AUTHOR=Huang Runzhi , Huang Dan , Wang Siqiao , Xian Shuyuan , Liu Yifan , Jin Minghao , Zhang Xinkun , Chen Shaofeng , Yue Xi , Zhang Wei , Lu Jianyu , Liu Huizhen , Huang Zongqiang , Zhang Hao , Yin Huabin 

TITLE=Repression of enhancer RNA PHLDA1 promotes tumorigenesis and progression of Ewing sarcoma via decreasing infiltrating T‐lymphocytes: A bioinformatic analysis

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.952162

DOI=10.3389/fgene.2022.952162

ISSN=1664-8021

ABSTRACT=Background: Enhancers transcript non-coding RNAs, known as enhancer RNAs (eRNAs), which may serve as potential diagnosis markers and therapeutic targets in Ewing sarcoma.
Materials and Methods: Differentially expressed genes (DEGs) were identified between 85 Ewing sarcoma samples downloaded from Treehouse database and 3 normal bone samples downloaded from Sequence Read Archive (SRA) database. Included in DEGs, differentially expressed eRNAs (DEeRNAs) and target genes corresponding to DEeRNAs (DETGs), as well as the differentially expressed TFs were annotated. Then, Cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) was used. Independent prognosis analysis and Kaplan-Meier survival analysis were implemented using sarcoma samples from the Cancer Genome Atlas (TCGA) database. Next, hallmarks of cancer by gene set variation analysis (GSVA), immune gene sets by single-sample gene set enrichment analysis (ssGSEA) were identified to significantly associated with Ewing sarcoma. After screening by co-expressed analysis, most significant DEeRNAs, DETGs and DETFs, immune cells, immune gene sets, hallmarks of cancer were merged to construct a co-expression regulatory network to eventually identified the key DEeRNAs in tumorigenesis of Ewing sarcoma. Moreover, Connectivity Map Analysis was utilized to identify small molecules targeting Ewing sarcoma. External validation based on multidimensional online databases and scRNA-seq analysis were used to verify our key findings.
Results: A six different dimension regulatory network was constructed based on 17 DEeRNAs, 29 DETFs, 9 DETGs, 5 immune cells, 24 immune gene sets, and 8 hallmarks of cancer. Four key DEeRNAs (CCR1, CD3D, PHLDA1 and RASD1) showed significant co-expression relationships in the network. Connectivity Map Analysis screened two candidate compounds, MS-275 and pyrvinium, that might target Ewing sarcoma. PHLDA1 (key DEeRNA) was extensively expressed in cancer stem cells of Ewing sarcoma, which play a critical role in the tumorigenesis of Ewing sarcoma..
Conclusion: PHLDA1 is a key regulator in the tumorigenesis and progression of Ewing sarcoma. PHLDA1 is directly repressed by EWS/FLI1 protein and low-expression of FOSL2, resulting in deregulation of FOX proteins and CC chemokine receptors. The decrease of infiltrating T‐lymphocytes and TNFA signaling may promote tumorigenesis and progression of Ewing sarcoma.