Characterizing heterogeneity of non‐small cell lung tumour microenvironment to identify signature prognostic genes

Mi, Kai; Chen, Fuhui; Qian, Zhipeng; Chen, Jing; Lv, Dongxu; Zhang, Chunlong; Xu, Yanjun; Wang, Hongguang; Zhang, Yuepeng; Jiang, Yanan; Shang, Desi

doi:10.1111/jcmm.16092

Cited by 13 publications

(13 citation statements)

References 54 publications

(99 reference statements)

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“…These observations were confirmed by the higher tumor cell aggregation in the low-risk group which was represented by TILs and TIS. This is consistent with previous reports that a high degree of immune cell infiltration was responsible for a significantly favorable prognosis in NSCLC ( 18 ). Our results also demonstrated that the low-risk group possessed raised CYT and TMB expressions, with higher degrees of CD8+ T cell infiltration.…”

Section: Discussionsupporting

confidence: 93%

“…Our results also demonstrated that the low-risk group possessed raised CYT and TMB expressions, with higher degrees of CD8+ T cell infiltration. Similar findings of better outcomes in those with higher CYT levels have also been reported in cancer patients ( 18 , 36 ). In patients with resected NSCLC, higher TMB scores were indicative of a more favorable prognosis ( 37 ).…”

Section: Discussionsupporting

confidence: 85%

“…characterized the molecular subtypes of NSCLC, which demonstrated important differences in immune host response ( 33 ). Also, our previous study identified different molecular subtypes of NSCLC according to the immune landscape and constructed a prognostic model ( 18 ). However, the role of non-coding RNA, especially miRNAs in the NSCLC immune microenvironment have not been well elucidated.…”

Section: Discussionmentioning

confidence: 99%

“…The proportion of immune cell infiltration was estimated using the "GSVA" R package and 27 human immune cell phenotypes (17)(18)(19). In addition, factors related to tumor immunogenicity were also contrasted between high-and low-risk groups.…”

Section: Approximation Of Tumor-infiltrating Immune Cellsmentioning

confidence: 99%

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Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer

Zhang

et al. 2021

Front. Oncol.

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BackgroundA detailed means of prognostic stratification in patients with non-small cell lung cancer (NSCLC) is urgently needed to support individualized treatment plans. Recently, microRNAs (miRNAs) have been used as biomarkers due to their previously reported prognostic roles in cancer. This study aimed to construct an immune-related miRNA signature that effectively predicts NSCLC patient prognosis.MethodsThe miRNAs and mRNA expression and mutation data of NSCLC was obtained from The Cancer Genome Atlas (TCGA). Immune-associated miRNAs were identified using immune scores calculated by the ESTIMATE algorithm. LASSO-penalized multivariate survival models were using for development of a tumor immune-related miRNA signature (TIM-Sig), which was evaluated in several public cohorts from the Gene Expression Omnibus (GEO) and the CellMiner database. The miRTarBase was used for constructing the miRNA-target interactions.ResultsThe TIM-Sig, including 10 immune-related miRNAs, was constructed and successfully predicted overall survival (OS) in the validation cohorts. TIM-Sig score negatively correlated with CD8+ T cell infiltration, IFN-γ expression, CYT activity, and tumor mutation burden. The correlation between TIM-Sig score and genomic mutation and cancer chemotherapeutics was also evaluated. A miRNA-target network of 10 miRNAs in TIM-Sig was constructed. Further analysis revealed that these target genes showed prognostic value in both lung squamous cell carcinoma and adenocarcinoma.ConclusionsWe concluded that the immune-related miRNAs demonstrated a potential value in clinical prognosis.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Section: Approximation Of Tumor-infiltrating Immune Cellsmentioning

confidence: 99%

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Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer

Zhang

et al. 2021

Front. Oncol.

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“…Immune checkpoints are key modulators of immune system function 29 . In our study, the expression of immune checkpoint-related genes of three ISs was analyzed, surprisingly, we found that the expression of T cell failure markers such as LAG3, HA VCR2, CTLA4, PDCD1, CD274 [30][31][32] was significantly higher in IS1 than in IS3.…”

Section: Discussionmentioning

confidence: 99%

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures

Gao

Zhao

et al. 2021

Sci Rep

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Cutaneous melanoma could be treated by immunotherapy, which only has limited efficacy on uveal melanoma (UM). UM immunotyping for predicting immunotherapeutic responses and guiding immunotherapy should be better understood. This study identified molecular subtypes and key genetic markers associated with immunotherapy through immunosignature analysis. We screened a 6-immune cell signature simultaneously correlated with UM prognosis. Three immune subtypes (IS) were determined based on the 6-immune cell signature. Overall survival (OS) of IS3 was the longest. Significant differences of linear discriminant analysis (LDA) score were detected among the three IS types. IS3 with the highest LDA score showed a low immunosuppression. IS1 with the lowest LDA score was more immunosuppressive. LDA score was significantly negatively correlated with most immune checkpoint-related genes, and could reflect UM patients’ response to anti-PD1 immunotherapy. Weighted correlation network analysis (WGCNA) identified that salmon, purple, yellow modules were related to IS and screened 6 prognostic genes. Patients with high-expressed NME1 and TMEM255A developed poor prognosis, while those with high-expressed BEX5 and ROPN1 had better prognosis. There was no notable difference in OS between patients with high-expressed LRRN1 and ST13 and those with low-expressed LRRN1 and ST13. NME1, TMEM255A, Bex5 and ROPN1 showed potential prognostic significance in UM.

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Identification of costimulatory molecule signatures for evaluating prognostic risk in non-small cell lung cancer

Yang,

Lu,

2024

Heliyon

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Characterizing heterogeneity of non‐small cell lung tumour microenvironment to identify signature prognostic genes

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 13 publications

References 54 publications

Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer

Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures

Identification of costimulatory molecule signatures for evaluating prognostic risk in non-small cell lung cancer

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