Objective:To explore the value of tumor stroma ratio (TSR) in non-small lung cancer (NSCLC) tissue in predicting the efficacy of tumor immunotherapy.Methods:The clinical and histopathological data of patients with stage ⅢB-Ⅳ NSCLC treated with immune checkpoint inhibitors in the Renmin Hospital of Wuhan University from January 2017 to December 2020 were collected. Taking 50% as the TSR boundary value, the patients were divided into low TSR group (≤50%) and high TSR group (>50%) . The histopathological features, 4-cycle objective response rate (ORR) and disease control rate (DCR) , 6-cycle ORR and DCR, and progression-free survival (PFS) were compared between the two groups. Univariate and multivariate Cox regression models were used to analyze the prognostic factors related to PFS.Results:A total of 50 patients were included, including 27 with low TSR and 23 with high TSR. There were no significant differences between the two groups in age ( χ2=0.59, P=0.441) , gender ( P=0.578) , smoking history ( χ2=0.12, P=0.730) , histopathological type ( χ2=2.33, P=0.313) , TNM stage ( χ2=0.22, P=0.636) , 4-cycle ORR ( χ2=0.48, P=0.487) and DCR ( P=0.593) , 6-cycle ORR ( χ2=0.05, P=0.818) and DCR ( P=0.641) . The incidence of brain metastasis was higher in the high TSR group than that in the low TSR group [34.8% (8/23) vs. 7.4% (2/27) , χ2=4.23, P=0.040]. Kaplan-Meier survival analysis showed that the PFS in the low TSR group was significantly longer than that in the high TSR group (15.6 months vs. 10.2 months, χ2=13.84, P<0.001) . Univariate analysis showed that TSR value ( HR=0.29, 95% CI: 0.14-0.58, P<0.001) and brain metastasis ( HR=2.38, 95% CI: 1.12-5.05, P=0.024) were correlated with the worse prognosis of NSCLC patients. Multivariate Cox regression analysis showed that TSR value was an independent prognostic factor for NSCLC immunotherapy ( HR=0.32, 95% CI: 0.14-0.70, P=0.004) . Conclusion:TSR is an independent predictor of immunotherapy for NSCLC, but whether it can predict the short-term efficacy of immunotherapy for advanced NSCLC still needs further research.

Tumor cells and tumor microenvironment (TME) are closely related. It is known that many factors will change the TME, then affect tumor development, however the change of TME is also inseparable from tumor cells. More and more studies have confirmed that the regulation of TME is the key to anti-tumor therapy. Therefore, it is critical to understand the effect of tumor cells on TME.

Objective:To investigate the value of net water uptake (NWU) for predicting early neurological improvement (ENI) after endovascular treatment in patients with acute anterior circulation large vessel occlusion stroke.Methods:A case-control study. A total of 132 patients (80 men, 52 women, median age 68 years) with acute anterior circulation large vessel occlusive stroke receiving endovascular treatment were retrospectively analyzed at Jinling Hospital from October 2014 to September 2019. Patients were divided into two groups based on the occurrence of ENI, which was defined as either an improvement of NIHSS score of ≥4 points, or an NIHSS score of 0 or 1 at 24 hours after endovascular treatment. The rank sum test, Chi square test, and other methods were used to compare differences in baseline characteristics between the two groups. Logistic regression analysis was used to investigate independent predictors of postoperative ENI. Receiver operating characteristic curve analysis used to assess the capacity of NWU to predict ENI.Results:Of the 132 patients in the study, ENI occurred in 47 and did not occur in 85. In multivariate logistic regression analysis age [odds ratio ( OR)=0.940, 95% confidence interval ( CI) 0.903-0.979, P=0.003], time from stroke onset to puncture ( OR=0.995, 95% CI 0.991-0.999, P=0.025), time from puncture to recanalization/end of operation ( OR=0.985, 95% CI 0.974-0.996, P=0.007), NWU ( OR=0.762, 95% CI 0.620-0.937, P=0.010), and mTICI ( OR=1.644, 95% CI 1.043-2.590, P=0.032) were predictive factors for ENI. Receiver operating characteristic curve analysis indicated that NWU could effectively predict ENI (area under the curve=0.642, 95% CI 0.543-0.741, P=0.007), and prediction accuracy was improved when it was combined with other clinical parameters. Conclusion:NWU is an independent predictor of ENI in patients with acute anterior circulation large vessel occlusive stroke undergoing endovascular treatment.