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2,376 results on '"Ye, Yi"'

2. Clinical characteristics of membranous nephropathy after allogeneic hematopoietic stem cell transplantation: A real-world multicenter study

Author

Jin, Yue, Zhao, Peng, Zhang, Yuan-Yuan, Ye, Yi-Shan, Zhou, Fang, Wan, Ding-Ming, Chen, Yi, Zhou, Jian, Li, Xin, Wang, Yan, Liu, Yue, Bian, Zhi-Lei, Yang, Kai-Qian, Li, Zhen, Zhang, Jian, Xu, Wen-Wei, Zhou, Jian-Ying, An, Zhuo-Yu, Fu, Hai-Xia, Chen, Yu-Hong, Chen, Qi, Wu, Jin, Wang, Jing-Zhi, Mo, Xiao-Dong, Chen, Huan, Chen, Yao, Wang, Yu, Chang, Ying-Jun, Huang, He, Huang, Xiao-Jun, and Zhang, Xiao-Hui

Published
2024
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4. Single-Cell Molecular Profiling of Head and Neck Squamous Cell Carcinoma Reveals Five Dysregulated Signaling Pathways Associated With Circulating Tumor Cells.

Author

Stucky, Andres, Viet, Chi, Aouizerat, Bradley, Ye, Yi, Doan, Coleen, Mundluru, Tarun, Sedhiazadeh, Parish, Sinha, Uttam, Chen, Xuelian, Zhang, Xi, Li, Shengwen, Cai, Jin, and Zhong, Jiang

Subjects
circulating tumor cells, head and neck squamous cell carcinoma (HNSCC), molecular pathway, single-cell RNASeq (scRNASeq), tumor heterogeneity, Humans, Neoplastic Cells, Circulating, Squamous Cell Carcinoma of Head and Neck, Signal Transduction, Head and Neck Neoplasms, Single-Cell Analysis, Biomarkers, Tumor, Male, Female, Gene Expression Profiling, Middle Aged, Gene Expression Regulation, Neoplastic
Abstract

OBJECTIVES: To determine the dysregulated signaling pathways of head and neck squamous cell carcinoma associated with circulating tumor cells (CTCs) via single-cell molecular characterization. INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) has a significant global burden and is a disease with poor survival. Despite trials exploring new treatment modalities to improve disease control rates, the 5 year survival rate remains low at only 60%. Most cancer malignancies are reported to progress to a fatal phase due to the metastatic activity derived from treatment-resistant cancer cells, regarded as one of the most significant obstacles to develope effective cancer treatment options. However, the molecular profiles of cancer cells have not been thoroughly studied. METHODS: Here, we examined in-situ HNSCC tumors and pairwisely followed up with the downstream circulating tumor cells (CTCs)-based on the surrogate biomarkers to detect metastasis that is established in other cancers - not yet being fully adopted in HNSCC treatment algorithms. RESULTS: Specifically, we revealed metastatic HNSCC patients have complex CTCs that could be defined through gene expression and mutational gene profiling derived from completed single-cell RNASeq (scRNASeq) that served to confirm molecular pathways inherent in these CTCs. To enhance the reliability of our findings, we cross-validated those molecular profiles with results from previously published studies. CONCLUSION: Thus, we identified 5 dysregulated signaling pathways in CTCs to derive HNSCC biomarker panels for screening HNSCC in situ tumors.

Published
2024

5. Healing Unsafe Dialogue Responses with Weak Supervision Signals

Author

Liang, Zi, Wang, Pinghui, Zhang, Ruofei, Zhang, Shuo, Huang, Xiaofan Ye Yi, and Feng, Junlan

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Recent years have seen increasing concerns about the unsafe response generation of large-scale dialogue systems, where agents will learn offensive or biased behaviors from the real-world corpus. Some methods are proposed to address the above issue by detecting and replacing unsafe training examples in a pipeline style. Though effective, they suffer from a high annotation cost and adapt poorly to unseen scenarios as well as adversarial attacks. Besides, the neglect of providing safe responses (e.g. simply replacing with templates) will cause the information-missing problem of dialogues. To address these issues, we propose an unsupervised pseudo-label sampling method, TEMP, that can automatically assign potential safe responses. Specifically, our TEMP method groups responses into several clusters and samples multiple labels with an adaptively sharpened sampling strategy, inspired by the observation that unsafe samples in the clusters are usually few and distribute in the tail. Extensive experiments in chitchat and task-oriented dialogues show that our TEMP outperforms state-of-the-art models with weak supervision signals and obtains comparable results under unsupervised learning settings.

