Purpose: In this multicenter phase 3 trial, the efficacy and safety of 60 Gy and 50 Gy doses delivered with modern radiotherapy technology for definitive concurrent chemoradiotherapy (CCRT) in patients with inoperable esophageal squamous cell carcinoma (ESCC) were evaluated. Patients and Methods: Patients with pathologically confirmed stage IIA‒IVA ESCC were randomized 1:1 to receive conventional fractionated 60 Gy or 50 Gy to the tumor and regional lymph nodes. Concurrent weekly chemotherapy (docetaxel 25 mg/m2; cisplatin 25 mg/m2) and two cycles of consolidation chemotherapy (docetaxel 70 mg/m2; cisplatin 25 mg/m2 days 1‒3) were administered. Results: A total of 319 patients were analyzed for survival, and the median follow-up was 34.0 months. The 1- and 3-year locoregional progression-free survival (PFS) rates for the 60 Gy group were 75.6% and 49.5% versus 72.1% and 48.4%, respectively, for the 50 Gy group [HR, 1.00; 95% confidence interval (CI), 0.75‒1.35; P = 0.98]. The overall survival rates were 83.7% and 53.1% versus 84.8% and 52.7%, respectively (HR, 0.99; 95% CI, 0.73‒1.35; P = 0.96), whereas the PFS rates were 71.2% and 46.4% versus 65.2% and 46.1%, respectively (HR, 0.97; 95% CI, 0.73‒1.30; P = 0.86). The incidence of grade 3+ radiotherapy pneumonitis was higher in the 60 Gy group (nominal P = 0.03) than in the 50 Gy group. Conclusions: The 60 Gy arm had similar survival endpoints but a higher severe pneumonitis rate compared with the 50 Gy arm. Fifty Gy should be considered as the recommended dose in CCRT for ESCC.

The present study aimed to develop a pathway-based prognosis prediction model for glioblastoma (GBM). Univariate and multivariate Cox regression analysis were used to identify prognosis-related genes and clinical factors using mRNA-seq data of GBM samples from The Cancer Genome Atlas (TCGA) database. The expression matrix of prognosis-related genes was transformed into pathway deregulation score (PDS) based on the Gene Set Enrichment Analysis (GSEA) repository using Pathifier software. With PDS scores as input, L1-penalized estimation-based Cox-proportional hazards (PH) model was used to identify prognostic pathways. Consequently, a prognosis prediction model based on these prognostic pathways was constructed for classifying patients in the TCGA set or each of the three validation sets into two risk groups. The survival difference between these risk groups was then analyzed using Kaplan-Meier survival analysis and log-rank test. In addition, a gene-based prognostic model was constructed using the Cox-PH model. The model of prognostic pathway combined with clinical factors was also evaluated. In total, 148 genes were discovered to be associated with prognosis. The Cox-PH model identified 13 prognostic pathways. Subsequently, a prognostic model based on the 13 pathways was constructed, and was demonstrated to successfully differentiate overall survival in the TCGA set and in three independent sets. However, the gene-based prognosis model was validated in only two of the three independent sets. Furthermore, the pathway+clinic factor-based model exhibited better predictive results compared with the pathway-based model. In conclusion, the present study suggests a promising prognosis prediction model of 13 pathways for GBM, which may be superior to the gene-level information-based prognostic model.

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The present study was performed to quantify tumor neo-vessels, macrophages and fibroblasts in the tumor microenvironment of hepatocellular carcinoma (HCC) and explore the prognostic factors of HCC. The distribution of tumor neo-vessels, macrophages and fibroblasts was quantified by immunohistochemistry and inverted microscopy with the CRi Nuance multispectral imaging system, and the correlation of these parameters with the clinico-pathological characteristics and overall survival of the patients was analyzed. The number of tumor neo-vessels and macrophages, and density of the fibroblasts, as calculated by the thickness of the tumor stroma in the tumor microenvironment, ranged from 51–429 (median, 218), 110–555 (median, 259) and 35.6–555.5 µm (median, 247.0), respectively. Using the median values as a cutoff, the cases were stratified into high- and low-density groups. Survival analysis demonstrated that the high-density groups regarding macrophages (χ2=5.249, P=0.022) and fibroblasts (χ2=18.073, P<0.001) had a significantly shorter disease-free survival (DFS) than the low-density groups. The high-density tumor neo-vessel group had a shorter DFS with a median of 5 months than the low-density group with a median of 7 months; however, there was no statistical significance between these two groups (χ2=1.663, P=0.197). Regarding the above three stromal components combined, all of the cases were classified into low-, middle- and high-density groups. Survival analysis demonstrated that the high-density group of stromal components had a shorter DFS than the other two groups with a median of 3 months (χ2=14.439, P=0.001). Multivariate analysis by Cox regression indicated that cirrhosis, metastasis stage, as well as macrophage and fibroblast density were independent prognostic factors. In conclusion, the key elements in the tumor microenvironment, including tumor neo-vessels, macrophages and fibroblasts, were heterogenic in HCC tissues and have significant roles in HCC invasion and metastasis. Stromal components are associated with the prognosis of patients with HCC; the higher the density of stromal components, the poorer the prognosis of patients with HCC.