Pub Date : 2024-10-09Epub Date: 2024-09-23DOI: 10.1016/j.xgen.2024.100659
Canhui Cao, Miaochun Xu, Ye Wei, Ting Peng, Shitong Lin, Xiaojie Liu, Yashi Xu, Tian Chu, Shiyi Liu, Ping Wu, Bai Hu, Wencheng Ding, Li Li, Ding Ma, Peng Wu
Evidence from clinical trials suggests that CXCR4 antagonists enhance immunotherapy effectiveness in several cancers. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood. Here, we employed single-cell transcriptomic analysis and identified CXCR4 as a marker gene in T cells, with CD8+PD-1high exhausted T (Tex) cells exhibiting high CXCR4 expression. By blocking CXCR4, the Tex phenotype was attenuated in vivo. Mechanistically, CXCR4-blocking T cells mitigated the Tex phenotype by regulating the JAK2-STAT3 pathway. Single-cell RNA/TCR/ATAC-seq confirmed that Cxcr4-deficient CD8+ T cells epigenetically mitigated the transition from functional to exhausted phenotypes. Notably, clinical sample analysis revealed that CXCR4+CD8+ T cells showed higher expression in patients with a non-complete pathological response. Collectively, these findings demonstrate the mechanism by which CXCR4 orchestrates CD8+ Tex cells and provide a rationale for combining CXCR4 antagonists with immunotherapy in clinical trials.
{"title":"CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8<sup>+</sup> T cells via JAK2/STAT3 pathway.","authors":"Canhui Cao, Miaochun Xu, Ye Wei, Ting Peng, Shitong Lin, Xiaojie Liu, Yashi Xu, Tian Chu, Shiyi Liu, Ping Wu, Bai Hu, Wencheng Ding, Li Li, Ding Ma, Peng Wu","doi":"10.1016/j.xgen.2024.100659","DOIUrl":"10.1016/j.xgen.2024.100659","url":null,"abstract":"<p><p>Evidence from clinical trials suggests that CXCR4 antagonists enhance immunotherapy effectiveness in several cancers. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood. Here, we employed single-cell transcriptomic analysis and identified CXCR4 as a marker gene in T cells, with CD8<sup>+</sup>PD-1<sup>high</sup> exhausted T (T<sub>ex</sub>) cells exhibiting high CXCR4 expression. By blocking CXCR4, the T<sub>ex</sub> phenotype was attenuated in vivo. Mechanistically, CXCR4-blocking T cells mitigated the T<sub>ex</sub> phenotype by regulating the JAK2-STAT3 pathway. Single-cell RNA/TCR/ATAC-seq confirmed that Cxcr4-deficient CD8<sup>+</sup> T cells epigenetically mitigated the transition from functional to exhausted phenotypes. Notably, clinical sample analysis revealed that CXCR4<sup>+</sup>CD8<sup>+</sup> T cells showed higher expression in patients with a non-complete pathological response. Collectively, these findings demonstrate the mechanism by which CXCR4 orchestrates CD8<sup>+</sup> T<sub>ex</sub> cells and provide a rationale for combining CXCR4 antagonists with immunotherapy in clinical trials.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The emergence of perturbation transcriptomics provides a new perspective for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to deconvolute compound-protein interactions from perturbation transcriptomics with knowledge graph embedding. By considering multi-level regulatory events within biological systems that share the same semantic context, PertKGE significantly improves deconvoluting accuracy in two critical "cold-start" settings: inferring targets for new compounds and conducting virtual screening for new targets. We further demonstrate the pivotal role of incorporating multi-level regulatory events in alleviating representational biases. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti-tumor immunotherapy effect of tankyrase inhibitor K-756 and the discovery of five novel hits targeting the emerging cancer therapeutic target aldehyde dehydrogenase 1B1 with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery.
