透過您的圖書館登入
IP:18.117.142.128
  • 學位論文

血管新生與標靶藥物於腫瘤治療之應用:磁振造影灌流與擴散影像之功能性評估及血管內皮細胞存活之訊息傳導

Application of angiogenesis and targeted therapy in cancer treatment:functional evaluation by dynamic contrast-enhanced and diffusion-weighted MRI and activation the survival pathway of vascular endothelial cell

指導教授 : 郭彥彬

並列摘要


Lung cancer is the most common cause of cancer death in Taiwan and other industrialized countries. It is a very important issue to study the mechanism of lung cancer response and treatment response to different treatment strategies and to develop new treatments. Dynamic contrast-enhanced (DCE) magnetic resonance imaging provides important pharmacokinetic parameters that detect the dynamic distribution after contrast agents injection and thus be able to measure sensitive pathological and physiological characteristics that are considered as non-invasive indicators of angiogenesis. Diffusion-weighted (DW) magnetic resonance imaging can be used to calculate the apparent diffusion coefficient (ADC) of water molecules that is correlated with the direction of fibers and tumor cellularity. The design of lung cancer mouse model is to study the biological characteristics of non-small cell lung cancer. Tyrosine kinase inhibitors and anti-angiogenesis drugs are the recent advances in the treatment of non-small cell lung cancer. Therefore, assessing the biologic therapeutic response in lung cancer mouse models and the clinical application of these targeted agents are important oncology studies. The purpose of chapter 1 of this study is to investigate the therapeutic response in lung cancer mice model and testing new treatment paradigms of lung cancer to EGFR TKI and anti-angiogenesis agent using DCE and DW MRI. Lung cancer mice model with HCC827 (gefitinib sensitive) and HCC827R (gefitinib resistant) was used for all studies for evaluate the response of TKI and anti-angiogenesis therapy, including: comparison among control group, erlotinib and combined erlotinib and bevacizumab. All animal studies from baseline to follow-up periods were performed using a 7T dedicated animal MR scanner (BioSpec, Bruker, Germany). Analysis of DCE-MRI was carried out using the Tofts model and commercial software. The parameters derived from the dynamic data included the volume transfer constant Ktrans (min-1/1000), rate constant Kep (min-1), extracellular extravascular space (EES) volume fraction (ve), and plasma volume fraction (vp) , initial area under the curve (iAUC). After completing the final MR study, the implanted tumors were excised and the specimens were examined by microvessel (CD31) and cleaved Parp stain. The results showed that tumor growth was significantly controlled by TKI and combined with antiangiogenesis drugs in HCC827 (gefitinib sensitive) model, and dynamic MR parameters such as Ktrans, Kep, and iAUC are significantly reduced, while apparent ADC values also increase early in diffusion MR imaging. These results are consistent with tumor vascular density analysis, including staining of necrotic cells seen in the treatment group. However, progressive enlargement of the tumors but no significant differences in DCE parameters or ADC were noted in the HCC827R model. Therefore, the use of non-invasive imaging technique can be used to assess the lung cancer mouse model of EGFR TKI and anti-angiogenesis drugs, further as an early diagnosis and predicted indicators of clinical imaging. Early detection of vascular changes within the microenvironment of the tumor by assessing the vascular perfusion and permeability will facilitate future clinical application. In addition, extend this issue of angiogenesis, a multi-steps process that involves interactions between cancer cells and their surrounding microenvironment. In the chapter 2 of this study, we found the morphology of human umbilical vein endothelial cells (HUVECs) was changed and richer capillary-like tubular structures were formed after interactions with human lung adenocarcinoma CL1-5 cells in the co-culture system. Then we performed the microarray system to analyze the change of the gene expression profile in HUVECs after co-culture with CL1-5 and survey the significant gene expression and the interactions between HUVECs and CL1-5 cells as well as to investigate the morphological and molecular mechanisms of HUVECs. Furthermore, a publicly available microarray dataset of 293 non-small-cell lung cancer (NSCLC) patients was employed to evaluate the prognostic potential of the gene signatures derived from HUVECs. The interaction between HUVECs and lung cancer cells changed the morphology of HUVECs, leading to a mesenchymal-like morphology and cytoskeleton rearrangement. Additionally, HUVECs showed increased cell motility and microvessel tubular formation ability and a decreased apoptotic percentage after co-culture with lung cancer cells. Transcriptomic profiling of HUVECs also revealed that several survival, apoptosis and angiogenesis-related genes were differentially expressed after interactions with lung cancer cells. Further investigations showed that PI3K/Akt signalling pathway and COX-2 are involved in endothelial tubular formation under the stimulation of lung cancer cells. The enhanced endothelial cell motility through the increased formation of lamellipodia and filopodia might due to Rac-1 activation. The inhibitors of PI3K and COX-2 could reverse the increased tube formation and induced the apoptosis of HUVECs. Moreover, the gene signatures derived from the DEGs in HUVECs could predict overall survival and disease-free survival of NSCLC patients and could serve as an independent prognostic factor potentially. These results demonstrated that lung cancer cells can promote endothelial cell tubular formation and survival, at least in part, through the PI3K/Akt signalling pathway and change the microenvironment to benefit tumor progression. The gene signatures from HUVECs are associated with the clinical outcome of NSCLC patients. The experiments of chapter 2 including cell culture, migration assay, F-actin stain, tubular formation, western Blotting, and Rac-1 activation assay were completed by Yi-Fang, Chen and the others experiments and data integration were done by Hao-Wei, Cheng.

參考文獻


Chapter 1
1. Slatore CG, Au DH, Gould MK; American Thoracic Society Disparities in Healthcare Group. An official American Thoracic Society systematic review: insurance status and disparities in lung cancer practices and outcome. Am J Respir Crit Care Med. 2010; 182: 1195-1205.
2. Folkman J. What is the evidence that tumors are angiogenesis dependent? J Natl Cancer Inst. 1990; 82: 4-6.
3. Folkman J. Clinical applications of research on angiogenesis. N Engl J Med. 1995; 333:1757-1763.
4. Weidner N. Intratumoral microvessel density as a prognostic factor in cancer. Am J Pathol. 1995; 147: 9-19.

延伸閱讀