Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-omics analysis reveals PUS1 triggered malignancy and correlated with immune infiltrates in NSCLC.

ABSTRACT: Non-small cell lung cancer (NSCLC) is the main pathological type of lung cancer. In this study, multi-omics analysis revealed a significant increase of pseudouridine synthase 1 (PUS1) in NSCLC and the high expression of PUS1 was associated with shorter OS (Overall Survival), PFS (Progression Free Survival), and PPS (Post Progression Survival) of NSCLC patients. Clinical subgroup analysis showed that PUS1 may be involved in the occurrence and development of NSCLC. Besides, TIMER, ESTIMATE, and IPS analysis suggested that PUS1 expression was associated with immune cell infiltration, and the expression of PUS1 was significantly negatively correlated with DC cell infiltration. GESA analysis also indicated PUS1 may involve in DNA_REPAIR, E2F_TARGETS, MYC_TARGETS_V2, G2M_CHECKPOINT and MYC_TARGETS_V1 pathways and triggered NSCLC malignancy through MCM5 or XPO1. Furthermore, PUS1 may be a potential target for NSCLC therapy.

SUBMITTER: Tan Y

PROVIDER: S-EPMC10683629 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Multi-omics analysis reveals PUS1 triggered malignancy and correlated with immune infiltrates in NSCLC.

Tan Yonghuang Y Wang Zhaotong Z Wang Yingzhao Y Tian Xiaolu X Huang Yunru Y Wu Guoyong G Lu Jianjun J

Aging 20231102 21

Non-small cell lung cancer (NSCLC) is the main pathological type of lung cancer. In this study, multi-omics analysis revealed a significant increase of pseudouridine synthase 1 (PUS1) in NSCLC and the high expression of PUS1 was associated with shorter OS (Overall Survival), PFS (Progression Free Survival), and PPS (Post Progression Survival) of NSCLC patients. Clinical subgroup analysis showed that PUS1 may be involved in the occurrence and development of NSCLC. Besides, TIMER, ESTIMATE, and IP ...[more]

PMID: 37925171

Similar Datasets

Multi-Omics Profiling Unveils the Complexity and Dynamics of Immune Infiltrates in Intrahepatic Cholangiocarcinoma.

Project description:Intrahepatic cholangiocarcinoma (ICC) is a highly heterogeneous malignancy. The reasons behind the global rise in the incidence of ICC remain unclear, and there exists limited knowledge regarding the immune cells within the tumor microenvironment (TME). In this study, a more comprehensive analysis of multi-omics data was performed using machine learning methods. The study found that the immunoactivity of B cells, macrophages, and T cells in the infiltrating immune cells of ICC exhibits a significantly higher level of immunoactivity in comparison to other immune cells. During the immune sensing and response, the effect of antigen-presenting cells (APCs) such as B cells and macrophages on activating NK cells was weakened, while the effect of activating T cells became stronger. Simultaneously, four distinct subpopulations, namely BLp, MacrophagesLp, BHn, and THn, have been identified from the infiltrating immune cells, and their corresponding immune-related marker genes have been identified. The immune sensing and response model of ICC has been revised and constructed based on our current comprehension. This study not only helps to deepen the understanding the heterogeneity of infiltrating immune cells in ICC, but also may provide valuable insights into the diagnosis, evaluation, treatment, and prognosis of ICC.

| S-EPMC11504529 | biostudies-literature

Multi-omics analysis reveals neoantigen-independent immune cell infiltration in copy-number driven cancers.

Project description:To realize the full potential of immunotherapy, it is critical to understand the drivers of tumor infiltration by immune cells. Previous studies have linked immune infiltration with tumor neoantigen levels, but the broad applicability of this concept remains unknown. Here, we find that while this observation is true across cancers characterized by recurrent mutations, it does not hold for cancers driven by recurrent copy number alterations, such as breast and pancreatic tumors. To understand immune invasion in these cancers, we developed an integrative multi-omics framework, identifying the DNA damage response protein ATM as a driver of cytokine production leading to increased immune infiltration. This prediction was validated in numerous orthogonal datasets, as well as experimentally in vitro and in vivo by cytokine release and immune cell migration. These findings demonstrate diverse drivers of immune cell infiltration across cancer lineages and may facilitate the clinical adaption of immunotherapies across diverse malignancies.

| S-EPMC5882811 | biostudies-other

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis.

