RESUMEN
Papillary renal cell carcinoma (PRCC) is a highly heterogeneous cancer, and PRCC patients with advanced/metastatic subgroup showed obviously shorter survival compared to other kinds of renal cell carcinomas. However, the molecular mechanism and prognostic predictors of PRCC remain unclear and are worth deep studying. The aim of this study is to identify novel molecular classification and construct a reliable prognostic model for PRCC. The expression data were retrieved from TCGA, GEO, GTEx and TARGET databases. CRISPR data was obtained from Depmap database. The key genes were selected by the intersection of CRISPR-Cas9 screening genes, differentially expressed genes, and genes with prognostic capacity in PRCC. The molecular classification was identified based on the key genes. Drug sensitivity, tumor microenvironment, somatic mutation, and survival were compared among the novel classification. A prognostic model utilizing multiple machine learning algorithms based on the key genes was developed and tested by independent external validation set. Our study identified three clusters (C1, C2 and C3) in PRCC based on 41 key genes. C2 had obviously higher expression of the key genes and lower survival than C1 and C3. Significant differences in drug sensitivity, tumor microenvironment, and mutation landscape have been observed among the three clusters. By utilizing 21 combinations of 9 machine learning algorithms, 9 out of 41 genes were chosen to construct a robust prognostic signature, which exhibited good prognostic ability. SERPINH1 was identified as a critical gene for its strong prognostic ability in PRCC by univariate and multiple Cox regression analyses. Quantitative real-time PCR and Western blot demonstrated that SERPINH1 mRNA and protein were highly expressed in PRCC cells compared with normal human renal cells. This study exhibited a new molecular classification and prognostic signature for PRCC, which may provide a potential biomarker and therapy target for PRCC patients.
RESUMEN
OBJECTIVE: To evaluate the protective effects of salvianolate on percutaneous coronary intervention (PCI) related myocardial injury or myocardial infarction after elective PCI in non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients. METHODS: A total of 149 patients with NSTE-ACS who underwent elective PCI were enrolled. The patients were randomly allocated in a 1:1 ratio to the salvianolate group (74 cases) or the control group (75 cases). After exclusion criteria of coronary angiography, 60 patients with PCI therapy remained in the salvianolate group and 68 in the control group. The incidence and the severity of PCI related myocardial injury or myocardial infarction, in addition to major adverse cardiac events (MACEs) during 1 year follow-up after PCI were studied between the two groups. Multivariate logistic regression analysis was used to determine the independent factors for PCI related myocardial injury or myocardial infarction after elective PCI. RESULTS: Compared with the control group, salvianolate treatment reduced the incidence of PCI related severe myocardial injury or myocardial infarction (11.7% vs. 26.5%, P=0.035). The rate of MACEs or all-cause death within 1 month or 1 year after the procedure was not significantly different between the two groups. CONCLUSIONS: Periprocedural treatment with salvianolate reduces the incidence of PCI related severe myocardial injury or myocardial infarction, although it does not influence clinical prognosis. [Chinese clinical trial registry: ChiCTR1800016992].