Significance of amyloid A immunoexpression in the prognosis of renal cell carcinoma

Identification of Prognostic Markers of DNA Damage and Oxidative Stress in Diagnosing Papillary Renal Cell Carcinoma Based on High-Throughput Bioinformatics Screening

Purpose

Papillary renal cell carcinoma (pRCC) is the second most common histological subtype of adult kidney tumors, with a poor prognosis due to limited understanding of the disease mechanism. Herein, we have performed high-throughput bioinformatic screening to explore and identify potential biomarkers of DNA damage and oxidative stress for pRCC.

Methods

RNA sequencing data related to pRCC were downloaded from the TCGA database, and differentially expressed genes (DEG) were identified by a wide variety of clustering and classification algorithms, including self-organized maps (SOM), artificial neural networks (ANN), support vector machines (SVM), fuzzy logic, and hyphenated techniques such as neuro-fuzzy networks. Then DAVID and STRING online biological information tools were used to analyze functional enrichment of the regulatory networks of DEG and construct a protein-protein interaction (PPI) network, and then the Cytoscape software was used to identify hub genes. The importance of key genes was assessed by the analysis of the Kaplan-Meier survival curves using the R software. Lastly, we have analyzed the expression of hub genes of DNA damage and oxidative stress (BDKRB1, NMUR2, PMCH, and SAA1) in pRCC tissues and adjacent normal tissues, as well as the relationship between the expression of hub genes in pRCC tissues and pathological characteristics and prognosis of pRCC patients.

Results

A total of 1,992 DEGs for pRCC were identified, with 1,142 upregulated ones and 850 downregulated ones. The DEGs were significantly enriched in activities including DNA damage and oxidative stress, chemical synaptic transmission, an integral component of the membrane, calcium ion binding, and neuroactive ligand-receptor interaction. cytoHubba in the Cytoscape software was used to determine the top 10 hub genes in the PPI network as BDKRB2, NMUR2, NMU, BDKRB1, LPAR5, KNG1, LPAR3, SAA1, MCHR1, PMCH, and NCAPH. Furthermore, the expression level of hub genes BDKRB1, NMUR2, PMCH, and SAA1 in pRCC tissues was significantly higher than that in the adjacent normal tissues. Meanwhile, the expression level of hub genes BDKRB1, NMUR2, PMCH, and SAA1 in pRCC tissues was significantly positively correlated with tumor stage, lymph node metastasis, and the histopathology grade of pRCC. In addition, high expression levels of hub genes BDKRB1, NMUR2, PMCH, and SAA1 were associated with a poor prognosis for patients with pRCC. Univariate and multivariate analyses showed that the expression of hub genes BDKRB1, NMUR2, PMCH, and SAA1 were independent risk factors for the prognosis of patients with pRCC.

Conclusion

The results of this analysis suggested that BDKRB1, NMUR2, PMCH, and SAA1 might be potential prognostic biomarkers and novel therapeutic targets for pRCC.

Serum amyloid A protein in cancer prognosis: a meta-analysis and systematic review

Background

Published studies showed divergent results of the prognostic value of serum amyloid A protein (SAA) in patients with different cancers. Therefore, we conducted this meta-analysis so as to assess the association between SAA and cancer prognosis.

Methods

A comprehensive search was conducted to identify the literatures working over SAA and survival in patients with cancers published until January 2020. Sufficient data for assessing overall survival in cancers were extracted descriptively and quantitatively from the studies and a pooled odds ratio was calculated using the Mantel-Haenszel fixed-effect or random-effect model.

Results

Ten eligible papers were identified by two reviewers independently, including 4 studies that evaluated renal cell carcinoma (RCC), 2 studies evaluated lung cancer and the other 3 studies evaluated melanoma, gastric cancer and different cancers. Elevated SAA expression and shorter overall survival (OS) had a statistically significant relation [pooled 1-year OR was 5.07, 95% confidence interval (CI), 3.71–6.94, Q=9.15, I²=0%; pooled 3-year OR was 4.21, 95% CI, 3.18–5.56, Q=14.94, I²=46%; pooled 5-year OR was 5.69, 95% CI, 2.66–12.18, Q=24.83, I²=80%]. Subgroup analysis of RCC patients showed remarkable association between SAA and shorter OS (pooled 1-year OR =4.76, 95% CI, 3.00–7.56, Q=4.18, I²=4%; pooled 3-year OR =4.89, 95% CI, 3.06–7.81, Q=2.88, I²=0%).

Conclusions

High SAA status is correlated with an unfavorable OS in different cancers, especially in RCC, and digestive cancer.

Beta-1,4-galactosyltransferase II predicts poor prognosis of patients with non-metastatic clear-cell renal cell carcinoma

Beta-1,4-galactosyltransferase II is found to be associated with the alterations of tumor-related glycosylation. However, the clinical significance of beta-1,4-galactosyltransferase II in non-metastatic clear-cell renal cell carcinoma has not been reported up to now. Herein, our researches suggested that the expression level of beta-1,4-galactosyltransferase II was first found to be positively associated with tumor size, Fuhrman grade, lymphovascular invasion, rhabdoid differentiation, tumor necrosis and poor overall survival and recurrence-free survival of patients with non-metastatic clear-cell renal cell carcinoma, both in training set and validation set. Moreover, beta-1,4-galactosyltransferase II expression was identified as an independent adverse prognosticator for overall survival and recurrence-free survival of patients with non-metastatic clear-cell renal cell carcinoma. Ultimately, prognostic accuracy of the nomogram integrating beta-1,4-galactosyltransferase II with other independent prognostic parameters was dramatically improved for overall survival and recurrence-free survival of patients with non-metastatic clear-cell renal cell carcinoma. Taken together, beta-1,4-galactosyltransferase II is a potential independent adverse prognostic factor for postoperative recurrence and survival, which could be developed as a useful biomarker for non-metastatic clear-cell renal cell carcinoma by a series of further independent and retrospective studies, so as to help the postsurgical management of clear-cell renal cell carcinoma patients.