Skip to main content

Gene Expression Signatures of the Tumor Microenvironment: Relation to Tumor Progress in Breast Cancer

  • Chapter
  • First Online:
Biomarkers of the Tumor Microenvironment
  • 1230 Accesses

Abstract

Cancer cell invasion and progression toward the metastatic stage are biological processes that have been studied for a long time. There is not one all-inclusive model that encompasses the complete picture of the different conditions and pathways operating in human tumors. Application of gene expression signatures is one way of mining the complex tumor landscape, and this has been proposed to represent a robust method to reflect the many signaling systems.

This chapter gives an update on gene expression signature studies related to breast cancer progress. Signatures reflecting cancer-associated stroma, in particular tumor fibroblasts, parts of the vascular system, and signature profiles pointing to immune-related alterations, are in focus. Several signature studies support that a combination of extracellular remodeling, activated vascular biology, and immune-related signaling takes place during breast cancer progress. Stromal alterations and processes are likely to represent a wide spectrum of novel biomarkers and companion treatment targets.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  1. Fidler IJ. The pathogenesis of cancer metastasis: the seed and soil hypothesis revisited. Nat Rev Cancer. 2003;3(6):453–8.

    Article  CAS  PubMed  Google Scholar 

  2. Talmadge JE, Fidler IJ. AACR centennial series: the biology of cancer metastasis: historical perspective. Cancer Res. 2010;70(14):5649–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Paget S. The distribution of secondary growths in cancer of the breast. Lancet. 1889;1:571–3.

    Article  Google Scholar 

  4. Nguyen DX, Massague J. Genetic determinants of cancer metastasis. Nat Rev Genet. 2007;8(5):341–52.

    Article  CAS  PubMed  Google Scholar 

  5. Nguyen DX, Bos PD, Massague J. Metastasis: from dissemination to organ-specific colonization. Nat Rev Cancer. 2009;9(4):274–84.

    Article  CAS  PubMed  Google Scholar 

  6. Bhat R, Bissell MJ. Of plasticity and specificity: dialectics of the microenvironment and macroenvironment and the organ phenotype. Wiley Interdiscip Rev Dev Biol. 2014;3(2):147–63.

    Article  CAS  PubMed  Google Scholar 

  7. Boudreau A, van't Veer LJ, Bissell MJ. An elite hacker: breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity. Cell Adhes Migr. 2012;6(3):236–48.

    Article  Google Scholar 

  8. Wculek SK, Malanchi I. Neutrophils support lung colonization of metastasis-initiating breast cancer cells. Nature. 2015;528(7582):413–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Valastyan S, Weinberg RA. Tumor metastasis: molecular insights and evolving paradigms. Cell. 2011;147(2):275–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Oppenheimer SB. Cellular basis of cancer metastasis: a review of fundamentals and new advances. Acta Histochem. 2006;108(5):327–34.

    Article  CAS  PubMed  Google Scholar 

  11. Kaplan RN, Rafii S, Lyden D. Preparing the soil: the premetastatic niche. Cancer Res. 2006;66(23):11089–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kaplan RN, Riba RD, Zacharoulis S, Bramley AH, Vincent L, Costa C, et al. VEGFR1-positive haematopoietic bone marrow progenitors initiate the pre-metastatic niche. Nature. 2005;438(7069):820–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hoshino A, Costa-Silva B, Shen TL, Rodrigues G, Hashimoto A, Tesic Mark M, et al. Tumour exosome integrins determine organotropic metastasis. Nature. 2015;527(7578):329–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403(6769):503–11.

    Article  CAS  PubMed  Google Scholar 

  15. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 1999;286(5439):531–7.

    Article  CAS  PubMed  Google Scholar 

  16. Kim H, Nam SW, Rhee H, Shan Li L, Ju Kang H, Hye Koh K, et al. Different gene expression profiles between microsatellite instability-high and microsatellite stable colorectal carcinomas. Oncogene. 2004;23(37):6218–25.

    Article  CAS  PubMed  Google Scholar 

  17. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52.

