Ekspresija ziksina kod obolelih od nesitnoćelijskog karcinoma pluća

  • Dejan D Ilić Special Hospital for Lung Diseases “Ozren”, Sokobanja, Serbia
  • Milan Rančić Department of Internal medicine, Faculty of Medicine, University of Niš, Serbia
  • Tatjana Stoimenov Jevtović Institute of Biochemistry, Faculty of Medicine, University of Niš, Serbia
  • Veljko Petrović University of Novi Sad, Faculty of Technical Sciences, Serbia
  • Marina Petrović Department of Internal medicine, Faculty of Medical Sciences, University of Kragujevac, Serbia
Ključne reči: ziksin;, pluća, nesitnoćelijski karcinom;, tumorski markeri, biološki;, dijagnoza, diferencijalna

Sažetak


Uvod/Cilj. Nesitnoćelijski karcinom pluća (engl. non-small cell lung cancer ‒ NSCLC) je najčešći uzrok smrti od malignih tumora širom sveta. Rano otkrivanje bolesti najviše obećava u smislu smanjenja smrtnosti od ovog tipa karcinoma. Ziksin (ZYX) je član porodice proteina fokalnih adhezija, nedavno identifikovan kao potencijalni marker za rano otkrivanje NSCLC. Cilj studije bio je procena nivoa ekspresije ZYX kod obolelih od NSCLC i poređenje profila njegove ekspresije u serumu između ranih i odmaklih kliničkih stadijuma bolesti, različitih patohistoloških suptipova i različitih histoloških gradusa tumora. Metode. Uzorci krvi dobijeni su od 90 bolesnika sa verifikovanim NSCLC u svim kliničkim stadijumima bolesti i od 30 bolesnika bez kliničkih i radioloških znakova malignoma i bez prethodno verifikovane maligne bolesti. Za kvantitativno određivanje koncentracije humanog ZYX u krvi koristili smo ELISA (eng. enzyme-linked immunoadsorbent assay) test. Rezultati. Utvrđen je viši nivo ZYX u serumu bolesnika obolelih od NSCLC u poređenju sa kontrolnom grupom, sa izuzetno značajnom razlikom (p = 0,00). ROC kriva pokazala je visoku specifičnost testa sa AUC = 0,912. Nije bilo statistički značajne razlike u vrednostima ZYX kod dva najčešća tipa NSCLC, adenokarcinoma i skvamocelularnog karcinoma (p = 0,758). Nije utvrđena statistički značajna razlika u nivoima ZYX kod različitih kliničkih stadijuma bolesti (p = 0,518). Kod samo tri bolesnika verifikovan je dobro diferentovani tumor, pa nije bilo moguće izvući korisne podatke iz ovako malog uzorka. Nije utvrđena statistički značajna razlika u dobijenim vrednostima ZYX kod bolesnika sa srednje diferentovanim i loše diferentovanim tumorom (p = 0,48). Zaključak. Utvrdili smo da je ZYX prekomerno eksprimiran kod NSCLC, ali nivo ekspresije nije značajnije korelisao sa veličinom tumora, niti uznapredovalim tumor, node, metastasis (TNM) stadijumom bolesti. Naši rezultati sugerišu da serumski ZYX ima potencijal kao dijagnostički tumor marker za rano otkrivanje NSCLC, bez obzira da li se radi o adenokarcinomu ili skvamocelularnom karcinomu pluća.

Reference

Siegel RL, Miller KD, Jemal A. Cancer statistics. CA Cancer J Clin 2016; 66(1): 7‒30.

Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB, et al. The 2015 World Health Organization classi-fication of lung tumors: impact of genetic, clinical and radio-logic advances since the 2004 classification. J Thorac Oncol 2015; 10(9): 1243‒60.

Edge SB, Byrd DR, Compton CC, Fritz A.G, Greene FL, Trotti A. AJCC Cancer Staging Manual. 7th ed. Chicago, IL: Ameri-can Joint Committee on Cancer; 2010.

Sun N, Chen Z, Tan F, Zhang B, Yao R, Zhou C, et al. Isocitrate dehydrogenase 1 is a novel plasma biomarker for the diagnosis of nonsmall cell lung cancer. Clin. Cancer Res 2013; 19(18): 5136−45.

Li X, Asmitananda T, Gao L, Gai D, Song Z, Zhang Y, et al. Bi-omarkers in the lung cancer diagnosis: A clinical perspective. Neoplasma 2012; 59(5): 500−7.

Massion PP, Caprioli RM. Proteomic strategies for the charac-terization and the early detection of lung cancer. J Thorac On-col 2006; 1(9): 1027‒39.

Atkinson AJ J Colburn WA, DeGruttola VG, DeMets DL, Down-ing GJ, Hoth DF et al. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Phar-macol Ther 2001; 69(3): 89‒95.

Hoagland LF, Campa MJ, Gottlin EB, Herndon JE, Patz EF. Haptoglobin and post-translational glycan-modified deriva-tives as serum biomarkers for the diagnosis of non-small cell lung cancer Cancer 2007; 110(10): 2260‒8.

Ulivi P, Mercatali L, Casoni GL, Scarpi E, Bucchi L, Silvestrini R, at al. Multiple marker detection in peripheral blood for NSCLC diagnosis. PLoS One 2013; 8(2): e57401.

Kanoh Y, Abe T, Masuda N, Akahoshi T. Progression of non-small cell lung cancer: diagnostic and prognostic utility of ma-trix metalloproteinase-2, C-reactive protein and serum amy-loid A. Oncol Rep 2013; 29(2): 469‒73.

