Zand Behrouz, Previs Rebecca A, Zacharias Niki M, Rupaimoole Rajesha, Mitamura Takashi, Nagaraja Archana Sidalaghatta, Guindani Michele, Dalton Heather J, Yang Lifeng, Baddour Joelle, Achreja Abhinav, Hu Wei, Pecot Chad V, Ivan Cristina, Wu Sherry Y, McCullough Christopher R, Gharpure Kshipra M, Shoshan Einav, Pradeep Sunila, Mangala Lingegowda S, Rodriguez-Aguayo Cristian, Wang Ying, Nick Alpa M, Davies Michael A, Armaiz-Pena Guillermo, Liu Jinsong, Lutgendorf Susan K, Baggerly Keith A, Eli Menashe Bar, Lopez-Berestein Gabriel, Nagrath Deepak, Bhattacharya Pratip K, Sood Anil K
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.
J Natl Cancer Inst. 2016 Jan 26;108(6):djv426. doi: 10.1093/jnci/djv426.
The clinical and biological effects of metabolic alterations in cancer are not fully understood.
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.
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.
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).
癌症中代谢改变的临床和生物学效应尚未完全明确。
在高级别浆液性卵巢癌(HGSOC)样本(n = 101)中,对170多种代谢物进行了分析,并与正常卵巢组织(n = 15)进行比较。为了确定NAT8L基因在不同癌症类型中的表达情况,我们使用可从开放获取的癌症基因组图谱(TCGA)网站(http://www.cbioportal.org/public-portal/)获取的RNASeqV2数据,分析了多种癌症类型的RNA表达。使用NAT8L小干扰RNA(siRNA)、分子技术和组织学分析,我们在体外和体内(每组n = 6 - 10只小鼠)环境中确定了癌细胞的活力、增殖、凋亡和肿瘤生长情况。数据采用学生t检验和Kaplan - Meier分析进行分析。统计检验为双侧检验。
肿瘤N - 乙酰天门冬氨酸(NAA)及其生物合成酶天冬氨酸N - 乙酰转移酶(NAT8L)水平高的患者总生存期比NAA和NAT8L水平低的患者更差。NAA水平高于中位数的患者总生存时间(3.6年)低于NAA水平低于中位数的患者(5.1年,P = 0.03)。其他癌症(黑色素瘤、肾细胞癌、乳腺癌、结肠癌和子宫癌)中NAT8L基因的高表达与较差的总生存期相关。NAT8L基因沉默降低了癌细胞的活力(HEYA8细胞系:对照siRNA为90.61% ± 2.53,NAT8L siRNA为39.43% ± 3.00,P < 0.001;A2780细胞系:对照siRNA为90.59% ± 2.53,NAT8L siRNA为7.44% ± 1.71,P < 0.001)和增殖能力(HEYA8细胞系:对照siRNA为74.83% ± 0.92,NAT8L siRNA为55.70% ± 1.54,P < 0.001;A2780细胞系:对照siRNA为50.17% ± 4.13,NAT8L siRNA为26.52% ± 3.70,P < 0.001),添加NAA后可恢复。在原位小鼠模型(卵巢癌和黑色素瘤)中,NAT8L基因沉默显著降低了肿瘤生长(A2780细胞系:对照siRNA为0.52 g ± 0.15,NAT8L siRNA为0.08 g ± 0.17,P < 0.001;HEYA8细胞系:对照siRNA为0.79 g ± 0.42,NAT8L siRNA为0.24 g ± 0.18,P = 0.008;A375 - SM细胞系:对照siRNA为0.55 g ± 0.22,NAT8L siRNA为0.21 g ± 0.17 g,P = 0.001)。NAT8L基因沉默下调了抗凋亡途径,该途径由叉头框蛋白M1(FOXM1)介导。
这些发现表明NAA途径在促进肿瘤生长中起重要作用,是抗癌治疗的一个有价值的靶点。能量代谢改变是癌症的一个标志(1)。增殖的癌细胞比非增殖的分化细胞有更高的代谢需求(2,3)。此外,癌症代谢改变会产生独特的代谢中间产物,可促进癌症的生存和进展(4,5)。此外,新出现的证据表明,增殖的癌细胞利用替代代谢途径来满足其对能量的高需求并积累生物量(6 - 8)。