Behrouz Zand1, Rebecca A Previs1, Niki M Zacharias1, Rajesha Rupaimoole1, Takashi Mitamura1, Archana Sidalaghatta Nagaraja1, Michele Guindani1, Heather J Dalton1, Lifeng Yang1, Joelle Baddour1, Abhinav Achreja1, Wei Hu1, Chad V Pecot1, Cristina Ivan1, Sherry Y Wu1, Christopher R McCullough1, Kshipra M Gharpure1, Einav Shoshan1, Sunila Pradeep1, Lingegowda S Mangala1, Cristian Rodriguez-Aguayo1, Ying Wang1, Alpa M Nick1, Michael A Davies1, Guillermo Armaiz-Pena1, Jinsong Liu1, Susan K Lutgendorf1, Keith A Baggerly1, Menashe Bar Eli1, Gabriel Lopez-Berestein1, Deepak Nagrath1, Pratip K Bhattacharya1, Anil K Sood2. 1. Departments of Gynecologic Oncology and Reproductive Medicine (BZ, RAP, RR, TM, ASN, HJD, WH, CI, SYW, KMG, SP, LSM, AMN, GAP, AKS), Cancer Systems Imaging (NMZ, CRM, PKB), Biostatistics (MG), Cancer Medicine (CVP), Center for RNA Interference and Non-Coding RNA (CI, LSM, CRA, GLB, AKS), Cancer Biology (YS, MBE, GLB, AKS), Experimental Therapeutics (CRA, GLB), Bioinformatics and Computational Biology (YW, KAB), Melanoma Medical Oncology (MAD), and Pathology (JL), University of Texas M. D. Anderson Cancer Center, Houston, TX; Department of Nanomedicine and Bioengineering, UT Health, Houston, TX (GLB, AKS); Departments of Psychology, Urology, and Obstetrics and Gynecology, the University of Iowa, Iowa City, IA (SKL); Laboratory for Systems Biology of Human Diseases (LY, JB, AA, DN), Department of Chemical and Biomolecular Engineering (LY, JB, AA, DN), and Department of Bioengineering (DN), Rice University, Houston, TX. 2. Departments of Gynecologic Oncology and Reproductive Medicine (BZ, RAP, RR, TM, ASN, HJD, WH, CI, SYW, KMG, SP, LSM, AMN, GAP, AKS), Cancer Systems Imaging (NMZ, CRM, PKB), Biostatistics (MG), Cancer Medicine (CVP), Center for RNA Interference and Non-Coding RNA (CI, LSM, CRA, GLB, AKS), Cancer Biology (YS, MBE, GLB, AKS), Experimental Therapeutics (CRA, GLB), Bioinformatics and Computational Biology (YW, KAB), Melanoma Medical Oncology (MAD), and Pathology (JL), University of Texas M. D. Anderson Cancer Center, Houston, TX; Department of Nanomedicine and Bioengineering, UT Health, Houston, TX (GLB, AKS); Departments of Psychology, Urology, and Obstetrics and Gynecology, the University of Iowa, Iowa City, IA (SKL); Laboratory for Systems Biology of Human Diseases (LY, JB, AA, DN), Department of Chemical and Biomolecular Engineering (LY, JB, AA, DN), and Department of Bioengineering (DN), Rice University, Houston, TX. asood@mdanderson.org.
