See the published version of this preprint at Journal of Translational Medicine.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research
HUI-YUN WANG
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6728-4376
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is sub-optimal in terms of predicting survival outcomes in patients with non-small lung carcinoma (NSCLC).Thus, the aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information in combination with the TNM system.
Methods: Patients with NSCLC were recruited from a hospital and divided into a discovery cohort (n=194) and validation cohort (n=172), and detected using a custom lncRNA microarray. Lung tissues obtained from patients at a different hospital (n = 73, independent validation cohort) were examined via qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program and used to identify those associated with survival in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort.
Results: In the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent cohort. Moreover, multivariate Cox analysis demonstrates that the 4-LncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts.
Conclusions: In this study, we identified a 4-lncRNA signature that can potentially serve as a powerful prognosis biomarker and can provide additional survival information to the traditional TNM staging system.
Keywords
Non-small cell lung cancer（NSCLC）; long non-coding RNA (lncRNA) ; signature; prognosis; TNM stage
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
This is a list of supplementary files associated with this preprint. Click to download.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Journal of Translational Medicine.
Version 2
Posted 07 Jul, 2020
No community comments so far
Editorial decision: Minor revision
On 01 Aug, 2020
Review #3 received
Received 20 Jul, 2020
Review #1 received
Received 14 Jul, 2020
Reviewer #3 agreed
On 13 Jul, 2020
Reviewer #2 agreed
On 10 Jul, 2020
Review #2 received
Received 10 Jul, 2020
Reviewer #1 agreed
On 08 Jul, 2020
Reviewers invited
Invitations sent on 07 Jul, 2020
Editor assigned
On 03 Jul, 2020
Submission checks complete
On 02 Jul, 2020
Editor invited
On 02 Jul, 2020
No comments provided
Editorial decision: Major revision
On 04 Jun, 2020
Review #3 received
Received 04 Jun, 2020
Reviewer #3 agreed
On 03 Jun, 2020
Review #2 received
Received 27 May, 2020
Review #1 received
Received 14 May, 2020
Reviewers invited
Invitations sent on 12 May, 2020
Reviewer #1 agreed
On 12 May, 2020
Reviewer #2 agreed
On 12 May, 2020
Editor assigned
On 28 Apr, 2020
Editor invited
On 27 Apr, 2020
Submission checks complete
On 23 Apr, 2020
First submitted
On 22 Apr, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Translational Medicine
Learn more about our company.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at Journal of Translational Medicine.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
HUI-YUN WANG
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6728-4376
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Journal of Translational Medicine.
Version 2
Posted 07 Jul, 2020
No community comments so far
Editorial decision: Minor revision
On 01 Aug, 2020
Review #3 received
Received 20 Jul, 2020
Review #1 received
Received 14 Jul, 2020
Reviewer #3 agreed
On 13 Jul, 2020
Reviewer #2 agreed
On 10 Jul, 2020
Review #2 received
Received 10 Jul, 2020
Reviewer #1 agreed
On 08 Jul, 2020
Reviewers invited
Invitations sent on 07 Jul, 2020
Editor assigned
On 03 Jul, 2020
Submission checks complete
On 02 Jul, 2020
Editor invited
On 02 Jul, 2020
No comments provided
Editorial decision: Major revision
On 04 Jun, 2020
Review #3 received
Received 04 Jun, 2020
Reviewer #3 agreed
On 03 Jun, 2020
Review #2 received
Received 27 May, 2020
Review #1 received
Received 14 May, 2020
Reviewers invited
Invitations sent on 12 May, 2020
Reviewer #1 agreed
On 12 May, 2020
Reviewer #2 agreed
On 12 May, 2020
Editor assigned
On 28 Apr, 2020
Editor invited
On 27 Apr, 2020
Submission checks complete
On 23 Apr, 2020
First submitted
On 22 Apr, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Translational Medicine
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Journal of Translational Medicine.
Background: Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is sub-optimal in terms of predicting survival outcomes in patients with non-small lung carcinoma (NSCLC).Thus, the aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information in combination with the TNM system.
Methods: Patients with NSCLC were recruited from a hospital and divided into a discovery cohort (n=194) and validation cohort (n=172), and detected using a custom lncRNA microarray. Lung tissues obtained from patients at a different hospital (n = 73, independent validation cohort) were examined via qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program and used to identify those associated with survival in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort.
Results: In the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent cohort. Moreover, multivariate Cox analysis demonstrates that the 4-LncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts.
Conclusions: In this study, we identified a 4-lncRNA signature that can potentially serve as a powerful prognosis biomarker and can provide additional survival information to the traditional TNM staging system.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
This is a list of supplementary files associated with this preprint. Click to download.
Loading...