期刊论文详细信息
BMC Research Notes
miRNome of inflammatory breast cancer
Alexander G Tonevitsky2  Udo Schumacher1  Andrey D Kaprin2  Irina A Mityakina2  Alexey E Lebedev4  Maxim U Shkurnikov2  Ilya N Nechaev2  Nadezhda A Khaustova4  Svetlana O Zhikrivetskaya4  Timur R Samatov4  Vladimir V Galatenko3  Diana V Maltseva4 
[1] Department of Anatomy and Experimental Morphology, University Cancer Center, University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg D-20246, Germany;P.A. Hertsen Moscow Research Oncology Institute, 2nd Botkinskii p. 3, Moscow 125284, Russia;Moscow State University, Leninskie Gory, 119991 Moscow, Russia;SRC Bioclinicum, Ugreshskaya str 2/85, 115088 Moscow, Russia
关键词: tp53 mutational status;    Microarray;    miRNA;    Inflammatory breast cancer;   
Others  :  1118047
DOI  :  10.1186/1756-0500-7-871
 received in 2014-08-26, accepted in 2014-11-28,  发布年份 2014
PDF
【 摘 要 】

Background

Inflammatory breast cancer (IBC) is an extremely malignant form of breast cancer which can be easily misdiagnosed. Conclusive prognostic IBC molecular biomarkers which are also providing the perspectives for targeted therapy are lacking so far. The aim of this study was to reveal the IBC-specific miRNA expression profile and to evaluate its association with clinicopathological parameters.

Methods

miRNA expression profiles of 13 IBC and 17 non-IBC patients were characterized using comprehensive Affymetrix GeneChip miRNA 3.0 microarray platform. Bioinformatic analysis was used to reveal IBC-specific miRNAs, deregulated pathways and potential miRNA targets.

Results

31 differentially expressed miRNAs characterize IBC and mRNAs regulated by them and their associated pathways can functionally be attributed to IBC progression. In addition, a minimal predictive set of 4 miRNAs characteristic for the IBC phenotype and associated with the TP53 mutational status in breast cancer patients was identified.

Conclusions

We have characterized the complete miRNome of inflammatory breast cancer and found differentially expressed miRNAs which reliably classify the patients to IBC and non-IBC groups. We found that the mRNAs and pathways likely regulated by these miRNAs are highly relevant to cancer progression. Furthermore a minimal IBC-related predictive set of 4 miRNAs associated with the TP53 mutational status and survival for breast cancer patients was identified.

