肝细胞癌中UBE2S互作蛋白的筛选及预后模型构建

doi:10.13481/j.1671-587X.20240121

吉林大学学报(医学版) ›› 2024, Vol. 50 ›› Issue (1): 168-177.doi: 10.13481/j.1671-587X.20240121

• 临床研究 • 上一篇

肝细胞癌中UBE2S互作蛋白的筛选及预后模型构建

王小燕^1,²,张豪^2,³,郭泽皓^2,³,曹骏^2,³,莫之婧^2,³()

^1.桂林医学院智能医学与生物技术学院实验教学中心，广西桂林 541199
^2.桂林医学院广西高校生物化学与分子生物学重点实验室，广西桂林 541199
^3.桂林医学院智能医学与生物技术学院生物化学教研室，广西桂林 541199

收稿日期:2023-03-28 出版日期:2024-01-28 发布日期:2024-01-31
通讯作者: 莫之婧 E-mail:mozhijing@glmc.edu.cn
作者简介:王小燕（1983－），女，江西省上饶市人，高级实验师，理学硕士，主要从事疾病分子机制方面的研究。
基金资助:
国家自然科学基金项目(32060159);广西壮族自治区科技厅自然科学基金项目(2020GXNSFAA159110);广西壮族自治区教育厅广西高校中青年教师基础能力提升项目(2023KY0525)

Screening of UBE2S interacting protein and construction of prognostic model in hepatocellular carcinoma

Xiaoyan WANG^1,²,Hao ZHANG^2,³,Zehao GUO^2,³,Jun CAO^2,³,Zhijing MO^2,³()

^1.Department of Experimental Teaching Center, School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
^2.Key Laboratory of Biochemistry and Molecular Biology of Guangxi Institutions of Higher Learning, Gulin Medical University, Guilin 541199, China
^3.Department of Biochemistry, College of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China

Received:2023-03-28 Online:2024-01-28 Published:2024-01-31
Contact: Zhijing MO E-mail:mozhijing@glmc.edu.cn

摘要/Abstract

摘要：

目的筛选泛素结合酶E2S（UBE2S）互作蛋白并构建肝细胞癌（HCC）基于UBE2S互作蛋白的预后模型（UIPM），分析UIPM评估HCC患者预后的价值。方法采用免疫共沉淀（Co-IP）技术筛选与Flag-UBE2S结合的蛋白复合体，经十二烷基硫酸钠-聚丙烯酰胺凝胶电泳（SDS-PAGE）和Western blotting法验证后，采用液相色谱-质谱联用仪（LC-MS）分析鉴定UBE2S互作蛋白，并对互作蛋白进行基因本体论（GO）功能和京都基因与基因组百科全书（KEGG）信号通路富集分析。采用R软件survival包筛选癌症基因组图谱（TGGA）中HCC预后相关蛋白与UBE2S互作蛋白取交集，通过LASSO回归分析从交集蛋白中获取关键蛋白构建UIPM，并建立预后模型风险评分公式，按照风险评分的中位值将TGGA中HCC患者分为高风险组和低风险组，通过受试者工作特征曲线（ROC）评估UIPM的预测准确性，并采用国际癌症基因组联盟（ICGC）数据库对UIPM预测准确性进行再次验证。采用单因素和多因素Cox回归分析评估UIPM风险评分是否为HCC的预后独立危险因素，并进一步构建列线图模型。结果 Co-IP联合LC-MS分析得到97个UBE2S互作蛋白。GO功能和KEGG信号通路富集分析，互作蛋白主要与半胱氨酸型内肽酶活性、氧化应激和细胞死亡有密切关联。TCGA筛选出5 163个HCC预后相关蛋白，与UBE2S互作蛋白取交集，获得40个预后相关互作蛋白，LASSO回归分析得到7个关键蛋白，包括UBE2S、热休克蛋白家族A成员8（HSPA8）、异质性胞核核糖核蛋白H1 （HNRNPH1）、含TCP1伴侣蛋白亚基3（CCT3）、真核翻译起始因子2亚基1（EIF2S1）、活化蛋白C激酶1受体（RACK1）和肌动蛋白相关蛋白2/3复合体亚基4（ARPC4），并构建了UIPM，高和低风险组HCC患者生存率存比较差异有统计学意义（P<0.05）。ROC曲线，UIPM预测HCC患者1、2和3年UIPM风险评分的ROC曲线下面积（AUC）值均大于0.7，表明预测模型准确度较高。ICGC数据库数据也证实UIPM预测准确度较高。单因素和多因素Cox回归分析，UIPM风险评分是HCC患者的独立预后危险因素（P<0.05）。列线图预测HCC患者生存率与实际生存率之间有较好的一致性。结论 97个互作蛋白与UBE2S相互作用，可能通过氧化应激和铁死亡相关通路的失调促进HCC发生发展。UIPM风险评分是HCC预后的独立危险因素，可以用于预测HCC患者预后。而UBE2S、HSPA8、HNRNPH1、CCT3、EIF2S1、RACK1和ARPC4有望成为HCC新的生物标志物和治疗靶点。

