The prognostic impact of EGFR, ErbB2 and MET gene amplification in human gastric carcinomas as measured by quantitative Real-Time PCR

Purpose: Identification of critical genes which play pivotal roles in controlling tumor growth and survival will establish the basis for developing therapeutic targets. In this study, we focused on frequencies of EGFR, ErbB2 and MET gene amplification in gastric cancer patients to develop personalized medicine to improve the treatment. Method: EGFR, ErbB2 and MET gene amplification, and mRNA expression were analyzed by the quantitative Real-Time PCR in paraffin-embedded samples from 115 patients with gastric cancer. Results: EGFR, ErbB2 and MET genes were amplified in 11.3 % (13/115), 6.1 % (7/115) and 19.1 % (22/115) of cancerous specimens, respectively. The correlation coefficient test clearly indicated that gene amplification in these three genes was positively correlated with mRNA transcription (EGFR: R = 0.631, p = 0.009; ErbB2: R = 0.652, p = 0.023; MET: R = 0.715, p < 0.001). EGFR and MET gene amplification was significantly associated with Ki-67 MI (p = 0.022 and p = 0.015). MET amplification was also significantly associated with age of ≥60 years (p = 0.021) and tumor size of ≥5 cm (p = 0.032). MET amplification, but not EGFR and ErbB2, was a significant prognostic factor in poor survival among patients with gastric cancer. Conclusions: EGFR, ErbB2 and MET genes are frequently amplified in gastric carcinoma. EGFR, ErbB2 and MET gene amplification is positively correlated with mRNA transcription. MET gene amplification correlates with a poor prognosis and poor survival in gastric carcinomas. © 2015, Springer-Verlag Berlin Heidelberg

Maximal power output of a stochastic thermodynamic engine

Classical thermodynamics aimed to quantify the efficiency of thermodynamic engines, by bounding the maximal amount of mechanical energy produced, compared to the amount of heat required. While this was accomplished early on, by Carnot and Clausius, the more practical problem to quantify limits of power that can be delivered, remained elusive due to the fact that quasistatic processes require infinitely slow cycling, resulting in a vanishing power output. Recent insights, drawn from stochastic models, appear to bridge the gap between theory and practice in that they lead to physically meaningful expressions for the dissipation cost in operating a thermodynamic engine over a finite time window. Indeed, the problem to optimize power can be expressed as a stochastic control problem. Building on this framework of stochastic thermodynamics we derive bounds on the maximal power that can be drawn by cycling an overdamped ensemble of particles via a time-varying potential while alternating contact with heat baths of different temperature (Tc cold, and Th hot). Specifically, assuming a suitable bound M on the spatial gradient of the controlling potential, we show that the maximal achievable power is bounded by [Formula presented]. Moreover, we show that this bound can be reached to within a factor of [Formula presented] by operating the cyclic thermodynamic process with a quadratic potential