Published
2023

6. Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding

Author

Zhang, Yu, Cheng, Hao, Shen, Zhihong, Liu, Xiaodong, Wang, Ye-Yi, and Gao, Jianfeng

Subjects
Computer Science - Computation and Language, Computer Science - Digital Libraries, Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Scientific literature understanding tasks have gained significant attention due to their potential to accelerate scientific discovery. Pre-trained language models (LMs) have shown effectiveness in these tasks, especially when tuned via contrastive learning. However, jointly utilizing pre-training data across multiple heterogeneous tasks (e.g., extreme multi-label paper classification, citation prediction, and literature search) remains largely unexplored. To bridge this gap, we propose a multi-task contrastive learning framework, SciMult, with a focus on facilitating common knowledge sharing across different scientific literature understanding tasks while preventing task-specific skills from interfering with each other. To be specific, we explore two techniques -- task-aware specialization and instruction tuning. The former adopts a Mixture-of-Experts Transformer architecture with task-aware sub-layers; the latter prepends task-specific instructions to the input text so as to produce task-aware outputs. Extensive experiments on a comprehensive collection of benchmark datasets verify the effectiveness of our task-aware specialization strategy, where we outperform state-of-the-art scientific pre-trained LMs. Code, datasets, and pre-trained models can be found at https://scimult.github.io/., Comment: 17 pages; Accepted to Findings of EMNLP 2023 (Project Page: https://scimult.github.io/)

Published
2023

7. Research on the Efficiency of Visual Guidance Recognition for Tilt Tray Sorter

Author

Tuo, Jiangmin, Tang, Chengsheng, Xie, Qing, Ye, Yi, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, and Rau, Pei-Luen Patrick, editor

Published
2024
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8. Mesenchymal Stromal Cells Increase the Natural Killer Resistance of Circulating Tumor Cells via Intercellular Signaling of cGAS‐STING‐IFNβ‐HLA

Author

Ye Yi, Guihui Qin, Hongmei Yang, Hao Jia, Qibing Zeng, Dejin Zheng, Sen Ye, Zhiming Zhang, Tzu‐Ming Liu, Kathy Qian Luo, Chu‐Xia Deng, and Ren‐He Xu

Subjects
cGAS‐STING‐IFNβ‐HLA pathway, circulating tumor cells, mesenchymal stromal cells, natural killer cells, Science
Abstract

Abstract Circulating tumor cells (CTCs) shed from primary tumors must overcome the cytotoxicity of immune cells, particularly natural killer (NK) cells, to cause metastasis. The tumor microenvironment (TME) protects tumor cells from the cytotoxicity of immune cells, which is partially executed by cancer‐associated mesenchymal stromal cells (MSCs). However, the mechanisms by which MSCs influence the NK resistance of CTCs remain poorly understood. This study demonstrates that MSCs enhance the NK resistance of cancer cells in a gap junction‐dependent manner, thereby promoting the survival and metastatic seeding of CTCs in immunocompromised mice. Tumor cells crosstalk with MSCs through an intercellular cGAS‐cGAMP‐STING signaling loop, leading to increased production of interferon‐β (IFNβ) by MSCs. IFNβ reversely enhances the type I IFN (IFN‐I) signaling in tumor cells and hence the expression of human leukocyte antigen class I (HLA‐I) on the cell surface, protecting the tumor cells from NK cytotoxicity. Disruption of this loop reverses NK sensitivity in tumor cells and decreases tumor metastasis. Moreover, there are positive correlations between IFN‐I signaling, HLA‐I expression, and NK tolerance in human tumor samples. Thus, the NK‐resistant signaling loop between tumor cells and MSCs may serve as a novel therapeutic target.

