Expression of cancer stem cell markers ALDH1 and Bmi1 in oral erythroplakia and the risk of oral cancer.

BACKGROUND: Oral erythroplakia (OE) is a notoriously aggressive oral pre-malignant lesion with a high tendency to oral cancer development, but its biological behavior is largely unknown. The objective of this study was to determine the expression of cancer stem cell markers ALDH1 and Bmi1 in OE and their correlation with malignant transformation of OE. METHODS: In a retrospective case-control study, expression patterns of ALDH1 and Bmi1 were determined using immunohistochemistry in samples from 34 patients with OE, including patients with untransformed lesions (n=17) and patients with malignant transformed lesions (n=17). RESULTS: ALDH1 and Bmi1 expression was observed in 19 (55.9%) and 20 (58.8%) of 34 patients with OE, respectively. Multivariate analysis revealed that ALDH1 expression was significantly associated with increased risk of transformation (P<0.05), but Bmi1 expression was not a significant marker (P > 0.05). Notably, the coexpression of both ALDH1 and Bmi1 was a strong indicator associated with 8.56-fold (95% confidence interval [CI], 1.74-42.17; P<0.01) for malignant transformation. Point prevalence analysis revealed that 78.6% (95% CI, 54.0-100) of the patient with coexpression of both ALDH1 and Bmi1 developed oral cancer. CONCLUSION: Our data indicated that the expression patterns of ALDH1 and Bmi1 in OE were associated with malignant transformation, suggesting that they may be valuable predictors for evaluating the risk of oral cancer.

Identification and Validation in a Novel Classification of Helicase Patterns for the Prediction of Tumor Proliferation and Prognosis.

Background: Helicases have been classified as a class of enzymes that determine the stability of the cellular genome. There is growing evidence that helicases can help tumor cells resist drug killing by repairing Deoxyribose Nucleic Acid (DNA) or stabilizing transcription, which may contribute to the understanding of drug resistance. Currently, identifying cancer biomarkers among helicases and stratifying patients according to helicase activity will be able to guide treatment well. Methods: We clustered 371 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) by consensus clustering based on helicase expression profiles to identify potential molecular subtypes. The Multiscale Embedded Gene Co-Expression Network Analysis (MEGENA) algorithm was used to find core differential gene modules between different molecular subtypes, and single-cell analysis was utlized to explore the potential function of hub gene. Immunohistochemical (IHC) staining was used to verify the diagnostic value of DDX56 and its ability to reflect the proliferation efficiency of cancer cells. Results: We identified two subtypes associated with helicase. High helicase subtype was associated with poor clinical outcome, massive M0 macrophage infiltration, and highly active cell proliferation features. In addition, we identified a new biomarker, DDX56, which has not been reported in HCC, was highly expressed in HCC tissues, associated with poor prognosis, and was also shown to be associated with high cell proliferative activity. Conclusion: In conclusion, based on helicase expression profiles, we have developed a new classification system for HCC, which is a proliferation-related system, and has clinical significance in evaluating prognosis and treating HCC patients, including immunotherapy and chemotherapy. In addition, we identified a new biomarker, DDX 56, which is overexpressed in HCC tissues, predicts a poor prognosis and is a validated index of tumor cell proliferation.