Numerous attempts for detection of circulating tumor cells (CTC) have been made to develop reliable assays for early diagnosis of cancers. In this study, we validated the application of folate receptor α (FRα) as the tumor marker to detect CTC through tumor-specific ligand PCR (LT-PCR) and assessed its utility for diagnosis of bladder transitional cell carcinoma (TCC). Immunohistochemistry for FRα was performed on ten bladder TCC tissues. Enzyme-linked immunosorbent assay (ELISA) for FRα was performed on both urine and serum specimens from bladder TCC patients (n = 64 and n = 20, respectively) and healthy volunteers (n = 20 and n = 23, respectively). Western blot analysis and qRT-PCR were performed to confirm the expression of FRα in bladder TCC cells. CTC values in 3-mL peripheral blood were measured in 57 bladder TCC patients, 48 healthy volunteers, and 15 subjects with benign urologic pathologies by the folate receptor α ligand-targeted PCR. We found that FRα protein was overexpressed in both bladder TCC cells and tissues. The levels of FRα mRNA were also much higher in bladder cancer cell lines 5637 and SW780 than those of leukocyte. Values of FRα were higher in both serum and urine specimens of bladder TCC patients than those of control. CTC values were also higher in 3-mL peripheral blood of bladder TCC patients than those of control (median 26.5 Cu/3 mL vs 14.0 Cu/3 mL). Area under the receiver operating characteristic (ROC) curve for bladder TCC detection was 0.819, 95 % CI (0.738-0.883). At the cutoff value of 15.43 Cu/3 mL, the sensitivity and the specificity for detecting bladder cancer are 82.14 and 61.9 %, respectively. We concluded that quantitation of CTCs through FRα ligand-PCR could be a promising method for noninvasive diagnosis of bladder TCC.
Background: As a common pathological type of lung cancer, lung adenocarcinoma (LUAD) is mainly treated by surgery, chemotherapy, targeted therapy and radiotherapy. Although a relatively mature treatment system has been established, there are few studies on the microenvironment of LUAD. Material and Methods: The immune and stromal scores of patients from the LUAD cohort in the TCGA database were obtained by using ESTIMATE. The relationship of immune and stromal scores with the clinicopathological characteristics and overall survival of LUAD patients was assessed by R. GO, KEGG and Cox regression analyses were employed to analyze intersecting genes and to identify reliable prognostic markers. The identified genes were also analyzed in the GEPIA database to assess their correlations with survival, and these relationships were verified with the Kaplan-Meier Plotter database. Results: The immune score was related to the survival time and tumor topography of LUAD patients. There was a significant correlation between stromal score and tumor metastasis. Through multivariate analysis, stage (HR = 1.640, 95% CI = 1.019-2.642, P = 0.042) and risk score (HR = 1.036, 95% CI = 1.026-1.046, P < 0.001). The genes (ARHGAP15, BTLA, CASS4, CLECL1, FAM129C, STAP1, TESPA1, and S100P) showed credible prognostic value in LUAD patients in TCGA through GEPIA database online analysis and verification in the Kaplan-Meier plotter database. Conclusions: In the microenvironment of lung adenocarcinoma, the differentially expressed genes screened by immune score and stromal score have certain value in evaluating the survival/prognosis of patients, as well as the invasion and progression of tumors.
Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified.Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score.Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups.Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.
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