Construction of a novel signature and prediction of the immune landscape in gastric cancer based on necroptosis-related genes

Li, Zhengtian; Liu, Dejun; Ye, Weizheng; Du, Gang; Li, Xi

doi:10.1038/s41598-022-15854-8

Cited by 5 publications

(3 citation statements)

References 63 publications

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“…In this context, they may contribute to a chronic in ammatory environment that supports tumor progression and fails to adequately modulate the tumor microenvironment. Our ndings align with and extend previous studies [4,22,23] . The study by Dai et al con rmed that the risk scores derived from six LMAGs through univariate and multivariate Cox regression analysis showed that the HRisk group had higher immune and stromal scores and lower tumor purity scores.…”

Section: Discussionsupporting

confidence: 93%

WITHDRAWN: Developing a Risk Model of Lipid Metabolism-associated Genes: Implications for Clinical Prognosis and Tumor Immune Microenvironment in Gastric Cancer

Xiao,

Yu,

Zhu

et al. 2024

Preprint

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Background Gastric cancer (GC) remains a significant clinical challenge due to its high mortality rate and complex pathophysiology. Recent advances have suggested that lipid metabolism plays a crucial role in the progression and prognosis of gastric cancer. This study aims to assess the implications of lipid metabolism-associated genes (LMAGs) in the molecular clinical prognosis and tumor immune microenvironment of GC. Methods We analyzed RNA-seq sequencing data from 371 GC transcriptomes in The Cancer Genome Atlas (TCGA) and 433 clinic datasets from the Gene Expression Omnibus (GEO). We selected the top 100 LMAGs for analysis. We applied univariate Cox regression to identify survival-related genes and used consensus clustering to explore molecular subtypes. We also performed copy number variation (CNV) and functional enrichment analysis. Using the LASSO and Cox regression analyses to construct and validate the GC-related prognostic risk model. Results A total of 3911 differentially expressed genes (DEGs) delineated distinct transcriptomic profiles between GC and normal gastric tissues were identified. Among these, 43 LMAGs were significantly associated with survival, most of which were poor prognostic factors. CNV analysis indicated prevalent gains in LMAGs in tumor samples. Consensus clustering revealed two distinct molecular subtypes (ARGcluster A and ARGcluster B) with significant differences in survival outcomes and gene expression profiles. Additionally, immune profiling revealed that ARGcluster A, associated with poorer outcomes, exhibited higher levels of pro-tumorigenic immune cells. Finally, we validated the expression, prognosis, and immune infiltration of fourteen key LMAGs in GC. Conclusion This study underscores the association between LMAGs with the prognosis and tumor immune microenvironment in GC. Further research is needed to validate these findings and explore potential therapeutic targets within the lipid metabolism pathway.

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Section: Discussionsupporting

confidence: 93%

WITHDRAWN: Developing a Risk Model of Lipid Metabolism-associated Genes: Implications for Clinical Prognosis and Tumor Immune Microenvironment in Gastric Cancer

Xiao,

Yu,

Zhu

et al. 2024

Preprint

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“…Necroptosis has a prominent role in tumorigenesis, tumor progression, cancer metastasis and prognosis, and immune regulation [ 8 , 9 ]. Necroptosis may contribute to the augmented therapeutic efficiency of tumors by accelerating cancer cell death or enhancing the sensitivity of tumor cells [ 10 , 11 ]. Some studies have reported the necroptosis-related gene (NRG) signature can predict poor prognosis in some human cancers, including NSCLC [ 12 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: A novel necroptosis signature for predicting survival in lung adenocarcinoma

