scholarly journals Prognostic and immune regulating roles of YIF1B in Pan-Cancer: a potential target for both survival and therapy response evaluation

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Jun Liu ◽  
Zheng Chen ◽  
Pingsen Zhao ◽  
Wenli Li
Keyword(s):  
Tumor Growth ◽  
Membrane Trafficking ◽  
Serotonin Receptor ◽  
Immune Cell ◽  
Therapy Response ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Poor Overall Survival ◽  
Cancer Types ◽  
Spearman Test

Abstract The neurotransmitter, serotonin has emerged as a tumor growth factor and immune response regulator through complex signaling pathways. Yip1 Interacting Factor Homolog B (YIF1B) is a membrane protein involved in serotonin receptor (HTR) membrane trafficking and signal transmission in neuropathy. Participation of YIF1B in serotonin-induced tumor growth and immune regulation has not been previously investigated. Data for analysis of YIF1B mRNA expression were downloaded from the website portals: The Cancer Genome Atlas (TCGA), GTEx, Cancer Cell Line Encyclopedia (CCLE) and International Cancer Genome Consortium (ICGC), including clinical and mutational information. Survival analysis included the Kaplan–Meier method for calculation of the cumulative incidence of the survival event and the log rank method for comparison of survival curves between groups. Infiltration levels of immune cells were calculated and correlated with YIF1B expression using the Spearman correlation test to evaluate significance. Further correlation analyses between YIF1B expression and mutation indicators such as tumor mutation burden (TMB), microsatellite instability (MSI), and mismatch repair (MMR) were also examined by the Spearman test. YIF1B expression was elevated in most cancer types and this high expression was indicative of poor overall survival (OS) and death-specific survival. In breast invasive carcinoma (BRCA) and liver hepatocellular carcinoma (LIHC), high YIF1B expression correlated with a poor disease-free interval (DFI), indicating a role in malignancy progression. There was a positive relationship between YIF1B expression and immune cell infiltration in several cancer types, and YIF1B also positively correlated with TMB, MSI, and methylation in some cancer types, linking its expression to possible evaluation of therapy response. The bioinformatics analyses have, therefore, established YIF1B as a good biomarker for prognostic and therapeutic evaluation.

scholarly journals A Pan-Cancer Analysis of SMARCA4 Alterations in Human Cancers

2021 ◽  
Vol 12 ◽  
Author(s):  
Ling Peng ◽  
Jisheng Li ◽  
Jie Wu ◽  
Bin Xu ◽  
Zhiqiang Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Tumor Immunity ◽  
Immune Cell ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Poor Overall Survival ◽  
Atpase Subunit ◽  
Human Cancers ◽  
Cancer Types

BackgroundSMARCA4, the essential ATPase subunit of SWI/SNF chromatin remodeling complex, regulates transcription through the control of chromatin structure and is increasingly thought to play significant roles in human cancers. This study aims to explore the potential role of SMARCA4 with a view to providing insights on pathologic mechanisms implicated here.MethodsThe potential roles of SMARCA4 in different tumors were explored based on The Cancer Genome Atlas (TCGA), Genotype-tissue expression (GTEx), Tumor Immune Estimation Resource (TIMER), and Gene Set Enrichment Analysis (GSEA) datasets. The expression difference, mutation and phosphorylation status, survival, pathological stage, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), tumor microenvironment (TME), and immune cell infiltration related to SMARCA4 were analyzed.ResultsHigh expression levels of SMARCA4 were observed in most cancer types. SMARCA4 expression in tumor samples correlates with poor overall survival in several cancers. Lung adenocarcinoma cases with altered SMARCA4 showed a poorer prognosis. Enhanced phosphorylation levels of S613, S695, S699, and S1417 were observed in several tumors, including breast cancer. SMARCA4 correlated with tumor immunity and associated with different immune cells and genes in different cancer types. TMB, MSI, MMR, and DNA methylation correlated with SMARCA4 dysregulation in cancers. SMARCA4 expression was negatively associated with CD8+ T-cell infiltration in several tumors. Furthermore, the SWI/SNF superfamily-type complex and ATPase complex may be involved in the functional mechanisms of SMARCA4, albeit these data require further confirmation.ConclusionsOur study offers a comprehensive understanding of the oncogenic roles of SMARCA4 across different tumors. SMARCA4 may correlate with tumor immunity.

