1.Negative expression of RECK indicates unfavorable clinical outcome for breast cancer
Shaoqiang CHENG ; Yang LIU ; Xiaoshuan ILANG ; Da PANG ; Guoqiang ZHANG ; Jinsong WANG ; Yanni SONG
Practical Oncology Journal 2014;(1):12-18
Objecive To explore the significance of RECK expression in breast cancer .Methods Im-munohistochemical staining was used to analyze RECK expression levels in patients with breast cancer .We com-pared these data with the clinicopathological features of these patients .Rseults Breast cancer patients with nega-tive RECK expression had significantly lower DFS and 5-year survival rates than patients with positive RECK expression.In addition,for node-negative breast cancer ,negative RECK expression indicated markedly unfavor -able survival rate than positive arm .Multivariate analysis further confirmed that RECK expression was an inde -pendent prognostic factor for patients with breast cancer .Conclusion The loss of RECK expression indicates un-favorable survival rate for patients with breast cancer .RECK expression is a new ,important risk factor for recur-rence in breast cancer .
2.Abnormal gray matter and structural covariance network in first-episode and early-onset depression
Yuan CHEN ; Yu JIANG ; Yi CHEN ; Shaoqiang HAN ; Ruiping ZHENG ; Shuying LI ; Yong ZHANG ; Kangkang XUE ; Junhong LIU ; Jingliang CHENG
Chinese Journal of Radiology 2021;55(9):941-947
Objective:To investigate the abnormalities of gray matter volume (GMV) and the synergistic changes in different cerebral regions in the first-episode and early-onset depression (EOD) patients.Methods:A total of 60 patients with untreated EOD (EOD group) and 64 healthy controls (control group) matched for age, gender, and education underwent high-resolution T 1WI MR scans. Voxel-based morphometry was used to calculate the cerebral GMV. The difference in GMV between the two groups was compared with the t-test. Different brain regions were selected as seeds for structural covariation network (SCN) analysis. Spearman correlation model was used to analyze the correlation between the GMV in different cerebral regions and illness duration as well as the scores of Hamilton rating scale for depression (HAMD) 17 items in EOD group. Results:Compared to control group, the EOD group had significantly increased GMV in the right orbitofrontal cortex, right dorsolateral prefrontal cortex, right inferior parietal lobule, right superior parietal lobule and bilateral precuneus ( P<0.05, corrected by FDR). Based on the right orbitofrontal cortex and dorsolateral prefrontal cortex as seed regions, structural covariance analysis revealed that abnormal cooperative brain regions in EOD group, mainly distributed in the bilateral frontal lobe, parietal lobe, occipital lobe, temporal lobe, paralimbic system and cerebellum ( P<0.05, corrected by FDR). In EOD group, significant negative correlations were observed between the GMV in the right orbitofrontal cortex ( r=-0.314, P=0.015), the left precuneus ( r=-0.283, P=0.029), and illness duration. Significant positive correlations were observed between the GMV in the right dorsolateral prefrontal cortex and the scores of anxiety/somatization factor of HAMD17 ( r=0.331, P=0.010), the left precuneus and weight factor of HAMD17 ( r=0.255, P=0.049), respectively. Conclusions:Abnormal GMV changes are observed in some regions of the prefrontal and parietal lobule in patients with untreated EOD, accompanied by extensive covariant brain regions and additional structural connectivity. In addition, the abnormal GMV changes in some regions are associated with clinical features. Part of the prefrontal and parietal lobule may be the biomarkers to objectively evaluate abnormal brain structure in depression patients in the early stage.
