cluster and principal component analysis of human glioblastoma multiforme (gbm) tumor proteome and principal component analysis of human glioblastoma multiforme (gbm) tumor proteome

background : glioblastoma multiforme (gbm) or grade iv astrocytoma is the most common and lethal adult malignant brain tumor. several of the molecular alterations detected in gliomas may have diagnostic and/or prognostic implications, proteomics has been widely applied in various areas of science, ranging from the deciphering of molecular pathogen nests of discuses. method: we extracted proteins of tumor and normal brain tissues and then evaluated the protein purity by bradford test and spectrophotometery method. in this study, we separated proteins by two-dimensional (2dg) gel electrophoresis method and the spots were then analyzed and compared using statistical data and specific software. proteins clustering analyses were performed on the list of proteins deemed significantly altered in glioblastoma tumors  ( t -test and one-way anova; p < 0.05). results: the 2d gel showed totally 876 spots. we reported, 172 spots exhibited different in expression level (fold > 2) for glioblastoma. on each analytical 2d gel, an average of 876 spots was observed. in this study, 188 spots exhibited up regulation of expression level, whereas the remaining 232 spots decreased in glioblastoma tumor relative to normal tissue. results demonstrate that functional clustering (up and down regulated) and principal component analysis has considerable merits in aiding the interpretation of proteomic data. conclusion: at the core of proteomics was 2d gel electrophoresis witch permitted the separation of thousands of protein , high resolution 2de can resolve up to 5,000 proteins simultaneously . using cluster analysis, we can also from groups of related variables, similar to what you do in factor analysis. keywords: glioblastoma; glioma; proteomics; cluster; 2dg electrophoresis please cite this article as: mehdi pooladi, mostafa rezaei-tavirani, mehrdad hashemi, saeed hesami-tackallou, solmaz khaghani-razi-abad, afshin moradi, ali reza zali, masoumeh mousavi, leila firozi-dalvand,azadeh rakhshan, mona zamanian azodi. cluster and principal component analysis of human glioblastoma multiforme (gbm) tumor proteome. iran j cancer prev. 2014; 7(2):87-95. references lemée jm, com e, clavreul a, avril t, quillien v, de tayrac m, pineau c, menei p. proteomic analysis of glioblastomas: what is the best brain control sample? j proteomics. 2013; 85:165-73. gollapalli k ,  ray s ,  srivastava r ,  renu d ,  singh p ,  dhali s ,  bajpaidikshit j ,  srikanth r ,  moiyadi a ,  srivastava s . investigation of serum proteome alterations in human glioblastomamultiforme. proteomics. 2012; 12(14):2378-90. zheng pp ,  kros jm ,  sillevis-smitt pa ,  luider tm . proteomics in primary brain tumors. front biosci.  2003; 8:451-63. collet b ,  guitton n ,  saïkali s ,  avril t ,  pineau c ,  hamlat a ,  mosser j , quillien v . differential analysis of glioblastomamultiforme proteome by a 2d-dige approach. proteome sci.  2011; 9(1):16. he j, liu y, lubman dm. targeting glioblastoma stem cells: cell surface markers. curr med chem. 2012; 19(35):6050-5. matthew e, zigzag d. mechanisism of glioma associated neovascularization. the american journal of pathology. 2012; 4:1126-40. chen s ,  zhao h ,  deng j ,  liao p ,  xu z ,  cheng y . comparative proteomics of glioma stem cells and differentiated tumor cells identifies s100a9 as a potential therapeutic target. j cell biochem. 