Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of Human Hepatocellular Carcinoma

Hong, Wang; Liang, Li; Gu, Yujun; Qi, Zhenhua; Qiu, Haibo; Yang, Xiaosong; Zeng, Weian; Ma, Lulu; Xie, Jingdun

doi:10.1016/j.omtn.2020.10.002

Cited by 171 publications

(206 citation statements)

References 60 publications

(57 reference statements)

Supporting

Mentioning

200

Contrasting

Order By: Relevance

“…P < 0.05, delta Beta value ≥ 0.2. A list of identified immune-related genes was downloaded from the ImmPort database ( http://www.immport.org ) [ 22 ] and was used to screen IR-DEGs using a coexpression strategy. The extent of immune cell infiltration was obtained from the Tumor IMmune Estimation Resource (TIMER), which estimates the immune cell infiltrates in patients from the TCGA database ( https://cistrome.shinyapps.io/timer/ ).…”

Section: Methodsmentioning

confidence: 99%

Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

et al. 2021

View full text Add to dashboard Cite

Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.

show abstract

Section: Methodsmentioning

confidence: 99%

Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Jiang et al showed that lncRNA 01094 induces radioresistance via regulation of the miR-577/CHEK2/ FOXM1 axis (13). Recently, the results of several studies have shown that lncRNAs also have a significant impact on the immune system in cancers such as triple-negative breast cancer, hepatocellular carcinoma (HCC), and glioblastoma multiforme (14)(15)(16), and these lncRNAs have been termed immune-related lncRNAs (irlncRNAs). Liu et al's study revealed that LINC00973 acts as an immune suppressor in ccRCC via its positive regulation of Siglec-15 (17).…”

Section: Introductionmentioning

confidence: 99%

Immune-related long non-coding RNAs can serve as prognostic biomarkers for clear cell renal cell carcinoma

Li¹,

Lu²,

Fang³

et al. 2021

Transl Androl Urol

View full text Add to dashboard Cite

Background:The immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC. Methods:The raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.Results: There were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC.We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine. Conclusions:Our study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.

show abstract

“…As lncRNAs are correlated with ir-genes, these lncRNAs may be involved in regulating the tumor immune microenvironment or the immune cells. The models of IRlncRs were applied to predict the prognosis of breast cancer, 30 hepatocellular carcinoma, 31 clear cell renal cell carcinoma, 20 and pancreatic cancer, 32 except for melanoma. In this study, we first established a novel model with lncRNAs signature to predict melanoma prognosis.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Immune-Related lncRNA Signature as a Prognostic Model for Skin Cutaneous Melanoma

Shuai¹,

Wang²,

He³

et al. 2021

PGPM

View full text Add to dashboard Cite

Purpose Skin cutaneous melanoma (SKCM) is the most aggressive skin cancer that results in high morbidity and mortality rate worldwide. Immune-related long non-coding RNAs (IRlncRs) play an important role in regulating gene expression in tumors. Therefore, in this study, we aimed to identify IRlncRs signature that could predict prognosis and therapeutic targets for melanoma irrespective of the gene expression levels. Methods RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). IRlncRs were identified using co-expression analysis and recognized using univariate analysis. The impact of IRlncRs on survival was analyzed using a modified least absolute shrinkage and selection operator (Lasso) regression model. A 1-year survival receiver operating characteristic curve was constructed, and the area under the curve was calculated to identify the optimal cut-off point to distinguish between high and low-risk groups in patients with SKCM. Furthermore, integrative analysis was performed to identify the impact of clinicopathological features, chemotherapeutic treatment, tumor-infiltrating immune cells, and mutant genes on survival. Results A total of 28 IRlncRs significantly associated with survival were identified. Seventeen IRlncRs pairs were used to build a survival risk model that could be used to distinguish between low and high-risk groups. The high-risk group was negatively associated with tumor-infiltrating immune cells and had a higher half inhibitory centration for chemotherapeutic agents such as cisplatin and vinblastine. Additionally, the high-risk group had a positive correlation with the expression of specific mutant genes such as BRAF and KIT. Conclusion Our findings demonstrate that some IRlncRs have a significant correlation with survival and therapeutic targets for SKCM patients and may provide new insight into the clinical diagnosis and treatment strategies for SKCM patients.

show abstract

Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of Human Hepatocellular Carcinoma

Cited by 171 publications

References 60 publications

Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

Immune-related long non-coding RNAs can serve as prognostic biomarkers for clear cell renal cell carcinoma

Identification and Validation of Immune-Related lncRNA Signature as a Prognostic Model for Skin Cutaneous Melanoma

Contact Info

Product

Resources

About