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摘要:
近年来，"肿瘤是一种代谢性疾病"已经成为共识，肿瘤的代谢重编程成为了当下研究的热点。一碳代谢包含了叶酸循环、蛋氨酸循环和转硫化途径。一碳单位可通过这三个途径产生和利用嘧啶、胸苷酸、S-腺苷蛋氨酸、谷胱甘肽等来调节肿瘤的生长和增殖。本文主要阐述肿瘤中一碳单位的产生与利用以及一碳代谢与肿瘤发生发展的相互作用，为一碳代谢在肿瘤发生中的机制研究以及肿瘤的营养素等治疗提供新思路。
Abstract:In recent years, it has already run into a common view that "tumor is a metabolic disease", and the reprogramming of tumor metabolism has become the focus of current research. One-carbon metabolism involves folate cycle, methionine cycle and trans-sulfuration pathway. By utilizing these three ways, one carbon unit can regulate tumor growth and proliferation with the production of pyrimidine, thymidine, s-adenosine, glutathione, etc. This paper mainly describes the production and utilization of one carbon unit in tumor, as well as the interaction between one carbon metabolism and tumor development, providing new ideas for studying the mechanism of one-carbon metabolism in tumorigenesis and the treatment of nutrients in tumor.
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Key words:
- One-carbon metabolism /
- Tumor therapy /
- Serine /
- Folic acid
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0 引言
目前，化学治疗仍是三阴性乳腺癌的主要治疗方法之一，但是肿瘤细胞对化疗药物的耐药性严重影响了治疗效果，化疗药物与肿瘤细胞的接触是诱导继发性耐药的主要原因[1]。由于阿霉素是乳腺癌化学方案的常用药物[2]，本研究观察阿霉素对三阴性乳腺癌耐药性的诱导作用并探究其机制。
ATP结合盒（ABC）转运蛋白在耐药的发展中起着至关重要的作用。ATP结合盒亚家族G成员2（ATP-binding cassette, sub-family G member 2, ABCG2）能排出大量异质化合物，导致耐药，引起治疗抵抗[3]。细胞耐药性的产生及耐药蛋白的表达受多种转录因子的调控。有研究报道cMyc能够调控包括ABCG2在内的ABC转运蛋白的表达[4]。cMyc是一个多功能的转录因子，参与调节细胞对阿霉素的敏感度[5]，而cMyc的表达受其上游基因Stat3的调控。Stat3在肿瘤组织中异常激活，引发其下游靶基因cMyc转录，从而使正常细胞转化为癌细胞，并增加肿瘤细胞的耐药性[6]。因此，本研究观察阿霉素对MDA-MB-468细胞耐药性的诱导作用并探讨Stat3-cMyc通路是否介导了耐药性的发生。
1 材料与方法
1.1 细胞株、试剂、仪器
人乳腺癌MDA-MB-468细胞株购自美国标准细胞库（American type culture collections, ATCC）。本研究实验剂和仪器包括：RPMI 1640培养基（Hyclone，美国）、青霉素/链霉素（索莱宝，北京，中国）、胎牛血清（四季青，杭州，中国）、阿霉素（索莱宝，北京，中国）、RIPA裂解液/苯甲基磺酰氟（索莱宝，北京，中国）、聚偏二氟乙烯膜（Millipore，Billerica，美国）、ABCG2抗体（Abcam，Cambridge，美国）、WP1066抑制剂（Selleckchem，上海，中国）和二甲基亚砜（索莱宝，北京，中国）等。
1.2 细胞培养
人乳腺癌MDA-MB-468细胞用含10%FBS和1%青霉素/链霉素的RPMI 1640在37℃、5%CO2培养箱中培养。以不同浓度的阿霉素（0、0.05、0.1和0.5 μmol/L）孵育细胞24 h，观察并筛选最适阿霉素浓度进行后续实验。
1.3 MTT法检测
细胞以3 000个/孔的密度接种至96孔板，然后分别加入终浓度为0、0.05、0.1和0.5 μmol/L的阿霉素。24 h后，每孔加入20 μl MTT溶液（5 mg/ml）继续培养4 h，吸弃培养液，每孔加150 μl DMSO溶液，振荡15 min后测定570 nm处的吸光度（OD570）。
1.4 细胞爬片及免疫荧光染色
