1
|
Sanchez DJ and Simon MC: Genetic and
metabolic hallmarks of clear cell renal cell carcinoma. Biochim
Biophys Acta Rev Cancer. 1870:23–31. 2018. View Article : Google Scholar : PubMed/NCBI
|
2
|
Guo K, Chen Q, He X, Yao K, Li Z, Liu Z,
Chen J, Liu Z, Guo C, Lu J, et al: Expression and significance of
Cystatin-C in clear cell renal cell carcinoma. Biomed Pharmacother.
107:1237–1245. 2018. View Article : Google Scholar : PubMed/NCBI
|
3
|
Weng WH, Chen YT, Yu KJ, Chang YH, Chuang
CK and Pang ST: Genetic alterations of her genes in chromophobe
renal cell carcinoma. Oncol Lett. 11:2111–2116. 2016. View Article : Google Scholar : PubMed/NCBI
|
4
|
Noguchi G, Tsutsumi S, Yasui M, Ohtake S,
Umemoto S, Nakaigawa N, Yao M and Kishida T: Significant response
to nivolumab for metastatic chromophobe renal cell carcinoma with
sarcomatoid differentiation: A case report. BMC Urol. 18:262018.
View Article : Google Scholar : PubMed/NCBI
|
5
|
Drendel V, Heckelmann B, Schell C, Kook L,
Biniossek ML, Werner M, Jilg CA and Schilling O: Proteomic
distinction of renal oncocytomas and chromophobe renal cell
carcinomas. Clin Proteomics. 15:252018. View Article : Google Scholar : PubMed/NCBI
|
6
|
He HT, Xu M, Kuang Y, Han XY, Wang MQ and
Yang Q: Biomarker and competing endogenous RNA potential of
tumor-specific long noncoding RNA in chromophobe renal cell
carcinoma. Onco Targets Ther. 9:6399–6406. 2016. View Article : Google Scholar : PubMed/NCBI
|
7
|
Casuscelli J, Weinhold N, Gundem G, Wang
L, Zabor EC, Drill E, Wang PI, Nanjangud GJ, Redzematovic A,
Nargund AM, et al: Genomic landscape and evolution of metastatic
chromophobe renal cell carcinoma. JCI Insight. 2:926882017.
View Article : Google Scholar : PubMed/NCBI
|
8
|
Vastrad C and Vastrad B: Bioinformatics
analysis of gene expression profiles to diagnose crucial and novel
genes in glioblastoma multiform. Pathol Res Pract. 214:1395–1461.
2018. View Article : Google Scholar : PubMed/NCBI
|
9
|
Li L, Cai S, Liu S, Feng H and Zhang J:
Bioinformatics analysis to screen the key prognostic genes in
ovarian cancer. J Ovarian Res. 10:272017. View Article : Google Scholar : PubMed/NCBI
|
10
|
Cao L, Chen Y, Zhang M, Xu D, Liu Y, Liu
T, Liu SX and Wang P: Identification of hub genes and potential
molecular mechanisms in gastric cancer by integrated bioinformatics
analysis. PeerJ. 6:e51802018. View Article : Google Scholar : PubMed/NCBI
|
11
|
Wang Y, Zhang Y, Huang Q and Li C:
Integrated bioinformatics analysis reveals key candidate genes and
pathways in breast cancer. Mol Med Rep. 17:8091–8100.
2018.PubMed/NCBI
|
12
|
Yusenko MV, Zubakov D and Kovacs G: Gene
expression profiling of chromophobe renal cell carcinomas and renal
oncocytomas by Affymetrix GeneChip using pooled and individual
tumours. Int J Biol Sci. 29:517–527. 2009. View Article : Google Scholar
|
13
|
Yusenko MV, Ruppert T and Kovacs G:
Analysis of differentially expressed mitochondrial proteins in
chromophobe renal cell carcinomas and renal oncocytomas by 2-D gel
electrophoresis. Int J Biol Sci. 6:213–224. 2010. View Article : Google Scholar : PubMed/NCBI
|
14
|
Jones J, Out 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
|
15
|
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
|
16
|
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong
S, Kong L, Gao G, Li CY and Wei L: Kobas 2.0: A web server for
annotation and identification of enriched pathways and diseases.
Nucleic Acids Res 39 (Web Server Issue). W316–W322. 2011.
View Article : Google Scholar
|
17
|
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
|
18
|
Chandrashekar DS, Bashel B, Balasubramanya
SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi BVSK and
Varambally S: UALCAN: A portal for facilitating tumor subgroup gene
expression and survival analyses. Neoplasia. 19:649–658. 2017.
View Article : Google Scholar : PubMed/NCBI
|
19
|
Zang Y, Gu L, Zhang Y, Wang Y and Xue F:
Identification of key genes and pathways in uterine leiomyosarcoma
through bioinformatics analysis. Oncol Lett. 15:9361–9368.
2018.PubMed/NCBI
|
20
|
Zhu N, Hou J, Wu Y, Li G, Liu J, Ma G,
Chen B and Song Y: Identification of key genes in rheumatoid
arthritis and osteoarthritis based on bioinformatics analysis.
Medicine (Baltimore). 97:e109972018. View Article : Google Scholar : PubMed/NCBI
|
21
|
Marech I, Ammendola M, Leporini C, Patruno
R, Luposella M, Zizzo N, Passantino G, Sacco R, Farooqi AA, Zuccalà
V, et al: C-kit receptor and tryptase expressing mast cells
correlate with angiogenesis in breast cancer patients. Oncotarget.
