Aberrant transcriptional and post-transcriptional regulation of SPAG5, a YAP-TAZ-TEAD downstream effector, fuels breast cancer cell proliferation.
Valeria CanuSara DonzelliAndrea SacconiFederica Lo SardoClaudio PulitoNoa BosselAnna Di BenedettoPaola MutiClaudio BottiEytan DomanySilvio BicciatoSabrina StranoYosef YardenGiovanni BlandinoPublished in: Cell death and differentiation (2020)
Sperm-associated antigen 5 (SPAG5) is an important driver of the cell mitotic spindle required for chromosome segregation and progression into anaphase. SPAG5 has been identified as an important proliferation marker and chemotherapy-sensitivity predictor, especially in estrogen receptor-negative breast cancer subtypes. Here, we report that SPAG5 is a direct target of miR-10b-3p, and its aberrantly high expression associates with poor disease-free survival in two large cohorts of breast cancer patients. SPAG5 depletion strongly impaired cancer cell cycle progression, proliferation, and migration. Interestingly, high expression of SPAG5 pairs with a YAP/TAZ-activated signature in breast cancer patients. Reassuringly, the depletion of YAP, TAZ, and TEAD strongly reduced SPAG5 expression and diminished its oncogenic effects. YAP, TAZ coactivators, and TEAD transcription factors are key components of the Hippo signaling pathway involved in tumor initiation, progression, and metastasis. Furthermore, we report that SPAG5 is a direct transcriptional target of TEAD/YAP/TAZ, and pharmacological targeting of YAP and TAZ severely reduces SPAG5 expression. Collectively, our data uncover an oncogenic feedback loop, comprising miR-10b-3p, SPAG5, and YAP/TAZ/TEAD, which fuels the aberrant proliferation of breast cancer.
Keyphrases
- cell cycle
- transcription factor
- poor prognosis
- signaling pathway
- cell proliferation
- estrogen receptor
- free survival
- gene expression
- binding protein
- long non coding rna
- pi k akt
- squamous cell carcinoma
- dna methylation
- young adults
- radiation therapy
- machine learning
- electronic health record
- childhood cancer
- regulatory t cells
- single cell
- big data
- dna binding
- artificial intelligence