【 授权许可】

   
2014 Maltseva et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20150206020318923.pdf 724KB PDF download
Figure 3. 1928KB Image download
Figure 2. 50KB Image download
Figure 1. 149KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】
  • [1]Hance KW, Anderson WF, Devesa SS, Young HA, Levine PH: Trends in inflammatory breast carcinoma incidence and survival: the surveillance, epidemiology, and end results program at the National Cancer Institute. J Natl Cancer Inst 2005, 97:966-975.
  • [2]Yamauchi H, Woodward WA, Valero V, Alvarez RH, Lucci A, Buchholz TA, Iwamoto T, Krishnamurthy S, Yang W, Reuben JM, Hortobágyi GN, Ueno NT: Inflammatory breast cancer: what we know and what we need to learn. Oncologist 2012, 17:891-899.
  • [3]Boutet G: Breast inflammation: clinical examination, aetiological pointers. Diagn Interv Imaging 2012, 93:78-84.
  • [4]Bertucci F, Finetti P, Rougemont J, Charafe-Jauffret E, Nasser V, Loriod B, Camerlo J, Tagett R, Tarpin C, Houvenaeghel G, Nguyen C, Maraninchi D, Jacquemier J, Houlgatte R, Birnbaum D, Viens P: Gene expression profiling for molecular characterization of inflammatory breast cancer and prediction of response to chemotherapy. Cancer Res 2004, 64:8558-8565.
  • [5]Van Laere S, Van der Auwera I, Van den Eynden G, Van Hummelen P, van Dam P, Van Marck E, Vermeulen PB, Dirix L: Distinct molecular phenotype of inflammatory breast cancer compared to non-inflammatory breast cancer using Affymetrix-based genome-wide gene-expression analysis. Br J Cancer 2007, 97:1165-1174.
  • [6]Van Laere S, Beissbarth T, Van der Auwera I, Van den Eynden G, Trinh XB, Elst H, Van Hummelen P, van Dam P, Van Marck E, Vermeulen P, Dirix L: Relapse-free survival in breast cancer patients is associated with a gene expression signature characteristic for inflammatory breast cancer. Clin Cancer Res 2008, 14:7452-7460.
  • [7]Iwamoto T, Bianchini G, Qi Y, Cristofanilli M, Lucci A, Woodward WA, Reuben JM, Matsuoka J, Gong Y, Krishnamurthy S, Valero V, Hortobagyi GN, Robertson F, Symmans WF, Pusztai L, Ueno NT: Different gene expressions are associated with the different molecular subtypes of inflammatory breast cancer. Breast Cancer Res Treat 2011, 125:785-795.
  • [8]Shkurnikov MY, Nechaev IN, Khaustova NA, Krainova NA, Savelov NA, Grinevich VN, Saribekyan EK: Expression profile of inflammatory breast cancer. Bull Exp Biol Med 2013, 155:667-672.
  • [9]Van Laere SJ, Ueno NT, Finetti P, Vermeulen P, Lucci A, Robertson FM, Marsan M, Iwamoto T, Krishnamurthy S, Masuda H, van Dam P, Woodward WA, Viens P, Cristofanilli M, Birnbaum D, Dirix L, Reuben JM, Bertucci F: Uncovering the molecular secrets of inflammatory breast cancer biology: an integrated analysis of three distinct affymetrix gene expression datasets. Clin Cancer Res 2013, 19:4685-4696.
  • [10]Turchinovich A, Samatov TR, Tonevitsky AG, Burwinkel B: Circulating miRNAs: cell-cell communication function? Front Genet 2013, 4:119.
  • [11]Calin GA, Croce CM: MicroRNA signatures in human cancers. Nat Rev Cancer 2006, 6:857-866.
  • [12]Van der Auwera I, Limame R, van Dam P, Vermeulen PB, Dirix LY, Van Laere SJ: Integrated miRNA and mRNA expression profiling of the inflammatory breast cancer subtype. Br J Cancer 2010, 103:532-541.
  • [13]Lerebours F, Cizeron-Clairac G, Susini A, Vacher S, Mouret-Fourme E, Belichard C, Brain E, Alberini JL, Spyratos F, Lidereau R, Bieche I: miRNA expression profiling of inflammatory breast cancer identifies a 5-miRNA signature predictive of breast tumor aggressiveness. Int J Cancer 2013, 133:1614-1623.
  • [14]Edge S, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A: AJCC Cancer Staging Manual. 7th edition. New York, NY: Springer; 2010.
  • [15]Affymetrix® Expression Console™ Software 1.4 User Manual. ©Affymetrix, Inc 2014. [http://media.affymetrix.com/support/downloads/manuals/expression_console_userguide.pdf webcite]
  • [16]Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003, 4:249-264.
  • [17]Bolstad BM, Irizarry RA, Astrand M, Speed TP: A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003, 19:185-193.
