Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

Zhang, Xinyang; Cao, Yu; Chen, Li

doi:10.1186/s12885-021-08654-2

Cited by 3 publications

(1 citation statement)

References 37 publications

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“…LncRNAs are involved in autophagy, modulating the expression of ATG genes by acting as ceRNAs for miRNAs ( 36 , 180 ). Recently, several autophagy-related lncRNAs have been proposed as biomarkers and signatures for diagnostic and prognostic purposes for many cancer types, including breast ( 182 , 183 ), bladder ( 184 , 185 ), pancreatic ( 186 ), colorectal ( 187 , 188 ), and lung ( 189 , 190 ). In most cases, the overall survival of patients in high-risk groups is significantly lower based on the presence of each proposed signature.…”

Section: Lncrnas In Drug Resistance Mechanismsmentioning

confidence: 99%

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

et al. 2022

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Head and neck squamous cell carcinoma (HNSCC) originates in the squamous cell lining the mucosal surfaces of the head and neck region, including the oral cavity, nasopharynx, tonsils, oropharynx, larynx, and hypopharynx. The heterogeneity, anatomical, and functional characteristics of the patient make the HNSCC a complex and difficult-to-treat disease, leading to a poor survival rate and a decreased quality of life due to the loss of important physiologic functions and aggressive surgical injury. Alteration of driver-oncogenic and tumor-suppressing lncRNAs has recently been recently in HNSCC to obtain possible biomarkers for diagnostic, prognostic, and therapeutic approaches. This review provides current knowledge about the implication of lncRNAs in drug resistance mechanisms in HNSCC. Chemotherapy resistance is a major therapeutic challenge in HNSCC in which lncRNAs are implicated. Lately, it has been shown that lncRNAs involved in autophagy induced by chemotherapy and epithelial–mesenchymal transition (EMT) can act as mechanisms of resistance to anticancer drugs. Conversely, lncRNAs involved in mesenchymal–epithelial transition (MET) are related to chemosensitivity and inhibition of invasiveness of drug-resistant cells. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in both processes and are important for cancer detection, progression, diagnosis, therapy response, and prognostic values. As the involvement of more lncRNAs is elucidated in chemoresistance mechanisms, an improvement in diagnostic and prognostic tools could promote an advance in targeted and specific therapies in precision oncology.

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Section: Lncrnas In Drug Resistance Mechanismsmentioning

confidence: 99%

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

et al. 2022

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A Novel Mitochondrial-Related Gene Signature for the Tumor Immune Microenvironment Evaluation and Prognosis Prediction in Lung Adenocarcinoma

Liu

et al. 2022

Journal of Immunology Research

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Lung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. More and more studies have reported that mitochondrial-related genes (MTRGs) were associated with the clinical outcomes of multiple tumors solely. In this study, we aimed to develop a novel prognostic model based on MTRGs. Differentially expressed MTRGs were identified from TCGA-LUAD and GSE31210 cohorts. Univariate Cox regression analysis was utilized to screen differentially expressed MTRGs that were related to prognosis of LUAD. Then, LASSO Cox regression analysis was used to develop a prognostic signature. ESTIMATE was used for estimating the fractions of immune cell types. In this study, we identified 44 overlapping differentially expressed MTRGs in TCGA-LUAD and GSE31210 cohorts. Among 44 overlapping differentially expressed MTRGs, nine genes were associated with prognosis of LUAD. When the penalty parameter lambda was the minimum, there were six genes meeting the conditions of constructing the signature, including SERPINB5, CCNB1, FGR MAOB, SH3BP5, and CYP24A1. The survival analysis suggested that prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. Cox regression analyses showed that the risk score was an independent predictor of LUAD prognosis. As with the results of ESTIMATE score, the degree of immune cell infiltration in the low-risk group was higher than that in the high-risk group, such as TIL, Treg, and B cells. In addition, TMB and cancer stem cell infiltration were higher in the low-risk group than the high-risk group. In conclusion, we developed a novel MTRG signature acting as a negative independent prognostic factor. In the future, individualized treatments and medical decision-making may benefit from using the predicted model.

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A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

2021

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Objective: To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).Background: Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and followup data, the prognostic model is preferred by researchers.Methods: PubMed and the Cochrane Library were searched using the items "NSCLC", "prognostic model", "prognosis prediction", and "survival prediction" from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified. Conclusions:The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

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Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

Cited by 3 publications

References 37 publications

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

A Novel Mitochondrial-Related Gene Signature for the Tumor Immune Microenvironment Evaluation and Prognosis Prediction in Lung Adenocarcinoma

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

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