Genomics, proteomics & bioinformatics最新文献_第4页

Toward A Pre-disease State-centered New Paradigm in Multi-omics Research. 迈向以疾病前期状态为中心的多组学研究新范式。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-14 DOI: 10.1093/gpbjnl/qzag016

Cheng Lu 陆铖, Yan Li 李艳, Quansheng Du 杜全生

引用次数: 0

The 2025 Westlake Autumn Symposium for AI Proteomics and Virtual Cell. 2025西湖秋季人工蛋白质组学与虚拟细胞学术研讨会。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-14 DOI: 10.1093/gpbjnl/qzag022

Rui Sun 孙瑞, Ruedi Aebersold, Qi Xiao 肖琦, Matthias Mann, Yan Zhou 周岩, Albert J R Heck, Yingrui Wang 王瑛睿, Uwe Völker, Xue Cai 蔡雪, Charles Boone, Zizhuo Zhou 周梓卓, Ming Li 李明, Zhen Dong 董振, Brenda Andrews, Shuaiyao Wang 王帅尧, Joseph Schacherer, Connie R Jimenez, Bernd Wollscheid, Liang Yue 岳靓, Ben C Collins, Heng Jiang 蒋恒, Dong Wang 王栋, Liujia Qian 钱鎏佳, Jia-Xing Yue 岳家兴, Yingying Sun 孙莹莹, Edouard Nice, Xiaofan Zhang 张晓帆, Yasset Perez-Riverol, Jun A 阿俊, Chris Sander, Henning Hermjakob, Wout Bittremieux, Wilson Wen Bin Goh, Ge Gao 高歌, Peijie Zhou 周沛劼, Siqi Sun 孙思琦, Han Wen 温翰, Ziyan Xu 许梓妍, Tiannan Guo 郭天南

引用次数: 0

Unraveling Cell of Origin in Breast Cancer via Joint Profiling of Whole Genome and Transcriptome in Individual Cells. 通过单个细胞的全基因组和转录组联合分析揭示乳腺癌细胞起源。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-14 DOI: 10.1093/gpbjnl/qzag021

Yueying He, Ruli Gao

引用次数: 0

Discovery and Validation of Non-canonical Antigens for Hepatocellular Carcinoma Immunotherapy. 肝癌免疫治疗非典型抗原的发现和验证。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-13 DOI: 10.1093/gpbjnl/qzag082

Stephen Li, Yujuan Dong, Jiaxun Liu, Shanglin Li, Dandan Pu, Yue Guo, Chun Kwok Wong, Nathalie Wong, Jason Wing Hon Wong

{"title":"Discovery and Validation of Non-canonical Antigens for Hepatocellular Carcinoma Immunotherapy.","authors":"Stephen Li, Yujuan Dong, Jiaxun Liu, Shanglin Li, Dandan Pu, Yue Guo, Chun Kwok Wong, Nathalie Wong, Jason Wing Hon Wong","doi":"10.1093/gpbjnl/qzag082","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag082","url":null,"abstract":"Hepatocellular carcinoma (HCC) is a highly prevalent and lethal form of liver cancer marked by high rates of tumor recurrence, posing substantial challenges to primary treatment options such as surgical resection and liver transplantation. Immunotherapy, which leverages T-cell-mediated recognition of tumor-specific antigens, has emerged as a promising alternative therapeutic strategy. While proteogenomics and ribosome profiling data across cancer types have provided growing evidence of active translation in non-canonical open reading frames (ncORFs), antigens derived from HCC-associated ncORFs remain largely unexplored. By integrating long-read and short-read RNA sequencing data with mass spectrometry, we have successfully identified twelve non-canonical peptides arising from cryptic translation of ncORFs. Enzyme-linked immunosorbent spot (ELISpot) assays confirmed cytokine release triggered by non-canonical peptides originating from distinct genomic loci. Subsequent RNA level analysis revealed four peptides with strong evidence of enriched expression in tumorigenesis. In-depth bioinformatics predictions indicate that these four peptides possess significant binding affinity for Major Histocompatibility Complex and T-Cell Receptor, with p2 emerging as the most promising candidate. Analysis using public datasets and experimental validation further highlighted the role of ribosome subunit recruitment and N6-Methyladenosine (m6A) modifications in enhancing translation initiation for tumor-enriched antigens. By addressing the existing shortage of knowledge in the HCC ncORF translation, this study identifies promising antigenic candidates for HCC immunotherapy, offering new avenues for effective treatment strategies and improved patient outcomes.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148763759","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}