关键词: 泛素结合酶E2S, 肝细胞癌, 免疫共沉淀, 液相色谱-质谱联用仪, 预后分析

Abstract:

Objective To screen the interacting protein of ubiquitin-conjugating enzyme E2S （UBE2S） and construct the hepatocellular carcinoma （HCC） based on UBE2S interacting protein prognosis model （UIPM），and to discuss the value of UIPM in assessing the prognosis of the HCC patients. Methods Co-immunoprecipitation （Co-IP） was used to screen the protein complexes binding to Flag-UBE2S. After validation by sodium dodecyl sulphate-polyacrylamide gel electrophoresis （SDS-PAGE） and Western blotting methods；liquid chromatography-mass spectrometer （LC-MS） was used to identify the UBE2S interacting proteins； Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） signaling pathway enrichment analysis were conducted on these proteins； the prognosis-related proteins from The Cancer Genome Atlas （TCGA） were cross-referenced with UBE2S interacting proteins by survival package of R software；the key proteins were extracted through LASSO regression analysis to build the UIPM； the prognostic model risk scoring formula was established. The HCC patients in TCGA were divided into high risk group and low risk group based on median value of the risk scores. The predictive accuracy of UIPM was evaluated by receiver operating characteristic curve （ROC）， and the predictive accuracy was further validated by International Cancer Genome Consortium （ICGC） Database； univariate regression analysis and multivariate Cox regression analysis were used to detect whether the UIPM risk score was an independent prognostic factor for HCC. Furthermore， the nomogram model was built. Results A total of 97 UBE2S interacting proteins were identified through Co-IP combined with LC-MS analysis.The GO functional enrichment analysis and KEGG signaling pathway enrichment analysis results showed that the interacting proteins were closely associated with cysteine-type endopeptidase activity， oxidative stress， and cell death. The TCGA revealed 5 163 HCC prognosis-related proteins； after intersecting with UBE2S interacting proteins， 40 prognosis-related interacting proteins were found. Seven key proteins were determined through LASSO regression analysis， including UBE2S， heat shock protein family A member 8 （HSPA8）， heterogeneous nuclear ribonucleoprotein H1 （HNRNPH1），chaperonin containing TCP1 subunit 3 （CCT3），eukaryotic translation initiation factor 2 subunit 1 （EIF2S1）， receptor for activated C kinase 1 （RACK1）， and actin related protein 2/3 complex subunit 4 （ARPC4）， and the UIPM was constructed. There was significant difference in survival rate of the patients between high risk group and low risk group （P<0.05）. The ROC curve analysis results showed the area under ROC curve（AUC） values of UIPM for predicting 1-year， 2-year， and 3-year survival risk scores of the HCC patients were all greater than 0.7， indicating the model had high predictive accuracy. This was also confirmed by ICGC Database data. The univariate and multivariate Cox regression analysis results showed that the UIPM risk score was an independent prognostic risk factor for the HCC patients （P<0.05）. The nomogram results showed good consistency between predicted survival rate and actual survival rate of the patient. Conclusion A total of 97 interacting proteins that interact with UBE2S may promote the occurence and devolopment of HCC through oxidative stress and dysregulation of ferroptosis pathways. The UIPM risk score is an independent risk factor for the prognosis of HCC and can be used to predict the outcomes of the patients. UBE2S， HSPA8， HNRNPH1， CCT3， EIF2S1， RACK1， and ARPC4 could be regarded as the new biomarkers and therapeutic targets for HCC.

