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981.
Lai Q Avolio AW Manzia TM Agnes S Tisone G Berloco PB Rossi M 《The International journal of biological markers》2011,26(3):153-159
Background: Milan criteria (MC) represent the most commonly adopted criteria for the selection of patients with hepatocellular carcinoma (HCC) waiting for liver transplantation (LT). However, MC are exclusively based on morphological aspects. The aim of the present study was to evaluate pre-LT-detectable biological parameters, to compare them with morphological ones in terms of tumor recurrence prediction and patient survival. Methods: A cohort of 153 consecutive adult patients who underwent LT for HCC on cirrhosis from January 1999 to March 2009 was retrospectively analyzed. Results: HCC recurrence was observed in 12 patients (7.8%). At multivariate logistic regression analysis, serum alpha-fetoprotein (AFP) was the unique independent negative risk factor for the development of HCC recurrence (odds ratio 2.0, p=0.03). Adopting a cutoff value of 210 ng/mL, patients who presented serum AFP =210 ng/mL showed a 5-year survival rate of 23.3% versus 76.2% observed in patients with pre-LT serum AFP <210 ng/mL (log-rank test: <0.0001). Conclusions: In our experience, AFP was the strongest predictor of HCC recurrence, stronger than tumor morphology. AFP could ameliorate the selection of LT candidates. Further studies to evaluate the combination of morphological and biological criteria are needed. 相似文献
982.
Kelly Karl Michael D. Paul Elena B. Pasquale Kalina Hristova 《The Journal of biological chemistry》2020,295(52):18494
Ligand bias is the ability of ligands to differentially activate certain receptor signaling responses compared with others. It reflects differences in the responses of a receptor to specific ligands and has implications for the development of highly specific therapeutics. Whereas ligand bias has been studied primarily for G protein–coupled receptors (GPCRs), there are also reports of ligand bias for receptor tyrosine kinases (RTKs). However, the understanding of RTK ligand bias is lagging behind the knowledge of GPCR ligand bias. In this review, we highlight how protocols that were developed to study GPCR signaling can be used to identify and quantify RTK ligand bias. We also introduce an operational model that can provide insights into the biophysical basis of RTK activation and ligand bias. Finally, we discuss possible mechanisms underpinning RTK ligand bias. Thus, this review serves as a primer for researchers interested in investigating ligand bias in RTK signaling. 相似文献
983.