  • [18]Tukey JW: Exploratory data analysis. Reading: Addison-Wesley; 1977.
  • [19]Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004, 5:R80. BioMed Central Full Text
  • [20]Smyth GK: Limma: linear models for microarray data. In Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Edited by Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W. New York: Springer; 2005:397-420.
  • [21]Smyth GK: Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004, 3:Article 3.
  • [22]Los Alamos National Security, LLC: Heatmap Online Service. 2013. [http://www.hiv.lanl.gov/content/sequence/HEATMAP/heatmap.html webcite]
  • [23]Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W, Liaw A, Lumley T, Maechler M, Magnusson A, Moeller S, Schwartz M, Venables B: R package gplots. 2014. [http://cran.r-project.org/web/packages/gplots/gplots.pdf webcite]
  • [24]Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, Gerangelos S, Koziris N, Dalamagas T, Hatzigeorgiou AG: TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 2012, 40:D222-229.
  • [25]Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T: miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res 2009, 37:D105-110.
  • [26]Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, Chu CF, Huang HY, Lin CM, Ho SY, Jian TY, Lin FM, Chang TH, Weng SL, Liao KW, Liao IE, Liu CC, Huang HD: miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 2014, 42:D78-D85.
  • [27]Huang DW, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nat Protoc 2009, 4:44-57.
  • [28]Huang DW, Sherman BT, Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 2009, 37:1-13.
  • [29]Galatenko VV, Lebedev AE, Nechaev IN, Shkurnikov MY, Tonevitskii EA, Podol'skii VE: On the construction of medical test systems using greedy algorithm and support vector machine. Bull Exp Biol Med 2014, 156:706-709.
  • [30]Cortes C, Vapnik V: Support-vector networks. Machine Learning 1995, 20:273-297.
  • [31]Karatzoglou A, Smola A, Hornik K, Zeileis A: kernlab - An S4 Package for Kernel Methods in R. J Stat Software 2004, 11:1-20.
  • [32]Kuhn M: R package Caret. 2014. [http://cran.r-project.org/web/packages/caret/caret.pdf webcite]
  • [33]Enerly E, Steinfeld I, Kleivi K, Leivonen SK, Aure MR, Russnes HG, Rønneberg JA, Johnsen H, Navon R, Rødland E, Mäkelä R, Naume B, Perälä M, Kallioniemi O, Kristensen VN, Yakhini Z, Børresen-Dale AL: miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors. PLoS One 2011, 6:e16915.
  • [34]Persson H, Kvist A, Rego N, Staaf J, Vallon-Christersson J, Luts L, Loman N, Jonsson G, Naya H, Hoglund M, Borg A, Rovira C: Identification of new microRNAs in paired normal and tumor breast tissue suggests a dual role for the ERBB2/Her2 gene. Cancer Res 2011, 71:78-86.
  • [35]Schrauder MG, Strick R, Schulz-Wendtland R, Strissel PL, Kahmann L, Loehberg CR, Lux MP, Jud SM, Hartmann A, Hein A, Bayer CM, Bani MR, Richter S, Adamietz BR, Wenkel E, Rauh C, Beckmann MW, Fasching PA: Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection. PLoS One 2012, 7:e29770.
  • [36]Gong C, Qu S, Liu B, Pan S, Jiao Y, Nie Y, Su F, Liu Q, Song E: MiR-106b expression determines the proliferation paradox of TGF-β in breast cancer cells. Oncogene 2013. 10.1038/onc.2013.525
  • [37]Wang B, Li J, Sun M, Sun L, Zhang X: MiRNA expression in breast cancer varies with lymph node metastasis and other clinicopathologic features. IUBMB Life 2014. 10.1002/iub.1273
  • [38]Sand M, Skrygan M, Sand D, Georgas D, Gambichler T, Hahn SA, Altmeyer P, Bechara FG: Comparative microarray analysis of microRNA expression profiles in primary cutaneous malignant melanoma, cutaneous malignant melanoma metastases, and benign melanocytic nevi. Cell Tissue Res 2013, 351:85-98.
  • [39]Bae J, Won M, Kim DY, Kim JH, Kim YM, Kim YT, Nam JH, Suh DS: Identification of differentially expressed microRNAs in endometrial cancer cells after progesterone treatment. Int J Gynecol Cancer 2012, 22:561-565.
  • [40]Zha R, Guo W, Zhang Z, Qiu Z, Wang Q, Ding J, Huang S, Chen T, Gu J, Yao M, He X: Genome-wide screening identified that miR-134 acts as a metastasis suppressor by targeting integrin β1 in hepatocellular carcinoma. PLoS One 2014, 9:e87665.