引用次数: 0

The Silicon Microbial Community. 硅微生物群落。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-12 DOI: 10.1093/gpbjnl/qzag081

Yuli Zhang, Kang Ning

引用次数: 0

Genetic Predisposition and Pharmacological Effects Shape the Divergent Effects of Type 2 Diabetes on Atherosclerosis. 遗传易感性和药理作用形成2型糖尿病对动脉粥样硬化的不同影响。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-08 DOI: 10.1093/gpbjnl/qzag079

Shufen Zheng, Yonglin Wu, Aijie Li, Zhuoyi Wu, Zhen Liu, Huawei Wang, Xiaoyan Jia, Philip S Tsao, Cuiping Pan

{"title":"Genetic Predisposition and Pharmacological Effects Shape the Divergent Effects of Type 2 Diabetes on Atherosclerosis.","authors":"Shufen Zheng, Yonglin Wu, Aijie Li, Zhuoyi Wu, Zhen Liu, Huawei Wang, Xiaoyan Jia, Philip S Tsao, Cuiping Pan","doi":"10.1093/gpbjnl/qzag079","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag079","url":null,"abstract":"Type 2 diabetes mellitus (T2D) increases the risk of atherosclerotic diseases, including coronary artery disease (CAD), but decreases that for abdominal aortic aneurysm (AAA), forming an intriguing diabetes-atherosclerosis paradox. We investigate how genetic underpinnings and drug effects shape these complex relationships. A robust positive correlation between T2D and CAD is found throughout the genome, whereas the weak genetic correlation between T2D and AAA is counter-balanced by two-thirds positive and one-third negative correlations. Through single nucleotide variant colocalization, gene annotation, pathway enrichment, and cell type associations, we discover that these positive correlations entail immune responses, whereas the negative correlation is characterized by beta-cell dysfunction and lipid metabolism. Furthermore, the effects of 98 canonical cardiovascular and metabolic drugs are elucidated by pathway pairing and drug-target Mendelian Randomization, revealing that the widely prescribed metformin and glitazones are also protective against atherosclerosis, whereas statins raise the T2D risk. Through screening the plasma proteome against 660 anti-inflammatory drugs, we identify 14 targets and 8 drugs for anti-inflammatory treatments of T2D and atherosclerosis. Our study discovers that both disease-disease and drug-disease interplay contribute to the complex relationships between diabetes and atherosclerosis. Importantly, immune responses synergize with diabetes and atherosclerotic diseases, suggesting anti-inflammatory therapies as a unified treatment strategy.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698667","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}

引用次数: 0

Immuno-oncology: Decoding Tumor-immune Ecosystems with Multi-omics and Artificial Intelligence for Precision Therapeutics. 免疫肿瘤学：用多组学和精确治疗的人工智能解码肿瘤免疫生态系统。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-08-04 DOI: 10.1093/gpbjnl/qzag078

Youqiong Ye, An-Yuan Guo, Song Liu, Yi Xing

引用次数: 0

Bispecific Antibodies in Cancer Immunotherapy: Mechanisms, Challenges, and Emerging Therapeutic Strategies. 癌症免疫治疗中的双特异性抗体：机制、挑战和新兴治疗策略。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-07-31 DOI: 10.1093/gpbjnl/qzag075

Yao Wu, Mingjie Liao, Han Chen, Yingchun Ye, Xiyuan Guo, Lin Li, Qin Liu, Xiaomei Xu, Siji Nian, Qing Yuan

