Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.,Science

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Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.
Science ( IF 44.7 ) Pub Date : 2024-09-06 , DOI: 10.1126/science.adk9217
Laksshman Sundaram _{1,

2,

3,

4} , Arvind Kumar ₃ , Matthew Zatzman ₅ , Adriana Salcedo ₃ , Neal Ravindra ₃ , Shadi Shams _{1,

6,

7} , Bryan H Louie _{6,

7} , S Tansu Bagdatli _{1,

6,

7} , Matthew A Myers ₅ , Shahab Sarmashghi ₈ , Hyo Young Choi _{9,

10} , Won-Young Choi ₁₁ , Kathryn E Yost _{6,

7} , Yanding Zhao _{1,

6,

7} , Jeffrey M Granja ₁ , Toshinori Hinoue ₁₂ , D Neil Hayes _{9,

10,

11} , Andrew Cherniack ₈ , Ina Felau ₁₃ , Hani Choudhry ₁₄ , Jean C Zenklusen ₁₃ , Kyle Kai-How Farh ₃ , Andrew McPherson ₅ , Christina Curtis _{1,

7,

15,

16,

17} , Peter W Laird ₁₂ , , John A Demchok ₁₈ , Liming Yang ₁₈ , Roy Tarnuzzer ₁₈ , Samantha J Caesar-Johnson ₁₈ , Zhining Wang ₁₉ , Ashley S Doane ₂₀ , Ekta Khurana _{20,

21,

22,

23} , Mauro A A Castro ₂₄ , Alexander J Lazar ₂₅ , Bradley M Broom ₂₆ , John N Weinstein _{26,

27} , Rehan Akbani ₂₆ , Shwetha V Kumar ₂₆ , Benjamin J Raphael ₂₈ , Christopher K Wong ₂₉ , Joshua M Stuart ₂₉ , Rojin Safavi ₂₉ , Christopher C Benz ₃₀ , Benjamin K Johnson ₁₂ , Cindy Kyi ₁₈ , Hui Shen ₁₂ , M Ryan Corces _{6,

31,

32,

33} , Howard Y Chang _{1,

6,

7,

34} , William J Greenleaf _{1,

7,

35}

Affiliation

Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Department of Computer Science, Stanford University, Stanford, CA, USA.
Illumina AI laboratory, Illumina Inc, Foster City, CA, USA.
NVIDIA Bio Research, NVIDIA, Santa Clara, CA, USA.
Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Department of Dermatology, Stanford University School of Medicine, Stanford, CA, USA.
Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305, USA.
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA.
UTHSC Center for Cancer Research, University of Tennessee Health Science Center, Memphis, TN, USA.
Center for Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA.
National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Department of Biochemistry, Faculty of Science, Cancer and Mutagenesis Unit, King Fahd Center for Medical Research, King Abdulaziz University, Jeddah, Saudi Arabia.
Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
Chan Zuckerberg Biohub, San Francisco, CA, USA.
Center for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USA.
Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, 9609 Medical Center Drive, Rockville, MD 20850, USA.
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA.
Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA.
Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA.
Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
Bioinformatics and Systems Biology Laboratory, Federal University of Paraná, Curitiba 81520-260, Brazil.
Departments of Pathology & Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030.
Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540.
Biomolecular Engineering Department, School of Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.
Buck Institute for Research on Aging, Novato, CA 94945, USA.
Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA.
Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Howard Hughes Medical Institute, Stanford University, School of Medicine, Stanford, CA, USA.
Department of Applied Physics, Stanford University, Stanford, CA, USA.

To identify cancer-associated gene regulatory changes, we generated single-cell chromatin accessibility landscapes across eight tumor types as part of The Cancer Genome Atlas. Tumor chromatin accessibility is strongly influenced by copy number alterations that can be used to identify subclones, yet underlying cis-regulatory landscapes retain cancer type-specific features. Using organ-matched healthy tissues, we identified the "nearest healthy" cell types in diverse cancers, demonstrating that the chromatin signature of basal-like-subtype breast cancer is most similar to secretory-type luminal epithelial cells. Neural network models trained to learn regulatory programs in cancer revealed enrichment of model-prioritized somatic noncoding mutations near cancer-associated genes, suggesting that dispersed, nonrecurrent, noncoding mutations in cancer are functional. Overall, these data and interpretable gene regulatory models for cancer and healthy tissue provide a framework for understanding cancer-specific gene regulation.

中文翻译：

单细胞染色质可及性揭示了原发性人类癌症中的恶性调节程序。

为了识别癌症相关基因调控变化，我们生成了八种肿瘤类型的单细胞染色质可及性景观，作为癌症基因组图谱的一部分。肿瘤染色质可及性受可用于识别亚克隆的拷贝数改变的强烈影响，但潜在的顺式调节景观保留了癌症类型特异性特征。使用器官匹配的健康组织，我们确定了不同癌症中“最接近健康”的细胞类型，证明基底样亚型乳腺癌的染色质特征与分泌型管腔上皮细胞最相似。经过训练学习癌症调节程序的神经网络模型揭示了癌症相关基因附近模型优先体细胞非编码突变的富集，这表明癌症中分散的、非复发的、非编码的突变是功能性的。总体而言，这些数据以及癌症和健康组织的可解释基因调控模型为理解癌症特异性基因调控提供了一个框架。

更新日期：2024-09-06

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