Abstract
In the field of pathology it is clear that molecular genomics and digital imaging represent two promising future directions, and both are as relevant to the tumor microenvironment as they are to the tumor itself (Beck AH et al. Sci Transl Med 3(108):108ra113–08ra113, 2011). Digital imaging, or whole slide imaging (WSI), of glass histology slides facilitates a number of value-added competencies which were not previously possible with the traditional analog review of these slides under a microscope by a pathologist. As an important tool for investigational research, digital pathology can leverage the quantification and reproducibility offered by image analysis to add value to the pathology field. This chapter will focus on the application of image analysis to investigate the tumor microenvironment and how quantitative investigation can provide deeper insight into our understanding of the tumor to tumor microenvironment relationship.
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References
Amat-Roldan I et al (2010) Fast image analysis in polarization SHG microscopy. Opt Express 18(16):17209–17219
Anderson A, Chaplain M, Rejniak K (eds) (2007) Single-cell-based models in biology and medicine. Birkhauser-Verlag, Mathematics and Bioscisnce in Interaction (MBI) series
Anitei M-G et al (2014) Prognostic and predictive values of the immunoscore in patients with rectal cancer. Clin Cancer Res 20(7):1891–1899
Beck AH et al (2011) Systematic analysis of breast cancer morphology uncovers stromal features associated with survival. Sci Transl Med 3(108):108ra113–108ra113
Ben-Baruch A (2002) Host microenvironment in breast cancer development: inflammatory cells, cytokines and chemokines in breast cancer progression-reciprocal tumor–microenvironment interactions. Breast Cancer Res 5(1):31
Bradford JA et al (2004) Fluorescence intensity multiplexing: simultaneous seven marker, two color immunophenotyping using flow cytometry. Cytometry Part A 61(2):142–152
Chien M-P et al (2013) Enzyme-directed assembly of nanoparticles in tumors monitored by in vivo whole animal imaging and ex vivo super-resolution fluorescence imaging. J Am Chem Soc 135(50):18710–18713
Deepak RU et al (2015) Computer assisted pap smear analyser for cervical cancer screening using quantitative microscopy. J Cytol Histol S3:010. doi:10.4172/2157-7099.S3-010
Dvorak HF et al (2011) Tumor microenvironment and progression. J Surg Oncol 103(6):468–474
Egeblad M et al (2008) Visualizing stromal cell dynamics in different tumor microenvironments by spinning disk confocal microscopy. Dis Model Mech 1(2–3):155–167
Estrella V et al (2013) Acidity generated by the tumor microenvironment drives local invasion. Cancer Res 73(5):1524–1535
Faratian D et al (2011) Heterogeneity mapping of protein expression in tumors using quantitative immunofluorescence. J Vis Exp 56:e3334
Glatz K, Pritt B, Glatz D, Hartmann A, O’Brien MJ, Blaszyk H (2007) A multinational, internet-based assessment of observer variability in the diagnosis of serrated colorectal polyps. Am J Clin Pathol 127(6):938–945
Gurcan MN et al (2009) Histopathological image analysis: a review. IEEE Rev Biomed Eng 2:147–171
Helm J, Centeno BA, Coppola D et al (2009) Histologic characteristics enhance predictive value of American Joint Committee on Cancer staging in resectable pancreas cancer. Cancer 115(18):4080–4089
Iyengar P et al (2005) Adipocyte-derived collagen VI affects early mammary tumor progression in vivo, demonstrating a critical interaction in the tumor/stroma microenvironment. J Clin Investig 115(5):1163
Junttila MR, de Sauvage FJ (2013) Influence of tumour micro-environment heterogeneity on therapeutic response. Nature 501(7467):346–354
Kayser K et al (2010) AI (artificial intelligence) in histopathology–from image analysis to automated diagnosis. Folia Histochem Cytobiol 47(3):355–354
Karabulut A, Jesper R, Marianne Hamilton T, Finn P, Nielsen HW, Erik D (1995) Observer variability in the histologic assessment of oral premalignant lesions. J Oral Pathol Med 24(5):198–200
Kenny PA, Lee GY, Bissell MJ (2007) Targeting the tumor microenvironment. Front Biosci 12:3468
Levenson RM, Cronin PJ, Pankratov KK (2003) Spectral imaging for brightfield microscopy. Biomedical Optics 2003. International Society for Optics and Photonics