scholarly journals Identification of RB1 Gene as a Immune-Related Prognostic Signature Based on Tumor Mutation Burdens in Bladder Cancer

2021 ◽  
Author(s):  
Ming Chen ◽  
Hong Cheng ◽  
Tiange Wu ◽  
Zeping Gui ◽  
Ying Gao ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Poor Overall Survival ◽  
Mutant Type

Abstract Background: Bladder cancer (BC) is known as the eleventh most common malignant tumor all over the world, for either males or females. Developing effective regimens targeting more promising biomarkers aiming for better prognosis are required. Immune checkpoint inhibitors (ICI) have been demonstrated as a prospective and practical means to resist cancers. Theoretically, adequate infiltration of immune cells indicates more immunotherapy targets and may promise better prognosis.Methods: Full transcriptome data (n=433), clinical information (n=581) and mutation sequencing (n=412) were obtained freely from The Cancer Genome Atlas and independent mutation sequencing data of 101 samples were acquired from International Cancer Genome Consortium. Statistical processing was conducted using R packages with R x64 4.0.2. Gene biologically functional research was performed with gene set enrichment analysis (GSEA) based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database. 22 types of immune cell infiltration were assessed and calculated in 398 samples of BC tumors.Results: Tumor mutation burdens (TMB) of mutant type groups were higher than wild type groups for 19 genes, except for FGFR3 and CREBBP verifying that genomic mutation associates positively with TMB in BC tumor. Kaplan-Meier analysis showed high mutation frequency on RB1 had a negative effect on prognosis of BC patients and RB1 was an independent prognostic factor (p=0.004, HR=1.776) in BC. It was also demonstrated that RB1 mainly participate in singling pathways of cell proliferation and cell cycle. Proportions and correlation of 22 types of immune cells in 433 samples were determined. Immune cells with similar function are inclined to co-exist in tumor microenvironment of BC. Among them, regulatory T cells (Tregs) were detected as a negatively correlated type immune cell to mutation of RB1 that probably increases the incidence of tumor immune escaping in BC.Conclusion: RB1 can be identified as an independent prognostic predictor, and there is a chance for contribution to poor overall survival as the mutation occurs. What's more, mutation of RB1 also functions as a biomarker that represses the infiltration of Tregs, increasing the incidence of tumor immune escaping in BC.

scholarly journals Pan-Cancer Analysis of PIMREG as a Biomarker for the Prognostic and Immunological Role

2021 ◽  
Vol 12 ◽  
Author(s):  
Hua Zhu ◽  
Xinyao Hu ◽  
Yingze Ye ◽  
Zhihong Jian ◽  
Yi Zhong ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Chemokine Receptors ◽  
Antigen Processing ◽  
Immune Cell ◽  
Nk Cell ◽  
Cell Lineage ◽  
Cell Receptor ◽  
The Cancer Genome Atlas ◽  
Cancer Types ◽  
Pan Cancer