Zang,

Wang,

Zhu

et al. 2023

BMC Med Genomics

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Background To explore the necroptosis-related genes (NRGs) signature and its predictive values in lung adenocarcinoma (LUAD). Methods The training cohort consisted of tumor samples from The Cancer Genome Atlas, and the validation set comprised data from the Gene Expression Omnibus. Univariate and multivariate Cox regression analyses were applied to identify the prognostic NRG signature as an independent molecular indicator. Correlation analysis was used for the association assessment between the NRG signature and immune checkpoint molecules. Results NRGs involved in necroptosis and immune NOD-like receptor signaling. The NRG signature based on eight NRGs can divide tumors into high-risk and low-risk groups, which was significantly associated with worse survival. Multivariate Cox regression analysis showed that this NRG signature remained an independent prognostic indicator. Stratification analyses demonstrated that this NRG signature was still effective for predicting survival in each stratum of age, gender, and tumor stage. The ROC curve showed a good predictive ability using the NRG signature in the validation cohort (AUC = 0.81). The NRG signature was related to immune checkpoint molecules PD − 1, PD-L1, and PD-L2. Conclusions The NRG signature could be a novel predictor of the prognosis and may become a potential therapeutic target in LUAD.

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“…The infiltration scores of 16 immune cells and the activities of 13 immune-related pathways were calculated using the GSVA software package employing the ssGSEA method 55 . Marker genes of various immune cells were obtained from previous studies 56 and are listed in Table S2 .…”

Section: Methodsmentioning

confidence: 99%

Identification of molecular subtypes and a prognostic signature based on m6A/m5C/m1A-related genes in lung adenocarcinoma

Zhang,

Jia,

et al. 2024

Sci Rep

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Lung cancer, specifically the histological subtype lung adenocarcinoma (LUAD), has the highest global occurrence and fatality rate. Extensive research has indicated that RNA alterations encompassing m6A, m5C, and m1A contribute actively to tumorigenesis, drug resistance, and immunotherapy responses in LUAD. Nevertheless, the absence of a dependable predictive model based on m6A/m5C/m1A-associated genes hinders accurately predicting the prognosis of patients diagnosed with LUAD. In this study, we collected patient data from The Cancer Genome Atlas (TCGA) and identified genes related to m6A/m5C/m1A modifications using the GeneCards database. The “ConsensusClusterPlus” R package was used to produce molecular subtypes by utilizing genes relevant to m6A/m5C/m1A identified through differential expression and univariate Cox analyses. An independent prognostic factor was identified by constructing a prognostic signature comprising six genes (SNHG12, PABPC1, IGF2BP1, FOXM1, CBFA2T3, and CASC8). Poor overall survival and elevated expression of human leukocyte antigens and immune checkpoints were correlated with higher risk scores. We examined the associations between the sets of genes regulated by m6A/m5C/m1A and the risk model, as well as the immune cell infiltration, using algorithms such as ESTIMATE, CIBERSORT, TIMER, ssGSEA, and exclusion (TIDE). Moreover, we compared tumor stemness indices (TSIs) by considering the molecular subtypes related to m6A/m5C/m1A and risk signatures. Analyses were performed based on the risk signature, including stratification, somatic mutation analysis, nomogram construction, chemotherapeutic response prediction, and small-molecule drug prediction. In summary, we developed a prognostic signature consisting of six genes that have the potential for prognostication in patients with LUAD and the design of personalized treatments that could provide new versions of personalized management for these patients.

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Construction of a novel signature and prediction of the immune landscape in gastric cancer based on necroptosis-related genes

Cited by 5 publications

References 63 publications

WITHDRAWN: Developing a Risk Model of Lipid Metabolism-associated Genes: Implications for Clinical Prognosis and Tumor Immune Microenvironment in Gastric Cancer

WITHDRAWN: Developing a Risk Model of Lipid Metabolism-associated Genes: Implications for Clinical Prognosis and Tumor Immune Microenvironment in Gastric Cancer

RETRACTED ARTICLE: A novel necroptosis signature for predicting survival in lung adenocarcinoma

Identification of molecular subtypes and a prognostic signature based on m6A/m5C/m1A-related genes in lung adenocarcinoma

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