Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

Mai, Shijie; Liang, Liping; Mai, Genghui; Liu, Xiguang; Diao, Dingwei; Cai, Ruijun; Liu, Le

doi:10.3389/fendo.2022.829175

Cited by 24 publications

(15 citation statements)

References 75 publications

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“…Metabolism-related lncRNAs have been demonstrated to play an important role in regulating cancer metabolism and the crosstalk between cancer metabolism and tumor microenvironment (17). Previous studies have also discovered a series of lncRNA biomarkers or signatures related to metabolism for lung cancer based on bioinformatics analysis (18)(19)(20). However, limited research has explored molecular subtypes and prognostic biomarkers based on lncRNAs related to pentose phosphate pathway that is one of metabolism pathways involved in cancer development (21).…”

Section: Introductionmentioning

confidence: 99%

Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs

Liu

Wang

2022

Front. Public Health

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This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.

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Section: Introductionmentioning

confidence: 99%

Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs

Liu

Wang

2022

Front. Public Health

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“…In BC, lactate is correlated with resistance to PI3K inhibitors ( Hillis and TOKER, 2020 ). In several cancers, lactate is essential in predicting prognosis, tumor microenvironment, and immune response ( Mai et al, 2022 ; Sun et al, 2022 ; Xie et al, 2022 ). However, the prognostic value of lactate in BC remains largely unknown.…”

Section: Discussionmentioning

confidence: 99%

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Jia

Zhang²,

Li³

et al. 2022

Front. Genet.

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Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan–Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

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“…Recent research has demonstrated that elevated lactic acid produced by Warburg effect is a poor prognostic indicator for metastatic lung cancer 9 . The effect of lactate has also been established and confirmed in the prognosis of colorectal cancer, 10 lung adenocarcinoma, 11 and esophageal squamous cell carcinoma 12 . Moreover, recent research has demonstrated that Warburg effect‐related genes have a significant effect on tumor progression and prognosis.…”

Section: Introductionmentioning

confidence: 94%

Warburg effect‐related risk scoring model to assess clinical significance and immunity characteristics of glioblastoma

Zhang,

Wang,

Zheng

et al. 2023

Cancer Medicine

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BackgroundGlioblastoma (GBM), the most common primary malignant brain tumor, has a poor prognosis, with a median survival of only 14.6 months. The Warburg effect is an abnormal energy metabolism, which is the main cause of the acidic tumor microenvironment. This study explored the role of the Warburg effect in the prognosis and immune microenvironment of GBM.MethodsA prognostic risk score model of Warburg effect‐related genes (Warburg effect signature) was constructed using GBM cohort data from The Cancer Genome Atlas. Cox analysis was performed to identify independent prognostic factors. Next, the nomogram was built to predict the prognosis for GBM patients. Finally, the drug sensitivity analysis was utilized to find the drugs that specifically target Warburg effect‐related genes.ResultsAge, radiotherapy, chemotherapy, and WRGs score were confirmed as independent prognostic factors for GBM by Cox analyses. The C‐index (0.633 for the training set and 0.696 for the validation set) and area under curve (>0.7) indicated that the nomogram exhibited excellent performance. The calibration curve also indicates excellent consistency of the nomogram between predictions and actual observations. In addition, immune microenvironment analysis revealed that patients with high WRGs scores had high immunosuppressive scores, a high abundance of immunosuppressive cells, and a low response to immunotherapy. The Cell Counting Kit‐8 assays showed that the drugs targeting Warburg effect‐related genes could inhibit the GBM cells growth in vitro.ConclusionOur research showed that the Warburg effect is connected with the prognosis and immune microenvironment of GBM. Therefore, targeting Warburg effect‐related genes may provide novel therapeutic options.

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Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

Cited by 24 publications

References 75 publications

Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs

Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Warburg effect‐related risk scoring model to assess clinical significance and immunity characteristics of glioblastoma

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