Title:Developing a RiskScore Model based on Angiogenesis-related
lncRNAs for Colon Adenocarcinoma Prognostic Prediction
Volume: 31
Issue: 17
Author(s): Xianguo Li, Junping Lei, Yongping Shi, Zuojie Peng, Minmin Gong*Xiaogang Shu*
Affiliation:
- Department of General Surgery, Xiangyang No.1 People's
Hospital, Hubei University of Medicine, Xiangyang, 441021, China
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of
Science and Technology, Wuhan, 430014, China
Keywords:
Colon adenocarcinoma, angiogenesis-related lncRNAs, RiskScore model, prognosis, drug sensitivity, immune microenvironment.
Abstract:
Aim: We screened key angiogenesis-related lncRNAs based on colon adenocarcinoma
(COAD) to construct a RiskScore model for predicting COAD prognosis and help reveal the
pathogenesis of the COAD as well as optimize clinical treatment.
Background: Regulatory roles of lncRNAs in tumor progression and prognosis have been confirmed,
but few studies have probed into the role of angiogenesis-related lncRNAs in COAD.
Objective: To identify key angiogenesis-related lncRNAs and build a RiskScore model to predict
the survival probability of COAD patients and help optimize clinical treatment.
Methods: Sample data were collected from The Cancer Genome Atlas (TCGA) and Gene Expression
Omnibus (GEO) database. The HALLMARK pathway score in the samples was calculated using
the single sample gene set enrichment analysis (ssGSEA) method. LncRNAs associated with
angiogenesis were filtered by an integrated pipeline algorithm. LncRNA-based subtypes were classified
by ConsensusClusterPlus and then compared with other established subtypes. A RiskScore
model was created based on univariate Cox, least absolute shrinkage and selection operator (LASSO)
regression and stepwise regression analysis. The Kaplan-Meier curve was drawn by applying
R package survival. The time-dependent ROC curves were drawn by the timeROC package. Finally,
immunotherapy benefits and drug sensitivity were analyzed using tumor immune dysfunction
and exclusion (TIDE) software and pRRophetic package.
Results: Pathway analysis showed that the angiogenesis pathway was a risk factor affecting the
prognosis of COAD patients. A total of 66 lncRNAs associated with angiogenesis were screened,
and three molecular subtypes (S1, S2, S3) were obtained. The prognosis of S1 and S2 was better
than that of S3. Compared with the existing subtypes, the S3 subtype was significantly different
from the other two subtypes. Immunoassay showed that immune cell scores of the S2 subtype
were lower than those of the S1 and S3 subtypes, which also had the highest TIDE scores. We recruited
8 key lncRNAs to develop a RiskScore model. The high RiskScore group with inferior survival
and higher TIDE scores was predicted to benefit limitedly from immunotherapy, but it may
be more sensitive to chemotherapeutics. A nomogram designed by RiskScore signature and other
clinicopathological characteristics shed light on rational predictive power for COAD treatment.
Conclusion: We constructed a RiskScore model based on angiogenesis-related lncRNAs, which
could serve as potential prognostic predictors for COAD patients and may offer clues for the intervention
of anti-angiogenic application. Our results may help evaluate the prognosis of COAD and
provide better treatment strategies.
