Discovery of tumor immune infiltration-related snoRNAs for predicting tumor immune microenvironment status and prognosis in lung adenocarcinoma.
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ABSTRACT:
SUBMITTER: Wan R
PROVIDER: S-EPMC8649667 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundImmune cells, vital components of tumor microenvironment, regulate tumor survival and progression. Lung adenocarcinoma (LUAD), the tumor with the highest mortality rate worldwide, reconstitutes tumor immune microenvironment (TIME) to avoid immune destruction. Data have shown that TIME influences LUAD prognosis and predicts immunotherapeutic efficacy. The related information about the role of TIME's characteristics in LUAD is limited.MethodsWe performed unsupervised consensus clustering via machine-learning techniques to identify TIME clusters among 1906 patients and gathered survival data. The characteristics of TIME clusters of LUAD were visualized by multi-omics analysis, pseudo-time dynamic analysis, and enrichment analysis. TIME score model was constructed by principal component analysis. Comprehensive analysis and validation were conducted to test the prognostic efficacy and immunotherapeutic response of TIME score.ResultsTIME clusters (A, B and C) were constructed and exhibited different immune infiltration states. Multi-omics analyses included significant mutated genes (SMG), copy number variation (CNV) and cancer stemness that were significantly different among the three clusters. TIME cluster A had a lower SMG, lower CNV, and lower stemness but a higher immune infiltration level compared to TIME clusters B and C. TIME score showed that patients in low TIME score group had higher overall survival rates, higher immune infiltration level and high expression of immune checkpoints. In validation cohorts, low TIME score subgroup had better drug sensitivity and favorable immunotherapeutic response.ConclusionWe constructed a stable model of LUAD immune microenvironment characteristics that may improve the prognostic accuracy of patients, provide improved explanations of LUAD responses to immunotherapy, and provide new strategies for LUAD treatment.
| S-EPMC8851380 | biostudies-literature
Project description:BackgroundReprogramming of lipid metabolism is closely associated with tumor development, serving as a common and critical metabolic feature that emerges during tumor evolution. Meanwhile, immune cells in the tumor microenvironment also undergo aberrant lipid metabolism, and altered lipid metabolism also has an impact on the function and status of immune cells, further promoting malignant biological behavior. Consequently, we focused on lipid metabolism-related genes for constructing a novel prognostic marker and evaluating immune status in prostate cancer.MethodsInformation about prostate cancer patients was obtained from TCGA and GEO databases. The NMF algorithm was conducted to identify the molecular subtypes. The least absolute shrinkage and selection operator (Lasso) regression analysis was applied to establish a prognostic risk signature. CIBERSORT algorithm was used to calculate immune cell infiltration levels in prostate cancer. External clinical validation data were used to validate the results.ResultsProstate cancer samples were divided into two subtypes according to the NMF algorithm. A six-gene risk signature (PTGS2, SGPP2, ALB, PLA2G2A, SRD5A2, and SLC2A4) was independent of prognosis and showed good stability. There were significant differences between risk groups of patients with respect to the infiltration of immune cells and clinical variables. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR.ConclusionWe constructed a six-gene signature with lipid metabolism in prostate cancer to effectively predict prognosis and reflect immune microenvironment status.
| S-EPMC9467780 | biostudies-literature
Project description:The neutrophils exhibit both anti-tumor and pro-tumor effects in cancers. The correlation between neutrophils and tumor development in lung adenocarcinoma (LUAD) is still uncertain, possibly due to a lack of specific neutrophil infiltration evaluation methods. In this study, we identified 30 hub genes that were significantly associated with neutrophil infiltration in LUAD through data mining, survival analysis, and multiple tumor-infiltrating immune cells (TICs) analysis, including TIMER, CIBERSORT, QUANTISEQ, XCELL, and MCPCOUNTER. Consensus clustering analysis showed that these 30 hub genes were correlated with clinical features in LUAD. We further developed a neutrophil scoring system based on these hub genes. The neutrophil score was significantly correlated with prognosis and tumor immune microenvironment (TIME) in LUAD. It was also positively associated with PD-L1 expression and negatively associated with tumor mutational burden (TMB). When combined with the neutrophil score, the predictive capacity of PD-L1 and TMB for prognosis was significantly improved. Thus, the 30 hub genes might play an essential role in the interaction of neutrophils and LUAD, and the neutrophil scoring system might effectually assess the infiltration of neutrophils. Furthermore, we verified the expression of these 30 genes in the LUAD tumor tissues collected from our department. We further found that overexpressed TNFAIP6 and TLR6 and downregulated P2RY13, SCARF1, DPEP2, PRAM1, CYP27A1, CFP, GPX3, and NCF1 in LUAD tissue might be potentially associated with neutrophils pro-tumor effects. The following in vitro experiments demonstrated that TNFAIP6 and TLR6 were significantly overexpressed, and P2RY13 and CYP27A1 were significantly downregulated in LUAD cell lines, compared to BEAS-2B cells. Knocking down TNFAIP6 in A549 and PC9 resulted in the upregulation of FAS, CCL3, and ICAM-1, and the downregulation of CCL2, CXCR4, and VEGF-A in neutrophils when co-culturing with the conditioned medium (CM) from LUAD cells. Knocking down TNFAIP6 in LUAD also led to an elevated early apoptosis rate of neutrophils. Therefore, overexpressed TNFAIP6 in LUAD cancer cells might lead to neutrophils "N2" polarization, which exhibited pro-tumor effects. Further research based on the genes identified in this pilot study might shed light on neutrophils' effects on LUAD in the future.
