Establishment of the Prognostic Index Reflecting Tumor Immune Microenvironment of Lung Adenocarcinoma Based on Metabolism-Related Genes

Zhang, Jianguo; Zhang, Jianzhong; Yuan, Cheng; Luo, Yuan; Li, Yangyi; Dai, Panpan; Sun, Wenjie; Zhang, Nannan; Ren, Jiangbo; Zhang, Mengjie; Gong, Yan; Xie, Conghua

doi:10.7150/jca.49266

Cited by 17 publications

(19 citation statements)

References 50 publications

(52 reference statements)

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“…With GCH = 149 in “A” but only 3 in “N” and 2 in both “B” and “C”, ENTPD2 is a strong candidate target gene whose manipulation may selectively destroy the primary tumor “A” with practically no effect on the other regions of the prostate. Recent reports considered ENTPD2 relevant for the lung adenocarcinoma [ 71 ] and hepatocellular carcinoma [ 72 ] transcriptomic signatures. Interestingly, expression of ENTPD2 was significantly up-regulated in the nodules “B” ( x = 2.95) and “C” ( x = 2.03) but not in “A” ( x = −1.08).…”

Section: Resultsmentioning

confidence: 99%

A Personalized Genomics Approach of the Prostate Cancer

Iacobaş

2021

Cells

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Decades of research identified genomic similarities among prostate cancer patients and proposed general solutions for diagnostic and treatments. However, each human is a dynamic unique with never repeatable transcriptomic topology and no gene therapy is good for everybody. Therefore, we propose the Genomic Fabric Paradigm (GFP) as a personalized alternative to the biomarkers approach. Here, GFP is applied to three (one primary—“A”, and two secondary—“B” & “C”) cancer nodules and the surrounding normal tissue (“N”) from a surgically removed prostate tumor. GFP proved for the first time that, in addition to the expression levels, cancer alters also the cellular control of the gene expression fluctuations and remodels their networking. Substantial differences among the profiled regions were found in the pathways of P53-signaling, apoptosis, prostate cancer, block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy, and sustained angiogenesis. ENTPD2, AP5M1 BAIAP2L1, and TOR1A were identified as the master regulators of the “A”, “B”, “C”, and “N” regions, and potential consequences of ENTPD2 manipulation were analyzed. The study shows that GFP can fully characterize the transcriptomic complexity of a heterogeneous prostate tumor and identify the most influential genes in each cancer nodule.

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Section: Resultsmentioning

confidence: 99%

A Personalized Genomics Approach of the Prostate Cancer

Iacobaş

2021

Cells

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“…In order to better understand the potential mechanisms of the different prognoses between the high– and low-risk subgroups, GO functional annotation, GSEA, and ssGSEA were performed in the train cohort. First, the package ‘limma’ in R was used to determine the differentially expressed genes (DEGs; |log2FC| >1 and FDR <0.05) between the high– and low-risk subgroups [ 37 ]. Following this, the ‘clusterProfiler’ package in R was used to conduct GO functional annotation of DEGs; meanwhile, GSEA was employed for Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using the software GSEA 4.0.3 ( http://www.gsea-msigdb.org ) [ 38 ].…”

Section: Methodsmentioning

confidence: 99%

Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma

et al. 2021

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Lung adenocarcinoma (LUAD) is one of the main causes of cancer deaths globally. Redox is emerging as a crucial contributor to the pathophysiology of LUAD, which can be regulated by long non-coding RNAs (lncRNAs). The aim of our research is to identify a novel redox-related lncRNA prognostic signature (redox-LPS) for better prediction of LUAD prognosis. 535 LUAD samples from The Cancer Genome Atlas (TCGA) database and 226 LUAD samples from the Gene Expression Omnibus (GEO) database were included in our study. 67 redox genes and 313 redox-related lncRNAs were identified. After performing LASSO-Cox regression analysis, a redox-LPS consisting of four lncRNAs (i.e., CRNDE, CASC15, LINC01137, and CYP1B1-AS1) was developed and validated. Our redox-LPS was superior to another three established models in predicting survival probability of LUAD patients. Univariate and multivariate Cox regression analysis revealed that risk score and stage were independent prognostic indicators. A nomogram plot including risk score and stage was constructed to predict survival probability of LUAD patients; this was further verified by calibration curves. Functional enrichment analysis and gene set enrichment analysis, were performed to determine the differences in cellular processes and signaling pathways between the high -and low-risk subgroups. A variety of algorithms (such as single-sample gene set enrichment analysis and CIBERSOFT) were conducted to uncover the landscape of tumor immune microenvironment in the high-and low-risk subgroups. In conclusion, a novel independent redox-LPS was constructed and validated for LUAD patients, which might provide new insights for clinical decision-making and precision medicine. Transcriptome profiling and clinical data of LUAD patients from TCGA (535samples;55268genes) Transcriptome profiling and clinical data of LUAD patients from GEO (226samples;20174genes) Train cohort (TCGA: 246) 71 redox-related genes Univariate cox regression Redox-related lncRNAs with prognostic values Lasso regression Redox-LPS Nomogram plot Calibration curve Vocalno plot GO functional annotation GSEA ssGSEA PCA Survival analysis ROC curve 10089 TCGA -derived lncRNAs Samples from TCGA : 535 Samples from GEO: 226 313 redox -related lncRNAs Multivariate cox regression Test1 cohort (TCGA: 244) Excluded samples (TCGA: 45) Test3 cohort (GEO: 226) Test2 cohort (TCGA: 490) Samples from TCGA : 535 Samples from GEO : 226 18870 intersecting genes Comparative analysis Co-expression analysis Clinical significance analysis ARTICLE HISTORY

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“…It has been found that MAO-B is overexpressed in lung cancer cells in comparison to normal cells. MAO-B expression increased (mRNA and protein levels) in A549 and H1299 upon ionizing radiation (IR) treatment in a dose-dependent manner [ 61 ]. Therefore, it is concluded that MAO-B can be considered a biomarker for NSCLC and IR resistance.…”

Section: Mao-b’s Role In Cancermentioning

confidence: 99%

Monoamine Oxidase (MAO) as a Potential Target for Anticancer Drug Design and Development

et al. 2021

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Monoamine oxidases (MAOs) are oxidative enzymes that catalyze the conversion of biogenic amines into their corresponding aldehydes and ketones through oxidative deamination. Owing to the crucial role of MAOs in maintaining functional levels of neurotransmitters, the implications of its distorted activity have been associated with numerous neurological diseases. Recently, an unanticipated role of MAOs in tumor progression and metastasis has been reported. The chemical inhibition of MAOs might be a valuable therapeutic approach for cancer treatment. In this review, we reported computational approaches exploited in the design and development of selective MAO inhibitors accompanied by their biological activities. Additionally, we generated a pharmacophore model for MAO-A active inhibitors to identify the structural motifs to invoke an activity.

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Establishment of the Prognostic Index Reflecting Tumor Immune Microenvironment of Lung Adenocarcinoma Based on Metabolism-Related Genes

Cited by 17 publications

References 50 publications

A Personalized Genomics Approach of the Prostate Cancer

A Personalized Genomics Approach of the Prostate Cancer

Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma

Monoamine Oxidase (MAO) as a Potential Target for Anticancer Drug Design and Development

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