    Article  CAS  PubMed  Google Scholar 

  18. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98(19):10869–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A. 2003;100(18):10393–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Li W, Wang R, Yan Z, Bai L, Sun Z. High accordance in prognosis prediction of colorectal cancer across independent datasets by multi-gene module expression profiles. PLoS One. 2012;7(3):e33653.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415(6871):530–6.

    Article  PubMed  Google Scholar 

  22. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365(9460):671–9.

    Article  CAS  PubMed  Google Scholar 

  23. van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AA, Voskuil DW, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347(25):1999–2009.

    Article  PubMed  Google Scholar 

  24. Rouzier R, Rajan R, Wagner P, Hess KR, Gold DL, Stec J, et al. Microtubule-associated protein tau: a marker of paclitaxel sensitivity in breast cancer. Proc Natl Acad Sci U S A. 2005;102(23):8315–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. DeRisi JL, Iyer VR, Brown PO. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science. 1997;278(5338):680–6.

    Article  CAS  PubMed  Google Scholar 

  26. Hughes TR, Marton MJ, Jones AR, Roberts CJ, Stoughton R, Armour CD, et al. Functional discovery via a compendium of expression profiles. Cell. 2000;102(1):109–26.

    Article  CAS  PubMed  Google Scholar 

  27. Huang E, Ishida S, Pittman J, Dressman H, Bild A, Kloos M, et al. Gene expression phenotypic models that predict the activity of oncogenic pathways. Nat Genet. 2003;34(2):226–30.

    Article  CAS  PubMed  Google Scholar 

  28. Bild AH, Yao G, Chang JT, Wang Q, Potti A, Chasse D, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature. 2006;439(7074):353–7.

    Article  CAS  PubMed  Google Scholar 

  29. Black EP, Huang E, Dressman H, Rempel R, Laakso N, Asa SL, et al. Distinct gene expression phenotypes of cells lacking Rb and Rb family members. Cancer Res. 2003;63(13):3716–23.

    CAS  PubMed  Google Scholar 

  30. Lamb J, Ramaswamy S, Ford HL, Contreras B, Martinez RV, Kittrell FS, et al. A mechanism of cyclin D1 action encoded in the patterns of gene expression in human cancer. Cell. 2003;114(3):323–34.

    Article  CAS  PubMed  Google Scholar 

  31. Biomarkers Definitions Working G. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69(3):89–95.

    Article  Google Scholar 

  32. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100(1):57–70.

    Article  CAS  PubMed  Google Scholar 

  33. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74.

    Article  CAS  PubMed  Google Scholar 

  34. Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, et al. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006;313(5795):1929–35.

    Article  CAS  PubMed  Google Scholar 

  35. Lamb J. The Connectivity map: a new tool for biomedical research. Nat Rev Cancer. 2007;7(1):54–60.

    Article  CAS  PubMed  Google Scholar 

  36. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A. 2003;100(14):8418–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Gyorffy B, Hatzis C, Sanft T, Hofstatter E, Aktas B, Pusztai L. Multigene prognostic tests in breast cancer: past, present, future. Breast cancer Res. 2015;17:11.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Manjili MH, Najarian K, Wang XY. Signatures of tumor-immune interactions as biomarkers for breast cancer prognosis. Future Oncol. 2012;8(6):703–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Allinen M, Beroukhim R, Cai L, Brennan C, Lahti-Domenici J, Huang H, et al. Molecular characterization of the tumor microenvironment in breast cancer. Cancer Cell. 2004;6(1):17–32.

    Article  CAS  PubMed  Google Scholar 

  40. Ma XJ, Dahiya S, Richardson E, Erlander M, Sgroi DC. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast cancer Res. 2009;11(1):R7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Roman-Perez E, Casbas-Hernandez P, Pirone JR, Rein J, Carey LA, Lubet RA, et al. Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients. Breast cancer Res. 2012;14(2):R51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Troester MA, Lee MH, Carter M, Fan C, Cowan DW, Perez ER, et al. Activation of host wound responses in breast cancer microenvironment. Clin Cancer Res. 2009;15(22):7020–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H, et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat Med. 2008;14(5):518–27.

