Recent advances of transcriptomics and proteomics in triple-negative breast cancer prognosis assessment.
Yuan LiXiangyi KongZhongzhao WangLixue XuanPublished in: Journal of cellular and molecular medicine (2022)
Triple-negative breast cancer (TNBC), a heterogeneous tumour that lacks the expression of oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), is often characterized by aggressiveness and tends to recur or metastasize. TNBC lacks therapeutic targets compared with other subtypes and is not sensitive to endocrine therapy or targeted therapy except chemotherapy. Therefore, identifying the prognostic characteristics and valid therapeutic targets of TNBC could facilitate early personalized treatment. Due to the rapid development of various technologies, researchers are increasingly focusing on integrating 'big data' and biological systems, which is referred to as 'omics', as a means of resolving it. Transcriptomics and proteomics analyses play an essential role in exploring prospective biomarkers and potential therapeutic targets for triple-negative breast cancers, which provides a powerful engine for TNBC's therapeutic discovery when combined with complementary information. Here, we review the recent progress of TNBC research in transcriptomics and proteomics to identify possible therapeutic goals and improve the survival of patients with triple-negative breast cancer. Also, researchers may benefit from this article to catalyse further analysis and investigation to decipher the global picture of TNBC cancer.
Keyphrases
- single cell
- epidermal growth factor receptor
- big data
- mass spectrometry
- artificial intelligence
- tyrosine kinase
- poor prognosis
- endothelial cells
- machine learning
- high throughput
- label free
- advanced non small cell lung cancer
- small molecule
- squamous cell carcinoma
- binding protein
- stem cells
- estrogen receptor
- healthcare
- papillary thyroid
- young adults
- health information
- replacement therapy
- sensitive detection
- deep learning
- risk assessment
- free survival
- loop mediated isothermal amplification