{"title":"Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics.","authors":"Shengkun Ni, Xiangtai Kong, Yingying Zhang, Zhengyang Chen, Zhaokun Wang, Zunyun Fu, Ruifeng Huo, Xiaochu Tong, Ning Qu, Xiaolong Wu, Kun Wang, Wei Zhang, Runze Zhang, Zimei Zhang, Jiangshan Shi, Yitian Wang, Ruirui Yang, Xutong Li, Sulin Zhang, Mingyue Zheng","doi":"10.1016/j.xgen.2024.100655","DOIUrl":"10.1016/j.xgen.2024.100655","url":null,"abstract":"<p><p>The emergence of perturbation transcriptomics provides a new perspective for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to deconvolute compound-protein interactions from perturbation transcriptomics with knowledge graph embedding. By considering multi-level regulatory events within biological systems that share the same semantic context, PertKGE significantly improves deconvoluting accuracy in two critical \"cold-start\" settings: inferring targets for new compounds and conducting virtual screening for new targets. We further demonstrate the pivotal role of incorporating multi-level regulatory events in alleviating representational biases. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti-tumor immunotherapy effect of tankyrase inhibitor K-756 and the discovery of five novel hits targeting the emerging cancer therapeutic target aldehyde dehydrogenase 1B1 with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100673
Yuerong Wang, Xian Fu, Yue Shen
The molecular mechanisms underlying the paradoxical effects1 of aneuploidy are still not completely understood. In this issue, Rojas et al.2 systematically analyzed the associated costs of aneuploidy and the molecular drivers involved, which revealed that aneuploidy stress is primarily driven by the cumulative effects of genes per chromosome. Notably, gene length was predicted as the most significant indicator of aneuploidy toxicity by machine learning.
{"title":"The hidden costs of aneuploidy: New insights from yeast.","authors":"Yuerong Wang, Xian Fu, Yue Shen","doi":"10.1016/j.xgen.2024.100673","DOIUrl":"https://doi.org/10.1016/j.xgen.2024.100673","url":null,"abstract":"<p><p>The molecular mechanisms underlying the paradoxical effects<sup>1</sup> of aneuploidy are still not completely understood. In this issue, Rojas et al.<sup>2</sup> systematically analyzed the associated costs of aneuploidy and the molecular drivers involved, which revealed that aneuploidy stress is primarily driven by the cumulative effects of genes per chromosome. Notably, gene length was predicted as the most significant indicator of aneuploidy toxicity by machine learning.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100676
Claudia Nussbaum, Sarah Kim-Hellmuth
Human milk has long been recognized for its critical role in infant and maternal health. In this issue of Cell Genomics, Johnson et al.1 apply a human genetics and genomics approach to shed light on the complex relationship between maternal genetics, milk variation, and the infant gut microbiome.
{"title":"Unlocking the genetic influence on milk variation and its potential implication for infant health.","authors":"Claudia Nussbaum, Sarah Kim-Hellmuth","doi":"10.1016/j.xgen.2024.100676","DOIUrl":"https://doi.org/10.1016/j.xgen.2024.100676","url":null,"abstract":"<p><p>Human milk has long been recognized for its critical role in infant and maternal health. In this issue of Cell Genomics, Johnson et al.<sup>1</sup> apply a human genetics and genomics approach to shed light on the complex relationship between maternal genetics, milk variation, and the infant gut microbiome.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100667
Tian Yu, James D Fife, Vineel Bhat, Ivan Adzhubey, Richard Sherwood, Christopher A Cassa
Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.
{"title":"FUSE: Improving the estimation and imputation of variant impacts in functional screening.","authors":"Tian Yu, James D Fife, Vineel Bhat, Ivan Adzhubey, Richard Sherwood, Christopher A Cassa","doi":"10.1016/j.xgen.2024.100667","DOIUrl":"https://doi.org/10.1016/j.xgen.2024.100667","url":null,"abstract":"<p><p>Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100657
Siyang Liu, Jilong Yao, Liang Lin, Xianmei Lan, Linlin Wu, Xuelian He, Nannan Kong, Yan Li, Yuqing Deng, Jiansheng Xie, Huanhuan Zhu, Xiaoxia Wu, Zilong Li, Likuan Xiong, Yuan Wang, Jinghui Ren, Xuemei Qiu, Weihua Zhao, Ya Gao, Yuanqing Chen, Fengxia Su, Yun Zhou, Weiqiao Rao, Jing Zhang, Guixue Hou, Liping Huang, Linxuan Li, Xinhong Liu, Chao Nie, Liqiong Luo, Mei Zhao, Zengyou Liu, Fang Chen, Shengmou Lin, Lijian Zhao, Qingmei Fu, Dan Jiang, Ye Yin, Xun Xu, Jian Wang, Huanming Yang, Rong Wang, Jianmin Niu, Fengxiang Wei, Xin Jin, Siqi Liu
Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.
