Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Cancer Cell International
Published in: Cancer Cell International 1/2020

Open Access 01-12-2020 | Primary research

Abnormal expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma based on data mining

Authors: Taotao Liang, Siyao Sang, Qi Shao, Chen Chen, Zhichao Deng, Ting Wang, Qiaozhen Kang

Published in: Cancer Cell International | Issue 1/2020

Login to get access

Abstract

Background

EPB41L1 gene (erythrocyte membrane protein band 4.1 like 1) encodes the protein 4.1N, a member of 4.1 family, playing a vital role in cell adhesion and migration, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma (KIRC) remain to be investigated.

Methods

In this study, we collected the mRNA expression of EPB41L1 in KIRC through the Oncomine platform, and used the HPA database to perform the pathological tissue immunohistochemistry in patients. Then, the sub-groups and prognosis of KIRC were performed by UALCAN and GEPIA web-tool, respectively. Further, the mutation of EPB41L1 in KIRC was analyzed by c-Bioportal. The co-expression genes of EPB41L1 in KIRC were displayed from the LinkedOmics database, and function enrichment analysis was used by LinkFinder module in LinkedOmics. The function of EPB41L1 in cell adhesion and migration was confirmed by wound healing assay using 786-O cells in vitro. Co-expression gene network was constructed through the STRING database, and the MCODE plug-in of which was used to build the gene modules, both of them was visualized by Cytoscape software. Finally, the top modular genes in the same patient cohort were constructed through data mining in TCGA by using the UCSC Xena browser.

Results

The results indicated that EPB41L1 was down-expressed in KIRC, leading to a poor prognosis. Moreover, there is a mutation in the FERM domain of EPB41L1, but it has no significant effect on the prognosis of KIRC. The co-expressed genes of EPB41L1 were associated with cell adhesion and confirmed in vitro. Further analysis suggested that EPB41L1 and amyloid beta precursor protein (APP) were coordinated to regulated cancer cell adhesion, thereby increasing the incidence of cancer cell metastasis and tumor invasion.

