Dataset Information

Transmembrane Transporter Sema3D Serves as a Tumor Suppressor in Localized Clear Cell Renal Cell Carcinoma.

ABSTRACT:

Background

The transmembrane transporter Sema3D is a vital molecule involved in axon guidance and carcinogenesis of variant malignancies. However, the relationship between Sema3D and clear cell renal cell carcinoma (ccRCC) is barely reported and remains unclear.

Methods

Sema3D expression and the connection of clinical and histological characteristics were first analyzed with transcriptome data in the TCGA repository. We then located and examined the Sema3D expression in ccRCC patients by using immunofluorescence staining in the tissue microarray. The prognostic value of Sema3D in localized ccRCC was evaluated by Cox proportional hazard analysis. Functional and gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to describe the potential mechanisms of Sema3D in ccRCC. Correlation analysis between Sema3D and tumor-infiltrating lymphocytes was calculated by ssGSEA.

Results

In 86 ccRCC patients, Sema3D mRNA and protein expression were downregulated in tumor tissues than the para-tumor tissues, and Sema3D was dominantly expressed in the extracellular space. Low expression of Sema3D was associated with advanced tumor stage, advanced histological grade, and poor prognosis in ccRCC. In the subgroup analysis of 81 localized ccRCC patients, Sema3D expression level was an independent protective prognostic factor for overall survival (OS) (HR = 0.125, p=0.043). Coagulation, complement, estrogen response, and KRAS signaling hallmark gene sets were identified as Sema3D-related signaling pathways. The expression level of Sema3D was significantly correlated with a high abundance of several immune cells (neutrophils, eosinophils, and T helper cells).

Conclusions

Transmembrane transporter Sema3D is an efficient prognostic biomarker for localized ccRCC patients, by playing the role of tumor suppressor in ccRCC. Sema3D can be a novel therapeutic target for ccRCC.

SUBMITTER: Xie R

PROVIDER: S-EPMC9262505 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Gene expression signatures have proven to be useful tools in many cancers to identify distinct subtypes of disease based on molecular features that drive pathogenesis, and to aid in predicting clinical outcomes. However, there are no current signatures for kidney cancer that are applicable in a clinical setting.To generate a signature biomarker for the clear cell renal cell carcinoma (ccRCC) good risk (ccA) and poor risk (ccB) subtype classification that could be readily applied to clinical samples to develop an integrated model for biologically defined risk stratification.A set of 72 ccRCC sample standards was used to develop a 34-gene classifier (ClearCode34) for assigning ccRCC tumors to subtypes. The classifier was applied to RNA-sequencing data from 380 nonmetastatic ccRCC samples from the Cancer Genome Atlas (TCGA), and to 157 formalin-fixed clinical samples collected at the University of North Carolina.Kaplan-Meier analyses were performed on the individual cohorts to calculate recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Training and test sets were randomly selected from the combined cohorts to assemble a risk prediction model for disease recurrence.The subtypes were significantly associated with RFS (p<0.01), CSS (p<0.01), and OS (p<0.01). Hazard ratios for subtype classification were similar to those of stage and grade in association with recurrence risk, and remained significant in multivariate analyses. An integrated molecular/clinical model for RFS to assign patients to risk groups was able to accurately predict CSS above established, clinical risk-prediction algorithms.The ClearCode34-based model provides prognostic stratification that improves upon established algorithms to assess risk for recurrence and death for nonmetastatic ccRCC patients.We developed a 34-gene subtype predictor to classify clear cell renal cell carcinoma tumors according to ccA or ccB subtypes and built a subtype-inclusive model to analyze patient survival outcomes.

Project description:The cysteine-serine-rich nuclear protein (CSRNP) family has prognostic value for various cancers. However, the association between this proteins and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to determine the prognostic value of the CSRNP family for patients with ccRCC. Therefore, the gene expression profiling interactive analysis database was used to analyze the mRNA expression of CSRNP family members (CSRNPs) in relation with survival. Combined and independent prognostic values of CSRNPs were evaluated using SurvExpress and multivariate Cox regression analyses, respectively. Potential signaling pathways impacted by CSRNPs were evaluated using Metascape. Associations between the CSRNP family and immunocyte infiltration were determined from single-sample gene set enrichment analysis. Both cBioPortal and MethSurv were used to explore whether genomic and epidemic alterations might influence prognosis. We found that when both CSRNP1 and CSRNP3 had a low expression, patients with ccRCC had a worse overall survival (OS). Therefore, a prognostic signature was constructed as follows: risk score = -0.224 × expmRNA of CSRNP1 + 0.820 × expmRNA of CSRNP2 - 1.428 × expmRNA of CSRNP3 . We found that OS was worse in patients from the high- than from the low-risk groups (AUC = 0.69). Moreover, this signature was an independent predictor after adjusting for clinical features. Functional enrichment analysis positively associated CSRNPs with the acute inflammatory response and humoral immune response pathways. This was validated by correlating each CSRNP with 28 types of immunocytes in tumor and normal tissues. A higher expression of CSRNP1 and CSRNP3 was associated with a better prognosis in both the high- and low-mutant burden groups. Cg19538674, cg07772537, and cg07811002 of CSRNP1, CSRNP2, and CSRNP3, respectively, were the predominant DNA methylation sites affecting OS. The CSRNP gene family signature may serve as a prognostic biomarker for predicting OS in patients with ccRCC. The association between CSRNPs and immune infiltration might offer future clinical treatment options.

Project description:BACKGROUND:We previously showed that the expression of follistatin-like protein 1 (FSTL1) was significantly down-regulated in metastatic clear-cell renal cell carcinoma (ccRCC). In this study, we aimed to characterize the role of FSTL1 in the development of ccRCC. METHODS:The effects of FSTL1 on cell activity and cell cycle were investigated in ccRCC cell lines with altered FSTL1 expression. Gene expression microarray assays were performed to identify the major signaling pathways affected by FSTL1 knockdown. The expression of FSTL1 in ccRCC and its effect on postoperative prognosis were estimated in a cohort with 89 patients. RESULTS:FSTL1 knockdown promoted anchorage-independent growth, migration, invasion, and cell cycle of ccRCC cell lines, whereas FSTL1 overexpression attenuated cell migration. FSTL1 knockdown up-regulated nuclear factor-κB (NF-κB) and hypoxia-inducible factor (HIF) signaling pathways, increased epithelial-to-mesenchymal transition, up-regulated interleukin-6 expression, and promoted tumor necrosis factor-α-induced degradation of NF-κB inhibitor (IκBα) in ccRCC cell lines. FSTL1 immunostaining was selectively positive in epithelial cytoplasm in the loop of Henle, and positive rate of FSTL1 was significantly lower in ccRCC tissues than in adjacent renal tissues (P < 0.001). The multivariate Cox regression analysis showed that the intratumoral FSTL1 expression conferred a favorable independent prognosis with a hazard ratio of 0.325 (95% confidence interval 0.118-0.894). HIF-2α expression was negatively correlated with FSTL1 expression in ccRCC specimens (r = - 0.229, P = 0.044). Intratumoral expression of HIF-2α, rather than HIF-1α, significantly predicted an unfavorable prognosis in ccRCC (log-rank, P = 0.038). CONCLUSIONS:FSTL1 plays a tumor suppression role possibly via repressing the NF-κB and HIF-2α signaling pathways. To increase FSTL1 expression might be a candidate therapeutic strategy for metastatic ccRCC.