Luonan Chen
China
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Articles by Luonan Chen
Explainable data generation from observed small samples by matrix tri-factorization
Abstract Data generation on small samples has exhibited great potential on real-world biomedical scenarios, especially on extreme cases such as early-stage or emerging biomedical conditions (e.g. Patient Zero of a brand-new disease with only one sample) because of insufficient sample information.
UniCure: A multi-modal model for predicting personalized cancer therapy response
Keywords UniCure multi-modal model personalized cancer therapy drug prioritization foundation model Get full text access Log in, subscribe or purchase for full access. References 1. Lamb, J. ∙ Crawford, E.D. ∙ Peck, D. ... The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease Science. 2006; 313:1929-1935 2. Subramanian, A. ∙ Narayan, R. ∙ Corsello, S.M. ... A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles Cell.
Microenvironment-aware transcriptome reconstruction in spatial transcriptomics
Abstract Imaging-based spatial transcriptomics provides single-cell resolution, but remains limited to targeted gene panels, leaving much of the transcriptome and cellular-state variation unobserved. Existing approaches infer unmeasured genes primarily through transcriptional alignment between spatial and reference datasets, which effectively recover broad cell identities, but may not fully capture context-dependent variation within cell types.
AI proteomics: from protein identification to virtual cells
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Abstract Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells.
By Yingying Sun, Zhiwei Liu, Rui Sun, Liujia Qian, Samuel Payne, Wout Bittremieux, Markus Ralser, Chen Li, Yi Chen, Zhen Dong, Yasset Perez-Riverol, Asif Khan, Chris Sander, Ruedi Aebersold, Juan Antonio Vizcaino, Jonathan Krieger, Jianhua Yao, Linfeng Zhang, Yunping Zhu, Yue Xuan, Liang Qiao, Henning Hermjakob, Haixu Tang, Huanhuan Gao, Yamin Deng, Qing Zhong, Cheng Chang, Nuno Bandeira, Ming Li, Siqi Sun, Yuedong Yang, Gilbert S. Omenn, Yue Zhang, Ping Xu, Xiaowen Liu, Christopher M. Overall, Yu Wang, Eric Deutsch, Luonan Chen, Jürgen Cox, Vadim Demichev, Fuchu He, Jiaxing Huang, Huilin Jin, Chao Liu, Nan Li, Zhongzhi Luan, Jiangning Song, Kaicheng Yu, Wanggen Wan, Tai Wang, Kang Zhang, Le Peng Zhang, Peter Bell, Matthias Mann, Bing Zhang, Tiannan Guo, Benjamin Boyang Sun
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Nature
Verified
Identifying critical period of type 2 diabetes in Chinese population with leading molecules based on dynamic network biomarkers
Abstract Diabetes has become a significant global public health challenge, and prediabetes (preD), as the earliest detectable stage of glucose metabolism disorder, constitutes a critical window for disease intervention. Currently, China has not established diagnostic criteria for HbA1c in preD, and there is limited understanding of the molecular mechanisms at the critical transition points during disease progression.
Towards the construction of a virtual yeast
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Abstract To advance the computational simulation of cellular life, we propose a virtual yeast, an artificial intelligence (AI)-driven agent that models eukaryotic cellular behaviours by integrating multimodal biological data, mechanistic reasoning and active experimentation using Saccharomyces cerevisiae as a genetically tractable and data-rich model system.
