Genome‐scale analysis to identify prognostic markers and predict the survival of lung adenocarcinoma. Issue 11 (13th August 2018)
- Record Type:
- Journal Article
- Title:
- Genome‐scale analysis to identify prognostic markers and predict the survival of lung adenocarcinoma. Issue 11 (13th August 2018)
- Main Title:
- Genome‐scale analysis to identify prognostic markers and predict the survival of lung adenocarcinoma
- Authors:
- Li, Yan‐Yan
Yang, Chun
Zhou, Pingting
Zhang, Shijie
Yao, Yuan
Li, Dong - Abstract:
- Abstract: Lung cancer is one of the most malignant cancers worldwide, and lung adenocarcinoma (LAC) remains the most common histologic subtype. However, the functional significance of RNA expression–based prognosis prediction in LAC is still unclear and needs to be further studied. By utilizing the Cox multivariate regression, we established a risk score staging system to predict the outcome of patients with LAC and subsequently identified 10 genes, including PTPRH, OGFRP1, LDHA, AL365203.1, LINC02178, AL512488.1, LINC01312, AL353746.1, DRAXINP1, and LINC02310, which were closely related to the prognosis of patients with LAC. The identified genes allowed us to classify patients into high‐risk group with poor outcome and low‐risk group with better outcome. Compared with other clinical factors, the risk score performs better in predicting the outcome of LAC patients. We used Gene‐Set Enrichment Analysis to identify the differences between the 2 groups in biological pathways. In conclusion, we identified 10 genes by utilizing Cox regression model and developed a risk staging model for LAC, which might prove significant for the clinical management of LAC patients. Abstract : We have identified 9 genes associated with survival of lung adenocarcinoma (LAC) patients using the Cox regression model. Further analysis revealed that the 10‐gene signature could be an independent factor predicting the prognosis of the LAC patients.
- Is Part Of:
- Journal of cellular biochemistry. Volume 119:Issue 11(2018)
- Journal:
- Journal of cellular biochemistry
- Issue:
- Volume 119:Issue 11(2018)
- Issue Display:
- Volume 119, Issue 11 (2018)
- Year:
- 2018
- Volume:
- 119
- Issue:
- 11
- Issue Sort Value:
- 2018-0119-0011-0000
- Page Start:
- 8909
- Page End:
- 8921
- Publication Date:
- 2018-08-13
- Subjects:
- Cox regression model -- lung adenocarcinoma -- prognostic signature -- The Cancer Genome Atlas
Cytochemistry -- Periodicals
572 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-4644 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jcb.27144 ↗
- Languages:
- English
- ISSNs:
- 0730-2312
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4955.010000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23720.xml