광학영상 기반 프랙탈 차원 분석을 통한 유방암세포의 형태적 특성 연구

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팜 띠 뚜이 린
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프랙탈 기하학은 불규칙적인 모양과 복잡한 구조를 갖는, 자연계에 존재하는 많은 사물의 특징을 파악하는데 유용한 도구이다. 프랙탈 기하학은 연구자의 경험과 숙련 수준에 의존하지 않고, 연구자마다 각각 다른 독립적인 평가를 가능하게 한다. 최근, 프랙탈 차원분석은 생물학적인 구조, 세포 현상을 분석하고 또한, 암 연구에 많이 응용되고 있다. 본 연구에서는, 인간의 상피세포 MCF10A의 프랙탈 특성을 원자간력 현미경을 이용하여 분석하였다. 사이토칼라신 D의 처리는 세포 가장자리의 울퉁불퉁함과 프랙탈의 수치를 감소시켰다. 더구나, 세포 형태의 프랙탈적 특성을 몇몇의 유방암 세포주에서 조사하였다. 유방암 세포주는 침입성이 약한 세포주 (MCF7, T47D, ZR-75-1), 침입성이 높은 세포주 (MDA-MB-231, MDA-MB-435S, Hs578T) 를 이용하여, 정상 세포주 (MCF10A) 와 비교 분석하였다. 박스 카운팅으로 구해진 세포 가장자리의 프랙탈 수치를 통계학적으로 분석하는데 약 20가지 세포 세포막의 광학적 이미지를 사용하였다. 실험결과, 세포 가장자리의 프랙탈 수치는 세포의 침입성이 높을수록 감소하였다. 정상 세포주 (MCF10A) 는 가장 높은 프랙탈 수치 (FD = 1.348) 가 나왔고, 침입성이 약한 세포주 (MCF7의 FD = 1.116, T47D의 FD = 1.100, ZR-75-1의 FD = 1.138) 는 더 낮은 수치, 그리고 침입성이 높은 세포주 (MDA-MB-231의 FD = 1.067, MDA-MB-435S의 FD = 1.067, Hs578T의 FD = 1.079) 는 가장 낮게 나왔다. 변화 분석을 통해 보여준 프랙탈 수치 (p < 0.05) 에서 정상세포와 암세포의 차이와 특히, 암세포의 침입성이 낮은 세포와 높은 세포의 차이는 주목할 만한 가치가 있다. 프랙탈 차원분석은 세포막 형태의 불규칙성을 설명하는데 굉장히 유용한 방법이며, 암세포 침입 단계를 알아내는데 새로운 방법을 제공하는 가치있는 도구이다.|Fractal geometry is a useful tool for characterizing irregular shapes and complex structures of many natural objects. It allows user-independent evaluation and does not rely on the experience level of the examiner. Recently, fractal dimension has gained increasing applications to analyze biological structures, cellular phenomena and also cancer research. Previous studies of fractal dimension analysis applied to cancer focused on vascular architecture, tumor border and cellular/nuclear morphology. In this study, the fractal property of human MCF10A epithelial cells was explored using atomic force microscope. Treatment with cytochalasin D decreased both the ruggedness and fractal dimension of the cell boundary. Furthermore, fractal property of cell morphology was examined in several breast cancer cell lines with weakly (MCF7, T47D, ZR-75-1), highly (MDA-MB-231, MDA-MB-435S, Hs578T) invasive potential, and normal cell line (MCF10A) in a comparative approach. The optical imaging of cell membranes of about 20 cells was used for statistical analysis, in which the fractal dimension values of cell boundary were determined by box-counting method. The results showed that the fractal dimensions of the cell boundary decreased when the degree of invasiveness increased. The normal cells (MCF10A) showed the highest fractal dimension value (FD = 1.348), while the weakly invasive cancer cells exhibited the lower fractal dimension value (FD = 1.116 for MCF7, 1.100 for T47D, 1.138 for ZR-75-1) and the highly invasive cancer cells have the lowest fractal dimension value (FD = 1.067 for MDA-MB-231, 1.067 for MDA-MB-435S, 1.079 for Hs578T). There were significant differences of fractal dimension between normal cells and cancer cells, especially between weakly and highly invasive cancer groups as shown by the analysis of variance (p < 0.05). Taken together, fractal dimension is a valuable tool to describe irregularity of cell membranes and provides a new way to detect cancer invasiveness stage.
Alternative Title
Fractal dimension analysis of breast cancer cell morphology based on optical imaging
Alternative Author(s)
Pham Thi Thuy Linh
조선대학교 대학원
일반대학원 해양생명과학
Awarded Date
Table Of Contents
List of Figures iii
List of Tables iv
국문 초록 viii
Chapter 1: Introduction 1
Chapter 2: Materials and Methods 5
2.1. Materials 5
2.2. Cell culture 5
2.3. Atomic force microscope (AFM) imaging 5
2.4. Differential interference contrast (DIC) imaging 6
2.5. Calculation of fractal dimension by box-counting method 7
2.6. Statistical analysis 9
Chapter 3: Results 10
3.1. Fractal nature of cell boundary structure 10
3.2. The molecular basis of the fractal nature of cell boundary ultrastructure 14
3.3. Comparison of fractal dimension between normal and cancer cells using AFM imaging 18
3.4. Optical imaging is a useful approach to reveal expanding boundary of the cell 21
3.5. Optimization of high resolution optical imaging for fractal dimension analysis 24
3.6. Development of FD analysis software for the optical (DIC) image of cells 28
3.7. Fractal dimension analysis of breast cancer cell morphology using optical imaging 36
3.8. Comparison of fractal dimension between normal, weakly and highly invasive cancer cells using optical imaging 42
Chapter 4: Discussion and Conclusion 46
Chapter 5: References 49

List of Figures
Figure 1. Box-counting method for fractal dimension calculation. 8
Figure 2. The cell boundary ultrastructure of MCF10A and its fractal properties. 12
Figure 3. Effect of cytochalasin D treatment on the FD of the MCF10A cell boundary. 16
Figure 4. Comparison between normal and cancer cells using AFM technique. 19
Figure 5. The cell morphologies of different cell lines were captured with (A) atomic force microscope and (B) differential interference contrast microscope. 22
Figure 6. Optimization of experimental conditions with MDA-MB-231 cell line. 26
Figure 7. Fractal dimension analysis of weakly invasive cancer cell morphology (MCF7, T47D, ZR-75-1) using optical imaging. 37
Figure 8. Fractal dimension analysis of highly invasive cancer cell morphology (MDA-MB-231, MDA-MB-435S, Hs578T) using optical imaging. 39
Figure 9. Comparison between normal, weakly invasive and highly invasive cancer cells using optical imaging. 43
조선대학교 대학원
팜 띠 뚜이 린. (2013). 광학영상 기반 프랙탈 차원 분석을 통한 유방암세포의 형태적 특성 연구.
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