Subcellular localization of early biochemical transformations in cancer-activated fibroblasts using infrared spectroscopic imaging

Label-free imaging of fibroblast membrane interfaces and protein signatures with vibrational infrared photothermal and phase signals

Label-free vibrational imaging of biological samples has attracted significant interest due to its integration of structural and chemical information. Vibrational infrared photothermal amplitude and phase signal (VIPPS) imaging provide label-free chemical identification by targeting the characteristic resonances of biological compounds that are present in the mid-infrared fingerprint region (3 µm - 12 µm). High contrast imaging of subcellular features and chemical identification of protein secondary structures in unlabeled and labeled fibroblast cells embedded in a collagen-rich extracellular matrix is demonstrated by combining contrast from absorption signatures (amplitude signals) with sensitive detection of different heat properties (lock-in phase signals). We present that the detectability of nano-sized cell membranes is enhanced to well below the optical diffraction limit since the membranes are found to act as thermal barriers. VIPPS offers a novel combination of chemical imaging and thermal diffusion characterization that paves the way towards label-free imaging of cell models and tissues as well as the study of intracellular heat dynamics.

Infrared spectral microscopy as a tool to monitor lung fibrosis development in a model system

Tissue fibrosis is a progressive and destructive disease process that can occur in many different organs including the liver, kidney, skin, and lungs. Fibrosis is typically initiated by inflammation as a result of chronic insults such as infection, chemicals and autoimmune diseases. Current approaches to examine organ fibrosis are limited to radiological and histological analyses. Infrared spectroscopic imaging offers a potential alternative approach to gain insight into biochemical changes associated with fibrosis progression. In this study, we demonstrate that IR imaging of a mouse model of pulmonary fibrosis can identify biochemical changes observed with fibrosis progression and the beginning of resolution using K-means analysis, spectral ratios and multivariate data analysis. This study demonstrates that IR imaging may be a useful approach to understand the biochemical events associated with fibrosis initiation, progression and resolution for both the clinical setting and for assessing novel anti-fibrotic drugs in a model system.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer

Molecular analysis techniques such as gene expression analysis and proteomics have contributed greatly to our understanding of cancer heterogeneity. In prior studies, gene expression analysis was shown to stratify patient outcome on the basis of tumor-microenvironment associated genes. A specific gene expression profile, referred to as ECM3 (Extracellular Matrix Cluster 3), indicated poorer survival in patients with grade III tumors. In this work, we aimed to visualize the downstream effects of this gene expression profile onto the tissue, thus providing a spatial context to altered gene expression profiles. Using infrared spectroscopic imaging, we identified spectral patterns specific to the ECM3 gene expression profile, achieving a high spectral classification performance of 0.87 as measured by the area under the curve of the receiver operating characteristic curve. On a patient level, we correctly identified 20 out of 22 ECM3 group patients and 19 out of 20 non-ECM3 group patients by using this spectroscopic imaging-based classifier. By comparing pixels that were identified as ECM3 or non-ECM3 with H&E and IHC images, we were also able to observe an association between tissue morphology and the gene expression clusters, showing the ability of our method to capture broad outcome associated features from infrared images.

A comparison of mid-infrared spectral regions on accuracy of tissue classification

Infrared (IR) spectroscopic imaging, utilizing both the molecular and structural disease signatures, enables extensive profiling of tumors and their microenvironments. Here, we examine the relative merits of using either the fingerprint or the high frequency regions of the IR spectrum for tissue histopathology. We selected a complex model as a test case, evaluating both stromal and epithelial segmentation for various breast pathologies. IR spectral classification in each of these spectral windows is quantitatively assessed by estimating area under the curve (AUC) of the receiver operating characteristic curve (ROC) for pixel level accuracy and images for diagnostic ability. We found only small differences, though some that may be sufficiently important in diagnostic tasks to be clinically significant, between the two regions with the fingerprint region-based classifiers consistently emerging as more accurate. The work provides added evidence and comparison with fingerprint region, complex models, and previously untested tissue type (breast) - that the use of restricted spectral regions can provide high accuracy. Our study indicates that the fingerprint region is ideal for epithelial and stromal models to obtain high pixel level accuracies. Glass slides provide a limited spectral feature set but provides accurate information at the patient level.

