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| 1 | Defined tumor antigen-specific T cells potentiate personalized TCR-T cell therapy and prediction of immunotherapy response显示文摘Personalized immunotherapy targeting tumor-specific antigens(TSAs)could generate efficient and safe antitumor immune response without damaging normal tissues.Although neoantigen vaccines have shown therapeutic effect in clinic trials,precise prediction of neoantigens from tumor mutations is still challenging.The host antitumor immune response selects and activates T cells recognizing tumor antigens.Hence,T cells engineered with T-cell receptors(TCRs)from these naturally occurring tumor antigen-specific T(Tas)cells in a patient will target personal TSAs in his/her tumor.To establish such a personalized TCR-T cell therapy,we comprehensively characterized T cells in tumor and its adjacent tissues by single-cell mRNA sequencing(scRNA-seq),TCR sequencing(TCR-seq)and in vitro neoantigen stimulation.Compared to bystander T cells circulating among tissues,Tas cells were characterized by tumor enrichment,tumor-specific clonal expansion and neoantigen specificity.We found that CXCL13 is a unique marker for both CD4^(+)and CD8^(+)Tas cells.Importantly,TCR-T cells expressing TCRs from Tas cells showed significant therapeutic effects on autologous patient-derived xenograft(PDX)tumors.Intratumoral Tas cell levels measured by CXCL13 expression precisely predicted the response to immune checkpoint blockade,indicating a critical role of Tas cells in the antitumor immunity.We further identified CD200 and ENTPD1 as surface markers for CD4^(^(+))and CD8^(^(+))Tas cells respectively,which enabled the isolation of Tas cells from tumor by Fluorescence Activating Cell Sorter(FACS)sorting.Overall,our results suggest that TCR-T cells engineered with Tas TCRs are a promising agent for personalized immunotherapy,and intratumoral Tas cell levels determine the response to immunotherapy. | Jingjing He Xinxin Xiong Han Yang Dandan Li Xuefei Liu Shuo Li Shuangye Liao Siyu Chen Xizhi Wen Kuai Yu Lingyi Fu Xingjun Dong Kaiyu Zhu Xiaojun Xia Tiebang Kang Chaochao Bian Xiang Li Haiping Liu Peirong Ding Xiaoshi Zhang Zhenjiang Liu Wende Li Zhixiang Zuo Penghui Zhou | 2022 | Cell Research2022，32，6： | 10 |
| 2 | Synthetic lethal short hairpin RNA screening reveals that ring finger protein 183 confers resistance to trametinib in colorectal cancer cells显示文摘Background: The mitogen-activated extracellular signal-regulated kinase 1/2(MEK1/2) inhibitor trametinib has shown promising therapeutic effects on melanoma, but its efficacy on colorectal cancer(CRC) is limited. Synthetic lethality arises with a combination of two or more separate gene mutations that causes cell death, whereas individual mutations keep cells alive. This study aimed to identify the genes responsible for resistance to trametinib in CRC cells,using a synthetic lethal short hairpin RNA(shRNA) screening approach.Methods: We infected HT29 cells with a pooled lentiviral shRNA library and applied next-generation sequencing to identify shRNAs with reduced abundance after 8-day treatment of 20 nmol/L trametinib. HCT116 and HT29 cells were used in validation studies. Stable ring finger protein 183(RNF183)-overexpressing cell lines were generated by pcDNA4-myc/his-RNF183 transfection. Stable RNF 183-knockdown cell lines were generated by infection of lentiviruses that express RNF183 shRNA, and small interference RNA(siRNA) was used to knock down RNF183 transiently.Quantitative real-time PCR was used to determine the mRNA expression. Western blotting, immunohistochemical analysis, and enzyme-linked immunosorbent assay(ELISA) were used to evaluate the protein abundance. MTT assay,colony formation assay, and subcutaneous xenograft tumor growth model were used to evaluate cell proliferation.Results: In the primary screening, we found that the abundance of RNF183 shRNA was markedly reduced after treatment with trametinib. Trametinib induced the expression of RNF183, which conferred resistance to drug-induced cell growth repression and apoptotic and non-apoptotic cell deaths. Moreover, interleukin-8(IL-8) was a downstream gene of RNF183 and was required for the function of RNF183 in facilitating cell growth. Additionally, elevated RNF183 expression partly reduced the inhibitory effect of trametinib on IL-8 expression. Finally, xenograft tumor model showed the synergism of RNF183 knockdown and trametinib in repressing the growth of CRC cells in vivo.Conclusion: The RNF183-IL-8 axis is responsible for the resistance of CRC cells to the MEK1/2 inhibitor trametinib and may serve as a candidate target for combined therapy for CRC. | Rong Geng Xin Tan Zhixiang Zuo Jiangxue Wu Zhizhong Pan Wei Shi Ranyi Liu Chen Yao Gaoyuan Wang Jiaxin Lin Lin Qiu Wenlin Huang Shuai Chen | 2017 | Chinese Journal of Cancer2017，36，12： | 2 |
