|
1
|
McGuire S: World cancer report 2014.
Geneva, Switzerland: World health organization, international
agency for research on cancer WHO press, 2015. Adv Nutr. 7:418–419.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Hirsch FR and Bunn PA Jr: Progressin
research on screening and genetics in lung cancer. Lancet Respir
Med. 2:19–21. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Travis WD: Update on small cell carcinoma
and its differentiation from squamous cell carcinoma and other
non-small cell carcinomas. Mod Pathol. 25(Suppl 1): S18–S30. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Yoon SM, Shaikh T and Hallman M:
Therapeutic management options for stage III non-small cell lung
cancer. World J Clin Oncol. 8:1–20. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Tian S: Classification and survival
prediction for early-stage lung adenocarcinoma and squamous cell
carcinoma patients. Oncol Lett. 14:5464–5470. 2017.PubMed/NCBI
|
|
6
|
Toyokawa G, Kozuma Y, Matsubara T,
Haratake N, Takamori S, Akamine T, Takada K, Katsura M, Shimokawa
M, Shoji F, et al: Prognostic impact of controlling nutritional
status score in resected lung squamous cell carcinoma. J Thorac
Dis. 9:2942–2951. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Pfeifer G: Defining driver DNA methylation
changes in human cancer. Int J Mol Sci. 19:pii: E1166. 2018.
View Article : Google Scholar
|
|
8
|
Tan SX, Hu RC, Tan YL, Liu JJ and Liu WE:
Promoter methylation-mediated downregulation of PRDM5 contributes
to the development of lung squamous cell carcinoma. Tumour Biol.
35:4509–4516. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Wang W, Qi X and Wu M: Effect of DR4
promoter methylation on the TRAIL-induced apoptosis in lung
squamous carcinoma cell. Oncol Rep. 34:2115–2125. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Zhang W, Cui Q, Qu W, Ding X, Jiang D and
Liu H: TRIM58/cg26157385 methylation is associated with eight
prognostic genes in lung squamous cell carcinoma. Oncol Rep.
40:206–216. 2018.PubMed/NCBI
|
|
11
|
Bhan A, Soleimani M and Mandal SS: Long
noncoding RNA and cancer: A new paradigm. Cancer Res. 77:3965–3981.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Tong J, Ma X, Yu H and Yang J: SNHG15: A
promising cancer-related long noncoding RNA. Cancer Manag Res.
11:5961–5969. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Yao F, Wang Q and Wu Q: The prognostic
value and mechanisms of lncRNA UCA1 in human cancer. Cancer Manag
Res. 11:7685–7696. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Lu T, Wang Y, Chen D, Liu J and Jiao W:
Potential clinical application of lncRNAs in non-small cell lung
cancer. Onco Targets Ther. 11:8045–8052. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Huang GQ, Ke ZP, Hu HB and Gu B:
Co-expression network analysis of long noncoding RNAs (IncRNAs) and
cancer genes revealsSFTA1P and CASC2abnormalities in lung squamous
cell carcinoma. Cancer Biol Ther. 18:115–122. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Li S, Teng Y, Yuan MJ, Ma TT, Ma J and Gao
XJ: A seven long-noncoding RNA signature predicts prognosis of lung
squamous cell carcinoma. Biomark Med. 14:53–63. 2020. View Article : Google Scholar
|
|
17
|
Huang G, Huang Q, Xie Z, Zhou H, Cao J,
Shi L and Yang M: A nine-long non-coding RNA signature for
prognosis prediction of patients with lung squamous cell carcinoma.
Cancer Biomark. 26:239–247. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Li R, Yang YE, Yin YH, Zhang MY, Li H and
Qu YQ: Methylation and transcriptome analysis reveal lung
adenocarcinoma-specific diagnostic biomarkers. J Transl Med.
