A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma

Shi, Xun; Liu, Huan; Pan, Shupei; Ke, Yue; Li, Yuxing; Wei, Guo; Wang, Yuchen; Ruan, Qinli; Zhang, Xiaozhi; Ma, Hongbing

doi:10.2147/ijgm.s333697

Cited by 14 publications

(14 citation statements)

References 42 publications

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“…The tumor-derived fraction of cell-free DNA (cfDNA) profiles was examined by whole genome sequencing in blood samples of 30 ES cases, and low scores were found to have a significant association with better chemoradiotherapy response [ 35 ]. Noncoding RNAs, including miRNAs and lncRNAs, play important roles in various biological processes, such as tumor proliferation [ 36 ], hypoxia [ 37 ], metabolism [ 6 ], methylation [ 38 ], apoptosis [ 39 ], and autophagy [ 40 ], and have been investigated as potential biomarkers or therapeutic targets in ESCC. A study by Chen et al found that high levels of miR-133a/b were associated with significantly long OS in ESCC and were an independent prognostic factor for these patients [ 36 ].…”

Section: Discussionmentioning

confidence: 99%

“…A study by Chen et al found that high levels of miR-133a/b were associated with significantly long OS in ESCC and were an independent prognostic factor for these patients [ 36 ]. A nine-autophagy-related lncRNA signature established by Shi et al showed a favorable treatment outcome prediction value for ESCC [ 40 ]. Several recent studies have reported that FRLs affect the development and progression of solid tumors by serving as competing endogenous RNAs, such as OIP5-AS1 in prostate cancer and MT1DP in non-small-cell lung cancer [ 41 , 42 ].…”

Section: Discussionmentioning

confidence: 99%

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Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Zhu

Zhao

et al. 2022

Oxidative Medicine and Cellular Longevity

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Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Zhu

Zhao

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…In a previous study ( Shi et al (2021) , also reported a prognostic model in ESCC consisted of nine autophagy-related lncRNAs. It is noticed that the 11 lncRNA signatures in our model had no overlap with theirs.…”

Section: Discussionmentioning

confidence: 99%

Risk Stratification and Validation of Eleven Autophagy-Related lncRNAs for Esophageal Squamous Cell Carcinoma

Zhao

Wang²,

Meng³

et al. 2022

Front. Genet.

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Esophageal squamous cell carcinoma (ESCC), the most prevalent subtype of esophageal cancer, ranks sixth in cancer-related mortality, making it one of the deadliest cancers worldwide. The identification of potential risk factors for ESCC might help in implementing precision therapies. Autophagy-related lncRNAs are a group of non-coding RNAs that perform critical functions in the tumor immune microenvironment and therapeutic response. Therefore, we aimed to establish a risk model composed of autophagy-related lncRNAs that can serve as a potential biomarker for ESCC risk stratification. Using the RNA expression profile from 179 patients in the GSE53622 and GSE53624 datasets, we found 11 lncRNAs (AC004690.2, AC092159.3, AC093627.4, AL078604.2, BDNF-AS, HAND2-AS1, LINC00410, LINC00588, PSMD6-AS2, ZEB1-AS1, and LINC02586) that were co-expressed with autophagy genes and were independent prognostic factors in multivariate Cox regression analysis. The risk model was constructed using these autophagy-related lncRNAs, and the area under the receiver operating characteristic curve (AUC) of the risk model was 0.728. To confirm that the model is reliable, the data of 174 patients from The Cancer Genome Atlas (TCGA) esophageal cancer dataset were analyzed as the testing set. A nomogram for ESCC prognosis was developed using the risk model and clinic-pathological characteristics. Immune function annotation and tumor mutational burden of the two risk groups were analyzed and the high-risk group displayed higher sensitivity in chemotherapy and immunotherapy. Expression of differentially expressed lncRNAs were further validated in human normal esophageal cells and esophageal cancer cells. The constructed lncRNA risk model provides a useful tool for stratifying risk and predicting the prognosis of patients with ESCC, and might provide novel targets for ESCC treatment.

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“…The survival time of the patients in the two groups was analyzed by K-M survival curves using the survminer package [ 30 ]. Then, ROC curves were adopted to calculate the AUC area to identify the specificity and sensitivity of the model, and the ROC curves were plotted using the survival ROC package with 1-, 3-, and 5-years as the survival time points [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

“…The correlation between risk score and clinical traits (age, sex, stage, T-stage, N-stage, alcohol, tobacco) in ESCC patients were evaluated by wilcox.test. To more closely understand the correlation between DEARlncRNAs and clinical traits, stratified survival analysis was used to investigate clinical traits for which the risk score had a difference [ 30 ]. The relationship between patients’ survival and clinical traits was then analyzed using the univariate and multivariate Cox regression analysis.…”

Section: Methodsmentioning

confidence: 99%

Integrative Analysis of Angiogenesis-Related Long Non-Coding RNA and Identification of a Six-DEARlncRNA Signature Associated with Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma

Cao

Wang

Liu

et al. 2022

Cancers

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Esophageal squamous cell carcinoma (ESCC) is a lethal gastrointestinal malignancy worldwide. We aimed to identify an angiogenesis-related lncRNAs (ARlncRNAs) signature that could predict the prognosis in ESCC. The GSE53624 and GSE53622 datasets were derived from the GEO database. The differently expressed ARlncRNAs (DEARlncRNAs) were retrieved by the weighted gene co-expression network analysis (WGCNA), differential expression analysis, and correlation analysis. Optimal lncRNA biomarkers were screened from the training set and the six-DEARlncRNA signature comprising AP000696.2, LINC01711, RP11-70C1.3, AP000487.5, AC011997.1, and RP11-225N10.1 could separate patients into high- and low-risk groups with markedly different survival. The validation of the reliability of the risk model was performed by the Kaplan-Meier test, ROC curves, and risk curves in the test set and validation set. Predictive independence analysis indicated that risk score is an independent prognostic biomarker for predicting the prognosis of ESCC patients. Subsequently, a ceRNA regulatory network and functional enrichment analysis were performed. The IC50 test revealed that patients in the high-risk group were resistant to Gefitinib and Lapatinib. Finally, the six DEARlncRNAs were detected by qRT-PCR. In conclusion, we demonstrated a novel ARlncRNA signature as an independent prognostic factor to distinguish the risk of ESCC patients and benefit the personalized clinical applications.

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A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma

Cited by 14 publications

References 42 publications

Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Risk Stratification and Validation of Eleven Autophagy-Related lncRNAs for Esophageal Squamous Cell Carcinoma

Integrative Analysis of Angiogenesis-Related Long Non-Coding RNA and Identification of a Six-DEARlncRNA Signature Associated with Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma

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