miR-15a/miR-16 down-regulates BMI1, impacting Ub-H2A mediated DNA repair and breast cancer cell sensitivity to doxorubicin.
Nibedita PatelKoteswara Rao GarikapatiRaj K PanditaDharmendra Kumar SinghTej K PanditaUtpal BhadraManika Pal BhadraPublished in: Scientific reports (2017)
The B-lymphoma Moloney murine leukemia virus insertion region-1 protein (BMI1) acts as an oncogene in various cancers, including breast cancer. Recent evidence suggests that BMI1 is rapidly recruited to sites of DNA double strand breaks where it facilitates histone H2A ubiquitination and DNA double strand break repair by homologous recombination. Here we show that miR-15a and miR-16 expression is decreased during the initial period after DNA damage where it would otherwise down-regulate BMI1, impairing DNA repair. Elevated miR-15a and miR-16 levels down-regulated BMI1 and other polycomb group proteins like RING1A, RING1B, EZH2 and also altered the expression of proteins associated with the BMI1 dependent ubiquitination pathway. Antagonizing the expression of miR-15a and miR-16, enhanced BMI1 protein levels and increased DNA repair. Further, overexpression of miR-15a and miR-16 sensitized breast cancer cells to DNA damage induced by the chemotherapeutic drug doxorubicin. Our results suggest that miR-15a and miR-16 mediate the down-regulation of BMI1, which impedes DNA repair while elevated levels can sensitize breast cancer cells to doxorubicin leading to apoptotic cell death. This data identifies a new target for manipulating DNA damage response that could impact the development of improved therapeutics for breast cancer.
Keyphrases
- dna repair
- dna damage
- cell proliferation
- long non coding rna
- long noncoding rna
- dna damage response
- poor prognosis
- body mass index
- cell death
- oxidative stress
- weight gain
- gene expression
- drug delivery
- machine learning
- emergency department
- transcription factor
- binding protein
- small molecule
- single molecule
- signaling pathway
- diffuse large b cell lymphoma
- electronic health record
- young adults
- deep learning