Abstract
BACKGROUND: The clinical and biological effects of metabolic alterations in cancer are not fully understood. METHODS: In high-grade serous ovarian cancer (HGSOC) samples (n = 101), over 170 metabolites were profiled and compared with normal ovarian tissues (n = 15). To determine NAT8L gene expression across different cancer types, we analyzed the RNA expression of cancer types using RNASeqV2 data available from the open access The Cancer Genome Atlas (TCGA) website (http://www.cbioportal.org/public-portal/). Using NAT8L siRNA, molecular techniques and histological analysis, we determined cancer cell viability, proliferation, apoptosis, and tumor growth in in vitro and in vivo (n = 6-10 mice/group) settings. Data were analyzed with the Student's t test and Kaplan-Meier analysis. Statistical tests were two-sided. RESULTS: Patients with high levels of tumoral NAA and its biosynthetic enzyme, aspartate N-acetyltransferase (NAT8L), had worse overall survival than patients with low levels of NAA and NAT8L. The overall survival duration of patients with higher-than-median NAA levels (3.6 years) was lower than that of patients with lower-than-median NAA levels (5.1 years, P = .03). High NAT8L gene expression in other cancers (melanoma, renal cell, breast, colon, and uterine cancers) was associated with worse overall survival. NAT8L silencing reduced cancer cell viability (HEYA8: control siRNA 90.61% ± 2.53, NAT8L siRNA 39.43% ± 3.00, P < .001; A2780: control siRNA 90.59% ± 2.53, NAT8L siRNA 7.44% ± 1.71, P < .001) and proliferation (HEYA8: control siRNA 74.83% ± 0.92, NAT8L siRNA 55.70% ± 1.54, P < .001; A2780: control siRNA 50.17% ± 4.13, NAT8L siRNA 26.52% ± 3.70, P < .001), which was rescued by addition of NAA. In orthotopic mouse models (ovarian cancer and melanoma), NAT8L silencing reduced tumor growth statistically significantly (A2780: control siRNA 0.52 g ± 0.15, NAT8L siRNA 0.08 g ± 0.17, P < .001; HEYA8: control siRNA 0.79 g ± 0.42, NAT8L siRNA 0.24 g ± 0.18, P = .008, A375-SM: control siRNA 0.55 g ± 0.22, NAT8L siRNA 0.21 g ± 0.17 g, P = .001). NAT8L silencing downregulated the anti-apoptotic pathway, which was mediated through FOXM1. CONCLUSION: These findings indicate that the NAA pathway has a prominent role in promoting tumor growth and represents a valuable target for anticancer therapy.Altered energy metabolism is a hallmark of cancer (1). Proliferating cancer cells have much greater metabolic requirements than nonproliferating differentiated cells (2,3). Moreover, altered cancer metabolism elevates unique metabolic intermediates, which can promote cancer survival and progression (4,5). Furthermore, emerging evidence suggests that proliferating cancer cells exploit alternative metabolic pathways to meet their high demand for energy and to accumulate biomass (6-8).
BACKGROUND: The clinical and biological effects of metabolic alterations in cancer are not fully understood. METHODS: In high-grade serous ovarian cancer (HGSOC) samples (n = 101), over 170 metabolites were profiled and compared with normal ovarian tissues (n = 15). To determine NAT8L gene expression across different cancer types, we analyzed the RNA expression of cancer types using RNASeqV2 data available from the open access The Cancer Genome Atlas (TCGA) website (http://www.cbioportal.org/public-portal/). Using NAT8L siRNA, molecular techniques and histological analysis, we determined cancer cell viability, proliferation, apoptosis, and tumor growth in in vitro and in vivo (n = 6-10 mice/group) settings. Data were analyzed with the Student's t test and Kaplan-Meier analysis. Statistical tests were two-sided. RESULTS:Patients with high levels of tumoralNAA and its biosynthetic enzyme, aspartate N-acetyltransferase (NAT8L), had worse overall survival than patients with low levels of NAA and NAT8L. The overall survival duration of patients with higher-than-median NAA levels (3.6 years) was lower than that of patients with lower-than-median NAA levels (5.1 years, P = .03). High NAT8L gene expression in other cancers (melanoma, renal cell, breast, colon, and uterine cancers) was associated with worse overall survival. NAT8L silencing reduced cancer cell viability (HEYA8: control siRNA 90.61% ± 2.53, NAT8L siRNA 39.43% ± 3.00, P < .001; A2780: control siRNA 90.59% ± 2.53, NAT8L siRNA 7.44% ± 1.71, P < .001) and proliferation (HEYA8: control siRNA 74.83% ± 0.92, NAT8L siRNA 55.70% ± 1.54, P < .001; A2780: control siRNA 50.17% ± 4.13, NAT8L siRNA 26.52% ± 3.70, P < .001), which was rescued by addition of NAA. In orthotopic mouse models (ovarian cancer and melanoma), NAT8L silencing reduced tumor growth statistically significantly (A2780: control siRNA 0.52 g ± 0.15, NAT8L siRNA 0.08 g ± 0.17, P < .001; HEYA8: control siRNA 0.79 g ± 0.42, NAT8L siRNA 0.24 g ± 0.18, P = .008, A375-SM: control siRNA 0.55 g ± 0.22, NAT8L siRNA 0.21 g ± 0.17 g, P = .001). NAT8L silencing downregulated the anti-apoptotic pathway, which was mediated through FOXM1. CONCLUSION: These findings indicate that the NAA pathway has a prominent role in promoting tumor growth and represents a valuable target for anticancer therapy.Altered energy metabolism is a hallmark of cancer (1). Proliferating cancer cells have much greater metabolic requirements than nonproliferating differentiated cells (2,3). Moreover, altered cancer metabolism elevates unique metabolic intermediates, which can promote cancer survival and progression (4,5). Furthermore, emerging evidence suggests that proliferating cancer cells exploit alternative metabolic pathways to meet their high demand for energy and to accumulate biomass (6-8).
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