CRISPR-Cas9-mediated gene knockout in primary human airway epithelial cells reveals a proinflammatory role for MUC18.

Targeted knockout of genes in primary human cells using CRISPR-Cas9-mediated genome-editing represents a powerful approach to study gene function and to discern molecular mechanisms underlying complex human diseases. We used lentiviral delivery of CRISPR-Cas9 machinery and conditional reprogramming culture methods to knockout the MUC18 gene in human primary nasal airway epithelial cells (AECs). Massively parallel sequencing technology was used to confirm that the genome of essentially all cells in the edited AEC populations contained coding region insertions and deletions (indels). Correspondingly, we found mRNA expression of MUC18 was greatly reduced and protein expression was absent. Characterization of MUC18 knockout cell populations stimulated with TLR2, 3 and 4 agonists revealed that IL-8 (a proinflammatory chemokine) responses of AECs were greatly reduced in the absence of functional MUC18 protein. Our results show the feasibility of CRISPR-Cas9-mediated gene knockouts in AEC culture (both submerged and polarized), and suggest a proinflammatory role for MUC18 in airway epithelial response to bacterial and viral stimuli.

Genomic profiling of thousands of candidate polymorphisms predicts risk of relapse in 778 Danish and German childhood acute lymphoblastic leukemia patients.

Childhood acute lymphoblastic leukemia survival approaches 90%. New strategies are needed to identify the 10-15% who evade cure. We applied targeted, sequencing-based genotyping of 25 000 to 34 000 preselected potentially clinically relevant single-nucleotide polymorphisms (SNPs) to identify host genome profiles associated with relapse risk in 352 patients from the Nordic ALL92/2000 protocols and 426 patients from the German Berlin-Frankfurt-Munster (BFM) ALL2000 protocol. Patients were enrolled between 1992 and 2008 (median follow-up: 7.6 years). Eleven cross-validated SNPs were significantly associated with risk of relapse across protocols. SNP and biologic pathway level analyses associated relapse risk with leukemia aggressiveness, glucocorticosteroid pharmacology/response and drug transport/metabolism pathways. Classification and regression tree analysis identified three distinct risk groups defined by end of induction residual leukemia, white blood cell count and variants in myeloperoxidase (MPO), estrogen receptor 1 (ESR1), lamin B1 (LMNB1) and matrix metalloproteinase-7 (MMP7) genes, ATP-binding cassette transporters and glucocorticosteroid transcription regulation pathways. Relapse rates ranged from 4% (95% confidence interval (CI): 1.6-6.3%) for the best group (72% of patients) to 76% (95% CI: 41-90%) for the worst group (5% of patients, P<0.001). Validation of these findings and similar approaches to identify SNPs associated with toxicities may allow future individualized relapse and toxicity risk-based treatments adaptation.