Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy

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.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

“…In another study, Paidi et al demonstrated the evaluation of response to checkpoint blockade immunotherapies in tumors with RS in immunogenic CT26 tumor model. 98 Immunotherapies have transformed the landscape of cancer treatment where blockade of immune checkpoint receptors cytotoxic T-lymphocyte-associated protein 4 (CTLA4) and programmed cell death ligand 1 (PD-L1) have been particularly effective in a broad array of cancer patients. 152 Whereas the impact of immunotherapies at the genomic and proteomic levels are being studied, the metabolic impact of this new class of treatment in tumors remains largely unexplored.…”

“…However, the RS features that determined these classification decisions were not well-defined in neural network-based models, which can limit feature discovery. In examples that will be discussed in greater detail in section Milligan et al and Paidi et al both used RF to classify cancer treatment response for radiation treatment and immunotherapy, respectively. These approaches were highly accurate, giving Milligan et al a 99.8% accuracy rate and Paidi et al a 2% error rate.…”

Absolute Quantification of Serum Exosomes in Patients with an SERS-Lateral Flow Strip Biosensor for Noninvasive Clinical Cancer Diagnosis

“…Thus, SERS enables omics-based molecular profiling of exos with molecular specificity, nondestructivity, water insensitivity, excellent multiplexing capability, antiphotobleaching, and less sample preparation. − In general, the complex SERS spectrum of a mixture could be described as a linear combination of its pure component spectra. , Multivariate spectral unmixing analysis of Raman spectra could identify and quantify the pure components in complex biological samples . In fact, multivariate spectral unmixing analysis has been successfully employed for determining the molecular composition and spatial distribution in various hyperspectral images. − …”

Raman spectroscopy combined with a support vector machine algorithm as a diagnostic technique for primary Sjögren’s syndrome

“…Raman spectroscopy is an optical spectroscopic technique based on the inelastic scattering of light. It can be used to detect biological macromolecules, including proteins, lipids, and DNA, in biological samples and provides abundant molecular information at the microscopic level 6 , 7 . Therefore, Raman spectroscopy is commonly used in biomolecular detection.…”