{"title":"Bispecific Antibodies in Cancer Immunotherapy: Mechanisms, Challenges, and Emerging Therapeutic Strategies.","authors":"Yao Wu, Mingjie Liao, Han Chen, Yingchun Ye, Xiyuan Guo, Lin Li, Qin Liu, Xiaomei Xu, Siji Nian, Qing Yuan","doi":"10.1093/gpbjnl/qzag075","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag075","url":null,"abstract":"Bispecific antibodies (BsAbs) have emerged as a promising therapeutic strategy in cancer immunotherapy, enabling simultaneous targeting of two distinct antigens to redirect immune effector cells, block compensatory pathways, and modulate the tumor immune microenvironment (TIME). Hundreds of BsAbs are currently in clinical trials, among which immune cell engagers (ICEs) demonstrate substantial therapeutic potential by bridging tumor cells and effector cells to enhance cytotoxic activity. However, the clinical translation of BsAbs is hampered by heterogeneous therapeutic responses, immune-related adverse events (irAEs), drug resistance, and inherent immunogenicity. In this review, we systematically dissect the applications of BsAbs in tumor immunotherapy, focusing on rational target combinations, underlying immunological mechanisms, and clinical therapeutic potential, while critically evaluating the advantages and limitations of representative BsAb modalities. We aim to address a key unresolved question: why some BsAb regimens achieve durable clinical efficacy (e.g., blinatumomab in hematological malignancies), whereas others show limited activity in solid tumors (e.g., vanucizumab). Through comparative mechanistic analysis, we clarify the critical trade-offs among therapeutic efficacy, systemic toxicity, and immunosuppressive barriers within the tumor microenvironment. To mitigate these translational bottlenecks, we summarize cutting-edge engineering approaches-including trispecific antibodies, prodrug-conjugated BsAbs, and proteolysis-targeting chimeras (PROTACs) - that optimize the balance between anti-tumor potency and off-target toxicity. This review provides a conceptual framework for advancing the translational development of BsAbs and guiding the rational design of next-generation precision cancer immunotherapies.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148649956","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}

引用次数: 0

Shared Genetic Factors Between Stress-related Disorders and Cardiovascular Disease. 压力相关疾病和心血管疾病之间的共同遗传因素。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-07-31 DOI: 10.1093/gpbjnl/qzag077

Can Hou, Yu Zeng, Huazhen Yang, Haowen Liu, Wenwen Chen, Xin Han, Henrik Larsson, Brian M D'Onofrio, Paul Lichtenstein, Chen Suo, Fang Fang, Unnur A Valdimarsdóttir, Huan Song

{"title":"Shared Genetic Factors Between Stress-related Disorders and Cardiovascular Disease.","authors":"Can Hou, Yu Zeng, Huazhen Yang, Haowen Liu, Wenwen Chen, Xin Han, Henrik Larsson, Brian M D'Onofrio, Paul Lichtenstein, Chen Suo, Fang Fang, Unnur A Valdimarsdóttir, Huan Song","doi":"10.1093/gpbjnl/qzag077","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzag077","url":null,"abstract":"Understanding whether and how shared genetic factors contribute to the comorbidity between stress-related disorders (SRDs) and cardiovascular disease (CVD) is important for integrated prevention and treatment, but current evidence remains limited. To address this gap, we integrated Swedish national registers (n = 4,123,631), UK Biobank (n = 502,291), and genome-wide association study summary statistics to explore shared genetic liability between SRDs and six CVD subtypes and to nominate pleiotropic loci, genes, and enriched pathways. Familial coaggregation analyses showed that the SRDs-CVD association attenuated with decreasing genetic relatedness among relatives, supporting the existence of shared genetic influences. Polygenic risk scores for SRDs significantly predicted a higher risk of any CVD and all subtypes (odds ratios = 1.05-1.09), and all SRDs-CVD pairs showed positive genetic correlations (rg = 0.09-0.35), whereas Mendelian randomization (MR) analyses did not support strong causal effects in either direction. Genome-wide cross-trait analyses identified 17 putative pleiotropic loci, and consensus-based gene mapping prioritized 16 putative pleiotropic genes. Enrichment analyses indicated that pleiotropic signals were enriched in processes related to hemostasis and coagulation, circulatory system development, and telomere maintenance. In validation analyses focusing on post-traumatic stress disorder (PTSD), we observed a similar pattern of genetic overlap with CVD and replicated a subset of loci, genes, and pathways. These findings support a genetic comorbidity framework in which shared genetic liability, largely driven by pleiotropic loci, contributes to the co-occurrence of SRDs and CVD and highlight candidate genes and biological processes for future experimental studies.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148650148","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}

引用次数: 0

COACH-D 2.0: A Server for Template-based Modeling of Protein-ligand Interactions. COACH-D 2.0：基于模板的蛋白质-配体相互作用建模服务器。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2026-07-30 DOI: 10.1093/gpbjnl/qzag076

Xiaoyu An, Hong Wei, Wenkai Wang, Qiuyi Lyu, Jianyi Yang, Zhenling Peng

引用次数: 0