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Integrated Bioinformatics Approach Reveals Crosstalk Between Tumor Stroma and Peripheral Blood Mononuclear Cells in Breast Cancer

  • He, Lang (Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China) ;
  • Wang, Dan (Department of Biomedicine, Chengdu Medical College) ;
  • Wei, Na (Sichuan Cancer Hospital and Institute) ;
  • Guo, Zheng (Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China)
  • Published : 2016.04.11

Abstract

Breast cancer is now the leading cause of cancer death in women worldwide. Cancer progression is driven not only by cancer cell intrinsic alterations and interactions with tumor microenvironment, but also by systemic effects. Integration of multiple profiling data may provide insights into the underlying molecular mechanisms of complex systemic processes. We performed a bioinformatic analysis of two public available microarray datasets for breast tumor stroma and peripheral blood mononuclear cells, featuring integrated transcriptomics data, protein-protein interactions (PPIs) and protein subcellular localization, to identify genes and biological pathways that contribute to dialogue between tumor stroma and the peripheral circulation. Genes of the integrin family as well as CXCR4 proved to be hub nodes of the crosstalk network and may play an important role in response to stroma-derived chemoattractants. This study pointed to potential for development of therapeutic strategies that target systemic signals travelling through the circulation and interdict tumor cell recruitment.

Keywords

References

  1. Alon R, Feigelson SW (2012). Chemokine-triggered leukocyte arrest: force-regulated bi-directional integrin activation in quantal adhesive contacts. Curr Opin Cell Biol, 24, 670-6. https://doi.org/10.1016/j.ceb.2012.06.001
  2. Barrett T, Wilhite SE, Ledoux P, et al (2013). NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res, 41, 991-5. https://doi.org/10.1093/nar/gks1193
  3. Biometric Research Branch home page (2015c).
  4. Breast Cancer Treatment (2015b). (PDQ(R)) - National Library of Medicine - PubMed Health.
  5. Christopher MJ, Rao M, Liu F, et al (2011). Expression of the G-CSF receptor in monocytic cells is sufficient to mediate hematopoietic progenitor mobilization by G-CSF in mice. J Exp Med, 208, 251-60. https://doi.org/10.1084/jem.20101700
  6. de la Puente P, Muz B, Azab F, et al (2013). Cell trafficking of endothelial progenitor cells in tumor progression. Clin Cancer Res, 19, 3360-8. https://doi.org/10.1158/1078-0432.CCR-13-0462
  7. Ding Y, Shen J, Zhang G, et al (2015). CD40 controls CXCR5-induced recruitment of myeloid-derived suppressor cells to gastric cancer. Oncotarget, 6, 38901-11. https://doi.org/10.18632/oncotarget.5644
  8. Domanska UM, Kruizinga RC, Nagengast WB, et al (2013). A review on CXCR4/CXCL12 axis in oncology: no place to hide. Eur J Cancer, 49, 219-30. https://doi.org/10.1016/j.ejca.2012.05.005
  9. Ellem SJ, Taylor RA, Furic L, et al (2014). A pro-tumourigenic loop at the human prostate tumour interface orchestrated by oestrogen, CXCL12 and mast cell recruitment. J Pathol, 234, 86-98. https://doi.org/10.1002/path.4386
  10. Finak G, Bertos N, Pepin F, et al (2008a). Stromal gene expression predicts clinical outcome in breast cancer. Nat Med, 14, 518-27. https://doi.org/10.1038/nm1764
  11. Franceschini A, Szklarczyk D, Frankild S, et al (2013). STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res, 41, 808-15. https://doi.org/10.1093/nar/gks1094
  12. Gil M, Komorowski MP, Seshadri M, et al (2014). CXCL12/CXCR4 blockade by oncolytic virotherapy inhibits ovarian cancer growth by decreasing immunosuppression and targeting cancer-initiating cells. J Immunol, 193, 5327-37. https://doi.org/10.4049/jimmunol.1400201
  13. Graeber TG, Eisenberg D (2001). Bioinformatic identification of potential autocrine signaling loops in cancers from gene expression profiles. Nat Genet, 29, 295-300. https://doi.org/10.1038/ng755
  14. Hanahan D, Coussens LM (2012). Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell, 21, 309-22. https://doi.org/10.1016/j.ccr.2012.02.022
  15. Hattori K, Heissig B, Tashiro K, et al (2001). Plasma elevation of stromal cell-derived factor-1 induces mobilization of mature and immature hematopoietic progenitor and stem cells. Blood, 97, 3354-60. https://doi.org/10.1182/blood.V97.11.3354
  16. Hiratsuka S, Duda DG, Huang Y, et al (2011). C-X-C receptor type 4 promotes metastasis by activating p38 mitogenactivated protein kinase in myeloid differentiation antigen(Gr-1)-positive cells. Proc Natl Acad Sci U S A, 108, 302-307. https://doi.org/10.1073/pnas.1016917108
