Infrared imaging of MDA-MB-231 breast cancer cell line phenotypes in 2D and 3D cultures.

One current challenge in the field of breast cancer infrared imaging is the identification of carcinoma cell subtypes in the tissue. Neither sequencing nor immunochemistry is currently able to provide a cell by cell thorough classification. The latter is needed to build accurate statistical models capable of recognizing the diversity of breast cancer cell lines that may be present in a tissue section. One possible approach for overcoming this problem is to obtain the IR spectral signature of well-characterized tumor cell lines in culture. Cultures in three-dimensional matrices appear to generate an environment that mimics better the in vivo environment. There are, at present, series of breast cancer cell lines that have been thoroughly characterized in two- and three-dimensional (2D and 3D) cultures by full transcriptomics analyses. In this work, we describe the methods used to grow, to process, and to characterize a triple-negative breast cancer cell line, MDA-MB-231, in 3D laminin-rich extracellular matrix (lrECM) culture and compare it with traditional monolayer cultures and tissue sections. While unsupervised analyses did not completely separate spectra of cells grown in 2D from 3D lrECM cultures, a supervised statistical analysis resulted in an almost perfect separation. When IR spectral responses of epithelial tumor cells from clinical triple-negative breast carcinoma samples were added to these data, a principal component analysis indicated that they cluster closer to the spectra of 3D culture cells than to the spectra of cells grown on a flat plastic substrata. This result is encouraging because of correlating well-characterized cell line features with clinical biopsies.

[1]  Genee Y. Lee,et al.  Three-dimensional culture models of normal and malignant breast epithelial cells , 2007, Nature Methods.

[2]  Benjamin Bird,et al.  Two step resonant Mie scattering correction of infrared micro‐spectral data: human lymph node tissue , 2010, Journal of biophotonics.

[3]  Keith R Bambery,et al.  Resonant Mie scattering (RMieS) correction applied to FTIR images of biological tissue samples. , 2012, The Analyst.

[4]  Decoding the evolution of a breast cancer genome , 2010, EMBO molecular medicine.

[5]  Harald Martens,et al.  RMieS‐EMSC correction for infrared spectra of biological cells: Extension using full Mie theory and GPU computing , 2010, Journal of biophotonics.

[6]  Rohit Bhargava,et al.  Integration of Molecular Profiling and Chemical Imaging to Elucidate Fibroblast-Microenvironment Impact on Cancer Cell Phenotype and Endocrine Resistance in Breast Cancer , 2014, PloS one.

[7]  Kevin C. Dorff,et al.  The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models , 2010, Nature Biotechnology.

[8]  M. Barcellos-Hoff,et al.  New highlights on stroma–epithelial interactions in breast cancer , 2004, Breast Cancer Research.

[9]  P. Lasch,et al.  Spatial resolution in infrared microspectroscopic imaging of tissues. , 2006, Biochimica et biophysica acta.

[10]  Claudio Sorio,et al.  Infrared spectroscopy and microscopy in cancer research and diagnosis. , 2012, American journal of cancer research.

[11]  E. Goormaghtigh,et al.  Amide-proton exchange of water-soluble proteins of different structural classes studied at the submolecular level by infrared spectroscopy. , 1997, Biochemistry.

[12]  Catherine C. Park,et al.  Breast cancer cells in three-dimensional culture display an enhanced radioresponse after coordinate targeting of integrin alpha5beta1 and fibronectin. , 2010, Cancer research.

[13]  Wen-Lin Kuo,et al.  A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. , 2006, Cancer cell.

[14]  E Goormaghtigh,et al.  Cell Discrimination by Attenuated Total Reflection—Fourier Transform Infrared Spectroscopy: The Impact of Preprocessing of Spectra , 2006, Applied spectroscopy.

[15]  Keith R Bambery,et al.  Fourier transform infrared imaging and small angle x-ray scattering as a combined biomolecular approach to diagnosis of breast cancer. , 2008, Medical physics.

[16]  Max Diem,et al.  Microspectroscopy of single proliferating HeLa cells , 2005 .

[17]  Mina J Bissell,et al.  The organizing principle: microenvironmental influences in the normal and malignant breast. , 2002, Differentiation; research in biological diversity.

[18]  Erik Goormaghtigh,et al.  Lipid quantification method using FTIR spectroscopy applied on cancer cell extracts. , 2014, Biochimica et biophysica acta.

[19]  H. Yamaguchi,et al.  Membrane lipids in invadopodia and podosomes: Key structures for cancer invasion and metastasis , 2010, Oncotarget.

[20]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[21]  E. Goormaghtigh,et al.  Effects of the confluence rate on the FTIR spectrum of PC-3 prostate cancer cells in culture. , 2010, The Analyst.

[22]  Sarah E. Holton,et al.  Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging. , 2011, Biophysical journal.

