OGDHL closely associates with tumor microenvironment and can serve as a prognostic biomarker for papillary thyroid cancer.

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. However, due to the lack of reliable prognostic biomarkers for PTC, overtreatment has been on the rise. Therefore, our research aims to identify new and promising prognostic biomarkers and provide fresh perspectives for clinical decision making.

METHODS

The RNA-seq data and clinical data of PTC samples were obtained from The Cancer Genome Atlas data portal. GSE64912 and GSE83520 datasets were downloaded through the GEOquery R package. The difference in the expression of oxoglutarate dehydrogenase like (OGDHL) between PTC and normal tissues was explored by the Wilcoxon test. Kaplan-Meier (KM) and Cox regression analyses were used to further explore the prognostic value of OGDHL. The tumor microenvironments of PTC patients were explored based on ssGSEA and Tumor Immune Estimation Resource online database. Gene Set Enrichment Analysis (GSEA) was performed to explore the biological processes associated with OGDHL.

RESULTS

The expression level of OGDHL in PTC was significantly altered compared to that in normal tissues (p < 0.05). Various biological processes associated with OGDHL were also explored through GSEA. KM analysis suggested that the low-OGDHL group had a better overall survival [OS, p = 3.49e-03, hazard ratio (HR) = 4.567]. The receiver operating characteristic curve also indicated the favorable prognostic potential of OGDHL. Moreover, OGDHL was proved to be an independent prognostic indicator in Cox analysis (p = 1.33e-02, HR = 0.152). In the analysis of the tumor microenvironment, the low-OGDHL group showed a lower immune score and stromal score, while tumor purity was higher. The expression of OGDHL was also closely correlated with the infiltration of immune cells.

CONCLUSION

Our study elucidated the influence of OGDHL on the prognosis of PTC and demonstrated its potential as a novel biomarker, which would provide new insights into the prognosis monitoring and clinical decision making in PTC patients.