1.Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms.
Wen-Yu JIA ; Feng TONG ; Heng-Xu LIU ; Shu-Qin JIN ; Yong-Chao ZHANG ; Chen-Feng ZHANG ; Zhen-Zhong WANG ; Xin ZHANG ; Wei XIAO
China Journal of Chinese Materia Medica 2025;50(2):430-438
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods*
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Drugs, Chinese Herbal/administration & dosage*
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Machine Learning
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Algorithms
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Humans
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Quality Control
2.Preliminary application of human-computer interaction CT imaging AI recognition and positioning technology in the treatment of type C1 distal radius fractures.
Yong-Zhong CHENG ; Xiao-Dong YIN ; Fei LIU ; Xin-Heng DENG ; Chao-Lu WANG ; Shu-Ke CUI ; Yong-Yao LI ; Wei YAN
China Journal of Orthopaedics and Traumatology 2025;38(1):31-40
OBJECTIVE:
To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures.
METHODS:
Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details.
RESULTS:
Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters.
CONCLUSION
Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans
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Male
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Female
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Radius Fractures/surgery*
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Middle Aged
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Adult
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Aged
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Aged, 80 and over
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Tomography, X-Ray Computed/methods*
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Retrospective Studies
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Software
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Wrist Fractures
3.A small molecule cryptotanshinone induces non-enzymatic NQO1-dependent necrosis in cancer cells through the JNK1/2/Iron/PARP/calcium pathway.
Ying HOU ; Bingling ZHONG ; Lin ZHAO ; Heng WANG ; Yanyan ZHU ; Xianzhe WANG ; Haoyi ZHENG ; Jie YU ; Guokai LIU ; Xin WANG ; Jose M MARTIN-GARCIA ; Xiuping CHEN
Acta Pharmaceutica Sinica B 2025;15(2):991-1006
Human NAD(P)H: quinone oxidoreductase 1 (NQO1) is a flavoenzyme expressed at high levels in multiple solid tumors, making it an attractive target for anticancer drugs. Bioactivatable drugs targeting NQO1, such as β-lapachone (β-lap), are currently in clinical trials for the treatment of cancer. β-Lap selectively kills NQO1-positive (NQO1+) cancer cells by inducing reactive oxygen species (ROS) via catalytic activation of NQO1. In this study, we demonstrated that cryptotanshinone (CTS), a naturally occurring compound, induces NQO1-dependent necrosis without affecting NQO1 activity. CTS selectively kills NQO1+ cancer cells by inducing NQO1-dependent necrosis. Interestingly, CTS directly binds to NQO1 but does not activate its catalytic activity. In addition, CTS enables activation of JNK1/2 and PARP, accumulation of iron and Ca2+, and depletion of ATP and NAD+. Furthermore, CTS selectively suppressed tumor growth in the NQO1+ xenograft models, which was reversed by NQO1 inhibitor and NQO1 shRNA. In conclusion, CTS induces NQO1-dependent necrosis via the JNK1/2/iron/PARP/NAD+/Ca2+ signaling pathway. This study demonstrates the non-enzymatic function of NQO1 in inducing cell death and provides new avenues for the design and development of NQO1-targeted anticancer drugs.
4.Genome-wide investigation of transcription factor footprints and dynamics using cFOOT-seq.
Heng WANG ; Ang WU ; Meng-Chen YANG ; Di ZHOU ; Xiyang CHEN ; Zhifei SHI ; Yiqun ZHANG ; Yu-Xin LIU ; Kai CHEN ; Xiaosong WANG ; Xiao-Fang CHENG ; Baodan HE ; Yutao FU ; Lan KANG ; Yujun HOU ; Kun CHEN ; Shan BIAN ; Juan TANG ; Jianhuang XUE ; Chenfei WANG ; Xiaoyu LIU ; Jiejun SHI ; Shaorong GAO ; Jia-Min ZHANG
Protein & Cell 2025;16(11):932-952
Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics*
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Humans
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Chromatin/genetics*
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Animals
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Binding Sites
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Mice
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DNA Footprinting/methods*
5.Development, comparison and validation of clinical predictive models for brain injury after in-hospital post-cardiac arrest in critically ill patients.
