ABSTRACT
We used diffuse reflectance spectroscopy to quantify tissue absorption and scattering-based parameters in similarly sized tumors derived from a panel of four isogenic murine breast cancer cell lines (4T1, 4T07, 168FARN, 67NR) that are each capable of accomplishing different steps of the invasion-metastasis cascade. We found lower tissue scattering, increased hemoglobin concentration, and lower vascular oxygenation in indolent 67NR tumors incapable of metastasis compared with aggressive 4T1 tumors capable of metastasis. Supervised learning statistical approaches were able to accurately differentiate between tumor groups and classify tumors according to their ability to accomplish each step of the invasion-metastasis cascade. We investigated whether the inhibition of metastasis-promoting genes in the highly metastatic 4T1 tumors resulted in measurable optical changes that made these tumors similar to the indolent 67NR tumors. These results demonstrate the potential of diffuse reflectance spectroscopy to noninvasively evaluate tumor biology and discriminate between indolent and aggressive tumors.
ABSTRACT
Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack of reliable biomarkers for prediction and evaluation of treatment response. Here, we demonstrate the first application of label-free Raman spectroscopy for elucidating biomolecular changes induced by anti-CTLA4 and anti-PD-L1 immune checkpoint inhibitors (ICI) in the tumor microenvironment (TME) of colorectal tumor xenografts. Multivariate curve resolution-alternating least squares (MCR-ALS) decomposition of Raman spectral datasets revealed early changes in lipid, nucleic acid, and collagen content following therapy. Support vector machine classifiers and random forests analysis provided excellent prediction accuracies for response to both ICIs and delineated spectral markers specific to each therapy, consistent with their differential mechanisms of action. Corroborated by proteomics analysis, our observation of biomolecular changes in the TME should catalyze detailed investigations for translating such markers and label-free Raman spectroscopy for clinical monitoring of immunotherapy response in cancer patients. SIGNIFICANCE: This study provides first-in-class evidence that optical spectroscopy allows sensitive detection of early changes in the biomolecular composition of tumors that predict response to immunotherapy with immune checkpoint inhibitors.