The current methods available for screening and detecting cervical squamous cell carcinoma (CSCC) have insufficient sensitivity and specificity. As a result, many patients suffered from erroneous and missed diagnosis. Because CSCC is usually asymptomatic at potentially curative stages, identification of biomarkers is an urgent need for the early detection of CSCC. Comparative proteomics based on two-dimensional differential in-gel electrophoresis (2D-DIGE) was employed to quantitatively analyze plasma proteins of healthy Uyghur women and with early stage cervical carcinoma. The 2D-DIGE image were analyzed statistically using DeCyder™ 2D software. The statistical analysis of proteomic data revealed that 43 protein spots showed significantly different expression (ratio > 1.5, P < 0.01). A further identification of these protein spots by MALDI-TOF-MS found out 16 different proteins. Bioinformatic analysis within the framework of Ingenuity Pathway Analysis (IPA(@)) showed that 10 plasma proteins as candidate biomarker were screened, mainly including lipid metabolism-related proteins (APOA4, APOA1, APOE), complement (EPPK1, CFHR1), metabolic enzymes (CP, F2, MASP2), glycoprotein (CLU), and immune function-related proteins (IGK@). Networks involved in lipid metabolism, molecular transport, and small molecule biochemistry were dysfunctional in CSCC. Acute phase response signaling and JAK/Stat signaling and IL-4 signaling, etc., were identified as the canonical pathways that are overrepresented in CSCC. Furthermore, the expression of three proteins (APOA1, APOE, CLU) were validated using ELISA in plasma of patients with different stage cervical lesion. With the combined proteomic and bioinformatic approach, this study was successful in identifying biomarker signatures for cervical cancer and might provide new insights into the mechanism of CSCC progression, potentially leading to the design of novel diagnostic and therapeutic strategies.