Guowu XU ; Yanxiang NIU ; Xin CHEN ; Wenjing ZHOU ; Abudou HALIDAN ; Heng JIN ; Jinxiang WANG
Chinese Critical Care Medicine 2025;37(6):560-567
OBJECTIVE:
To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment.
METHODS:
A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria.
RESULTS:
A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876).
CONCLUSIONS
A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.
Humans
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Critical Illness
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Retrospective Studies
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Heart Arrest/complications*
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Nomograms
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Brain Injuries/etiology*
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Intensive Care Units
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Algorithms
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Male
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Female
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Middle Aged
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ROC Curve
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Risk Factors
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Risk Assessment
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Logistic Models
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Aged
6.Construction of the quality evaluation scale of specification of management for humanistic caring in outpatients and its reliability and validity testing
Lixia YUE ; Na CUI ; Xu CHE ; Heng ZHANG ; Hongxia WANG ; Shujie GUO ; Hongling SHI ; Ruiying YU ; Xia XIN ; Xiaohuan CHEN ; Li WANG ; Zhiwei ZHI ; Lei TAN ; Xican ZHENG
Chinese Medical Ethics 2024;37(11):1366-1377
Objective:To construct the quality evaluation scale of specification of management for humanistic caring in outpatients and test its reliability and validity.Methods:Referring to the group standards in Specification of Management for Humanistic Caring in Outpatients released by the China Association for Life Care,as well as relevant guidelines and literature,a pool of items for the quality evaluation scale of specification of management for humanistic caring in outpatients was formed.After expert consultation and expert argumentation,a quality evaluation scale of specification of management for humanistic caring in outpatients was constructed.From January to February 2024,243 hospital managers from 5 hospitals in Zhengzhou were selected as survey subjects to conduct item analysis,and reliability and validity testing on the scale.Results:Two rounds of expert inquiry and two rounds of expert argumentation were conducted,with questionnaire response rates of 92.00%and 100.00%,respectively,and expert authority coefficients of 0.952.In the second round of the expert inquiry scale,the mean importance score of the first-level indicators was 4.80 to 5.00,the full score ratio was 88.00%to 100.00%,the coefficient of variation was 0.04 to 0.17,and Kendall's coefficient of concordance was 0.857(P<0.001);the mean importance score of the second-level indicators was 4.60 to 5.00,the full score ratio was 80.00%to 100.00%,the coefficient of variation was 0.00 to 0.21,and Kendall's coefficient of concordance was 0.775(P<0.001);the mean importance score of the third-level indicators was 4.60 to 5.00,the full score ratio was 76.00%to 100.00%,the coefficient of variation was 0.00 to 0.21,and Kendall's coefficient of concordance was 0.830(P<0.001).Finally,a quality evaluation scale of specification of management for humanistic caring in outpatients was formed,including 5 first-level indicators,25 second-level indicators,and 58 third-level indicators.Exploratory factor analysis produced 5 common factors with a cumulative variance contribution rate of 74.628%.The Pearson correlation coefficients between the five-factor scores ranged from 0.648 to 0.798,and the correlation coefficients between the factor scores and the total score of the scale ranged from 0.784 to 0.938.The scale-level content validity index(S-CVI)of the scale was 0.945,the item-content validity index(I-CVI)was 0.725 to 1.000,the Cronbach's alpha coefficient of the total scale was 0.973,and the retest reliability coefficient was 0.934.Conclusion:The constructed quality evaluation scale of specification of management for humanistic caring in outpatients has good scientific validity and reliability,and can be used as an evaluation tool for specification of management for humanistic caring in outpatients.
