Tumor endothelium-derived PODXL correlates with immunosuppressive microenvironment and poor prognosis in cervical cancer patients receiving radiotherapy or chemoradiotherapy.
Rui HuangFuhao WangWenxue ZouXiaohui LiTianyu LeiPeihang LiYajun SongChao LiuJinbo YuePublished in: Biomarker research (2024)
Podocalyxin-like protein (PODXL) is known to originate from tumor cells in several cancers; however, which cell type it is expressed in, whether and how it may contribute to tumor progression after radiotherapy or chemoradiotherapy in cervical cancer (CC) remain unknown. In this study, we investigated these issues using a cohort of 180 immune stain data, single-cell RNA sequencing (scRNA-seq) data of 29,453 cells, and bulk RNA sequencing data from 187 cervical cancer samples treated with radiotherapy or chemoradiotherapy. ScRNA-seq analysis revealed that PODXL was predominantly expressed in tumor endothelial cells (TECs) of CC, which was corroborated by tumor section staining. Moreover, the PODXL expression level was negatively associated with progression-free survival and overall survival of 180 CC patients receiving radiotherapy or chemoradiotherapy (both p < 0.001). Furthermore, compared with PODXL low TECs, PODXL high TECs exhibited a diminished anti-tumor immune response and enhanced tumor-promoting features characteristics. In addition, PODXL over-expression was also found to be negatively associated with immune response and indicated poor survival in bulk RNA sequencing data of CC treated with radiotherapy or chemoradiotherapy. These results underscore the role of PODXL in CC, suggesting it as a promising target and prognostic marker for patients treated with radiotherapy or chemoradiotherapy.
Keyphrases
- locally advanced
- single cell
- poor prognosis
- rectal cancer
- squamous cell carcinoma
- rna seq
- radiation therapy
- immune response
- free survival
- long non coding rna
- early stage
- electronic health record
- big data
- endothelial cells
- radiation induced
- high throughput
- induced apoptosis
- stem cells
- genome wide
- nitric oxide
- data analysis
- cell cycle arrest
- dna methylation
- young adults
- machine learning
- oxidative stress
- artificial intelligence
- dendritic cells
- single molecule