9:7918–7927. 2018. View Article : Google Scholar : PubMed/NCBI
|
22
|
Pai T, Bal M, Shetty O, Gurav M, Ostwal V,
Ramaswamy A, Ramadwar M and Desai S: Unraveling the spectrum of kit
mutations in gastrointestinal stromal tumors: An Indian tertiary
cancer center experience. South Asian J Cancer. 6:113–117. 2017.
View Article : Google Scholar : PubMed/NCBI
|
23
|
Ji S, Zhang B, Liu J, Qin Y, Liang C, Shi
S, Jin K, Liang D, Xu W, Xu H, et al: ALDOA functions as an
oncogene in the highly metastatic pancreatic cancer. Cancer Lett.
374:127–135. 2016. View Article : Google Scholar : PubMed/NCBI
|
24
|
Mlakar V, Berginc G, Volavsek M, Stor Z,
Rems M and Glavac D: Presence of activating KRAS mutations
correlates significantly with expression of tumour suppressor genes
DCN and TPM1 in colorectal cancer. BMC Cancer. 9:2822009.
View Article : Google Scholar : PubMed/NCBI
|
25
|
Katsura M, Shoji F, Okamoto T, Shimamatsu
S, Hirai F, Toyokawa G, Morodomi Y, Tagawa T, Oda Y and Maehara Y:
Correlation between CXCR4/CXCR7/CXCL12 chemokine axis expression
and prognosis in lymph-node-positive lung cancer patients. Cancer
Sci. 109:154–165. 2018. View Article : Google Scholar : PubMed/NCBI
|
26
|
Tang YA, Chen CH, Sun HS, Cheng CP, Tseng
VS, Hsu HS, Su WC, Lai WW and Wang YC: Global Oct4 target gene
analysis reveals novel downstream PTEN and TNC genes required for
drug-resistance and metastasis in lung cancer. Nucleic Acids Res.
43:1593–1608. 2015. View Article : Google Scholar : PubMed/NCBI
|
27
|
Wang X, Zhang L, Li H, Sun W, Zhang H and
Lai M: THBS2 is a potential prognostic biomarker in colorectal
cancer. Sci Rep. 6:333662016. View Article : Google Scholar : PubMed/NCBI
|
28
|
Tu Z, Chen Q, Zhang JT, Jiang X, Xia Y and
Chan HC: CFTR is a potential marker for nasopharyngeal carcinoma
prognosis and metastasis. Oncotarget. 7:76955–76965. 2016.
View Article : Google Scholar : PubMed/NCBI
|
29
|
Xia X, Wang J, Liu Y and Yue M: Lower
cystic fibrosis transmembrane conductance regulator (CFTR) promotes
the proliferation and migration of endometrial carcinoma. Med Sci
Monit. 23:966–974. 2017. View Article : Google Scholar : PubMed/NCBI
|
30
|
Oh IH, Oh C, Yoon TY, Choi JM, Kim SK,
Park HJ, Eun YG, Chung DH, Kwon KH and Choe BK: Association of CFTR
gene polymorphisms with papillary thyroid cancer. Oncol Lett.
3:455–461. 2012. View Article : Google Scholar : PubMed/NCBI
|
31
|
Qiao D, Yi L, Hua L, Xu Z, Ding Y, Shi D,
Ni L, Song N, Wang Y and Wu H: Cystic fibrosis transmembrane
conductance regulator (CFTR) gene 5t allele may protect against
prostate cancer: A case-control study in chinese han population. J
Cyst Fibros. 7:210–214. 2008. View Article : Google Scholar : PubMed/NCBI
|
32
|
Xu J, Yong M, Li J, Dong X, Yu T, Fu X and
Hu L: High level of CFTR expression is associated with tumor
aggression and knockdown of CFTR suppresses proliferation of
ovarian cancer in vitro and in vivo. Oncol Rep.
33:2227–2234. 2015. View Article : Google Scholar : PubMed/NCBI
|
33
|
Peng X, Wu Z, Yu L, Li J, Xu W, Chan HC,
Zhang Y and Hu L: Overexpression of cystic fibrosis transmembrane
conductance regulator (CFTR) is associated with human cervical
cancer malignancy, progression and prognosis. Gynecol Oncol.
125:470–476. 2012. View Article : Google Scholar : PubMed/NCBI
|
34
|
Li W, Wang C, Peng X, Zhang H, Huang H and
Liu H: CFTR inhibits the invasion and growth of esophageal cancer
cells by inhibiting the expression of NF-κB. Cell Biol Int.
42:1680–1687. 2018. View Article : Google Scholar : PubMed/NCBI
|
35
|
Than BL, Linnekamp JF, Starr TK,
Largaespada DA, Rod A, Zhang Y, Bruner V, Abrahante J, Schumann A,
Luczak T, et al: CFTR is a tumor suppressor gene in murine and
human intestinal cancer. Oncogene. 35:4179–4187. 2016. View Article : Google Scholar : PubMed/NCBI
|
36
|
Son JW, Kim YJ, Cho HM, Lee SY, Lee SM,
Kang JK, Lee JU, Lee YM, Kwon SJ, Choi E, et al: Promoter
hypermethylation of the CFTR, gene and clinical/pathological
features associated with non-small cell lung cancer. Respirology.
16:1203–1209. 2011. View Article : Google Scholar : PubMed/NCBI
|