Publications by authors named "Yi-Kun Feng"

Aims: Considering morphological heterogeneity of lung adenocarcinoma (LUAD) and no objective prognostic grading system existing currently, we aim to establish an 'optimised architecture-based grading system' (OAGS) to predict prognosis for resected LUAD.

Methods: A multicentral study involving three independent cohorts of LUAD was conducted. Predictive ability of the OAGS for recurrence-free probability (RFP) and overall survival (OS) was assessed in training cohort (n=228) by the area under the receiver operating characteristic curve (AUC), Harrell's concordance index (-index) and Kaplan-Meier survival analyses, which was validated in testing (n=135) and validation (n=226) cohorts.

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Background: Glioblastoma (GBM) is one of the most deadly primary malignant brain tumors in adults. R132H mutation of isocitrate dehydrogenase 1 (IDH1) predicts a better prognosis of GBM. IDH1-R132H is associated with increased hypoxia-inducible factor-1α (HIF-1α) expression in GBM tumors.

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