7.Mannitol inhibits the proliferation of neural stem cell by a p38 mitogen-activated protein kinase-dependent signaling pathway
Hai-Zhen DUAN ; Xin ZHOU ; Quan HU ; Meng-Long LIU ; Shu-Hong WANG ; Ji ZHANG ; Xu-Heng JIANG ; Tian-Xi ZHANG ; An-Yong YU
Chinese Journal of Traumatology 2024;27(1):42-52
Purpose::Mannitol is one of the first-line drugs for reducing cerebral edema through increasing the extracellular osmotic pressure. However, long-term administration of mannitol in the treatment of cerebral edema triggers damage to neurons and astrocytes. Given that neural stem cell (NSC) is a subpopulation of main regenerative cells in the central nervous system after injury, the effect of mannitol on NSC is still elusive. The present study aims to elucidate the role of mannitol in NSC proliferation.Methods::C57 mice were derived from the animal house of Zunyi Medical University. A total of 15 pregnant mice were employed for the purpose of isolating NSCs in this investigation. Initially, mouse primary NSCs were isolated from the embryonic cortex of mice and subsequently identified through immunofluorescence staining. In order to investigate the impact of mannitol on NSC proliferation, both cell counting kit-8 assays and neurospheres formation assays were conducted. The in vitro effects of mannitol were examined at various doses and time points. In order to elucidate the role of Aquaporin 4 (AQP4) in the suppressive effect of mannitol on NSC proliferation, various assays including reverse transcription polymerase chain reaction, western blotting, and immunocytochemistry were conducted on control and mannitol-treated groups. Additionally, the phosphorylated p38 (p-p38) was examined to explore the potential mechanism underlying the inhibitory effect of mannitol on NSC proliferation. Finally, to further confirm the involvement of the p38 mitogen-activated protein kinase-dependent (MAPK) signaling pathway in the observed inhibition of NSC proliferation by mannitol, SB203580 was employed. All data were analyzed using SPSS 20.0 software (SPSS, Inc., Chicago, IL). The statistical analysis among multiple comparisons was performed using one-way analysis of variance (ANOVA), followed by Turkey's post hoc test in case of the data following a normal distribution using a Shapiro-Wilk normality test. Comparisons between 2 groups were determined using Student's t-test, if the data exhibited a normal distribution using a Shapiro-Wilk normality test. Meanwhile, data were shown as median and interquartile range and analyzed using the Mann-Whitney U test, if the data failed the normality test. A p < 0.05 was considered as significant difference. Results::Primary NSC were isolated from the mice, and the characteristics were identified using immunostaining analysis. Thereafter, the results indicated that mannitol held the capability of inhibiting NSC proliferation in a dose-dependent and time-dependent manner using cell counting kit-8, neurospheres formation, and immunostaining of Nestin and Ki67 assays. During the process of mannitol suppressing NSC proliferation, the expression of AQP4 mRNA and protein was downregulated, while the gene expression of p-p38 was elevated by reverse transcription polymerase chain reaction, immunostaining, and western blotting assays. Subsequently, the administration of SB203580, one of the p38 MAPK signaling pathway inhibitors, partially abrogated this inhibitory effect resulting from mannitol, supporting the fact that the p38 MAPK signaling pathway participated in curbing NSC proliferation induced by mannitol.Conclusions::Mannitol inhibits NSC proliferation through downregulating AQP4, while upregulating the expression of p-p38 MAPK.
