Stanford Advisors

Lab Affiliations

All Publications

  • Intestinal toxicity to CTLA-4 blockade driven by IL-6 and myeloid infiltration. The Journal of experimental medicine Zhou, Y., Medik, Y. B., Patel, B., Zamler, D. B., Chen, S., Chapman, T., Schneider, S., Park, E. M., Babcock, R. L., Chrisikos, T. T., Kahn, L. M., Dyevoich, A. M., Pineda, J. E., Wong, M. C., Mishra, A. K., Cass, S. H., Cogdill, A. P., Johnson, D. H., Johnson, S. B., Wani, K., Ledesma, D. A., Hudgens, C. W., Wang, J., Wadud Khan, M. A., Peterson, C. B., Joon, A. Y., Peng, W., Li, H. S., Arora, R., Tang, X., Raso, M. G., Zhang, X., Foo, W. C., Tetzlaff, M. T., Diehl, G. E., Clise-Dwyer, K., Whitley, E. M., Gubin, M. M., Allison, J. P., Hwu, P., Ajami, N. J., Diab, A., Wargo, J. A., Watowich, S. S. 2023; 220 (2)


    Immune checkpoint blockade (ICB) has revolutionized cancer treatment, yet quality of life and continuation of therapy can be constrained by immune-related adverse events (irAEs). Limited understanding of irAE mechanisms hampers development of approaches to mitigate their damage. To address this, we examined whether mice gained sensitivity to anti-CTLA-4 (alphaCTLA-4)-mediated toxicity upon disruption of gut homeostatic immunity. We found alphaCTLA-4 drove increased inflammation and colonic tissue damage in mice with genetic predisposition to intestinal inflammation, acute gastrointestinal infection, transplantation with a dysbiotic fecal microbiome, or dextran sodium sulfate administration. We identified an immune signature of alphaCTLA-4-mediated irAEs, including colonic neutrophil accumulation and systemic interleukin-6 (IL-6) release. IL-6 blockade combined with antibiotic treatment reduced intestinal damage and improved alphaCTLA-4 therapeutic efficacy in inflammation-prone mice. Intestinal immune signatures were validated in biopsies from patients with ICB colitis. Our work provides new preclinical models of alphaCTLA-4 intestinal irAEs, mechanistic insights into irAE development, and potential approaches to enhance ICB efficacy while mitigating irAEs.

    View details for DOI 10.1084/jem.20221333

    View details for PubMedID 36367776

  • ITHscore: comprehensive quantification of intra-tumor heterogeneity in NSCLC by multi-scale radiomic features. European radiology Li, J., Qiu, Z., Zhang, C., Chen, S., Wang, M., Meng, Q., Lu, H., Wei, L., Lv, H., Zhong, W., Zhang, X. 2023; 33 (2): 893-903


    To quantify intra-tumor heterogeneity (ITH) in non-small cell lung cancer (NSCLC) from computed tomography (CT) images.We developed a quantitative ITH measurement-ITHscore-by integrating local radiomic features and global pixel distribution patterns. The associations of ITHscore with tumor phenotypes, genotypes, and patient's prognosis were examined on six patient cohorts (n = 1399) to validate its effectiveness in characterizing ITH.For stage I NSCLC, ITHscore was consistent with tumor progression from stage IA1 to IA3 (p < 0.001) and captured key pathological change in terms of malignancy (p < 0.001). ITHscore distinguished the presence of lymphovascular invasion (p = 0.003) and pleural invasion (p = 0.001) in tumors. ITHscore also separated patient groups with different overall survival (p = 0.004) and disease-free survival conditions (p = 0.005). Radiogenomic analysis showed that the level of ITHscore in stage I and stage II NSCLC is correlated with heterogeneity-related pathways. In addition, ITHscore was proved to be a stable measurement and can be applied to ITH quantification in head-and-neck cancer (HNC).ITH in NSCLC can be quantified from CT images by ITHscore, which is an indicator for tumor phenotypes and patient's prognosis.• ITHscore provides a radiomic quantification of intra-tumor heterogeneity in NSCLC. • ITHscore is an indicator for tumor phenotypes and patient's prognosis. • ITHscore has the potential to be generalized to other cancer types such as HNC.

