{'fraction_non_alphanumeric': 0.06721215663354763, 'fraction_numerical': 0.04266510812390415, 'mean_word_length': 4.366771159874608, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Decreased expression of Ep-CAM protein is significantly associated with the progression and prognosis of oral squamous cell carcinomas in Taiwan.

BACKGROUND
The epithelial cell adhesion molecule (Ep-CAM) is involved in cell signaling, migration, proliferation, cell-cycle regulation, and cancer metastasis.


METHODS
This study used an immunohistochemical technique to examine the expression of Ep-CAM protein in 84 specimens of oral squamous cell carcinoma (OSCC), 98 specimens of oral epithelial dysplasia (OED, 31 mild, 41 moderate, and 26 severe OED cases), and 15 specimens of normal oral mucosa (NOM).


RESULTS
We found that the mean Ep-CAM labeling indices (LIs) decreased significantly from NOM (80 +/- 18%) and mild OED (76 +/- 14%) through moderate OED (66 +/- 22%) and severe OED (55 +/- 20%) to OSCC samples (46 +/- 16%, P < 0.001). A significant correlation was found between the lower mean Ep-CAM LI and OSCCs with larger tumor size (P = 0.003), positive lymph node metastasis (P = 0.022), more advanced clinical stages (P < 0.001), cancer recurrence (P = 0.021), or extracapsular spread of lymph node (P = 0.015). However, only Ep-CAM LI < 50% (P < 0.0001) was identified as an independent unfavorable prognosis factor by multivariate analyses with Cox proportional hazard regression model. Kaplan-Meier curve showed that OSCC patients with an Ep-CAM LI < 50% had a significantly poorer cumulative survival than those with an Ep-CAM LI > or = 50% (P < 0.00001, log-rank test).


CONCLUSIONS
We conclude that the decreased expression of Ep-CAM protein is an early event in oral carcinogenesis. The Ep-CAM LI in OSCC samples can predict the progression of OSCCs and the survival of OSCC patients.