Key words: Ubiquitin-conjugating enzyme E2S, Hepatocellular carcinoma, Co-immunoprecipitation, Liquid chromatograph mass spectrometer, Prognostic analysis

中图分类号:

R735.7

王小燕,张豪,郭泽皓,曹骏,莫之婧. 肝细胞癌中UBE2S互作蛋白的筛选及预后模型构建[J]. 吉林大学学报(医学版), 2024, 50(1): 168-177.

Xiaoyan WANG,Hao ZHANG,Zehao GUO,Jun CAO,Zhijing MO. Screening of UBE2S interacting protein and construction of prognostic model in hepatocellular carcinoma[J]. Journal of Jilin University(Medicine Edition), 2024, 50(1): 168-177.

图/表 9

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参考文献 31

1	BRAY F， FERLAY J， SOERJOMATARAM I， et al. Global cancer statistics 2018： GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries［J］.CA Cancer J Clin，2018，68（6）：394-424.
2	CAO W， CHEN H D， YU Y W， et al. Changing profiles of cancer burden worldwide and in China： a secondary analysis of the global cancer statistics 2020［J］. Chin Med J， 2021， 134（7）： 783-791.
3	KIRKIN V， DIKIC I. Ubiquitin networks in cancer［J］. Curr Opin Genet Dev， 2011， 21（1）： 21-28.
4	LI Z Y， WANG Y， LI Y D， et al. Ube2s stabilizes β-Catenin through K11-linked polyubiquitination to promote mesendoderm specification and colorectal cancer development［J］. Cell Death Dis， 2018， 9（5）： 456.
5	TANG H， FANG T， JI M， et al. UBE2S exerts oncogenic activities in urinary bladder cancer by ubiquitinating TSC1［J］. Biochem Biophys Res Commun， 2021， 578： 7-14.
6	HU L， CHENG X B， BINDER Z， et al. Molecular and clinical characterization of UBE2S in glioma as a biomarker for poor prognosis and resistance to chemo-radiotherapy［J］. Front Oncol， 2021， 11： 640910.
7	ZHANG M J， LIU Y， YIN Y， et al. UBE2S promotes the development of ovarian cancer by promoting PI3K/AKT/mTOR signaling pathway to regulate cell cycle and apoptosis［J］. Mol Med， 2022， 28（1）： 62.
8	HU W J， LI M， CHEN Y G， et al. UBE2S promotes the progression and Olaparib resistance of ovarian cancer through Wnt/β-catenin signaling pathway［J］. J Ovarian Res， 2021， 14（1）： 121.
9	LIN T H， HSU W H， TSAI P H， et al. Dietary flavonoids， luteolin and quercetin， inhibit invasion of cervical cancer by reduction of UBE2S through epithelial-mesenchymal transition signaling［J］. Food Funct， 2017， 8（4）： 1558-1568.
10	LIU Z， XU L J. UBE2S promotes the proliferation and survival of human lung adenocarcinoma cells［J］. BMB Rep， 2018， 51（12）： 642-647.
11	HO J Y， LU H Y， CHENG H H， et al. UBE2S activates NF-κB signaling by binding with IκBα and promotes metastasis of lung adenocarcinoma cells［J］. Cell Oncol （Dordr）， 2021， 44（6）： 1325-1338.
12	QIN Y N， DU J， FAN C F. Ube2S regulates Wnt/β-catenin signaling and promotes the progression of non-small cell lung cancer［J］.Int J 　Med Sci，2020，17（2）： 274-279.
13	GUO Y J， CHEN X Y， ZHANG XW， et al. UBE2S and UBE2C confer a poor prognosis to breast cancer via downregulation of Numb ［J］. Front Oncol， 2023， 13： 992233.
14	PENG S M， CHEN X， HUANG C Y， et al. UBE2S as a novel ubiquitinated regulator of p16 and β-catenin to promote bone metastasis of prostate cancer［J］. Int J Biol Sci， 2022， 18（8）： 3528-3543.
15	PAN Y H， YANG M， LIU L P， et al. UBE2S enhances the ubiquitination of p53 and exerts oncogenic activities in hepatocellular carcinoma［J］. Biochem Biophys Res Commun， 2018， 503（2）： 895-902.
16	ZHANG R Y， LIU Z K， WEI D， et al. UBE2S interacting with TRIM28 in the nucleus accelerates cell cycle by ubiquitination of p27 to promote hepatocellular carcinoma development［J］. Signal Transduct Target Ther， 2021， 6（1）： 64.
17	GUI L， ZHANG S C， XU Y Z， et al. UBE2S promotes cell chemoresistance through PTEN-AKT signaling in hepatocellular carcinoma［J］. Cell Death Discov， 2021， 7（1）： 357.
18	MA Y L， LI K Z， LI S J， et al. Prognostic value of ubiquitin-conjugating enzyme E2 S overexpression in hepatocellular carcinoma［J］. Int J Biol Macromol， 2018， 119： 225-231.
19	GOEMAN J J. L1 penalized estimation in the Cox proportional hazards model［J］. Biom J， 2010， 52（1）： 70-84.
20	COMBS J A， DENICOLA G M. The non-essential amino acid cysteine becomes essential for tumor proliferation and survival［J］. Cancers，2019，11（5）： 678.
21	ANGELI J P F， SCHNEIDER M， PRONETH B，et al. Inactivation of the ferroptosis regulator Gpx4 triggers acute renal failure in mice［J］.Nat Cell Biol，2014， 16（12）： 1180-1191.
22	YANG W S， SRIRAMARATNAM R， WELSCH M E，et al. Regulation of ferroptotic cancer cell death by GPX4［J］. Cell， 2014， 156（1/2）： 317-331.
23	JIANG X J， STOCKWELL B R， CONRAD M. Ferroptosis： mechanisms， biology and role in disease［J］.Nat Rev Mol Cell Biol，2021，22（4）：266-282.
24	MATSCHKE V， THEISS C， MATSCHKE J. Oxidative stress： the lowest common denominator of multiple diseases［J］. Neural Regen Res， 2019， 14（2）： 238-241.
25	WANG J， CHEN W， WEI W W， et al. Oncogene TUBA1C promotes migration and proliferation in hepatocellular carcinoma and predicts a poor prognosis［J］. Oncotarget， 2017， 8（56）： 96215-96224.
26	JIANG K Q， DONG C Y， YIN Z L， et al. Exosome-derived ENO1 regulates integrin α6β4 expression and promotes hepatocellular carcinoma growth and metastasis［J］. Cell Death Dis， 2020， 11（11）： 972.
27	XU H， DONG X Y， CHEN Y M， et al. Serum exosomal hnRNPH1 mRNA as a novel marker for hepatocellular carcinoma［J］. Clin Chem Lab Med， 2018， 56（3）： 479-484.
28	CHEN Y H， PENG C H， CHEN J R， et al. WTAP facilitates progression of hepatocellular carcinoma via m6A-HuR-dependent epigenetic silencing of ETS1［J］. Mol Cancer， 2019， 18（1）： 127.
29	YANG C X， SHAO Y D， WANG X J， et al. The effect of the histone chaperones HSPA8 and DEK on tumor immunity in hepatocellular carcinoma［J］. Int J Mol Sci， 2023， 24（3）： 2653.
30	DUAN F F， WU H， JIA D W， et al. O-GlcNAcylation of RACK1 promotes hepatocellular carcinogenesis［J］. J Hepatol， 2018， 68（6）： 1191-1202.
31	HUANG S L， DONG C R， LI D， et al. ARPC2： a pan-cancer prognostic and immunological biomarker that promotes hepatocellular carcinoma cell proliferation and invasion［J］. Front Cell Dev Biol， 2022， 10： 896080.

