Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer

Gu, Xinpei; Chu, Liuxi; Kang, Yanlan

doi:10.3389/fgene.2022.894024

Cited by 5 publications

(5 citation statements)

References 42 publications

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“…Based on available studies, FSTL3 has been shown to be associated with poor prognosis in various neoplastic diseases [31][32][33] . This point helped us to con rm the reliability of this study.…”

Section: Discussionmentioning

confidence: 99%

Integrative Identification of Angiogenesis-Related Genes for Predicting Immune Interaction and Prognosis in LUAD

Miao

Ainiwaer

et al. 2023

Preprint

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Background Tumor microenvironment is characterized by angiogenesis. A tumor's microenvironment (TME) and its interactions with immunotherapy influence immunotherapy's effectiveness. In the study of Lung adenocarcinoma (LUAD), there is currently no clear link between multiple angiogenesis genes and clinical results, immune cell infiltration, and immunotherapy. Methods Clinical information and corresponding Gene expression were downloaded from the GEO and TCGA. Thirty-six angiogenesis-related genes (ARGs) were comprehensively evaluated, and correlations between angiogenesis and patterns of transcription and prognosis. The immune difference shows different functions and Infiltration in the sub-cluster. KEGG pathway and GO enrichment analyses were conducted based on distinct clusters. ARG_score was established to quantify the angiogenic subtype of each patient. Finally, we assessed their value in predicting prognosis and treatment response in the different risk groups. Results The mutations of ARGs in LUAD specimens were discussed at the genetic level. We identified two distinct molecular subtypes and observed that ARG mutations were associated with clinical characteristics, prognosis, and TME of patients. Next, an ARG_score predicting overall survival (OS) was established, confirming its robust predictive power for patients with LUAD. Moreover, a highly reliable Nomogram was created. Low risk score demonstrated better OS. In addition, the ARG_score was shown to be significantly correlated with cancer stem cell index and drug sensitivity. FSTL3 is considered potential target gene. Conclusion In general, we were the first to characterize the prognosis of ARGs in patients with LUAD. Angiogenesis may play an essential role in the development of LUAD. This characterization may assist in clarifying the features of angiogenesis in TME and enable the exploration of more cost-effective immunotherapy strategies.

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Section: Discussionmentioning

confidence: 99%

Integrative Identification of Angiogenesis-Related Genes for Predicting Immune Interaction and Prognosis in LUAD

Miao

Ainiwaer

et al. 2023

Preprint

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“…Based on cell-cluster-markers and TAMs-related-genes, TOP 8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) significantly associated with prognosis were obtained (Figure 2). These have obvious benefits to clinicians for the assessment of patient prognosis (36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49). The same data were used to construct a risk score model containing 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, and GPR65) for prognostic evaluation (Figure 2) (50)(51)(52)(53)(54)(55).…”

Section: Discussionmentioning

confidence: 99%

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Zhu¹,

Zheng²,

Liu³

et al. 2022

Front. Immunol.

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PurposeTo investigate the significance of macrophage infiltration to the prognosis of lung adenocarcinoma.MethodsR language bioinformatics analysis technology, was used to obtain macrophage infiltration-related module genes through WGCNA (Weighted Gene Co-Expression Network Analysis). Marker genes of macrophage subtypes were identified using single-cell sequencing of lung adenocarcinoma tissue. Risk score models were constructed and validated using external data cohorts and clinical samples.ResultsAnalysis of cohorts TCGA-LUAD, GSE11969, GSE31210, GSE50081, GSE72094 and GSE8894, revealed a negative correlation between macrophage infiltration and survival. Immunohistochemical analyses of clinical samples were consistent with these data. Based on cell-cluster-markers and TAMs-related-genes, TOP8 genes were obtained (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) with a significant association to prognosis. Risk score models including 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65) for prognosis were constructed. The efficacy, stability and generalizability of the risk score models were validated using multiple data cohorts (GSE19188, GSE26939, GSE31210, GSE50081, GSE42127, and GSE72094).ConclusionsMacrophage infiltration negatively correlates with prognosis in patients with lung adenocarcinoma. Based on cell-cluster-markers and TAMs-related-genes, both TOP8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, TK1) and risk score models using C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65 could predict disease prognosis.

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“…Module membership (MM) was defined as the correlation between the summary profile of the module and gene expression. The biological functions of gene modules were characterized by gene ontology (GO) using EnrichR (Gu et al, 2022).…”

Section: Functional Classification Of Epigenetically Regulated Msi-re...mentioning

confidence: 99%

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome

Liu²,

Zheng³

et al. 2023

Front. Genet.

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Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration.Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA–LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling.Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype.Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.

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Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer

Cited by 5 publications

References 42 publications

Integrative Identification of Angiogenesis-Related Genes for Predicting Immune Interaction and Prognosis in LUAD

Integrative Identification of Angiogenesis-Related Genes for Predicting Immune Interaction and Prognosis in LUAD

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome

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