将盖玻片置于24孔板孔底，分别将MDA-MB-468和MDA-MB-468/ADM细胞以1×104个/孔接种，待细胞爬满盖玻片后进行免疫荧光染色。用PBS轻轻冲洗后在4%多聚甲醛中固定15 min。PBS洗涤爬片3次，山羊血清封闭1 h。将细胞用ABCG2一抗在4℃冰箱中孵育、过夜。PBS洗涤后，用二抗于37℃温育1 h。PBS洗涤细胞，用DAPI染色10 min，再次洗涤3次后滴加荧光防淬灭剂，观察免疫荧光染色并拍照。
1.5 蛋白质印迹分析
抽提各组细胞的总蛋白，利用BCA法测定总蛋白浓度，以每个泳道20 μg浓度的蛋白样品上样，经SDS-PAGE电泳后，利用半干电转化法将蛋白转移至PVDF膜上，经过封闭、一抗（稀释倍数1:1 000）孵育、TBST洗脱、HRP标记的二抗（稀释倍数1:5 000）孵育、TBST再洗脱等步骤后，用增强化学发光法检测信号及X线片曝光，并且经定影显影处理，获得清晰条带。
1.6 统计学方法
运用SPSS13.0统计软件进行分析，所有结果采用（x±s）表示，组间均数的比较采用独立t检验（双侧），P < 0.05为差异有统计学意义。
2 结果
2.1 持续低剂量阿霉素刺激诱导MDA-MB-468细胞产生耐药性
不同浓度阿霉素作用于MDA-MB-468细胞24 h后可见0.05 μmol/L与0.1 μmol/L浓度的阿霉素未引起细胞明显的损伤，大部分细胞生长良好。当浓度增加到0.5 μmol/L时，几乎所有细胞都受损，可见大量坏死细胞；MTT法测得在0.05 μmol/L、0.1 μmol/L及0.5 μmol/L浓度下阿霉素对MDA-MB-468细胞的抑制率分别为0.14、0.20、0.38，而且阿霉素对MDA-MB-468细胞的半数最大效应浓度（concentration for 50% of maximal effect, EC50）为0.94 μmol/L（P=0.038）。综合以上结果，我们选用0.1 μmol/L的阿霉素继续进行后续研究。
用0.1 μmol/L的阿霉素持续刺激MDA-MB-468细胞4周后获得耐药细胞，命名为MDA-MB-468/ADM。MTT实验检测MDA-MB-468/ADM细胞对阿霉素敏感度，结果显示MDA-MB-468/ADM的EC50为5.2 μmol/L，较MDA-MB-468的EC50（0.94 μmol/L）显著升高（P=0.041），说明长期使用0.1 μmol/L的阿霉素后，MDA-MB-468细胞对阿霉素的敏感度显著下降，产生耐药，见图 1。
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图 1 MTT测定经24h处理后的MDA-MB-468细胞与MDA-MB-468/ADM细胞对阿霉素的敏感度(x±s, n=3)Figure 1 Sensitivity of MDA-MB-468 and MDA-MB-468/ADM cells to adriamycin after 24h treatment detected by MTT assay (x±s, n=3)2.2 MDA-MB-468/ADM细胞中高表达耐药蛋白ABCG2
与正常MDA-MB-468细胞相比，MDA-MB-468/ADM细胞中代表ABCG2表达水平的红色荧光明显增多增强，见图 2A。Western blot检测结果也表明了MDA-MB-468/ADM细胞中ABCG2的高表达，见图 2B。提示用0.1 μmol/L阿霉素持续刺激后，三阴性乳腺癌MDA-MB-468细胞对阿霉素产生耐药。
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图 2 MDA-MB-468/ADM细胞中耐药蛋白ABCG2的表达Figure 2 Expression of drug resistance protein ABCG2 in MDA-MB-468/ADM cellsA: Immunofluorescence staining results showed the increased expression of ABCG2 (red) in MDA-MB-468/ADM cells, staining with DAPI (blue); B: Western blot analysis results showed high expression of ABCG2 in MDA-MB-468/ADM cells (n=3, *: P < 0.05)2.3 MDA-MB-468/ADM细胞高表达p-Stat3与cMyc
为探究MDA-MB-468细胞对阿霉素产生耐药的机制，我们进一步检测了MDA-MB-468/ADM细胞中转录因子p-stat3与cMyc的表达水平，观察MDA-MB-468细胞对阿霉素耐药性的产生是否与Stat3-cMyc途径有关。Western blot结果显示，MDA-MB-468/ADM中p-Stat3与cMyc的表达均明显升高，而两组细胞中总的Stat3表达水平未见显著变化。这些结果表明Stat3的激活和cMyc表达的增多可能参与了MDA-MB-468细胞对阿霉素耐药性的产生，见图 3。
