International Journal of General Medicine (Jun 2024)
Unveiling the Impact of MRC1 on Immune Infiltration and Patient’s Prognosis: A Pan-Cancer Analysis Based on Single-Cell and Bulk Sequencing
Abstract
Zhiwei Wu, Changhao Huang Department of Organ Transplantation, XiangYa Hospital of Central South University, Changsha, People’s Republic of ChinaCorrespondence: Changhao Huang, Email [email protected]: Mannose receptor C-type 1 (MRC1) is an endocytic lectin receptor primarily expressed in macrophages, dendritic cells, and some endothelial cells. However, the role of MRC1 in cancers remains unclear.Methods: We analyzed MRC1 expression using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and single-cell datasets. We systematically explored the prognostic implications and diagnostic value of MRC1. Immune-related indicators, including immune cells, immune scores, and immune checkpoint molecules, were used to estimate their correlation with MRC1 expression. Finally, we explored its potential ties to immunotherapy success markers such as tumor mutation burden and DNA repair genes.Results: MRC1 showed both pro- and anti-tumor leanings depending on the cancer types. High levels correlated with poorer outcomes in six cancers but improved prognosis in some cancers like glioblastoma multiforme. This trend extended to the immune arena, where MRC1 intertwined with diverse immune parameters, suggesting its influence on affecting the tumor’s immunological landscape. Intriguingly, its expression positively associated with factors favoring immunotherapy efficacy while negatively correlating with some potential barriers. Single-cell analysis pinpointed a specific link between MRC1 and DNA damage/repair pathways in breast cancer.Conclusion: Our study provides a comprehensive landscape of MRC1 levels and diverse regulatory patterns in different cancers, deepening the understanding of MRC1’s roles in tumorigenesis and immunity.Keywords: MRC1, biomarker, immunotherapy, single-cell, pan-cancer analysis