  17. Huang DW, Sherman BT, Lempicki RA (2009). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 4, 44-57. https://doi.org/10.1038/nprot.2008.211
  18. Irizarry RA, Hobbs B, Collin F, et al (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4, 249-64. https://doi.org/10.1093/biostatistics/4.2.249
  19. Joyce JA, Fearon DT (2015). T cell exclusion, immune privilege, and the tumor microenvironment. Science, 348, 74-80. https://doi.org/10.1126/science.aaa6204
  20. Kuehn C, Vermette P, Fulop T (2014). Cross talk between the extracellular matrix and the immune system in the context of endocrine pancreatic islet transplantation. A review article. Pathol Biol (Paris), 62, 67-78. https://doi.org/10.1016/j.patbio.2014.01.001
  21. Kwast AB, Voogd AC, Menke-Pluijmers MB, et al (2014). Prognostic factors for survival in metastatic breast cancer by hormone receptor status. Breast Cancer Res Treat, 145, 503-11. https://doi.org/10.1007/s10549-014-2964-0
  22. LaBreche HG, Nevins JR, Huang E (2011). Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors. Bmc Med Genomics, 4, 61. https://doi.org/10.1186/1755-8794-4-61
  23. Ley K, Laudanna C, Cybulsky MI, et al (2007). Getting to the site of inflammation: the leukocyte adhesion cascade updated. Nat Rev Immunol, 7, 678-89. https://doi.org/10.1038/nri2156
  24. Lourenco S, Teixeira VH, Kalber T, et al (2015). Macrophage migration inhibitory factor-CXCR4 is the dominant chemotactic axis in human mesenchymal stem cell recruitment to tumors. J Immunol, 194, 3463-74. https://doi.org/10.4049/jimmunol.1402097
  25. Maenhout SK, Thielemans K, Aerts JL (2014). Location, location, location: functional and phenotypic heterogeneity between tumor-infiltrating and non-infiltrating myeloidderived suppressor cells. Oncoimmunol, 3, 956579. https://doi.org/10.4161/21624011.2014.956579
  26. McAllister SS, Weinberg RA (2014a). The tumour-induced systemic environment as a critical regulator of cancer progression and metastasis. Nat Cell Biol, 16, 717-27. https://doi.org/10.1038/ncb3015
  27. McAllister SS, Weinberg RA (2014b). The tumour-induced systemic environment as a critical regulator of cancer progression and metastasis. Nat Cell Biol, 16, 717-27. https://doi.org/10.1038/ncb3015
  28. Orimo A, Gupta PB, Sgroi DC, et al (2005). Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell, 121, 335-48. https://doi.org/10.1016/j.cell.2005.02.034
  29. Quail DF, Joyce JA (2013). Microenvironmental regulation of tumor progression and metastasis. Nat Med, 19, 1423-37. https://doi.org/10.1038/nm.3394
  30. Schmid MC, Franco I, Kang SW, et al (2013). PI3-kinase gamma promotes Rap1a-mediated activation of myeloid cell integrin alpha4beta1, leading to tumor inflammation and growth. Plos One, 8, 60226. https://doi.org/10.1371/journal.pone.0060226
  31. Seubert B, Grunwald B, Kobuch J, et al (2015). Tissue inhibitor of metalloproteinases (TIMP)-1 creates a premetastatic niche in the liver through SDF-1/CXCR4-dependent neutrophil recruitment in mice. Hepatol, 61, 238-48. https://doi.org/10.1002/hep.27378
  32. Shaked Y, McAllister S, Fainaru O, et al (2014). Tumor dormancy and the angiogenic switch: possible implications of bone marrow- derived cells. Curr Pharm Des, 20, 4920-33. https://doi.org/10.2174/1381612819666131125153536
  33. Shannon P, Markiel A, Ozier O, et al (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 13, 2498-504. https://doi.org/10.1101/gr.1239303
  34. Shetty S, Bruns T, Weston CJ, et al (2012). Recruitment mechanisms of primary and malignant B cells to the human liver. Hepatol, 56, 1521-31. https://doi.org/10.1002/hep.25790
  35. Song N, Choi JY, Sung H, et al (2015). Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes. Plos One, 10, 122413.
  36. Spaeth E, Klopp A, Dembinski J, et al (2008). Inflammation and tumor microenvironments: defining the migratory itinerary of mesenchymal stem cells. Gene Ther, 15, 730-8. https://doi.org/10.1038/gt.2008.39
  37. Tusher VG, Tibshirani R, Chu G (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A, 98, 5116-21. https://doi.org/10.1073/pnas.091062498
  38. UniProt (2015d). a hub for protein information. Nucleic Acids Res, 43, 204-12. https://doi.org/10.1093/nar/gku989
  39. WHO (2015a). Breast cancer: prevention and control.
  40. Zhang QQ, Hu XW, Liu YL, et al (2015). CD11b deficiency suppresses intestinal tumor growth by reducing myeloid cell recruitment. Sci Rep, 5, 15948. https://doi.org/10.1038/srep15948