Infrared micro-spectroscopy of human tissue: principles and future promises

This article summarizes the methods employed, and the progress achieved over the past two decades in applying vibrational (Raman and IR) micro-spectroscopy to problems of medical diagnostics and cellular biology. During this time, several research groups have verified the enormous information contained in vibrational spectra; in fact, information on protein, lipid and metabolic composition of cells and tissues can be deduced by decoding the observed vibrational spectra. This decoding process is aided by the availability of computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared micro-spectral data has enabled the collection of images of cells and tissues based solely on vibrational spectroscopic data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational spectroscopy in the biological and biomedical arenas.

Gene expression data and FTIR spectra provide a similar phenotypic description of breast cancer cell lines in 2D and 3D cultures

Gene expression patterns and FTIR spectral data are strongly correlated. Both identified the genotypes and phenotypes of breast cancer cell lines.

Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis

Infrared spectroscopic tissue imaging is a potentially powerful adjunct tool to current histopathology techniques. By coupling the biochemical signature obtained through infrared spectroscopy to the spatial information offered by microscopy, this technique can selectively analyze the chemical composition of different features of unlabeled, unstained tissue sections. In the past, the tissue features that have received the most interest were parenchymal and epithelial cells, chiefly due to their involvement in dysplasia and progression to carcinoma; however, the field has recently turned its focus toward stroma and areas of fibrotic change. These components of tissue present an untapped source of biochemical information that can shed light on many diverse disease processes, and potentially hold useful predictive markers for these same pathologies. Here we review the recent applications of infrared spectroscopic imaging to stromal and fibrotic regions of diseased tissue, and explore the potential of this technique to advance current capabilities for tissue analysis.

Insights into Biochemical Alteration in Cancer-Associated Fibroblasts by using Novel Correlative Spectroscopy

The microenvironment of a tumor changes chemically and morphologically during cancer progression. Cancer‐stimulated fibroblasts promote tumor growth, however, the mechanism of the transition to a cancer‐stimulated fibroblast remains elusive. Here, the multi‐modal spectroscopic methods Fourier transform infrared imaging (FTIRI), X‐ray absorption spectroscopy (XAS) and X‐ray fluorescence imaging (XFI) are used to characterize molecular and atomic alterations that occur in cancer‐stimulated fibroblasts. In addition to chemical changes in lipids (olefinic and acyl chain) and protein aggregation observed with FTIRI, a new infrared biomarker for oxidative stress in stimulated fibroblasts is reported. Oxidative stress is observed to cause lipid peroxidation, which leads to the appearance of a new band at 1721 cm⁻¹, assigned to 4‐hydroxynonenal. Complementary to FTIRI, XFI is well suited to determining atom concentrations and XAS can reveal the speciation of individual elements. XFI reveals increased concentrations of P, S, K, Ca within stimulated fibroblasts. Furthermore, XAS studies reveal alterations in the speciation of S and Ca in stimulated fibroblasts, which might provide insight into the mechanisms of cancer progression. Using XFI, not only is the concentration change of individual elements observed, but also the subcellular localization. This study demonstrates the wealth of biochemical information provided by a multi‐modal imaging approach and highlights new avenues for future research into the microenvironment of breast tumors.

qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

Attenuated total reflection Fourier-transform infrared (ATR-FTIR) imaging of tissues and live cells

FTIR spectroscopic imaging is a label-free, non-destructive and chemically specific technique that can be utilised to study a wide range of biomedical applications such as imaging of biopsy tissues, fixed cells and live cells, including cancer cells. In particular, the use of FTIR imaging in attenuated total reflection (ATR) mode has attracted much attention because of the small, but well controlled, depth of penetration and corresponding path length of infrared light into the sample. This has enabled the study of samples containing large amounts of water, as well as achieving an increased spatial resolution provided by the high refractive index of the micro-ATR element. This review is focused on discussing the recent developments in FTIR spectroscopic imaging, particularly in ATR sampling mode, and its applications in the biomedical science field as well as discussing the future opportunities possible as the imaging technology continues to advance.

