A nomogram integrating ferroptosis-and immune-related biomarker for prediction of prognosis and diagnosis in kidney renal clear cell carcinoma.

OBJECTIVE: Approximately 60% of patients with kidney renal clear cell carcinoma (KIRC) die within the first 2-3 years. The prognosis for patients with KIRC and its metastases is poor. Ferroptosis and providing immunity are novel treatment targets for several cancers, including KIRC. Therefore, it is important to identify suitable ferroptosis- and immune-related signatures to predict the prognosis and diagnosis of patients with KIRC. MATERIALS AND METHODS: The corresponding data of patients with KIRC were obtained from the Cancer Genome Atlas. Univariate and multivariate Cox regression analyses were used to screen candidate biomarkers in patients with KIRC. RESULTS: We found that four FI-DEGs (BID, MET, LTB4R, and HMOX1) were independently associated with the overall survival of patients with KIRC. The prognosis and diagnosis model constructed using these four biomarkers could predict the outcome of KIRC, as measured by the receiver operating characteristic analyses. CONCLUSIONS: We identified 4 FI-DEGs that could be used as biomarkers in patients with KIRC. The present study not only contributes to understanding the roles of ferroptosis and immunity in the development of KIRC, but also to the diagnosis and prognosis of KIRC, although it remains to be further studied.

MicroRNA related prognosis biomarkers from high throughput sequencing data of kidney renal papillary cell carcinoma.

OBJECTIVE: Renal cell carcinoma (RCC) is the most common type of kidney cancer which could be mainly classified as kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). KIRP ranks second in terms of morbidity rate which comprised 10%-15% of patients. Till now, there were few biomarkers could forecast the outcomes of KIRP. The aim of this study was to identify novel prognostic biomarkers to predict clinical outcomes for KIRP. MATERIALS AND METHODS: In this study, we firstly downloaded 326 miRNAs (35 controls vs. 291 patients), 321 mRNAs (33 controls vs. 288 patients) data and their corresponding clinical information from The Cancer Genome Atlas database. Then, we used DESeq2 analysis, univariate and multivariate Cox regression analysis, pathologic MNT correlation analysis, and specific prognostic model analysis to identify the potential prognosis biomarkers. RESULTS: We found 25 differential expression miRNAs (DEMs) and 7 differential expression genes (DEGs) were associated with the overall survival rates of KIRP patients. After multivariate Cox regression analysis, we established 2 prognostic prediction models and calculated the area under the 1-, 3-, and 5-year curve (AUC) values of DEMs and DEGs respectively. Among them, the prognostic index (PI) of DEMs and DEGs showed good predictive ability which was 0.8293/0.7205, 0.8148/0.7301 and 0.7776/0.6810 respectively. CONCLUSIONS: In this study, we found that 3 DEMs and 2 DEGs could be used as prognostic biomarkers to predict the outcome for KIRP. Our study was just a primary analysis based on high-throughput sequencing and clinical information.

[Clinical comparison analysis in surgically induced astigmatism of the total, anterior and posterior cornea after 2.2-mm versus 3.0-mm clear corneal incision cataract surgery].

Objective: To compare the surgical induced astigmatism(SIA) of the total, anterior and posterior cornea between eyes with 2.2-mm and 3.0-mm clear corneal incisions in phacoemulsification. Methods: A prospective double-blind randomized controlled study was conducted on 131 patients (131 eyes) with age-related cataract from October 2017 to June 2018. They were randomized according to the random number table. Sixty-nine patients received phacoemulsification through a 2.2-mm clear corneal incision at 140 degrees; 62 patients were recruited in the control group with a 3.0-mm clear corneal incision at the same position. Lens density was graded and compared between the groups preoperatively. Total corneal refractive power (TCRP), simulated keratometry (SimK) and posterior corneal astigmatism (PCA) (Apex, 4-mm zone) were recorded through the Pentacam preoperatively and at 1 week, 1 month and 3 months postoperatively. Corneal astigmatism was decomposed to vertical/horizontal (X) and oblique changes (Y) using the power vector analysis. Independent sample t test and matched t test were used for statistical analysis. Results: A total of 123 patients (123 eyes) completed 3 months of follow-up including 65 in the 2.2-mm group and 58 in the control group. The age of the two groups was (69±9) and (71±10) years old, and the lens density was (2.08±0.47) and (2.12±0.46) grades, respectively. Both the age and the lens density of the two groups were not statistically significant (both P>0.05). Preoperative TCRP, SimK and PCA were not statistically significant (all P>0.05). SIA was calculated using the vector analysis. Centroid SIA conducted from TCRP, SimK and PCA in the 2.2-mm group was -0.11 D@146°, -0.11 D@151° and -0.03 D@67°, respectively, at 3 months postoperatively. In the 3.0-mm group, it was -0.25 D@158°, -0.24 D@147° and -0.04 D@47°, respectively. Statistical significance was found between the two groups in the Y polar value of SIA of the anterior surface [(-0.10±0.30) vs.(-0.22±0.37) D, t=-2.133, P=0.035] and the SIA of the posterior surface [(0.24±0.16) vs. (0.19±0.12) D, t=2.009, P=0.047] at 3 months postoperatively. In the comparison of the SIA of TCRP and anterior surface, statistical significance was found in the absolute value of SIA at all the intervals in the 2.2-mm group [(0.87±0.80) vs. (0.58±0.48) D, (0.58±0.48) vs. (0.50±0.28)D, (0.57±0.37) vs. (0.47±0.28) D, t=5.102, 4.155, 3.877, all P<0.01] and at 1 week and 1 month in the 3.0-mm group [(0.82±0.57) vs. (0.58±0.41) D, (0.59±0.36) vs. (0.50±0.28) D, t=5.034, 3.919, both P<0.01]. X components of SIA(TCRP) and SIA(simk) were significantly different at 3 month postoperatively in 3.0-mm group (P<0.05). Y components of SIA(TCRP) and SIA(SimK) were significantly different at 1 week postoperatively in the 2.2-mm group[(-0.48±0.85) vs.(-0.24±0.42) D, P<0.01] and 3.0-mm group [(-0.58±0.66) vs. (-0.37±0.42) D, P<0.01]. Conclusions: Compared with the 3.0-mm incision, the 2.2-mm coaxial micro-incision cataract surgery has a lower and more stable SIA. The effect of a clear corneal incision in cataract surgery on the total cornea is more obvious than that on the anterior surface of the cornea. The difference is significant in the early stage and gradually decrease with time. (Chin J Ophthalmol, 2019, 55: 495-501).