  • [41]Jima DD, Zhang J, Jacobs C, Richards KL, Dunphy CH, Choi WW, Au WY, Srivastava G, Czader MB, Rizzieri DA, Lagoo AS, Lugar PL, Mann KP, Flowers CR, Bernal-Mizrachi L, Naresh KN, Evens AM, Gordon LI, Luftig M, Friedman DR, Weinberg JB, Thompson MA, Gill JI, Liu Q, How T, Grubor V, Gao Y, Patel A, Wu H, Zhu J, et al.: Hematologic Malignancies Research Consortium. Deep sequencing of the small RNA transcriptome of normal and malignant human B cells identifies hundreds of novel microRNAs. Blood 2010, 116:e118-127.
  • [42]Vimalraj S, Miranda PJ, Ramyakrishna B, Selvamurugan N: Regulation of breast cancer and bone metastasis by microRNAs. Dis Markers 2013, 35:369-387.
  • [43]Imam JS, Plyler JR, Bansal H, Prajapati S, Bansal S, Rebeles J, Chen HI, Chang YF, Panneerdoss S, Zoghi B, Buddavarapu KC, Broaddus R, Hornsby P, Tomlinson G, Dome J, Vadlamudi RK, Pertsemlidis A, Chen Y, Rao MK: Genomic loss of tumor suppressor miRNA-204 promotes cancer cell migration and invasion by activating AKT/mTOR/Rac1 signaling and actin reorganization. PLoS One 2012, 7:e52397.
  • [44]Tahiri A, Leivonen SK, Lüders T, Steinfeld I, Ragle Aure M, Geisler J, Mäkelä R, Nord S, Riis ML, Yakhini Z, Kleivi Sahlberg K, Børresen-Dale AL, Perälä M, Bukholm IR, Kristensen VN: Deregulation of cancer-related miRNAs is a common event in both benign and malignant human breast tumors. Carcinogenesis 2014, 35:76-85.
  • [45]Jiang L, He D, Yang D, Chen Z, Pan Q, Mao A, Cai Y, Li X, Xing H, Shi M, Chen Y, Bruce IC, Wang T, Jin L, Qi X, Hua D, Jin J, Ma X: MiR-489 regulates chemoresistance in breast cancer via epithelial mesenchymal transition pathway. FEBS Lett 2014, 588:2009-2015.
  • [46]Yu F, Yao H, Zhu P, Zhang X, Pan Q, Gong C, Huang Y, Hu X, Su F, Lieberman J: let-7 regulates self renewal and tumorigenicity of breast cancer cells. Cell 2007, 131:1109-1123.
  • [47]Hu B, Ying X, Wang J, Piriyapongsa J, Jordan IK, Sheng J, Yu F, Zhao P, Li Y, Wang H, Ng WL, Hu S, Wang X, Wang C, Zheng X, Li W, Curran WJ, Wang Y: Identification of a tumor-suppressive human-specific microRNA within the FHIT tumor-suppressor gene. Cancer Res 2014, 74:2283-2294.
  • [48]Cairo S, Wang Y, de Reyniès A, Duroure K, Dahan J, Redon MJ, Fabre M, McClelland M, Wang XW, Croce CM, Buendia MA: Stem cell-like micro-RNA signature driven by Myc in aggressive liver cancer. Proc Natl Acad Sci U S A 2010, 107:20471-20476.
  • [49]Yanaihara N, Caplen N, Bowman E, Seike M, Kumamoto K, Yi M, Stephens RM, Okamoto A, Yokota J, Tanaka T, Calin GA, Liu CG, Croce CM, Harris CC: Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 2006, 9:189-198.
  • [50]Pollard JW: Macrophages define the invasive microenvironment in breast cancer. J Leukoc Biol 2008, 84:623-630.
  • [51]Mohamed MM, El-Ghonaimy EA, Nouh MA, Schneider RJ, Sloane BF, El-Shinawi M: Cytokines secreted by macrophages isolated from tumor microenvironment of inflammatory breast cancer patients possess chemotactic properties. Int J Biochem Cell Biol 2014, 46:138-147.
  • [52]Cobos Jiménez V, Bradley EJ, Willemsen AM, van Kampen AH, Baas F, Kootstra NA: Next-generation sequencing of microRNAs uncovers expression signatures in polarized macrophages. Physiol Genomics 2014, 46:91-103.
  • [53]Alberts B, Johnson A, Lewis J, Raff M: Molecular Biology of the Cell. 5th edition. New York, NY: Garland Science; 2007.
  • [54]Broderick JA, Salomon WE, Ryder SP, Aronin N, Zamore PD: Argonaute protein identity and pairing geometry determine cooperativity in mammalian RNA silencing. RNA 2011, 17:1858-1869.
  • [55]Arvidsson Y, Andersson E, Bergström A, Andersson MK, Altiparmak G, Illerskog AC, Ahlman H, Lamazhapova D, Nilsson O: Amyloid precursor-like protein 1 is differentially upregulated in neuroendocrine tumours of the gastrointestinal tract. Endocr Relat Cancer 2008, 15:569-581.
  • [56]Srivastava M, Khurana P, Sugadev R: Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data. BMC Res Notes 2012, 5:617. BioMed Central Full Text
  • [57]Ma W, Zhang TF, Lu P, Lu SH: Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors. Eur Rev Med Pharmacol Sci 2014, 18:212-216.
