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Abstract
Background
Clear cell renal cell carcinoma (ccRCC) is a dominant subtype of kidney cancer with a dismal outcome at advanced stages. Ataxin 3 (ATXN3) has been proven to play a cancer-promoting role in several tumors and is upregulated in the patients with renal cell carcinoma. Thus, the objective of this research is to examine the biological roles and underlying mechanisms of ATXN3 in ccRCC.
Methods
Bioinformatics analysis was carried out to analyze ATXN3 expression in ccRCC tissues and patient survival. Gain- and loss-of-function assays were applied to explore the effect of ATXN3 on ccRCC cell malignant behavior in vitro. The effect of ATXN3 on the NF-κB pathway was assessed by Western blot and immunofluorescence staining. The binding between ATXN3 and S100A8 and the effect of ATXN3 on S100A8 ubiquitination were verified using coimmunoprecipitation.
Results
ATXN3 was upregulated in ccRCC tissues and correlated with adverse patient outcome. ATXN3 overexpression facilitated the proliferation, stemness, invasion and migratory capacity of ccRCC cells, whereas silencing had the opposite effect. ATXN3 enhanced the activity of the NF-κB pathway. Silencing ATXN3 facilitated S100A8 ubiquitination. Rescue experiments demonstrated that S100A8 downregulation reversed the promoting effect of ATXN3 on malignant behavior and NF-κB pathway activation in ccRCC cells.
Conclusion
ATXN3 exerts a cancer-promoting effect in ccRCC by regulating S100A8 ubiquitination. Therefore, targeting the ATXN3/S100A8/NF-κB axis may provide a novel underlying therapeutic strategy for ccRCC.
Supplementary Materials
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Editor-in-Chief
László ROSIVALL (Semmelweis University, Budapest, Hungary)
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Anna BERHIDI (Semmelweis University, Budapest, Hungary)
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| 2022 | |
|---|---|
| Web of Science | |
| Total Cites WoS |
335 |
| Journal Impact Factor | 1.4 |
| Rank by Impact Factor |
Physiology (Q4) |
| Impact Factor without Journal Self Cites |
1.4 |
| 5 Year Impact Factor |
1.6 |
| Journal Citation Indicator | 0.42 |
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Physiology (Q4) |
| Scimago | |
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33 |
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0.362 |
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Physiology (medical) (Q3) |
| Scopus | |
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2.8 |
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Physiology 68/102 (33rd PCTL) |
| Scopus SNIP |
0.508 |
| 2021 | |
|---|---|
| Web of Science | |
| Total Cites WoS |
330 |
| Journal Impact Factor | 1,697 |
| Rank by Impact Factor |
Physiology 73/81 |
| Impact Factor without Journal Self Cites |
1,697 |
| 5 Year Impact Factor |
1,806 |
| Journal Citation Indicator | 0,47 |
| Rank by Journal Citation Indicator |
Physiology 69/86 |
| Scimago | |
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31 |
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0,32 |
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| Scopus | |
| Scopus Cite Score |
2,7 |
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Physiology (medical) 69/101 (Q3) |
| Scopus SNIP |
0,591 |
| 2020 | |
| Total Cites | 245 |
| WoS | |
| Journal Impact Factor |
2,090 |
| Rank by | Physiology 62/81 (Q4) |
| Impact Factor | |
| Impact Factor | 1,866 |
| without | |
| Journal Self Cites | |
| 5 Year | 1,703 |
| Impact Factor | |
| Journal | 0,51 |
| Citation Indicator | |
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| Citable | 42 |
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| Scimago | 29 |
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| Scimago | Physiology (medical) Q3 |
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| 2019 | |
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137 |
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1,361 |
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1,221 |
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0,294 |
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34 |
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33 |
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1 |
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2,1 |
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9,3 |
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0,00028 |
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0,215 |
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97,06 |
| Normalized Eigenfactor |
0,03445 |
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12,963 |
| Scimago H-index |
27 |
| Scimago Journal Rank |
0,267 |
| Scopus Scite Score |
235/157=1,5 |
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Physiology (medical) 73/99 (Q3) |
| Scopus SNIP |
0,38 |
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