Refining the lung cancer mouse model through environmental enrichment

The five-year survival rate of patients with stage IV non-small cell lung cancer is less than 10%. Although lung cancer mouse models have led to groundbreaking findings in recent years, current models do not fully recapitulate the immune response and mutation burden observed in human tumours. Accumulating evidence suggests that housing mice in enriched environments has a variety of benefits. In my proposal, I aim to refine the lung cancer mouse model by housing mice in an enriched environment to improve their well-being and assess if enriched housing inhibits tumour growth, increases the cancer immune response, and inhibits cancer-associated cachexia.

Mice will be habituated to their environments for five weeks prior to intravenous injection with a novel immunogenic cell line KPAR1.3, derived from a tumour grown in a Rag-/-;KrasLSL-G12D;P53fl/fl;R26LSL-APOBEC3Bi mouse model of lung cancer. Anxiety will be assessed using an elevated plus maze. Tumour growth will be measured at three weeks post-injection by microCT, and at four weeks a grip test will be performed to determine cachexia levels. A subset of mice will be treated with checkpoint inhibitors to examine if tumours are more sensitive to immunotherapy in mice housed in enriched environments. In addition, tumours will be analysed by immunohistochemistry and flow cytometry to analyse tumour immune cell infiltrate. A representative muscle in the mouse will be stained to evaluate muscle size to assess if cachexia is reduced with environmental enrichment.

This refined model system is easy to set up and applicable to many different cancers, so should have a broad impact across the cancer biology field. This model system should also reduce the number of mice required as complex breeding schemes will not be necessary.
 

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Fellowship

Status:

Active

Principal investigator

Dr Deborah Caswell

Institution

The Francis Crick Institute

Grant reference number

NC/S001832/1

Award date:

Jan 2019

Grant amount

£125,478