Objective To explore the prognostic predictors of patients with chromophobe renal cell carcinoma(ChRCC),and to construct a nomogram model and prognostic risk staging.Methods The data of this study were derived from the Surveillance,Epidemiology,and End Results(SEER)database.Cox regression analysis was used to determine the independent prognostic factors,and a nomogram model was constructed to predict the survival period of patients with ChRCC.The discrimination and accuracy of the model were evaluated using the consistency index and calibration curve.Prognostic risk staging was established and compared with the TNM staging system.Results A total of 6382 patients with ChRCC were included.They were randomly divided into training group(n=4467)and validation group(n=1915)in a 7:3 ratio.The results of the Cox regression analysis showed that age,gender,race,place of residence,lymph node metastasis,bone metastasis,lung metastasis,tumor breaking through the renal capsule,major vein invasion,pathological appearance of sarcomatous features,and surgical method were all independent influencing factors for the prognosis of ChRCC(P＜0.05).The C-index of this nomogram prognostic model was significantly higher than that of the TNM staging system(0.790 vs.0.617).The same trend was also observed in the validation group.The K-M survival curve based on the prognostic risk staging by the nomogram showed that there was a significant difference among the populations in each stage(P＜0.001),and the discrimination was superior to the TNM staging of renal cancer.Conclusion The prognostic nomogram model for ChRCC patients constructed based on comprehensive pathological factors can achieve high accuracy and stability.The prognostic risk staging established by this model can serve as a practical supplementary tool for evaluating the prognosis of ChRCC patients in clinical practice.

Objective To explore the prognostic predictors of patients with chromophobe renal cell carcinoma(ChRCC),and to construct a nomogram model and prognostic risk staging.Methods The data of this study were derived from the Surveillance,Epidemiology,and End Results(SEER)database.Cox regression analysis was used to determine the independent prognostic factors,and a nomogram model was constructed to predict the survival period of patients with ChRCC.The discrimination and accuracy of the model were evaluated using the consistency index and calibration curve.Prognostic risk staging was established and compared with the TNM staging system.Results A total of 6382 patients with ChRCC were included.They were randomly divided into training group(n=4467)and validation group(n=1915)in a 7:3 ratio.The results of the Cox regression analysis showed that age,gender,race,place of residence,lymph node metastasis,bone metastasis,lung metastasis,tumor breaking through the renal capsule,major vein invasion,pathological appearance of sarcomatous features,and surgical method were all independent influencing factors for the prognosis of ChRCC(P＜0.05).The C-index of this nomogram prognostic model was significantly higher than that of the TNM staging system(0.790 vs.0.617).The same trend was also observed in the validation group.The K-M survival curve based on the prognostic risk staging by the nomogram showed that there was a significant difference among the populations in each stage(P＜0.001),and the discrimination was superior to the TNM staging of renal cancer.Conclusion The prognostic nomogram model for ChRCC patients constructed based on comprehensive pathological factors can achieve high accuracy and stability.The prognostic risk staging established by this model can serve as a practical supplementary tool for evaluating the prognosis of ChRCC patients in clinical practice.

Gastric cancer with hemorrhage and cerebral infarction is a serious complica-tion with poor prognosis in clinic. Although the incidence rate is extremely low, the fatality and disability rates are very high. In addition, the opposition in treatment between the two complica-tions increases the difficulty of clinical diagnosis and treatment. The authors report the diagnosis and treatment of a gastric cancer patient with hemorrhage and new cerebral infarction, in order to to provide reference for related treatments.

Objective:To explore the effect of hederagenin (HE) on the proliferation of bladder cancer cell T24 in vitro and in nude mice.Methods:Human bladder cancer cells T24 were divided into control group and experimental group. The experimental group was cultured with DMEM medium containing 25μg/mL hederogenin, and CCK8 was used to detect cell proliferation ability. Nude mice were divided into a control group and an experimental group and injected with T24 cells. The cells of the experimental group were injected with ivy sapogenin at 30 mg/kg every other day. The protein of T24 cells and tumor mass was extracted to detect the expression of p-JNK/JNK and p-p38/p38.Results:After the bladder cancer cells T24 were treated with hederagenin, the CCK8 results showed that the cell proliferation ability of the experimental group was significantly decreased ( P<0.05) . The expression levels of p-JNK in experimental group and control group were 0.21±0.06 and 0.89±0.15, respectively, and the expression levels of p-p38 were 0.38±0.09 and 1.44±0.26, respectively. The expressions of p-JNK and p-p38 were up-regulated (all P<0.05) . In vivo, it was found that after treatment with ivisaponin, the volume of tumor mass were 1192.07±250.92μm 3 in the subcutaneous tumor experimental group and 2280.50±600.1μm 3 in the control group, and the mass were 0.65±0.29g and 1.62±0.38g, respectively. The mass and volume of the experimental group were decreased (all P<0.05) . We extracted mass proteins, and western blotting results showed that the expression levels of p-JNK in the experimental group and control group were 0.38±0.08 and 1.03±0.19, respectively, and the expression levels of p-p38 were 0.71±0.12 and 1.36±0.25, respectively. The expressions of p-JNK and p-p38 were up-regulated (all P<0.05) . Conclusion:Hederagenin inhibits the proliferation of bladder cancer in vitro and in nude mice through the JNK/p38 MAPK signaling pathway.