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The effect of the Cyclin-Dependent Kinase 4/6 inhibitor, Abemaciclib, on prostate cancer cell lines, singly and in combination with the Androgen Receptor inhibitor, Enzalutamide.

Idiopathic Pulmonary Fibrosis (IPF) is a devastating fatal lung disease leading to death at a median of 3 years after diagnosis and while new antifibrotic drugs offer hope of slowing disease progression, lung transplant is the only effective cure. Genetic factors contribute significantly to the risk of developing IPF with up to 30% of patients with IPF possessing the most common at-risk-allele MUC5B. In Ireland our preliminary data suggests that and the prevalence of MUC5B reaches a global-maximum of 12.5% and data from the IPF-National-Registry suggests that 17% of cases cluster in families, one of the highest rates of any country in the world.
Familial-pulmonary-fibrosis has a worse prognosis than sporadic-IPF, responds poorly to current treatments and some patients can have serious adverse reactions to immunosuppression after transplantation. Currently, in Ireland there is no referral or diagnostic pathway for patients with familial-pulmonary-fibrosis and there are no data on what type of mutations are prevalent or clinical outcomes.
Mutations in genes related to telomere homeostasis, and more rarely in surfactant production can lead to familial-pulmonary-fibrosis and abnormal surfactant protein processing in lung alveolar cells has been shown to have a key role in the pathogenesis of pulmonary fibrosis. We have employed gene-edited patient-derived induced-pluripotent-stem-cells to generate alveolar cells and successfully model surfactant deficiency in vitro.
We hypothesise that improved molecular and clinical phenotyping of patients with pulmonary fibrosis can provide a precision diagnosis and treatment thereby reducing clinical risk to patients and their families.
We aim to:
1) Genotype and precisely phenotype patients with a family history of IPF employing a national referral network.
2) Continually monitor patients using spirometry and deep learning analysis of follow-up radiology in a prospective observational-cohort-study.
3) Model clinical outcomes for patients by combining a patient-derived induced-pluirpotent-stem-cell model of lung disease with radiological and physiological data.