Published
2024
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9. Towards Real-time High-Definition Image Snow Removal: Efficient Pyramid Network with Asymmetrical Encoder-decoder Architecture

Author

Ye, Tian, Chen, Sixiang, Liu, Yun, Ye, Yi, and Chen, Erkang

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In winter scenes, the degradation of images taken under snow can be pretty complex, where the spatial distribution of snowy degradation is varied from image to image. Recent methods adopt deep neural networks to directly recover clean scenes from snowy images. However, due to the paradox caused by the variation of complex snowy degradation, achieving reliable High-Definition image desnowing performance in real time is a considerable challenge. We develop a novel Efficient Pyramid Network with asymmetrical encoder-decoder architecture for real-time HD image desnowing. The general idea of our proposed network is to utilize the multi-scale feature flow fully and implicitly mine clean cues from features. Compared with previous state-of-the-art desnowing methods, our approach achieves a better complexity-performance trade-off and effectively handles the processing difficulties of HD and Ultra-HD images. The extensive experiments on three large-scale image desnowing datasets demonstrate that our method surpasses all state-of-the-art approaches by a large margin both quantitatively and qualitatively, boosting the PSNR metric from 31.76 dB to 34.10 dB on the CSD test dataset and from 28.29 dB to 30.87 dB on the SRRS test dataset.

Published
2022

12. Underwater Light Field Retention : Neural Rendering for Underwater Imaging

Author

Ye, Tian, Chen, Sixiang, Liu, Yun, Ye, Yi, Chen, Erkang, and Li, Yuche

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Underwater Image Rendering aims to generate a true-tolife underwater image from a given clean one, which could be applied to various practical applications such as underwater image enhancement, camera filter, and virtual gaming. We explore two less-touched but challenging problems in underwater image rendering, namely, i) how to render diverse underwater scenes by a single neural network? ii) how to adaptively learn the underwater light fields from natural exemplars, i,e., realistic underwater images? To this end, we propose a neural rendering method for underwater imaging, dubbed UWNR (Underwater Neural Rendering). Specifically, UWNR is a data-driven neural network that implicitly learns the natural degenerated model from authentic underwater images, avoiding introducing erroneous biases by hand-craft imaging models. Compared with existing underwater image generation methods, UWNR utilizes the natural light field to simulate the main characteristics ofthe underwater scene. Thus, it is able to synthesize a wide variety ofunderwater images from one clean image with various realistic underwater images. Extensive experiments demonstrate that our approach achieves better visual effects and quantitative metrics over previous methods. Moreover, we adopt UWNR to build an open Large Neural Rendering Underwater Dataset containing various types of water quality, dubbed LNRUD. The source code and LNRUD are available at https: //github.com/Ephemeral182/UWNR.

Published
2022

14. The development of a cSMART-based integrated model for hepatocellular carcinoma diagnosis

Author

Wu, Tong, Fan, Rong, Bai, Jian, Yang, Zhao, Qian, Yun-Song, Du, Lu-Tao, Wang, Chun-Ying, Wang, Ying-Chao, Jiang, Guo-Qing, Zheng, Dan, Fan, Xiao-Tang, Zheng, Bo, Liu, Jing-Feng, Deng, Guo-Hong, Shen, Feng, Hu, He-Ping, Ye, Yi-Nong, Zhang, Qing-Zheng, Zhang, Jing, Gao, Yan-Hang, Xia, Jie, Yan, Hua-Dong, Liang, Min-Feng, Yu, Yan-Long, Sun, Fu-Ming, Gao, Yu-Jing, Sun, Jian, Zhong, Chun-Xiu, Wang, Yin, Wang, Hui, Kong, Fei, Chen, Jin-Ming, Wen, Hao, Wu, Bo-Ming, Wang, Chuan-Xin, Wu, Lin, Hou, Jin-Lin, Liu, Xiao-Long, Wang, Hong-Yang, and Chen, Lei

Published
2023
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16. Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification

Author

Zhang, Yu, Shen, Zhihong, Wu, Chieh-Han, Xie, Boya, Hao, Junheng, Wang, Ye-Yi, Wang, Kuansan, and Han, Jiawei

