Similar Datasets
Project description:Presented is the differential expression of mRNA and miRNA in 44 Stage I and Stage II patients who developed metastasis within 5 years of nephrectomy, compared to 21 patients who remained disease free. Extracted RNA from nephrectomy specimens preserved in FFPE blocks was sequenced using RNAseq. MiRNA expression was done using the TaqMan OpenArray qPCR protocol.
2020-07-28 | GSE155209 | GEO
Project description:Introduction: For patients with localized node-negative (Stage I and II) clear cell renal cell carcinomas (ccRCC), current clinicopathological staging has limited predictive capability because of their low risk. Analyzing molecular signatures at the time of nephrectomy can aid in understanding future metastatic potential. Objective: Develop a molecular signature that can stratify patients who have clinically low risk ccRCC, but have high risk genetic changes driving an aggressive metastatic phenotype. Patients, Materials, and Methods: Presented is the differential expression of mRNA and miRNA in 44 Stage I and Stage II patients, 21 who developed metastasis within 5 years of nephrectomy, compared to 23 patients who remained disease free for more than 5 years. Extracted RNA from nephrectomy specimens preserved in FFPE blocks was sequenced using RNAseq. MiRNA expression was performed using the TaqMan OpenArray qPCR protocol. Results: One hundred thirty one genes and 2 miRNA were differentially expressed between the two groups. Canonical correlation (CC) analysis was applied and four CCs (CC32, CC20, CC9, and CC7) have an AUC > 0.65 in our dataset with similar predictive power in the TCGA-KIRC dataset. Gene set enrichment showed CC9 as kidney development/adhesion, CC20 as oxidative phosphorylation pathway, CC32 as RNA binding/spindle and CC7 as immune response. In a multivariate Cox model, the four CCs were able to identify high/low risk groups for metastases in the TCGA-KIRC (p < 0.05) with odds ratios of CC32 = 5.7, CC20 = 4.4, CC9 = 3.6, and CC7 = 2.7. Conclusion: These results identify molecular signatures for more aggressive tumors in clinically low risk ccRCC patients who have a higher potential of metastasis than would be expected.
| S-EPMC7431518 | biostudies-literature
Project description:Prognostic Molecular Signatures and Biomarkers for Metastatic Progression in Stage I and II Clear Cell Renal Cell Carcinomas
| PRJNA648969 | ENA
Project description:Prognostic Molecular Biomarkers for Metastatic Progression in Stage I and II Clear Cell Renal Cell Carcinomas
| PRJNA648973 | ENA
Project description:Presented is the differential expression of mRNA and miRNA in 44 Stage I and Stage II patients who developed metastasis within 5 years of nephrectomy, compared to 21 patients who remained disease free. Extracted RNA from nephrectomy specimens preserved in FFPE blocks was sequenced using RNAseq. MiRNA expression was done using the TaqMan OpenArray qPCR protocol.
2020-07-27 | GSE143630 | GEO
Project description:Background: Kidney renal clear cell carcinoma (KIRC) is the malignancy originated from the renal epithelium, with a high rate of distant metastasis. Aberrant alternative splicing (AS) of pre-mRNA are widely reported to be involved in the tumorigenesis and metastasis of multiple cancers. The aim of this study is to explore the mechanism of alternative splicing events (ASEs) underlying tumorigenesis and metastasis of KIRC. Methods: RNA-seq of 537 KIRC samples downloaded from the TCGA database and ASEs data from the TCGASpliceSeq database were used to identify ASEs in patients with KIRC. The univariate and Lasso regression analysis were used to screen the most significant overall survival-related ASEs (OS-SEs). Based on those, the OS-SEs model was proposed. The interaction network of OS-SEs and splicing factors (SFs) with absolute value of correlation coefficient value >0.750 was constructed by Pearson correlation analysis. The OS-SEs significantly related to distant metastasis and clinical stage were identified by non-parametric test, and those were also integrated into co-expression analysis with prognosis-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways identified by Gene Set Variation Analysis (GSVA). ASEs with significance were selected for multiple online database validation. Results: A total of prognostic 6,081 overall survival-related ASEs (OS-SEs) were identified by univariate Cox regression analysis and a prediction model was constructed based on 5 OS-SEs screened by Lasso regression with the Area Under Curve of 0.788. Its risk score was also illustrated to be an independent predictor, which the good reliability of the model. Among 390 identified candidate SFs, DExD-Box Helicase 39B (DDX39B) was significantly correlated with OS and metastasis. After external database validation, Retained Intron of Ras Homolog Family Member T2 (RHOT2) and T-Cell Immune Regulator 1 (TCIRG1) were identified. In the co-expression analysis, overlapped co-expression signal pathways for RHOT2 and TCIRG1 were sphingolipid metabolism and N-glycan biosynthesis. Conclusions: Based on the results of comprehensive bioinformatic analysis, we proposed that aberrant DDX39B regulated RHOT2-32938-RI and TCIRG1-17288-RI might be associated with the tumorigenesis, metastasis, and poor prognosis of KIRC via sphingolipid metabolism or N-glycan biosynthesis pathway.