Sung HJ, Ahn JM, Yoon YH, Rhim TY, Park CS, Park JY, at al. Identification and validation of SAA as a potential lung cancer biomarker and its involvement in metastatic pathogenesis of lung cancer. J Proteome Res 2011; 10(3): 1383‒95.

Rodríguez-Piñeiro AM, Blanco-Prieto S, Sánchez-Otero N, Rodríguez-Berrocal FJ, de la Cadena MP. On the identification of bi-omarkers for non-small cell lung cancer in serum and pleural effusion J Proteomics 2010; 73(8): 1511‒22.

Zhang L, Chen J, Ke Y, Mansel RE, Jiang WG. Expression of pigment epithelial derived factor is reduced in non-small cell lung cancer and is linked to clinical outcome. Int J Mol Med 2006; 17(5): 937‒44.

Li Y, Zhang Y, Qiu F, Qiu Z. Proteomic identification of exo-somal LRG1: a potential urinary biomarker for detecting NSCLC. Electrophoresis 2011; 32(15): 1976‒83.

Yang J, Tan D, Asch HL, Swede H, Bepler G, Geradts J, at al. Prognostic significance of gelsolin expression level and varia-bility in non-small cell lung cancer. Lung Cancer 2004; 46: 29‒42.

Kim YJ, Sertamo K, Pierrard MA, Mesmin C, Kim SY, Schlesser M, at al. Verification of the Biomarker Candidates for Non-small-cell Lung Cancer Using a Targeted Proteomics Ap-proach. J Proteome Res 2015; 14(3): 1412‒9.

Duff MD, Mestre J, Maddali S, Yan ZP, Stapleton P, Daly JM. Analysis of gene expression in the tumor-associated macro-phage . Surg Res 2007; 142(1): 119‒28.

Smith MA, Blankman E, Gardel ML, Luettjohann L, Beckerle MC. A zyxin-mediated mechanism for actin stress fiber maintenance and repair. Dev Cell 2010; 19(3): 365‒76.

Hirota T, Morisaki T, Nishiyama Y, Marumoto T, Tada K, Hara T, at al. Zyxin, a regulator of actin filament assembly, targets the mitotic apparatus by interacting with h-warts/LATS1 tu-mor suppressor. J Cell Biol 2000; 149(5): 1073‒86.

Diepenbruck M, Waldmeier L, Ivanek R, Berninger P, Arnold P, van Nimwegen, at al. Tead2 expression levels control the subcel-lular distribution of yap and Taz, zyxin expression and epithe-lial–mesenchymal transition, J. Cell Sci 2014; 127(Pt 7): 1523–36.

Mise N, Savai R, Yu H, Schwarz J, Kaminski N, Eickelberg O. Zyxin is a transforming growth factor-β (TGF-β)/Smad3 tar-get gene that regulates lung cancer cell motility via integrin α5β1. J Biol Chem 2012; 287(37): 31393‒405.

Ma B, Cheng H, Gao R, Mu C, Chen L, Wu S, at al. Zyxin-Siah2–Lats2 axis mediates cooperation between Hippo and TGF-b signalling pathways. Nat Commun 2016; 7: 11123.

Sy SM, Lai PB, Pang E, Wong NL, To KF, Johnson PJ, at al. Novel identification of zyxin upregulations in the motile phe-notype of hepatocellular carcinoma, Mod Pathol 2006; 19(8): 1108–16.

Kawashima Y, Fukutomi T, Tomonaga T, Takahashi H, Nomura F, Maeda T, at al. High-yield peptide-extraction method for the discovery of subnanomolar biomarkers from small serum sam-ples. J Proteome Res 2010; 9(4): 1694‒705.

Mair P, Schoenbrodt F, Wilcox RR. WRS2: Wilcox robust esti-mation and testing. (English). CRAN. 2017. Available from: https://cran.r-project.org/web/packages/WRS2/index.html [cited 2018 July 18].

Torchiano M. Effsize: Efficient Effect Size Computation. CRAN. 2017. Available from:

https://cran.r-project.org/web/packages/effsize/index.html [cited 2018 July 18].

Grosjean P, Ibanez F. Pastecs: Package for Analysis of Space-Time Ecological Series. CRAN. 2014. Available from: https://cran.r-project.org/web/packages/pastecs/index.html [cited 2018 July 18].

Mendeş M, Akkartal E. Comparison of ANOVA F and WELCH tests with their respective permutation versions in terms of type I error rates and test power. Kafkas Univ Vet Fak Derg 2010; 16(5): 711–6.

Yuen KK. The two-sample trimmed t for unequal population variances. Biometrika 1974; 61(1): 165–70.

Wilcox RR. Introduction to robust estimation and hypothesis testing. 3rd ed. Amsterdam, Boston: Academic Press; 2012.

Sawilowsky SS. New effect size rules of thumb. J Mod Appl Statl Methods 2009; 8(2): 597‒99.

Wilcox RR, Tian TS. Measuring effect size: a robust heterosce-dastic approach for two or more groups. J Appl Stat 2011; 38(7): 1359–68.

Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fager-strom RM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011; 365(5): 395‒409.

Katki HA, Kovalchik SA, Berg CD, Cheung LC, Chaturvedi AK. Development and validation of risk models to select ever-smokers for CT lung-cancer screening. JAMA 2016; 315(21): 2300–11.

Chassagnon G, Revel MP. Dépistage du cancer du poumon: état des lieux et perspectives. J Radiol Diagn Intervent 2016; 97(4): 369‒74. (French)

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2021/01/15
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