SOX9 Expression Is Superior to Other Stem Cell Markers K19 and EpCAM in Predicting Prognosis in Hepatocellular Carcinoma.
Marianna B RuzinovaChangqing MaElizabeth M BruntCharles W GossNeeta VachharajaniWilliam C ChapmanTa-Chiang LiuPublished in: The American journal of surgical pathology (2022)
Various stem cell markers (eg, epithelial cell adhesion molecule [EpCAM], cytokeratin 19 [K19]) have been reported as predictors of poor prognosis in hepatocellular carcinoma (HCC). However, the data remain limited, particularly in Western populations, and are often contradictory. In this study, the prognostic value of positive SOX9 immunohistochemistry was compared with that of more established markers EpCAM and K19 in a large cohort (n=216) of North American patients. The independent HCC cohort in The Cancer Gene Atlas (n=360) was utilized to validate our findings. Finally, molecular signatures associated with SOX9-high HCC were determined. We found that the expression of SOX9, but not EpCAM or K19, was associated with worse overall survival and disease-free survival (DFS) and was an independent prognostic factor for DFS in our North American cohort, in which hepatitis C infection was the most common underlying etiology. High SOX9 mRNA level, but not increased expression of EpCAM mRNA or K19 mRNA, was also associated with worse DFS and was an independent prognostic factor for DFS in The Cancer Gene Atlas cohort. This group had underlying causes, including an increased incidence of hepatitis B, significantly different from our initial cohort. High SOX9 mRNA level is associated with molecular pathways important in HCC pathogenesis. Increased SOX9 expression is clinically and biologically relevant for HCC arising in patients with a variety of underlying etiologies. Immunohistochemistry for SOX9 is a reliable proxy for increased SOX9 mRNA and can be used to predict prognosis in HCC cases.
Keyphrases
- stem cells
- poor prognosis
- cell adhesion
- prognostic factors
- transcription factor
- long non coding rna
- binding protein
- circulating tumor cells
- free survival
- ejection fraction
- genome wide
- end stage renal disease
- risk factors
- papillary thyroid
- genome wide identification
- peritoneal dialysis
- south africa
- dna methylation
- cell therapy
- patient reported outcomes
- lymph node metastasis
- data analysis
- artificial intelligence