><p><strong>Results: </strong>All 36/36 in vitro mixed and 12/12 non-mixed samples were correctly classified with MixInfect2, and major strain proportions were estimated with high accuracy (within 3% of the true strain proportion), outperforming previous tools. Reconstructed major strain sequences closely matched the true constituent sequence by taking the allele at the highest frequency at hSNPs, while the best-performing approach to reconstruct the minor proportion strain sequence was identifying the closest non-mixed isolate in the same population, though no approach was effective when the minor strain proportion was at 5%. Finally, fewer mixed infections were identified in Moldova than previous estimates (6.6% vs 17.4%) and we found multiple instances where the constituent strains of mixed samples were present in transmission clusters.</p><p><strong>Conclusions: </strong>MixInfect2 accurately detects samples with evidence of mixed infection from short-read WGS data and provides an excellent estimate of the mixture proportions. While there are limitations in reconstructing the constituent strain sequences of mixed samples, we present recommendations for the best approach to include these isolates in further analyses.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"8"},"PeriodicalIF":10.4,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.","authors":"Arda Halu, Sarvesh Chelvanambi, Julius L Decano, Joan T Matamalas, Mary Whelan, Takaharu Asano, Namitra Kalicharran, Sasha A Singh, Joseph Loscalzo, Masanori Aikawa","doi":"10.1186/s13073-025-01431-x","DOIUrl":"10.1186/s13073-025-01431-x","url":null,"abstract":"<p><strong>Background: </strong>Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.</p><p><strong>Methods: </strong>We build cell type-specific gene-drug perturbation networks from CMap data using a statistical procedure we call Quantile-based Instance Z-score Consensus (QUIZ-C). Using these networks and a large-scale disease-gene network consisting of 569 disease signatures from the Enrichr database, we calculate Pathophenotypic Congruity Scores (PACOS) between input gene signatures and drug perturbation signatures and combine these scores with cheminformatic data from ChEMBL to prioritize drugs. We benchmark our approach by calculating area under the receiver operating characteristic curves (AUROC) for 73 gene sets from the Molecular Signatures Database (MSigDB) using target gene expression profiles from the Comparative Toxicogenomics Database (CTD). We validate the drugs predicted in our proofs-of-concept using real-time polymerase chain reaction (qPCR) experiments.</p><p><strong>Results: </strong>Cell type-specific gene-drug perturbation networks built using QUIZ-C are topologically distinct, reflecting the biological uniqueness of the cell lines in CMap, and are enriched in known drug targets. Pathopticon demonstrates a better prediction performance than solely cheminformatic measures as well as state-of-the-art network and deep learning-based methods. Top predictions made by Pathopticon have high chemical structural diversity, suggesting their potential for building compound libraries. In proof-of-concept applications on vascular diseases, we demonstrate that Pathopticon helps guide in vitro experiments by identifying pathways that are potentially regulated by the predicted therapeutic candidates.</p><p><strong>Conclusions: </strong>Our network-based analytical framework integrating pharmacogenomics and cheminformatics (available at https://github.com/r-duh/Pathopticon ) provides a feasible blueprint for a cell type-specific drug discovery and repositioning platform with broad implications for the efficiency and success of drug development.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"7"},"PeriodicalIF":10.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143004371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nanopore-based random genomic sampling for intraoperative molecular diagnosis.","authors":"Francesco E Emiliani, Abdol Aziz Ould Ismail, Edward G Hughes, Gregory J Tsongalis, George J Zanazzi, Chun-Chieh Lin","doi":"10.1186/s13073-025-01427-7","DOIUrl":"10.1186/s13073-025-01427-7","url":null,"abstract":"<p><strong>Background: </strong>Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging. Despite recent advances in intraoperative methylation classifications of brain tumors, accuracy may be compromised by low tumor purity. Copy number variations (CNVs), which are almost ubiquitous in cancer, offer highly sensitive molecular biomarkers for diagnosis. These quantitative genomic alterations provide insight into dysregulated oncogenic pathways and can reveal potential targets for molecular therapies.</p><p><strong>Methods: </strong>We develop iSCORED, a one-step random genomic DNA reconstruction method that enables efficient, unbiased quantification of genome-wide CNVs. By concatenating multiple genomic fragments into long reads, the method leverages low-pass sequencing to generate approximately 1-2 million genomic fragments within 1 h. This approach allows for ultrafast high-resolution CNV analysis at a genomic resolution of 50 kb. In addition, concurrent methylation profiling enables brain tumor methylation classification and identifies promoter methylation in amplified oncogenes, providing an integrated diagnostic approach.