Fundamental developments in infrared spectroscopic imaging for biomedical applications

Infrared chemical imaging is a rapidly emerging field with new advances in instrumentation, data acquisition and data analysis. These developments have had significant impact in biomedical applications and numerous studies have now shown that this technology offers great promise for the improved diagnosis of the diseased state. Relying on purely biochemical signatures rather than contrast from exogenous dyes and stains, infrared chemical imaging has the potential to revolutionise histopathology for improved disease diagnosis. In this review we discuss the recent advances in infrared spectroscopic imaging specifically related to spectral histopathology (SHP) and consider the current state of the field. Finally we consider the practical application of SHP for disease diagnosis and consider potential barriers to clinical translation highlighting current directions and the future outlook.

Distinguishing nuclei-specific benzo[a]pyrene-induced effects from whole-cell alterations in MCF-7 cells using Fourier-transform infrared spectroscopy

Exposure to chemicals such as benzo[a]pyrene (B[a]P) can generate intracellular toxic mechanisms. Fourier-transform infrared (FTIR) spectroscopy is a novel approach that allows the non-destructive analysis of underlying chemical bond alterations in patho-physiological processes. This study set out to examine whether B[a]P-induced whole cell alterations could be distinguished from effects on nuclei of exposed cells. Using attenuated total reflection FTIR (ATR-FTIR) spectroscopy, alterations in nuclei isolated from B[a]P-treated MCF-7 cells concentrated either in G0/G1- or S-phase were observed. B[a]P-induced effects in whole-cells included alterations to lipids, DNA and protein spectral regions. Absorbance areas for protein and DNA/RNA regions in B[a]P-treated whole cells differed significantly (P<0.0001) from vehicle controls and these observations correlated with alterations noted in isolated nuclei. Our findings provide evidence that FTIR spectroscopy has the ability to identify specific chemical-induced alterations.

Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP)

We report results of a study utilizing a novel tissue classification method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples on a tissue microarray. The spectral diagnostic method allows reproducible and objective classification of unstained tissue sections. This is accomplished by acquiring infrared data sets containing thousands of spectra, each collected from tissue pixels ∼6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology is presented, suggesting that spectral histopathology can achieve levels of diagnostic accuracy that is comparable to that of multipanel immunohistochemistry.

Direct determination of phosphatase activity from physiological substrates in cells

A direct and continuous approach to determine simultaneously protein and phosphate concentrations in cells and kinetics of phosphate release from physiological substrates by cells without any labeling has been developed. Among the enzymes having a phosphatase activity, tissue non-specific alkaline phosphatase (TNAP) performs indispensable, multiple functions in humans. It is expressed in numerous tissues with high levels detected in bones, liver and neurons. It is absolutely required for bone mineralization and also necessary for neurotransmitter synthesis. We provided the proof of concept that infrared spectroscopy is a reliable assay to determine a phosphatase activity in the osteoblasts. For the first time, an overall specific phosphatase activity in cells was determined in a single step by measuring simultaneously protein and substrate concentrations. We found specific activities in osteoblast like cells amounting to 116 ± 13 nmol min(-1) mg(-1) for PPi, to 56 ± 11 nmol min(-1) mg(-1) for AMP, to 79 ± 23 nmol min(-1) mg(-1) for beta-glycerophosphate and to 73 ± 15 nmol min(-1) mg(-1) for 1-alpha-D glucose phosphate. The assay was also effective to monitor phosphatase activity in primary osteoblasts and in matrix vesicles. The use of levamisole--a TNAP inhibitor--served to demonstrate that a part of the phosphatase activity originated from this enzyme. An IC50 value of 1.16 ± 0.03 mM was obtained for the inhibition of phosphatase activity of levamisole in osteoblast like cells. The infrared assay could be extended to determine any type of phosphatase activity in other cells. It may serve as a metabolomic tool to monitor an overall phosphatase activity including acid phosphatases or other related enzymes.

