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.
BackgroundTraditional Uighur medicine shares an origin with Greco-Arab medicine. It describes the health of a human body as the dynamic homeostasis of four normal Hilits (humours), known as Kan, Phlegm, Safra, and Savda. An abnormal change in one Hilit may cause imbalance among the Hilits, leading to the development of a syndrome. Abnormal Savda is a major syndrome of complex diseases that are associated with common biological changes during disease development. Here, we studied the protein expression profile common to tumour patients with Abnormal Savda to elucidate the biological basis of this syndrome and identify potential biomarkers associated with Abnormal Savda.MethodsPatients with malignant tumours were classified by the diagnosis of Uighur medicine into two groups: Abnormal Savda type tumour (ASt) and non-Abnormal Savda type tumour (nASt), which includes other syndromes. The profile of proteins that were differentially expressed in ASt compared with nASt and normal controls (NC) was analysed by iTRAQ proteomics and evaluated by bioinformatics using MetaCore™ software and an online database. The expression of candidate proteins was verified in all plasma samples by enzyme-linked immunosorbent assay (ELISA).ResultsWe identified 31 plasma proteins that were differentially expressed in ASt compared with nASt, of which only 10 showed quantitatively different expression between ASt and NC. Bioinformatics analysis indicated that most of these proteins are known biomarkers for neoplasms of the stomach, breast, and lung. ELISA detection showed significant upregulation of plasma SAA1 and SPP24 and downregulation of PIGR and FASN in ASt compared with nASt and NC (p < 0.05).ConclusionsAbnormal Savda may be causally associated with changes in the whole regulation network of protein expression during carcinogenesis. The expression of potential biomarkers might be used to distinguish Abnormal Savda from other syndromes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12906-015-0526-6) contains supplementary material, which is available to authorized users.
BackgroundWe established a rat model of chronic mountain sickness using acetyl-L-cysteine. Then we studied the effects and mechanisms of acetyl-L-cysteine (Da) in rats with chronic mountain sickness using nuclear magnetic resonance (H1-NMR) metabolomics methods.Material/MethodsUsing NMR spectroscopy combined with pattern recognition and orthogonal partial least squares discriminant analysis, we analyzed the impact of Da on blood metabolism in rats with chronic mountain sickness by determining different metabolites and changes in metabolic network in the blood of rats with mountain sickness after the intragastric administration of different doses of Da suspension.ResultsIncreased levels of amino acids (valine, tyrosine, 1-methyl-histidine, leucine, phenylalanine, and methionine) were detected in the blood of rats in the chronic mountain sickness group, yet significantly decreased levels were detected in control rats. At the same time, β-glucose and α-glucose levels were markedly elevated in the blood of rats in the model group but decreased in the chronic mountain sickness group, which indicated a statistically significant difference compared with the chronic altitude sickness model group (P<0.05).ConclusionsDa has a significant impact on the metabolism of rats with chronic mountain sickness. Da may act on the disturbed glucose metabolism and amino acid metabolism in rats triggered by chronic mountain sickness, resulting in the treatment and prevention of this disease.
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