Cancer Biomarkers - Volume 20, issue 1

Authors: Qi, Jie | Ma, Liang | Wang, Xiaogang | Li, Ying | Wang, Kejun

Article Type: Research Article

Abstract: OBJECTIVE: Osteosarcoma (OS) is the most frequent type of bone malignancy, and this disease has a poor prognosis. We aimed to identify the significant genes related with OS by integrating module-identification method and attract approach. METHODS: OS-related microarray data E-GEOD-36001 were obtained from ArrayExpress database, and then protein-protein interaction (PPI) networks of normal and OS were re-weighted by means of spearman correlation coefficient (SCC). Next, maximal cliques were detected from the re-weighted PPI networks using clusteringbased on maximal cliques approach. Afterwards, highly overlapped cliques were merged according to the interconnectivity, following by candidate modules and …seed modules identification. Attract proposed by Mar et al. who have suggested that this approach can extract and annotate the gene-sets which can distinguish between disease and control samples, and obtained differences of these gene-sets among the expression profile of samples were defined as attractors. Thus, we applied attract method to extract differential modules from the seed modules, and these obtained differential modules were defined as attractors. The genes in attractors were determined as attractor genes. RESULTS: After eliminating the maximal cliques with nodes less than 4, there were 1,884 and 528 maximal cliques in normal and OS PPI networks, which were used to conduct module analysis. A total of 60 and 19 candidate modules were obtained in control and OS PPI networks, respectively. By comparing with normal group, 2 seed module pairs with similar gene composition were found. Significantly, based on attract method, we found that these 2 modules were differential. These 2 modules had the same gene size with 4 genes. Of note, genes CCNB1 and KIF11 simultaneously appeared in these two attractors. CONCLUSIONS: We successfully identified two attractors via integrating module-identification method and attract approach, and attractor genes, for example, CCNB1 and KIF11 might play pathophysiological roles in OS development and progression. Show more

Keywords: Osteosarcoma, attract, modules

DOI: 10.3233/CBM-170144

Citation: Cancer Biomarkers, vol. 20, no. 1, pp. 87-93, 2017

Authors: Hua, Yongqiang | Chen, Hao | Wang, Libing | Wang, Feng | Wang, Peng | Ning, Zhouyu | Li, Ye | Liu, Luming | Chen, Zhen | Meng, Zhiqiang

Article Type: Research Article

Abstract: BACKGROUND: Circulating microRNAs (miRNAs) are emerging as novel biomarkers for various types of cancer including pancreatic cancer (PC). OBJECTIVE: We aimed to explore the diagnostic and prognostic significance of serum miR-373 in PC. METHODS: In the current study, we recruited a total of 103 PC patients, 30 patients with benign pancreatic tumor, 20 patients with chronic pancreatitis and 50 healthy volunteers. Total RNA was isolated from all the blood samples, and relative miR-373 expression levels were detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). RESULTS: Our findings demonstrated that serum …miR-373 expression was greatly down-regulated in PC patients. The area under the receiver-operating characteristic (ROC) curve (AUC) for serum miR-373 was 0.852 for discriminating PC patients from normal control subjects. In addition, a positive correlation was observed between reduced serum miR-373 level and several clinical parameters, including TNM stage, lymph node metastasis and distant metastasis. Moreover, PC patients with lower serum miR-373 level had shorter 5 year overall survival. Finally, serum miR-373 was proved to be an independent predictor for PC. CONCLUSIONS: Taken together, serum miR-373 might serve as a promising biomarker for the early detection and prognosis prediction of PC. Show more

Keywords: Pancreatic cancer, serum miR-373, diagnosis, prognosis, biomarker

DOI: 10.3233/CBM-170231

Citation: Cancer Biomarkers, vol. 20, no. 1, pp. 95-100, 2017

Authors: Fu, Luoqin | Liu, Suxia | Wang, Huiju | Ma, Yingyu | Li, Li | He, Xianglei | Mou, Xiaozhou | Tong, Xiangmin | Hu, Zhiming | Ru, Guoqing