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图 3 Western blot检测在MDA-MB-468和MDA-MB-468/ADM细胞中p-Stat3、Stat3及cMyc的表达(n=3, *: P < 0.05, **: P < 0.01)Figure 3 p-Stat3, Stat3 and cMyc expression in MDA-MB-468 and MDA-MB-468/ADM cells analyzed by Western blot (n=3, *: P < 0.05, **: P < 0.01)2.4 抑制Stat3活化可下调cMyc及ABCG2的表达
为进一步证明Stat3-cMyc途径在阿霉素诱导三阴性乳腺癌MDA-MB-468细胞耐药性产生中的作用，我们用Stat3磷酸化的抑制剂WP1066抑制Stat3活化，观察转录因子cMyc的表达是否受到影响。结果显示WP1066（1.25 μmol/L）作用于MDA-MB-468/ADM细胞后，磷酸化的Stat3显著降低（P=0.014），同时cMyc表达水平明显下降（P=0.044）。另外WP1066处理后MDA-MB-468/ADM细胞耐药蛋白ABCG2的表达也显著减少（P=0.000）。这些结果进一步说明阿霉素通过Stat3-cMyc途径诱导了MDA-MB-468细胞耐药性的产生，而抑制Stat3的活化后，耐药蛋白表达减少，细胞的耐药性减弱，见图 4。
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图 4 Western blot检测MDA-MB-468、MDA-MB-468/ADM、MDA-MB-468/ADM/WP1066三组细胞中p-Stat3、Stat3、cMyc及ABCG2的表达Figure 4 Stat3, p-Stat3, cMyc and ABCG2 expression in MDA-MB-468, MDA-MB-468/ADM and MDA-MB-468/ADM/WP1066 cells analyzed by Western blot*: P < 0.05, **: P < 0.01 (x±s, n=3)2.5 抑制Stat3活化增强了MDA-MB-468/ADM细胞对阿霉素的敏感度
由于WP1066下调了耐药蛋白ABCG2的表达，因此我们进一步通过MTT法检测MDA-MB-468/ADM细胞对阿霉素敏感度的变化。结果显示，阿霉素对MDA-MB-468/ADM细胞的EC50为6.774 μmol/L，而在使用WP1066之后的EC50降低至1.29 μmol/L（P=0.000），这表明WP1066抑制Stat3的活化增强了MDA-MB-468/ADM细胞对阿霉素的敏感度，见图 5。
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图 5 MTT法检测经36 h处理后的MDA-MB-468、MDA-MB-468/ADM、MDA-MB-468/ADM/WP 1066三组细胞对阿霉素的敏感度(x±s, n=3)Figure 5 Sensitivity of MDA-MB-468, MDA-MB-468/ADM and MDA-MB-468/ADM/WP1066 cells to adriamycin after 36h treatment detected by MTT assay (x±s, n=3)3 讨论
目前肿瘤细胞的耐药性是临床治疗的难点与研究的热点，阐明肿瘤耐药的机制可以为肿瘤的治疗提供新的治疗方向和靶点。
本研究应用低剂量阿霉素持续诱导人三阴性乳腺癌MDA-MB-468细胞，导致细胞产生耐药性，对阿霉素的敏感度显著下降，耐药蛋白ABCG2表达增高。为探究MDA-MB-468细胞对阿霉素产生耐药的机制，本实验进一步检测了MDA-MB-468/ADM细胞中转录因子p-stat3与cMyc的表达水平，观察MDA-MB-468细胞对阿霉素耐药性的产生与Stat3-cMyc途径有关。为进一步证明Stat3-cMyc途径在阿霉素诱导三阴性乳腺癌MDA-MB-468细胞耐药性产生中的作用，实验用Stat3磷酸化的抑制剂WP1066抑制Stat3活化，发现转录因子cMyc的表达也受到影响。进一步的机制研究揭示了Stat3-cMyc通路在阿霉素诱导的耐药中具有重要作用。
文献报道，Stat3信号通路与肿瘤细胞对化疗的耐药性有关[7]。Stat3的激活可以帮助癌细胞逃避由药物引起的死亡，从而诱发耐药性。Yue等[8]证明了Stat3的过度活化可以促进顺铂耐药的卵巢癌进展，相反，如果抑制Stat3信号通路则会促进耐药性癌细胞的凋亡，增加癌细胞对各种药物的敏感度。Li等[9]研究也有相似的发现，抑制Stat3信号通路后人胃癌细胞的凋亡增强，耐药性减弱。那么Stat3在三阴性乳腺癌耐药性的产生中有何作用？文献报道，乳腺癌组织中Stat3的活化增强与乳腺癌的临床分期和侵袭转移密切相关[10]。多种致癌性细胞因子与细胞膜的相应受体结合后导致Stat3与酪氨酸磷酸化通道相偶联后被激活，激活后的Stat3可在核内与特异性DNA启动子相结合，调节cMyc、Oct4、Sox2等相关基因表达[11]。作为调节多种转录因子功能的重要枢纽，Stat3有望成为肿瘤基因治疗中的有效靶点。有研究表明，在肿瘤中cMyc的表达水平与耐药性有关[4, 12-13]，cMyc能够调控ABC转运蛋白的表达水平，而ABCG2与肿瘤细胞的耐药性直接相关，但Stat3/cMyc在三阴性乳腺癌产生耐药性方面的影响及机制却未见报道。
