Transcriptomic Immune Profiles Can Represent the Tumor Immune Microenvironment Related to the Tumor Budding Histology in Uterine Cervical Cancer.
Tan Minh LeHong Duc Thi NguyenEunmi LeeDonghyeon LeeYe Seul ChoiJunghwan ChoNora Jee-Young ParkHyung Soo HanGun Oh ChongPublished in: Genes (2022)
Tumor budding (TB) histology has become a critical biomarker for several solid cancers. Despite the accumulating evidence for the association of TB histology with poor prognosis, the biological characteristics of TB are little known about in the context related to the tumor immune microenvironment (TIME) in uterine cervical cancer (CC). Therefore, this study aimed to identify the transcriptomic immune profiles related to TB status and further provide robust medical evidence for clinical application. In our study, total RNA was extracted and sequenced from 21 CC tissue specimens. As such, 1494 differentially expressed genes (DEGs) between the high- and low-TB groups were identified by DESeq2. After intersecting the list of DEGs and public immune genes, we selected 106 immune-related DEGs. Then, hub genes were obtained using Least Absolute Shrinkage and Selection Operator regression. Finally, the correlation between the hub genes and immune cell types was analyzed and four candidate genes were identified (one upregulated ( FCGR3B ) and three downregulated ( ROBO2 , OPRL1 , and NR4A2 ) genes). These gene expression levels were highly accurate in predicting TB status (area under the curve >80%). Interestingly, FCGR3B is a hub gene of several innate immune pathways; its expression significantly differed in the overall survival analysis ( p = 0.0016). In conclusion, FCGR3B , ROBO2 , OPRL1 , and NR4A2 expression can strongly interfere with TB growth and replace TB to stratify CC patients.
Keyphrases
- poor prognosis
- mycobacterium tuberculosis
- bioinformatics analysis
- genome wide
- gene expression
- genome wide identification
- long non coding rna
- healthcare
- end stage renal disease
- stem cells
- innate immune
- chronic kidney disease
- newly diagnosed
- mental health
- single cell
- genome wide analysis
- copy number
- transcription factor
- rna seq
- peritoneal dialysis
- binding protein
- drug induced
- electronic health record