2013; 114(12):2795-808. gajadhar a, desouzalv, siu kwm, guha a. primary malignant brain tumors-current and potential impact of proteomics-based analysis. drug discovery. 2010; 7:73. ohgaki h, kleihues p. genetic pathways to primary and secondary giioblastoma. the american journal of patbiology. 2007; 170 (5):1445-51. kleihues p, burger pc, scheithauer bw. the new who classification of brain tumors. brain pathol. 1993; 3(3):255-68. ohgaki h ,  dessen p ,  jourde b ,  horstmann s ,  nishikawa t ,  di patre pl ,  burkhard c ,  schüler d ,  probst-hensch nm ,  maiorkapc , baeza n , pisani p ,  yonekawa y ,  yasargil mg ,  lütolf um ,  kleihues p . genetic pathways to glioblastoma: a population-based study. cancer res.  2004; 64(19):6892-9. ohgaki h, kleihues p. population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. j neuropatholexp neurol. 2005; 64(6):479-89. degroot j ,  reardon da ,  batchelor tt . antiangiogenic therapy for glioblastoma. am socclinoncoleduc book.  2013;71-8. patel vn ,  gokulrangan g ,  chowdhury sa ,  chen y ,  sloan ae ,  koyutürk m , barnholtz- sloan j ,  chance mr . network signatures of survival in glioblastomamultiforme. ploscomput biol.  2013; 9(9):e1003237. desouza lv, matta a, karim z, mukherjee j, wang xs, krakovska o, zadeh g, guha a, siu km. role of moesin in hyaluronan induced cell migration in glioblastomamultiforme. mol cancer. 2013; 12:74. elstner a ,  stockhammer f ,  nguyen-dobinsky tn ,  nguyen ql , pilgermann i ,  gill a , guhr a ,  zhang t ,  von eckardstein k ,  picht t veelken j ,  martuza rl ,  von deimling a ,  kurtz a . identification of diagnostic serum protein profiles of glioblastoma patients. j neurooncol. 2011; 102(1):71-80. sallinen sl, sallinen pk, haapasalo hk, helin hj, helén pt, schraml p, kallioniemi op, kononen j. identification of differentially expressed genes in human gliomas by dna microarray and tissue chip techniques. cancer res. 2000; 60(23): 6617-22. furuta m, weil rj, vortmeyer ao, huang s, lei j, huang tn, lee ys, bhowmick da, lubensky ia, oldfield eh, zhuang z. protein patterns and proteins that identify subtypes of glioblastomamultiforme. oncogene. 2004; 23(40):6806-14. kim s, dougherty er, shmulevich i, hess kr, hamilton sr, trent jm, fuller gn, zhang w. identification of combination gene sets for glioma classification. mol cancer ther. 2002; 1(13):1229-36. park c k, hye june d, park s-h, jung h-w, choo b-k. moultifarious proteomic signatures and regional heterogenetic in glioblastomas . journal neurooncol. 2009; 98:31-39. diehn m ,  nardini c ,  wang ds ,  mcgovern s ,  jayaraman m ,  liang y , aldape k ,  cha s ,  kuo md . identification of noninvasive imaging surrogates for brain tumor gene-expression modules. procnatlacadsci usa.  2008; 105(13):5213-8.  earnest f 4th, kelly pj, scheithauer bw, kall ba, cascino tl, ehman rl, forbes gs, axley pl. cerebral astrocytomas: histopathologic correlation of mr and ct contrast enhancement with stereotactic biopsy. radiology. 1988; 166(3):823-7. hobbs sk, shi g, homer r, harsh g, atlas sw, bednarski md. magnetic resonance image-guided proteomics of human glioblastomamultiforme. j magnreson imaging. 2003; 18(5):530-6. jansen m ,  yip s ,  louis dn . molecular pathology in adult gliomas: diagnostic, prognostic, and predictive markers. lancet neurol. 2010; 9(7):717-26. riemenschneider mj ,  jeuken jw ,  wesseling p ,  reifenberger g . molecular diagnostics of glioma: stste of the art. actaneuropathol. 