Project description:We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy. Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched normal samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed. We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (p = 0.02), CD8+ T cells (p = 0.09), CD4+ memory activated T cells (p = 0.07), and neutrophils (p = 0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (p = 0.05), CECR7 (p < 0.001), TRIM16 (p = 0.003), and IL7R (p = 0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes. Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L were associated with TMB and promoted antitumor immunity in HCC.

| S-EPMC7928364 | biostudies-literature

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer.

Project description:Triple negative breast cancer (TNBC) is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with non-tumorigenic epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method that had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFβ signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. We observed overexpression of PTEN, which antagonizes the PI3K/AKT/mTOR pathway, and MYC, which downregulates the same pathway in the HCC1937 cells relative to the MDA-MB-231 cells. The PI3K/AKT/mTOR and Wnt/beta-catenin pathways are both downregulated in HCC1937 cells relative to MDA-MB-231 cells, which likely explains the divergent sensitivities of these cell lines to inhibitors of downstream signaling pathways. The DNA methylation and RNAseq data is freely available via GEO GSE171958 and the proteomics data is available via the ProteomeXchange PXD025238.

| S-EPMC8504614 | biostudies-literature

Prognostic biomarker DARS2 correlated with immune infiltrates in bladder tumor.

Project description:BackgroundDARS2 is a pivotal member of the Aminoacyl-tRNA synthetases family that is critical for regulating protein translation. However, the biological role of DARS2 in bladder cancer remains elusive.MethodsWe analyzed the correlation between DARS2 expression and prognosis, tumor stage, and immune infiltration in bladder cancer using The Cancer Genome Atlas (TCGA) database. We validated findings in clinical samples from The First Affiliated Hospital of Nanchang University and explored the biological functions of DARS2 using cell and animal models.ResultsWe found DARS2 to be upregulated in bladder cancer, associated with tumor progression and poor prognosis. Immune infiltration analysis suggested that DARS2 may facilitate immune evasion by modulating PD-L1. Cell and animal experiments validated that DARS2 knockdown and overexpress can inhibit or increase cancer cell proliferation, metastasis, tumorigenesis, immune escape, and PD-L1 levels.ConclusionsOur study reveals DARS2 as a potential prognostic biomarker and immunotherapy target in BLCA.

| S-EPMC10827901 | biostudies-literature

A spatial multi-omics atlas of the human lung reveals a novel immune cell survival niche

Project description: Not available

| S-SUBS17 | biostudies-other

Multi-Omics Analysis Reveals Aberrant Gut-Metabolome-Immune Network in Schizophrenia.

Project description:Schizophrenia (SCZ) is associated with several immune dysfunctions, including elevated levels of pro-inflammatory cytokines. Microorganisms and their metabolites have been found to regulate the immune system, and that intestinal microbiota is significantly disturbed in schizophrenic patients. To systematically investigate aberrant gut-metabolome-immune network in schizophrenia, we performed an integrative analysis of intestinal microbiota, serum metabolome, and serum inflammatory cytokines in 63 SCZ patients and 57 healthy controls using a multi-omics strategy. Eighteen differentially abundant metabolite clusters were altered in patients displayed higher cytokine levels, with a significant increase in pro-inflammatory metabolites and a significant decrease in anti-inflammatory metabolites (such as oleic acid and linolenic acid). The bacterial co-abundance groups in the gut displayed more numerous and stronger correlations with circulating metabolites than with cytokines. By integrating these data, we identified that certain bacteria might affect inflammatory cytokines by modulating host metabolites, such as amino acids and fatty acids. A random forest model was constructed based on omics data, and seven serum metabolites significantly associated with cytokines and α-diversity of intestinal microbiota were able to accurately distinguish the cases from the controls with an area under the receiver operating characteristic curve of 0.99. Our results indicated aberrant gut-metabolome-immune network in SCZ and gut microbiota may influence immune responses by regulating host metabolic processes. These findings suggest a mechanism by which microbial-derived metabolites regulated inflammatory cytokines and insights into the diagnosis and treatment of mental disorders from the microbial-immune system in the future.

| S-EPMC8927969 | biostudies-literature

Prognostic Role of Tumor Mutation Burden Combined With Immune Infiltrates in Skin Cutaneous Melanoma Based on Multi-Omics Analysis.