| S-EPMC10777728 | biostudies-literature
Project description:Background: Notch signaling is a key regulator of immune cell differentiation and linked to autoimmune diseases, tumorigenesis and tumor-induced immunomodulation. An abnormally activated Notch signaling pathway contributes to almost all of the key features of cancer, including tumor angiogenesis, stemness, and epithelial-mesenchymal transition. Consequently, we investigated Notch pathway-related genes for developing prognostic marker and assessing immune status in bladder cancer. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to analyze RNA-seq data for bladder cancer. Cluster subtypes were identified using the NMF algorithm. In order to establish a prognostic risk signature, the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis was utilized. GSEA was carried out to investigate the molecular mechanisms. Immune cell infiltration levels in bladder cancer were calculated using the CIBERSORT algorithm. External clinical tissue samples were used to validate the expression levels of signature genes. Results: Based on the NMF algorithm, bladder cancer samples were divided into two cluster subtypes and displayed different survival outcome and immune microenvironment. A six-gene risk signature (DTX3L, CNTN1, ENO1, GATA3, MAGEA1, and SORBS2) was independent for prognosis and showed good stability. The infiltration of immune cells and clinical variables were significantly different among the risk groups of patients. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR. Conclusion: We established a 6-gene signature associated with Notch pathway in bladder cancer to effectively predict prognosis and reflect immune microenvironment status.
| S-EPMC9279929 | biostudies-literature
Project description:Lung adenocarcinoma (LUAD), a malignancy with high incidence and mortality rates worldwide, contains multiple genomic and epigenomic abnormalities. And the useful tumor markers associated with these abnormalities need further investigation. Whereas apoptosis is a form of programmed cell death, the expression of apoptosis-related genes in LUAD and its relationship with prognosis is unclear. In the present study, we identified 64 differentially expressed apoptosis-related genes (DEARGs) that were differentially expressed between LUAD tissue and normal lung tissue. Based on these DEARGs, all LUAD cases were classified into two subtypes using The Cancer Genome Atlas (TCGA) cohort to assess the prognostic value of apoptosis-related genes for survival. An 11-gene signature was established by applying the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression method to construct a multigene prediction model and classify all LUAD patients in the TCGA cohort into high or low AS-score groups. Patients in the low AS-score group had significantly higher survival and prognosis than those in the high AS-score group. Taking the median risk score of the AS-score, LUAD patients in the GSE68465 cohort were divided into two risk groups, low and high. The overall survival (OS) time was longer in the low AS-score group. Combined with clinical characteristics, the AS-score was an independent predictor of LUAD patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that the differential genes between the two groups were mainly enriched in cellular immunity. Further analysis revealed higher immune checkpoint protein expression and higher tumor mutational burden (TMB) in the high AS-score group, suggesting better efficacy of immunotherapy in the high AS-score group than the low AS-score group. And the high AS-score group was better in chemotherapy and targeted therapy efficiency. In conclusion, the AS-score constructed based on apoptosis-related genes can predict the prognosis of LUAD patients and provide some guidance for the antitumor treatment of LUAD patients.
| S-EPMC9094710 | biostudies-literature
Project description:The role of reactive oxygen species (ROS) is critical in the emergence and progression of lung adenocarcinoma (LUAD), affecting cell survival, proliferation, angiogenesis, and metastasis. Further investigations are needed to elucidate these effects' precise pathways and devise therapeutic approaches targeting ROS. Moreover, the expression pattern and clinical significance of the ROS-related genes in LUAD remain elusive. Through comprehensive analysis incorporating 1494 LUAD cases from The Cancer Genome Atlas, six Gene Expression Omnibus series, and a Chinese LUAD cohort, we identified a ROS-related signature with substantial predictive value in various LUAD patient cohorts. The ROS-related signature has demonstrated a significant negative relationship with antitumor immunity and dendritic cell maturation and activation. Moreover, The ROS-related signature showed predictive value on immunotherapy outcomes across multiple types of solid tumors, including LUAD. These findings reinforce the ROS-related signature as a predictive tool for LUAD and provide new insights into its link with antitumor immunity and immunotherapy efficacy. These results have implications for refining clinical assessments and tailoring immunotherapeutic strategies for patients with LUAD.
