Analysis of nutritional risk, skeletal muscle depletion, and lipid metabolism phenotype in acute radiation enteritis

Establishment of a prognostic nomogram based on the clinical and inflammatory parameters as well as acute radiation enteritis for patients with cervical cancer receiving radiotherapy

Objective

Acute radiation enteritis is one of the most common complications of radiotherapy for patients with cervical cancer. This study aims to investigate the effect of acute radiation enteritis on the prognosis of patients with cervical cancer receiving radiotherapy and to establish a nomogram predicting the patients' overall survival (OS).

Methods

The clinical data of 288 patients with cervical cancer who were admitted to our department from 2014 to 2020 were retrospectively analyzed, and the survival of patients were followed up. The Kaplan-Meier method was used to calculate the survival rate and for univariate analysis, and the Cox regression model was used for multivariate prognostic analysis. A nomogram survival prediction model was established based on independent risk factors, and the concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the predictive accuracy of the model. The clinical applicability of the model was assessed by the decision curve. External validation of the nomogram prediction model was performed in 74 patients admitted to our hospital from 2020 to 2021.

Results

60 patients (20.8%) developed grade 2 or higher acute radiation enteritis. The 1-, 3-, and 5-year OS rates were 94.4%, 80.9%, and 77.4%, respectively. Multivariate Cox regression analysis showed that: Age ≥ 60 years, diabetes/hypertension, anemia, FIGO stage III-IV, poor differentiation, pelvic lymph node metastasis, NLR ≥ 2.54 and grade 2 or higher acute radiation enteritis were independent risk factors for OS in cervical cancer patients undergoing radiotherapy (P < 0.05). The C-index of OS nomogram model was 0.815 (95% CI: 0.766-0.864). The AUC of 3-year and 5-year OS were 0.849 (95%CI: 0.789-0.909) and 0.840 (95%CI: 0.782-0.899), respectively. The AUC value of 3-year OS in the external validation set was 0.779 (95%CI: 0.635-0.922). The calibration curve showed that the model was well calibrated, and the decision curve verified the clinical applicability of the constructed nomogram.

Conclusion

This study established an accurate predicting nomogram based on independent prognostic factors in cervical cancer patients receiving radiotherapy, and patients with grade 2 or higher acute radiation enteritis should be paid more attention to in clinical practice.

Transcriptomics integrated with metabolomics reveals partial molecular mechanisms of nutritional risk and neurodevelopment in children with congenital heart disease

Purpose

To explore molecular mechanisms affecting nutritional risk and neurodevelopment in children with congenital heart disease (CHD) by combining transcriptome and metabolome analysis.

Methods

A total of 26 blood and serum samples from 3 groups of children with CHD low nutritional risk combined with normal neurodevelopment (group A), low nutritional risk combined with neurodevelopmental disorders (group B) and high nutritional risk combined with normal neurodevelopment (group C) were analyzed by transcriptome and metabolomics to search for differentially expressed genes (DEGs) and metabolites (DEMs). Functional analysis was conducted for DEGs and DEMs. Further, the joint pathway analysis and correlation analysis of DEGs and DEMs were performed.

Results

A total of 362 and 1,351 DEGs were detected in group B and C compared to A, respectively. A total of 6 and 7 DEMs were detected in group B and C compared to A in positive mode, respectively. There were 39 and 31 DEMs in group B and C compared to A in negative mode. Transcriptomic analysis indicated that neurodevelopment may be regulated by some genes such as NSUN7, SLC6A8, CXCL1 and LCN8, nutritional risk may be regulated by SLC1A3 and LCN8. Metabolome analysis and joint pathway analysis showed that tryptophan metabolism, linoleic and metabolism and glycerophospholipid metabolism may be related to neurodevelopment, and glycerophospholipid metabolism pathway may be related to nutritional risk.

Conclusion

By integrating transcriptome and metabolome analyses, this study revealed key genes and metabolites associated with nutritional risk and neurodevelopment in children with CHD, as well as significantly altered pathways. It has important clinical translational significance.