Molecular characterization of metabolic subtypes of gastric cancer based on metabolism-related lncRNA
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ABSTRACT:
SUBMITTER: Li L
PROVIDER: S-EPMC8563741 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe treatment of gastric cancer remains a challenge.MethodsWe divided gastric cancer into three subtypes based on 14 cancer functional states. We investigated differences between subtypes through multi-omics data, especially at the single-cell level, which allowed us to analyze differences from the perspective of each type of cell rather than the whole.ResultsThe cluster 1 is characterized by high levels of tumor progression-related cancer functional status, worst survival outcomes, low metabolic level, high infiltration of immunosuppressive cells, high copy number variations (CNV), and low tumor mutational burden (TMB). The cluster 2 is characterized by low levels of tumor progression-related cancer functional status, favorable prognosis, moderate metabolic level, low immune cell infiltration, high CNV, and moderate TMB. Then, the cluster 3 is characterized by the high level of all cancer functional status, high metabolic level, low CNV, high TMB, high infiltration of immune cells with high cytotoxicity, and better response to immunotherapy. We also established a prognostic model based on cancer functional status and validated its robustness.ConclusionsCollectively, our study identified gastric cancer subtypes and provided new insights into the clinical treatment of gastric cancer.
| S-EPMC9899380 | biostudies-literature
Project description:IntroductionGastric cancer (GC) is the fourth leading cause of cancer death worldwide. Due to the lack of effective chemotherapy methods for advanced gastric cancer and poor prognosis, the emergence of immunotherapy has brought new hope to gastric cancer. Further research is needed to improve the response rate to immunotherapy and identify the populations with potential benefits of immunotherapy. It is unclear whether m7G-related lncRNAs influence tumour immunity and the prognosis of immunotherapy.MethodsThis study evaluated 29 types of immune cells and immune functions in gastric cancer patients, and m7G-related lncRNAs and their molecular subtypes were identified. In addition, we also studied the biological function characteristics of m7G-related lncRNA molecular subtypes. Finally, the patient's risk score was calculated based on m7G-related lncRNAs, and a nomogram of staging and risk groups was established to predict the prognosis. For experimental verification, RT-qPCR were preformed from the native cohort.ResultsAfter identifying m7G-related lncRNAs and their molecular subtypes, we found three molecular subtypes, the B subtype had the highest level of infiltration, and the B subtype may benefit more from immunotherapy. We divided GC patients into two regulator subtypes based on biological function. The two subtypes have significant immunological differences and can be used to judge ICI treatment. We established a risk score formula based on five lncRNAs, including LINC00924, LINC00944, LINC00865, LINC00702, and ZFAS1. Patients with poor prognoses were closely related to patients in the high-risk group. After comprehensive analysis of different risk groups, the efficacy of the high-risk group on bleomycin, cisplatin, docetaxel, doxorubicin and etoposide was better than that of the low-risk group, suggesting that risk subgroups based on risk scores play a guiding role in chemotherapy and that the high-risk group may benefit more from immunotherapy. RT-qPCR results showed that LINC00924, LINC00944, and LINC00865 were highly expressed in tumour tissues, while LINC00702 and ZFAS1 were expressed at low levels in tumour tissues.DiscussionIn conclusion, we were the first to discover that m7G-related lncRNAs play a vital role in the tumour immune microenvironment of gastric cancer, and a risk prediction model was established to identify patients with potential benefits from immunotherapy and predict the prognosis of GC patients.