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Large-scale multi-label text classification (LMTC) aims to associate a document with its relevant labels from a large candidate set. Most existing LMTC approaches rely on massive human-annotated training data, which are often costly to obtain and suffer from a long-tailed label distribution (i.e., many labels occur only a few times in the training set). In this paper, we study LMTC under the zero-shot setting, which does not require any annotated documents with labels and only relies on label surface names and descriptions. To train a classifier that calculates the similarity score between a document and a label, we propose a novel metadata-induced contrastive learning (MICoL) method. Different from previous text-based contrastive learning techniques, MICoL exploits document metadata (e.g., authors, venues, and references of research papers), which are widely available on the Web, to derive similar document-document pairs. Experimental results on two large-scale datasets show that: (1) MICoL significantly outperforms strong zero-shot text classification and contrastive learning baselines; (2) MICoL is on par with the state-of-the-art supervised metadata-aware LMTC method trained on 10K-200K labeled documents; and (3) MICoL tends to predict more infrequent labels than supervised methods, thus alleviates the deteriorated performance on long-tailed labels., Comment: 12 pages; Accepted to WWW 2022

Published
2022

20. Association of relative deprivation with social withdrawal and its underlying mechanisms: A large cross-sectional study among Chinese migrant adolescents

Author

Xiong, Meng, Hu, Zhi-qin, and Ye, Yi-duo

Subjects
Social isolation -- Research, Psychological research, Teenage immigrants -- Social aspects -- Psychological aspects, Psychology and mental health
Abstract

Despite existing studies showing that relative deprivation is a risk factor for migrant populations' social withdrawal, the underlying mechanisms are largely unclear. The current study used a moderated mediation model to investigate perceived social support as a possible mediator and in-group identity as a possible moderator in the relationship between relative deprivation and social withdrawal. A large sample of 1772 Chinese migrant adolescents completed questionnaires that measured relative deprivation, social withdrawal, perceived social support, and in-group identity. Relative deprivation was significantly and positively correlated with migrant adolescents' social withdrawal, and perceived social support partially mediated this relationship. Moreover, in-group identity moderated the indirect effect of relative deprivation on social withdrawal via perceived social support, with a high level of in-group identity weakening the association between relative deprivation and perceived social support. It is recommended that parents and educators pay closer attention to adolescents' perceived social support and in-group identity to provide appropriate interventions., Author(s): Meng Xiong [sup.1] [sup.2] , Zhi-qin Hu [sup.1] , Yi-duo Ye [sup.3] Author Affiliations: (1) grid.410654.2, 0000 0000 8880 6009, Department of Psychology, School of Education and Sports Sciences, [...]

Published
2023
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21. Online risky behavior and sleep quality among Chinese college students: The chain mediating role of rumination and anxiety

Author

Qiu, Wen-Fu, Ma, Jian-Ping, Xie, Zhen-Yu, Xie, Xiao-Tong, Wang, Cong-Xing, and Ye, Yi-Duo

Subjects
College students -- Psychological aspects -- Health aspects, Psychological research, Risk-taking (Psychology) -- Health aspects, Rumination (Psychology) -- Health aspects, Anxiety -- Research, Sleep -- Psychological aspects -- Health aspects, Psychology and mental health
Abstract

This study explored the chain mediating effects of rumination and anxiety in the relationship between online risky behavior and sleep quality among Chinese college students. A sample of 1039 Chinese college students (Mage = 19.49, SD = 1.14, 53.32% males) were investigated with Online Risky Behavior Scale (ORBS), Pittsburgh Sleep Quality Index scale (PSQI), Ruminative Responses Scale (RRS) and Self-rating Anxiety Scale (SAS). The results showed that: (1) There is a significant positive correlation among online risky behavior, sleep quality, rumination and anxiety, and (2) Online risky behavior could not directly affect sleep quality, but it can affect sleep quality through the mediation of rumination and anxiety. The chain mediating effects includes three paths: The mediating role of rumination, the mediating role of anxiety, and the chain mediating role of rumination and anxiety after controlling for gender, grade, major, and network usage time. These findings contribute to a deeper understanding of how online risky behavior affects sleep quality and provide important practical guidance for improving sleep quality., Author(s): Wen-Fu Qiu [sup.1] , Jian-Ping Ma [sup.2] , Zhen-Yu Xie [sup.1] , Xiao-Tong Xie [sup.1] , Cong-Xing Wang [sup.1] , Yi-Duo Ye [sup.1] Author Affiliations: (1) grid.411503.2, 0000 0000 [...]

