PURPOSE: Midkine (MK) has been reported to be a possible molecular marker for the diagnosis of pancreatic cancer. We investigated the feasibility of quantitative analysis of MK mRNA by quantitative real-time RT-PCR (qRT-PCR) as a promising tool for the diagnosis of pancreatic cancer. RESULTS: We found that pancreatic cancer tissues expressed significantly higher levels of MK mRNA than intraductal pancreatic mucinous neoplasm (IPMN) and non-neoplastic pancreatic tissues (P < 0.05); in contrast, we did not find any differences in MK mRNA expression between IPMN and non-neoplastic pancreatic tissues. Additionally, we observed that poorly differentiated carcinoma samples expressed higher levels of MK mRNA than well-differentiated carcinoma samples, although a significant difference was not observed. CONCLUSIONS: The present data suggests that quantitative analysis of MK mRNA provides an objective and sensitive evaluation and may be a promising modality for the diagnosis of pancreatic cancer and the prediction of its prognosis.
PURPOSE:Midkine (MK) has been reported to be a possible molecular marker for the diagnosis of pancreatic cancer. We investigated the feasibility of quantitative analysis of MK mRNA by quantitative real-time RT-PCR (qRT-PCR) as a promising tool for the diagnosis of pancreatic cancer. RESULTS: We found that pancreatic cancer tissues expressed significantly higher levels of MK mRNA than intraductal pancreatic mucinous neoplasm (IPMN) and non-neoplastic pancreatic tissues (P < 0.05); in contrast, we did not find any differences in MK mRNA expression between IPMN and non-neoplastic pancreatic tissues. Additionally, we observed that poorly differentiated carcinoma samples expressed higher levels of MK mRNA than well-differentiated carcinoma samples, although a significant difference was not observed. CONCLUSIONS: The present data suggests that quantitative analysis of MK mRNA provides an objective and sensitive evaluation and may be a promising modality for the diagnosis of pancreatic cancer and the prediction of its prognosis.
Authors: I Miyashiro; T Kaname; E Shin; E Wakasugi; T Monden; Y Takatsuka; N Kikkawa; T Muramatsu; M Monden; T Akiyama Journal: Breast Cancer Res Treat Date: 1997-03 Impact factor: 4.872
Authors: S Maeda; H Shinchi; H Kurahara; Y Mataki; H Noma; K Maemura; K Aridome; T Yokomine; S Natsugoe; T Aikou; S Takao Journal: Br J Cancer Date: 2007-07-10 Impact factor: 7.640