By Liujia Qian, Zizhuo Zhou, Peijie Zhou, Zhen Dong, Xudong Zhang, Zhangyang Gao, Siqi Sun, Kevin Roy, Shuaiyao Wang, Nicola Zamboni, Charles Boone, Michael Costanzo, Jianzhe Li, Gianni Liti, Jia-Xing Yue, Markus Ralser, Evan Williams, Mattia Zampieri, Heng Jiang, Tailin Wu, Yalin Wang, Feiran Li, Joseph Schacherer, Rui Sun, Zhaoxing Li, Yaming Deng, Yi Chen, Zhiping Xie, Huiqiang Lou, Xiaowen Wang, Linhai Xie, Liangyi Chen, Kai Lei, George Rosenberger, Xue Cai, Yingrui Wang, Qi Xiao, Huaizong Shen, Gaowen Liu, Lei Ma, Brenda Andrews, HUI LU, Kiryl D. Piatkevich, Yi Zhu, Lei Bai, Yizhi Cai, Yuping Chen, Ge Gao, Fuchu He, Luonan Chen, Stan Z Li, Hongwu Ma, Liang Qiao, Lars M. Steinmetz, Tang K. Tang, Xiaofan Zhang, JING YANG, Yifan Yang, Kaicheng Yu, Jianyang Zeng, Yefeng Zheng, Bowen Zhou, Tiannan Guo, Zhenwu Dai, Leihan Tang
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Nature
Verified
Efficient preservation of old methane-derived organic carbon in deep-sea surface sediments
Abstract Methane released from the subseafloor is significantly attenuated during upward migration, yet the preservation of methane-derived organic carbon (OC) in global deep-sea sediments remains poorly understood. Here, we measured carbon isotopes coupled with temperature-ramped analyses on various methane seepage sediments. Our results reveal a correlation between the radiocarbon (14C) content in deep-sea surface sediments and sulfate-methane transition depth.
stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi-Omics
1 Introduction The widespread application of single-cell and spatial omics technologies has led to the accumulation of vast datasets across diverse tissues, capturing gene expression, chromatin accessibility, and protein profiles in spatially resolved contexts [1-4].
Hallmarks of the pre-disease state: prevention and control of the pre-disease state, a tipping point between health and disease - Cell Discovery
Complex diseases, including cancers, diabetes, and other chronic diseases, are not caused by individual genes or factors. Instead, they arise from dynamic interactions among multiple genetic, environmental, and lifestyle factors. Disease pathogenesis is a prolonged, dynamically evolving process, not a simple binary switch between health and disease.
CLIM-TIME identifies metastatic microenvironment modulators for T cell therapy response
Keywords spatial CRISPR metastasis tumor microenvironment T cell therapy Hippo pathway T cell infiltration extracellular matrix LOXL2 tumor suppressor gene immunotherapy Get full text access Log in, subscribe or purchase for full access. References 1. June, C.H. ∙ O’Connor, R.S. ∙ Kawalekar, O.U. ... CAR T cell immunotherapy for human cancer Science. 2018; 359:1361-1365 2. Ghorashian, S. ∙ Kramer, A.M. ∙ Onuoha, S. ...
Analysis of the transcriptomic and metabolomic landscape of prostate cancer with different anatomical origins using snFLARE-seq and mxFRIZNGRND - Nature Communications
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Abstract Prostate cancer cells of different anatomical locations display remarkable heterogeneity. This poses a challenge to the clinical relevance of pre-clinical models and the efficacy of contemporary therapeutic approaches. Here we develop the snFLARE-seq and mxFRIZNGRND methodologies to directly investigate the transcriptomic and metabolomic landscape of prostate cancer patients utilizing formalin-fixed paraffin-embedded (FFPE) specimens.
By Dongyin He, Haoran Hu, Kai Xiao, Yuhang Zhang, Yongbing Cheng, Shaozhuo Jiao, Yimei Hao, Yuanyuan Cai, Ziqun Liu, Xinran Yan, Qinsheng Chen, Xiyan Mu, Qi Wang, Shan Peng, Xiaoling Zhi, Qing Ye, Yuyao Yang, Meixia Che, Shengsong Huang, Hongqian Guo, Luonan Chen, Huiru Tang, Xuefeng Qiu, Guoqin Sang, Yanxia Chang
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Nature
Verified
Concurrent PIK3CA mutant promotes cachexia through inflammatory signaling in EGFR mutant lung cancer - Nature Communications
Abstract PIK3CA mutation is frequently concurrent with known oncogenic drivers such as EGFR mutation in lung cancer, raising an interesting question about its real function. Cachexia is a systemic disease arising from tumor-organ crosstalk, significantly contributing to cancer-related mortality.
Interindividual variability in gut microbiome mediates the efficacy of resistant starch on MASLD
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Keywords metabolic dysfunction-associated steatotic liver disease gut microbiota resistant starch treatment effect heterogeneity prebiotics precision medicine multi-omics Bifidobacterium pseudocatenulatum Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD), previously recognized as non-alcoholic fatty liver disease (NAFLD), is gaining increasing attention as a global health crisis.1 It encompasses a spectrum ranging from simple steatosis to metabolic...