本研究发现低浓度（0.1 μmol/L）阿霉素持续刺激使MDA-MB-468细胞对阿霉素的敏感度明显降低，MDA-MB-468/ADM细胞中p-Stat3和cMyc的表达较MDA-MB-468细胞显著增加，这些发现与上述文献中对Stat3和cMyc在肿瘤耐药性中的作用相一致。另外，刘丽等[6]在喉鳞癌细胞的研究中也揭示了Stat3-cMyc通路的重要作用，与本研究的结果相吻合。由此推测，MDA-MB-468/ADM对阿霉素耐药的机制很可能与Stat3的激活和p-Stat3介导的cMyc表达的增多有关。为进一步证明Stat3-cMyc通路在阿霉素诱导的乳腺癌耐药性中的关键作用，本实验应用WP1066抑制MDA-MB-468/ADM中Stat3的活化，发现随着p-Stat3的降低，cMyc和ABCG2的表达也相应下降，这与Granato等[14]证实抑制Stat3信号可下调cMyc的表达一致。再次MTT检测发现WP1066作用后MDA-MB-468/ADM细胞对阿霉素的敏感度显著增强，这与Li等[9]研究结果一致。
总之，本实验结果表明阿霉素可以诱导Stat3活化，上调转录因子cMyc及耐药蛋白ABCG2的表达，促进了三阴性乳腺癌MDA-MB-468细胞对阿霉素耐药性的产生。因此，抑制Stat3的表达与活化可有效逆转乳腺癌对阿霉素的耐药性，特异性靶向Stat3-cMyc途径联合化疗药物治疗有望成为一种有效治疗乳腺癌的新措施，改善乳腺癌患者的预后。
Competing interests: The authors declare that they have no competing interests.作者贡献柴东奇：查阅文献，构思及撰写文章王卫星：指导文章书写及修改 -
[1] Diaz-Ruiz R, Rigoulet M, Devin A. The Warburg and Crabtree effects: On the origin of cancer cell energy metabolism and of yeast glucose repression[J]. Biochim Biophys Acta, 2011, 1807(6): 568-576. doi: 10.1016/j.bbabio.2010.08.010
[2] Newman AC, Maddocks ODK. One-carbon metabolism in cancer[J]. Br J Cancer, 2017, 116(12): 1499-1504. doi: 10.1038/bjc.2017.118
[3] Maddocks OD, Berkers CR, Mason SM, et al. Serine starvation induces stress and p53-dependent metabolic remodelling in cancer cells[J]. Nature, 2013, 493(7433): 542-546. doi: 10.1038/nature11743
[4] Newman AC, Maddocks ODK. Serine and Functional Metabolites in Cancer[J]. Trends Cell Biol, 2017, 27(9): 645-657. doi: 10.1016/j.tcb.2017.05.001
[5] Dayton TL, Jacks T, Vander Heiden MG. PKM2, cancer metabolism, and the road ahead[J]. EMBO Rep, 2016, 17(12): 1721-1730. doi: 10.15252/embr.201643300
[6] Hitosugi T, Zhou L, Elf S, et al. Phosphoglycerate mutase 1 coordinates glycolysis and biosynthesis to promote tumor growth[J]. Cancer Cell, 2012, 22(5): 585-600. doi: 10.1016/j.ccr.2012.09.020
[7] Possemato R, Marks KM, Shaul YD, et al. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer[J]. Nature, 2011, 476(7360): 346-350. doi: 10.1038/nature10350
[8] Ma X, Li B, Liu J, et al. Phosphoglycerate dehydrogenase promotes pancreatic cancer development by interacting with eIF4A1 and eIF4E[J]. J Exp Clin Cancer Res, 2019, 38(1): 66. doi: 10.1186/s13046-019-1053-y
