Modeling collective cell behavior in cancer: Perspectives from an interdisciplinary conversation.

IF 9 1区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2023-04-19 DOI:10.1016/j.cels.2023.03.002

Frederick R Adler, Alexander R A Anderson, Abhinav Bhushan, Paul Bogdan, Jose Javier Bravo-Cordero, Amy Brock, Yun Chen, Edna Cukierman, Kathleen E DelGiorno, Gerald V Denis, Meghan C Ferrall-Fairbanks, Zev Jordan Gartner, Ronald N Germain, Deborah M Gordon, Ginger Hunter, Mohit Kumar Jolly, Loukia Georgiou Karacosta, Karthikeyan Mythreye, Parag Katira, Rajan P Kulkarni, Matthew L Kutys, Arthur D Lander, Ashley M Laughney, Herbert Levine, Emil Lou, Pedro R Lowenstein, Kristyn S Masters, Dana Pe'er, Shelly R Peyton, Manu O Platt, Jeremy E Purvis, Gerald Quon, Jennifer K Richer, Nicole C Riddle, Analiz Rodriguez, Joshua C Snyder, Gregory Lee Szeto, Claire J Tomlin, Itai Yanai, Ioannis K Zervantonakis, Hannah Dueck

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Abstract

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.

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癌症细胞集体行为的建模：跨学科对话的视角。

集体细胞行为有助于癌症发展的所有阶段。了解集体行为是如何通过细胞-细胞相互作用和决策产生的，将促进我们对癌症生物学的理解，并提供新的治疗方法。在此，我们总结了关于癌症多细胞行为的跨学科讨论，从其他科学学科中吸取教训，并确定了未来的方向。

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来源期刊

Cell Systems Medicine-Pathology and Forensic Medicine

CiteScore

16.50

自引率

1.10%

发文量

审稿时长

42 days

期刊介绍： In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.