Tumor circadian clock strength influences metastatic potential and predicts patient prognosis in luminal A breast cancer

• 成果类型: Article
• 署名作者: Li, Shi-Yang; Hammarlund, Jan A.; Wu, Gang; Lian, Jia-Wen; Howell, Sacha J.; Clarke, Robert B.; Adamson, Antony D.; Goncalves, Catia F.; Hogenesch, John B.; Anafi, Ron C.; Meng, Qing-Jun
• 署名单位: University of Manchester; Drexel University; Cincinnati Children's Hospital Medical Center; University System of Ohio; University of Cincinnati; Cincinnati Children's Hospital Medical Center; University of Manchester; University of Pennsylvania
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11656
• DOI: 10.1073/pnas.2311854121
• 发表日期: 2024-02-13
• 关键词: set enrichment analysis; gene set; expression; chronotherapy; ORGANIZATION; rhythms; atlas; plays

摘要

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular circadian rhythms in noncancerous and cancerous human breast tissues and their clinical relevance are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time- stamped biopsies with public datasets. For noncancerous breast tissue, inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype- specific changes in circadian organization. Luminal A organoids and informatic ordering of luminal A samples exhibit continued, albeit dampened and reprogrammed rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among luminal A samples. Cycling of EMT pathway genes was markedly increased in high- magnitude luminal A tumors. Surprisingly, patients with high- magnitude tumors had reduced 5- y survival. Correspondingly, 3D luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype- specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis. Significance Collecting time- course breast cancer biopsies is difficult. As a result, the influence of daily rhythms on breast tumor biology remains a mystery and physicians cannot personalize the timing of cancer therapies. We used machine learning to overcome this barrier, integrating data from hundreds of patients and ordering these data along circadian time. We identified rhythmic genes and pathways in normal human breast tissue and dampened and reprogrammed rhythms in luminal A breast cancers. Critically, patients with luminal A tumors that showed stronger global expression rhythms had an reduced 5- y survival. These same tumors showed increased cycling of EMT pathway genes. Using 3D cultures of patient- derived tumor cells, we show that luminal A clocks regulate cell invasion and metastasis.