TY - JOUR
T1 - Multi-omics integration analysis robustly predicts high-grade patient survival and identifies CPT1B effect on fatty acid metabolism in Bladder Cancer
AU - Vantaku, Venkatrao
AU - Dong, Jianrong
AU - Ambati, Chandrashekar R.
AU - Perera, Dimuthu
AU - Donepudi, Sri Ramya
AU - Amara, Chandra Sekhar
AU - Putluri, Vasanta
AU - Ravi, Shiva Shankar
AU - Robertson, Matthew J.
AU - Piyarathna, Danthasinghe Waduge Badrajee
AU - Villanueva, Mariana
AU - Von Rundstedt, Friedrich Carl
AU - Karanam, Balasubramanyam
AU - Ballester, Leomar Y.
AU - Terris, Martha K.
AU - Bollag, Roni J.
AU - Lerner, Seth P.
AU - Apolo, Andrea B.
AU - Villanueva, Hugo
AU - Lee, Minjae
AU - Sikora, Andrew G.
AU - Lotan, Yair
AU - Sreekumar, Arun
AU - Coarfa, Cristian
AU - Putluri, Nagireddy
N1 - Funding Information:
This research was fully supported by American Cancer Society (ACS) Award 127430-RSG-15-105-01-CNE (N. Putluri), NIH/NCI R01CA220297 (N. Putluri), and NIH/NCI R01CA216426 (N. Putluri), partially supported by the following grants: NIH/NCI U01 CA167234 (A.S.K), CPRIT RP170295 (C.C.), as well as funds from Alkek Center for Molecular Discovery (A. Sreekumar). This project was also supported by the Agilent Technologies Center of Excellence (COE) in Mass Spectrometry at Baylor College of Medicine, Metabolomics Core, Human Tissue Acquisition and Pathology at Baylor College of Medicine with funding from the NIH (P30 CA125123), CPRIT Proteomics and Metabolomics Core Facility (N. Putluri; RP170005), and Dan L. Duncan Cancer Center. CAM assay was supported by the Patient-Derived XenograftandAdvancedinvivoModelsCoreFacilityatBaylorCollegeofMedicine with funding from the Cancer Prevention and Research Institute of Texas (CPRIT) grant #170691. We would like to thank the team of the Georgia Cancer Center Biorepository / BRAG-Onc for biospecimen collection and annotation.
Publisher Copyright:
© 2019 American Association for Cancer Research.
PY - 2019/6/15
Y1 - 2019/6/15
N2 - Purpose: The perturbation of metabolic pathways in high-grade bladder cancer has not been investigated. We aimed to identify a metabolic signature in high-grade bladder cancer by integrating unbiased metabolomics, lipidomics, and transcriptomics to predict patient survival and to discover novel therapeutic targets. Experimental Design: We performed high-resolution liquid chromatography mass spectrometry (LC-MS) and bioinformatic analysis to determine the global metabolome and lipidome in high-grade bladder cancer.Wefurther investigated the effects of impaired metabolic pathways using in vitro and in vivo models. Results: We identified 519 differential metabolites and 19 lipids that were differentially expressed between low-grade and high-grade bladder cancer using the NIST MS metabolomics compendium and lipidblast MS/MS libraries, respectively. Pathway analysis revealed a unique set of biochemical pathways that are highly deregulated in high-grade bladder cancer. Integromics analysis identified a molecular gene signature associated with poor patient survival in bladder cancer. Low expression of CPT1B in high-grade tumors was associated with low FAO and low acyl carnitine levels in high-grade bladder cancer, which were confirmed using tissue microarrays. Ectopic expression of the CPT1B in high-grade bladder cancer cells led to reduced EMT in in vitro, and reduced cell proliferation, EMT, and metastasis in vivo. Conclusions: Our study demonstrates a novel approach for the integration of metabolomics, lipidomics, and transcriptomics data, and identifies a common gene signature associated with poor survival in patients with bladder cancer. Our data also suggest that impairment of FAO due to downregulation of CPT1B plays an important role in the progression toward high-grade bladder cancer and provide potential targets for therapeutic intervention.
AB - Purpose: The perturbation of metabolic pathways in high-grade bladder cancer has not been investigated. We aimed to identify a metabolic signature in high-grade bladder cancer by integrating unbiased metabolomics, lipidomics, and transcriptomics to predict patient survival and to discover novel therapeutic targets. Experimental Design: We performed high-resolution liquid chromatography mass spectrometry (LC-MS) and bioinformatic analysis to determine the global metabolome and lipidome in high-grade bladder cancer.Wefurther investigated the effects of impaired metabolic pathways using in vitro and in vivo models. Results: We identified 519 differential metabolites and 19 lipids that were differentially expressed between low-grade and high-grade bladder cancer using the NIST MS metabolomics compendium and lipidblast MS/MS libraries, respectively. Pathway analysis revealed a unique set of biochemical pathways that are highly deregulated in high-grade bladder cancer. Integromics analysis identified a molecular gene signature associated with poor patient survival in bladder cancer. Low expression of CPT1B in high-grade tumors was associated with low FAO and low acyl carnitine levels in high-grade bladder cancer, which were confirmed using tissue microarrays. Ectopic expression of the CPT1B in high-grade bladder cancer cells led to reduced EMT in in vitro, and reduced cell proliferation, EMT, and metastasis in vivo. Conclusions: Our study demonstrates a novel approach for the integration of metabolomics, lipidomics, and transcriptomics data, and identifies a common gene signature associated with poor survival in patients with bladder cancer. Our data also suggest that impairment of FAO due to downregulation of CPT1B plays an important role in the progression toward high-grade bladder cancer and provide potential targets for therapeutic intervention.
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U2 - 10.1158/1078-0432.CCR-18-1515
DO - 10.1158/1078-0432.CCR-18-1515
M3 - Article
C2 - 30846479
AN - SCOPUS:85067434462
SN - 1078-0432
VL - 25
SP - 3689
EP - 3701
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 12
ER -