1.Thrombospondin 2 and tumors
Journal of International Oncology 2021;48(3):164-166
Thrombospondin (THBS) 2, as a member of the THBS family, is expressed in a variety of tumor cells and has important significance in the development and metastasis of tumors. In recent years, studies have reported that the specific role of THBS2 in different tumors is different, and it participates in a variety of biological processes, such as cell apoptosis, wound healing, angiogenesis and inflammation. At present, the role of THBS2 in tumorigenesis, development, and prognosis is not completely clear. Exploring the abnormal expression and mechanism of THBS2 in tumors is expected to provide a new method for tumor diagnosis and treatment.
2.The value of magnetic resonance imaging and pathological multi parameters in predicting the efficacy of neoadjuvant chemotherapy for advanced breast cancer
Zhengtong WANG ; Fan ZHAO ; Chongchong LI ; Yueqin CHEN ; Zhanguo SUN ; Hao YU ; Zhitao SHI ; Lin CHEN ; Weiwei WANG
Journal of Chinese Physician 2024;26(9):1343-1349
Objective:To explore the value of conventional magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI) sequence and pathological examination in predicting the efficacy of neoadjuvant chemotherapy (NAC) in advanced breast cancer.Methods:The clinical data of 65 cases of advanced breast cancer with NAC confirmed by pathology in the Affiliated Hospital of Jining Medical University from March 2022 to May 2023 were retrospectively analyzed, including 20 cases in the pathological complete remission (pCR) group and 45 cases in the non pCR group; All patients underwent routine MRI, DWI, DKI examinations and pathological analysis. The clinical pathological data, routine MRI features, apparent diffusion coefficient (ADC) values, mean kurtosis coefficient (MK), and mean diffusion coefficient (MD) between the two groups were analyzed; We compared the differences in various parameters between two groups and plotted receiver operating characteristic (ROC) curves to compare their diagnostic efficacy of NAC in breast cancer.Results:There were significant differences in molecular typing, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2) and Ki-67 between pCR group and non pCR group (all P<0.05). In pCR group, Her-2 overexpression type and triple negative breast cancer (TNBC) type breast cancer were more common. ER and PR were mostly negative, Her-2 was mostly positive, and Ki 67 was mainly positive. The difference in tumor T2WI signal between the pCR group and the non pCR group was statistically significant ( P<0.05), with the pCR group showing mostly moderate/low T2WI signal. The ADC and MD values of the pCR group were lower than those of the non pCR group, while the MK value of the pCR group was higher than that of the non pCR group, and the differences were statistically significant (all P<0.001). The area under the ROC curve (AUC) for predicting the efficacy of NAC using a clinical pathological model was 0.829, which was higher than the AUC of molecular subtypes, ER, PR, Her-2, and Ki-67 ( Z=3.008, 2.697, 2.815, 2.131, 2.376, all P<0.05); The AUC of the DKI+ DWI predicting the efficacy of NAC was 0.934, which was higher than that of the DWI single sequence model, and the difference in type was statistically significant ( Z=2.396, P=0.017). The diagnostic efficacy of the DKI+ DWI model was higher than that of the single parameter ADC, MD, and MK, and the differences were statistically significant ( Z=2.396, 2.219, 2.161, all P<0.05); The AUC of the combined imaging and pathology model was 0.983, and its diagnostic efficacy was higher than that of the conventional MRI feature model, pathology model, DWI model, and DKI model, with statistically significant differences ( Z=5.877, 2.961, 3.240, 2.264, all P<0.05). Conclusions:The results of pathology, conventional MRI, DWI and DKI parameters of pCR and non pCR breast cancer patients are significantly different, and the combined model is better than the single model in predicting the efficacy of NAC.