| S-EPMC10988302 | biostudies-literature
Project description:N7-Methylguanosine (m7G) modification holds significant importance in regulating posttranscriptional gene expression in epigenetics. Long non-coding RNAs (lncRNAs) have been demonstrated to play a crucial role in cancer progression. m7G-related lncRNA may be involved in the progression of pancreatic cancer (PC), although the underlying mechanism of regulation remains obscure. We obtained RNA sequence transcriptome data and relevant clinical information from the TCGA and GTEx databases. Univariate and multivariate Cox proportional risk analyses were performed to build a twelve-m7G-associated lncRNA risk model with prognostic value. The model was verified using receiver operating characteristic curve analysis and Kaplan–Meier analysis. The expression level of m7G-related lncRNAs in vitro was validated. Knockdown of SNHG8 increased the proliferation and migration of PC cells. Differentially expressed genes between high- and low-risk groups were identified for gene set enrichment analysis, immune infiltration, and potential drug exploration. We conducted an m7G-related lncRNA predictive risk model for PC patients. The model had independent prognostic significance and offered an exact survival prediction. The research provided us with better knowledge of the regulation of tumor-infiltrating lymphocytes in PC. The m7G-related lncRNA risk model may serve as a precise prognostic tool and indicate prospective therapeutic targets for PC patients.
| S-EPMC10217316 | biostudies-literature
Project description:BackgroundGastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.ObjectiveWe aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.Methods and resultsIn this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the "The Cancer Genome Atlas (TCGA)". Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.ConclusionsNecroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.
| S-EPMC9646549 | biostudies-literature
Project description:Objective: Because of the modest immunotherapeutic response among ovarian carcinoma (OC) patients, it is significant to evaluate antitumor immune response and develop more effective precision immunotherapeutic regimens. Here, this study aimed to determine diverse immune subtypes of OC. Methods: This study curated the expression profiles of prognostic immunologically relevant genes and conducted consensus clustering analyses for determining immune subtypes among OC patients in TCGA cohort. With Boruta algorithm, characteristic genes were screened for conducting an immune scoring system through principal component analysis algorithm. The single-sample gene set enrichment analysis and ESTIAMTE methods were adopted for quantifying the immune infiltrates and responses to chemotherapeutic agents were estimated with pRRophetic algorithm. Two immunotherapeutic cohorts were used for investigating the efficacy of immune score in predicting therapeutic benefits. Results: Two immune subtypes were conducted among 377 OC patients. Immune subtype 2 was characterized by worse clinical prognosis, more frequent genetic variations and mutations, enhanced immune infiltrates, and increased expression of MHC molecules and programmed cell death protein 1/programmed death ligand 1 (PD-1/PD-L1). In total, 30 prognosis-relevant characteristic immune subtype-derived genes were identified for constructing the immune score of OC patients. High immune score was linked with more dismal prognosis, decreased immune infiltrations, and expression of MHC molecules. High immune score presented favorable sensitivity to doxorubicin and vinorelbine and reduced sensitivity to cisplatin. In addition, immune score possessed the potential in predicting benefits from anti-PD-1/PD-L1 therapy. Conclusion: Collectively, our findings propose two complex and diverse immune subtypes of OC. Quantitative assessment of immune subtypes in individual patients strengthens the understanding of tumor microenvironment features and promotes more effective immunotherapeutic regimens.
| S-EPMC8977982 | biostudies-literature
Project description:BackgroundColon cancer (CC) is the leading cause of tumour-related death worldwide. SnoRNA plays a critical role in the tumour microenvironment. The tumour microenvironment can be shaped by tumour-infiltrating immune cells, which control the destiny of immunotherapy efficacy. This study uniquely focused on snoRNAs derived from immune cells to identify new biomarkers for immune landscape.MethodsA novel computational framework was initiated for identifying tumour immune infiltration-associated snoRNAs (TIIsno) signatures and developed a TIIsno score model from integrative snoRNA profiling analysis of 21 purified immune cell lines, 43 colon cancer cell lines, and three datasets (training, test, real-world validation set).FindingsOur study found that a high TIIsno score was associated with poor CC prognosis. TIIsno scores were seen to be negatively correlated with (I) the infiltration level of most immune cells, (II) the inhibitory immune checkpoints expression level, and (III) the immune score. These findings, taken together with the observation that TIIsno score is lower in MSI-H patients, suggests that patients with a low TIIsno score may have a better response to immunotherapy.InterpretationIn conclusion, we successfully identified TIIsno and constructed a TIIsno score model, a new potential biomarker of immunotherapy response, which can effectively predict the prognosis of CC patients as well.FundingNational Key R & D Program of China, National Natural Science Foundation of China, key projects from the Nature Science Foundation of Hunan Province, projects from Beijing CSCO Clinical Oncology Research Foundation, Fundamental Research Funds for the Central Universities of Central South University.
| S-EPMC8844792 | biostudies-literature