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  3. Multi-omics characterization of autophagy-related molecular features for therapeutic targeting of autophagy

Multi-omics characterization of autophagy-related molecular features for therapeutic targeting of autophagy

  • Nat Commun. 2022 Oct 26;13(1):6345. doi: 10.1038/s41467-022-33946-x.
Mei Luo # 1 2 3,  Lin Ye # 1,  Ruimin Chang # 1,  Youqiong Ye 3 4,  Zhao Zhang 3,  Chunjie Liu 2 3,  Shengli Li 3,  Ying Jing 3,  Hang Ruan 3,  Guanxiong Zhang 1,  Yi He 1,  Yaoming Liu 3,  Yu Xue 2,  Xiang Chen 5,  An-Yuan Guo 6,  Hong Liu 7,  Leng Han 8 9 10
Affiliations

Affiliations

  • 1 Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • 2 Center for Artificial Intelligence Biology, Hubei Bioinformatics & Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
  • 3 Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
  • 4 Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
  • 5 Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China. chenxiangck@126.com.
  • 6 Center for Artificial Intelligence Biology, Hubei Bioinformatics & Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. guoay@hust.edu.cn.
  • 7 Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China. hongliu1014@csu.edu.cn.
  • 8 Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. leng.han@tamu.edu.
  • 9 Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA. leng.han@tamu.edu.
  • 10 Department of Translational Medical Sciences, College of Medicine, Texas A&M University, Houston, TX, USA. leng.han@tamu.edu.
  • # Contributed equally.
PMID: 36289218 DOI: 10.1038/s41467-022-33946-x
Abstract

Autophagy is a major contributor to anti-cancer therapy resistance. Many efforts have been made to understand and overcome autophagy-mediated therapy resistance, but these efforts have been unsuccessful in clinical applications. In this study, we establish an Autophagy signature to estimate tumor Autophagy status. We then classify approximately 10,000 tumor samples across 33 Cancer types from The Cancer Genome Atlas into Autophagy score-high and Autophagy score-low groups. We characterize the associations between multi-dimensional molecular features and tumor Autophagy, and further analyse the effects of Autophagy status on drug response. In contrast to the conventional view that the induction of Autophagy serves as a key resistance mechanism during Cancer therapy, our analysis reveals that Autophagy induction may also sensitize Cancer cells to anti-cancer drugs. We further experimentally validate this phenomenon for several anti-cancer drugs in vitro and in vivo, and reveal that Autophagy inducers potentially sensitizes tumor cells to etoposide through downregulating the expression level of DDIT4. Our study provides a comprehensive landscape of molecular alterations associated with tumor Autophagy and highlights an opportunity to leverage multi-omics analysis to utilize multiple drug sensitivity induced by Autophagy.

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