17:3242019. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Barrett T, Wilhite SE, Ledoux P,
Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH,
Sherman PM, Holko M, et al: NCBI GEO: Archive for functional
genomics data sets-update. Nucleic Acids Res. 41(Database Issue):
D991–D995. 2013. View Article : Google Scholar
|
|
20
|
Sandoval J, Mendez-Gonzalez J, Nadal E,
Chen G, Carmona FJ, Sayols S, Moran S, Heyn H, Vizoso M, Gomez A,
et al: A prognostic DNA methylation signature for stage I
non-small-cell lung cancer. J Clin Oncol. 31:4140–4147. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Yates B, Braschi B, Gray KA, Seal RL,
Tweedie S and Bruford EA: Genenames.orgurisimpleGenenames.org: The HGNC and
VGNC resources in 2017. Nucleic Acids Res. 45(D1): D619–D625. 2017.
View Article : Google Scholar
|
|
22
|
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
|
|
23
|
Law CW, Alhamdoosh M, Su S, Dong X, Tian
L, Smyth GK and Ritchie ME: RNA-seq analysis is easy as 1-2-3 with
limma, Glimma and edgeR. F1000Res. 5:14082016. View Article : Google Scholar
|
|
24
|
Wang L, Cao C, Ma Q, Zeng Q, Wang H, Cheng
Z, Zhu G, Qi J, Ma H, Nian H and Wang Y: RNA-seq analyses of
multiple meri-stems of soybean: Novel and alternative transcripts,
evolutionary and functional implications. BMC Plant Biol.
14:1692014. View Article : Google Scholar
|
|
25
|
Kotthaus H, Korb I, Engel M and Marwedel
P: Dynamic page sharing optimization for the R language. Acm
Sigplan Notices. 50:79–90. 2014. View Article : Google Scholar
|
|
26
|
Kong S and Nan B: Non-asymptotic oracle
inequalities for the high-dimensional Cox regression via lasso.
Stat Sin. 24:25–42. 2012.
|
|
27
|
Goeman JJ: L1 penalized estimation in the
Cox proportional hazards model. Biom J. 52:70–84. 2010.
|
|
28
|
Camp RL, Marisa DF and Rimm DL: X-tile: A
new bio-informatics tool for biomarker assessment and outcome-based
cut-point optimization. Clin Cancer Res. 10:7252–7259. 2004.
View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Liu XR, Pawitan Y and Clements MS:
Generalized survival models for correlated time-to-event data. Stat
Med. 36:4743–4762. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Steyerberg EW and FRANK E HARRELL Jr:
Regression modeling strategies: With applications, to linear
models, logistic and ordinal regression, and survival analysis, 2nd
ed. Heidelberg Springer. Biometrics. 72:1006–1007. 2016. View Article : Google Scholar
|
|
31
|
Subramanian A, Tamayo P, Mootha VK,
Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub
TR, Lander ES and Mesirov JP: Gene set enrichment analysis: A
knowledge-based approach for interpreting genome-wide expression
profiles. Proc Natl Acad Sci USA. 102:15545–15550. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
van den Hoogen C, van der Horst G, Cheung
H, Buijs JT, Lippitt JM, Guzmán-Ramírez N, Hamdy FC, Eaton CL,
Thalmann GN, Cecchini MG, et al: High aldehyde dehydrogenase
activity identifies tumor-initiating and metastasis-initiating
cells in human prostate cancer. Cancer Res. 70:5163–5173. 2010.
View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Giacalone NJ, Den RB, Eisenberg R, Chen H,
Olson SJ, Massion PP, Carbone DP and Lu B: ALDH7A1 expression is
associated with recurrence in patients with surgically resected
non-small-cell lung carcinoma. Future Oncol. 9:737–745. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Hata A, Nakajima T, Matsusaka K, Fukuyo M,
Morimoto J, Yamamoto T, Sakairi Y, Rahmutulla B, Ota S, Wada H, et
al: A low DNA methylation epigenotype in lung squamous cell
carcinoma and its association with idiopathic pulmonary fibrosis
and poorer prognosis. Int J Cancer. 146:388–399. 2020. View Article : Google Scholar
|
|
35
|
Zhu S, Kuek V, Bennett S, Xu H, Rosen V
and Xu J: Protein Cytl1: Its role in chondrogenesis, cartilage
homeostasis, and disease. Cell Mol Life Sci. 76:3515–3523. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Kwon YJ, Lee SJ, Koh JS, Kim SH, Lee HW,
Kang MC, Bae JB, Kim YJ and Park JH: Genome-wide analysis of DNA
methylation and the gene expression change in lung cancer. J Thorac
Oncol. 7:20–33. 2012. View Article : Google Scholar
|
|
37
|
Kim SN, Kim NH, Lee W, Seo DW and Kim YK:
Histone deacetylase inhibitor induction of P-glycoprotein
transcription requires both histone deacetylase 1 dissociation and
recruitment of CAAT/enhancer binding protein beta and pCAF to the
promoter region. Mol Cancer Res. 7:735–744. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Tsai PC, Glastonbury CA, Eliot MN,
Bollepalli S, Yet I, Castillo-Fernandez JE, Carnero-Montoro E,
Hardiman T, Martin TC, Vickers A, et al: Smoking induces
coordinated DNA methylation and gene expression changes in adipose
tissue with consequences for metabolic health. Clin Epigenetics.