PF number	Accession	Score	Mass	Match	Sequence	emPAI	Protein
3	P08670	873	53 676	24	16	3.17	VIM
6	P62736	588	42 381	26	13	3.49	ACTA2
9	P13645	509	59 020	11	8	0.82	KRT10
11	Q92614	385	234 168	6	5	0.09	MYO18A
13	P11142	330	71 082	6	5	0.31	HSPA8
14	P06733	314	47 481	6	5	0.50	ENO1
15	P35527	311	62 255	5	5	0.29	KRT9
16	P35908	294	65 678	7	6	0.41	KRT2
17	P02533	282	51 872	6	5	0.45	KRT14
18	P08779	277	51 578	6	5	0.45	KRT16
20	P25705	245	59 828	3	3	0.17	ATP5F1A
22	P11021	231	72 402	5	5	0.25	HSPA5
24	Q9BQE3	212	50 548	5	4	0.37	TUBA1C
25	P06396	195	86 043	6	4	0.25	GSN
26	P23396	190	26 842	4	4	0.60	RPS3
27	P07437	175	50 095	4	4	0.29	TUBB
30	A0A075B6S2	133	13 249	4	2	0.58	IGKV2D-29
31	P01023	125	164 613	2	2	0.04	A2M
32	P52272	122	77 749	3	2	0.13	HNRNPM
33	P13929	117	47 299	2	2	0.14	ENO3

