Top

Published in:

01-10-2011 | Original Article

Relationships of ESR1 and XBP1 expression in human breast carcinoma and stromal cells isolated by laser capture microdissection compared to intact breast cancer tissue

Authors: Sarah A. Andres, James L. Wittliff

Published in: Endocrine | Issue 2/2011

Abstract

Results from investigations of human genomics which utilize intact tissue biopsy specimens maybe compromised due to a host of uncontrolled variables including cellular heterogeneity of a sample collected under diverse conditions, then processed and stored using different protocols. To determine the cellular origin and assess relationships of mRNA expression of two genes reported to be co-expressed in human breast carcinoma (estrogen receptor-α, ESR1 and X-box binding protein 1, XBP1), gene expression analyses were performed with intact tissue sections and compared with those of laser capture microdissection (LCM)-procured carcinoma and stromal cells from serial sections of the same tissue. Frozen sections of human breast carcinomas were first evaluated for structural integrity and pathology after hematoxylin and eosin (H&E) staining. Total RNA preparations from intact tissue sections and LCM-procured carcinoma and stromal cells were reverse transcribed for measurements of ESR1 and XBP1 expression by quantitative PCR (qPCR). These results were compared with those obtained from microarray analyses of LCM-procured carcinoma cells. Levels of ESR1 and XBP1 were detected in the intact breast cancer tissue sections suggesting coordinate gene expression. Although coordinate expression of these genes was observed in the LCM-procured carcinoma cells, it was not discerned in LCM-procured stromal cells. The origin of coordinate expression of ESR1 and XBP1 observed in whole tissue sections of human breast cancer biopsies is due principally to their co-expression in carcinoma cells and not in the surrounding stromal cells as substantiated using LCM-procured cells. Collectively, a microgenomic process was established from human tissue preparation to RNA characterization and analysis to identify molecular signatures of specific cell types predicting clinical behavior.

N. Chalabi, L. Delort, C.L. Le, S. Satih, Y.J. Bignon, D. Bernard-Gallon, Gene signature of breast cancer cell lines treated with lycopene. Pharmacogenomics 7, 663–672 (2006)PubMedCrossRef

C.P. Giacomini, S.Y. Leung, X. Chen, S.T. Yuen, Y.H. Kim, E. Bair, J.R. Pollack, A gene expression signature of genetic instability in colon cancer. Cancer Res. 65, 9200–9205 (2005)PubMedCrossRef

S. Nanni, C. Priolo, A. Grasselli, M. D’Eletto, R. Merola, F. Moretti, M. Gallucci, C.P. De, S. Sentinelli, A.M. Cianciulli, M. Mottolese, P. Carlini, D. Arcelli, M. Helmer-Citterich, C. Gaetano, M. Loda, A. Pontecorvi, S. Bacchetti, A. Sacchi, A. Farsetti, Epithelial-restricted gene profile of primary cultures from human prostate tumors: a molecular approach to predict clinical behavior of prostate cancer. Mol. Cancer Res. 4, 79–92 (2006)PubMedCrossRef

D.T. Ross, U. Scherf, M.B. Eisen, C.M. Perou, C. Rees, P. Spellman, V. Iyer, S.S. Jeffrey, M. van de Rijn, M. Waltham, A. Pergamenschikov, J.C. Lee, D. Lashkari, D. Shalon, T.G. Myers, J.N. Weinstein, D. Botstein, P.O. Brown, Systematic variation in gene expression patterns in human cancer cell lines. Nat. Genet. 24, 227–235 (2000)PubMedCrossRef

T. Sorlie, C.M. Perou, R. Tibshirani, T. Aas, S. Geisler, H. Johnsen, T. Hastie, M.B. Eisen, M. van de Rijn, S.S. Jeffrey, T. Thorsen, H. Quist, J.C. Matese, P.O. Brown, D. Botstein, L.P. Eystein, A.L. Borresen-Dale, Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 98, 10869–10874 (2001)PubMedCrossRef

C. Sotiriou, S.Y. Neo, L.M. McShane, E.L. Korn, P.M. Long, A. Jazaeri, P. Martiat, S.B. Fox, A.L. Harris, E.T. Liu, Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc. Natl. Acad. Sci. USA 100, 10393–10398 (2003)PubMedCrossRef

L.J. Van’t Veer, H. Dai, M.J. van de Vijver, Y.D. He, A.A. Hart, M. Mao, H.L. Peterse, K. van der Kooy, M.J. Marton, A.T. Witteveen, G.J. Schreiber, R.M. Kerkhoven, C. Roberts, P.S. Linsley, R. Bernards, S.H. Friend, Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002)CrossRef

M.J. van de Vijver, Y.D. He, L.J. van’t Veer, H. Dai, A.A. Hart, D.W. Voskuil, G.J. Schreiber, J.L. Peterse, C. Roberts, M.J. Marton, M. Parrish, D. Atsma, A. Witteveen, A. Glas, L. Delahaye, T. van der Velde, H. Bartelink, S. Rodenhuis, E.T. Rutgers, S.H. Friend, R. Bernards, A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002)

K.A. Cole, D.B. Krizman, M.R. Emmert-Buck, The genetics of cancer—a 3D model. Nat. Genet. 21, 38–41 (1999)PubMedCrossRef

10.