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) localizes to the nucleus and can significantly elevate the nuclear localization of clathrin assembly lymphomedullary leukocythemia gene. Although there is some evidence to support an important action for PIMREG in the occurrence and development of certain cancers, currently no pan-cancer analysis of PIMREG is available. Therefore, we intended to estimate the prognostic predictive value of PIMREG and to explore its potential immune function in 33 cancer types. By using a series of bioinformatics approaches, we extracted and analyzed datasets from Oncomine, The Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia (CCLE) and the Human Protein Atlas (HPA), to explore the underlying carcinogenesis of PIMREG, including relevance of PIMREG to prognosis, microsatellite instability (MSI), tumor mutation burden (TMB), tumor microenvironment (TME) and infiltration of immune cells in various types of cancer. Our findings indicate that PIMREG is highly expressed in at least 24 types of cancer, and is negatively correlated with prognosis in major cancer types. In addition, PIMREG expression was correlated with TMB in 24 cancers and with MSI in 10 cancers. We revealed that PIMREG is co-expressed with genes encoding major histocompatibility complex, immune activation, immune suppression, chemokine and chemokine receptors. We also found that the different roles of PIMREG in the infiltration of different immune cell types in different tumors. PIMREG can potentially influence the etiology or pathogenesis of cancer by acting on immune-related pathways, chemokine signaling pathway, regulation of autophagy, RIG-I like receptor signaling pathway, antigen processing and presentation, FC epsilon RI pathway, complement and coagulation cascades, T cell receptor pathway, NK cell mediated cytotoxicity and other immune-related pathways. Our study suggests that PIMREG can be applied as a prognostic marker in a variety of malignancies because of its role in tumorigenesis and immune infiltration.

scholarly journals Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

scholarly journals ASF1B Promotes Oncogenesis in Lung Adenocarcinoma and Other Cancer Types

2021 ◽  
Vol 11 ◽  
Author(s):  
Wencheng Zhang ◽  
Zhouyong Gao ◽  
Mingxiu Guan ◽  
Ning Liu ◽  
Fanjie Meng ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Regulatory Subunit ◽  
Cell Cycle Distribution ◽  
Cancer Type ◽  
Dependent Manner ◽  
Cancer Types

Anti-silencing function 1B histone chaperone (ASF1B) is known to be an important modulator of oncogenic processes, yet its role in lung adenocarcinoma (LUAD) remains to be defined. In this study, an integrated assessment of The Cancer Genome Atlas (TCGA) and genotype-tissue expression (GTEx) datasets revealed the overexpression of ASF1B in all analyzed cancer types other than LAML. Genetic, epigenetic, microsatellite instability (MSI), and tumor mutational burden (TMB) analysis showed that ASF1B was regulated by single or multiple factors. Kaplan-Meier survival curves suggested that elevated ASF1B expression was associated with better or worse survival in a cancer type-dependent manner. The CIBERSORT algorithm was used to evaluate immune microenvironment composition, and distinct correlations between ASF1B expression and immune cell infiltration were evident when comparing tumor and normal tissue samples. Gene set enrichment analysis (GSEA) indicated that ASF1B was associated with proliferation- and immunity-related pathways. Knocking down ASF1B impaired the proliferation, affected cell cycle distribution, and induced cell apoptosis in LUAD cell lines. In contrast, ASF1B overexpression had no impact on the malignant characteristics of LUAD cells. At the mechanistic level, ASF1B served as an indirect regulator of DNA Polymerase Epsilon 3, Accessory Subunit (POLE3), CDC28 protein kinase regulatory subunit 1(CKS1B), Dihydrofolate reductase (DHFR), as established through proteomic profiling and Immunoprecipitation-Mass Spectrometry (IP-MS) analyses. Overall, these data suggested that ASF1B serves as a tumor promoter and potential target for cancer therapy and provided us with clues to better understand the importance of ASF1B in many types of cancer.

scholarly journals KDM1A Identified as a Potential Oncogenic Driver and Prognostic Biomarker via Multi-Omics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Lingyue Li ◽  
Yiyu Wang ◽  
Yuan Mou ◽  
Hao Wu ◽  
Ye Qin
Keyword(s):  
Immune Cell ◽  
Prognostic Biomarker ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Th2 Cells ◽  
Th1 Cell ◽  
Transport Pathways ◽  
Epigenetic Factor ◽  
Omics Analysis ◽  
Cancer Types

