Delay in the assessment of tumor response to radiotherapy continues to pose a major challenge to quality of life for patients with nonresponsive tumors. Here, we exploited label-free Raman spectroscopic mapping to elucidate radiation-induced biomolecular changes in tumors and uncovered latent microenvironmental differences between treatment-resistant and -sensitive tumors. We used isogenic radiation-resistant and -sensitive A549 human lung cancer cells and human head and neck squamous cell carcinoma (HNSCC) cell lines (UM-SCC-47 and UM-SCC-22B, respectively) to grow tumor xenografts in athymic nude mice and demonstrated the molecular specificity and quantitative nature of Raman spectroscopic tissue assessments. Raman spectra obtained from untreated and treated tumors were subjected to chemometric analysis using multivariate curve resolution-alternating least squares (MCR-ALS) and support vector machine (SVM) to quantify biomolecular differences in the tumor microenvironment. The Raman measurements revealed significant and reliable differences in lipid and collagen content postradiation in the tumor microenvironment, with consistently greater changes observed in the radiation-sensitive tumors. In addition to accurately evaluating tumor response to therapy, the combination of Raman spectral markers potentially offers a route to predicting response in untreated tumors prior to commencing treatment. Combined with its noninvasive nature, our findings provide a rationale for in vivo studies using Raman spectroscopy, with the ultimate goal of clinical translation for patient stratification and guiding adaptation of radiotherapy during the course of treatment. Significance: These findings highlight the sensitivity of label-free Raman spectroscopy to changes induced by radiotherapy and indicate the potential to predict radiation resistance prior to commencing therapy.

Recent advances in animal modeling, imaging technology, and functional genomics have permitted precise molecular observations of the metastatic process. However, a comprehensive understanding of the premetastatic niche remains elusive, owing to the limited tools that can map subtle differences in molecular mediators in organ-specific microenvironments. Here, we report the ability to detect premetastatic changes in the lung microenvironment, in response to primary breast tumors, using a combination of metastatic mouse models, Raman spectroscopy, and multivariate analysis of consistent patterns in molecular expression. We used tdTomato fluorescent protein expressing MDA-MB-231 and MCF-7 cells of high and low metastatic potential, respectively, to grow orthotopic xenografts in athymic nude mice and allow spontaneous dissemination from the primary mammary fat pad tumor. Label-free Raman spectroscopic mapping was used to record the molecular content of premetastatic lungs. These measurements show reliable distinctions in vibrational features, characteristic of the collageneous stroma and its cross-linkers as well as proteoglycans, which uniquely identify the metastatic potential of the primary tumor by recapitulating the compositional changes in the lungs. Consistent with histological assessment and gene expression analysis, our study suggests that remodeling of the extracellular matrix components may present promising markers for objective recognition of the premetastatic niche, independent of conventional clinical information. Cancer Res; 77(2); 247–56. ©2016 AACR.