    View details for DOI 10.1007/s00330-022-09055-0

    View details for PubMedID 36001124

  • Cellular features of localized microenvironments in human meniscal degeneration: a single-cell transcriptomic study. eLife Fu, W., Chen, S., Yang, R., Li, C., Gao, H., Li, J., Zhang, X. 2022; 11


    Musculoskeletal tissue degeneration impairs the life quality and function of many people. Meniscus degeneration is a major origin of knee osteoarthritis and a common threat to athletic ability, but its cellular mechanism remains elusive.We built a cell atlas of 12 healthy or degenerated human meniscus samples from the inner and outer meniscal zones of 8 patients using scRNA-seq to investigate meniscal microenvironment homeostasis and its changes in the degeneration process and verified findings with immunofluorescent imaging.We identified and localized cell types in inner and outer meniscus and found new chondrocyte subtypes associated with degeneration. The observations suggested understandings on how cellular compositions, functions, and interactions participated in degeneration, and on the possible loop-like interactions among extracellular matrix disassembly, angiogenesis, and inflammation in driving the degeneration.The study provided a rich resource reflecting variations in the meniscal microenvironment during degeneration and suggested new cell subtypes as potential therapeutic targets. The hypothesized mechanism could also be a general model for other joint degenerations.The National Natural Science Foundation of China (81972123, 82172508, 62050178, 61721003), the National Key Research and Development Program of China (2021YFF1200901), Fundamental Research Funds for the Central Universities (2015SCU04A40); The Innovative Spark Project of Sichuan University (2018SCUH0034); Sichuan Science and Technology Program (2020YFH0075); Chengdu Science and Technology Bureau Project (2019-YF05-00090-SN); 1.3.5 Project for Disciplines of Excellence of West China Hospital Sichuan University (ZYJC21030, ZY2017301); 1.3.5 Project for Disciplines of Excellence - Clinical Research Incubation Project, West China Hospital, Sichuan University (2019HXFH039).

    View details for DOI 10.7554/eLife.79585

    View details for PubMedID 36548025

    View details for PubMedCentralID PMC9779791

  • hECA: The cell-centric assembly of a cell atlas. iScience Chen, S., Luo, Y., Gao, H., Li, F., Chen, Y., Li, J., You, R., Hao, M., Bian, H., Xi, X., Li, W., Li, W., Ye, M., Meng, Q., Zou, Z., Li, C., Li, H., Zhang, Y., Cui, Y., Wei, L., Chen, F., Wang, X., Lv, H., Hua, K., Jiang, R., Zhang, X. 2022; 25 (5): 104318


    The accumulation of massive single-cell omics data provides growing resources for building biomolecular atlases of all cells of human organs or the whole body. The true assembly of a cell atlas should be cell-centric rather than file-centric. We developed a unified informatics framework for seamless cell-centric data assembly and built the human Ensemble Cell Atlas (hECA) from scattered data. hECA v1.0 assembled 1,093,299 labeled human cells from 116 published datasets, covering 38 organs and 11 systems. We invented three new methods of atlas applications based on the cell-centric assembly: "in data" cell sorting for targeted data retrieval with customizable logic expressions, "quantitative portraiture" for multi-view representations of biological entities, and customizable reference creation for generating references for automatic annotations. Case studies on agile construction of user-defined sub-atlases and "in data" investigation of CAR-T off-targets in multiple organs showed the great potential enabled by the cell-centric ensemble atlas.

    View details for DOI 10.1016/j.isci.2022.104318

    View details for PubMedID 35602947

    View details for PubMedCentralID PMC9114628

  • Toward a unified information framework for cell atlas assembly. National science review Chen, S., Luo, Y., Gao, H., Li, F., Li, J., Chen, Y., You, R., Lv, H., Hua, K., Jiang, R., Zhang, X. 2022; 9 (3): nwab179


    This perspective discusses the need and directions for the development of a unified information framework to enable the assembly of cell atlases and a revolution in medical research on the virtual body of assembled cell systems.

    View details for DOI 10.1093/nsr/nwab179

    View details for PubMedID 35350228

    View details for PubMedCentralID PMC8951195

  • A new statistic for efficient detection of repetitive sequences. Bioinformatics (Oxford, England) Chen, S., Chen, Y., Sun, F., Waterman, M. S., Zhang, X. 2019; 35 (22): 4596-4606


    Detecting sequences containing repetitive regions is a basic bioinformatics task with many applications. Several methods have been developed for various types of repeat detection tasks. An efficient generic method for detecting most types of repetitive sequences is still desirable. Inspired by the excellent properties and successful applications of the D2 family of statistics in comparative analyses of genomic sequences, we developed a new statistic D2R that can efficiently discriminate sequences with or without repetitive regions.Using the statistic, we developed an algorithm of linear time and space complexity for detecting most types of repetitive sequences in multiple scenarios, including finding candidate clustered regularly interspaced short palindromic repeats regions from bacterial genomic or metagenomics sequences. Simulation and real data experiments show that the method works well on both assembled sequences and unassembled short reads.The codes are available at under GPL 3.0 license.Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btz262

    View details for PubMedID 30993316

    View details for PubMedCentralID PMC7963086