    Article  CAS  PubMed  Google Scholar 

  44. Casey T, Bond J, Tighe S, Hunter T, Lintault L, Patel O, et al. Molecular signatures suggest a major role for stromal cells in development of invasive breast cancer. Breast Cancer Res Treat. 2009;114(1):47–62.

    Article  CAS  PubMed  Google Scholar 

  45. Van den Eynden GG, Smid M, Van Laere SJ, Colpaert CG, Van der Auwera I, Bich TX, et al. Gene expression profiles associated with the presence of a fibrotic focus and the growth pattern in lymph node-negative breast cancer. Clin Cancer Res. 2008;14(10):2944–52.

    Article  PubMed  Google Scholar 

  46. Chang HY, Sneddon JB, Alizadeh AA, Sood R, West RB, Montgomery K, et al. Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds. PLoS Biol. 2004;2(2):E7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Marchini C, Montani M, Konstantinidou G, Orru R, Mannucci S, Ramadori G, et al. Mesenchymal/stromal gene expression signature relates to basal-like breast cancers, identifies bone metastasis and predicts resistance to therapies. PLoS One. 2010;5(11):e14131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Ye X, Weinberg RA. Epithelial-Mesenchymal plasticity: a central regulator of cancer progression. Trends Cell Biol. 2015;25(11):675–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Guo W, Keckesova Z, Donaher JL, Shibue T, Tischler V, Reinhardt F, et al. Slug and Sox9 cooperatively determine the mammary stem cell state. Cell. 2012;148(5):1015–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell. 2008;133(4):704–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Morel AP, Lievre M, Thomas C, Hinkal G, Ansieau S, Puisieux A. Generation of breast cancer stem cells through epithelial-mesenchymal transition. PLoS One. 2008;3(8):e2888.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Planche A, Bacac M, Provero P, Fusco C, Delorenzi M, Stehle JC, et al. Identification of prognostic molecular features in the reactive stroma of human breast and prostate cancer. PLoS One. 2011;6(5):e18640.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Winslow S, Leandersson K, Edsjo A, Larsson C. Prognostic stromal gene signatures in breast cancer. Breast Cancer Res. 2015;17:23.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Desmedt C, Majjaj S, Kheddoumi N, Singhal SK, Haibe-Kains B, El Ouriaghli F, et al. Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment. Clinical Cancer Res. 2012;18(4):1004–14.

    Article  CAS  Google Scholar 

  55. Rajski M, Zanetti-Dallenbach R, Vogel B, Herrmann R, Rochlitz C, Buess M. IGF-I induced genes in stromal fibroblasts predict the clinical outcome of breast and lung cancer patients. BMC Med. 2010;8(1):1–18.

    Google Scholar 

  56. Bredholt G, Mannelqvist M, Stefansson IM, Birkeland E, Bo TH, Oyan AM, et al. Tumor necrosis is an important hallmark of aggressive endometrial cancer and associates with hypoxia, angiogenesis and inflammation responses. Oncotarget. 2015;6(37):39676–91.

    Article  PubMed  PubMed Central  Google Scholar 

  57. West RB, Nuyten DS, Subramanian S, Nielsen TO, Corless CL, Rubin BP, et al. Determination of stromal signatures in breast carcinoma. PLoS Biol. 2005;3(6):e187.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Dvorak HF. Tumors: wounds that do not heal. Similarities between tumor stroma generation and wound healing. N Engl J Med. 1986;315(26):1650–9.

    Article  CAS  PubMed  Google Scholar 

  59. Tchou J, Kossenkov AV, Chang L, Satija C, Herlyn M, Showe LC, et al. Human breast cancer associated fibroblasts exhibit subtype specific gene expression profiles. BMC Med Genet. 2012;5:39.

    CAS  Google Scholar 

  60. Bauer M, Su G, Casper C, He R, Rehrauer W, Friedl A. Heterogeneity of gene expression in stromal fibroblasts of human breast carcinomas and normal breast. Oncogene. 2010;29(12):1732–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Singer CF, Gschwantler-Kaulich D, Fink-Retter A, Haas C, Hudelist G, Czerwenka K, et al. Differential gene expression profile in breast cancer-derived stromal fibroblasts. Breast Cancer Res Treat. 2008;110(2):273–81.

