Exploring the molecular mechanisms of comorbidity between thyroid cancer and breast cancer through multi-omics data

Sci Rep. 2025 Jul 2;15(1):23309. doi: 10.1038/s41598-025-06566-w.

Abstract

Thyroid Cancer (TC) and Breast Cancer (BC) are highly prevalent malignancies in women, and studies have shown that they may be related by molecular mechanisms. However, the molecular regulatory networks and key genes involved in the co-occurrence of the two tumors are still unclear. This study aims to explore potential diagnostic markers and therapeutic targets using bioinformatics. The TC (GSE3467) and BC (GSE61304) datasets were downloaded from the NCBI GEO database, and the data were analyzed for differentially expressed genes (DEGs) using the limma package of the R language. Disease-related gene modules were screened by weighted gene co-expression network analysis (WGCNA), and the hub genes were further screened by computational ranking by semantic similarity. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzed the biological functions of hub genes. Immune infiltration analysis was performed to reveal the association and expression correlation between the hub genes and immune cells and to explore the relationship between the hub genes and genes related to immunity, autophagy, and ferroptosis. In addition, mRNA-miRNA regulatory networks were constructed, and key regulatory miRNAs were screened by network topology analysis. Potential therapeutic drugs were screened using online tools, and drug molecules were docked in parallel. A total of 58 overlapping differential genes associated with TC and BC were identified, 27 common genes were obtained by intersection with 133 common genes identified by WGCNA, and seven hub genes were obtained by screening. We found that hub genes in both diseases are associated with autophagy, and ferroptosis. Six key regulatory miRNAs were screened, and six potential therapeutic agents were identified using Enrichr and PubChem databases. This bioinformatics study elucidated the possible co-occurrence mechanisms of TC and BC, providing new insights into their underlying pathogenesis and exploring new targets for medical intervention.

Keywords: Autophagy; Bioinformatics analysis; Breast cancer; Drug prediction; Ferroptosis; Hub genes; Thyroid cancer.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Breast Neoplasms* / epidemiology
  • Breast Neoplasms* / genetics
  • Comorbidity
  • Computational Biology / methods
  • Databases, Genetic
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • MicroRNAs / genetics
  • Multiomics
  • Protein Interaction Maps
  • Thyroid Neoplasms* / epidemiology
  • Thyroid Neoplasms* / genetics

Substances

  • MicroRNAs
  • Biomarkers, Tumor