Improving prediction of prostate cancer recurrence using chemical imaging

Precise Outcome prediction is crucial to providing optimal cancer care across the spectrum of solid cancers. Clinically-useful tools to predict risk of adverse events (metastases, recurrence), however, remain deficient. Here, we report an approach to predict the risk of prostate cancer recurrence, at the time of initial diagnosis, using a combination of emerging chemical imaging, a diagnostic protocol that focuses simultaneously on the tumor and its microenvironment, and data analysis of frequent patterns in molecular expression. Fourier transform infrared (FT-IR) spectroscopic imaging was employed to record the structure and molecular content from tumors prostatectomy. We analyzed data from a patient cohort that is mid-grade dominant – which is the largest cohort of patients in the modern era and in whom prognostic methods are largely ineffective. Our approach outperforms the two widely used tools, Kattan nomogram and CAPRA-S score in a head-to-head comparison for predicting risk of recurrence. Importantly, the approach provides a histologic basis to the prediction that identifies chemical and morphologic features in the tumor microenvironment that is independent of conventional clinical information, opening the door to similar advances in other solid tumors.

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging of human tissue sections towards improving pathology

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.

Statistical analysis of a lung cancer spectral histopathology (SHP) data set

We report results on a statistical analysis of an infrared spectral dataset comprising a total of 388 lung biopsies from 374 patients.

A FTIR imaging characterization of fibroblasts stimulated by various breast cancer cell lines

It is well known that the microenvironment plays a major role in breast cancer progression. Yet, the mechanism explaining the transition from normal fibroblasts to cancer-stimulated fibroblasts remains to be elucidated. Here we report a FTIR imaging study of the effects of three different breast cancer cell lines on normal fibroblasts in culture. Fibroblast activation process was monitored by FTIR imaging and spectra compared by multivariate statistical analyses. Principal component analysis evidenced that the fibroblasts stimulated by these cancer cell lines grouped together and remained distinctly separated from normal fibroblasts indicating a modified different chemical composition in the cancer-stimulated fibroblasts. Similar changes in fibroblasts were induced by the various breast cancer cell lines belonging to different sub-types. Most significant changes were observed in the region of 2950 and 1230 cm⁻¹, possibly related to changes in lipids and in the 1230 cm⁻¹ area assigned to phosphate vibrations (nucleotides). Interestingly, the cancer-cell induced changes in the fibroblasts also occurred when there was no possible direct contact between the two cell lines in the co-culture. When contact was possible, the spectral changes were similar, suggesting that soluble factors but not direct cell-cell interactions were responsible for fibroblast activation. Overall, the results indicate that IR imaging could be used in the future for analyzing the microenvironment of breast tumors.

Using Fourier transform IR spectroscopy to analyze biological materials

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

A new paradigm for mechanobiological mechanisms in tumor metastasis

Tumor metastases and epithelial to mesenchymal transition (EMT) involve tumor cell invasion and migration through the dense collagen-rich extracellular matrix surrounding the tumor. Little is neither known about the mechanobiological mechanisms involved in this process, nor the role of the mechanical forces generated by the cells in their effort to invade and migrate through the stroma. In this paper we propose a new fundamental mechanobiological mechanism involved in cancer growth and metastasis, which can be both protective or destructive depending on the magnitude of the forces generated by the cells. This new mechanobiological mechanism directly challenges current paradigms that are focused mainly on biological and biochemical mechanisms associated with tumor metastasis. Our new mechanobiological mechanism describes how tumor expansion generates mechanical forces within the stroma to not only resist tumor expansion but also inhibit or enhance tumor invasion by, respectively, inhibiting or enhancing matrix metalloproteinase (MMP) degradation of the tensed interstitial collagen. While this mechanobiological mechanism has not been previously applied to the study of tumor metastasis and EMT, it may have the potential to broaden our understanding of the tumor invasive process and assist in developing new strategies for preventing or treating cancer metastasis.

