A machine learning approach is applied to Raman spectra of cells from the MIA PaCa-2 human pancreatic cancer cell line to distinguish between tumor repopulating cells (TRCs) and parental control cells, and to aid in the identification of molecular signatures. Fifty-one Raman spectra from the two types of cells are analyzed to determine the best combination of data type, dimension size, and classification technique to differentiate the cell types. An accuracy of 0.98 is obtained from support vector machine (SVM) and k-nearest neighbor (kNN) classifiers with various dimension reduction and feature selection tools. We also identify some possible biomolecules that cause the spectral peaks that led to the best results.

Soft 3D-fibrin-gel selected tumor repopulating cells (TRCs) from the B16F1 melanoma cell line exhibit extraordinary self-renewal and tumor-regeneration capabilities. However, their biomarkers and gene regulatory features remain largely unknown. Here, we utilized the next-generation sequencing-based RNA sequencing (RNA-seq) technique to discover novel biomarkers and active gene regulatory features of TRCs. Systems biology analysis of RNA-seq data identified differentially expressed gene clusters, including the cell adhesion cluster, which subsequently identified highly specific and novel biomarkers, such as Col2a1, Ncam1, F11r, and Negr1. We validated the expression of these genes by real-time qPCR. The expression level of Col2a1 was found to be relatively low in TRCs but twenty-fold higher compared to the parental control cell line, thus making the biomarker very specific for TRCs. We validated the COL2A1 protein by immunofluorescence microscopy, showing a higher expression of COL2A1 in TRCs compared to parental control cells. KEGG pathway analysis showed the JAK/STAT, hypoxia, and Akt signaling pathways to be active in TRCs. Besides, the aerobic glycolysis pathway was found to be very active, indicating a typical Warburg Effect on highly tumorigenic cells. Together, our study revealed highly specific biomarkers and active cell signaling pathways of melanoma TRCs that can potentially target and neutralize TRCs.