M.R. Emmert-Buck, R.F. Bonner, P.D. Smith, R.F. Chuaqui, Z. Zhuang, S.R. Goldstein, R.A. Weiss, L.A. Liotta, Laser capture microdissection. Science 274, 998–1001 (1996)PubMedCrossRef

11.

J.L. Wittliff, S.T. Kunitake, S.S. Chu, J.C. Travis, Applications of laser capture microdissection in genomics and proteomics. J. Clin. Ligand Assay 23, 66 (2000)

12.

J.L. Wittliff, M.G. Erlander, Laser capture microdissection and its applications in genomics and proteomics. Methods Enzymol. 356, 12–25 (2002)PubMedCrossRef

13.

R.F. Bonner, M. Emmert-Buck, K. Cole, T. Pohida, R. Chuaqui, S. Goldstein, L.A. Liotta, Laser capture microdissection: molecular analysis of tissue. Science 278, 1481–1483 (1997)PubMedCrossRef

14.

M.R. Emmert-Buck, J.W. Gillespie, C.P. Paweletz, D.K. Ornstein, V. Basrur, E. Appella, Q.H. Wang, J. Huang, N. Hu, P. Taylor, E.F. Petricoin III, An approach to proteomic analysis of human tumors. Mol. Carcinog. 27, 158–165 (2000)PubMedCrossRef

15.

X.J. Ma, R. Salunga, J.T. Tuggle, J. Gaudet, E. Enright, P. McQuary, T. Payette, M. Pistone, K. Stecker, B.M. Zhang, Y.X. Zhou, H. Varnholt, B. Smith, M. Gadd, E. Chatfield, J. Kessler, T.M. Baer, M.G. Erlander, D.C. Sgroi, Gene expression profiles of human breast cancer progression. Proc. Natl. Acad. Sci. USA 100, 5974–5979 (2003)PubMedCrossRef

16.

J.L. Wittliff, Laser capture microdissection and its applications in genomics and proteomics, in Techniques in Confocal Microscopy, ed. by P.M. Conn (Elsevier, Oxford, 2010), pp. 463–478

17.

J.L. Wittliff, W. Raffelsberger, Mechanisms of signal transduction: sex hormones, their receptors and clinical utility. J. Clin. Ligand Assay 18, 211–235 (1995)

18.

J.L. Wittliff, R. Pasic, K.I. Bland, Steroid and peptide hormone receptors: methods, quality control, and clinical use, in The Breast: Comprehensive Management of Benign and Malignant Diseases, ed. by K. Bland, E.M. Copeland (W.B. Saunders Co., Philadelphia, 1998), pp. 458–498

19.

S.J. Santner, R.J. Pauley, L. Tait, J. Kaseta, R.J. Santen, Aromatase activity and expression in breast cancer and benign breast tissue stromal cells. J. Clin. Endocrinol. Metab. 82, 200–208 (1997)PubMedCrossRef

20.

R.J. Santen, S.J. Santner, R.J. Pauley, L. Tait, J. Kaseta, L.M. Demers, C. Hamilton, W. Yue, J.P. Wang, Estrogen production via the aromatase enzyme in breast carcinoma: Which cell type is responsible? J. Steroid Biochem. Mol. Biol. 61, 267–271 (1997)PubMedCrossRef

21.

R.A. Smith, R.A. Lea, S.R. Weinstein, L.R. Griffiths, Progesterone, glucocorticoid, but not estrogen receptor mRNA is altered in breast cancer stroma. Cancer Lett. 255, 77–84 (2007)PubMedCrossRef

22.

B.P. Gomez, R.B. Riggins, A.N. Shajahan, U. Klimach, A. Wang, A.C. Crawford, Y. Zhu, A. Zwart, M. Wang, R. Clarke, Human X-box binding protein-1 confers both estrogen independence and antiestrogen resistance in breast cancer cell lines. FASEB J. 21, 4013–4027 (2007)PubMedCrossRef

23.

M. Lacroix, G. Leclercq, About GATA3, HNF3A, and XBP1, three genes co-expressed with the oestrogen receptor-alpha gene (ESR1) in breast cancer. Mol. Cell. Endocrinol. 219, 1–7 (2004)PubMedCrossRef

24.

