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Construction of a Six Immune-Related lncRNAs Signature to Predict Outcome, Immune Cell Infiltration and Immunotherapy Response in Patients with Hepatocellular Carcinoma
Pengcheng Zhou
Southeast University Medical College
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1477-0586
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors worldwide with poor prognosis. Growing evidence has demonstrated that immune-related long non-coding RNAs (lncRNAs) are relevant to tumor microenvironment (TME) and can help to assess the effects of immunotherapy and evaluate prognosis. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of immunotherapy and prognosis in HCC.
Methods: HCC RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) project database. Firstly, we used ESTIMATE to evaluate the tumor microenvironment (TME). Then, cox regression analysis was used to construct a prognostic signature and the risk score. Univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), the receiver operating characteristic (ROC) curve and stratification analyses were applied to confirm. Gene set enrichment analysis (GSEA) analysis was employed to explore the biological processes and pathways. Besides, CIBERSORT was used to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, the relationship between the immune-related lncRNA signature and immune checkpoint genes was investigated. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays were used to demonstrated the expression of the six lncRNAs.
Results:.
We identified a six immune-related lncRNAs (MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV) with the ability to stratify patients into high-risk and low-risk groups with significantly different survival. Univariate Cox regression, multivariate Cox regression, ROC and stratification analyses confirmed that the six immune-related lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated different distributions in PCA. GSEA suggested that the six immune-related lncRNA signature is involved in the immune-related biological processes and pathways. Besides, the six immune-related lncRNA signature was associated with the infiltration of immune cells. Furthermore, the six immune-related lncRNA signature was associated with the expression of critical immune genes and could predict the clinical response of immunotherapy. Finally, qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell line.
Conclusions: In summary, we identified a six immune-related lncRNA signature with the ability to predict outcome, immune cell infiltration and immunotherapy response in patients with hepatocellular carcinoma.
Keywords
hepatocellular carcinoma, lncRNA, immune, TCGA, risk score, immunotherapy
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This preprint is under consideration at Cancer Cell International. A preprint is 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
Construction of a Six Immune-Related lncRNAs Signature to Predict Outcome, Immune Cell Infiltration and Immunotherapy Response in Patients with Hepatocellular Carcinoma
Pengcheng Zhou
Southeast University Medical College
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1477-0586
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: Under Revision
Version 1
Posted 22 Sep, 2020
No community comments so far
Editorial decision: Major revision
On 12 Jan, 2021
Review #1 received
Received 10 Nov, 2020
Reviewer #1 agreed
On 06 Nov, 2020
Reviewers invited
Invitations sent on 20 Sep, 2020
Editor assigned
On 17 Sep, 2020
First submitted
On 16 Sep, 2020
Submission checks complete
On 16 Sep, 2020
Editor invited
On 16 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors worldwide with poor prognosis. Growing evidence has demonstrated that immune-related long non-coding RNAs (lncRNAs) are relevant to tumor microenvironment (TME) and can help to assess the effects of immunotherapy and evaluate prognosis. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of immunotherapy and prognosis in HCC.
Methods: HCC RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) project database. Firstly, we used ESTIMATE to evaluate the tumor microenvironment (TME). Then, cox regression analysis was used to construct a prognostic signature and the risk score. Univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), the receiver operating characteristic (ROC) curve and stratification analyses were applied to confirm. Gene set enrichment analysis (GSEA) analysis was employed to explore the biological processes and pathways. Besides, CIBERSORT was used to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, the relationship between the immune-related lncRNA signature and immune checkpoint genes was investigated. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays were used to demonstrated the expression of the six lncRNAs.
Results:.
We identified a six immune-related lncRNAs (MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV) with the ability to stratify patients into high-risk and low-risk groups with significantly different survival. Univariate Cox regression, multivariate Cox regression, ROC and stratification analyses confirmed that the six immune-related lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated different distributions in PCA. GSEA suggested that the six immune-related lncRNA signature is involved in the immune-related biological processes and pathways. Besides, the six immune-related lncRNA signature was associated with the infiltration of immune cells. Furthermore, the six immune-related lncRNA signature was associated with the expression of critical immune genes and could predict the clinical response of immunotherapy. Finally, qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell line.
Conclusions: In summary, we identified a six immune-related lncRNA signature with the ability to predict outcome, immune cell infiltration and immunotherapy response in patients with hepatocellular carcinoma.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
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Figure 9
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