10:1262018. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Liu K, Kang M, Li J, Qin W and Wang R:
Prognostic value of the mRNA expression of members of the HSP90
family in non-small cell lung cancer. Exp Ther Med. 17:2657–2665.
2019.PubMed/NCBI
|
|
40
|
Lu C, Chen H, Shan Z and Yang L:
Identification of differentially expressed genes between lung
adenocarcinoma and lung squamous cell carcinoma by gene expression
profiling. Mol Med Rep. 14:1483–1490. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Tian FM, Zhong CY, Wang XN and Meng Y:
PDE3A is hyper-methylated in cisplatin resistant non-small cell
lung cancer cells and is a modulator of chemotherapy response. Eur
Rev Med Pharmacol Sci. 21:2635–2641. 2017.PubMed/NCBI
|
|
42
|
Lee YH, Pang SW and Tan KO: PNMA2 mediates
heterodimeric interactions and antagonizes chemo-sensitizing
activities mediated by members of PNMA family. Biochem Biophys Res
Commun. 473:224–229. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Cui T, Hurtig M, Elgue G, Li SC, Veronesi
G, Essaghir A, Demoulin JB, Pelosi G, Alimohammadi M, Öberg K and
Giandomenico V: Paraneoplastic antigen Ma2 autoantibodies as
specific blood biomarkers for detection of early recurrence of
small intestine neuroendocrine tumors. PLoS One. 5:e160102010.
View Article : Google Scholar
|
|
44
|
Yamada H, Yanagisawa K, Tokumaru S,
Taguchi A, Nimura Y, Osada H, Nagino M and Takahashi T: Detailed
characterization of a homozygously deleted region corresponding to
a candidate tumor suppressor locus at 21q11-21 in human lung
cancer. Genes Chromosomes Cancer. 47:810–818. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Li W, Zhang G, Li X, Wang X, Li Q, Hong L,
Shen Y, Zhao C, Gong X, Chen Y and Zhou J: Thyroid hormone receptor
interactor 13 (TRIP13) overexpression associated with tumor
progression and poor prognosis in lung adenocarcinoma. Biochem
Biophys Res Commun. 499:416–424. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Zhang Y, Xue Q, Pan G, Meng QH, Tuo X, Cai
X, Chen Z, Li Y, Huang T, Duan X and Duan Y: Integrated analysis of
genome-wide copy number alterations and gene expression profiling
of lung cancer in Xuanwei, China. PLoS One. 12:e01690982017.
View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Yao J, Zhang X, Li J, Zhao D, Gao B, Zhou
H, Gao S and Zhang L: Silencing TRIP13 inhibits cell growth and
metastasis of hepatocellular carcinoma by activating of
TGF-β1/smad3. Cancer Cell Int. 18:2082018. View Article : Google Scholar
|
|
48
|
Hu F, Zeng W and Liu X: A gene signature
of survival prediction for kidney renal cell carcinoma by
multi-omic data analysis. Int J Mol Sci. 20:pii: E5720. 2019.
View Article : Google Scholar
|
|
49
|
Liu H and Zhao H: Prognosis related
miRNAs, DNA methylation, and epigenetic interactions in lung
adenocarcinoma. Neoplasma. 66:487–493. 2019. View Article : Google Scholar : PubMed/NCBI
|