| S-EPMC10017847 | biostudies-literature
Project description:N6-methyladenosine (m6A) is a common form of mRNA modification regulated by m6A RNA methylation regulators and play an important role in the progression of gastric cancer (GC). However, the prognostic role of m6A-related lncRNA in gastric cancer has not been fully explored. This study aims at exploring the biological function and prognostic roles of the m6A-related lncRNA signature in gastric cancer. A total of 800 m6A-related lncRNAs were identified through Pearson correlation analysis between m6A regulators and all lncRNAs. Eleven m6A-related lncRNA signatures were identified through a survival analysis and the Kaplan-Meier (KM) curve analysis results suggest that patients in the low-risk group have a better overall survival (OS) and disease-free survival (DFS) outcome than the high-risk group. Also, the lncRNA signature can serve as an independent prognostic factor for OS and DFS. The gene set enrichment analysis (GSEA) result suggests that patients in the high-risk group were mainly enriched in the ECM receptor interaction, focal adhesion, and cytokine-cytokine receptor interaction pathway, while the low-risk group was characterized by the base excision repair pathway. We further constructed an individualized prognostic prediction model via the nomogram based on the independent prognostic factor for the OS and DFS, respectively. In addition, some candidate drugs aimed at GC risk group differentiation were identified using the Connective Map (CMAP) database. Lastly, four subgroups (C1, C2, C3, and C4) were identified based on the m6A-related lncRNA expression, through a consensus clustering algorithm. Among them, C1 and C2 have a greater likelihood to respond to immune checkpoint inhibitor immunotherapy, suggesting that the C1 and C2 subgroup might benefit from immunotherapy. In conclusion, the m6A-related lncRNA signature can independently predict the OS and DFS of GC and may aid in development of personalized immunotherapy strategies.
| S-EPMC8076577 | biostudies-literature
Project description:Molecular subtypes in gastric cancer.
| PRJNA329144 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-03-20 | GSE84437 | GEO
Project description:Recent studies have demonstrated the biological significance of cuproptosis modification, a newly discovered programmed cell death, in tumor progression. Nonetheless, the potential role of cuproptosis-related genes (CRGs) in the immune landscape and tumor microenvironment (TME) formation of colorectal cancer (CRC) remains unknown. We comprehensively assessed cuproptosis modification patterns of 1339 CRC samples based on 27 CRGs and systematically analyzed the correlation of these patterns with TME. The CRG-score was constructed to quantify cuproptosis characteristics by LASSO and multivariate Cox regression methods, and its predictive capability was validated in an independent cohort. We identified three distinct cuproptosis modification patterns in CRC. The TME immune cell infiltration demonstrated immune heterogeneity among these three subtypes. Enrichment for multiple metabolism signatures was pronounced in cluster A. Cluster C was significantly correlated with the signaling pathways of immune activation-related, resulting in poor prognoses. Cluster B with mixed features possibly represents a transition phenotype or intratumoral heterogeneity. Then, based on constructed eight-gene CRG-score, we found that the signature could predict the disease-free survival of CRC patients, and the low CRG-score was related to increased neoantigen load, immunity activation, and microsatellite instability-high (MSI-H). Additionally, we observed significant correlations of the CRG-score with the cancer stem cell index and chemotherapeutic drug susceptibility. This study demonstrated that cuproptosis was correlated with tumor progression, prognosis, and TME. Our findings may improve the understanding of CRGs in TME infiltration characterization of CRC patients and contribute to guiding more effective clinical therapeutic strategies.
| S-EPMC9579866 | biostudies-literature
Project description:BackgroundCuproptosis (copper death) is a recently found cell death type produced by copper iron; nonetheless, the properties of cuproptosis molecular subtypes and possible involvement of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) in ovarian cancer (OC) remain unknown.MethodsCRG changes were characterized at the genomic and transcriptional levels in 656 OC samples, and their expression patterns were investigated using three different datasets.ResultsWe identified three distinct molecular subtypes, and discovered that variations in molecular subtypes were linked to patient prognosis, TME cell infiltration characteristics, malignancy, and immune-related pathways. Then, in order to predict overall survival (OS), we created a risk score and tested its predictive potential in OC patients. As a result, we created a very accurate nomogram to increase risk score clinical applicability. Better OS, younger age, early stage, and immune activity were all associated with a low risk score. The hallmarks of a high-risk score are older age, advanced stage, immunosuppression, and a bad prognosis. Furthermore, risk score was linked to immune checkpoint expression (including PD-L1, CTLA4), targeted therapy gene expression (PARP, PDGFRA), cancer stem cell (CSC), chemotherapy and targeted medication sensitivity.ConclusionsOur comprehensive analysis of CRGs in OC showed their potential role in TME, clinicopathological characteristics, chemotherapy and targeted drug screening and prognosis. These discoveries could help us better understand CRGs in OC, as well as pave the path for novel ways to assess prognosis and design more effective immunotherapy strategies.
