|
1
|
Chen W, Zheng R, Baade PD, Zhang S, Zeng
H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China,
2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Asghar K, Farooq A, Zulfiqar B and Rashid
MU: Indoleamine 2,3-dioxygenase: As a potential prognostic marker
and immunotherapeutic target for hepatocellular carcinoma. World J
Gastroenterol. 23:2286–2293. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Ruan H, Wang T, Yang C, Jin G, Gu D, Deng
X, Wang C, Qin W and Jin H: Co-expression of LASS2 and TGF-β1
predicts poor prognosis in hepatocellular carcinoma. Sci Rep.
6:324212016. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Thomas MB and Zhu AX: Hepatocellular
carcinoma: The need for progress. J Clin Oncol. 23:2892–2899. 2005.
View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Lou J, Zhang L, Lv S, Zhang C and Jiang S:
Biomarkers for hepatocellular carcinoma. Biomark Cancer. 9:1–9.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Tateyama M, Yatsuhashi H, Taura N,
Motoyoshi Y, Nagaoka S, Yanagi K, Abiru S, Yano K, Komori A, Migita
K, et al: Alpha-fetoprotein above normal levels as a risk factor
for the development of hepatocellular carcinoma in patients
infected with hepatitis C virus. J Gastroenterol. 46:92–100. 2011.
View Article : Google Scholar : PubMed/NCBI
|
|
7
|
He B, Yin J, Gong S, Gu J, Xiao J, Shi W,
Ding W and He Y: Bioinformatics analysis of key genes and pathways
for hepatocellular carcinoma transformed from cirrhosis. Medicine
(Baltimore). 96:e69382017. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Wang Z, Gerstein M and Snyder M: RNA-Seq:
A revolutionary tool for transcriptomics. Nat Rev Genet. 10:57–63.
2009. View
Article : Google Scholar : PubMed/NCBI
|
|
9
|
Nagalakshmi U, Waern K and Snyder M:
RNA-Seq: A method for comprehensive transcriptome analysis. Curr
Protoc Mol Biol Chapter. 4:Unit 4.11.1–13. 2010.
|
|
10
|
Zhang C, Peng L, Zhang Y, Liu Z, Li W,
Chen S and Li G: The identification of key genes and pathways in
hepatocellular carcinoma by bioinformatics analysis of
high-throughput data. Med Oncol. 34:1012017. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Ye ZH, Gao L, Wen DY, He Y, Pang YY and
Chen G: Diagnostic and prognostic roles of IRAK1 in hepatocellular
carcinoma tissues: An analysis of immunohistochemistry and
RNA-sequencing data from the cancer genome atlas. Onco Targets
Ther. 10:1711–1723. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
He R, Gao L, Ma J, Peng Z, Zhou S, Yang L,
Feng Z, Dang Y and Chen G: The essential role of MTDH in the
progression of HCC: A study with immunohistochemistry, TCGA,
meta-analysis and in vitro investigation. Am J Transl Res.
9:1561–1579. 2017.PubMed/NCBI
|
|
13
|
Peng L, Yuan XQ, Zhang CY, Ye F, Zhou HF,
Li WL, Liu ZY, Zhang YQ, Pan X and Li GC: High TGF-β1 expression
predicts poor disease prognosis in hepatocellular carcinoma
patients. Oncotarget. 8:34387–34397. 2017.PubMed/NCBI
|
|
14
|
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
|
|
15
|
Zhang X, Ye ZH, Liang HW, Ren FH, Li P,
Dang YW and Chen G: Down-regulation of miR-146a-5p and its
potential targets in hepatocellular carcinoma validated by a TCGA-
and GEO-based study. FEBS Open Bio. 7:504–521. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Li G, Zhong Y, Shen Q, Zhou Y, Deng X, Li
C, Chen J, Zhou Y and He M: NEK2 serves as a prognostic biomarker
for hepatocellular carcinoma. Int J Oncol. 50:405–413. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Ho DW, Kai AK and Ng IO: TCGA
whole-transcriptome sequencing data reveals significantly
dysregulated genes and signaling pathways in hepatocellular
carcinoma. Front Med. 9:322–330. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Komatsu H, Iguchi T, Masuda T, Hirata H,
Ueda M, Kidogami S, Ogawa Y, Sato K, Hu Q, Nambara S, et al:
Attenuated RND1 expression confers malignant phenotype and predicts
poor prognosis in hepatocellular carcinoma. Ann Surg Oncol.
24:850–859. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Wang J, Zhang SM, Wu JM, Lu ZC, Yang JR,
Wu HS, Chen H, Lin B, Xu RH and Cao TS: Mastermind-like
transcriptional coactivator 1 overexpression predicts poor
prognosis in human with hepatocellular carcinoma. Ann Clin Lab Sci.