2010; 120(5):567-84. iwadate y ,  sakaida t ,  hiwasa t ,  nagai y ,  ishikura h ,  takiguchi m , yamaura a . molecular classification and survival prediction in human gliomas based on proteome analysis. cancer res.  2004; 64(7): 2496-501. boja es ,  rodriguez h . the path to clinical proteomics research: integration of proteomics, genomics, clinical laboratory and regulatory science. korean j lab med.  2011; 31(2):61-71. xiong g, xiao h, lu j, zhang d, bi c, peng l, xiong g, xiong l, chen p, liang s. differential protein expression in low-grade astrocytomas and peritumoral human brain tissues. neural regeneration research. 2010; 5 (24):1915-20. vogel tw ,  zhuang z ,  li j ,  okamoto h ,  furuta m ,  lee ys ,  zeng w , oldfield eh , vortmeyer ao ,  weil rj . proteins and protein pattern differences between glioma cell lines and glioblastomamultiforme. clin cancer res. 2005; 11(10):3624-32. petrás m, hutóczki g, varga i, vereb g, szöllosi j, bognár l, ruszthi p, kenyeres a, tóth j, hanzély z, scholtz b, klekner a. expression pattern of invasion-related molecules in brain tumors of different origin. magyonkol. 2009; 53(3):253-8. deighton rf ,  mcgregor r ,  kemp j ,  mcculloch j ,  whittle ir . glioma pathophysiology: insights emerging from proteomics. brain pathol. 2010; 20(4):691-703.  defaria gp, de oliveira ja, de oliveira jg, romano sde o, neto vm, maia rc. differences in the expression pattern of p-glycoprotein and mrp1 in low-grade and high-grade gliomas. cancer invest. 2008; 26(9):883-9. georgiou hm ,  rice ge ,  baker ms . proteomic analysis of human plasma: failure of centrifugal ultrafiltration to remove albumin and other high molecular weight proteins. proteomics.  2001; 1(12):1503-6. manabe t ,  mizuma h ,  watanabe k . a nondenaturing protein map of human plasma proteins correlated with a denaturing polypeptide map combining techniques of micro two-dimensional gel electrophoresis. electrophoresis. 1999; 20(4-5):830-5. shimazaki y ,  muro m ,  manabe t . selection of an effective enzyme for digestion of non-denaturing proteins using microscale two-dimensional electrophoresis. clinchimacta.  2000; 302(1-2):221-4. molloy mp ,  herbert br ,  slade mb ,  rabilloud t ,  nouwens as , williams kl ,  gooley aa . proteomic analysis of the escherichia coli outer membrane. eur j biochem.  2000; 267(10):2871-81. whittle ir, short dm, deighton rf, kerr le, smith c, mcculloch j. proteomics analysis of gliomas. br j neurosurg. 2007 dec;21(6):576-82. stummer w ,  pichlmeier u ,  meinel t ,  wiestler od ,  zanella f ,  reulen hj ; ala-glioma study group . fluorescence-guided surgery with 5-aminolevulinic acid for resection of malignant glioma: a randomised controlled multicentre phase iii trial. lancet oncol.  2006; 7(5):392-401. levidou g ,  korkolopoulou p ,  agrogiannis g ,  paidakakos n ,  bouramas d ,  patsouris e . low- grade oligodendroglioma of the pineal gland: a case report and review of the literature. diagn pathol.  2010; 5:59. schwartz sa ,  weil rj ,  johnson md ,  toms sa ,  caprioli rm . protein profiling in brain tumors using mass spectrometry: feasibility of a new technique for the analysis of protein expression. clin cancer res.  2004; 10(3):981-7. zhou h ,  ning z ,  wang f ,  seebun d ,  figeys d . proteomic reactors and their applications in biology. febs j.  2011; 278(20):3796-806. weiss w ,  görg a . high-resolution two-dimensional electrophoresis. methods mol biol. 2009; 564:13-32. banerjee hn ,  mahaffey k ,  riddick e ,  banerjee a ,  bhowmik n ,  patra m . search for a diagnostic/prognostic biomarker for the brain cancer glioblastomamultiforme by 2d-dige-ms technique. mol cell biochem. 