Proteomic Profiling of Small Extracellular Vesicles Isolated from the Plasma of Vietnamese Patients with Non-Small Cell Lung Cancer Reveals Some Potential Biomarkers

Background: Considering the poor prognosis of non-small cell lung cancer (NSCLC), the objective of this study was to examine the potential of plasma-derived vesicles as a source of lung cancer-specific proteins. Extracellular vesicle (EV) cargos are specific to the source cells, hence they have the potential of being a source of cancer-specific proteins.  Methods: The proteins differently expressed in cancer were determined and derived from EVs isolated from the plasma of NSCLC patients at the National Lung Hospital. To this end, purification was done using gel filtration chromatography and ultracentrifugation. In addition, nano liquid chromatography mass spectrometry (LC–MS/MS) was used for analyzing. Results: Fifty-seven EV-derived proteins related to NSCLC were highlighted in this research. Some of them have not been addressed before, such as EEF1A1 (elongation factor 1-α1), KPNB1 (Importin subunit beta 1), SRC (proto-oncogene tyrosine-protein kinase) and ACTC1 (actin, alpha cardiac muscle 1). This list was further confirmed through a comparison with ExoCarta and Vesiclepedia. Conclusion: This study is the first work to show the involvement of several novel proteins of small EV (EEF1A1, KPNB1, SRC, and ACTC1) in the progression of NSCLC. The results suggested that they could serve as novel biomarkers for non-small cell lung cancer in the future.     

Quantile regression and empirical likelihood for the analysis of longitudinal data with monotone missing responses due to dropout,with applications to quality of life measurements from clinical trials

The analysis of quality of life (QoL) data can be challenging due to the skewness of responses and the presence of missing data. In this paper, we propose a new weighted quantile regression method for estimating the conditional quantiles of QoL data with responses missing at random. The proposed method makes use of the correlation information within the same subject from an auxiliary mean regression model to enhance the estimation efficiency and takes into account of missing data mechanism. The asymptotic properties of the proposed estimator have been studied and simulations are also conducted to evaluate the performance of the proposed estimator. The proposed method has also been applied to the analysis of the QoL data from a clinical trial on early breast cancer, which motivated this study.     

Genetic and epigenetic alterations of the EGFR and mutually independent association with BRCA1, MGMT,and RASSF1A methylations in Vietnamese lung adenocarcinomas

Genetic and epigenetic alterations importantly contribute to the pathogenesis of lung cancer. In the study, we measured the frequency and distribution of molecular abnormalities of EGFR as well as the aberrant promoter methylations of BRCA1, MGMT, MLH1, and RASSF1A in Vietnamese lung adenocarcinomas. We investigated the association between genetic and epigenetic alteration, and between each abnormality with clinicopathologic parameters. Somatic EGFR mutation that was found in 49/139 (35.3%) lung adenocarcinomas showed a significant association with young age, female gender, and non-smokers. EGFR overexpression was identified in 82 tumors (59.0%) and statistical relationships with EGFR or BRCA1 methylation but not EGFR mutation. In addition, EGFR, BRCA1, MGMT, MLH1, and RASSF1A methylations were found in 33 (23.7%), 41 (29.5%), 46 (33.1%), 28 (20.1%), and 41 (29.5%) cases of a total of 139 lung adenocarcinomas, respectively. The RASSF1A methylation was found to be linked to the smoking habit. Methylations in MGMT and RASSF1A were also found to correlate with metastasis status. Furthermore, the distribution of EGFR mutation and that of BRCA1, MGMT or RASSF1A methylation were significantly exclusive in lung adenocarcinomas. The main finding of our study demonstrate that epigenetic abnormalities might play a critical role for the lung tumorigenesis in patients with smoking history and metastasis, and partly affect the predictive value of EGFR mutations through blocking expression due to promoter EGFR hypermethylation. Mutually exclusive distribution of genetic and epigenetic alterations reflects differently biological characteristics in the etiology of lung adenocarcinomas.