We employ Raman spectroscopy to diagnose benign and malignant lesions in human breast tissue based on chemical composition. In this study, 130 Raman spectra are acquired from ex vivo samples of human breast tissue (normal, fibrocystic change, fibroadenoma, and infiltrating carcinoma) from 58 patients. Data are fit by using a linear combination model in which nine basis spectra represent the morphologic and chemical features of breast tissue. The resulting fit coefficients provide insight into the chemical͞morpho-logical makeup of the tissue and are used to develop diagnostic algorithms. The fit coefficients for fat and collagen are the key parameters in the resulting diagnostic algorithm, which classifies samples according to their specific pathological diagnoses, attaining 94% sensitivity and 96% specificity for distinguishing cancerous tissues from normal and benign tissues. The excellent results demonstrate that Raman spectroscopy has the potential to be applied in vivo to accurately classify breast lesions, thereby reducing the number of excisional breast biopsies that are performed.spectral diagnosis ͉ optical vibrational disease

Ultrasensitive Raman measurements in single living cells are possible through exploiting the effect of surface-enhanced Raman scattering (SERS). Colloidal gold particles (60 nm in size) that are deposited inside cells as “SERS-active nanostructures” result in strongly enhanced Raman signals of the native chemical constituents of the cells. Particularly strong field enhancement can be observed when gold colloidal particles form colloidal clusters. The strongly enhanced Raman signals allow Raman measurements of a single cell in the 400–1800 cm−1 range with 1-μm lateral resolution in relatively short collection times (1 second for one mapping point) using 3–5 mW near-infrared excitation. SERS mapping over a cell monolayer with 1-μm lateral resolution shows different Raman spectra at almost all places, reflecting the very inhomogeneous chemical constitution of the cells. Colloidal gold supported Raman spectroscopy in living cells provides a tool for sensitive and structurally selective detection of native chemicals inside a cell, such as DNA and phenylalanine, and for monitoring their intracellular distributions. This might open up exciting opportunities for cell biology and biomedical studies.

We present the first demonstration of in vivo collection of Raman spectra of breast tissue. Raman spectroscopy, which analyzes molecular vibrations, is a promising new technique for the diagnosis of breast cancer. We have collected 31 Raman spectra from nine patients undergoing partial mastectomy procedures to show the feasibility of in vivo Raman spectroscopy for intraoperative margin assessment. The data was fit with an established model, resulting in spectral-based tissue characterization in only 1 second. Application of our previously developed diagnostic algorithm resulted in perfect sensitivity and specificity for distinguishing cancerous from normal and benign tissues in our small data set. Significantly, we have detected a grossly invisible cancer that, upon pathologic review, required the patient to undergo a second surgical procedure. Had Raman spectroscopy been used in a real-time fashion to guide tissue excision during the procedure, the additional reexcision surgery might have been avoided. These preliminary findings suggest that Raman spectroscopy has the potential to lessen the need for reexcision surgeries resulting from positive margins and thereby reduce the recurrence rate of breast cancer following partial mastectomy surgeries. (Cancer Res 2006; 66(6): 3317-22)

Raman spectroscopy has the potential to provide real-time, in situ diagnosis of breast cancer during needle biopsy or surgery via an optical fiber probe. Understanding the chemical/morphological basis of the Raman spectrum of breast tissue is a necessary step in developing Raman spectroscopy as a tool for in situ breast cancer diagnosis. To understand the relationship between the Raman spectrum of a sample of breast tissue and its disease state, near-infrared Raman spectroscopic images of human breast tissue were acquired using a confocal microscope. These images were then compared with phase contrast and hematoxylinand eosin-stained images to develop a chemical/morphological model of breast tissue Raman spectra. This model fits macroscopic tissue spectra with a linear combination of basis spectra derived from spectra of the cell cytoplasm, cell nucleus, fat, b-carotene, collagen, calcium hydroxyapatite, calcium oxalate dihydrate, cholesterol-like lipid deposits and water. Each basis spectrum represents data acquired from multiple patients and, when appropriate, from a variety of normal and diseased states. The model explains the spectral features of a range of normal and diseased breast tissue samples, including breast cancer. It can be used to relate the Raman spectrum of a breast tissue sample to diagnostic parameters used by pathologists.

