Multi-omics analysis-based macrophage differentiation-associated papillary thyroid cancer patient classifier

• Published in: Translational oncology Vol. 43; p. 101889
• Main Authors: Sun, Hanlin, Chang, Zhengyan, Li, Hongqiang, Tang, Yifeng, Liu, Yihao, Qiao, Lixue, Feng, Guicheng, Huang, Runzhi, Han, Dongyan, Yin, De-tao
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.05.2024; Neoplasia Press; Elsevier
• Subjects: Macrophage differentiation; Multi-omics; Original Research; Papillary thyroid carcinoma; Single-cell RNA sequencing; Tumor immune microenvironment; Tumor immune microenvironment; Macrophage differentiation; Single-cell RNA sequencing; Multi-omics; Papillary thyroid carcinoma
• ISSN: 1936-5233; 1936-5233
• DOI: 10.1016/j.tranon.2024.101889

•The first PTC patient classifier defined by tumor macrophage differentiation.•Integrated sequencing data identifies key gene sets.•Macrophage states in PTC link to immune/metabolic shifts.•Poor prognosis PTC patient group shows M2 macrophage traits. The reclassification of Papillary Thyroid Carcinoma (PTC) is an area of research that warrants attention. The connection between thyroid cancer, inflammation, and immune responses necessitates considering the mechanisms of differential prognosis of thyroid tumors from an immunological perspective. Given the high adaptability of macrophages to environmental stimuli, focusing on the differentiation characteristics of macrophages might offer a novel approach to address the issues related to PTC subtyping. Single-cell RNA sequencing data of medullary cells infiltrated by papillary thyroid carcinoma obtained from public databases was subjected to dimensionality reduction clustering analysis. The RunUMAP and FindAllMarkers functions were utilized to identify the gene expression matrix of different clusters. Cell differentiation trajectory analysis was conducted using the Monocle R package. A complex regulatory network for the classification of Immune status and Macrophage differentiation-associated Papillary Thyroid Cancer Classification (IMPTCC) was constructed through quantitative multi-omics analysis. Immunohistochemistry (IHC) staining was utilized for pathological histology validation. Through the integration of single-cell RNA and bulk sequencing data combined with multi-omics analysis, we identified crucial transcription factors, immune cells/immune functions, and signaling pathways. Based on this, regulatory networks for three IMPTCC clusters were established. Based on the co-expression network analysis results, we identified three subtypes of IMPTCC: Immune-Suppressive Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (ISMPTCC), Immune-Neutral Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (INMPTCC), and Immune-Activated Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (IAMPTCC). Each subtype exhibits distinct metabolic, immune, and regulatory characteristics corresponding to different states of macrophage differentiation.