Mutational analysis of the insulin‑like growth factor 1 receptor tyrosine kinase domain in non-small cell lung cancer patients

The insulin‑like growth factor 1 receptor (IGF1R) pathway plays an important role in the pathogenesis of non‑small cell lung cancer (NSCLC) and also provides a mechanism of resistance to targeted therapies. IGF1R is therefore an ideal therapeutic target and several inhibitors have entered clinical trials. However, thus far the response to these inhibitors has been poor, highlighting the importance of predictive biomarkers to identify patient cohorts who will benefit from these targeted agents. It is well‑documented that mutations and/or deletions in the epidermal growth factor receptor (EGFR) tyrosine kinase (TK) domain predict sensitivity of NSCLC patients to EGFR TK inhibitors. Single‑nucleotide polymorphisms (SNPs) in the IGF pathway have been associated with disease, including breast and prostate cancer. The aim of the present study was to elucidate whether the IGF1R TK domain harbours SNPs, somatic mutations or deletions in NSCLC patients and correlates the mutation status to patient clinicopathological data and prognosis. Initially 100 NSCLC patients were screened for mutations/deletions in the IGF1R TK domain (exons 16‑21) by sequencing analysis. Following the identification of SNP rs2229765, a further 98 NSCLC patients and 866 healthy disease‑free control patients were genotyped using an SNP assay. The synonymous SNP (rs2229765) was the only aberrant base change identified in the IGF1R TK domain of 100 NSCLC patients initially analysed. SNP rs2229765 was detected in exon 16 and was found to have no significant association between IGF1R expression and survival. The GA genotype was identified in 53.5 and 49.4% of NSCLC patients and control individuals, respectively. No significant difference was found in the genotype (P=0.5487) or allele (P=0.9082) frequencies between the case and control group. The present findings indicate that in contrast to the EGFR TK domain, the IGF1R TK domain is not frequently mutated in NSCLC patients. The synonymous SNP (rs2229765) had no significant association between IGF1R expression and survival in the cohort of NSCLC patients.

Paper 1: The disruptive forces of the sharing economy

Overview: - The sharing economy unlocks a previously unused value of goods and labour, and causes disruption in established industries. - The pattern of disruption is similar regardless of the industry that's impacted. While the initial phases of disruption are transformational for many (e.g. lost jobs), often the industries end up stronger than before they were before the disruption. - Due to different in setting, upholding and enforcing standards, it is hard to assess the regulatory trade-offs. Safety, labour relations and social fairness are important factors to consider across the industry.