SUMMARY During obesity, adipose tissue macrophages (ATMs) adopt a ‘metabolically-activated’ (MMe) phenotype. However, the functions of MMe macrophages are poorly understood. Here we combine proteomic and functional methods to demonstrate that in addition to potentiating inflammation, MMe macrophages also promote dead adipocyte clearance through lysosomal exocytosis. We identify NADPH-oxidase-2 (NOX2) as a driver of the inflammatory and adipocyte-clearing properties of MMe macrophages, and show that compared to wild-type, Nox2−/− mice exhibit a time-dependent metabolic phenotype during diet-induced obesity. After 8-weeks of high-fat feeding, Nox2−/− mice exhibit attenuated ATM inflammation and mildly improved glucose tolerance. After 16-weeks of high-fat feeding, Nox2−/− mice develop severe insulin resistance, hepatosteatosis, and visceral lipoatrophy characterized by dead adipocyte accumulation and defective ATM lysosomal exocytosis, a phenotype reproduced in myeloid cell-specific Nox2−/− mice. Collectively, our findings suggest that MMe macrophages perform detrimental and beneficial functions, whose contribution to metabolic phenotypes during obesity is determined by disease progression.

Using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy, we have developed an algorithm that successfully classifies normal breast tissue, fibrocystic change, fibroadenoma, and infiltrating ductal carcinoma in terms of physically meaningful parameters. We acquire 202 spectra from 104 sites in freshly excised breast biopsies from 17 patients within 30 min of surgical excision. The broadband diffuse reflectance and fluorescence spectra are collected via a portable clinical spectrometer and specially designed optical fiber probe. The diffuse reflectance spectra are fit using modified diffusion theory to extract absorption and scattering tissue parameters. Intrinsic fluorescence spectra are extracted from the combined fluorescence and diffuse reflectance spectra and analyzed using multivariate curve resolution. Spectroscopy results are compared to pathology diagnoses, and diagnostic algorithms are developed based on parameters obtained via logistic regression with cross-validation. The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy (total efficiency) of the algorithm are 100, 96, 69, 100, and 91%, respectively. All invasive breast cancer specimens are correctly diagnosed. The combination of diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy yields promising results for discrimination of breast cancer from benign breast lesions and warrants a prospective clinical study.

We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.

Lipid accumulation within the lumen of endolysosomal vesicles is observed in various pathologies including atherosclerosis, liver disease, neurological disorders, lysosomal storage disorders, and cancer. Current methods cannot measure lipid flux specifically within the lysosomal lumen of live cells. We developed an optical reporter, composed of a photoluminescent carbon nanotube of a single chirality, that responds to lipid accumulation via modulation of the nanotube’s optical band gap. The engineered nanomaterial, composed of short, single-stranded DNA and a single nanotube chirality, localizes exclusively to the lumen of endolysosomal organelles without adversely affecting cell viability or proliferation or organelle morphology, integrity, or function. The emission wavelength of the reporter can be spatially resolved from within the endolysosomal lumen to generate quantitative maps of lipid content in live cells. Endolysosomal lipid accumulation in cell lines, an example of drug-induced phospholipidosis, was observed for multiple drugs in macrophages, and measurements of patient-derived Niemann–Pick type C fibroblasts identified lipid accumulation and phenotypic reversal of this lysosomal storage disease. Single-cell measurements using the reporter discerned subcellular differences in equilibrium lipid content, illuminating significant intracellular heterogeneity among endolysosomal organelles of differentiating bone-marrow-derived monocytes. Single-cell kinetics of lipoprotein-derived cholesterol accumulation within macrophages revealed rates that differed among cells by an order of magnitude. This carbon nanotube optical reporter of endolysosomal lipid content in live cells confers additional capabilities for drug development processes and the investigation of lipid-linked diseases.