Objective: To explore the expressions of galectin-1 and human DNA methyltransferase 1 (DNMT1) in cervical cancer tissues and normal cervical tissues and their clinical significance. Method: Eighty-four patients with cervical cancer were randomly selected. 84 samples of cancer tissues and their para-carcinoma tissues were analyzed with regard to the following parameters: Galectin-1 and DNMT1 mRNA analyzed by RT-PCR, and galectin-1 and DNMT1 protein by western blotting. The relationships between the expressions of galectin-1 and DNMT1 protein, the clinicopathological factors, and the prognoses were analyzed. A correlation analysis was performed between the galectin-1 and DNMT1 protein expressions in the cervical cancer tissues. Result: The expressions of galectin-1 and DNMT1 mRNA and protein in the cervical cancer tissues were higher than they were in the para-carcinoma tissues (P<0.05). The expression of galectin-1 protein was correlated with pathological stage, lymph node metastasis, high-risk HPV infection, and pathological differentiation (P<0.05), but not with age or pathological type (P>0.05). The expression of DNMT1 protein was correlated with pathological stage, lymph node metastasis, high-risk HPV infection, and pathological differentiation (P<0.05), but not with age or pathological type (P>0.05). The 3-year survival of subjects with a high expression of galectin-1 or DNMT1 protein was significantly lower than it was in patients with low expressions (P<0.05). There was a positive correlation between the expressions of galectin-1 and DNMT1 mRNA in cervical cancer tissues (r=0.599, P<0.001). The expressions of galectin-1 and DNMT1 protein in cervical cancer tissues are also positively correlated (r=0.617, P<0.001). Conclusion: Galectin-1 and DNMT1 are highly expressed in cervical cancer tissues, and their expressions are closely related to the pathological stage, lymph node metastasis, high-risk HPV infection, pathological differentiation, and the prognosis of patients with cervical cancer, and the expressions may be used as a predictor of disease progression and prognosis.