{"title":"Genome-wide association study of maternal plasma metabolites during pregnancy.","authors":"Siyang Liu, Jilong Yao, Liang Lin, Xianmei Lan, Linlin Wu, Xuelian He, Nannan Kong, Yan Li, Yuqing Deng, Jiansheng Xie, Huanhuan Zhu, Xiaoxia Wu, Zilong Li, Likuan Xiong, Yuan Wang, Jinghui Ren, Xuemei Qiu, Weihua Zhao, Ya Gao, Yuanqing Chen, Fengxia Su, Yun Zhou, Weiqiao Rao, Jing Zhang, Guixue Hou, Liping Huang, Linxuan Li, Xinhong Liu, Chao Nie, Liqiong Luo, Mei Zhao, Zengyou Liu, Fang Chen, Shengmou Lin, Lijian Zhao, Qingmei Fu, Dan Jiang, Ye Yin, Xun Xu, Jian Wang, Huanming Yang, Rong Wang, Jianmin Niu, Fengxiang Wei, Xin Jin, Siqi Liu","doi":"10.1016/j.xgen.2024.100657","DOIUrl":"https://doi.org/10.1016/j.xgen.2024.100657","url":null,"abstract":"<p><p>Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11Epub Date: 2024-08-06DOI: 10.1016/j.xgen.2024.100628
Laura V Blanton, Adrianna K San Roman, Geryl Wood, Ashley Buscetta, Nicole Banks, Helen Skaletsky, Alexander K Godfrey, Thao T Pham, Jennifer F Hughes, Laura G Brown, Paul Kruszka, Angela E Lin, Daniel L Kastner, Maximilian Muenke, David C Page
Recent in vitro studies of human sex chromosome aneuploidy showed that the Xi ("inactive" X) and Y chromosomes broadly modulate autosomal and Xa ("active" X) gene expression. We tested these findings in vivo. Linear modeling of CD4+ T cells and monocytes from individuals with one to three X chromosomes and zero to two Y chromosomes revealed 82 sex-chromosomal and 344 autosomal genes whose expression changed significantly with Xi and/or Y dosage in vivo. Changes in sex-chromosomal expression were remarkably constant in vivo and in vitro; autosomal responses to Xi and/or Y dosage were largely cell-type specific (∼2.6-fold more variation than sex-chromosomal responses). Targets of the sex-chromosomal transcription factors ZFX and ZFY accounted for a significant fraction of these autosomal responses both in vivo and in vitro. We conclude that the human Xi and Y transcriptomes are surprisingly robust and stable, yet they modulate autosomal and Xa genes in a cell-type-specific fashion.
