Multi-Omics Characterization of E3 Regulatory Patterns in Different Cancer Types.
Zhongyan LiJingting WanShangfu LiYun TangYang-Chi-Dung LinJie NiXiaoxuan CaiJinhan YuHsien-Da HuangTzong-Yi LeePublished in: International journal of molecular sciences (2024)
Ubiquitination, a post-translational modification, refers to the covalent attachment of ubiquitin molecules to substrates. This modification plays a critical role in diverse cellular processes such as protein degradation. The specificity of ubiquitination for substrates is regulated by E3 ubiquitin ligases. Dysregulation of ubiquitination has been associated with numerous diseases, including cancers. In our study, we first investigated the protein expression patterns of E3 ligases across 12 cancer types. Our findings indicated that E3 ligases tend to be up-regulated and exhibit reduced tissue specificity in tumors. Moreover, the correlation of protein expression between E3 ligases and substrates demonstrated significant changes in cancers, suggesting that E3-substrate specificity alters in tumors compared to normal tissues. By integrating transcriptome, proteome, and ubiquitylome data, we further characterized the E3-substrate regulatory patterns in lung squamous cell carcinoma. Our analysis revealed that the upregulation of the SKP2 E3 ligase leads to excessive degradation of BRCA2, potentially promoting tumor cell proliferation and metastasis. Furthermore, the upregulation of E3 ubiquitin-protein ligase TRIM33 was identified as a biomarker associated with a favorable prognosis by inhibiting the cell cycle. This work exemplifies how leveraging multi-omics data to analyze E3 ligases across various cancers can unveil prognosis biomarkers and facilitate the identification of potential drug targets for cancer therapy.
Keyphrases
- cell proliferation
- cell cycle
- single cell
- papillary thyroid
- squamous cell carcinoma
- structural basis
- cancer therapy
- transcription factor
- small molecule
- electronic health record
- gene expression
- amino acid
- signaling pathway
- childhood cancer
- rna seq
- big data
- poor prognosis
- drug delivery
- protein protein
- lymph node metastasis
- pi k akt
- physical activity
- mass spectrometry
- emergency department
- radiation therapy
- weight loss
- single molecule
- drug induced
- machine learning
- locally advanced