Dataset Information

Pan-Cancer Proteogenomic Characterization of Metastatic Brain Tumors

ABSTRACT: 4D-DIA data Derived from Paired Primary Tumors, Brain Metastasis and Giloblastoma

ORGANISM(S): Homo Sapiens

SUBMITTER: Gao Zhang

PROVIDER: PXD059751 | iProX | Mon Jan 20 00:00:00 GMT 2025

REPOSITORIES: iProX

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Publications

A proteogenomic atlas of 1032 brain metastases identifies molecular subtypes, immune landscapes, and therapeutic vulnerabilities.

Yang Zhenyu Z Wei Shiyou S Duan Hao H Wang Xiuqi X Zhang Dainan D Kiang Karrie Mei-Yee KM Deng Yulan Y Yang Yuanzhong Y Ku Yin Y Hu Wanming W Zou Chaowei C Tang Meiqin M Jiang Yu Y Liu Yu Y Lan Hongbin H Chen Zexin Z Leung Gilberto Ka-Kit GK Jia Wang W Mou Yonggao Y Liu Lunxu L Zhang Gao G

Nature communications 20260126 1

The molecular heterogeneity of brain metastases hampers therapeutic development for cures. To address this unmet and urgent need, we construct a comprehensive multi-omic, single cell, and spatially resolved atlas of 1,032 pan-cancer brain metastases, identifying four robust molecular subtypes with distinct biological programs and clinical associations. These brain metastases subtypes (BrMS) are defined by unique biological states: neural-like (BrMS1), metabolic (BrMS3), highly proliferative/immu ...[more]

PMID: 41587979

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Project description:Metabolic rewiring is essential for breast tumor growth and progression to metastatic disease, yet little is known regarding how cancer cells modify their acquired metabolic programs in response to different metastatic microenvironments. Transcriptional and metabolomic analysis have previously shown that liver-metastatic breast cancer cells adopt an intrinsic metabolic profile characterized by increased HIF-1α activity and dependence on glycolysis. Stable isotope tracing analysis (SITA) performed in vivo confirmed that the glycolytic nature of liver-metastatic breast cancer cells is retained when these cells are grown as primary tumors or as liver metastases. However, our data also reveal that unique metabolic adaptations are specifically induced by the liver microenvironment. Indeed, liver metastases display elevated expression of genes involved in glutathione (GSH) biosynthesis and reactive oxygen species (ROS) detoxification when compared to primary tumors. Moreover, breast cancer liver metastases rely strongly on glucose and glutamine-derived carbons to support de novo GSH synthesis. Glutathione is a tripeptide that acts as a major scavenger for reactive oxygen species (ROS). Liver metastases display reduced levels of 8-Oxo-2'-deoxyguanosine, confirming their increased capacity to buffer ROS. We demonstrated the dependence of liver metastases formation on these distinct metabolic adaptations by depleting glutamate-cysteine ligase (Gcl), the rate-limiting enzyme in glutathione biosynthesis. Gcl depletion, and decreased GSH levels, strongly reduced the capacity of liver-metastatic cells to form distant metastasis within the liver. We performed gene expression analysis of liver metastasis and primary tumors from liver-metastatic breast cancer cells derived from 4T1 cells. 4T1-2776 (76) and 4T1-2792 (92) cells were injected in the mammary fat pads of BALB/c and grown as primary tumors or were grown as liver metastasis after splenic injection. Tissues were harvested from primary tumors and liver metastasis and submitted to laser-capture microdissection (LCM). For liver metastasis, tumour tissue was harvested at 10 days, 2 weeks and 3 weeks after splenic injection. For each time point, tissue was isolated from the tumor centre (core), a peripheral area of the tumor (margin), a region of the liver proximal to the tumor (adjacent) and a region of the liver far from the tumor (distant). For primary tumors from 4T1-2776 cells (1034, 1036, 1043) and 4T1-2792 (MFP2L, MFP3L, MFP5L) tissue was collected from the tumor core and margin, at the experimental endpoint.

Dataset Information

Pan-Cancer Proteogenomic Characterization of Metastatic Brain Tumors

Publications

A proteogenomic atlas of 1032 brain metastases identifies molecular subtypes, immune landscapes, and therapeutic vulnerabilities.

Similar Datasets

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