46:502–507. 2016.PubMed/NCBI
|
|
20
|
Blednov YA, Benavidez JM, Black M, Leiter
CR, Osterndorff-Kahanek E, Johnson D, Borghese CM, Hanrahan JR,
Johnston GA, Chebib M and Harris RA: GABAA receptors containing ρ1
subunits contribute to in vivo effects of ethanol in mice. PLoS
One. 9:e855252014. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Xuei X, Flury-Wetherill L, Dick D, Goate
A, Tischfield J, Nurnberger J Jr, Schuckit M, Kramer J, Kuperman S,
Hesselbrock V, et al: GABRR1 and GABRR2, encoding the GABA-A
receptor subunits rho1 and rho2, are associated with alcohol
dependence. Am J Med Genet B Neuropsychiatr Genet. 153B:418–427.
2010. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Oczko-Wojciechowska M, Włoch J, Wiench M,
Fujarewicz K, Simek K, Gala G, Gubała E, Szpak-Ulczok S and Jarzab
B: Gene expression profile of medullary thyroid
carcinoma-preliminary results. Endokrynol Pol. 57:420–426. 2006.(In
Polish). PubMed/NCBI
|
|
23
|
Xu X, Chang X, Li Z, Wang J, Deng P, Zhu
X, Liu J, Zhang C, Chen S and Dai D: Aberrant SOX11 promoter
methylation is associated with poor prognosis in gastric cancer.
Cell Oncol (Dordr). 38:183–194. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Zhang S, Li S and Gao JL: Promoter
methylation status of the tumor suppressor gene SOX11 is associated
with cell growth and invasion in nasopharyngeal carcinoma. Cancer
Cell Int. 13:1092013. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Yang Z, Jiang S, Lu C, Ji T, Yang W, Li T,
Lv J, Hu W, Yang Y and Jin Z: SOX11: Friend or foe in tumor
prevention and carcinogenesis? Ther Adv Med Oncol.
11:17588359198534492019. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Shepherd JH, Uray IP, Mazumdar A,
Tsimelzon A, Savage M, Hilsenbeck SG and Brown PH: The SOX11
transcription factor is a critical regulator of basal-like breast
cancer growth, invasion, and basal-like gene expression.
Oncotarget. 7:13106–13121. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Makoukji J, Makhoul NJ, Khalil M, El-Sitt
S, Aldin ES, Jabbour M, Boulos F, Gadaleta E, Sangaralingam A,
Chelala C, et al: Gene expression profiling of breast cancer in
Lebanese women. Sci Rep. 6:366392016. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Walter RF, Mairinger FD, Werner R, Ting S,
Vollbrecht C, Theegarten D, Christoph DC, Zarogoulidis K, Schmid
KW, Zarogoulidis P and Wohlschlaeger J: SOX4, SOX11 and PAX6 mRNA
expression was identified as a (prognostic) marker for the
aggressiveness of neuroendocrine tumors of the lung by using
next-generation expression analysis (NanoString). Future Oncol.
11:1027–1036. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Matsuo N, Tanaka S, Yoshioka H, Koch M,
Gordon MK and Ramirez F: Collagen XXIV (Col24a1) gene expression is
a specific marker of osteoblast differentiation and bone formation.
Connect Tissue Res. 49:68–75. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Misawa K, Kanazawa T, Imai A, Endo S,
Mochizuki D, Fukushima H, Misawa Y and Mineta H: Prognostic value
of type XXII and XXIV collagen mRNA expression in head and neck
cancer patients. Mol Clin Oncol. 2:285–291. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Soung YH, Lee JW, Kim SY, Nam SW, Park WS,
Lee JY, Yoo NJ and Lee SH: Mutational analysis of the kinase domain
of MYLK2 gene in common human cancers. Pathol Res Pract.
202:137–140. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Phelps DL, Borley JV, Flower KJ, Dina R,
Darb-Esfahani S, Braicu I, Sehouli J, Fotopoulou C,
Wilhelm-Benartzi CS, Gabra H, et al: Methylation of MYLK3 gene
promoter region: A biomarker to stratify surgical care in ovarian
cancer in a multicentre study. Br J Cancer. 116:1287–1293. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Li L, Lu J, Xue W, Wang L, Zhai Y, Fan Z,
Wu G, Fan F, Li J, Zhang C, et al: Target of obstructive sleep
apnea syndrome merge lung cancer: Based on big data platform.
Oncotarget. 8:21567–21578. 2017.PubMed/NCBI
|
|
34
|
Laenen G, Thorrez L, Börnigen D and Moreau
Y: Finding the targets of a drug by integration of gene expression
data with a protein interaction network. Mol Biosyst. 9:1676–1685.
2013. View Article : Google Scholar : PubMed/NCBI
|