Background. Lysine-specific demethylase 1A (KDM1A) is a histone demethylation enzyme and a crucial epigenetic factor for multiple pathological pathways that mediate carcinogenesis and immunogenicity. Although increasing evidence supposes the association between KDM1A and cancers, no systematic multi-omics analysis of KDM1A is available. Methods. We systematically evaluated the KDM1A expression of various cancer and normal tissues and the unique relationship between KDM1A expression and prognosis of cancer cases based on The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The genetic variations, phosphorylation, and DNA methylation of KDM1A were analyzed via various tools. We further analyzed the correlation of KDM1A expression and fibroblasts and immune cell infiltration score of TCGA samples via TIMER2.0. Results. KDM1A was highly expressed in 17 types of total 33 cancers, while it expressed low levels in only 4 cancers. High KDM1A expression was associated with worse survival status in various cancers. KDM1A expression was positively correlated with the cancer-associated fibroblasts and myeloid-derived suppressor cells infiltration levels in most cancer types. Additionally, KDM1A in most cancer types was negatively correlated with Th1 cell infiltration and positively correlated with Th2 cells. Moreover, spliceosome, cell cycle, and RNA transport pathways were involved in the functional mechanisms of KDM1A via enrichment analysis. Conclusions. Our study describes the epigenetic factor KDM1A as an oncogene and prognostic biomarker. Our findings provide valuable guidance for further analysis of KDM1A function in pathogenesis and potential clinical treatment.

scholarly journals OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers

2020 ◽  
Vol 49 (D1) ◽  
pp. D1289-D1301 ◽  
Author(s):  
Tao Wang ◽  
Shasha Ruan ◽  
Xiaolu Zhao ◽  
Xiaohui Shi ◽  
Huajing Teng ◽  
...  
Keyword(s):  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Cell Population ◽  
Cancer Types ◽  
Neutral Mutations ◽  
Analysis Platform

Abstract The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, ‘Mutation’, ‘Gene’, ‘Pathway’ and ‘Cancer’, to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

scholarly journals An Accurate Prognostic Model and Treatment for Pancreatic Carcinoma Based on the Tumor Immune Microenvironment

2021 ◽  
Author(s):  
Shujie Wang ◽  
zhenchong li ◽  
chunsheng liu ◽  
qi zhou ◽  
zuyi ma ◽  
...  
Keyword(s):  
Immune Cell ◽  
Nk Cell ◽  
Immune Therapy ◽  
R Package ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Gene ◽  
Therapy Effect ◽  
The Relationship ◽  
Worse Prognosis

Abstract BackgroundPancreatic adenocarcinoma (PAAD) is a highly malignant cancer with a poor prognosis. The tumor microenvironment (TME) is closely related to tumorigenesis, progression, and treatment. However, the relationship between TME immune cell genes and prognosis in PAAD is currently unclear.Methodsn this study, we identified three prognostic subtypes based on the TME by using data from The Cancer Genome Atlas (TCGA) database, The International Cancer Genome Consortium (ICGC) database and University of California Santa Cruz (UCSC) database. The Silhouette plot analysis was used to evaluate 758 immune genes expression in PAAD from each database, then to divide all samples into three subtypes (Clusters A, B, C) by Lasso’s binomial logistic regression. We analyzed the relationship between subtypes and prognosis by the survival R package. CIBERSORT was used for evaluating the expression changes of immune cells. We detect the copy number variation areas between two groups through GISTIC 2.0 algorithm. The TIDE network tool was used to predict the response of immune therapy.ResultsWe defined three clusters (Clusters A, B, and C) based on the analysis of immune gene expression. Cluster B got a worse prognosis than the other two clusters. The Cluster B group had the highest level of Macrophages M0 and Macrophage M2. NK cell resting was much higher in Cluster B than other groups in TME. Gene KRAS was mutated in 77% of all samples. Cluster C had a better immune therapy effect than others.ConclusionsWe found a news model to predicted patients’ prognosis who with pancreatic adenocarcinoma. Cluster B had the significant worse prognosis than other groups. Patients in Cluster C could get batter treatment effect by using immunotherapy.

scholarly journals Systematic Pan-Cancer Analysis Identifies TREM2 as an Immunological and Prognostic Biomarker

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Cheng ◽  
Xiaowei Wang ◽  
Kechao Nie ◽  
Lin Cheng ◽  
Zheyu Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Immunoglobulin Superfamily ◽  
Cancer Types ◽  
Pan Cancer

