See the published version of this preprint at Cancer Cell International.
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.
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Primary research
Xiuwei Chen
Harbin Medical University Cancer Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5771-6662
Hang Yin
Tumor Hospital of Harbin Medical University
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis.
Methods: Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan-Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results.
Results: A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan-Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells.
Conclusions: Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.
Keywords
long non-coding RNA, immune, biomarkers, transcription factor, endometrial cancer, The Cancer Genome Atlas
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This is a list of supplementary files associated with this preprint. Click to download.
- 2.5FigureS1formula.tif
Figure S1 The calculation formula of risk score.
- 3.1FigureS2.tif
Figure S2 Identification of immune related and differentially expressed genes associated with overall survival (OS) of EC patients. The forest plot showed 53 out of 410 immune-related DE genes are related to survival.
- 3.5FigureS3.tif
Figure S3 Verification of the signature in the testing set. (a) Kaplan-Meier survival analysis between high- and low-risk groups patients with EC. (b) Receiver operating characteristic (ROC). (c) The distribution of risk score, survival duration and expression profiles of 4-lncRNA in high- and low-risk groups.
- 3.5FigureS4.tif
Figure S4 Verification of the signature in the entire set. (a) Kaplan-Meier survival analysis between high- and low-risk groups patients with EC. (b) Receiver operating characteristic (ROC). (c) The distribution of risk score, survival duration and expression profiles of 4-lncRNA in high- and low-risk groups.
- 3.6FigureS5.tif
Figure S5 Assessment of independent risk factors in training set. (a) Age, grade and risk score were the independent prognostic indicators by univariate analysis. (b) Grade and risk score were the independent prognostic indicators by multivariate analysis. (c) ROC curves showed the predict potential of 4-lncRNA signature.
- 3.6FigureS6.tif
Figure S6 Assessment of independent risk factors in testing set. (a) Grade and risk score were the independent prognostic indicators by univariate analysis. (b) Grade and risk score were the independent prognostic indicators by multivariate analysis. (c) ROC curves showed the predict potential of 4-lncRNA signature.
- FigureS7.tif
Figure S7 Statement on informed consent.
- 2.7TableS1.docx
Table S1 Primers applied in qPCR.
- 3.2TableS2.docx
Table S2 Co-expression analysis of DE TFs and immune-OS-related DE genes. The co-expression analysis result displays that there were interactions between 29 DE TFs and 17 immune-OS-related DE genes.
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CURRENT STATUS: Published
View the published article at Cancer Cell International.
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Posted 18 Sep, 2020
No community comments so far
Editorial decision: Accept
On 22 Sep, 2020
Review #1 received
Received 20 Sep, 2020
Reviewer #2 agreed
On 17 Sep, 2020
Review #2 received
Received 17 Sep, 2020
Reviewers invited
Invitations sent on 16 Sep, 2020
Reviewer #1 agreed
On 16 Sep, 2020
Editor assigned
On 15 Sep, 2020
Submission checks complete
On 14 Sep, 2020
Editor invited
On 14 Sep, 2020
No comments provided
Review #1 received
Received 22 Aug, 2020
Editorial decision: Major revision
On 22 Aug, 2020
Reviewer #2 agreed
On 08 Aug, 2020
Review #2 received
Received 08 Aug, 2020
Reviewers invited
Invitations sent on 07 Aug, 2020
Reviewer #1 agreed
On 07 Aug, 2020
Editor assigned
On 31 Jul, 2020
Submission checks complete
On 30 Jul, 2020
Editor invited
On 30 Jul, 2020
First submitted
On 29 Jul, 2020
Metrics
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PDF Downloads: ...
HTML Views: ...
Subject Areas
Cancer Biology
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See the published version of this preprint at Cancer Cell International.
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
Primary research
Xiuwei Chen
Harbin Medical University Cancer Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5771-6662
Hang Yin
Tumor Hospital of Harbin Medical University
Corresponding Author
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 Cancer Cell International.
Version 2
Posted 18 Sep, 2020
No community comments so far
Editorial decision: Accept
On 22 Sep, 2020
Review #1 received
Received 20 Sep, 2020
Reviewer #2 agreed
On 17 Sep, 2020
Review #2 received
Received 17 Sep, 2020
Reviewers invited
Invitations sent on 16 Sep, 2020
Reviewer #1 agreed
On 16 Sep, 2020
Editor assigned
On 15 Sep, 2020
Submission checks complete
On 14 Sep, 2020
Editor invited
On 14 Sep, 2020
No comments provided
Review #1 received
Received 22 Aug, 2020
Editorial decision: Major revision
On 22 Aug, 2020
Reviewer #2 agreed
On 08 Aug, 2020
Review #2 received
Received 08 Aug, 2020
Reviewers invited
Invitations sent on 07 Aug, 2020
Reviewer #1 agreed
On 07 Aug, 2020
Editor assigned
On 31 Jul, 2020
Submission checks complete
On 30 Jul, 2020
Editor invited
On 30 Jul, 2020
First submitted
On 29 Jul, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cancer Biology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Cancer Cell International.
Background: Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis.
Methods: Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan-Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results.
Results: A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan-Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells.
Conclusions: Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
This is a list of supplementary files associated with this preprint. Click to download.
- 2.5FigureS1formula.tif
Figure S1 The calculation formula of risk score.
- 3.1FigureS2.tif
Figure S2 Identification of immune related and differentially expressed genes associated with overall survival (OS) of EC patients. The forest plot showed 53 out of 410 immune-related DE genes are related to survival.
- 3.5FigureS3.tif
Figure S3 Verification of the signature in the testing set. (a) Kaplan-Meier survival analysis between high- and low-risk groups patients with EC. (b) Receiver operating characteristic (ROC). (c) The distribution of risk score, survival duration and expression profiles of 4-lncRNA in high- and low-risk groups.
- 3.5FigureS4.tif
Figure S4 Verification of the signature in the entire set. (a) Kaplan-Meier survival analysis between high- and low-risk groups patients with EC. (b) Receiver operating characteristic (ROC). (c) The distribution of risk score, survival duration and expression profiles of 4-lncRNA in high- and low-risk groups.
- 3.6FigureS5.tif
Figure S5 Assessment of independent risk factors in training set. (a) Age, grade and risk score were the independent prognostic indicators by univariate analysis. (b) Grade and risk score were the independent prognostic indicators by multivariate analysis. (c) ROC curves showed the predict potential of 4-lncRNA signature.
- 3.6FigureS6.tif
Figure S6 Assessment of independent risk factors in testing set. (a) Grade and risk score were the independent prognostic indicators by univariate analysis. (b) Grade and risk score were the independent prognostic indicators by multivariate analysis. (c) ROC curves showed the predict potential of 4-lncRNA signature.
- FigureS7.tif
Figure S7 Statement on informed consent.
- 2.7TableS1.docx
Table S1 Primers applied in qPCR.
- 3.2TableS2.docx
Table S2 Co-expression analysis of DE TFs and immune-OS-related DE genes. The co-expression analysis result displays that there were interactions between 29 DE TFs and 17 immune-OS-related DE genes.
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