    Article  CAS  PubMed  Google Scholar 

  62. Frings O, Augsten M, Tobin NP, Carlson J, Paulsson J, Pena C, et al. Prognostic significance in breast cancer of a gene signature capturing stromal PDGF signaling. Am J Pathol. 2013;182(6):2037–47.

    Article  CAS  PubMed  Google Scholar 

  63. Siletz A, Kniazeva E, Jeruss JS, Shea LD. Transcription factor networks in invasion-promoting breast carcinoma-associated fibroblasts. Cancer Microenviron. 2013;6(1):91–107.

    Article  CAS  PubMed  Google Scholar 

  64. Navab R, Strumpf D, Bandarchi B, Zhu CQ, Pintilie M, Ramnarine VR, et al. Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer. Proc Natl Acad Sci U S A. 2011;108(17):7160–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Woelfle U, Cloos J, Sauter G, Riethdorf L, Janicke F, van Diest P, et al. Molecular signature associated with bone marrow micrometastasis in human breast cancer. Cancer Res. 2003;63(18):5679–84.

    CAS  PubMed  Google Scholar 

  66. Bergamaschi A, Tagliabue E, Sorlie T, Naume B, Triulzi T, Orlandi R, et al. Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome. J Pathol. 2008;214(3):357–67.

    Article  CAS  PubMed  Google Scholar 

  67. Triulzi T, Casalini P, Sandri M, Ratti M, Carcangiu ML, Colombo MP, et al. Neoplastic and stromal cells contribute to an extracellular matrix gene expression profile defining a breast cancer subtype likely to progress. PLoS One. 2013;8(2):e56761.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wallgard E, Larsson E, He L, Hellstrom M, Armulik A, Nisancioglu MH, et al. Identification of a core set of 58 gene transcripts with broad and specific expression in the microvasculature. Arterioscler Thromb Vasc Biol. 2008;28(8):1469–76.

    Article  CAS  PubMed  Google Scholar 

  69. Hu Z, Fan C, Livasy C, He X, Oh DS, Ewend MG, et al. A compact VEGF signature associated with distant metastases and poor outcomes. BMC Med. 2009;7:9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Pepin F, Bertos N, Laferriere J, Sadekova S, Souleimanova M, Zhao H, et al. Gene-expression profiling of microdissected breast cancer microvasculature identifies distinct tumor vascular subtypes. Breast Cancer Res. 2012;14(4):R120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Bender RJ, Mac Gabhann F. Expression of VEGF and semaphorin genes define subgroups of triple negative breast cancer. PLoS One. 2013;8(5):e61788.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Wallace JA, Li F, Balakrishnan S, Cantemir-Stone CZ, Pecot T, Martin C, et al. Ets2 in tumor fibroblasts promotes angiogenesis in breast cancer. PLoS One. 2013;8(8):e71533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Xiao L, Harrell JC, Perou CM, Dudley AC. Identification of a stable molecular signature in mammary tumor endothelial cells that persists in vitro. Angiogenesis. 2014;17(3):511–8.

    Article  CAS  PubMed  Google Scholar 

  74. Chang CW, Tsai CW, Wang HF, Tsai HC, Chen HY, Tsai TF, et al. Identification of a developmentally regulated striatum-enriched zinc-finger gene, Nolz-1, in the mammalian brain. Proc Natl Acad Sci U S A. 2004;101(8):2613–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Matsumoto K, Nishihara S, Kamimura M, Shiraishi T, Otoguro T, Uehara M, et al. The prepattern transcription factor Irx2, a target of the FGF8/MAP kinase cascade, is involved in cerebellum formation. Nat Neurosci. 2004;7(6):605–12.