By Xiaoxue Long, Hui Wang, Yuwei Lu, Xiaojing J. Gao, Yuanyuan Xiao, Mingliang Zhang, Jingyi Guo, Jingyi Yang, Qian Li, Guiyun Zhou, Ruibao Yang, Feng Chen, Qingqing Wu, Liming Sun, Chengshuang Chu, Xuexue Zhu, Zhengjun Wu, Quanlu Ren, Chunping You, Zhenmin Liu, Dan Liu, Di Cheng, Anran Chen, Qian Wu, Li Wei, Lei Zhang, Jun Li, Gianni Panagiotou, Weiping Jia, Rong Zeng, Yueqiong Ni, Luonan Chen, Huating Li, Piao Kang, Qichen Fang
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Cell Metabolism
Verified
Delayformer: Spatiotemporal Transformation for Predicting High‐Dimensional Dynamics
1 Introduction Time-series data, which comprises sequences of values or observations obtained over successive periods, is ubiquitous across diverse domains, such as meteorology (temperature,[1] precipitation,[2] typhoon movement[3]), finance (stock prices,[4] economic indicators[5]), healthcare (heart rate,[6] patient monitoring[7]), epidemic outbreak prediction,[8] and industry (instrument detection,[9] electricity allocation[10]).
Cellular and molecular mechanisms of seahorse male pregnancy
Abstract Seahorses and their relatives (syngnathids) show a unique sex role reversal. Their male pregnancy is facilitated by an evolutionary novel organ—the brood pouch that functions analogously to the mammalian uterus and placenta despite originating from entirely different tissues.
Unveiling potential threats: backdoor attacks in single-cell pre-trained models - Cell Discovery
Dear Editor, The advancement of single-cell sequencing technology has empowered fields such as developmental biology, immunology, and oncology, underscoring its significance in revealing individual cell characteristics in health and disease. Many computational methods and workflows have been specifically designed for single-cell data analysis to accurately characterize cellular heterogeneity1.
Multi-omics with dynamic network biomarker algorithm prefigures organ-specific metastasis of lung adenocarcinoma - Nature Communications
Abstract Efficacious strategies for early detection of lung cancer metastasis are of significance for improving the survival of lung cancer patients.
JAK/STAT signaling maintains an intermediate cell population during prostate basal cell fate determination - Nature Genetics
Abstract Unipotent basal and luminal stem cells maintain prostate homeostasis, with an intermediate cell population emerging during prostate inflammation or cancer. However, the identities of basal stem cell and intermediate cell population remain unclear. Here we identified a rare intermediate cell population expressing luminal markers (termed Basal-B) with enhanced organoid formation capacity, and a larger basal population (termed Basal-A).
Reconstructing Molecular Networks by Causal Diffusion Do‐Calculus Analysis with Deep Learning
1 Introduction Understanding cause-and-effect relationships is crucial to elucidate the molecular mechanisms of biological processes at a network level.
DNFE: Directed-network flow entropy for detecting the tipping points during biological processes
Abstract There generally exists a critical state or tipping point from a stable state to another in dynamic biological processes, beyond which a significant qualitative transition occurs. Identifying this tipping point and its driving network is essential to prevent or delay catastrophic consequences.
Publisher Correction: Sex differences orchestrated by androgens at single-cell resolution - Nature
Correction to: Nature https://doi.org/10.1038/s41586-024-07291-6 Published online 10 April 2024 In the version of the article initially published, in Fig. 1c, the label now reading “MC vs MS” originally read “MC vs FS”. In Extended Data Fig. 2c, the labels now reading “Male-Sham” and “Male-Castration” read “Female-Sham” and “Female-DHT”, respectively. These errors have now been corrected in the HTML and PDF versions of the article. About this article Li, F., Xing, X., Jin, Q. et al.
Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning - Nature Communications
Abstract Spatially resolved transcriptomics (SRT) has enabled precise dissection of tumor-microenvironment (TME) by analyzing its intracellular molecular networks and intercellular cell-cell communication (CCC). However, lacking computational exploration of complicated relations between cells, genes, and histological regions, severely limits the ability to interpret the complex structure of TME.
Sex differences orchestrated by androgens at single-cell resolution - Nature
Abstract Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1,2,3,4,5,6,7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations.
Multi-modal molecular determinants of clinically relevant osteoporosis subtypes - Cell Discovery
Abstract Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy.