Li H, Fan X, Houghton JM (2007) Tumor microenvironment: the role of the tumor stroma in cancer. J Cell Biochem 101(4):805–815
Lloyd MC et al (2010) Using image analysis as a tool for assessment of prognostic and predictive biomarkers for breast cancer: how reliable is it? J Pathol Inform 1:29
Lloyd MC, Alfarouk KO, Verduzco D, Bui MM, Gillies RJ, Ibrahim ME, Brown JS, Gatenby RA (2014) Vascular measurements correlate with estrogen receptor status. BMC Cancer 14(1):279
Lloyd MC, Rejniak KA, Brown JS, Gatenby RA, Minor ES, Bui MM (2015) Pathology to enhance precision medicine in oncology: lessons from landscape ecology. Adv Anat Pathol 22(4):267–272
Mass RD et al (2005) Evaluation of clinical outcomes according to HER2 detection by fluorescence in situ hybridization in women with metastatic breast cancer treated with trastuzumab. Clin Breast Cancer 6(3):240–246
Mavaddat N et al (2010) Incorporating tumour pathology information into breast cancer risk prediction algorithms. Breast Cancer Res 12(3):R28
McInerney T, Terzopoulos D (1996) Deformable models in medical image analysis: a survey. Med Image Anal 1(2):91–108
Messina JL et al (2012) 12-Chemokine gene signature identifies lymph node-like structures in melanoma: potential for patient selection for immunotherapy? Sci Rep 2:765
Nyberg P, Salo T, Kalluri R (2007) Tumor microenvironment and angiogenesis. Front Biosci: A J Virtual Libr 13:6537–6553
Ohashi A et al (2005) Quantitative analysis of the microvascular architecture observed on magnification endoscopy in cancerous and benign gastric lesions. Endoscopy 37(12):1215–1219
Oka M (1990) Second harmonic generation. U.S. Patent No. 4,910,740. 20 Mar
Peng C-W et al (2011) Patterns of cancer invasion revealed by QDs-based quantitative multiplexed imaging of tumor microenvironment. Biomaterials 32(11):2907–2917
Provenzano PP, Eliceiri KW, Keely PJ (2009) Multiphoton microscopy and fluorescence lifetime imaging microscopy (FLIM) to monitor metastasis and the tumor microenvironment. Clin Exp Metastasis 26(4):357–370
Rejniak KA (2012) Homeostatic imbalance in epithelial ducts and its role in carcinogenesis. Scientifica 132978
Robertson AJ, Anderson JM, Swanson Beck J, Burnett RA, Howatson SR, Lee FD, Lessells AM, McLaren KM, Moss SM, Simpson JG (1989) Observer variability in histopathological reporting of cervical biopsy specimens. J Clin Pathol 42(3):231–238
Rojo MG, Bueno G, Slodkowska J (2010) Review of imaging solutions for integrated quantitative immunohistochemistry in the Pathology daily practice. Folia Histochem Cytobiol 47(3):349–348
Sarode VR et al (2011) A comparative analysis of biomarker expression and molecular subtypes of pure ductal carcinoma in situ and invasive breast carcinoma by image analysis: relationship of the subtypes with histologic grade, Ki67, p53 overexpression, and DNA ploidy. Int J Breast Cancer 217060
Schindewolf T et al (1994) Evaluation of different image acquisition techniques for a computer vision system in the diagnosis of malignant melanoma. J Am Acad Dermatol 31(1):33–41
Serra J (1982) Image analysis and mathematical morphology, vol 1. Academic, New York
Song N, Tao LI, Xue-Min Z (2014) Immune cells in tumor microenvironment. Prog Biochem Biophys 41(10):1075–1084
Sugimoto H, Mundel TM, Kieran MW, Kalluri R (2006) Identification of fibroblast heterogeneity in the tumor microenvironment. Cancer Biol Ther 5(12):1640–1646
Uchugonova A et al (2013) Multiphoton tomography visualizes collagen fibers in the tumor microenvironment that maintain cancer cell anchorage and shape. J Cell Biochem 114(1):99–102
Wetzels RH et al (1989) Detection of basement membrane components and basal cell keratin 14 in noninvasive and invasive carcinomas of the breast. Am J Pathol 134(3):571
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Lloyd, M.C., Johnson, J.O., Kasprzak, A., Bui, M.M. (2016). Image Analysis of the Tumor Microenvironment. In: Rejniak, K. (eds) Systems Biology of Tumor Microenvironment. Advances in Experimental Medicine and Biology, vol 936. Springer, Cham. https://doi.org/10.1007/978-3-319-42023-3_1
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DOI: https://doi.org/10.1007/978-3-319-42023-3_1
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