最近对人类性染色体非整倍体的体外研究表明,Xi("非活性 "X)和 Y 染色体可广泛调节常染色体和 Xa("活性 "X)基因的表达。我们在体内检验了这些发现。对具有一至三条 X 染色体和零至两条 Y 染色体的个体的 CD4+ T 细胞和单核细胞进行线性建模,发现有 82 个性染色体基因和 344 个常染色体基因的表达在体内随 Xi 和/或 Y 的剂量发生显著变化。性染色体表达的变化在体内和体外都非常稳定;常染色体对Xi和/或Y剂量的反应在很大程度上具有细胞类型特异性(比性染色体反应的变化大2.6倍)。性染色体转录因子 ZFX 和 ZFY 的靶标在体内和体外均占这些常染色体反应的很大一部分。我们的结论是,人类的 Xi 和 Y 转录组具有惊人的稳健性和稳定性,但它们以细胞类型特异性的方式调节常染色体基因和 Xa 基因。
{"title":"Stable and robust Xi and Y transcriptomes drive cell-type-specific autosomal and Xa responses in vivo and in vitro in four human cell types.","authors":"Laura V Blanton, Adrianna K San Roman, Geryl Wood, Ashley Buscetta, Nicole Banks, Helen Skaletsky, Alexander K Godfrey, Thao T Pham, Jennifer F Hughes, Laura G Brown, Paul Kruszka, Angela E Lin, Daniel L Kastner, Maximilian Muenke, David C Page","doi":"10.1016/j.xgen.2024.100628","DOIUrl":"10.1016/j.xgen.2024.100628","url":null,"abstract":"<p><p>Recent in vitro studies of human sex chromosome aneuploidy showed that the Xi (\"inactive\" X) and Y chromosomes broadly modulate autosomal and Xa (\"active\" X) gene expression. We tested these findings in vivo. Linear modeling of CD4<sup>+</sup> T cells and monocytes from individuals with one to three X chromosomes and zero to two Y chromosomes revealed 82 sex-chromosomal and 344 autosomal genes whose expression changed significantly with Xi and/or Y dosage in vivo. Changes in sex-chromosomal expression were remarkably constant in vivo and in vitro; autosomal responses to Xi and/or Y dosage were largely cell-type specific (∼2.6-fold more variation than sex-chromosomal responses). Targets of the sex-chromosomal transcription factors ZFX and ZFY accounted for a significant fraction of these autosomal responses both in vivo and in vitro. We conclude that the human Xi and Y transcriptomes are surprisingly robust and stable, yet they modulate autosomal and Xa genes in a cell-type-specific fashion.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480847/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141903762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11Epub Date: 2024-08-30DOI: 10.1016/j.xgen.2024.100639
Rodrigo Martín, Nicolás Gaitán, Frédéric Jarlier, Lars Feuerbach, Henri de Soyres, Marc Arbonés, Tom Gutman, Montserrat Puiggròs, Alvaro Ferriz, Asier Gonzalez, Lucía Estelles, Ivo Gut, Salvador Capella-Gutierrez, Lincoln D Stein, Benedikt Brors, Romina Royo, Philippe Hupé, David Torrents
The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.
{"title":"ONCOLINER: A new solution for monitoring, improving, and harmonizing somatic variant calling across genomic oncology centers.","authors":"Rodrigo Martín, Nicolás Gaitán, Frédéric Jarlier, Lars Feuerbach, Henri de Soyres, Marc Arbonés, Tom Gutman, Montserrat Puiggròs, Alvaro Ferriz, Asier Gonzalez, Lucía Estelles, Ivo Gut, Salvador Capella-Gutierrez, Lincoln D Stein, Benedikt Brors, Romina Royo, Philippe Hupé, David Torrents","doi":"10.1016/j.xgen.2024.100639","DOIUrl":"10.1016/j.xgen.2024.100639","url":null,"abstract":"<p><p>The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142115578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1016/j.xgen.2024.100658
Paxton Kostos, Anna Galligos, Jennifer L Gerton
In this issue of Cell Genomics, Rothschild et al.1 reveal how ribosomal RNA diversity impacts ribosome structure and its implications for health and disease. Their innovative methodologies uncover distinct ribosome subtypes with significant structural variations and expression patterns. This work reveals connections to tissue-specific biology and cancer, positing new research avenues.