Published
2023
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31. Towards Real-Time High-Definition Image Snow Removal: Efficient Pyramid Network with Asymmetrical Encoder-Decoder Architecture

Author

Ye, Tian, Chen, Sixiang, Liu, Yun, Ye, Yi, Bai, JinBin, Chen, Erkang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Lei, editor, Gall, Juergen, editor, Chin, Tat-Jun, editor, Sato, Imari, editor, and Chellappa, Rama, editor

Published
2023
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33. Cell-free DNA testing for early hepatocellular carcinoma surveillance

Author

Chen, Lei, Wu, Tong, Fan, Rong, Qian, Yun-Song, Liu, Jing-Feng, Bai, Jian, Zheng, Bo, Liu, Xiao-Long, Zheng, Dan, Du, Lu-Tao, Jiang, Guo-Qing, Wang, Ying-Chao, Fan, Xiao-Tang, Deng, Guo-Hong, Wang, Chun-Ying, Shen, Feng, Hu, He-Ping, Zhang, Qing-Zheng, Ye, Yi-Nong, Zhang, Jing, Gao, Yan-Hang, Xia, Jie, Yan, Hua-Dong, Liang, Min-Feng, Yu, Yan-Long, Sun, Fu-Ming, Gao, Yu-Jing, Sun, Jian, Zhong, Chun-Xiu, Wang, Yin, Wang, Hui, Kong, Fei, Chen, Jin-Ming, Wen, Hao, Wu, Bo-Ming, Wang, Chuan-Xin, Wu, Lin, Hou, Jin-Lin, and Wang, Hong-Yang

Published
2024
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40. Definitive Endodermal Cells Supply an in vitro Source of Mesenchymal Stem/Stromal Cells

Author

Yumeng Zhang, Ye Yi, Xia Xiao, Lingling Hu, Jiaqi Xu, Dejin Zheng, Ho Cheng Koc, Un In Chan, Ya Meng, Ligong Lu, Weiwei Liu, Xiaoling Xu, Ningyi Shao, Edwin Chong Wing Cheung, Ren-He Xu, and Guokai Chen

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Mesenchymal stem/Stromal cells (MSCs) have great therapeutic potentials, and they have been isolated from various tissues and organs including definitive endoderm (DE) organs, such as the lung, liver and intestine. MSCs have been induced from human pluripotent stem cells (hPSCs) through multiple embryonic lineages, including the mesoderm, neural crest, and extraembryonic cells. However, it remains unclear whether hPSCs could give rise to MSCs in vitro through the endodermal lineage. Here, we report that hPSC-derived, SOX17+ definitive endoderm progenitors can further differentiate to cells expressing classic MSC markers, which we name definitive endoderm-derived MSCs (DE-MSCs). Single cell RNA sequencing demonstrates the stepwise emergence of DE-MSCs, while endoderm-specific gene expression can be elevated by signaling modulation. DE-MSCs display multipotency and immunomodulatory activity in vitro and possess therapeutic effects in a mouse ulcerative colitis model. This study reveals that, in addition to the other germ layers, the definitive endoderm can also contribute to MSCs and DE-MSCs could be a cell source for regenerative medicine.