M.P. Davies, D.L. Barraclough, C. Stewart, K.A. Joyce, R.M. Eccles, R. Barraclough, P.S. Rudland, D.R. Sibson, Expression and splicing of the unfolded protein response gene XBP-1 are significantly associated with clinical outcome of endocrine-treated breast cancer. Int. J. Cancer 123, 85–88 (2008)PubMedCrossRef

25.

S. Sengupta, C.G. Sharma, V.C. Jordan, Estrogen regulation of X-box binding protein-1 and its role in estrogen induced growth of breast and endometrial cancer cells. Horm. Mol. Biol. Clin. Investig. 2, 235–243 (2010)PubMedCrossRef

26.

D.Y. Wang, R. Fulthorpe, S.N. Liss, E.A. Edwards, Identification of estrogen-responsive genes by complementary deoxyribonucleic acid microarray and characterization of a novel early estrogen-induced gene: EEIG1. Mol. Endocrinol. 18, 402–411 (2004)PubMedCrossRef

27.

L. Ding, J. Yan, J. Zhu, H. Zhong, Q. Lu, Z. Wang, C. Huang, Q. Ye, Ligand-independent activation of estrogen receptor alpha by XBP-1. Nucleic Acids Res. 31, 5266–5274 (2003)PubMedCrossRef

28.

Y. Fang, J. Yan, L. Ding, Y. Liu, J. Zhu, C. Huang, H. Zhao, Q. Lu, X. Zhang, X. Yang, Q. Ye, XBP-1 increases ERalpha transcriptional activity through regulation of large-scale chromatin unfolding. Biochem. Biophys. Res. Commun. 323, 269–274 (2004)PubMedCrossRef

29.

F. Bertucci, V. Nasser, S. Granjeaud, F. Eisinger, J. Adelaide, R. Tagett, B. Loriod, A. Giaconia, A. Benziane, E. Devilard, J. Jacquemier, P. Viens, C. Nguyen, D. Birnbaum, R. Houlgatte, Gene expression profiles of poor-prognosis primary breast cancer correlate with survival. Hum. Mol. Genet. 11, 863–872 (2002)PubMedCrossRef

30.

T. Fujimoto, M. Onda, H. Nagai, T. Nagahata, K. Ogawa, M. Emi, Upregulation and overexpression of human X-box binding protein 1 (hXBP-1) gene in primary breast cancers. Breast Cancer 10, 301–306 (2003)PubMedCrossRef

31.

D.A. Kerr II, J.F. Eliason, J.L. Wittliff, Steroid receptor and growth factor receptor expression in human nonsmall cell lung cancers using cells procured by laser-capture microdissection. Adv. Exp. Med. Biol. 617, 377–384 (2008)PubMedCrossRef

32.

N.L. Simone, R.F. Bonner, J.W. Gillespie, M.R. Emmert-Buck, L.A. Liotta, Laser-capture microdissection: opening the microscopic frontier to molecular analysis. Trends Genet. 14, 272–276 (1998)PubMedCrossRef

33.

N.L. Simone, A.T. Remaley, L. Charboneau, E.F. Petricoin III, J.W. Glickman, M.R. Emmert-Buck, T.A. Fleisher, L.A. Liotta, Sensitive immunoassay of tissue cell proteins procured by laser capture microdissection. Am. J. Pathol. 156, 445–452 (2000)PubMedCrossRef

34.

M. Fleisher, A.M. Dnistrian, C.M. Sturgeon, J.L. Wittliff, Practice guidelines and recommendations for use of tumor markers in the clinic, in Tumor Markers: Physiology, Pathobiology, Technology, and Clinical Applications, ed. by D.P. Diamandis, H.A. Fritsche, H. Lilja, D.W. Chan, M.K. Schwartz (AACC Press, Washington, 2002), pp. 33–63

35.

M. Srinivasan, D. Sedmak, S. Jewell, Effect of fixatives and tissue processing on the content and integrity of nucleic acids. Am. J. Pathol. 161, 1961–1971 (2002)PubMedCrossRef

36.

M.W. Pfaffl, A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 29, e45 (2001)PubMedCrossRef

37.

X.J. Ma, W. Wang, R. Salunga, J.T. Tuggle, K. Stecker, T.M. Baer, M.G. Erlander, J.L. Wittliff, Gene expression associated with clinical outcome in breast cancer via laser capture microdissection. Breast Cancer Res. Treat. 82 (2003)

38.

J.L. Wittliff, X.J. Ma, K.K. Stecker, R.C. Salunga, J.T. Tuggle, Y.K. Tran, K.N. Mesina, T.R. Payette, P.R. McQuary, M.P. Pistone, B.M. Zhang, D.D. Hartwig, T.H. Wittliff, W. Wang, M.G. Erlander, Gene expression profiles and tumor marker signatures of human breast carcinoma cells procured by laser capture microdissection. Endocr. Soc. Abs. 538 (2002)

39.