8.Toxicology study on repeated administration of Qingre Xiaoyanning tablets
Li ZHAO ; Li-Jun FU ; Zhi-Yi ZHOU ; Shuai YI ; Heng-Xin WANG
The Chinese Journal of Clinical Pharmacology 2024;40(1):82-86
Objective To explore the effect of Qingre Xiaoyanning tablets on chronic toxicity in SD rats.Methods A total of 120 SD rats were randomly divided into blank group(water)and experimental-L,-M,-H groups(2.63,5.25 and 10.50 g·kg 1 Qingre Xiaoyanning dry paste powder),with 30 rats per group.Four groups were administered continuously for 4 weeks with a recovery period of 4 weeks.SD rats were dissected as planned.The general condition,weight gain,hematological and biochemical indexes,major organ coefficients,macroscopic and microscopic tissue morphology were observed.Results There were no significant differences in the general condition,body mass growth,coagulation index and histopathology of rats between the experimental-L,-M,-H groups and the blank group.End of administration,the mean hemoglobin concentrations of experimental-H and blank groups were(370.70±3.78)and(365.90±5.77)g·L-1,glucose were(5.98±0.63)and(6.61±0.93)mmol·L-1,blood urea nitrogen(BUN)were(4.72±1.01)and(5.78±1.64)mmol·L-1,liver coefficients were 3.05±0.17 and 2.89±0.19,and the differences were statistically significant(P≤0.05,P≤0.01).Resumption of the final,direct bilirubin of experimental-L and blank groups were(0.38±0.18)and(0.19±0.18)pmol·L 1,BUN of experimental-M and blank groups were(4.45±0.56)and(5.65±1.16)mmol·L-1,and the differences were statistically significant(all P≤0.05).Conclusion Repeated administration of Qingre Xiaoyanning tablets showed no significant toxicity in SD rats.
9.Regulation of microRNA in the development of primary hepatocellular carcinoma
Da-Wei CHEN ; Zhi-Xin WANG ; Heng LI ; San-Qiang LI
The Chinese Journal of Clinical Pharmacology 2024;40(8):1231-1235
Hepatocellular carcinoma(HCC)accounts for more than 80%of primary liver cancer,and the prognosis of patients is very poor due to factors such as untimely diagnosis,failure of chemotherapy and frequent recurrence.MicroRNA is a kind of endogenous noncoding RNA,which can inhibit the translation of messenger RNA in liver malignant tumors,regulate the proliferation,apoptosis,migration and invasion of HCC cells,and play an important role in the development of HCC.Therefore,the mechanism of miRNAs in the development of HCC and its research progress in diagnosis and treatment are deeply discussed.
10.Relationship and clinical significance of ctDNA methylation and postoperative recurrence of thyroid cancer
Xin-Yu LIU ; Heng-Guan CUI ; Ting ZHOU ; Xiao-Liang WANG ; Wei-Xing SHEN
Chinese Journal of Current Advances in General Surgery 2024;27(8):618-621
Objective:To investigate the relationship and clinical significance of circulating tu-mor DNA(ctDNA)methylation with postoperative recurrence of thyroid cancer.Method:5 pa-tients with recurrent thyroid cancer in our hospital from March 2021 to April 2022 were selected as the observation group,and 2 healthy volunteers were selected as the control group.The level of ctDNA methylation in peripheral blood of the two groups was detected by Illumina high-throughput sequencing system.Gene ontology(GO)function analysis and Kyoto gene and genome encyclope-dia(KEGG)signal pathway analysis were carried out on the methylation region genes with signifi-cant differences through the DAVID gene function analysis platform.Result:There were 7787 dif-ferential ctDNA methylation sites between the two groups.2914(37.4%)were hypermethylation sites and 4873(62.6%)were low methylation sites.GO functional analysis showed that differentially methylated genes were enriched in molecular functions such as DNA-binding transcriptional acti-vation,cell-substrate adhesion,glycoprotein complex and other cellular components.KEGG path-way analysis showed that differentially methylated genes were enriched in thyroid carcinoma signal pathway,cell adhesion molecules,RAP1 signal pathway,RAS signal pathway,MAPK signal path-way and so on.Conclusion:ctDNA methylation may be involved in cancer recurrence in postop-erative patients with thyroid cancer.Monitoring the level of ctDNA methylation in peripheral blood may be an effective method to indicate the recurrence or metastasis of thyroid cancer and guide clinical diagnosis and treatment.

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