Published
2023
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41. Polygames: Improved Zero Learning

Author

Cazenave, Tristan, Chen, Yen-Chi, Chen, Guan-Wei, Chen, Shi-Yu, Chiu, Xian-Dong, Dehos, Julien, Elsa, Maria, Gong, Qucheng, Hu, Hengyuan, Khalidov, Vasil, Li, Cheng-Ling, Lin, Hsin-I, Lin, Yu-Jin, Martinet, Xavier, Mella, Vegard, Rapin, Jeremy, Roziere, Baptiste, Synnaeve, Gabriel, Teytaud, Fabien, Teytaud, Olivier, Ye, Shi-Cheng, Ye, Yi-Jun, Yen, Shi-Jim, and Zagoruyko, Sergey

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games. It can be improved using a fully convolutional structure (no fully connected layer). Using such an architecture plus global pooling, we can create bots independent of the board size. The training can be made more robust by keeping track of the best checkpoints during the training and by training against them. Using these features, we release Polygames, our framework for Zero learning, with its library of games and its checkpoints. We won against strong humans at the game of Hex in 19x19, which was often said to be untractable for zero learning; and in Havannah. We also won several first places at the TAAI competitions.

Published
2020

43. Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma

Author

Viet, Chi T., Asam, Kesava R., Yu, Gary, Dyer, Emma C., Kochanny, Sara, Thomas, Carissa M., Callahan, Nicholas F., Morlandt, Anthony B., Cheng, Allen C., Patel, Ashish A., Roden, Dylan F., Young, Simon, Melville, James, Shum, Jonathan, Walker, Paul C., Nguyen, Khanh K., Kidd, Stephanie N., Lee, Steve C., Folk, Gretchen S., Viet, Dan T., Grandhi, Anupama, Deisch, Jeremy, Ye, Yi, Momen-Heravi, Fatemeh, Pearson, Alexander T., and Aouizerat, Bradley E.

Published
2024
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46. SPTAN1/NUMB axis senses cell density to restrain cell growth and oncogenesis through Hippo signaling

Author

Su, Dongxue, Li, Yuxi, Zhang, Weiji, Gao, Huan, Cheng, Yao, Hou, Yongqiang, Li, Junhong, Ye, Yi, Lai, Zhangjian, Li, Zhe, Huang, Haitao, Li, Jiaxin, Li, Jinhuan, Cheng, Mengyu, Nian, Cheng, Wu, Na, Zhou, Zhien, Xing, Yunzhi, Zhao, Yu, Liu, He, Tang, Jiayu, Chen, Qinghua, Hong, Lixin, Li, Wengang, Peng, Zhihai, Zhao, Bin, Johnson, Randy L., Liu, Pingguo, Hong, Wanjin, Chen, Lanfen, and Zhou, Dawang

Subjects
Carcinogenesis -- Growth, Liver cancer, Membrane proteins -- Growth, Company growth, Health care industry
Abstract

The loss of contact inhibition is a key step during carcinogenesis. The Hippo-Yes-associated protein (Hippo/YAP) pathway is an important regulator of cell growth in a cell density-dependent manner. However, how Hippo signaling senses cell density in this context remains elusive. Here, we report that high cell density induced the phosphorylation of spectrin a chain, nonerythrocytic 1 (SPTAN1), a plasma membrane-stabilizing protein, to recruit NUMB endocytic adaptor protein isoforms 1 and 2 (NUMB1/2), which further sequestered microtubule affinity-regulating kinases (MARKs) in the plasma membrane and rendered them inaccessible for phosphorylation and inhibition of the Hippo kinases sterile 20-like kinases MST1 and MST2 (MST1/2). WW45 interaction with MST1/2 was thereby enhanced, resulting in the activation of Hippo signaling to block YAP activity for cell contact inhibition. Importantly, low cell density led to SPTAN1 dephosphorylation and NUMB cytoplasmic location, along with MST1/2 inhibition and, consequently, YAP activation. Moreover, double KO of NUMB and WW45 in the liver led to appreciable organ enlargement and rapid tumorigenesis. Interestingly, NUMB isoforms 3 and 4, which have a truncated phosphotyrosine-binding (PTB) domain and are thus unable to interact with phosphorylated SPTAN1 and activate MST1/2, were selectively upregulated in liver cancer, which correlated with YAP activation. We have thus revealed a SPTAN1/ NUMB1/2 axis that acts as a cell density sensor to restrain cell growth and oncogenesis by coupling external cell-cell contact signals to intracellular Hippo signaling., Introduction Cells within multicellular organisms are able to sense cell-cell contact and their density to control the proper tissue morphogenesis and organ size (1, 2). When cell density increases, contact [...]

Published
2023
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