Four-protein model for predicting prognostic risk of lung cancer

doi:10.1007/s11684-021-0867-0

Front. Med.

2022, Vol. 16

Issue (4) : 618-626 https://doi.org/10.1007/s11684-021-0867-0

RESEARCH ARTICLE

Four-protein model for predicting prognostic risk of lung cancer

Xiang Wang¹, Minghui Wang¹, Lin Feng¹, Jie Song¹, Xin Dong²(

), Ting Xiao¹(

), Shujun Cheng¹(

)

¹. State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
². Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China

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Abstract

Patients with lung cancer at the same stage may have markedly different overall outcome and a lack of specific biomarker to predict lung cancer outcome. Heat-shock protein 90 β (HSP90β) is overexpressed in various tumor cells. In this study, the ELISA results of HSP90β combined with CEA, CA125, and CYFRA21-1 were used to construct a recursive partitioning decision tree model to establish a four-protein diagnostic model and predict the survival of patients with lung cancer. Survival analysis showed that the recursive partitioning decision tree could distinguish the prognosis between high- and low-risk groups. Results suggested that the joint detection of HSP90β, CEA, CA125, and CYFRA21-1 in the peripheral blood of patients with lung cancer is plausible for early diagnosis and prognosis prediction of lung cancer.

Keywords lung cancer HSP90β decision tree model prognosis

Corresponding Author(s): Xin Dong,Ting Xiao,Shujun Cheng

About author:

Tongcan Cui and Yizhe Hou contributed equally to this work.

Just Accepted Date: 29 October 2021 Online First Date: 09 March 2022 Issue Date: 02 September 2022

Cite this article:

Xiang Wang,Minghui Wang,Lin Feng, et al. Four-protein model for predicting prognostic risk of lung cancer[J]. Front. Med., 2022, 16(4): 618-626.

URL:

https://academic.hep.com.cn/fmd/EN/10.1007/s11684-021-0867-0
https://academic.hep.com.cn/fmd/EN/Y2022/V16/I4/618

Group	Number	HSP90β levels (ng/mL)			P value
Group	Number	Mean±SD	Range	Median	P value
Healthy group	282	52.15±50.61	14.22–293.61	30.41	<0.001^a
?Age (year)					<0.001
??>60	93	71.47±58.19	14.37–293.61	50.17
??≤60	189	42.65±43.55	14.22–277.25	23.17
?Gender					0.394
??Male	182	53.07±50.30	14.37–293.61	32.09
??Female	100	50.82±51.55	14.22–277.25	29.57
Lung cancer	1162	196.65±127.72	15.96–686.28	162.02
?SCLC	80	247.11±123.38	40.71–661.23	221.80	<0.001^b
??Age					0.528
???>60	26	227.25±98.73	70.80–505.89	207.00
???≤60	54	256.68±133.44	40.71–661.23	231.15
??Gender					0.158
???Male	58	237.63±126.53	40.71–661.23	214.62
???Female	22	272.10±113.60	134.26–530.86	231.37
?NSCLC ??Age	1082	192.91±127.30	14.93–686.28	157.06	0.973
???>60	553	191.35±124.61	14.93–681.09	158.00
???≤60	529	194.55±130.15	15.54–686.28	155.01
??Gender
???Male	681	195.51±128.19	14.93–686.28	156.99	0.295
???Female	401	188.50±125.81	16.83–681.09	157.37
??Stage					0.130
???I	510	187.81±132.76	15.96–686.28	147.22
???II	204	195.67±118.11	16.66–663.66	169.90
???III–IV	350	196.85±124.20	14.93–673.27	159.59
???NA	18
??Lymph node metastasis					0.118
???Yes	459	197.63±123.92	15.54–673.27	161.57
???No	565	190.54±131.51	15.96–686.28	150.21
???NA	58
??Pathologic types					0.086
???LUSC	371	201.22±130.39	15.54–686.28	157.12
???LUAD	705	188.34±125.66	14.93–681.09	155.91
???NA	6
??Differentiation					0.137
???High	124	171.14±109.59	31.78–498.61	137.50
???Middle	550	196.88±129.22	15.96–681.09	164.41
???Low	378	197.34±130.44	14.93–686.28	156.26
???NA	30
??Smoking history					0.170
???Yes	576	196.41±126.28	15.96–686.28	157.69
???No	499	188.39±127.84	14.93–681.09	155.01
???NA	7
??Family history					0.143
???Yes	166	181.69±127.28	16.66–673.49	133.43
???No	904	194.63±126.87	14.93–686.28	160.56
???NA	12