    Article  CAS  PubMed  Google Scholar 

  76. Mannelqvist M, Stefansson IM, Bredholt G, Hellem Bo T, Oyan AM, Jonassen I, et al. Gene expression patterns related to vascular invasion and aggressive features in endometrial cancer. Am J Pathol. 2011;178(2):861–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Mannelqvist M, Wik E, Stefansson IM, Akslen LA. An 18-gene signature for vascular invasion is associated with aggressive features and reduced survival in breast cancer. PLoS One. 2014;9(6):e98787.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Stefansson IM, Raeder M, Wik E, Mannelqvist M, Kusonmano K, Knutsvik G, et al. Increased angiogenesis is associated with a 32-gene expression signature and 6p21 amplification in aggressive endometrial cancer. Oncotarget. 2015;6:10634–45.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Harrell JC, Pfefferle AD, Zalles N, Prat A, Fan C, Khramtsov A, et al. Endothelial-like properties of claudin-low breast cancer cells promote tumor vascular permeability and metastasis. Clin Exp Metastasis. 2014;31(1):33–45.

    Article  CAS  PubMed  Google Scholar 

  80. Pitroda SP, Zhou T, Sweis RF, Filippo M, Labay E, Beckett MA, et al. Tumor endothelial inflammation predicts clinical outcome in diverse human cancers. PLoS One. 2012;7(10):e46104.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Teschendorff AE, Miremadi A, Pinder SE, Ellis IO, Caldas C. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol. 2007;8(8):R157.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Rody A, Karn T, Liedtke C, Pusztai L, Ruckhaeberle E, Hanker L, et al. A clinically relevant gene signature in triple negative and basal-like breast cancer. Breast Cancer Res. 2011;13(5):R97.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Alexe G, Dalgin GS, Scanfeld D, Tamayo P, Mesirov JP, DeLisi C, et al. High expression of lymphocyte-associated genes in node-negative HER2+ breast cancers correlates with lower recurrence rates. Cancer Res. 2007;67(22):10669–76.

    Article  CAS  PubMed  Google Scholar 

  84. Schmidt M, Bohm D, von Torne C, Steiner E, Puhl A, Pilch H, et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res. 2008;68(13):5405–13.

    Article  CAS  PubMed  Google Scholar 

  85. Schmidt M, Hellwig B, Hammad S, Othman A, Lohr M, Chen Z, et al. A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors. Clinical Cancer Res. 2012;18(9):2695–703.

    Article  CAS  Google Scholar 

  86. Hsu DS, Kim MK, Balakumaran BS, Acharya CR, Anders CK, Clay T, et al. Immune signatures predict prognosis in localized cancer. Cancer Investig. 2010;28(7):765–73.

    Article  CAS  Google Scholar 

  87. Bianchini G, Qi Y, Alvarez RH, Iwamoto T, Coutant C, Ibrahim NK, et al. Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and -negative cancers. J Clin Oncol. 2010;28(28):4316–23.

    Article  PubMed  Google Scholar 

  88. Nagalla S, Chou JW, Willingham MC, Ruiz J, Vaughn JP, Dubey P, et al. Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis. Genome Biol. 2013;14(4):R34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Ascierto ML, Kmieciak M, Idowu MO, Manjili R, Zhao Y, Grimes M, et al. A signature of immune function genes associated with recurrence-free survival in breast cancer patients. Breast Cancer Res Treat. 2012;131(3):871–80.

    Article  CAS  PubMed  Google Scholar 

  90. Iglesia MD, Vincent BG, Parker JS, Hoadley KA, Carey LA, Perou CM, et al. Prognostic B-cell signatures using mRNA-seq in patients with subtype-specific breast and ovarian cancer. Clinical Cancer Res. 2014;20(14):3818–29.

    Article  CAS  Google Scholar 

  91. Coronella JA, Spier C, Welch M, Trevor KT, Stopeck AT, Villar H, et al. Antigen-driven oligoclonal expansion of tumor-infiltrating B cells in infiltrating ductal carcinoma of the breast. J Immunol. 2002;169(4):1829–36.

    Article  CAS  PubMed  Google Scholar 

  92. Hansen MH, Nielsen H, Ditzel HJ. The tumor-infiltrating B cell response in medullary breast cancer is oligoclonal and directed against the autoantigen actin exposed on the surface of apoptotic cancer cells. Proc Natl Acad Sci U S A. 2001;98(22):12659–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Nzula S, Going JJ, Stott DI. Antigen-driven clonal proliferation, somatic hypermutation, and selection of B lymphocytes infiltrating human ductal breast carcinomas. Cancer Res. 2003;63(12):3275–80.