Gene name	Gene ID	Gene biotype	HR	95% CI	P_Cox
CCT3	ENSG00000163468	Protein coding	2.087	1.459－2.985	5.63687E-05
TUBA1C	ENSG00000167553	Protein coding	2.040	1.433－2.904	7.63003E-05
ARPC4	ENSG00000241553	Protein coding	2.048	1.433－2.928	8.44439E-05
ENO1	ENSG00000074800	Protein coding	1.982	1.390－2.826	0.000 156 723
HNRNPH1	ENSG00000169045	Protein coding	1.950	1.366－2.784	0.000 236 773
PRDX1	ENSG00000117450	Protein coding	1.899	1.338－2.696	0.000 333 502
H2AZ1	ENSG00000164032	Protein coding	1.902	1.335－2.710	0.000 369 261
IDH3B	ENSG00000101365	Protein coding	1.840	1.294－2.615	0.000 684 482
RAB6A	ENSG00000175582	Protein coding	1.831	1.287－2.605	0.000 769 835
SLC2A1	ENSG00000117394	Protein coding	1.813	1.275－2.577	0.000 926 358
PKM	ENSG00000067225	Protein coding	1.807	1.271－2.568	0.000 975 417
EIF2S1	ENSG00000134001	Protein coding	1.774	1.246－2.524	0.001 459 454
SLC25A3	ENSG00000075415	Protein coding	1.758	1.239－2.495	0.001 574 133
YWHAZ	ENSG00000164924	Protein coding	1.758	1.238－2.496	0.001 614 956
CAPZA2	ENSG00000198898	Protein coding	1.740	1.221－2.477	0.002 150 215
RPL18	ENSG00000063177	Protein coding	1.723	1.214－2.447	0.002 339 329
CALM1	ENSG00000198668	Protein coding	1.709	1.200－2.432	0.002 938 229
AKR1B10	ENSG00000198074	Protein coding	1.711	1.198－2.444	0.003 143 354
WTAP	ENSG00000146457	Protein coding	1.704	1.196－2.427	0.003 170 283
ACTR3	ENSG00000115091	Protein coding	1.670	1.177－2.369	0.004 042 542

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[4]	崔银星, 孔菲, 赵旭, 高普均. O-GlcNAc转移酶在肝细胞癌组织中的表达及其临床意义[J]. 吉林大学学报(医学版), 2017, 43(05): 980-984.
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[6]	张毅，张君薇，谢淑丽，王广义. RNAi沉默STAT3基因联合mTOR抑制剂rapamycin诱导BEL-7402肝癌细胞凋亡[J]. 吉林大学学报(医学版), 2013, 39(5): 903-908.
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[8]	丁军, 刘桂峰, 修殿辉, 程凯亮, 赵金山. 葡聚糖超顺磁性氧化铁纳米颗粒在检测小鼠肝癌病灶中的应用及效果评价[J]. J4, 2010, 36(6): 1167-1170.
[9]	孙亚欣，张志超，贾明库. CD40与ICAM-1在原发性肝细胞癌组织中的表达及临床意义[J]. J4, 2009, 35(2): 348-351.
[10]	郭宏华，王江滨，孙文伟，李岩，张建中. 生长抑素受体亚型SSTR2和SSTR5 mRNA在肝癌组织中的表达及其临床意义[J]. J4, 2009, 35(1): 154-158.
[11]	李玉琴，谭岩，李树蕾，刘力华，段秀梅，方艳秋，许淑芬. 构建人肝细胞癌相关抗原HCA661和mtHSP70刺激表位的融合基因疫苗[J]. J4, 2007, 33(2): 373-376.

肝细胞癌中UBE2S互作蛋白的筛选及预后模型构建

Screening of UBE2S interacting protein and construction of prognostic model in hepatocellular carcinoma

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