Article Type: Research Article

Abstract: BACKGROUND: NIMA-related kinase 2 (NEK2), a serine/threonine kinase, is located in the centrosome and is a member of cell cycle regulation related protein kinase (CCRK) family. Aberrant expression of NEK2 is linked with carcinogenesis and progression of various tumors. OBJECTIVE: To investigate the expression level of NEK2 and its relationship with clinicopathological factors in hepatocellular carcinoma (HCC). METHODS: Immunohistochemistry was used to measure the expression of NEK2 in 310 patients’ specimen tissues and 197 adjacent normal liver tissues of HCC cases, and the subsequent prognostic value for each sample was estimated. …RESULTS: NEK2 expression levels in HCC were lower than in adjacent tissues (49.7% vs. 72.6%, P < 0.001). First, patients with relatively low NEK2 expression had increased cancer progression and poorer prognosis than those with high expression. Second, NEK2 expression was significantly reduced in patients with large tumors (P = 0.025), with stage III Edmondson-Steiner Grading (P = 0.015). Third, patients’ tumor size positively correlated with high AFP concentration (P = 0.017). Fourth, using the Kaplan-Meier survival curve, we found a lower survival rate in patients with decreased expression of NEK2 than those with high NEK2 expression in HCC (P = 0.029, Log-rank test). CONCLUSIONS: Low NEK2 expression might be a useful predictor in HCC as a poor prognostic factor, and could serve as a potential therapeutic target for HCC. Show more

Keywords: NIMA-related kinase 2, hepatocellular carcinoma, immunohistochemistry, prognostic factors

DOI: 10.3233/CBM-170586

Citation: Cancer Biomarkers, vol. 20, no. 1, pp. 101-106, 2017

Authors: Rashed, Hayam E. | Hussein, Samia | Mosaad, Hala | Abdelwahab, Mai M. | Abdelhamid, Mohamed I. | Mohamed, Salem Y. | Mohamed, Abdel Motaleb | Fayed, Alaa

Article Type: Research Article

Abstract: BACKGROUND: Epithelial-mesenchymal transition (EMT) is one of the main events in colorectal cancer (CRC) spread. Snail-1 is a zinc transcription factor that mediates EMT in tumor cells probably by down-regulation of E-cadherin and claudin-1. OBJECTIVES: To detect the expression of epithelial markers (claudin-1 and E-cadherin) and mesenchymal markers (snail-1 and vimentin) in primary cancer colon. Also, to select stage II cancer patients of a high risk that can benefit from postoperative adjuvant chemotherapy. METHODS: Reverse transcription-polymerase chain …reaction (RT-PCR) and immunohistochemical analysis were performed to investigate snail-1, claudin-1, E-cadherin and vimentin expressions at mRNA and protein levels in fresh tissues of cancer colon and normal colonic mucosa. The correlations between the expression of these markers and clinicopathological parameters were performed. RESULTS: Normal colonic mucosa revealed complete membranous expression of claudin-1, preserved E-cadherin and negative snail-1 and vimentin expressions. Compared to control, the expression of snail-1 and vimentin mRNA in cancer colon was significantly up-regulated while the expression of claudin-1 and E-cadherin mRNA was significantly down-regulated. These changes were significantly associated with stage and lymph node involvement at both mRNA and protein levels (p < 0.05). There were significant negative correlations between vimentin and each of E-cadherin and claudin-1 gene expression and between snail-1 and each of E-cadherin and claudin-1 gene expression. Moreover, these changes were independent predictors of recurrence of stage II cancer colon cases. CONCLUSION: There is a clinical significance of snail-1, claudin-1, E-cadherin and vimentin as possible markers for recognizing patients with lymph node involvement, advanced stage and high incidence of tumor recurrence in cancer colon. Show more

Keywords: RT-PCR, immunohistochemistry, colon cancer, snail-1, claudin-1, vimentin, E-cadherin

DOI: 10.3233/CBM-170034

Citation: Cancer Biomarkers, vol. 20, no. 1, pp. 107-122, 2017