| 3 | Dysregulated adaptive immune response contributes to severe COVID-19显示文摘Dear Editor,The outbreak of the new coronavirus 5ARS-CoV-2 has resulted in a global pandemic.Due to the lack of a specific drug against this virus,the current clinical management of this disease mainly depends on supportive care to reduce inflammatory responses and to keep the lung functioning1. | Kuai Yu Jingjing He Yongjian Wu Baosong Xie Xuefei Liu Bo Wei Haibo Zhou Bingliang Lin Zhixiang Zuo Wen Wen Wenxiong Xu Bin Zou Lai Wei Xi Huang Penghui Zhou | 2020 | Cell Research2020，30，9： | 1 |
| 4 | mi- Records: an integrated resource for microRNA-target interac- tions 显示文摘 | XIAO Feifei ZUO Zhixiang CAI Guoshuai | 2009 | Nucleic Acids Res2009，37，： | 1 |
| 5 | DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning显示文摘Protein nitration and nitrosylation are essential post-translational modifications(PTMs)involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are linked to numerous chronic diseases.Therefore, the identification of substrates that undergo such modifications in a site-specific manner is an important research topic in the community and will provide candidates for targeted therapy. In this study, we aimed to develop a computational tool for predicting nitration and nitrosylation sites in proteins. We first constructed four types of encoding features, including positional amino acid distributions, sequence contextual dependencies, physicochemical properties, and position-specificscoring features, to represent the modified residues. Based on these encoding features, we established a predictor called DeepNitro using deep learning methods for predicting protein nitration and nitrosylation. Using n-fold cross-validation, our evaluation shows great AUC values for DeepNitro, 0.65 for tyrosine nitration, 0.80 for tryptophan nitration, and 0.70 for cysteine nitrosylation, respectively,demonstrating the robustness and reliability of our tool. Also, when tested in the independent dataset, DeepNitro is substantially superior to other similar tools with a 7%à42% improvement in the prediction performance. Taken together, the application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites. DeepNitro is implemented in JAVA and PHP and is freely available for academic research at http://gffzz99614c6466484d9dhn0kvp6wnbnn96o6o.ffgz.tsg.suse.edu.cn. | Yubin Xie Xiaotong Luo Yupeng Li Li Chen Wenbin Ma Junjiu Huang Jun Cui Yong Zhao Yu Xue Zhixiang Zuo Jian Ren | 2018 | Genomics, Proteomics & Bioinformatics2018，16，4： | 1 |
| 6 | VSOLassoBag:a variable-selection oriented LASSO bagging algorithm for biomarker discovery in omic-based translational research显示文摘Screening biomolecular markers from high-dimensional biological data is one of the long-standing tasks for biomedical translational research.With its advantages in both feature shrinkage and biological interpretability,Least Absolute Shrinkage and Selection Operator(LASSO)algorithm is one of the most popular methods for the scenarios of clinical biomarker development.However,in practice,applying LASSO on omics-based data with high dimensions and low-sample size may usually result in an excess number of predictive variables,leading to the overfitting of the model.Here,we present VSOLassoBag,a wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient and stable variables with high confidence from omics-based data.Using a bagging strategy in combination with a parametric method or inflection point search method,VSOLassoBag can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates.The application of VSOLassoBag on both simulation datasets and real-world datasets shows that the algorithm can effectively identify markers for either case-control binary classification or prognosis prediction.In addition,by comparing with multiple existing algorithms,VSOLassoBag shows a comparable performance under different scenarios while resulting in fewer features than others.In summary,VSOLassoBag,which is available at http://gffzza891166c5c83403bsn0kvp6wnbnn96o6o.ffgz.tsg.suse.edu.cn/VSOLassoBag/under the GPL v3 license,provides an alternative strategy for selecting reliable biomarkers from high-dimensional omics data.For user’s convenience,we implement VSOLassoBag as an R package that provides multithreading computing configurations. | Jiaqi Liang Chaoye Wang Di Zhang Yubin Xie Yanru Zeng Tianqin Li Zhixiang Zuo Jian Ren Qi Zhao | 2023 | Journal of Genetics and Genomics2023，50，3： | 0 |
| 7 | Corrigendum to“Actin polymerization induces mitochondrial distribution during collective cell migration”[Journal of Genetics and Genomics(2023)50 46-49]显示文摘This erratum clarifies information in the Letter to the Editor“Actin polymerization induces mitochondrial distribution during collective cell migration”by Qu et al.(2023).In the section for the list of author names,“Chen Qu,Yating Kan,Hui Zuo,Mengqi Wu,Zhixiang Dong,Xinyi Wang,Qing Zhang,Heng Wang,Dou Wang,Jiong Chen”should be“Chen Qu,Yating Kan,Xinyi Wang,Hui Zuo,Mengqi Wu,Zhixiang Dong,Qing Zhang,Heng Wang,Dou Wang,Jiong Chen”. | Chen Qu Yating Kan Xinyi Wang Hui Zuo Mengqi Wu Zhixiang Dong Qing Zhang Heng Wang Dou Wang Jiong Chen | 2023 | Journal of Genetics and Genomics2023，50，3： | 0 |