[9] Zhang B, Zheng A, Hydbring P, et al. PHGDH Defines a Metabolic Subtype in Lung Adenocarcinomas with Poor Prognosis[J]. Cell Rep, 2017, 19(11): 2289-2303. doi: 10.1016/j.celrep.2017.05.067
[10] Ducker GS, Ghergurovich JM, Mainolfi N, et al. Human SHMT inhibitors reveal defective glycine import as a targetable metabolic vulnerability of diffuse large B-cell lymphoma[J]. Proc Natl Acad Sci U S A, 2017, 114(43): 11404-11409. doi: 10.1073/pnas.1706617114
[11] Macfarlane AJ, Perry CA, McEntee MF, et al. Shmt1 heterozygosity impairs folate-dependent thymidylate synthesis capacity and modifies risk of Apc(min)-mediated intestinal cancer risk[J]. Cancer Res, 2011, 71(6): 2098-2107. doi: 10.1158/0008-5472.CAN-10-1886
[12] Pai YJ, Leung KY, Savery D, et al. Glycine decarboxylase deficiency causes neural tube defects and features of non-ketotic hyperglycinemia in mice[J]. Nat Commun, 2015, 6: 6388. doi: 10.1038/ncomms7388
[13] Reina-Campos M, Diaz-Meco MT, Moscat J. The complexity of the serine glycine one-carbon pathway in cancer[J]. J Cell Biol, 2020, 219(1): e201907022. doi: 10.1083/jcb.201907022
[14] Zhang WC, Shyh-Chang N, Yang H, et al. Glycine decarboxylase activity drives non-small cell lung cancer tumor-initiating cells and tumorigenesis[J]. Cell, 2012, 148(1-2): 259-272. doi: 10.1016/j.cell.2011.11.050
[15] Clare CE, Brassington AH, Kwong WY, et al. One-Carbon Metabolism: Linking Nutritional Biochemistry to Epigenetic Programming of Long-Term Development[J]. Annu Rev Anim Biosci, 2019, 7: 263-287. doi: 10.1146/annurev-animal-020518-115206
[16] Yang M, Vousden KH. Serine and one-carbon metabolism in cancer[J]. Nat Rev Cancer, 2016, 16(10): 650-662. doi: 10.1038/nrc.2016.81
[17] Ducker GS, Chen L, Morscher RJ, et al. Reversal of Cytosolic One-Carbon Flux Compensates for Loss of the Mitochondrial Folate Pathway[J]. Cell Metab, 2016, 23(6): 1140-1153. doi: 10.1016/j.cmet.2016.04.016
[18] Nilsson R, Jain M, Madhusudhan N, et al. Metabolic enzyme expression highlights a key role for MTHFD2 and the mitochondrial folate pathway in cancer[J]. Nat Commun, 2014, 5: 3128. doi: 10.1038/ncomms4128
[19] Nishimura T, Nakata A, Chen X, et al. Cancer stem-like properties and gefitinib resistance are dependent on purine synthetic metabolism mediated by the mitochondrial enzyme MTHFD2[J]. Oncogene, 2019, 38(14): 2464-2481. doi: 10.1038/s41388-018-0589-1
