|
1
|
AICR, . American Institute for Cancer
Research, World Cancer Research Fund: Lung Cancer Statistics.
https://www.wcrf.org/dietandcancer/cancer-trends/lung-cancer-statistics2018
February. 2019
|
|
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
|
Cronin KA, Lake AJ, Scott S, Sherman RL,
Noone AM, Howlader N, Henley SJ, Anderson RN, Firth AU, Ma J, et
al: Annual report to the nation on the status of cancer, part I:
National cancer statistics. Cancer. 124:2785–2800. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Fitzmaurice C, Akinyemiju TF, Al Lami FH,
Alam T, Alizadeh-Navaei R, Allen C, Alsharif U, Alvis-Guzman N,
Amini E, Anderson BO, et al Global Burden of Disease Cancer
Collaboration, : Global, regional, and national cancer incidence,
mortality, years of life lost, years lived with disability, and
disability-adjusted life-years for 29 cancer groups, 1990 to 2016:
A systematic analysis for the global burden of disease study. JAMA
Oncol. 4:1553–1568. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Pilleron S, Sarfati D, Janssen-Heijnen M,
Vignat J, Ferlay J, Bray F and Soerjomataram I: Global cancer
incidence in older adults, 2012 and 2035: A population-based study.
Int J Cancer. 144:49–58. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
AICR, . American Institute for Cancer
Research, World Cancer Research Fund. Continuous Update Project
Report: Lung Cancer. http://www.aicr.org/continuous-update-project/lung-cancer.html2018
February. 2019
|
|
7
|
Zappa C and Mousa SA: Non-small cell lung
cancer: Current treatment and future advances. Transl Lung Cancer
Res. 5:288–300. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Field RW and Withers BL: Occupational and
environmental causes of lung cancer. Clin Chest Med. 33:681–703.
2012. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Durham AL and Adcock IM: The relationship
between COPD and lung cancer. Lung Cancer. 90:121–127. 2015.
View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Sekine Y, Katsura H, Koh E, Hiroshima K
and Fujisawa T: Early detection of COPD is important for lung
cancer surveillance. Eur Respir J. 39:1230–1240. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Dai J, Yang P, Cox A and Jiang G: Lung
cancer and chronic obstructive pulmonary disease: From a clinical
perspective. Oncotarget. 8:18513–18524. 2017.PubMed/NCBI
|
|
12
|
Ytterstad E, Moe PC and Hjalmarsen A: COPD
in primary lung cancer patients: Prevalence and mortality. Int J
Chron Obstruct Pulmon Dis. 11:625–636. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Vestbo J, Hurd SS, Agustí AG, Jones PW,
Vogelmeier C, Anzueto A, Barnes PJ, Fabbri LM, Martinez FJ,
Nishimura M, et al: Global strategy for the diagnosis, management,
and prevention of chronic obstructive pulmonary disease: GOLD
executive summary. Am J Respir Crit Care Med. 187:347–365. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Chen ZH, Kim HP, Ryter SW and Choi AM:
Identifying targets for COPD treatment through gene expression
analyses. Int J Chron Obstruct Pulmon Dis. 3:359–370. 2008.
View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Morrow JD, Qiu W, Chhabra D, Rennard SI,
Belloni P, Belousov A, Pillai SG and Hersh CP: Identifying a gene
expression signature of frequent COPD exacerbations in peripheral
blood using network methods. BMC Med Genomics. 8:12015. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Raza K: Analysis of microarray data using
artificial intelligence based techniques. In: Computational
Intelligence Applications in Bioinformatics. Dash S and Subudhi B
(eds). IGI Global. (Pennsylvania, PA). 216–239. 2016.
|
|
17
|
Jabeen A, Ahmad N and Raza K: Differential
expression analysis of ZIKV infected human RNA sequence reveals
potential biomarkers. bioRxiv. 4982952018.
|
|
18
|
Raza K: Reconstruction, topological and
gene ontology enrichment analysis of cancerous gene regulatory
network modules. Curr Bioinform. 11:243–258. 2016. View Article : Google Scholar
|
|
19
|
Benjamini Y and Hochberg Y: Controlling
the false discovery rate: A practical and powerful approach to
multiple testing. J R Stat Soc B. 57:289–300. 1995.
|
|
20
|
Anderson SK, Gallinger S, Roder J, Frey J,
Young HA and Ortaldo JR: A cyclophilin-related protein involved in
the function of natural killer cells. Proc Natl Acad Sci USA.
90:542–546. 1993. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Davis TL, Walker JR, Campagna-Slater V,
Finerty PJ, Paramanathan R, Bernstein G, MacKenzie F, Tempel W,
Ouyang H, Lee WH, et al: Structural and biochemical
characterization of the human cyclophilin family of peptidyl-prolyl
isomerases. PLoS Biol. 8:e10004392010. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Weissbach L and Treadwell BV: A
plasminogen-related gene is expressed in cancer cells. Biochem
Biophys Res Commun. 186:1108–1114. 1992. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Renkema GH, Boot RG, Au FL, Donker-Koopman
WE, Strijland A, Muijsers AO, Hrebicek M and Aerts JM:
Chitotriosidase, a chitinase, and the 39-kDa human cartilage
glycoprotein, a chitin-binding lectin, are homologues of family 18
glycosyl hydrolases secreted by human macrophages. Eur J Biochem.
251:504–509. 1998. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Lee CG, Hartl D, Lee GR, Koller B,
Matsuura H, Da Silva CA, Sohn MH, Cohn L, Homer RJ, Kozhich AA, et
al: Role of breast regression protein 39 (BRP-39)/chitinase
3-like-1 in Th2 and IL-13-induced tissue responses and apoptosis. J
Exp Med. 206:1149–1166. 2009. View Article : Google Scholar : PubMed/NCBI
|