Quantifying collagen structure in breast biopsies using second-harmonic generation imaging

Quantitative second-harmonic generation imaging is employed to assess stromal collagen in normal, hyperplastic, dysplastic, and malignant breast tissues. The cellular scale organization is quantified using Fourier transform-second harmonic generation imaging (FT-SHG), while the molecular scale organization is quantified using polarization-resolved second-harmonic generation measurements (P-SHG). In the case of FT-SHG, we apply a parameter that quantifies the regularity in collagen fiber orientation and find that malignant tissue contains locally aligned fibers compared to other tissue conditions. Alternatively, using P-SHG we calculate the ratio of tensor elements (d(15)/d(31), d(22)/d(31), and d(33)/d(31)) of the second-order susceptibility χ(2) for collagen fibers in breast biopsies. In particular, d(15)/d(31) shows potential differences across the tissue pathology. We also find that trigonal symmetry (3m) is a more appropriate model to describe collagen fibers in malignant tissues as opposed to the conventionally used hexagonal symmetry (C6). This novel method of targeting collagen fibers using a combination of two quantitative SHG techniques, FT-SHG and P-SHG, holds promise for breast tissue analysis and applications to characterizing cancer in a manner that is compatible with clinical practice.

Attenuated total reflectance Fourier-transform infrared spectroscopic imaging for breast histopathology

Histopathology forms the gold standard for the diagnosis of breast cancer. Fourier Transform Infrared (FT-IR) spectroscopic imaging has been proposed to be a potentially powerful adjunct to current histopathological techniques. Most studies using FT-IR imaging for breast tissue analysis have been in the transmission or transmission-reflection mode, in which the wavelength and optics limit the data to a relatively coarse spatial resolution (typically, coarser than 5 μm × 5 μm per pixel). This resolution is insufficient to examine many histologic structures. Attenuated Total Reflectance (ATR) FT-IR imaging incorporating a Germanium optic can allow for a four-fold increase in spatial resolution due to the material's high refractive index in the mid-IR. Here, we employ ATR FT-IR imaging towards examining cellular and tissue structures that constitute and important component of breast cancer diagnosis. In particular, we resolve and chemically characterize endothelial cells, myoepithelial cells and terminal ductal lobular units. Further extending the ability of IR imaging to examine sub-cellular structures, we report the extraction of intact chromosomes from a breast cancer cells and their spatially localized analysis as a novel approach to understand changes associated with the molecular structure of DNA in breast cancer.

Applications of Infrared and Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics: Present Status and Future Promises

This paper summarizes the progress achieved over the past fifteen years in applying vibrational (Raman and IR) spectroscopy to problems of medical diagnostics and cellular biology. During this time, a number of research groups have verified the enormous information content of vibrational spectra; in fact, genomic, proteomic, and metabolomic information can be deduced by decoding the observed vibrational spectra. This decoding process is aided enormously by the availability of high-power computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared microspectral data has rendered practical the collection of images based solely on spectral data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational biological and biomedical arenas.

Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging

Glandular tumors arising in epithelial cells comprise the majority of solid human cancers. Glands are supported by stroma, which is activated in the proximity of a tumor. Activated stroma is often characterized by the molecular expression of α-smooth muscle actin (α-SMA) within fibroblasts. However, the precise spatial and temporal evolution of chemical changes in fibroblasts upon epithelial tumor signaling is poorly understood. Here we report a label-free method to characterize fibroblast changes by using Fourier transform infrared spectroscopic imaging and comparing spectra with α-SMA expression in primary normal human fibroblasts. We recorded the fibroblast activation process by spectroscopic imaging using increasingly tissue-like conditions: 1), stimulation with the growth factor TGFβ1; 2), coculture with MCF-7 human breast cancerous epithelial cells in Transwell coculture; and 3), coculture with MCF-7 in three-dimensional cell culture. Finally, we compared the spectral signatures of stromal transformation with normal and malignant human breast tissue biopsies. The results indicate that this approach reveals temporally complex spectral changes and thus provides a richer assessment than simple molecular imaging based on α-SMA expression. Some changes are conserved across culture conditions and in human tissue, providing a label-free method to monitor stromal transformations.