Therapy-Induced Senescence Drives Bone Loss.
Zhangting YaoBhavna MuraliQihao RenXianmin LuoDouglas V FagetTom ColeBiancamaria RicciDinesh ThotalaJoseph MonahanJan M van DeursenDarren BakerRoberta FaccioJulie K SchwarzSheila A StewartPublished in: Cancer research (2020)
Chemotherapy is important for cancer treatment, however, toxicities limit its use. While great strides have been made to ameliorate the acute toxicities induced by chemotherapy, long-term comorbidities including bone loss remain a significant problem. Chemotherapy-driven estrogen loss is postulated to drive bone loss, but significant data suggests the existence of an estrogen-independent mechanism of bone loss. Using clinically relevant mouse models, we showed that senescence and its senescence-associated secretory phenotype (SASP) contribute to chemotherapy-induced bone loss that can be rescued by depleting senescent cells. Chemotherapy-induced SASP could be limited by targeting the p38MAPK-MK2 pathway, which resulted in preservation of bone integrity in chemotherapy-treated mice. These results transform our understanding of chemotherapy-induced bone loss by identifying senescent cells as major drivers of bone loss and the p38MAPK-MK2 axis as a putative therapeutic target that can preserve bone and improve a cancer survivor's quality of life. SIGNIFICANCE: Senescence drives chemotherapy-induced bone loss that is rescued by p38MAPK or MK2 inhibitors. These findings may lead to treatments for therapy-induced bone loss, significantly increasing quality of life for cancer survivors.
Keyphrases
- bone loss
- chemotherapy induced
- dna damage
- endothelial cells
- induced apoptosis
- drug induced
- high glucose
- metabolic syndrome
- cell cycle arrest
- locally advanced
- stem cells
- machine learning
- squamous cell carcinoma
- estrogen receptor
- cell death
- insulin resistance
- electronic health record
- lymph node metastasis
- extracorporeal membrane oxygenation
- bone mineral density
- acute respiratory distress syndrome
- high fat diet induced
- data analysis
- respiratory failure