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Objective:To investigate the value of lipid metabolism-related genes (LMRG) for predicting the efficacy of neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC).Methods:GSE46862, a genome-wide expression data of LARC treated with neoadjuvant radiotherapy, was obtained from the Gene Expression Database, and differential expression analysis was performed to obtain differentially expressed genes. The LMRG were collected from the MSigDB database and intersected with differentially expressed genes to obtain differentially expressed LMRG. Candidate LMRG were identified based on three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine - recursive feature elimination (SVM-RFE), and random forest (RF). Functional enrichment analysis was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to obtain potential function and involved pathways. The accuracy of the candidate LMRG in predicting the efficacy of neoadjuvant chemoradiotherapy for LARC was assessed using receiver operating characteristic (ROC) curve analysis.Results:A total of eight candidate LMRG ( ALOX5AP, FADS2, GALC, PLA2G12A, AGPAT1, AACS, DGKG, ACSBG2) were screened which were mainly involved in biological processes related to lipid metabolism and were involved in the regulation of several important lipid metabolism-related signaling pathways. In addition, these eight candidate LMRG possessed high area under the ROC curve (AUC) for predicting the efficacy of neoadjuvant chemoradiotherapy for LARC. Conclusion:The eight LMRG identified based on three machine learning algorithms had high accuracy in predicting the efficacy of neoadjuvant chemoradiotherapy for LARC, providing clues to identify molecular markers and potential therapeutic targets for preoperative neoadjuvant radiotherapy evaluation of LARC.
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Objective:To evaluate the dose calculation accuracy of cone-beam CT (CBCT) image by actual measurement method.Methods:CBCT images of 60 patients in the Second Affiliated Hospital of Soochow University from September, 2021 to May, 2022 were retrospectively analyzed. CBCT images of full-fan and half-fan scanning of the head, half-fan scanning of the chest and pelvis were obtained by the Varian OBI system. Hounsfield unit - electron density (HU-ED) curves corresponding to the scanning conditions were established with CIRS electron density phantom. The radiotherapy plans were designed on the CBCT images, and the dose calculation results of the detection point were compared with the ionization chamber measurement results to analyze the dose error. Then, three-dimensional dose verification system was adopted to detect the accuracy of the CBCT image radiotherapy plans implementation process in 60 patients, and the accuracy of dose calculation was verified according to the D 99%, D mean, D 1% of target volume, D mean and D 1% of organs at risk (OAR), and the γ pass rate. Results:In point dose detection in phantom, the dose calculation errors of CBCT images in the above four scanning patterns were -1.06%±0.87%、-1.67%±0.86%, 0.91%±0.73%, -1.54%±0.90%, respectively. In dosimetric verification based on patients' CBCT image treatment plan, the mean difference of D mean, D 99%, and D 1% of planning target volume (PTV) in all scanning modes were not higher than 2%, and the D mean and D 1% differences of other OAR were not higher than 3%, except for the lens of patients in the head. The average γ values of target volume and OAR were less than 0.5 under the criteria of 3%/2 mm. Conclusions:Under the condition of correctly establishing HU-ED curves, intensity-modulated radiation therapy (IMRT) / volumetric-modulated arc therapy (VMAT) planning based on CBCT images can be employed to estimate and monitor the actual dose to target volume and OAR in adaptive radiotherapy. Full-fan scanning patterns can further improve the accuracy of dose calculation for the head of patients.
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Neoadjuvant chemoradiotherapy (NCRT) has become the standard treatment for patients with locally advanced rectal cancer (LARC).However,the response to NCRT varies among LARC patients and a subset of patients show resistance to NCRT.NCRT may delay the timing of surgery and even reduce the overall survival.Therefore,it is of significance to identify biomarkers for predicting the clinical efficacy of NCRT,screen patients who are resistant to NCRT and perform surgery as early as possible,eventually establishing an individualized therapeutic strategy.MicroRNAs are a class of small non-coding RNAs that post-transcriptionally regulate gene expression,which areinvolved in multiple signaling pathways and DNA damage repair process and affect the radiosensitivity of rectal cancer cells.Many recent studies have evaluated the role of microRNA in predicting the response to NCRT.The purpose of this article is to review the research progress and validate the role of microRNA in predicting the clinical efficacy of NCRT for rectal cancer.
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Objective To investigate the multiple risk factors for lower extremity lymphedema in patients following treatment of common gynecologic cancers by meta-analysis for systematic analysis and comprehensive quantitative study.Methods Clinical trials published up until August 2016 were retrieved from PubMed, Embase, and the Cochrane Library.The quality of the included studies was assessed by the Newcastle-Ottawa Scale, and data analysis was performed using Stata 14.0 and RevMan 5.3.The strength of the associations between risk factors and gynecologic cancer-related lower extremity lymphedema was described as odds ratio (OR) and 95% confidence intervals (CI).Results Eighteen studies were included in the meta-analysis, and 8 relevant factors were identified.The risk factors for lower extremity lymphedema after treatment of gynecologic cancer mainly included radiotherapy (OR=2.45, 95%CI:2.05-2.95, P=0.000), FIGO stage (OR=2.29, 95%CI:1.66-3.14, P=0.000), and pelvic lymph node dissection (OR=2.00, 95%CI:1.02-3.91, P=0.040).Conclusions Radiotherapy, FIGO stage, and pelvic lymph node dissection are the main risk factors for lower extremity lymphedema after treatment of gynecologic cancers.
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Objective MicroRNAs (miRNAs) play important roles in the chemoradiotherapy efficacy of rectal cancer (RC).This study aimed to screen the chemoradiotherapy-associated microRNAs and their target genes of RC through bioinformatics approaches in order to promote the fundamental study of RC chemoradiotherapy.Methods The chemoradiotherapy-associated microRNAs were manually searched through the published papers via PubMed and its target genes were identified by comprehensively analyzing these public data of microRNA-mRNA and gene expression profiles.Both gene ontology (GO) and pathway analysis of the target genes were performed by DAVID and IPA programs,respectively.Results A total of 38 microRNAs were collected from PubMed,and 3 545 putative target genes were inferred from the integrated microRNA-mRNA associations,among them,131 were differentially expressed (DE) (P ＜ 0.05) in the selected gene expression profile (GSE35452).The GO and pathway enrichment analyses indicated that the DE genes were closely involved in the responses of chemoradiotherapy of RC.Conclusions These microRNAs and their regulated DE genes may contribute to the molecular mechanism of the differential efficacy of RC chemoradiotherapy,which may provide a theoretical reference for predicting the response of RC to chemoradiotherapy.