A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia - Nature Communications
Abstract Achalasia is a rare motility disorder of the esophagus caused by the gradual degeneration of myenteric neurons. Immune-mediated ganglionitis has been proposed to underlie the loss of myenteric neurons. Here, we measure the immune cell transcriptional profile of paired lower esophageal sphincter (LES) tissue and blood samples in achalasia and controls using single-cell RNA sequencing (scRNA-seq).
Cell-type annotation with accurate unseen cell-type identification using multiple references
Loading metrics Open Access Peer-reviewed Research Article ? This is an uncorrected proof. Abstract The recent advances in single-cell RNA sequencing (scRNA-seq) techniques have stimulated efforts to identify and characterize the cellular composition of complex tissues. With the advent of various sequencing techniques, automated cell-type annotation using a well-annotated scRNA-seq reference becomes popular.
Human endoderm stem cells reverse inflammation-related acute liver failure through cystatin SN-mediated inhibition of interferon signaling - Cell Research
Abstract Acute liver failure (ALF) is a life-threatening disease that occurs secondary to drug toxicity, infection or a devastating immune response. Orthotopic liver transplantation is an effective treatment but limited by the shortage of donor organs, the requirement for life-long immune suppression and surgical challenges. Stem cell transplantation is a promising alternative therapy for fulminant liver failure owing to the immunomodulatory abilities of stem cells.
STAMarker: Determining spatial domain-specific variable genes with saliency maps in deep learning
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Therapeutic targeting of the mevalonate–geranylgeranyl diphosphate pathway with statins overcomes chemotherapy resistance in small cell lung cancer - Nature Cancer
Abstract Small cell lung cancer (SCLC) lacks effective treatments to overcome chemoresistance. Here we established multiple human chemoresistant xenograft models through long-term intermittent chemotherapy, mimicking clinically relevant therapeutic settings. We show that chemoresistant SCLC undergoes metabolic reprogramming relying on the mevalonate (MVA)–geranylgeranyl diphosphate (GGPP) pathway, which can be targeted using clinically approved statins.
Single-cell transcriptomics identifies a distinct luminal progenitor cell type in distal prostate invagination tips
Abstract The identification of prostate stem/progenitor cells and characterization of the prostate epithelial cell lineage hierarchy are critical for understanding prostate cancer initiation. Here, we characterized 35,129 cells from mouse prostates, and identified a unique luminal cell type (termed type C luminal cell (Luminal-C)) marked by Tacstd2, Ck4 and Psca expression.
Personalized prediction of human diseases with single-sample dynamic network biomarkers
*Author for correspondence: E-mail Address: lnchen@sibs.ac.cn Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry & Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China CAS Center for Excellence in Animal Evolution & Genetics, Chinese Academy of Sciences, Kunming 650223, China School of Life Science & Technology, Shanghai Tech...
The effects of graded levels of calorie restriction: VI. Impact of short-term graded calorie restriction on transcriptomic responses of the hypothalamic hunger and circadian signaling pathways
1. Mercken EM, Crosby SD, Lamming DW, Jebailey L, Krzysik-Walker S, Villareal DT, Capri M, Franceschi C, Zhang Y, Becker K, Sabatini DM, de Cabo R, Fontana L. Calorie restriction in humans inhibits the PI3K/AKT pathway and induces a younger transcription profile. Aging Cell. 2013;12:645–651. [PMC free article] [PubMed] [Google Scholar] 2. Fontana L, Meyer TE, Klein S, Holloszy JO. Long-term calorie restriction is highly effective in reducing the risk for atherosclerosis in humans.
Integrating data- and model-driven strategies in systems biology
The 11th International Conference on Computational Systems Biology (ISB 2017), co-organized by Southern University of Science and Technology (SUSTech), Computational Systems Biology Society of ORSC and Systems Biology Division of CSBMB was held in Shenzhen, China, August 18–21, 2017.
Identifying joint biomarker panel from multiple level dataset by an optimization model
Aim: Joint biomarker panel takes advantage of coherence across multiple level datasets and holds the promise to improve disease diagnosis accuracy. Methods: We collected 101 colorectal cancer and 95 benign samples, measured the molecular concentrations by serum assays and mass spectra, and developed LPGLO (Linear Programming based on Group Lasso Optimization) to identify the joint biomarker panel.
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