  • [58]Somlo G, Chu P, Frankel P, Ye W, Groshen S, Doroshow JH, Danenberg K, Danenberg P: Molecular profiling including epidermal growth factor receptor and p21 expression in high-risk breast cancer patients as indicators of outcome. Ann Oncol 2008, 19:1853-1859.
  • [59]Hussey GS, Chaudhury A, Dawson AE, Lindner DJ, Knudsen CR, Wilce MC, Merrick WC, Howe PH: Identification of an mRNP complex regulating tumorigenesis at the translational elongation step. Mol Cell 2011, 41:419-431.
  • [60]Maltseva DV, Khaustova NA, Fedotov NN, Matveeva EO, Lebedev AE, Shkurnikov MU, Galatenko VV, Schumacher U, Tonevitsky AG: High-throughput identification of reference genes for research and clinical RT-qPCR analysis of breast cancer samples. J Clin Bioinforma 2013, 3:13. BioMed Central Full Text
  • [61]Jiang W, Newsham IF: The tumor suppressor DAL-1/4.1B and protein methylation cooperate in inducing apoptosis in MCF-7 breast cancer cells. Mol Cancer 2006, 5:4. BioMed Central Full Text
  • [62]Khaidakov M, Mitra S, Kang BY, Wang X, Kadlubar S, Novelli G, Raj V, Winters M, Carter WC, Mehta JL: Oxidized LDL receptor 1 (OLR1) as a possible link between obesity, dyslipidemia and cancer. PLoS One 2011, 6:e20277.
  • [63]Szczyrba J, Nolte E, Hart M, Döll C, Wach S, Taubert H, Keck B, Kremmer E, Stöhr R, Hartmann A, Wieland W, Wullich B, Grässer FA: Identification of ZNF217, hnRNP-K, VEGF-A and IPO7 as targets for microRNAs that are downregulated in prostate carcinoma. Int J Cancer 2013, 132:775-784.
  • [64]Ju JH, Yang W, Lee KM, Oh S, Nam K, Shim S, Shin SY, Gye MC, Chu IS, Shin I: Regulation of cell proliferation and migration by keratin19-induced nuclear import of early growth response-1 in breast cancer cells. Clin Cancer Res 2013, 19:4335-4346.
  • [65]Tu SH, Chang CC, Chen CS, Tam KW, Wang YJ, Lee CH, Lin HW, Cheng TC, Huang CS, Chu JS, Shih NY, Chen LC, Leu SJ, Ho YS, Wu CH: Increased expression of enolase alpha in human breast cancer confers tamoxifen resistance in human breast cancer cells. Breast Cancer Res Treat 2010, 121:539-553.
  • [66]Chen S, Cai J, Zhang W, Zheng X, Hu S, Lu J, Xing J, Dong Y: Proteomic identification of differentially expressed proteins associated with the multiple drug resistance in methotrexate-resistant human breast cancer cells. Int J Oncol 2014, 45:448-458.
  • [67]Killian A, Sarafan-Vasseur N, Sesboüé R, Le Pessot F, Blanchard F, Lamy A, Laurent M, Flaman JM, Frébourg T: Contribution of the BOP1 gene, located on 8q24, to colorectal tumorigenesis. Genes Chromosomes Cancer 2006, 45:874-881.
  • [68]Morishita A, Zaidi MR, Mitoro A, Sankarasharma D, Szabolcs M, Okada Y, D'Armiento J, Chada K: HMGA2 is a driver of tumor metastasis. Cancer Res 2013, 73:4289-4299.
  • [69]Sun M, Song CX, Huang H, Frankenberger CA, Sankarasharma D, Gomes S, Chen P, Chen J, Chada KK, He C, Rosner MR: HMGA2/TET1/HOXA9 signaling pathway regulates breast cancer growth and metastasis. Proc Natl Acad Sci U S A 2013, 110:9920-9925.
  • [70]Linderholm B, Lindh B, Tavelin B, Grankvist K, Henriksson R: p53 and vascular-endothelial-growth-factor (VEGF) expression predicts outcome in 833 patients with primary breast carcinoma. Int J Cancer 2000, 89:51-62.
  • [71]Mohammed RA, Green A, El-Shikh S, Paish EC, Ellis IO, Martin SG: Prognostic significance of vascular endothelial cell growth factors -A, -C and -D in breast cancer and their relationship with angio- and lymphangiogenesis. Br J Cancer 2007, 96:1092-1100.
  • [72]Cao YEG, Wang E, Pal K, Dutta SK, Bar-Sagi D, Mukhopadhyay D: VEGF exerts an angiogenesis-independent function in cancer cells to promote their malignant progression. Cancer Res 2012, 72:3912-3918.
  • [73]Petitjean A, Achatz MI, Borresen-Dale AL, Hainaut P, Olivier M: TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes. Oncogene 2007, 26:2157-2165.
  • [74]Langerød A, Zhao H, Borgan Ø, Nesland JM, Bukholm IR, Ikdahl T, Kåresen R, Børresen-Dale AL, Jeffrey SS: TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer. Breast Cancer Res 2007, 9:R30. BioMed Central Full Text
  文献评价指标  
  下载次数:19次 浏览次数:2次