[The influence of two calculation methods on the outcomes of Toric intraocular lenses].

Objective: To evaluate the influence of Barrett calculator and AcrySof calculator on astigmatism correction effect. Methods: This is a randomized prospective study. A total of 64 cases (81 eyes) who planed to undergo phacoemulsification at Tianjin Medical University Eye Hospital during January 2017 and March 2018 were enrolled and divided into two groups randomly, including of the Barrett calculator group of 34 cases (41 eyes) and the AcrySof calculator group of 30 cases (40 eyes). Preoperative ocular biological parameters were measured using Lenstar LS900. The Toric intraocular lenses (IOL) plans were determined based on Barrett calculator and the AcrySof calculator for the two groups respectively. Subjective optometry was performed by phoropter and Toric IOL alignment was detected by slitlamp examination at 1 and 3 months postoperatively. Statistical analysis was taken with the data of 29 cases (35 eyes) in the Barrett calculator group and 26 cases (35 eyes) in the AcrySof calculator group, there were 20 males (25 eyes) and 35 females (45 eyes) with an average age of (72±10) years. The difference between the predicted residual astigmatism by the two calculators and the residual astigmatism obtained by postoperative optometry is the error of refractive astigmatism (ERA). The magnitude error is the algebraic difference of ERA. Vector error(VE) is a vector difference of ERA. Statistical analysis of magnitude error and VE between the two groups were taken by student's t test or rank sum test. Results: At 1 months and 3 months, the magnitude error absolute value of Barrett calculator group were (0.19±0.16)D, (0.28±0.24)D, and those of AcrySof calculator group were (0.36±0.28)D, (0.46±0.41)D, and the differences were statistically significant (t=-3.050, -2.036, both P<0.05). At 1 month postoperatively, the overall, with-the-rule astigmatism, and against-the-rule astigmatism VE of the Barrett calculator group were (0.30±0.21)D, (0.26±0.22)D, (0.37±0.26)D respectively, and those of the AcrySof calculator group were (0.47±0.33)D, (0.51±0.34)D and (0.52±0.38)D respectively, the differences between the two groups were statistically significant (t=-2.533, -2.436, -2.150, all P<0.05). At 3 months postoperatively, the overall, with-the-rule astigmatism, and against-the-rule astigmatism VE of the Barrett calculator group were (0.37±0.28)D, (0.29±0.17)D, (0.35±0.27)D respectively, and those of the AcrySof calculator group were (0.59±0.46)D, (0.54±0.37)D, (0.64±0.52)D respectively, the differences between the two groups were statistically significant (t=-2.142, -2.038, -2.481, all P<0.05).The difference of X(EV) between the Barrett calculator group and the AcrySof calculator group was statistically significant[-0.13(-0.36-0.80)D vs. 0.19(-1.01-0.71)D, Z=-2.965,P<0.01], and the difference of Y(EV) was statistically significant [-0.02(-0.51-0.64)D vs. -0.15(-0.88-1.10)D, Z=-2.076, P<0.05] at 1 months. There was no significant difference in X(EV) and Y(EV) (both P>0.05) at 3 months. Conelusion: As compared to AcrySof Toric calculator, the application of Barrett calculator in selecting Toric IOL may reduce ERA and improve Toric IOL correction outcomes. (Chin J Ophthalmol, 2019, 55:208-213).

Effect of cyclosporin A particles of varying diameters on gastric cancer cell apoptosis.

Human health is significantly threatened by gastric cancer, which is the most common malignant tumor; although drastic, surgery is currently the only way to cure it. However, high recurrence rates and low survival rates are associated with the disease. Therefore, to improve the effectiveness of gastric cancer treatment and to increase the clinical cure rate, we investigated the effect of cyclosporin A particles of varying diameter on gastric cancer cell apoptosis. Flow cytometry was used to detect apoptosis induced by Annexin V-fluorescein isothiocyanate/propidium iodide-double labeling. We also determined the content of reactive oxygen species and the expression level of P-glycoprotein in cells after treatment with cyclosporin A. The results indicated that increases in the concentration and action time of cyclosporin A were associated with statistically significant increases in the apoptosis rate of gastric cancer cells when the experimental and control groups were compared (P < 0.05 and P < 0.01, respectively). In conclusion, during a certain action time and concentration range, cyclosporin A inhibits the proliferation of human gastric cancer cells and can induce their apoptosis.