Tab.1 Correlation between HSP90β protein concentration and clinical information of 1162 patients with lung cancer

Fig.1 (A) Plasma protein concentration of HSP90β in patients with lung cancer (NSCLC, non-small-cell lung cancer; SCLC, small-cell lung cancer). (B) Representative images of IHC for three types of lung cancer. (C) Expression of HSP90β in three types of lung cancer tumor and normal tissues.

Tab.2 Statistical result of HSP90β expression in tissues of three lung cancer types

Fig.2 Recursive partitioning decision tree model constructed using 150 patients with lung cancer. CA125, U/mL; CYFRA21-1, CEA, HSP90β, ng/mL.

Fig.3 (A) Overall survival analysis of all patients (log-rank test) based on high or low risk. (B) Forest plot illustrating the hazard ratio (95% CI) for overall survival calculated using univariate and multivariable Cox proportional hazard regression models. CI, confidence interval.

1	RL Siegel, KD Miller, A Jemal. Cancer statistics, 2015. CA Cancer J Clin 2015; 65(1): 5–29 https://doi.org/10.3322/caac.21254 pmid: 25559415
2	CK Park, SH Lee, JH Han, CY Kim, DW Kim, SH Paek, DG Kim, DS Heo, IH Kim, HW Jung. Recursive partitioning analysis of prognostic factors in WHO grade III glioma patients treated with radiotherapy or radiotherapy plus chemotherapy. BMC Cancer 2009; 9(1): 450 https://doi.org/10.1186/1471-2407-9-450 pmid: 20017960
3	KR Lamborn, SM Chang, MD Prados. Prognostic factors for survival of patients with glioblastoma: recursive partitioning analysis. Neuro-oncol 2004; 6(3): 227–235 https://doi.org/10.1215/S1152851703000620 pmid: 15279715
4	Y Liu, D Lin, T Xiao, Y Ma, Z Hu, H Zheng, S Zheng, Y Liu, M Li, L Li, Y Cao, S Guo, N Han, X Di, K Zhang, S Cheng, Y Gao. An immunohistochemical analysis-based decision tree model for estimating the risk of lymphatic metastasis in pN0 squamous cell carcinomas of the lung. Histopathology 2011; 59(5): 882–891 https://doi.org/10.1111/j.1365-2559.2011.04013.x pmid: 22092400
5	M Taipale, DF Jarosz, S Lindquist. HSP90 at the hub of protein homeostasis: emerging mechanistic insights. Nat Rev Mol Cell Biol 2010; 11(7): 515–528 https://doi.org/10.1038/nrm2918 pmid: 20531426
6	D Mahalingam, R Swords, JS Carew, ST Nawrocki, K Bhalla, FJ Giles. Targeting HSP90 for cancer therapy. Br J Cancer 2009; 100(10): 1523–1529 https://doi.org/10.1038/sj.bjc.6605066 pmid: 19401686
7	J Trepel, M Mollapour, G Giaccone, L Neckers. Targeting the dynamic HSP90 complex in cancer. Nat Rev Cancer 2010; 10(8): 537–549 https://doi.org/10.1038/nrc2887 pmid: 20651736
8	WB Pratt, DO Toft. Regulation of signaling protein function and trafficking by the hsp90/hsp70-based chaperone machinery. Exp Biol Med (Maywood) 2003; 228(2): 111–133 https://doi.org/10.1177/153537020322800201 pmid: 12563018
9	HM Beere. Stressed to death: regulation of apoptotic signaling pathways by the heat shock proteins. Sci STKE 2001; 2001(93): re1 pmid: 11752668