| S-EPMC6803439 | biostudies-literature
Project description:Early-stage (I and II) ovarian carcinoma patients generally have good prognosis. Yet, some patients die earlier than expected. Thus, it is important to stratify early-stage patients into risk groups to identify those in need of more aggressive treatment regimens. The prognostic value of 29 histotype-specific biomarkers identified using RNA sequencing was evaluated for early-stage clear-cell (CCC), endometrioid (EC) and mucinous (MC) ovarian carcinomas (n = 112) using immunohistochemistry on tissue microarrays. Biomarkers with prognostic significance were further evaluated in an external ovarian carcinoma data set using the web-based Kaplan-Meier plotter tool. Here, we provide evidence of aberrant protein expression patterns and prognostic significance of 17 novel histotype-specific prognostic biomarkers [10 for CCC (ARPC2, CCT5, GNB1, KCTD10, NUP155, RPL13A, RPL37, SETD3, SMYD2, TRIO), three for EC (CECR1, KIF26B, PIK3CA), and four for MC (CHEK1, FOXM1, KIF23, PARPBP)], suggesting biological heterogeneity within the histotypes. Combined predictive models comprising the protein expression status of the validated CCC, EC and MC biomarkers together with established clinical markers (age, stage, CA125, ploidy) improved the predictive power in comparison with models containing established clinical markers alone, further strengthening the importance of the biomarkers in ovarian carcinoma. Further, even improved predictive powers were demonstrated when combining these models with our previously identified prognostic biomarkers PITHD1 (CCC) and GPR158 (MC). Moreover, the proteins demonstrated improved risk prediction of CCC-, EC-, and MC-associated ovarian carcinoma survival. The novel histotype-specific prognostic biomarkers may not only improve prognostication and patient stratification of early-stage ovarian carcinomas, but may also guide future clinical therapy decisions.
| S-EPMC7040170 | biostudies-literature
Project description:While the transmembrane glycoprotein mucin 1 (MUC1) is clustered at the apical borders of normal epithelial cells, with transformation and loss of polarity, MUC1 is found at high levels in the cytosol and is uniformly distributed over the entire surface of carcinoma cells, where it can promote tumor progression and adversely affects the response to therapy. Clear cell renal cell carcinoma (ccRCC), the main histotype of kidney cancer, is typically highly resistant to conventional and targeted therapies for reasons that remain largely unknown. In this context, we investigated whether MUC1 also plays a pivotal role in the cellular and molecular events driving ccRCC progression and chemoresistance. We showed, using loss- and gain-of-function approaches in ccRCC-derived cell lines, that MUC1 not only influences tumor progression but also induces a multi-drug-resistant profile reminiscent of the activation of ABC drug efflux transporters. Overall, our results suggest that targeting MUC1 may represent a novel therapeutic approach to limit ccRCC progression and improve drug sensitivity.
| S-EPMC10814283 | biostudies-literature
Project description:Clear cell RCC is the most common, and more likely to metastasize, of the three main histological types of RCC. Pathologic stage is the most important prognostic indicator and nuclear grade can predict outcome within stages of localized RCC. Epithelial tumors are thought to accumulate a series of genetic and epigenetic changes as they progress through well-defined clinical and histopathological changes. MicroRNAs (miRNAs) are involved in the regulation of mRNA expression from many human genes and miRNA expression is dysregulated in cancer. To better understand the contribution of dysregulated miRNA expression to the progression and biology of ccRCC, we examined the differences in expression levels of 723 human miRNAs through a series of analyses by stage, grade, and disease progression status in a large series of 94 ccRCC. We found a consistent signature that included significant upregulation of miR-21-5p, 142-3p, let-7g-5p, let-7i-5p and 424-5p, as well as downregulation of miR-204-5p, to be associated with ccRCC of high stage, or high grade, or progression. Discrete signatures associated with each of stage, grade, or progression were also identified. The let-7 family was significantly downregulated in ccRCC compared with normal renal parenchyma. Expression of the 6 most significantly differentially expressed miRNAs between ccRCC was verified by stem-loop qRT-PCR. Pathways predicted as targets of the most significantly dysregulated miRNAs included signaling, epithelial cancers, metabolism, and epithelial to mesenchymal transition. Our studies help to further elucidate the biology underlying the progression of ccRCC and identify miRNAs for potential translational application.
| S-EPMC3974834 | biostudies-other
Project description:Prognostic Molecular Signatures for Metastatic Potential in Clinically Low-Risk Stage I and II Clear Cell Renal Cell Carcinomas
| PRJNA601152 | ENA