Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Li L

PROVIDER: S-EPMC8677413 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe tumor microenvironment (TME) plays a crucial role in the initiation and progression of cancer. Bladder cancer (BLCA) is a malignant tumor of the genitourinary system. Its heterogeneity results in significant differences in the prognosis of patients. To date, this is still a huge challenge for clinical treatment. In recent years, more and more evidence showed that dysregulation of transcription factors (TFs) plays an important role in tumor progression, invasion, and metastasis. Unfortunately, the role of TFs on the tumor microenvironment in bladder cancer is unclear.MethodsThe original data of BLCA and corresponding adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. TFs were downloaded from the Animal Transcription Factor DataBase (Animal TFDB). Intersection analysis was used to obtain TFs that were differentially expressed between tumor and adjacent tissues. Gene Set Cancer Analysis (GSCALite) and CIBERSORT software were used to reveal the key differentially expressed TFs (DE-TFs). Subsequently, UALCAN and Human Protein Atlas (HPA) databases were used to disclose the expression of key DE-TFs in BLCA. The K-M curve divulged the relationship between the key DE-TFs and the patient's overall survival (OS), and the univariate and multivariate Cox regression analyses were conducted to explore independent prognostic factors. The cluster profiler package and Gene Set Enrichment Analysis (GSEA) were used for functional enrichment of genes related to the key DE-TFs. Finally, CIBERSORT software analyzed the immune landscape of BLCA.ResultsWe obtained a total of 117 BLCA-related DE-TFs. Among them, ETV7 was identified as the key DE-TFs due to its association with the autophagy activation pathway and various immune cells in cancer. Online databases of UALCAN and HPA indicated that ETV7 was overexpressed in tumors and negatively correlated with tumor severity. The K-M curve showed that the OS of patients with high expression of ETV7 was poor, which indicated that it was an independent prognostic factor. Functional enrichment of 87 DEGs between ETV7-high and -low expression groups indicated that it was closely related to the immune response and the functions of a variety of immune cells. Finally, CIBERSORT results proved that the high and low expression of ETV7 also caused significant differences in the tumor immune microenvironment of patients.ConclusionOverall, we proved that the transcription factor ETV7 was a novel prognostic factor, which may improve the individualized outcome prediction in BLCA by regulating the tumor immune microenvironment.