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Purpose: To investigate the prognostic value of serum transferrin (TRF) level before intensity-modulated radiation therapy (IMRT) on radio-sensitivity and overall survival (OS) in patients with nasopharyngeal carcinoma (NPC). Methods: From October 2012 to October 2016, a total of 348 patients with NPC in the First Affiliated Hospital of Fujian Medical University were retrospectively analyzed in our study. The concentration of serum TRF was detected by the method of enzyme-linked immunosorbent assay (ELISA). In the whole group, 46 patients received IMRT, and 302 patients received IMRT plus chemotherapy. The radio-sensitive tumor was defined when the local tumor lesions disappeared completely in the nasopharyngeal MRI scan and no tumor residues were found under the electronic nasopharyngoscope one month after the end of radiotherapy. Results: The serum TRF level before IMRT was (1.34–3.89) g/L, with a median of 2.16 g/L and a mean of (2.20 ± 0.42) g/L. In the whole group, 242 cases (69.5%) were radiosensitive, and 106 cases (30.5%) were insensitive. The number of radiosensitive patients in the group of HTRF (transferrin > 2.16 g/L) and LTRF (transferrin ≤ 2.16 g/L) before radiotherapy was 129 (74.6%) and 113 (64.6%), respectively. The difference in radio-sensitivity between the two groups was statistically significant (χ2 = 4.103, p = 0.043). Logistic regression analysis showed that the level of TRF before radiotherapy (OR = 1.702; 95% CI 1.044~2.775; p = 0.033) was an independent factor for radio-sensitivity. The log-rank test showed that patients in the LTRF group achieved a significantly worse OS (χ2 = 5.388, p = 0.02) than those in the HTRF group. Cox regression analysis showed that baseline TRF level (HR = 1.706; 95% CI 1.065~2.731; p = 0.026) was an independent prognostic factor for overall survival. Conclusions: The low level of TRF before IMRT is a risk factor for radio-sensitivity and a prognostic factor for poor OS in NPC patients. It may be a promising marker to predict radio-sensitivity and OS in NPC patients who accept IMRT. [ABSTRACT FROM AUTHOR]

Background: To investigate nutritional impairment during intensity‐modulated radiotherapy (IMRT) in patients with nasopharyngeal carcinoma (NPC) taking normal nutrition before IMRT and its effect on treatment‐related toxicities (TRTs) and survival. Methods: Modified nutrition index (m‐NI) of 187 patients with NPC, comprised eight indicators (body mass index, circumference of upper arm muscles, total lymphocyte count, red blood cell count, levels of albumin, pre‐albumin, transferrin, and hemoglobin), were evaluated before/after IMRT. Patient characteristics, m‐NI, and the follow‐up data for survival and TRTs were analyzed. Results: The m‐NI scores of patients with NPC decreased significantly after IMRT. Severe nutritional impairment (SNI; decrease in m‐NI score ≥50%) was an independent prognostic factor for overall survival (OS) and an independent risk factor for grade ≥2 oral mucositis. Classification T4 disease and smoking were SNI risk factors. Conclusions: SNI during IMRT is a risk factor for oral mucositis and a prognostic factor for worse OS in patients with NPC. [ABSTRACT FROM AUTHOR]

Objective: As a prevalent and infiltrative cancer type of the central nervous system, the prognosis of lower-grade glioma (LGG) in adults is highly heterogeneous. Recent evidence has demonstrated the prognostic value of the mRNA expression-based stemness index (mRNAsi) in LGG. Our aim was to develop a stemness index-based signature (SI-signature) for risk stratification and survival prediction. Methods: Differentially expressed genes (DEGs) between LGG in the Cancer Genome Atlas (TCGA) and normal brain tissue samples from the Genotype-Tissue Expression (GTEx) project were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the mRNAsi-related gene sets. Meanwhile, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the functional annotation of the key genes. ESTIMATE was used to calculate tumor purity for acquiring the correct mRNAsi. Differences in overall survival (OS) between the high and low mRNAsi (corrected mRNAsi) groups were compared using the Kaplan Meier analysis. By combining the Lasso regression with univariate and multivariate Cox regression, the SI-signature was constructed and validated using the Chinese Glioma Genome Atlas (CGGA). Results: There was a significant difference in OS between the high and low mRNAsi groups, which was also observed in the two corrected mRNAsi groups. Based on threshold limits, 86 DEGs were most significantly associated with mRNAsi via WGCNA. Seven genes (ADAP2 , ALOX5AP , APOBEC3C , FCGRT , GNG5 , LRRC25 , and SP100) were selected to establish a risk signature for primary LGG. The ROC curves showed a fair performance in survival prediction in both the TCGA and the CGGA validation cohorts. Univariate and multivariate Cox regression revealed that the risk group was an independent prognostic factor in primary LGG. The nomogram was developed based on clinical parameters integrated with the risk signature, and its accuracy for predicting 3- and 5-years survival was assessed by the concordance index, the area under the curve of the time-dependent receiver operating characteristics curve, and calibration curves. Conclusion: The SI-signature with seven genes could serve as an independent predictor, and suggests the importance of stemness features in risk stratification and survival prediction in primary LGG. [ABSTRACT FROM AUTHOR]

Objective: Despite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the immune microenvironment, the aim of our study was to develop an immune-related signature for risk stratification and prognosis prediction in LGG. Methods: RNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. Immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort). Univariate, multivariate cox regression, and Lasso regression were employed to identify differentially expressed immune-related genes (DEGs) and establish the signature. A nomogram was constructed, and its performance was evaluated by Harrell's concordance index (C-index), receiver operating characteristic (ROC), and calibration curves. Relationships between the risk score and tumor-infiltrating immune cell abundances were evaluated using CIBERSORTx and TIMER. Results: Noted, 277 immune-related DEGs were identified. Consecutively, 6 immune genes (CANX , HSPA1B , KLRC2 , PSMC6 , RFXAP , and TAP1) were identified as risk signature and Kaplan–Meier curve, ROC curve, and risk plot verified its performance in TCGA and CGGA datasets. Univariate and multivariate Cox regression indicated that the risk group was an independent predictor in primary LGG. The prognostic signature showed fair accuracy for 3- and 5-year overall survival in both internal (TCGA) and external (CGGA) validation cohorts. However, predictive performance was poor in the recurrent LGG cohort. The CIBERSORTx algorithm revealed that naïve CD4+ T cells were significant higher in low-risk group. Conversely, the infiltration levels of M1-type macrophages, M2-type macrophages, and CD8+T cells were significant higher in high-risk group in both TCGA and CGGA cohorts. Conclusion: The present study constructed a robust six immune-related gene signature and established a prognostic nomogram effective in risk stratification and prediction of overall survival in primary LGG. [ABSTRACT FROM AUTHOR]