[23]  E. Goormaghtigh,et al.  Determination of soluble and membrane protein structure by Fourier transform infrared spectroscopy. II. Experimental aspects, side chain structure, and H/D exchange. , 1994, Sub-cellular biochemistry.

[24]  Philip M. Long,et al.  Breast cancer classification and prognosis based on gene expression profiles from a population-based study , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[25]  Rohit Bhargava,et al.  Attenuated total reflectance Fourier-transform infrared spectroscopic imaging for breast histopathology. , 2012, Vibrational Spectroscopy.

[26]  E. Goormaghtigh,et al.  Protein secondary structure content in solution, films and tissues: redundancy and complementarity of the information content in circular dichroism, transmission and ATR FTIR spectra. , 2009, Biochimica et biophysica acta.

[27]  M J Bissell,et al.  Microenvironmental Regulators of Tissue Structure and Function Also Regulate Tumor Induction and Progression : The Role of Extracellular Matrix and Its Degrading Enzymes , 2022 .

[28]  H. Degani,et al.  Metabolic markers of breast cancer: enhanced choline metabolism and reduced choline-ether-phospholipid synthesis. , 2002, Cancer research.

[29]  Max Diem,et al.  Artificial neural networks as supervised techniques for FT‐IR microspectroscopic imaging , 2006, Journal of chemometrics.

[30]  Rohit Bhargava,et al.  Towards a practical Fourier transform infrared chemical imaging protocol for cancer histopathology , 2007, Analytical and bioanalytical chemistry.

[31]  E. Goormaghtigh,et al.  Evaluation of the information content in infrared spectra for protein secondary structure determination. , 2006, Biophysical journal.

[32]  Christine Desmedt,et al.  Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment. , 2014, The Analyst.

[33]  Erik Goormaghtigh,et al.  FTIR spectral signature of anticancer drug effects on PC-3 cancer cells: is there any influence of the cell cycle? , 2013, The Analyst.

[34]  H. Kleinman,et al.  Matrigel: basement membrane matrix with biological activity. , 2005, Seminars in cancer biology.

[35]  R. Xiang,et al.  Cancer Associated Fibroblasts Promote Tumor Growth and Metastasis by Modulating the Tumor Immune Microenvironment in a 4T1 Murine Breast Cancer Model , 2009, PloS one.

[36]  Peter Lasch,et al.  Minimising contributions from scattering in infrared spectra by means of an integrating sphere. , 2013, The Analyst.

[37]  G. Kroemer,et al.  Prognostic and predictive impact of intra- and peritumoral immune infiltrates. , 2011, Cancer research.

[38]  S. Scully,et al.  Extracellular Matrix-Induced Gene Expression in Human Breast Cancer Cells , 2009, Molecular Cancer Research.

[39]  C. Hirschmugl,et al.  Restoration and spectral recovery of mid-infrared chemical images. , 2012, Analytical chemistry.

[40]  J. Troge,et al.  Tumour evolution inferred by single-cell sequencing , 2011, Nature.

[41]  J. Rosen,et al.  Modelling breast cancer: one size does not fit all , 2007, Nature Reviews Cancer.

[42]  Ziad J. Sahab,et al.  Active Roles of Tumor Stroma in Breast Cancer Metastasis , 2012, International journal of breast cancer.

[43]  Genee Y. Lee,et al.  The morphologies of breast cancer cell lines in three‐dimensional assays correlate with their profiles of gene expression , 2007, Molecular oncology.

[44]  J. Buhmann,et al.  Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry , 2014, Nature Methods.

[45]  R. Lempicki,et al.  Evaluation of gene expression measurements from commercial microarray platforms. , 2003, Nucleic acids research.

[46]  Benjamin Bird,et al.  Spectral detection of micro-metastases in lymph node histo-pathology. , 2009, Journal of biophotonics.

[47]  P. Lasch,et al.  IR spectra and IR spectral maps of individual normal and cancerous cells. , 2002, Biopolymers.

[48]  N. Clarke,et al.  FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm. , 2012, The Analyst.

[49]  Valerie Speirs,et al.  Choosing the right cell line for breast cancer research , 2011, Breast Cancer Research.

[50]  C. Sotiriou,et al.  Breast cancer and melanoma cell line identification by FTIR imaging after formalin-fixation and paraffin-embedding. , 2013, The Analyst.

[51]  Bryan Frank,et al.  Independence and reproducibility across microarray platforms , 2005, Nature Methods.

[52]  Goormaghtigh Erik,et al.  SUBTRACTION OF ATMOSPHERIC WATER CONTRIBUTION IN FOURIER TRANSFORM INFRARED SPECTROSCOPY OF BIOLOGICAL MEMBRANES AND PROTEINS , 1994 .

[53]  H. Moses,et al.  Stromal fibroblasts in cancer initiation and progression , 2004, Nature.

[54]  Max Diem,et al.  Infrared Spectroscopy of Human Cells and Tissue: Detection of Disease , 2002, Technology in cancer research & treatment.