2012; 367(1-2):59-63. zanini c, mandili g, bertin d, cerutti f, baci d, leone m, morra i, di montezemolo cordero l, forni m. analysis of different medulloblastoma histotypes by two-dimensional gel and maldi-tof. childs nerv syst. 2011; 27(12):2077-85. beckner me ,  chen x ,  an j ,  day bw ,  pollack if . proteomic characterization of harvested pseudopodia with differential gel electrophoresis and specific antibodies. lab invest.  2005; 85(3):316-27. meunier b ,  bouley j ,  piec i ,  bernard c ,  picard b ,  hocquette jf . data analysis methods for detection of differential protein expression in two-dimensional gel electrophoresis. anal biochem.  2005; 340(2):226-30. dowsey aw, dunn mg, yang gz. the role of bioinformatics in two dimensional gel electrophoresis. proteomics. 2003; 3(8):1567-96. appel r ,  hochstrasser d ,  roch c ,  funk m ,  muller af ,  pellegrini c . automatic classification of two-dimensional gel electrophoresis pictures by heuristic clustering analysis: a step toward machine learning. electrophoresis. 1988; 9(3):136-42. ardekani am ,  akhondi mm ,  sadeghi mr . application of genomic and proteomic technologies to early detection of cancer. arch iran med.  2008; 11(4):427-34. fang x ,  wang c ,  balgley bm ,  zhao k ,  wang w ,  he f ,  weil rj ,  lee cs . targeted tissue proteomic analysis of human astrocytomas. j proteome res.  2012; 11(8):3937-46. rosenkranz k, may c, meier c, marcus k. proteomic analysis of alterations induced by perinatal hypoxic-ischemic brain injury. j proteome res. 2012; 11(12):5794-803. shoemaker ld ,  achrol as ,  sethu p ,  steinberg gk ,  chang sd . clinical neuroproteomics and biomarkers: from basic research to clinical decision making. neurosurgery.  2012; 70(3):518-25. phan jh ,  quo cf ,  wang md . functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics. prog brain res.  2006; 158:83-108. gibbons fd ,  roth fp . judging the quality of gene expression-based clustering methods using gene annotation. genome res. 2002; 12(10):1574-81. d`haeseleer p. how does gene expression clustering work? nat biotechnol. 2005;23(12):1499-501. lilley ks ,  friedman db . all about dige: quantification technology for differential-display 2d-gel proteomics. expert rev proteomics. 2004; 1(4):401-9. harris ra, yang a, stein rc, lucy k, brusten l, herath a, parekh r, waterfield md, o'hare mj, neville ma, page mj, zvelebil mj. cluster analysis of an extensive human breast cancer cell line protein expression map database. proteomics. 2002; 2(2):212-23. jiménez cr ,  stam fj ,  li kw ,  gouwenberg y ,  hornshaw mp ,  de winter f , verhaagen j ,  smit ab . proteomics of the injured rat sciatic nerve reveals protein expression dynamics during regeneration. mol cell proteomics. 2005; 4(2):120-32. pooladi m , sobhi s, khaghanirazi abad s , hashemi m, moradi a, zali ar, mousavi m, zali h, rakhan a, razaei-tavirani m.. the investigation of heat shock protein hsp70 expression change in human brain asterocytoma tumor. iranian journal of cancer prevention. 2013; 6:6-11. eisen mb, spellman pt, brown po, botstein d. cluster analysis and display of genome-wide expression patterns. procnatlacadsci u s a. 1998; 95(25):14863-8. jiang y ,  qi x ,  chrenek ma ,  gardner c ,  boatright jh ,  grossniklaus he ,  nickerson jm . functional principal component analysis reveals discriminating categories of retinal pigment epithelial morphology in mice. invest ophthalmol vis sci. 2013; 54(12):7274-83. meunier b ,  dumas e ,  piec i ,  béchet d ,  hébraud m ,  hocquette jf . assessment of hierarchical clustering methodologies for proteomic data mining. j proteome res. 2007; 6(1):358-66. deighton rf ,  short dm ,  mcgregor rj ,  gow aj ,  whittle ir ,  mcculloch j . the utility of functional interaction and cluster analysis in cns proteomics. j neurosci methods.  2009; 180(2):321-9.