| S-EPMC9617300 | biostudies-literature
Project description:Pancreatic cancer consists one of tumors with the highest degree of malignancy and the worst prognosis. To date, immunotherapy has become an effective means to improve the prognosis of patients with pancreatic cancer. Long non-coding RNAs (lncRNAs) have also been associated with the immune response. However, the role of immune-related lncRNAs in the immune response of pancreatic cancer remains unclear. In this study, we identified immune-related lncRNA pairs through a new combinatorial algorithm, and then clustered and deeply analyzed the immune characteristics and functional differences between subtypes. Subsequently, the prognostic model of 3 candidate lncRNA pairs was determined by multivariate COX analysis. The results showed significant prognostic differences between the C1 and C2 subtypes, which may be due to the differential infiltration of CTL and NK cells and the activation of tumor-related pathways. The prognostic model of the 3 lncRNA pairs (AC244035.1_vs._AC063926.1, AC066612.1_vs._AC090124.1, and AC244035.1_vs._LINC01885) was established, which exhibits stable and effective prognostic prediction performance. These 3 lncRNA pairs may regulate the anti-tumor effect of immune cells through ion channel pathways. In conclusion, our research demonstrated the panoramic differences in immune characteristics between subtypes and stable prognostic models, and identified new potential targets for immunotherapy.
| S-EPMC8292792 | biostudies-literature
Project description:ObjectiveTumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB-based gene signature and molecular subtypes in gastric cancer.MethodsBased on differentially expressed genes (DEGs) between high- and low-TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease-free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB-related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms.ResultsHigh-TMB patients had prolonged survival duration. TMB-related DEGs were distinctly enriched in cancer- (MAPK, P53, PI3K-Akt, and Wnt pathways) and immune-related pathways (T cell selection and differentiation). The TMB-based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high-risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High-risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB-based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity.ConclusionCollectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision-making.
| S-EPMC9122698 | biostudies-literature
Project description:BackgroundEnhancer RNAs (eRNAs), the transcriptional products of active enhancers, are of great significance in the initial progression of cancers. However, the biological function and bioinformatics profiles of eRNA in gastric cancer remains largely enigmatic.MethodsFirstly, STAD were clustered into three subtypes with the data of eRNA expression from TCeA. Then we explored the difference of the tumor immune microenvironment, transcription levels, and transcription regulation among the three clusters. Finally, samples collected from 12 patients diagnosed with STAD were used to conduct qRT-PCR, verifying the conclusion based on network database.ResultsThe three clusters were detected to have different tumor microenvironments: Cluster A has an immune "cold" microenvironment. While cluster B features as more infiltration of immune cells, accompanied with higher expression of immune checkpoints such as PDCD1, LAG3, and TIGIT. Besides, Cluster C shows a higher stromal feature with B lineage, neutrophils, and fibroblasts. Further analyses indicated that CpG island methylation level of Cluster B is different from the other two clusters. Meanwhile, Cluster A and B showed significant enrichment of TP53 and KRAS mutation respectively while Cluster C has higher tumor mutation burden (TMB) and microsatellite instability (MSI). With the elaboration of transcriptional regulation of epigenetic clustering, we detected that Cluster A enriched in epithelial phenotype pathways. Cluster B enriched in cell-cell adhesion. Cluster C enriched in fibroblast proliferation. The clinical cohort show that Cluster B patients have lower interstitial cell characteristics and CAF infiltration.ConclusionWe identified three unique epigenetic clusters of STAD through the differential activation of super-enhancers, and identified Cluster B with a higher immune infiltrating and a better prognosis, which provides a novel understanding of eRNAs and potential clinical applicability of eRNA-based molecular subtypes in gastric cancer.
| S-EPMC9883414 | biostudies-literature