[20] Koufaris C, Valbuena GN, Pomyen Y, et al. Systematic integration of molecular profiles identifies miR-22 as a regulator of lipid and folate metabolism in breast cancer cells[J]. Oncogene, 2016, 35(21): 2766-2776. doi: 10.1038/onc.2015.333
[21] Pikman Y, Puissant A, Alexe G, et al. Targeting MTHFD2 in acute myeloid leukemia[J]. J Exp Med, 2016, 213(7): 1285-1306. doi: 10.1084/jem.20151574
[22] Nilsson R, Nicolaidou V, Koufaris C. Mitochondrial MTHFD isozymes display distinct expression, regulation, and association with cancer[J]. Gene, 2019, 716: 144032. doi: 10.1016/j.gene.2019.144032
[23] Fan J, Ye J, Kamphorst JJ, et al. Quantitative flux analysis reveals folate-dependent NADPH production[J]. Nature, 2014, 510(7504): 298-302. doi: 10.1038/nature13236
[24] Meiser J, Tumanov S, Maddocks O, et al. Serine one-carbon catabolism with formate overflow[J]. Sci Adv, 2016, 2(10): e1601273. doi: 10.1126/sciadv.1601273
[25] Struck AW, Thompson ML, Wong LS, et al. S-adenosyl-methionine-dependent methyltransferases: highly versatile enzymes in biocatalysis, biosynthesis and other biotechnological applications[J]. Chembiochem, 2012, 13(18): 2642-2655. doi: 10.1002/cbic.201200556
[26] Maddocks OD, Labuschagne CF, Adams PD, et al. Serine Metabolism Supports the Methionine Cycle and DNA/RNA Methylation through De Novo ATP Synthesis in Cancer Cells[J]. Mol Cell, 2016, 61(2): 210-221. doi: 10.1016/j.molcel.2015.12.014
[27] Mentch SJ, Mehrmohamadi M, Huang L, et al. Histone Methylation Dynamics and Gene Regulation Occur through the Sensing of One-Carbon Metabolism[J]. Cell Metab, 2015, 22(5): 861-873. doi: 10.1016/j.cmet.2015.08.024
[28] Zeng JD, Wu WKK, Wang HY, et al. Serine and one-carbon metabolism, a bridge that links mTOR signaling and DNA methylation in cancer[J]. Pharmacol Res, 2019, 149: 104352. doi: 10.1016/j.phrs.2019.104352
[29] Kottakis F, Nicolay BN, Roumane A, et al. LKB1 loss links serine metabolism to DNA methylation and tumorigenesis[J]. Nature, 2016, 539(7629): 390-395. doi: 10.1038/nature20132
[30] Bindu DP, Snyder SH. H2S signalling through protein sulfhydration and beyond[J]. Nat Rev Mol Cell Biol, 2012, 13(8): 499-507. doi: 10.1038/nrm3391
[31] Shackelford DB, Shaw RJ. The LKB1-AMPK pathway: metabolism and growth control in tumour suppression[J]. Nat Rev Cancer, 2009, 9(8): 563-575. doi: 10.1038/nrc2676