{"title":"Ribosomes unraveled: The path from variant to impact.","authors":"Paxton Kostos, Anna Galligos, Jennifer L Gerton","doi":"10.1016/j.xgen.2024.100658","DOIUrl":"10.1016/j.xgen.2024.100658","url":null,"abstract":"<p><p>In this issue of Cell Genomics, Rothschild et al.<sup>1</sup> reveal how ribosomal RNA diversity impacts ribosome structure and its implications for health and disease. Their innovative methodologies uncover distinct ribosome subtypes with significant structural variations and expression patterns. This work reveals connections to tissue-specific biology and cancer, positing new research avenues.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11Epub Date: 2024-08-30DOI: 10.1016/j.xgen.2024.100642
Hüseyin Tayran, Elanur Yilmaz, Prabesh Bhattarai, Yuhao Min, Xue Wang, Yiyi Ma, Ni Wang, Inyoung Jeong, Nastasia Nelson, Nada Kassara, Mehmet Ilyas Cosacak, Ruya Merve Dogru, Dolly Reyes-Dumeyer, Jakob Mørkved Stenersen, Joseph S Reddy, Min Qiao, Delaney Flaherty, Tamil Iniyan Gunasekaran, Zikun Yang, Nathalie Jurisch-Yaksi, Andrew F Teich, Takahisa Kanekiyo, Giuseppe Tosto, Badri N Vardarajan, Özkan İş, Nilüfer Ertekin-Taner, Richard Mayeux, Caghan Kizil
Genetic variants in ABCA7, an Alzheimer's disease (AD)-associated gene, elevate AD risk, yet its functional relevance to the etiology is unclear. We generated a CRISPR-Cas9-mediated abca7 knockout zebrafish to explore ABCA7's role in AD. Single-cell transcriptomics in heterozygous abca7+/- knockout combined with Aβ42 toxicity revealed that ABCA7 is crucial for neuropeptide Y (NPY), brain-derived neurotrophic factor (BDNF), and nerve growth factor receptor (NGFR) expressions, which are crucial for synaptic integrity, astroglial proliferation, and microglial prevalence. Impaired NPY induction decreased BDNF and synaptic density, which are rescuable with ectopic NPY. In induced pluripotent stem cell-derived human neurons exposed to Aβ42, ABCA7-/- suppresses NPY. Clinical data showed reduced NPY in AD correlated with elevated Braak stages, genetic variants in NPY associated with AD, and epigenetic changes in NPY, NGFR, and BDNF promoters linked to ABCA7 variants. Therefore, ABCA7-dependent NPY signaling via BDNF-NGFR maintains synaptic integrity, implicating its impairment in increased AD risk through reduced brain resilience.
{"title":"ABCA7-dependent induction of neuropeptide Y is required for synaptic resilience in Alzheimer's disease through BDNF/NGFR signaling.","authors":"Hüseyin Tayran, Elanur Yilmaz, Prabesh Bhattarai, Yuhao Min, Xue Wang, Yiyi Ma, Ni Wang, Inyoung Jeong, Nastasia Nelson, Nada Kassara, Mehmet Ilyas Cosacak, Ruya Merve Dogru, Dolly Reyes-Dumeyer, Jakob Mørkved Stenersen, Joseph S Reddy, Min Qiao, Delaney Flaherty, Tamil Iniyan Gunasekaran, Zikun Yang, Nathalie Jurisch-Yaksi, Andrew F Teich, Takahisa Kanekiyo, Giuseppe Tosto, Badri N Vardarajan, Özkan İş, Nilüfer Ertekin-Taner, Richard Mayeux, Caghan Kizil","doi":"10.1016/j.xgen.2024.100642","DOIUrl":"10.1016/j.xgen.2024.100642","url":null,"abstract":"<p><p>Genetic variants in ABCA7, an Alzheimer's disease (AD)-associated gene, elevate AD risk, yet its functional relevance to the etiology is unclear. We generated a CRISPR-Cas9-mediated abca7 knockout zebrafish to explore ABCA7's role in AD. Single-cell transcriptomics in heterozygous abca7<sup>+/-</sup> knockout combined with Aβ42 toxicity revealed that ABCA7 is crucial for neuropeptide Y (NPY), brain-derived neurotrophic factor (BDNF), and nerve growth factor receptor (NGFR) expressions, which are crucial for synaptic integrity, astroglial proliferation, and microglial prevalence. Impaired NPY induction decreased BDNF and synaptic density, which are rescuable with ectopic NPY. In induced pluripotent stem cell-derived human neurons exposed to Aβ42, ABCA7<sup>-/-</sup> suppresses NPY. Clinical data showed reduced NPY in AD correlated with elevated Braak stages, genetic variants in NPY associated with AD, and epigenetic changes in NPY, NGFR, and BDNF promoters linked to ABCA7 variants. Therefore, ABCA7-dependent NPY signaling via BDNF-NGFR maintains synaptic integrity, implicating its impairment in increased AD risk through reduced brain resilience.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480862/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142115575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}