</p><p><strong>Results: </strong>In our retrospective cohort of 26 malignant brain tumors, iSCORED demonstrated 100% concordance in CNV detection, including chromosomal alterations and oncogene amplifications, when compared to clinically validated assays such as Next-Generation Sequencing and Chromosomal Microarray. Furthermore, we validated iSCORED's real-time applicability in 15 diagnostically challenging primary brain tumors, achieving 100% concordance in detecting aberrant CNV detection, including diagnostic chromosomal gains/losses and oncogene amplifications (10/10). Of these, 14 out of 15 brain tumor methylation classifications aligned with final pathological diagnoses. This streamlined workflow-from tissue arrival to automatic generation of CNV and methylation reports-can be completed within 105 min.</p><p><strong>Conclusions: </strong>The iSCORED pipeline represents the first method capable of high-resolution CNV detection within the intraoperative timeframe. By combining CNV detection and methylation classification, iSCORED provides a rapid and comprehensive molecular diagnostic tool that can inform rapid clinical decision. The integrated approach not only enhances the accuracy of tumor diagnosis but also optimizes surgical planning and identifies potential molecular therapies, all within the critical intraoperative timeframe.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"6"},"PeriodicalIF":10.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143004373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analyses of mouse and human prostate single-cell transcriptomes reveal widespread epithelial plasticity in tissue regression, regeneration, and cancer.","authors":"Luis Aparicio, Laura Crowley, John R Christin, Caroline J Laplaca, Hanina Hibshoosh, Raul Rabadan, Michael M Shen","doi":"10.1186/s13073-025-01432-w","DOIUrl":"10.1186/s13073-025-01432-w","url":null,"abstract":"<p><strong>Background: </strong>Despite extensive analysis, the dynamic changes in prostate epithelial cell states during tissue homeostasis as well as tumor initiation and progression have been poorly characterized. However, recent advances in single-cell RNA-sequencing (scRNA-seq) technology have greatly facilitated studies of cell states and plasticity in tissue maintenance and cancer, including in the prostate.</p><p><strong>Methods: </strong>We have performed meta-analyses of new and previously published scRNA-seq datasets for mouse and human prostate tissues to identify and compare cell populations across datasets in a uniform manner. Using random matrix theory to denoise datasets, we have established reference cell type classifications for the normal mouse and human prostate and have used optimal transport to compare the cross-species transcriptomic similarities of epithelial cell populations. In addition, we have integrated analyses of single-cell transcriptomic states with copy number variants to elucidate transcriptional programs in epithelial cells during human prostate cancer progression.</p><p><strong>Results: </strong>Our analyses demonstrate transcriptomic similarities between epithelial cell states in the normal prostate, in the regressed prostate after androgen-deprivation, and in primary prostate tumors. During regression in the mouse prostate, all epithelial cells shift their expression profiles toward a proximal periurethral (PrU) state, demonstrating an androgen-dependent plasticity that is restored to normal during androgen restoration and gland regeneration. In the human prostate, we find substantial rewiring of transcriptional programs across epithelial cell types in benign prostate hyperplasia and treatment-naïve prostate cancer. Notably, we detect copy number variants predominantly within luminal acinar cells in prostate tumors, suggesting a bias in their cell type of origin, as well as a larger field of transcriptomic alterations in non-tumor cells. Finally, we observe that luminal acinar tumor cells in treatment-naïve prostate cancer display heterogeneous androgen receptor (AR) signaling activity, including a split between AR-positive and AR-low profiles with similarity to PrU-like states.</p><p><strong>Conclusions: </strong>Taken together, our analyses of cellular heterogeneity and plasticity provide important translational insights into the origin and treatment response of prostate cancer. In particular, the identification of AR-low tumor populations suggests that castration-resistance and predisposition to neuroendocrine differentiation may be pre-existing properties in treatment-naïve primary tumors that are selected for by androgen-deprivation therapies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"5"},"PeriodicalIF":10.4,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11740708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143004372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}