10	L Whitesell, EG Mimnaugh, B De Costa, CE Myers, LM Neckers. Inhibition of heat shock protein HSP90-pp60v-src heteroprotein complex formation by benzoquinone ansamycins: essential role for stress proteins in oncogenic transformation. Proc Natl Acad Sci USA 1994; 91(18): 8324–8328 https://doi.org/10.1073/pnas.91.18.8324 pmid: 8078881
11	A Kamal, MF Boehm, FJ Burrows. Therapeutic and diagnostic implications of Hsp90 activation. Trends Mol Med 2004; 10(6): 283–290 https://doi.org/10.1016/j.molmed.2004.04.006 pmid: 15177193
12	A Maloney, P Workman. HSP90 as a new therapeutic target for cancer therapy: the story unfolds. Expert Opin Biol Ther 2002; 2(1): 3–24 https://doi.org/10.1517/14712598.2.1.3 pmid: 11772336
13	JS Isaacs, W Xu, L Neckers. Heat shock protein 90 as a molecular target for cancer therapeutics. Cancer Cell 2003; 3(3): 213–217 https://doi.org/10.1016/S1535-6108(03)00029-1 pmid: 12676580
14	TM Gress, F Müller-Pillasch, C Weber, MM Lerch, H Friess, M Büchler, HG Beger, G Adler. Differential expression of heat shock proteins in pancreatic carcinoma. Cancer Res 1994; 54(2): 547–551 pmid: 8275493
15	AM Mileo, M Fanuele, F Battaglia, G Scambia, P Benedetti-Panici, S Mancuso, U Ferrini. Selective over-expression of mRNA coding for 90 kDa stress-protein in human ovarian cancer. Anticancer Res 1990; 10(4): 903–906 pmid: 2382987
16	SE Holt, DL Aisner, J Baur, VM Tesmer, M Dy, M Ouellette, JB Trager, GB Morin, DO Toft, JW Shay, WE Wright, MA White. Functional requirement of p23 and Hsp90 in telomerase complexes. Genes Dev 1999; 13(7): 817–826 https://doi.org/10.1101/gad.13.7.817 pmid: 10197982
17	A Akalin, LW Elmore, HL Forsythe, BA Amaker, ED McCollum, PS Nelson, JL Ware, SE Holt. A novel mechanism for chaperone-mediated telomerase regulation during prostate cancer progression. Cancer Res 2001; 61(12): 4791–4796 pmid: 11406554
18	P Csermely, T Schnaider, C Soti, Z Prohászka, G Nardai. The 90-kDa molecular chaperone family: structure, function, and clinical applications. A comprehensive review. Pharmacol Ther 1998; 79(2): 129–168 https://doi.org/10.1016/S0163-7258(98)00013-8 pmid: 9749880
19	AS Sreedhar, E Kalmár, P Csermely, YF Shen. Hsp90 isoforms: functions, expression and clinical importance. FEBS Lett 2004; 562(1–3): 11–15 https://doi.org/10.1016/S0014-5793(04)00229-7 pmid: 15069952
20	M Ogata, Z Naito, S Tanaka, Y Moriyama, G Asano. Overexpression and localization of heat shock proteins mRNA in pancreatic carcinoma. J Nippon Med Sch 2000; 67(3): 177–185 https://doi.org/10.1272/jnms.67.177 pmid: 10851351
21	V Cambiazo, M González, C Isamit, RB Maccioni. The β-isoform of heat shock protein hsp-90 is structurally related with human microtubule-interacting protein Mip-90. FEBS Lett 1999; 457(3): 343–347 https://doi.org/10.1016/S0014-5793(99)01070-4 pmid: 10471805
22	AS Sreedhar, K Mihály, B Pató, T Schnaider, A Steták, K Kis-Petik, J Fidy, T Simonics, A Maraz, P Csermely. Hsp90 inhibition accelerates cell lysis. Anti-Hsp90 ribozyme reveals a complex mechanism of Hsp90 inhibitors involving both superoxide- and Hsp90-dependent events. J Biol Chem 2003; 278(37): 35231–35240 https://doi.org/10.1074/jbc.M301371200 pmid: 12842893