J.L. Wittliff, X.J. Ma, W. Wang, R. Salunga, J.T. Tuggle, K. Stecker, T.H. Wittliff, M.G. Erlander, Expression of estrogen receptor-associated genes in breast cancer cells procured by laser capture microdissection. Jensen Symp. Abs. 81 (2003)

40.

A.L. Bookout, C.L. Cummins, D.J. Mangelsdorf, J.M. Pesola, M.F. Kramer, High-throughput real-time quantitative reverse transcription PCR. Curr. Protoc. Mol. Biol. Chapter 15, Unit 15.8 (2006)

41.

H.J. Motulsky, Prism 4 Statistics Guide—Statistical Analyses for Laboratory and Clinical Researchers, 4th edn. (GraphPad Software Inc., San Diego, 2003), pp. 71–73

42.

A. Casabianca, C. Orlandi, A. Fraternale, M. Magnani, Development of a real-time PCR assay using SYBR Green I for provirus load quantification in a murine model of AIDS. J. Clin. Microbiol. 42, 4361–4364 (2004)PubMedCrossRef

43.

M.W. Pfaffl, G.W. Horgan, L. Dempfle, Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res. 30, e36 (2002)PubMedCrossRef

44.

E. Zini, M. Franchini, M. Osto, A. Vogtlin, F. Guscetti, P. Linscheid, K. Kaufmann, B. Sigrist, M. Ackermann, T.A. Lutz, C.E. Reusch, Quantitative real-time PCR detection of insulin signalling-related genes in pancreatic islets isolated from healthy cats. Vet. J. 183, 287–293 (2008)PubMedCrossRef

45.

S.Z. Haslam, K.A. Nummy, The ontogeny and cellular distribution of estrogen receptors in normal mouse mammary gland. J. Steroid Biochem. Mol. Biol. 42, 589–595 (1992)PubMedCrossRef

46.

S.Z. Haslam, T.L. Woodward, Host microenvironment in breast cancer development: epithelial-cell-stromal-cell interactions and steroid hormone action in normal and cancerous mammary gland. Breast Cancer Res. 5, 208–215 (2003)PubMedCrossRef

47.

R. Judd, Advantages of an immunohistochemical estrogen receptor assay. South. Med. J. 84, 853–856, 861 (1991)

48.

T. Suzuki, P.J. Higgins, D.R. Crawford, Control selection for RNA quantitation. Biotechniques 29, 332–337 (2000)PubMed

49.

S.L. Hembruff, D.J. Villeneuve, A.M. Parissenti, The optimization of quantitative reverse transcription PCR for verification of cDNA microarray data. Anal. Biochem. 345, 237–249 (2005)PubMedCrossRef

50.

J. Vandesompele, P.K. De, F. Pattyn, B. Poppe, R.N. Van, P.A. De, F. Speleman, Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3, RESEARCH0034 (2002)

51.

P. Scriven, S. Coulson, R. Haines, S. Balasubramanian, S. Cross, L. Wyld, Activation and clinical significance of the unfolded protein response in breast cancer. Br. J. Cancer 101, 1692–1698 (2009)PubMedCrossRef

52.

S. Myhre, H. Mohammed, T. Tramm, J. Alsner, G. Finak, M. Park, J. Overgaard, A.L. Borresen-Dale, A. Frigessi, T. Sorlie, In silico ascription of gene expression differences to tumor and stromal cells in a model to study impact on breast cancer outcome. PLoS. ONE. 5, e14002 (2010)PubMedCrossRef

53.

V.R. Grann, A.B. Troxel, N.J. Zojwalla, J.S. Jacobson, D. Hershman, A.I. Neugut, Hormone receptor status and survival in a population-based cohort of patients with breast carcinoma. Cancer 103, 2241–2251 (2005)PubMedCrossRef

Title: Relationships of ESR1 and XBP1 expression in human breast carcinoma and stromal cells isolated by laser capture microdissection compared to intact breast cancer tissue
Authors: Sarah A. Andres
James L. Wittliff
Publication date: 01-10-2011
Publisher: Springer US
Published in: Endocrine / Issue 2/2011
Print ISSN: 1355-008X
Electronic ISSN: 1559-0100
DOI: https://doi.org/10.1007/s12020-011-9522-x

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 2/2011

Asymmetric dimethylarginine level in hyperglycemic gestation

Relationship between Sloan-Kettering virus expression and mouse follicular development

Epidemiology of insulinoma in Tunisia

Surgical treatment of type 2 diabetes: the surgeon perspective

Elevated serum γ-glutamyltransferase predicts the development of impaired glucose metabolism in middle-aged and elderly Chinese

Cross-talk and modulation of signaling between somatostatin and growth factor receptors

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

At a glance: The STEP trials