Genome-wide MicroRNA Expression Profiles in COPD: Early Predictors for Cancer Development.
10.1016/j.gpb.2018.06.001
- Author:
Andreas KELLER
1
;
Tobias FEHLMANN
2
;
Nicole LUDWIG
3
;
Mustafa KAHRAMAN
4
,
5
;
Thomas LAUFER
5
,
6
;
Christina BACKES
2
;
Claus VOGELMEIER
7
;
Caroline DIENER
3
;
Frank BIERTZ
8
;
Christian HERR
9
;
Rudolf A JÖRRES
10
;
Hans-Peter LENHOF
11
,
12
;
Eckart MEESE
3
;
Robert BALS
9
;
COSYCONET Study Group
Author Information
1. Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany. Electronic address: andreas.keller@ccb.uni-saarland.de.
2. Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
3. Department of Human Genetics, Saarland University Hospital, 66421 Homburg, Germany.
4. Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
5. Hummingbird Diagnostics GmbH, 69120 Heidelberg, Germany.
6. Department of Human Genetics, Saarland University Hospital, 66421 Homburg, Germany
7. Department of Internal Medicine, Division for Pulmonary Diseases, Philipps University of Marburg, 35043 Marburg, Germany.
8. Institute for Biostatistics, Hannover Medical School, 30625 Hanover, Germany.
9. Department of Internal Medicine V - Pulmonology, Allergology, Intensive Care Medicine, Saarland University Hospital, 66421 Homburg, Germany.
10. Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Comprehensive Pneumology Center Munich (CPC-M), Ludwig-Maximilians-University Munich, Member of the German Center for Lung Research (DZL), 80539 Munich, Germany.
11. Chair for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
12. Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
- Collective Name:COSYCONET Study Group
- Publication Type:Journal Article
- Keywords:
Biomarker;
COPD;
COSYCONET;
Cancer;
Lung;
microRNA
- MeSH:
Aged;
Biomarkers, Tumor;
genetics;
Cohort Studies;
Female;
Gene Expression Profiling;
Genome, Human;
Humans;
Male;
MicroRNAs;
genetics;
Neoplasms;
diagnosis;
etiology;
genetics;
Prognosis;
Pulmonary Disease, Chronic Obstructive;
complications
- From:
Genomics, Proteomics & Bioinformatics
2018;16(3):162-171
- CountryChina
- Language:English
-
Abstract:
Chronic obstructive pulmonary disease (COPD) significantly increases the risk of developing cancer. Biomarker studies frequently follow a case-control set-up in which patients diagnosed with a disease are compared to controls. Longitudinal cohort studies such as the COPD-centered German COPD and SYstemic consequences-COmorbidities NETwork (COSYCONET) study provide the patient and biomaterial base for discovering predictive molecular markers. We asked whether microRNA (miRNA) profiles in blood collected from COPD patients prior to a tumor diagnosis could support an early diagnosis of tumor development independent of the tumor type. From 2741 participants of COSYCONET diagnosed with COPD, we selected 534 individuals including 33 patients who developed cancer during the follow-up period of 54 months and 501 patients who did not develop cancer, but had similar age, gender and smoking history. Genome-wide miRNA profiles were generated and evaluated using machine learning techniques. For patients developing cancer we identified nine miRNAs with significantly decreased abundance (two-tailed unpaired t-test adjusted for multiple testing P < 0.05), including members of the miR-320 family. The identified miRNAs regulate different cancer-related pathways including the MAPK pathway (P = 2.3 × 10). We also observed the impact of confounding factors on the generated miRNA profiles, underlining the value of our matched analysis. For selected miRNAs, qRT-PCR analysis was applied to validate the results. In conclusion, we identified several miRNAs in blood of COPD patients, which could serve as candidates for biomarkers to help identify COPD patients at risk of developing cancer.
