Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Liang, Xiaolong; Yu, Gangfeng; Zha, Lang; Guo, Xiong; Cheng, Anqi; Qin, Chuan; Zhang, Han; Wang, Ziwei

doi:10.3389/fcell.2021.797341

Cited by 5 publications

(5 citation statements)

References 86 publications

(103 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Next, the nomogram predicted survival time was almost consistent with the actual survival time. For example, Liang et al reported that the chemokine signature was identified for predicting overall survival in gastric cancer and showed good predictive efficiency, similar to our model [ 32 ]. In total, our risk model has sufficient efficiency and accuracy in predicting the survival outcomes of COAD patients.…”

Section: Discussionsupporting

confidence: 75%

A Novel Prognostic Chemokine-Related lncRNAs Signature Associated with Immune Landscape in Colon Adenocarcinoma

et al. 2022

Self Cite

View full text Add to dashboard Cite

Chemokines have been reported to be involved in tumorigenesis and progression and can also modulate the tumor microenvironment. However, it is still unclear whether chemokine-related long noncoding RNAs (lncRNAs) can affect the prognosis of colon adenocarcinoma (COAD). We summarized chemokine-related genes and downloaded RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) database. A total of 52 prognostic chemokine-related lncRNAs were screened by univariate Cox regression analysis; patients were grouped according to cluster analysis results. Lasso regression analysis was applied to determine chemokine-related lncRNAs to construct a risk model for further research. This study first investigated the differences between the prognosis and immune status of two chemokine-related lncRNAs clusters by consensus clustering. Then, using various algorithms, we obtained ten chemokine-related lncRNAs to construct a new prognostic chemokine-related lncRNAs risk model. The risk model’s predictive efficiency, validity, and accuracy were further validated and determined in the test and training cohorts. Furthermore, this risk model played a vital role in predicting immune cell infiltration, immune checkpoint gene expression, tumor mutational burden (TMB), immunotherapy score, and drug sensitivity in COAD patients. These findings elucidated the critical role of novel prognostic chemokine-related lncRNAs in prognosis, immune landscape, and drug therapy, thereby providing valuable insights for prognosis assessment and personalized treatment strategies for COAD patients.

show abstract

Section: Discussionsupporting

confidence: 75%

A Novel Prognostic Chemokine-Related lncRNAs Signature Associated with Immune Landscape in Colon Adenocarcinoma

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…In immunotherapy, standard protocols emphasize immune checkpoint inhibitors, such as Keytruda and Opdivo, which target PD-1 or PD-L1 to activate the patient's immune system [36]. However, immunotherapy is not suitable for all patients, and the effectiveness of immunotherapy depends on PLOS ONE multiple factors, for example, the infiltrating of immune cells, the expression level of immune checkpoint genes, and somatic mutation status [37]. Therefore, it is crucial to develop effective immune characteristic models based on chromatin epigenetic regulator-related lncRNAs to improve the prognosis and assist clinicians and researchers in determining the appropriate immunotherapy approach.…”

Section: Discussionmentioning

confidence: 99%

Correlation between chromatin epigenetic-related lncRNA signature (CELncSig) and prognosis, immune microenvironment, and immunotherapy in non-small cell lung cancer

et al. 2023

View full text Add to dashboard Cite

Chromatin regulators drive cancer epigenetic changes, and lncRNA can play an important role in epigenetic changes as chromatin regulators. We used univariate Cox, LASSO, and multivariate Cox regression analysis to select epigenetic-associated lncRNA signatures. Twenty-five epigenetic-associated lncRNA signatures (CELncSig) were identified to establish the immune prognostic model. According to Kaplan-Meier analysis, the overall survival of the high-risk group was significantly lower than the low-risk group. Receiver operating characteristic (ROC) curves, C-index, survival curve, nomogram, and principal component analysis (PCA) were performed to validate the risk model. In GO/KEGG analysis, differentially expressed lncRNAs were correlated with the PI3K−Akt pathway, suggesting that they were highly associated with the metastasis of LUAD. Interestingly, in the immune escape analysis, the TIDE score was lower, and the possibility of immune dysfunction is also slighter in the high-risk group, which means they still have the potential to receive immunotherapy. And CELncsig is highly correlated with immune pathways T_cell_co-inhibition and Check-point. Also, the IMvigor210 cohort analysis indicated that our risk-scoring model has significant potential clinical application value in lung cancer immunotherapy. And we also screened out ten potential chemotherapy agents using the ‘pRRophetic’ package.

show abstract

“…The levels of TMB are also correlated with the prognosis of GC patients. The increasing TMB level indicates a good prognosis of GC patients [ 22 – 24 ]. In addition, TMB could be used to predict the therapy response of patients to immunotherapy in multiple cancer types [ 25 – 27 ].…”

Section: Discussionmentioning

confidence: 99%

Significance of a Tumor Mutation Burden Gene Signature with Prognosis and Immune Feature of Gastric Cancer Patients

Li¹,

Lan²

2022

International Journal of Genomics

View full text Add to dashboard Cite

Gastric cancer (GC) is a common digestive tumor which ranks the fourth most common malignancy worldwide. Immunotherapy is a promising treatment for GC, especially for advanced gastric cancer (AGC). However, in clinical practice, not all patients are sensitive to immunotherapy. Recent studies showed that tumor mutation burden (TMB) is closely correlated with the response of immunotherapy. The current study identified a TMB-related genes’ signature to predict the prognosis and immune feature of GC patients. Firstly, we acquired the TMB data and expression data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI) GEO databases. Then, we extracted TMB-related genes from the expression data of TCGA and two GEO cohorts. By using univariate Cox analysis, we identified that the 429 genes were correlated to GC patients’ overall survival. Subsequently, an immune prognostic signature was constructed by using the least absolute shrinkage and selection operator analysis (LASSO) and multivariate Cox regression analysis. The signature could be utilized to predict the prognosis of GC patients. In addition, the signature showed a closed correlation with immune feature of GC patients. In conclusion, our risk signature could offer hints for the prognosis of GC patients and might provide insights to formulate new immunotherapy strategies for GC patients.

show abstract

Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Cited by 5 publications

References 86 publications

A Novel Prognostic Chemokine-Related lncRNAs Signature Associated with Immune Landscape in Colon Adenocarcinoma

A Novel Prognostic Chemokine-Related lncRNAs Signature Associated with Immune Landscape in Colon Adenocarcinoma

Correlation between chromatin epigenetic-related lncRNA signature (CELncSig) and prognosis, immune microenvironment, and immunotherapy in non-small cell lung cancer

Significance of a Tumor Mutation Burden Gene Signature with Prognosis and Immune Feature of Gastric Cancer Patients

Contact Info

Product

Resources

About