Project description:Tumor mutation burden (TMB) and tumor infiltrating lymphocytes have been well-recognized as molecular determinants of immunotherapeutic responsiveness in many types of cancer. However, the relationship between TMB with immune infiltrates and their prognostic role are reported occasionally in skin cutaneous melanoma (SKCM). We obtained the somatic mutation data and transcriptome profiles of 454 SKCM patients from The Cancer Genome Atlas (TCGA) database, and analyzed the mutation profiles using "maftools" package. Correlation analysis revealed that lower TMB levels conferred poor survival outcomes, associated with lower age and advanced pathological stage. Differential analysis was conducted to the genome expression between two TMB groups using "limma" package, and we identified four hub TMB-related immune genes including CNTFR, CRABP2, GAL, and PAEP. We further analyzed the underlying relationships of the copy number variations (CNVs) of four hub genes with immune infiltrates in SKCM microenvironment through TIMER database. The results indicated that diverse forms of CNVs carried by hub genes could commonly inhibit immune infiltrates. Based on the CIBERSORT method, we compared the proportions of 22 immune cells in two TMB groups and assessed their prognostic value. The data revealed that infiltrations levels of regulatory T (Treg) cell and dendritic activated cells in high-TMB group were lower than that in low-TMB group, while M1 and M2 macrophages showed the opposite trend, especially the levels of neutrophil and macrophage correlated positively with prognosis of SKCM. Finally, we constructed a TMB Prognostic Index (TMBPI) to evaluate the predictive accuracy of the four hub TMB-related immune genes. The ROC curve was drawn to assess the predictive accuracy with AUC = 0.664 and higher TMBPI conferred poor survival outcomes, which warranted further investigation and larger samples to validate.

| S-EPMC7683772 | biostudies-literature

DISC1 as a prognostic biomarker correlated with immune infiltrates in gastric cancer.

Project description:Multiple mental diseases could arise in people who have the disrupted in schizophrenia 1 (DISC1) gene. However, it was unknown how DISC1 might contribute to the development of tumors and immune responses. We extracted data from the Cancer Genome Atlas (TCGA) and TISIDB databases from stomach adenocarcinoma (STAD) patients, which revealed that DISC1 overexpression was closely associated with tumor histological type (mucinous vs. tubular, OR = 2.860, CI = 1.423-5.872, p = 0.004), as well as tumor stage and grade. Furthermore, the higher the DISC1 expression, the lower the overall 10-year survival rate. Patients with low DISC1 expression had a significantly longer progression-free interval (PFI) and disease-specific survival (DSS) than patients with high DISC1 expression. However, patients with higher DISC1 expression in the T3&T4, N0&N1 and M0 subgroups had poorer prognosis in terms of OS, DSS and PFI, as could be seen in the subgroup survival analysis. Public datasets were used to predict lncRNA-miRNA-DISC1 regulation. DISC1 was significantly up-regulated in GC(gastric cancer), and its expression levels showed a moderate to strong positive correlation with infiltration levels of effector memory T cells (Tem) and central memory T cells (Tcm), and a negative correlation was observed with Th17 cells and NK CD56bright cells. In addition, concomitant with the high expression of the DISC1 gene was a decrease in MHC-I (Major Histocompatibility Complex-I)expression and an increase in MHC-II expression, and altered chemokine expression. The upregulation of CXCL12 and CXCR4 expression could be caused by an increase in DISC1 expression. The above expression variability and correlation suggest a role for DISC1 in regulating tumor immunity in GC. These findings suggest that high expression of DISC1 could be an independent prognostic factor for GC.

| S-EPMC10161376 | biostudies-literature

PODN is a prognostic biomarker and correlated with immune infiltrates in osteosarcoma.

Project description:BackgroundOsteosarcoma was the most common primary bone malignancy in children and adolescents. It was imperative to identify effective prognostic biomarkers for this cancer. This study was aimed to identify potential crucial genes of osteosarcoma by integrated bioinformatics analysis.MethodsIdentification of differentially expressed genes from public data gene expression profiles (GSE42352), functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction and module analysis, Cox regression and survival analysis was conducted.ResultsTotally 17 co-differential genes were found to be differentially expressed. These genes were enriched in biological processes, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) pathway of inflammatory immune response. PPI network was constructed with 63 differentially expressed genes that co-existed between the test set and the validation set. The area under the receiver operating characteristic curve (AUC value) was 0.855, which indicated that the expression of PODN had a good diagnostic value for osteosarcoma. Furthermore, Cox regression and survival analysis revealed 5 genes were statistically significant.ConclusionsPODN was regarded as a potential biomarker for the diagnosis and prognosis of osteosarcoma, ACTA2, COL6A1, FAP, OLFML2B and COL6A3, can be used as potential prognostic indicators for osteosarcoma.

| S-EPMC8285818 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data