| 8 | VirusMap:A visualization database for the influenza A virus显示文摘Influenza A virus,a highly virulent pathogen that has caused several pandemic events over the course of human history,still remains a major threat to human health at present.The most serious influenza pandemic in recorded history was the 1918 Spanish flu outbreak,which killed about 20-100 million people worldwide(Murray et al.,2006).Also,the H5N1 virus was known for its | Yubin Xie Xiaotong Luo Zhihao He Yueyuan Zheng Zhixiang Zuo Qi Zhao Yanyan Miao Jian Ren | 2017 | Journal of Genetics and Genomics2017，44，5： | 0 |
| 9 | Actin polymerization induces mitochondrial distribution during collective cell migration显示文摘Collective cell migration plays critical roles in various developmental,physiological,and pathological processes such as morphogenesis,wound healing,and tumor metastasis(Friedl and Gilmour,2009).During collective migration,each coherent group of associated cells needs to interpret external directional signal and convert it into a front-back asymmetry across a collective group(Rorth,2011).But the underlying mechanism for the establishment and maintenance of front-back asymmetry during collective migration is still not well understood. | Chen Qu Yating Kan Hui Zuo Mengqi Wu Zhixiang Dong Xinyi Wang Qing Zhang Heng Wang Dou Wang Jiong Chen | 2023 | Journal of Genetics and Genomics2023，50，1： | 0 |
| 10 | TIGER:A Web Portal of Tumor Immunotherapy Gene Expression Resource显示文摘Immunotherapy is a promising cancer treatment method;however,only a few patients benefit from it.The development of new immunotherapy strategies and effective biomarkers of response and resistance is urgently needed.Recently,high-throughput bulk and single-cell gene expression profling technologies have generated valuable resources.However,these resources are not well organized and systematic analysis is difficult.Here,we present TIGER,a tumor immunotherapy gene expression resource,which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes,as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples.TIGER provides many useful modules for analyzing collected and user-provided data.Using the resource in TIGER,we identified a tumor-enriched subset of CD4^(+)T cells.Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy.We believe that TIGER will be helpful in understanding anti-tumor immunity mechanisms and discovering effective biomarkers. | Zhihang Chen Ziwei Luo Di Zhang Huiqin Li Xuefei Liu Kaiyu Zhu Hongwan Zhang Zongping Wang Penghui Zhou Jian Ren An Zhao Zhixiang Zuo | 2023 | Genomics, Proteomics & Bioinformatics2023，21，2： | 0 |
| 11 | BioTreasury:a community-based repository enabling indexing and rating of bioinformatics tools显示文摘The exponential growth of bioinformatics tools in recent years has posed challenges for scientists in selecting the most suitable one for their data analysis assignments.Therefore,to aid scientists in making informed choices,a community-based platform that indexes and rates bioinformatics tools is urgently needed.In this study,we introduce Bio Treasury(http://gffzz793fa12de37c4e97hn0kvp6wnbnn96o6o.ffgz.tsg.suse.edu.cn),an integrated communitybased repository that provides an interactive platform for users and developers to share their experiences in various bioinformatics tools.Bio Treasury offers a comprehensive collection of well-indexed bioinformatics software,tools,and databases,totaling over 10,000 entries.In the past two years,we have continuously improved and maintained Bio Treasury,adding several exciting features,including creating structured homepages for every tool and user,a hierarchical category of bioinformatics tools and classifying tools using large language model(LLM).Bio Treasury streamlines the tool submission process with intelligent auto-completion.Additionally,Bio Treasury provides a wide range of social features,for example,enabling users to participate in interactive discussions,rate tools,build and share tool collections for the public.We believe Bio Treasury can be a valuable resource and knowledge-sharing platform for the biomedical community.It empowers researchers to effectively discover and evaluate bioinformatics tools,fostering collaboration and advancing bioinformatics research. | Qi Zhao Xin Zhou Jingxing Wu Jieyi Cai Xiaoqiong Bao Lin Tang Chaoye Wang Chunlei Liu Yukai Wang Yuyan Teng Mohan Zheng Weiping Mu Zhixiang Zuo Yubin Xie Xiaotong Luo Jian Ren | 2024 | Science China(Life Sciences)2024，67，2： | 0 |
| 12 | LncPipe" A Nextflow-based pipeline for identification and analysis of long non-coding RNAs from RNA-Seq data显示文摘Long noncoding RNAs(lncRNAs)have been increasingly implicated in a variety of human diseases,including autoimmune disease(Wu et al.,2015),neurodegenerative diseases(Wapinski and Chang,2011)and cancer(Huarte,2015).Due to recent advances in next-generation sequencing technologies,tens of thousands of lnc RNAs have been identified and annotated,a number of | Qi Zhao Yu Sun Dawei Wang Hongwan Zhang Kai Yu Jian Zheng Zhixiang Zuo | 2018 | Journal of Genetics and Genomics2018，45，7： | 0 |
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