3.The role and mechanism of HOXD3 in the stemness and chemotherapy resistance of breast cancer cells
Yanxia HE ; Jun YAN ; Hongbin LI ; Qingyuan ZHANG ; Shaoqiang CHENG ; Yue ZHANG
Chinese Journal of Clinical Oncology 2018;45(12):614-619
Objective: To investigate the effect of HOXD3 expression on the stem cell-like characteristics of breast cancer cells and the relationship between HOXD3 expression and multi-drug resistance in breast cancer cells. Methods: From January 2006 to December 2008, 87 specimens of breast cancer patients from the Affiliated Tumor Hospital of Harbin Medical University were collected. The ex-pression of HOXD3 in breast cancer cells and tissues was detected by immunohistochemical staining method. The expression levels of HOXD3 in CDDP or DOX-resistant cell lines MDA-MB-231 and MDA-MB-435 were detected by RT-PCR, Western blot and immunofluo-rescence staining. The effect of HOXD3 overexpression on the expression levels of stem cell biomarkers in breast cancer cell lines MDA-MB-231 and MDA-MB-435 was analyzed. MTT assay and colony formation assay were used to demonstrate the role of HOXD3 in che-motherapy resistance of breast cancer cells. Results: The relative expression of HOXD3 mRNA in breast cancer was 4.16, which was sig-nificantly higher than 2.05 in normal tissues adjacent to cancer; the relative expression levels of HOXD3 mRNA in breast cancer cell lines MDA-MB-231, MDA-MBB-435 and MCF-7 were 3.25, 2.84 and 2.23, which were all higher than 1.00 in normal breast epithelial cell line MCF-10A ( all P<0.05 ). The IC50s of MDA-MB-231 and MDA-MB-435 cell lines resistant to CDDP or DOX were (20.82±0.05) μmol/L, (19.69±0.47) μmol/L, (32.26±0.23) mmol/L and (26.08±0.55) mmol/L, respectively. Both were higher than the corresponding original cell lines (all P<0.05), and the drug resistance times were 2.47 and 3.10 or 1.86 and 2.08, respectively. The number of tumor spheres and stem cell biomarker expression levels of MDA-MB-231 and MDA-MB-435 with HOXD3 overexpression were significantly in-creased (all P<0.05). Conclusions: The expression of HOXD3 plays an important role in the maintenance of stem cell-like properties and drug resistance of breast cancer cells. The results of this study will help us better understand the complexity of breast cancer and pro-vide a theoretical basis for the development of targeted molecular therapy.
4.Study of the relationship between smoking and brain aging using machine learning model based on MRI
Xinyu GAO ; Mengzhe ZHANG ; Shaoqiang HAN ; Zhengui YANG ; Weijian WANG ; Ke XU ; Jingliang CHENG ; Yong ZHANG
Chinese Journal of Radiology 2022;56(12):1347-1351
Objective:To explore the value of machine learning models based on MRI predict the brain age of smokers and healthy controls, and further to explore the relationship between smoking and brain aging.Methods:This was a retrospective study. Dataset 1 consisted of 95 male smokers [20-50 (34±7) years old] and 49 healthy controls [20-50 (33±7) years old] recruited from August 2014 to October 2017 in First Affiliated Hospital of Zhengzhou University. Dataset 2 contained 114 healthy male volunteers [20-50 (34±11) years old] from the Southwestern University Adult Imaging Database from 2010 to 2015. All subjects underwent high-resolution 3D T 1WI scan. Gaussian process regression (GPR) model and support vector machine model were constructed to predict brain age based on structural MR images of healthy controls in dataset 1 and dataset 2. After the performance of the model was verified by the cross-validation method, the mean absolute error (MAE) between the predicted brain age and the actual age and the correlation ( r-value) between the actual age and the predicted brain age were calculated, and the best model was finally selected. The best models were applied to smokers and healthy controls to predict brain age. Finally, a general linear model was used to compare the differences in brain-predicted age difference (PAD) between smokers and healthy controls with age, taking years of education and total intracranial volume as covariates. Result:The performance of GPR model (MAE=5.334, r=0.747) in predicting brain age was better than support vector machine model (MAE=6.040, r=0.679). The GPR model predicted that PAD value of smokers in dataset 1 (2.19±6.64) was higher than that of healthy controls in dataset 1 (-0.80±8.94), and the difference was statistically significant ( F=8.52, P=0.004). Conclusion:GPR model based MRI has better performance in predicting brain age in smokers and healthy controls, and smokers show increased PAD values, further indicating that smoking accelerates brain aging.