Triggering receptor expressed on myeloid cells-2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although increasing evidence supports a vital role for TREM2 in tumorigenesis of some cancers, no systematic pan-cancer analysis of TREM2 is available. Thus, we aimed to explore the prognostic value, and investigate the potential immunological functions, of TREM2 across 33 cancer types. Based on datasets from The Cancer Genome Atlas, and the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and Human Protein Atlas, we employed an array of bioinformatics methods to explore the potential oncogenic roles of TREM2, including analyzing the relationship between TREM2 and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration of different tumors. The results show that TREM2 is highly expressed in most cancers, but present at low levels in lung cancer. Further, TREM2 is positively or negatively associated with prognosis in different cancers. Additionally, TREM2 expression was associated with TMB and MSI in 12 cancer types, while in 20 types of cancer, there was a correlation between TREM2 expression and DNA methylation. Six tumors, including breast invasive carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, were screened out for further study, which demonstrated that TREM2 gene expression was negatively correlated with infiltration levels of most immune cells, but positively correlated with infiltration levels of M1 and M2 macrophages. Moreover, correlation with TREM2 expression differed according to T cell subtype. Our study reveals that TREM2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.

scholarly journals LINC02257, an Enhancer RNA of Prognostic Value in Colon Adenocarcinoma, Correlates With Multi-Omics Immunotherapy-Related Analysis in 33 Cancers

2021 ◽  
Vol 8 ◽  
Author(s):  
Junbo Xiao ◽  
Yajun Liu ◽  
Jun Yi ◽  
Xiaowei Liu
Keyword(s):  
Survival Analysis ◽  
Signaling Pathway ◽  
Large Scale ◽  
Immune Cell ◽  
Colon Adenocarcinoma ◽  
Akt Signaling ◽  
The Cancer Genome Atlas ◽  
Akt Signaling Pathway ◽  
Free Interval ◽  
Cancer Types

Accumulated evidence supports that long non-coding RNAs (lncRNAs) are involved significantly in the development of human cancers. Enhancer RNAs (eRNAs), a subtype of lncRNAs, have recently attracted much attention about their roles in carcinogenesis. Colon adenocarcinoma is one of the most commonly diagnosed tumors with unfavorable prognosis. It highlights the great significance of screening and identifying novel biomarkers. More importantly, it remains to be elucidated with respect to the function of eRNAs in colon adenocarcinoma, as is in pan-cancers. The expression of LINC02257 was determined based on the data obtained from The Cancer Genome Atlas (TCGA). Further evaluation was performed on the basis of the following analyses: clinicopathology and survival analysis, gene ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, as well as multi-omics immunotherapy-related analysis and co-expression analysis. The statistical analysis was conducted in R software, and immune cell infiltration of LINC02257 expression in cancers was investigated by using the CIBERSORT algorithm. By large-scale data mining, our study highlighted that a total of 39 eRNA genes were associated with colon adenocarcinoma prognosis, among which 25 eRNAs showed significant associations with their predicted target genes. LINC02257 was identified as the most significant survival-associated eRNA, with DUSP10 as its target gene. Besides, the high expression of LINC02257 in colon adenocarcinoma was more vulnerable to unfavorable prognosis and correlated with various clinical characteristics. GO and KEGG analyses revealed that LINC02257 was closely correlated with extracellular matrix organization via the PI3K-Akt signaling pathway. Besides, LINC02257 expression correlated with a multi-omics analysis of 33 cancer types, such as survival analysis [overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI)] and immunotherapy-related analysis [tumor microenvironment (TME), tumor mutational burden (TMB), and microsatellite instability (MSI)]. Finally, we investigated the co-expression genes of LINC02257 and its potential signaling pathways across different cancer types. LINC02257 is screened and can function as an independent prognostic biomarker through the PI3K-Akt signaling pathway for colon adenocarcinoma. Simultaneously, LINC02257 may be a multifaceted and significant immunotherapy-related eRNA in different cancers.

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