Investigating tumor-associated macrophages and their polarization in colorectal cancer using Boolean implication networks.

Abstract

Tumor-associated Macrophages (or TAMs) are amongst the most common cells that play a significant role in the initiation and progression of colorectal cancer (CRC). [Ghosh et al., 2023] have built a Boolean-logic dependent model to propose a set of gene signatures capable of identifying macrophage polarization states. The signature, called the Signature of Macrophage Reactivity and Tolerance (SMaRT), comprises of 338 human genes (equivalently, 298 mouse genes). The SMaRT signature was constructed using datasets that were not specialized towards any particular disease. To specifically investigate macrophage polarization in CRC, in this paper, we (a) perform a comprehensive analysis of the SMaRT signature on single-cell human and mouse colorectal cancer RNA-seq datasets and (b) adopt transfer learning to construct a "refined" SMaRT signature that specifically characterizes TAM polarization in the CRC tumor microenvironment. Towards validation of our refined gene signature, we use: (a) 5 RNA-seq datasets derived from single-cell human datasets; and (b) 5 large-cohort microarray datasets from humans. Furthermore, we propose the translational potential of our refined gene signature while investigating microsatellite stability and CpG island methylator phenotype (CIMP) in colorectal cancer. Overall, our refined gene signature and its extensive validation provide a path for its adoption in clinical practice in diagnosing colorectal cancer and associated attributes.

Availability and implementation: The data, codes, and software packages used in our research are linked and shared publicly at https://github.com/tirtharajdash/TAMs-CRC .