5.Changes in functional connectivity of raphe nucleus in patients with first-episode depression complicated with suicidal ideation
Yu JIANG ; Yuan CHEN ; Shaoqiang HAN ; Ruiping ZHENG ; Bingqian ZHOU ; Shuying LI ; Jingliang CHENG
Chinese Journal of Interventional Imaging and Therapy 2024;21(1):22-27
Objective To observe the changes in functional connectivity(FC)of raphe nucleus in patients with first-episode depression complicated with suicidal ideation(SI).Methods Ninety-eight first-episode depression patients were prospectively enrolled and assigned into SI group(n=56)or non SI group(n=42)based on complicated with SI or not,while 47 healthy volunteers were recruited as control group.Resting-state functional MRI was performed.FC between dorsal raphe nucleus(DRN),median raphe nucleus(MRN)and the whole brain were analyzed and compared among 3 groups and between each 2 groups,and the correlations of FC of different brain regions with clinical data of SI group were explored.Results Compared with control group,FC between DRN and left cerebellum and left putamen in SI group and non SI group decreased(all P<0.05),between MRN and right inferior temporal gyrus increased but between MRN and left inferior frontal gyrus,right superior occipital gyrus,left inferior parietal lobule,left putamen decreased(all P<0.05).FC between DRN and left putamen in SI group was higher than that in non SI group(P<0.05).FC between MRN and right central posterior gyrus of SI group increased compared with that in the rest 2 groups(both P<0.05).FC between MRN and left putamen in SI group was positively correlated with body mass score of Hamilton depression scale-24(HAMD-24)(rs=0.297,P=0.026).Conclusion Abnormal changes of FC between raphe nucleus and cortex,also between raphe nucleus and subcortical area occurred,and FC between MRN and left putamen positively correlated with body mass score of HAMD-24 in patients with first-episode depression complicated with SI.
6.PRKAR1α expression in non-small cell lung cancer and its clinicopathologic significance.
Shaoqiang WANG ; Yuanda CHENG ; Zhiwei HE ; Wolong ZHOU ; Yang GAO ; Chaojun DUAN ; Chunfang ZHANG
Journal of Central South University(Medical Sciences) 2016;41(11):1148-1154
To evaluate the expression of cAMP-dependent protein kinase type I-alpha regulatory subunit (PRKAR1α) in non-small cell lung cancer (NSCLC) and its correlation with clinicopathological features.
Methods: PRKAR1α expressions in 79 NSCLC patients and matched adjacent non-carcinoma tissues were analyzed by using qRT-PCR and immunohistochemistry.
Results: The negative rates of PRKAR1α protein in NSCLC, lung squamous cell carcinoma (SCL) and lung adenocarcinoma (ACL) were 58.2%, 77.8%, 32.4%, respectively. Compared to the matched adjacent non-carcinoma tissues, there were significant differences in levels of PRKAR1α mRNA and protein in ACL (P<0.05), but not in SCL and overall NSCLC (P>0.05). The expression of PRKAR1α protein was positively correlated with histological type, TNM stage, and lymph node metastasis (P<0.05). Tumor size and histogenesis differentiation were not related to the decreased PRKAR1α (P>0.05).
Conclusion: Low expression of PRKAR1α in ACL might be involved in the pathogenesis, which might serve as a novel diagnostic candidate.
Adenocarcinoma
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chemistry
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classification
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genetics
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Adenocarcinoma of Lung
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Biomarkers, Tumor
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Carcinoma, Non-Small-Cell Lung
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chemistry
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genetics
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Carcinoma, Squamous Cell
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chemistry
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genetics
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Cyclic AMP-Dependent Protein Kinase RIalpha Subunit
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physiology
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Female
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Gene Expression Profiling
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Humans
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Immunohistochemistry
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Lung Neoplasms
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chemistry
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classification
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genetics
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Lymphatic Metastasis
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genetics
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Male
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Neoplasm Staging
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RNA, Messenger
7.Application of PDCA in the information management of blood transfusion medical records
Jiao LIU ; Yuanming YANG ; Dongmei GE ; Cong CHENG ; Shaoqiang ZHANG ; Ying LI ; Haiyan WANG
Chinese Journal of Blood Transfusion 2021;34(9):952-955
【Objective】 To explore the application effect of PDCA in improving the informationization of blood transfusion medical records. 【Methods】 The PDCA cycle theory and other quality management tools were used to analyze the causes of defects in blood transfusion records in a tertiary A hospital. Corresponding improvement measures for informationnization were formulated, and the situation before and after the improvement were compared to analyze the improvement effect. 【Results】 After the application of PDCA, the quality of blood transfusion records was significantly improved, and the defect rate decreased from 31.5% (193/612)to 12.1%(73/604), and the difference was statistically significant (P<0.05). 【Conclusion】 PDCA plays an important role in improving the quality of clinical blood transfusion records, standardizing the writing, and ensuring the safety and scientificity of the blood transfusion process.