23	X Liu, L Ye, J Wang, D Fan. Expression of heat shock protein 90 β in human gastric cancer tissue and SGC7901/VCR of MDR-type gastric cancer cell line. Chin Med J (Engl) 1999; 112(12): 1133–1137 pmid: 11721455
24	AS Sreedhar, P Csermely. Heat shock proteins in the regulation of apoptosis: new strategies in tumor therapy: a comprehensive review. Pharmacol Ther 2004; 101(3): 227–257 https://doi.org/10.1016/j.pharmthera.2003.11.004 pmid: 15031001
25	J Bertram, K Palfner, W Hiddemann, M Kneba. Increase of P-glycoprotein-mediated drug resistance by hsp 90 β. Anticancer Drugs 1996; 7(8): 838–845 https://doi.org/10.1097/00001813-199611000-00004 pmid: 8991187
26	R Molina, X Filella, JM Augé, R Fuentes, I Bover, J Rifa, V Moreno, E Canals, N Viñolas, A Marquez, E Barreiro, J Borras, P Viladiu. Tumor markers (CEA, CA 125, CYFRA 21-1, SCC and NSE) in patients with non-small cell lung cancer as an aid in histological diagnosis and prognosis. Comparison with the main clinical and pathological prognostic factors. Tumour Biol 2003; 24(4): 209–218 https://doi.org/10.1159/000074432 pmid: 14654716
27	AK Karam, BY Karlan. Ovarian cancer: the duplicity of CA125 measurement. Nat Rev Clin Oncol 2010; 7(6): 335–339 https://doi.org/10.1038/nrclinonc.2010.44 pmid: 20368726
28	S Cedrés, I Nuñez, M Longo, P Martinez, E Checa, D Torrejón, E Felip. Serum tumor markers CEA, CYFRA21-1, and CA-125 are associated with worse prognosis in advanced non-small-cell lung cancer (NSCLC). Clin Lung Cancer 2011; 12(3): 172–179 https://doi.org/10.1016/j.cllc.2011.03.019 pmid: 21663860
29	J-Y Xu, C Zhang, X Wang, L Zhai, Y Ma, Y Mao, K Qian, C Sun, Z Liu, S Jiang, M Wang, L Feng, L Zhao, P Liu, B Wang, X Zhao, H Xie, X Yang, L Zhao, Y Chang, J Jia, X Wang, Y Zhang, Y Wang, Y Yang, Z Wu, L Yang, B Liu, T Zhao, S Ren, A Sun, Y Zhao, W Ying, F Wang, G Wang, Y Zhang, S Cheng, J Qin, X Qian, Y Wang, J Li, F He, T Xiao, M Tan. Integrative proteomic characterization of human lung adenocarcinoma. Cell 2020; 182(1): 245–261.e17 https://doi.org/10.1016/j.cell.2020.05.043
30	X Wang, Y Wang, L Feng, M Wang, K Zhang, Y Mao, T Xiao, S Cheng. Elevated expression of lung development-related protein HSP90β indicates poor prognosis in non-small cell lung cancer through affecting the cell cycle and apoptosis. Signal Transduct Target Ther 2021; 6(1): 82 https://doi.org/10.1038/s41392-021-00465-y pmid: 33633110
31	TM Therneau, EJ Atkinson. An introduction to recursive partitioning using the RPART routines. Mayo Foundation: Technical report 1997; 61: 452
32	SH Millson, AW Truman, A Rácz, B Hu, B Panaretou, J Nuttall, M Mollapour, C Söti, PW Piper. Expressed as the sole Hsp90 of yeast, the α and β isoforms of human Hsp90 differ with regard to their capacities for activation of certain client proteins, whereas only Hsp90β generates sensitivity to the Hsp90 inhibitor radicicol. FEBS J 2007; 274(17): 4453–4463 https://doi.org/10.1111/j.1742-4658.2007.05974.x pmid: 17681020