Conclusions

In summary, EPB41L1 is constantly down-expressed in KIRC tissues, resulting a poor prognosis. Therefore, we suggest that it can be an effective biomarker for the diagnosis of KIRC.
Appendix
Available only for authorised users
Literature
1.
Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010;127(12):2893–917.CrossRef
2.
Motzer RJ, Bander NH, Nanus DM. Renal-cell carcinoma. N Engl J Med. 1996;335(12):865–75.CrossRef
3.
Zhao H, Cao Y, Wang Y, Zhang L, Chen C, Wang Y, Lu X, Liu S, Yan F. Dynamic prognostic model for kidney renal clear cell carcinoma (KIRC) patients by combining clinical and genetic information. Sci Rep. 2018;8(1):17613.CrossRef
4.
Conboy J, Kan YW, Shohet SB, Mohandas N. Molecular cloning of protein 4.1, a major structural element of the human erythrocyte membrane skeleton. Proc Natl Acad Sci USA. 1986;83(24):9512–6.CrossRef
5.
Parra M, Gascard P, Walensky LD, Gimm JA, Blackshaw S, Chan N, Takakuwa Y, Berger T, Lee G, Chasis JA, et al. Molecular and functional characterization of protein 4.1B, a novel member of the protein 4.1 family with high level, focal expression in brain. J Biol Chem. 2000;275(5):3247–55.CrossRef
6.
Parra M, Gascard P, Walensky LD, Snyder SH, Mohandas N, Conboy JG. Cloning and characterization of 4.1G (EPB41L2), a new member of the skeletal protein 4.1 (EPB4.1) gene family. Genomics. 1998;49(2):298–306.CrossRef
7.
Walensky LD, Blackshaw S, Liao D, Watkins CC, Weier HU, Parra M, Huganir RL, Conboy JG, Mohandas N, Snyder SH. A novel neuron-enriched homolog of the erythrocyte membrane cytoskeletal protein 4.1. J Neurosci. 1999;19(15):6457–67.CrossRef
8.
Ji Z, Shi X, Liu X, Shi Y, Zhou Q, Liu X, Li L, Ji X, Gao Y, Qi Y, et al. The membrane-cytoskeletal protein 4.1N is involved in the process of cell adhesion, migration and invasion of breast cancer cells. Exp Ther Med. 2012;4(4):736–40.CrossRef
9.
Xi C, Ren C, Hu A, Lin J, Yao Q, Wang Y, Gao Z, An X, Liu C. Defective expression of Protein 4.1N is correlated to tumor progression, aggressive behaviors and chemotherapy resistance in epithelial ovarian cancer. Gynecol Oncol. 2013;131(3):764–71.CrossRef
10.
Zhang L, Hu A, Li M, Zhang H, Ren C, An X, Liu C. 4.1N suppresses hypoxia-induced epithelial-mesenchymal transition in epithelial ovarian cancer cells. Mol Med Rep. 2016;13(1):837–44.CrossRef
11.
Nagata M, Sakurai-Yageta M, Yamada D, Goto A, Ito A, Fukuhara H, Kume H, Morikawa T, Fukayama M, Homma Y, et al. Aberrations of a cell adhesion molecule CADM4 in renal clear cell carcinoma. Int J Cancer. 2012;130(6):1329–37.CrossRef
12.
Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, Barrette T, Pandey A, Chinnaiyan AM. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia. 2004;6(1):1–6.CrossRef
13.
Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson A, Kampf C, Sjostedt E, Asplund A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347(6220):1260419.CrossRef
14.
Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98–102.CrossRef
15.
Chandrashekar DS, Bashel B, Balasubramanya S, Creighton CJ, Ponce-Rodriguez I, Chakravarthi B, Varambally S. UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia. 2017;19(8):649–58.CrossRef
16.
Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, Sun Y, Jacobsen A, Sinha R, Larsson E, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6(269):l1.CrossRef
17.
Vasaikar SV, Straub P, Wang J, Zhang B. LinkedOmics: analyzing multi-omics data within and across 32 cancer types. Nucleic Acids Res. 2018;46(D1):D956–63.CrossRef
18.
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30.CrossRef
19.
The Gene Ontology (GO) project in 2006. Nucleic Acids Res. 2006; 34(Database issue):D322-D326.
20.
Zweig AS, Karolchik D, Kuhn RM, Haussler D, Kent WJ. UCSC genome browser tutorial. Genomics. 2008;92(2):75–84.CrossRef
21.
Casper J, Zweig AS, Villarreal C, Tyner C, Speir ML, Rosenbloom KR, Raney BJ, Lee CM, Lee BT, Karolchik D, et al. The UCSC Genome Browser database: 2018 update. Nucleic Acids Res. 2018;46(D1):D762–9.CrossRef
22.
Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Lin J, Minguez P, Bork P, von Mering C, et al. STRING v91: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 2013;41:D808–15.CrossRef
23.
Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics. 2011;27(3):431–2.CrossRef
24.
Chen W, Hill H, Christie A, Kim MS, Holloman E, Pavia-Jimenez A, Homayoun F, Ma Y, Patel N, Yell P, et al. Targeting renal cell carcinoma with a HIF-2 antagonist. Nature. 2016;539(7627):112–7.CrossRef
25.
Bergers G, Hanahan D. Modes of resistance to anti-angiogenic therapy. Nat Rev Cancer. 2008;8(8):592–603.CrossRef
26.
Chaffer CL, Weinberg RA. A perspective on cancer cell metastasis. Science. 2011;331(6024):1559–64.CrossRef
27.
Campbell S, Uzzo RG, Allaf ME, Bass EB, Cadeddu JA, Chang A, Clark PE, Davis BJ, Derweesh IH, Giambarresi L, et al. Renal Mass and Localized Renal Cancer: AUA Guideline. J Urol. 2017;198(3):520–9.CrossRef
28.
Ji SQ, Su XL, Cheng WL, Zhang HJ, Zhao YQ, Han ZX. Down-regulation of CD74 inhibits growth and invasion in clear cell renal cell carcinoma through HIF-1alpha pathway. Urol Oncol. 2014;32(2):153–61.CrossRef
29.
Muller UC, Zheng H. Physiological functions of APP family proteins. Cold Spring Harb Perspect Med. 2012;2(2):a6288.CrossRef
30.
Nguyen KV, Leydiker K, Wang R, Abdenur J, Nyhan WL. A neurodevelopmental disorder with a nonsense mutation in the Ox-2 antigen domain of the amyloid precursor protein (APP) gene. Nucleosides Nucleotides Nucleic Acids. 2017;36(5):317–27.PubMed
31.
Sokol DK, Maloney B, Long JM, Ray B, Lahiri DK. Autism, Alzheimer disease, and fragile X: APP, FMRP, and mGluR5 are molecular links. Neurology. 2011;76(15):1344–52.CrossRef
32.
Stanga S, Brambilla L, Tasiaux B, Dang AH, Ivanoiu A, Octave JN, Rossi D, van Pesch V, Kienlen-Campard P. A Role for GDNF and Soluble APP as biomarkers of amyotrophic lateral sclerosis pathophysiology. Front Neurol. 2018;9:384.CrossRef
33.
Gehrmann J, Banati RB, Cuzner ML, Kreutzberg GW, Newcombe J. Amyloid precursor protein (APP) expression in multiple sclerosis lesions. Glia. 1995;15(2):141–51.CrossRef
34.
Masters CL, Beyreuther K. Alzheimer’s centennial legacy: prospects for rational therapeutic intervention targeting the Abeta amyloid pathway. Brain. 2006;129(Pt 11):2823–39.CrossRef
35.
Sobol A, Galluzzo P, Weber MJ, Alani S, Bocchetta M. Depletion of Amyloid Precursor Protein (APP) causes G0 arrest in non-small cell lung cancer (NSCLC) cells. J CELL PHYSIOL. 2015;230(6):1332–41.CrossRef
36.
Galvao FJ, Grokoski KC, Da SB, Lamers ML, Siqueira IR. The amyloid precursor protein (APP) processing as a biological link between Alzheimer’s disease and cancer. Ageing Res Rev. 2019;49:83–91.CrossRef
37.
Wu X, Chen S, Lu C. Amyloid precursor protein promotes the migration and invasion of breast cancer cells by regulating the MAPK signaling pathway. Int J Mol Med. 2020;45(1):162–74.PubMed
Metadata
Title
Abnormal expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma based on data mining
Authors
Taotao Liang
Siyao Sang
Qi Shao
Chen Chen
Zhichao Deng
Ting Wang
Qiaozhen Kang
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2020
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-020-01449-8

Other articles of this Issue 1/2020

Cancer Cell International 1/2020 Go to the issue

Primary research

Clinicopathological and prognostic significance of nestin expression in patients with breast cancer: a systematic review and meta-analysis

Primary research

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

Primary research

DNA methylation data-based molecular subtype classification and prediction in patients with gastric cancer

Primary research

M2 bone marrow-derived macrophage-derived exosomes shuffle microRNA-21 to accelerate immune escape of glioma by modulating PEG3

Correction

Correction to: The m6A eraser FTO facilitates proliferation and migration of human cervical cancer cells

Review

Autophagy regulation using luteolin: new insight into its anti-tumor activity
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits