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Detecting genetic mutations in circulating cell-free DNA (cfDNA) is a promising approach of liquid biopsy. Between June 2014 and May 2015, 168 plasma samples were collected monthly from 20 patients with metastatic lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutation receiving gefitinib therapy. Clinically relevant EGFR mutations, including exon 19 deletion, L858R and T790M, were quantified using droplet digital polymerase chain reaction. In baseline samples, 19 (95.0%) patients had the same mutation with the matched tumors, and pretreatment T790M mutations were also detected in 3 (15.0%) patients. The dynamics of EGFR mutations were generally associated with treatment response for patients with or without measurable disease. For patients with immeasurable tumor deposits, monitoring disease evolution using cfDNA-based mutation quantification appeared to be more reliable compared with measuring the diameters of target tumor lesions. In addition, molecular progressive disease, defined as a =20% increase of EGFR mutation concentration compared with the lowest concentration recorded during treatment, was tracked up to 8 months prior to objective progression. In survival analysis, sex (P=0.005), pretreatment T790M mutation status (P=0.006), T790M mutation status at the disease progression (P=0.043) and growth rate of EGFR mutations (P=0.023), had a significant impact on median progression-free survival. In conclusion, dynamic monitoring of EGFR mutations in cfDNA is feasible and appears to be useful in early prediction of drug resistance for patients with lung cancer receiving EGFR tyrosine kinase inhibitors. [ABSTRACT FROM AUTHOR]

Polycomb group (PcG) proteins form at least two key complexes, namely polycomb repressive complex 1 and polycomb repressive complex 2. These complexes are involved in the progression of various cancers. Systematic research has not been conducted on the aberrant expression of PcG members in gliomas. Using the Chinese Glioma Genome Atlas data set, PcG expression patterns between normal brain tissues and glioma samples were analyzed, and a PcG-based classifier was then developed using BRB Cox regression and risk-score model. These results were validated in an independent GSE16011 set. A total of six PcGs [chromobox protein homolog (CBX) 6, CBX7, PHD finger protein 1, enhancer of zeste homolog 2 (EZH2), DNA (cytosine-5-)-methyltransferase 3ß (DNMT3B) and polyhomeotic-like protein 2] were identified to be associated with glioma grade. Survival analysis then revealed a five-PcG gene signature one protective gene (enhancer of zeste homolog 1) and four risky genes (EZH2, PHD finger protein 19, DNMT3A and DNMT3B), which may identify patients with high risk of poor prognosis of glioma. Multivariate Cox analysis indicated that the five-PcG signature was an independent prognostic biomarker. These findings indicated that a novel prognostic classifier, five-PcG signature, served as an independent prognostic marker for patients with glioma. [ABSTRACT FROM AUTHOR]