33	MI Gallegos Ruiz, K Floor, P Roepman, JA Rodriguez, GA Meijer, WJ Mooi, E Jassem, J Niklinski, T Muley, N van Zandwijk, EF Smit, K Beebe, L Neckers, B Ylstra, G Giaccone. Integration of gene dosage and gene expression in non-small cell lung cancer, identification of HSP90 as potential target. PLoS One 2008; 3(3): e0001722 https://doi.org/10.1371/journal.pone.0001722 pmid: 18320023
34	Q Cheng, JT Chang, J Geradts, LM Neckers, T Haystead, NL Spector, HK Lyerly. Amplification and high-level expression of heat shock protein 90 marks aggressive phenotypes of human epidermal growth factor receptor 2 negative breast cancer. Breast Cancer Res 2012; 14(2): R62 https://doi.org/10.1186/bcr3168 pmid: 22510516
35	G Wang, X Gu, L Chen, Y Wang, B Cao, Q E. Comparison of the expression of 5 heat shock proteins in benign and malignant salivary gland tumor tissues. Oncol Lett 2013; 5(4): 1363–1369 https://doi.org/10.3892/ol.2013.1166 pmid: 23599795
36	BK Eustace, T Sakurai, JK Stewart, D Yimlamai, C Unger, C Zehetmeier, B Lain, C Torella, SW Henning, G Beste, BT Scroggins, L Neckers, LL Ilag, DG Jay. Functional proteomic screens reveal an essential extracellular role for hsp90α in cancer cell invasiveness. Nat Cell Biol 2004; 6(6): 507–514 https://doi.org/10.1038/ncb1131 pmid: 15146192
37	K Sidera, M Samiotaki, E Yfanti, G Panayotou, E Patsavoudi. Involvement of cell surface HSP90 in cell migration reveals a novel role in the developing nervous system. J Biol Chem 2004; 279(44): 45379–45388 https://doi.org/10.1074/jbc.M405486200 pmid: 15302889
38	S Tsutsumi, B Scroggins, F Koga, MJ Lee, J Trepel, S Felts, C Carreras, L Neckers. A small molecule cell-impermeant Hsp90 antagonist inhibits tumor cell motility and invasion. Oncogene 2008; 27(17): 2478–2487 https://doi.org/10.1038/sj.onc.1210897 pmid: 17968312
39	M Grunnet, JB Sorensen. Carcinoembryonic antigen (CEA) as tumor marker in lung cancer. Lung Cancer 2012; 76(2): 138–143 https://doi.org/10.1016/j.lungcan.2011.11.012 pmid: 22153832
40	S Ando, H Kimura, N Iwai, N Yamamoto, T Iida. Positive reactions for both Cyfra21-1 and CA125 indicate worst prognosis in non-small cell lung cancer. Anticancer Res 2003; 23(3C): 2869–2874 pmid: 12926125
41	L Hui, G Liping. Statistical estimation of diagnosis with genetic markers based on decision tree analysis of complex disease. Comput Biol Med 2009; 39(11): 989–992 https://doi.org/10.1016/j.compbiomed.2009.07.015 pmid: 19712931
42	D Al-Dlaeen, A Alashqur. Using decision tree classification to assist in the prediction of Alzheimer’s disease. International Conference on Computer Science and Information Technology 2014: 122–126
43	S Mai, T Turner, R Stocker. Using decision tree for diagnosing heart disease patients. Australasian Data Mining Conference 2011: 23–30

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