[32] Gravel SP, Hulea L, Toban N, et al. Serine deprivation enhances antineoplastic activity of biguanides[J]. Cancer Res, 2014, 74(24): 7521-7533. doi: 10.1158/0008-5472.CAN-14-2643-T
[33] Maneikyte J, Bausys A, Leber B, et al. Dietary glycine decreases both tumor volume and vascularization in a combined colorectal liver metastasis and chemotherapy model[J]. Int J Biol Sci, 2019, 15(8): 1582-1590. doi: 10.7150/ijbs.35513
[34] Kim W, Woo HD, Lee J, et al. Dietary folate, one-carbon metabolism-related genes, and gastric cancer risk in Korea[J]. Mol Nutr Food Res, 2016, 60(2): 337-345. doi: 10.1002/mnfr.201500384
[35] Huang JY, Butler LM, Wang R, et al. Dietary Intake of One-Carbon Metabolism-Related Nutrients and Pancreatic Cancer Risk: The Singapore Chinese Health Study[J]. Cancer Epidemiol Biomarkers Prev, 2016, 25(2): 417-424. doi: 10.1158/1055-9965.EPI-15-0594
[36] Reina-Campos M, Linares JF, Duran A, et al. Increased Serine and One-Carbon Pathway Metabolism by PKCλ/ι Deficiency Promotes Neuroendocrine Prostate Cancer[J]. Cancer Cell, 2019, 35(3): 385-400. doi: 10.1016/j.ccell.2019.01.018
[37] Pacold ME, Brimacombe KR, Chan SH, et al. A PHGDH inhibitor reveals coordination of serine synthesis and one-carbon unit fate[J]. Nat Chem Biol, 2016, 12(6): 452-458. doi: 10.1038/nchembio.2070
[38] Koufaris C, Gallage S, Yang T, et al. Suppression of MTHFD2 in MCF-7 Breast Cancer Cells Increases Glycolysis, Dependency on Exogenous Glycine, and Sensitivity to Folate Depletion[J]. J Proteome Res, 2016, 15(8): 2618-2625. doi: 10.1021/acs.jproteome.6b00188
[39] Locasale JW. Serine, glycine and one-carbon units: cancer metabolism in full circle[J]. Nat Rev Cancer, 2013, 13(8): 572-583. doi: 10.1038/nrc3557
[40] Toh TB, Lim JJ, Chow EK. Epigenetics in cancer stem cells[J]. Mol Cancer, 2017, 16(1): 29. doi: 10.1186/s12943-017-0596-9
[41] Akar RO, Selvi S, Ulukaya E, et al. Key actors in cancer therapy: epigenetic modifiers[J]. Turk J Biol, 2019, 43(3): 155-170. doi: 10.3906/biy-1903-39
[42] Eckschlager T, Plch J, Stiborova M, et al. Histone Deacetylase Inhibitors as Anticancer Drugs[J]. Int J Mol Sci, 2017, 18(7): 1414. doi: 10.3390/ijms18071414
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