    CAS  PubMed  Google Scholar 

  94. Perez EA, Thompson EA, Ballman KV, Anderson SK, Asmann YW, Kalari KR, et al. Genomic analysis reveals that immune function genes are strongly linked to clinical outcome in the north central cancer treatment group n9831 adjuvant trastuzumab trial. J Clinical Oncol. 2015;33(7):701–8.

    Article  CAS  Google Scholar 

  95. Rody A, Holtrich U, Pusztai L, Liedtke C, Gaetje R, Ruckhaeberle E, et al. T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers. Breast Cancer Res. 2009;11(2):R15.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  96. Akalay I, Janji B, Hasmim M, Noman MZ, Andre F, De Cremoux P, et al. Epithelial-to-mesenchymal transition and autophagy induction in breast carcinoma promote escape from T-cell-mediated lysis. Cancer Res. 2013;73(8):2418–27.

    Article  CAS  PubMed  Google Scholar 

  97. Akalay I, Tan TZ, Kumar P, Janji B, Mami-Chouaib F, Charpy C, et al. Targeting WNT1-inducible signaling pathway protein 2 alters human breast cancer cell susceptibility to specific lysis through regulation of KLF-4 and miR-7 expression. Oncogene. 2015;34(17):2261–71.

    Article  CAS  PubMed  Google Scholar 

  98. Kudo-Saito C, Shirako H, Takeuchi T, Kawakami Y. Cancer Metastasis is accelerated through immunosuppression during snail-induced EMT of cancer cells. Cancer Cell. 2009;15(3):195–206.

    Article  CAS  PubMed  Google Scholar 

  99. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A. 1998;95(25):14863–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Gibbons FD, Roth FP. Judging the quality of gene expression-based clustering methods using gene annotation. Genome Res. 2002;12(10):1574–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Simon RMKE, McShane LM, Radmacher MD, Wright GW, Zhao Y. Statistics for biology and health: design and analysis of DNA microarray investigations. New York: Springer; 2004.

    Google Scholar 

  102. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet. 2006;38(9):1043–8.

    Article  CAS  PubMed  Google Scholar 

  103. Chen DT, Hsu YL, Fulp WJ, Coppola D, Haura EB, Yeatman TJ, et al. Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer. J Natl Cancer Inst. 2011;103(24):1859–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Kato K. Algorithm for in vitro diagnostic multivariate index assay. Breast Cancer. 2009;16(4):248–51.

    Article  PubMed  Google Scholar 

  106. Petersen K, Rajcevic U, Abdul Rahim SA, Jonassen I, Kalland KH, Jimenez CR, et al. Gene set based integrated data analysis reveals phenotypic differences in a brain cancer model. PLoS One. 2013;8(7):e68288.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Cancer Genome Atlas N. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.

    Article  CAS  Google Scholar 

  108. Ciriello G, Gatza ML, Beck AH, Wilkerson MD, Rhie SK, Pastore A, et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell. 2015;163(2):506–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Moffitt RA, Marayati R, Flate EL, Volmar KE, Loeza SG, Hoadley KA, et al. Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma. Nat Genet. 2015;47(10):1168–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Lawson DA, Bhakta NR, Kessenbrock K, Prummel KD, Yu Y, Takai K, et al. Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells. Nature. 2015;526:131–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Reuter JA, Ortiz-Urda S, Kretz M, Garcia J, Scholl FA, Pasmooij AM, et al. Modeling inducible human tissue neoplasia identifies an extracellular matrix interaction network involved in cancer progression. Cancer Cell. 2009;15(6):477–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Elisabeth Wik .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Wik, E., Akslen, L.A. (2017). Gene Expression Signatures of the Tumor Microenvironment: Relation to Tumor Progress in Breast Cancer. In: Akslen, L., Watnick, R. (eds) Biomarkers of the Tumor Microenvironment. Springer, Cham. https://doi.org/10.1007/978-3-319-39147-2_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-39147-2_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39145-8

  • Online ISBN: 978-3-319-39147-2

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics