|
1
|
Xu WH, Xu Y, Wang J, Wan FN, Wang HK, Cao
DL, Shi GH, Qu YY, Zhang HL and Ye DW: Prognostic value and immune
infiltration of novel signatures in clear cell renal cell carcinoma
microenvironment. Aging (Albany NY). 11:6999–7020. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Bray F, Ferlay J, Soerjomataram I, Siegel
RL, Torre LA and Jemal A: Global cancer statistics 2018: GLOBOCAN
estimates of incidence and mortality worldwide for 36 cancers in
185 countries. CA Cancer J Clin. 68:394–424. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Siegel RL, Miller KD and Jemal A: Cancer
statistics, 2017. CA Cancer J Clin. 67:7–30. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Butz H, Szabó PM, Nofech-Mozes R, Rotondo
F, Kovacs K, Mirham L, Girgis H, Boles D, Patocs A and Yousef GM:
Integrative bioinformatics analysis reveals new prognostic
biomarkers of clear cell renal cell carcinoma. Clin Chem.
60:1314–1326. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Wang Q, Tang H, Luo X, Chen J, Zhang X, Li
X, Li Y, Chen Y, Xu Y and Han S: Immune-associated gene signatures
serve as a promising biomarker of immunotherapeutic prognosis for
renal clear cell carcinoma. Front Immunol. 13:8901502022.
View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Sacco E, Pinto F, Sasso F, Racioppi M,
Gulino G, Volpe A and Bassi P: Paraneoplastic syndromes in patients
with urological malignancies. Urol Int. 83:1–11. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Flanigan RC, Campbell SC, Clark JI and
Picken MM: Metastatic renal cell carcinoma. Curr Treat Options
Oncol. 4:385–390. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Jonasch E, Walker CL and Rathmell WK:
Clear cell renal cell carcinoma ontogeny and mechanisms of
lethality. Nat Rev Nephrol. 17:245–261. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Ke J, Chen J and Liu X: Analyzing and
validating the prognostic value and immune microenvironment of
clear cell renal cell carcinoma. Anim Cells Syst (Seoul). 26:52–61.
2022. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Lai Y, Tang F, Huang Y, He C, Chen C, Zhao
J, Wu W and He Z: The tumour microenvironment and metabolism in
renal cell carcinoma targeted or immune therapy. J Cell Physiol.
236:1616–1627. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Choueiri TK and Motzer RJ: Systemic
therapy for metastatic renal-cell carcinoma. N Engl J Med.
376:354–366. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Li Z, Xu H, Yu L, Wang J, Meng Q, Mei H,
Cai Z, Chen W and Huang W: Patient-derived renal cell carcinoma
organoids for personalized cancer therapy. Clin Transl Med.
12:e9702022. View
Article : Google Scholar : PubMed/NCBI
|
|
13
|
Stransky L, Cotter K and Forgac M: The
function of V-ATPases in cancer. Physiol Rev. 96:1071–1091. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Gleize V, Boisselier B, Marie Y,
Poëa-Guyon S, Sanson M and Morel N: The renal v-ATPase a4 subunit
is expressed in specific subtypes of human gliomas. Glia.
60:1004–1012. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Cotter K, Stransky L, McGuire C and Forgac
M: Recent insights into the structure, regulation, and function of
the V-ATPases. Trends Biochem Sci. 40:611–622. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Breton S and Brown D: Regulation of
luminal acidification by the V-ATPase. Physiology (Bethesda).
28:318–329. 2013.PubMed/NCBI
|
|
17
|
Sun-Wada GH and Wada Y: Vacuolar-type
proton pump ATPases: Acidification and pathological relationships.
Histol Histopathol. 28:805–815. 2013.PubMed/NCBI
|
|
18
|
Hinton A, Sennoune SR, Bond S, Fang M,
Reuveni M, Sahagian GG, Jay D, Martinez-Zaguilan R and Forgac M:
Function of a subunit isoforms of the V-ATPase in pH homeostasis
and in vitro invasion of MDA-MB231 human breast cancer cells. J
Biol Chem. 284:16400–16408. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Sennoune SR, Bakunts K, Martínez GM,
Chua-Tuan JL, Kebir Y, Attaya MN and Martínez-Zaguilán R: Vacuolar
H+-ATPase in human breast cancer cells with distinct
metastatic potential: Distribution and functional activity. Am J
Physiol Cell Physiol. 286:C1443–C1452. 2004. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Lu X, Qin W, Li J, Tan N, Pan D, Zhang H,
Xie L, Yao G, Shu H, Yao M, et al: The growth and metastasis of
human hepatocellular carcinoma xenografts are inhibited by small
interfering RNA targeting to the subunit ATP6L of proton pump.
Cancer Res. 65:6843–6849. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Su K, Collins MP, McGuire CM, Alshagawi
MA, Alamoudi MK, Li Z and Forgac M: Isoform a4 of the vacuolar
ATPase a subunit promotes 4T1-12B breast cancer cell-dependent
tumor growth and metastasis in vivo. J Biol Chem. 298:1023952022.
View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Gumz ML, Zou H, Kreinest PA, Childs AC,
Belmonte LS, LeGrand SN, Wu KJ, Luxon BA, Sinha M, Parker AS, et
al: Secreted frizzled-related protein 1 loss contributes to tumor
phenotype of clear cell renal cell carcinoma. Clin Cancer Res.
13:4740–4749. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Tun HW, Marlow LA, von Roemeling CA,
Cooper SJ, Kreinest P, Wu K, Luxon BA, Sinha M, Anastasiadis PZ and
Copland JA: Pathway signature and cellular differentiation in clear
cell renal cell carcinoma. PLoS One. 5:e106962010. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Jones J, Otu H, Spentzos D, Kolia S, Inan
M, Beecken WD, Fellbaum C, Gu X, Joseph M, Pantuck AJ, et al: Gene
signatures of progression and metastasis in renal cell cancer. Clin
Cancer Res. 11:5730–5739. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Brannon AR, Reddy A, Seiler M, Arreola A,
Moore DT, Pruthi RS, Wallen EM, Nielsen ME, Liu H, Nathanson KL, et
al: Molecular stratification of clear cell renal cell carcinoma by
consensus clustering reveals distinct subtypes and survival
patterns. Genes Cancer. 1:152–163. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Valletti A, Gigante M, Palumbo O, Carella
M, Divella C, Sbisà E, Tullo A, Picardi E, D'Erchia AM, Battaglia
M, et al: Genome-wide analysis of differentially expressed genes
and splicing isoforms in clear cell renal cell carcinoma. PLoS One.
8:e784522013. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Wotschofsky Z, Gummlich L, Liep J, Stephan
C, Kilic E, Jung K, Billaud JN and Meyer HA: Integrated microRNA
and mRNA signature associated with the transition from the locally
confined to the metastasized clear cell renal cell carcinoma
exemplified by miR-146-5p. PLoS One. 11:e01487462016. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Gerlinger M, Horswell S, Larkin J, Rowan
AJ, Salm MP, Varela I, Fisher R, McGranahan N, Matthews N, Santos
CR, et al: Genomic architecture and evolution of clear cell renal
cell carcinomas defined by multiregion sequencing. Nat Genet.
46:225–233. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
von Roemeling CA, Radisky DC, Marlow LA,
Cooper SJ, Grebe SK, Anastasiadis PZ, Tun HW and Copland JA:
Neuronal pentraxin 2 supports clear cell renal cell carcinoma by
activating the AMPA-selective glutamate receptor-4. Cancer Res.
74:4796–4810. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW,
Shi W and Smyth GK: limma powers differential expression analyses
for RNA-sequencing and microarray studies. Nucleic Acids Res.
43:e472015. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
R Core Team, . R: A language and
environment for statistical computing. R Foundation for Statistical
Computing Vienna, Austria: ISBN 3-900051-07-0. 2012, http://www.R-project.org/
|
|
32
|
Kolde R, Laur S, Adler P and Vilo J:
Robust rank aggregation for gene list integration and
meta-analysis. Bioinformatics. 28:573–580. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Huang da W, Sherman BT and Lempicki RA:
Systematic and integrative analysis of large gene lists using DAVID
bioinformatics resources. Nat Protoc. 4:44–57. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Huang da W, Sherman BT and Lempicki RA:
Bioinformatics enrichment tools: Paths toward the comprehensive
functional analysis of large gene lists. Nucleic Acids Res.
37:1–13. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Szklarczyk D, Morris JH, Cook H, Kuhn M,
Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, et al:
The STRING database in 2017: Quality-controlled protein-protein
association networks, made broadly accessible. Nucleic Acids Res.
45:D362–D368. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Shannon P, Markiel A, Ozier O, Baliga NS,
Wang JT, Ramage D, Amin N, Schwikowski B and Ideker T: Cytoscape: A
software environment for integrated models of biomolecular
interaction networks. Genome Res. 13:2498–2504. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Chin CH, Chen SH, Wu HH, Ho CW, Ko MT and
Lin CY: cytoHubba: Identifying hub objects and sub-networks from
complex interactome. BMC Syst Biol. 8 (Suppl 4):S112014. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Livak KJ and Schmittgen TD: Analysis of
relative gene expression data using real-time quantitative PCR and
the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001.
View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Joeckel E, Haber T, Prawitt D, Junker K,
Hampel C, Thüroff JW, Roos FC and Brenner W: High calcium
concentration in bones promotes bone metastasis in renal cell
carcinomas expressing calcium-sensing receptor. Mol Cancer.
13:422014. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Rasti A, Abolhasani M, Zanjani LS, Asgari
M, Mehrazma M and Madjd Z: Reduced expression of CXCR4, a novel
renal cancer stem cell marker, is associated with high-grade renal
cell carcinoma. J Cancer Res Clin Oncol. 143:95–104. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Zhang Y, Zhu X, Qiao X, Sun L, Xia T and
Liu C: Clinical implications of HSC70 expression in clear cell
renal cell carcinoma. Int J Med Sci. 18:239–244. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Luo Y, Shen D, Chen L, Wang G, Liu X, Qian
K, Xiao Y, Wang X and Ju L: Identification of 9 key genes and small
molecule drugs in clear cell renal cell carcinoma. Aging (Albany
NY). 11:6029–6052. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Du GW, Yan X, Chen Z, Zhang RJ, Tuoheti K,
Bai XJ, Wu HH and Liu TZ: Identification of transforming growth
factor beta induced (TGFBI) as an immune-related prognostic factor
in clear cell renal cell carcinoma (ccRCC). Aging (Albany NY).
12:8484–8505. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Cui T, Guo J and Sun Z: A computational
prognostic model of lncRNA signature for clear cell renal cell
carcinoma with genome instability. Expert Rev Mol Diagn.
22:213–222. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Yap NY, Ong TA, Pailoor J, Gobe G and
Rajandram R: The significance of CD14 in clear cell renal cell
carcinoma progression and survival prognosis. Biomarkers. 28:24–31.
2023. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Smith AN, Borthwick KJ and Karet FE:
Molecular cloning and characterization of novel tissue-specific
isoforms of the human vacuolar H(+)-ATPase C, G and d subunits, and
their evaluation in autosomal recessive distal renal tubular
acidosis. Gene. 297:169–177. 2002. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Nishisho T, Hata K, Nakanishi M, Morita Y,
Sun-Wada GH, Wada Y, Yasui N and Yoneda T: The a3 isoform vacuolar
type H+-ATPase promotes distant metastasis in the mouse
B16 melanoma cells. Mol Cancer Res. 9:845–855. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Avnet S, Di Pompo G, Lemma S, Salerno M,
Perut F, Bonuccelli G, Granchi D, Zini N and Baldini N: V-ATPase is
a candidate therapeutic target for Ewing sarcoma. Biochim Biophys
Acta. 1832:1105–1016. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Xu J, Xie R, Liu X, Wen G, Jin H, Yu Z,
Jiang Y, Zhao Z, Yang Y, Ji B, et al: Expression and functional
role of vacuolar H(+)-ATPase in human hepatocellular carcinoma.
Carcinogenesis. 33:2432–2440. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Lu Q, Lu S, Huang L, Wang T, Wan Y, Zhou
CX, Zhang C, Zhang Z and Li X: The expression of V-ATPase is
associated with drug resistance and pathology of non-small-cell
lung cancer. Diagn Pathol. 8:1452013. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Kulshrestha A, Katara GK, Ibrahim S,
Pamarthy S, Jaiswal MK, Gilman Sachs A and Beaman KD: Vacuolar
ATPase ‘a2’ isoform exhibits distinct cell surface accumulation and
modulates matrix metalloproteinase activity in ovarian cancer.
Oncotarget. 6:3797–3810. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Huang L, Lu Q, Han Y, Li Z, Zhang Z and Li
X: ABCG2/V-ATPase was associated with the drug resistance and tumor
metastasis of esophageal squamous cancer cells. Diagn Pathol.
7:1802012. View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Michel V, Licon-Munoz Y, Trujillo K,
Bisoffi M and Parra KJ: Inhibitors of vacuolar ATPase proton pumps
inhibit human prostate cancer cell invasion and prostate-specific
antigen expression and secretion. Int J Cancer. 132:E1–E10. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Chung C, Mader CC, Schmitz JC, Atladottir
J, Fitchev P, Cornwell ML, Koleske AJ, Crawford SE and Gorelick F:
The vacuolar-ATPase modulates matrix metalloproteinase isoforms in
human pancreatic cancer. Lab Invest. 91:732–743. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Cotter K, Capecci J, Sennoune S, Huss M,
Maier M, Martinez-Zaguilan R and Forgac M: Activity of plasma
membrane V-ATPases is critical for the invasion of MDA-MB231 breast
cancer cells. J Biol Chem. 290:3680–3692. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
56
|
Forgac M: Vacuolar ATPases: Rotary proton
pumps in physiology and pathophysiology. Nat Rev Mol Cell Biol.
8:917–929. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
McGuire C, Cotter K, Stransky L and Forgac
M: Regulation of V-ATPase assembly and function of V-ATPases in
tumor cell invasiveness. Biochim Biophys Acta. 1857:1213–1218.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Schneider LS, von Schwarzenberg K, Lehr T,
Ulrich M, Kubisch-Dohmen R, Liebl J, Trauner D, Menche D and
Vollmar AM: Vacuolar-ATPase inhibition blocks iron metabolism to
mediate therapeutic effects in breast cancer. Cancer Res.
75:2863–2874. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
59
|
Schempp CM, von Schwarzenberg K, Schreiner
L, Kubisch R, Müller R, Wagner E and Vollmar AM: V-ATPase
inhibition regulates anoikis resistance and metastasis of cancer
cells. Mol Cancer Ther. 13:926–937. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
60
|
Wiedmann RM, von Schwarzenberg K,
Palamidessi A, Schreiner L, Kubisch R, Liebl J, Schempp C, Trauner
D, Vereb G, Zahler S, et al: The V-ATPase-inhibitor archazolid
abrogates tumor metastasis via inhibition of endocytic activation
of the Rho-GTPase Rac1. Cancer Res. 72:5976–5987. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
61
|
Kubisch R, Fröhlich T, Arnold GJ,
Schreiner L, von Schwarzenberg K, Roidl A, Vollmar AM and Wagner E:
V-ATPase inhibition by archazolid leads to lysosomal dysfunction
resulting in impaired cathepsin B activation in vivo. Int J Cancer.
134:2478–2488. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
62
|
Capecci J and Forgac M: The function of
vacuolar ATPase (V-ATPase) a subunit isoforms in invasiveness of
MCF10a and MCF10CA1a human breast cancer cells. J Biol Chem.
288:32731–32741. 2013. View Article : Google Scholar : PubMed/NCBI
|
