Association of IRS1 Gly972Arg and IRS2 Gly1057Asp polymorphisms with gastric cancer in Turkish subjects

The Role of Insulin Receptor Substrate Proteins in Bronchopulmonary Dysplasia and Asthma: New Potential Perspectives

Insulin receptor substrates (IRSs) are proteins that are involved in signaling through the insulin receptor (IR) and insulin-like growth factor (IGFR). They can also interact with other receptors including growth factor receptors. Thus, they represent a critical node for the transduction and regulation of multiple signaling pathways in response to extracellular stimuli. In addition, IRSs play a central role in processes such as inflammation, growth, metabolism, and proliferation. Previous studies have highlighted the role of IRS proteins in lung diseases, in particular asthma. Further, the members of the IRS family are the common proteins of the insulin growth factor signaling cascade involved in lung development and disrupted in bronchopulmonary dysplasia (BPD). However, there is no study focusing on the relationship between IRS proteins and BPD yet. Unfortunately, there is still a significant gap in knowledge in this field. Thus, in this review, we aimed to summarize the current knowledge with the major goal of exploring the possible roles of IRS in BPD and asthma to foster new perspectives for further investigations.

Construction and Validation of a Protein Prognostic Model for Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSCC), as the major type of lung cancer, has high morbidity and mortality rates. The prognostic markers for LUSCC are much fewer than lung adenocarcinoma. Besides, protein biomarkers have advantages of economy, accuracy and stability. The aim of this study was to construct a protein prognostic model for LUSCC. The protein expression data of LUSCC were downloaded from The Cancer Protein Atlas (TCPA) database. Clinical data of LUSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 237 proteins were identified from 325 cases of LUSCC patients based on the TCPA and TCGA database. According to Kaplan-Meier survival analysis, univariate and multivariate Cox analysis, a prognostic prediction model was established which was consisted of 6 proteins (CHK1_pS345, CHK2, IRS1, PAXILLIN, BRCA2 and BRAF_pS445). After calculating the risk values of each patient according to the coefficient of each protein in the risk model, the LUSCC patients were divided into high risk group and low risk group. The survival analysis demonstrated that there was significant difference between these two groups (p= 4.877e-05). The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was 0.699, which suggesting that the prognostic risk model could effectively predict the survival of LUSCC patients. Univariate and multivariate analysis indicated that this prognostic model could be used as independent prognosis factors for LUSCC patients. Proteins co-expression analysis showed that there were 21 proteins co-expressed with the proteins in the risk model. In conclusion, our study constructed a protein prognostic model, which could effectively predict the prognosis of LUSCC patients.