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.     

WNT10A variants: following the pattern of inheritance in tooth agenesis and self-reported family history of cancer

Clinical Oral Investigations - The aim of this study was the analysis of WNT10A variants in seven families of probands with various forms of tooth agenesis and self-reported family history of...     

Is low or high body mass index in patients operated for oral squamous cell carcinoma associated with the perioperative complication rate?

The aim of this study was to analyse the effect of body mass index (BMI), both low and high values, on the perioperative complication rate in patients with oral squamous cell carcinoma (OSCC). The medical records of 259 patients operated between 2014 and 2017 for OSCC were reviewed. Univariate and multivariate analyses were performed. Sixty of the 259 patients developed 87 complications. Low or high BMI was not associated with the perioperative complication rate. A longer operating time and increased blood loss were associated with a higher perioperative complication rate and higher Clavien–Dindo grade. Low BMI, American Society of Anesthesiologists score 2 and 3, a longer operating time, and increased blood loss were associated with a longer hospital stay. Low BMI was associated with a longer hospital stay. Neither low nor high BMI was associated with the perioperative complication rate. A longer operating time and increased blood loss were associated with a higher perioperative complication rate and higher Clavien–Dindo grade.