Background: The aim of this study was to determine the prognostic factors associated with survival in patients with ductal carcinoma of the prostate (DAC) and to develop a nomogram model for them that can be individually predicted. Methods: We explored prognostic factors affecting patients with ductal adenocarcinoma of the prostate using univariate and multifactorial COX regression analyses, Kaplan-Meier method, using clinical data from DAC patients collected between 2003-2017 from the Surveillance, Epidemiology and End Results (SEER) database. Nomogram models predicting overall survival in DAC patients were drawn based on the results of the multifactorial analysis, and the discriminatory power and ability of the prediction models were assessed by prediction curves, the area under the curve(AUC) and decision curve analysis (DCA). Results: A total of 834 patients were included in this study and were randomized in a 7:3 ratio into a training cohor (n = 585) and a validation cohor (n = 249). After univariate and multivariate Cox regression analyses, we identified that eight independent risk factors (age, T-stage, N-stage, M-stage, surgery, lymph node dissection, Gleason score, PSA) were identified for patients with DAC, and subsequently the first static and online nomogram for predicting overall survival for patients with DAC were created, respectively. Calibration curves were plotted and found that predicted survival closely matched actual survival, with AUC for the training cohort at 1-, 3-, 5-year being 0.807, 0.841 and 0.850 respectively. Further internal validation was performed and the AUC for the internal Validation cohort were 0.887, 0.848 and 0.817 respectively. The AUC and DCA were better than the TNM system. In addition, our study also found that patients with non-metastatic DAC who underwent the RP surgical approach or surgery combined with lymph node dissection had a better prognosis.Finally patients in the training and validation cohort were divided into high and low risk groups based on nomogram scores. Conclusion:We constructed and validated the first static and online nomogram for predicting patients with DAC. The high predictive accuracy and reliability of this study will help physicians to analyse the prognosis of patients and individualise treatment.
Bladder urothelial carcinoma (BLCA) is the most common malignant tumor of the urinary tract with a high lethality rate, and its immunotherapy resistance and tumor recurrence have become a major challenge in its clinical treatment. G Protein-Coupled Receptors (GPRs) are the largest family of receptors on the cell membrane surface, involved in multiple signaling pathways, and are excellent targets for oncology drug action. The transcriptome profile, single cell transcriptome profile, and clinical data of BLCA were extracted and integrated from TCGA and GEO databases, respectively. The GPR-related genes were obtained from GSEA-MSigDB database. The GPR-related gene signatures of 15 genes were constructed by using the methods of least absolute shrinkage and selection operator regression, multifactor Cox model. At the same time, tumor microenvironment (TME)-score signatures were constructed based on the immune microenvironment of BLCA, and GPR-TME-score signature was further constructed. The stability of this model was verified by using the external dataset GSE160693. We constructed risk groups by combining BLCA patient prognostic information, and with the help of BLCA scRNA transcriptome profiling, we explored differences in prognosis, immune scores, cell–cell interactions, tumor mutational burden, immune checkpoints, and response to immunotherapy in each risk group. We found that the GPR-TME-score signature was an independent prognostic factor for BLCA patients. the TME-score was a protective factor for the prognosis of BLCA patients. Among BLCA patients, GPR-high + TME-low risk group had the worst prognosis, while GPR-high + TME-high risk group had the best prognosis, and the latter had better immune score and immunotherapy response. The above differences in immune response among the subgroups may be related to the higher immune cell infiltration in the GPR-high + TME-high group. GPR-related gene signatures and TME are closely related to BLCA prognosis and immunotherapy, and GPR-related gene signature can be a useful tool to assess BLCA prognosis and immunotherapy response.
Bilateral renal clear cell carcinoma (BRCC) is a rare type of renal cell carcinoma (RCC) that accounts for only 1–5% of RCC cases and has a poor clinical prognosis. The origin, tumor microenvironment, cellular molecular features, and intra-tumoral heterogeneity of BRCC are still unclear. We downloaded BRCC single-cell transcriptome sequencing data from the gene expression omnibus database biochip GSE171306, containing 3,575 cells from left-sided clear cell renal cell carcinoma (ccRCC) and 3,568 cells from right-sided ccRCC, and used a series of R packages for data quality control (QC) and subsequent analysis of BRCC single-cell transcriptome data, including the use of the R packages Seurat and scCancer for cell QC, identification of major cell types, and cell annotation; R package scran for calculation of cell cycle scores; R package infercnv for malignancy scoring of tumor cells; R package ReactomeGSA for functional enrichment analysis; R package Monocle 2 for the analysis of cell differentiation trajectories; and R package CellphoneDB for the analysis of intercellular interactions. In this study, by analyzing the high-quality single-cell transcriptome data of BRCC, we identified 18 cell types and found that left- and right-sided ccRCC were approximately the same in terms of cell type and the number of each cell but differed significantly in terms of tumor cell malignancy score, tumor microenvironment, and cell stemness score. In the cell differentiation trajectory analysis of BRCC, we found that endothelial cells and macrophages play an extremely important role in its tumor progression. Further cell communication analysis was performed, and we found that it may signal through ligand–receptors, such as vascular endothelial growth factor–vascular endothelial growth factor receptor1 (VEGF–VEGFR1), MIF–(CD74-CXCR4), and growth arrest-specific protein 6–AXL, to influence the development of BRCC. The analysis of single-cell transcriptomic data of human BRCC suggests that left- and right-sided ccRCC may be of the same tumor origin, but the left-sided ccRCC is more malignant and has a better immune response.
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