Lactate-dependent chaperone-mediated autophagy induces oscillatory HIF-1α activity promoting proliferation of hypoxic cells.

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2022-12-21 Epub Date: 2022-12-02 DOI:10.1016/j.cels.2022.11.003
Kshitiz, Junaid Afzal, Yasir Suhail, Hao Chang, Maimon E Hubbi, Archer Hamidzadeh, Ruchi Goyal, Yamin Liu, Peng Sun, Stefania Nicoli, Chi V Dang, Andre Levchenko
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Abstract

Response to hypoxia is a highly regulated process, but little is known about single-cell responses to hypoxic conditions. Using fluorescent reporters of hypoxia response factor-1α (HIF-1α) activity in various cancer cell lines and patient-derived cancer cells, we show that hypoxic responses in individual cancer cells can be highly dynamic and variable. These responses fall into three classes, including oscillatory activity. We identify a molecular mechanism that can account for all three response classes, implicating reactive-oxygen-species-dependent chaperone-mediated autophagy of HIF-1α in a subset of cells. Furthermore, we show that oscillatory response is modulated by the abundance of extracellular lactate in a quorum-sensing-like mechanism. We show that oscillatory HIF-1α activity rescues hypoxia-mediated inhibition of cell division and causes broad suppression of genes downregulated in cancers and activation of genes upregulated in many cancers, suggesting a mechanism for aggressive growth in a subset of hypoxic tumor cells.

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乳酸依赖性伴侣介导的自噬诱导 HIF-1α 的振荡活性,促进缺氧细胞的增殖。
对缺氧的反应是一个高度调控的过程,但人们对单细胞对缺氧条件的反应知之甚少。利用各种癌细胞系和患者衍生癌细胞中缺氧反应因子-1α(HIF-1α)活性的荧光报告,我们发现单个癌细胞的缺氧反应是高度动态和可变的。这些反应可分为三类,其中包括振荡活动。我们发现了一种能解释所有三种反应的分子机制,它与细胞亚群中由反应性氧物种依赖的伴侣介导的 HIF-1α 自噬有关。此外,我们还发现振荡响应在一种类似于法定人数感应的机制中受细胞外乳酸丰度的调节。我们的研究表明,HIF-1α的振荡活性可挽救缺氧介导的细胞分裂抑制,并广泛抑制癌症中下调的基因,激活许多癌症中上调的基因,这表明缺氧肿瘤细胞亚群的侵袭性生长机制。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
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.
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