SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK are prognosis-related in colorectal cancer

AIM: To investigate the expression of markers that are correlated with the prognosis of colorectal cancer (CRC) patients. METHODS: One hundred and fifty-six CRC patientswere followed up for more than 3 years after radical surgery. Immunohistochemical (IHC) analysis was performed to detect the expression of 14 pathway-related markers (p53, APC, p21ras, E-cadherin, endothelin-B receptor, Shp2, ADCY-2, SPARCL1, neuroligin1, hsp27, mmp-9, MAPK, MSH2 and rho) in specimens from these patients. Bioinformatics analysis involving a Support Vector Machine (SVM) was used to determine the best prognostic model from combinations of these markers. RESULTS: Seven markers (SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK) were significantly related to the prognosis and clinical pathological features of the CRC patients (P < 0.05). Prognostic models were established through SVM from combinations of these 7 markers and proved able to differentiate patients with dissimilar survival, especially in stage Ⅱ/Ⅲ patients. According to the best prognostic model, the p53/SPARCL1 model, patients having high p53 and low SPARCL1 expression had about 50% lower 3-year survival than others (P < 0.001). CONCLUSION: SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK are potential prognostic markers in CRC. A p53/SPARCL1 bioinformatics model may be used as a supplement to tumor-nodes-metastasis staging.

Discovering differential protein expression caused by CagA-induced ERK pathway activation in AGS cells using the SELDI-ProteinChip platform

AIM： To identify the protein expression differences related to the CagA-induced ERK pathway activation in AGS cells. METHODS： Human AGS cells transfected with cagA and blank vector were treated with specific mitogenactivated protein kinase kinase （MEK） inhibitor. Total cell proteins were combined by strong anion exchange （SAX2） and weak cation exchange （CM10） ProteinChip arrays and analyzed using surface-enhanced laser desorption/ ionization time-of-flight mass spectrometry （SELDI-TOF- MS） proteomics technology. Protein expression profiles were compared with those of inhibitor-untreated cagA transfectants. SwissProt/TrEMBL database searching for differentially expressed proteins was carried out using the TagIdent tool with the pI and mass information. RESULTS： When a total of 16 proteins that showed expression differences in inhibitor-untreated cagA transfectants were compared with vector transfectants, three proteins with m/z 4229, 8162 and 9084 were found to have no expression differences after treatment with MEK inhibitor, while the other 13 maintained the same expression differences after inhibitor treatment. Seven pieces of meaningful matching information for the three proteins were obtained from database searching. CONCLUSION： Biomarkers with m/z 4229, 8162 and 9084 are ERKI/2 phosphorylation dependent, andtherefore are the downstream molecules of ERK1/2 in the ERK/MAPK signaling pathway. The three biomarkers may be important cancer-associated proteins according to SwissProt/TrEMBL database information.

Detection of nasopharyngeal carcinoma using surface-enhanced laser desorption and ionization mass spectrometry profiles of the serum proteome

Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consistent biomarkers for NPC, particularly for early detection of NPC. Methods: A proteomic pattern was identified in a training set (134 NPC patients and 73 control individuals) using the surface-enhanced laser desorption and ionization-mass spectrometry (SELDI-MS), and used to screen the test set (44 NPC patients and 25 control individuals) to determine the screening accuracy. To confirm the accuracy, it was used to test another group of 52 NPC patients and 32 healthy individuals at 6 months later. Results: Eight proteomic biomarkers with top-scored peak mass/charge ratios (m/z) of 8605 Da, 5320 Da, 5355 Da, 5380 Da, 5336 Da, 2791 Da, 7154 Da, and 9366 Da were selected as the potential biomarkers of NPC with a sensitivity of 90.9% (40/44) and a specificity of 92.0% (23/25). The performance was better than the current diagnostic method by using the Epstein-Barr virus (EBV) capsid antigen IgA antibodies (VCA/IgA). Similar sensitivity (88.5%) and specificity (90.6%) were achieved in another group of 84 samples. Conclusion: SELDI-MS profiling might be a potential tool to identify patients with NPC, particularly at early clinical stages.

Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion

Objective: Biomarker assay is a noninvasive method for the early detection of esophageal squamous cellcarcinoma (ESCC). Searching for new biomarkers with high specificity and sensitivity is very important for the earlydetection of ESCC. Serum surface-enhanced laser desorption/ionization-time of flight mass spectrometry(SELDI-TOF-MS) is a high throughput technology for identifying cancer biomarkers using drops of sera. Methods: Inthis study, 185 serum samples were taken from ESCC patients in a high incidence area and screened by SELDI. Asupport vector machine (SVM) algorithm was adopted to analyze the samples. Results: The SVM patterns success-fully distinguished ESCC from pre-cancerous lesions (PCLs). Also, types of PCL, including dysplasia (DYS) and basalcell hyperplasia (BCH), and healthy controls (HC) were distinguished with an accuracy of 95.2% (DYS), 96.6% (BCH),and 93.8% (HC), respectively. A marker of 25.1 kDa was identified in the ESCC patterns whose peak intensity wasobserved to increase significantly during the development of esophageal carcinogenesis, and to decrease obviously after surgery. Conclusions: We selected five ESCC biomarkers to form a diagnostic pattern which can discriminateamong the different stages of esophageal carcinogenesis. This pattern can significantly improve the detection ofESCC.

Proteomic analysis of primary colon cancer-associated fibroblasts using the SELDI-ProteinChip platform

Objective： Cancer-associated fibroblasts （CAFs） are one of the hallmarks of the cancer microenvironment. Recent evidence has indicated that CAFs are more competent in enhancing cancer cell growth and migration than normal fibroblasts. However, the unique protein expression of CAFs has not been fully elucidated. This study aims to investigate the characterizations of colon CAFs by comparing the differential protein expression between CAFs and normal fibroblasts. Methods： Primary fibroblasts were isolated from surgical specimen of human colon cancer and matched normal colonic tissue. Purity of the cell population was verified through immunostain analysis. Total cell lysates and conditioned media from each group of cells were extracted, and protein expression analysis was con- ducted using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF-MS） ProteinChip platform. Results： Most primary cells showed typical fibroblast-like features after two weeks. Increased proportion of a-smooth muscle actin-positive myofibroblasts was detected within the CAFs in four of the six pairs of primary cells. Fibroblast activation protein was weakly expressed in most cells without differences. Using SELDI-TOF-MS ProteinChip platform, four protein peaks mass over charge ratio （m/z） 1142, 3011, 4035, and 4945 were detected in the total cell lysates, and two protein peaks m/z 1368 and 1389 were detected in the conditioned media. The potential candidate proteins found in the Swiss-Prot database include morphogenetic neuropeptides, FMRFamide-related peptides, insulin-like growth factor II, thymosin 13-4-like protein 3, and tight junction-associated protein 1. Conclusions： Using the SELDI-ProteinChip platform, differential protein expressions were identified in colon CAFs compared with normal colonic stromal fibroblasts. The complex proteomic alternations in colon CAFs may play important roles related to the colon cancer microenvironment.