Tumor Associated Macrophages and Colorectal Cancer: AI-Assisted Predictive Modeling of Macrophage Polarization in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading malignant diseases in the United States, predominantly due to its poor prognosis and high metastasis. Tumor-associated macrophages (TAMs) are amongst the most common cells that play a significant role in cancer survival and progression in the tumor microenvironment. By using single-cell CRC-specific RNAseq datasets and computational approaches developed in-house, I aim to answer two specific scientific questions: (Q1) Do TAMs show distinctive signature in CRC samples in contrast with healthy samples?; and (Q2) Can I relate the pro-inflammatory and anti-inflammatory polarization of TAMs to the prognosis of colorectal cancer? I filter macrophage cells from eight publicly-available single-cell CRC-specific RNAseq datasets, obtained from both human (Homo Sapiens) and mouse (Mus Musculus) samples and refine a computational model, called SMaRT, to identify a distinctive signature for accurately predicting macrophage-polarization states in the specialized context of CRC. The computational analysis suggests: (a) TAMs are consistently more reactive in tumorous cells as compared to the healthy cells and that the separation between their source samples is statistically significant; (b) A TAM-specific composite gene signature can be reliably used to separate samples that are cancerous versus samples that are healthy. Specifically, these findings provide sufficient and statistically significance evidence that TAMs have a distinctively different signature in CRC samples, majorly falling in the spectrum of the immuno-reactive polarization state.