• Proceedings of the KSME Conference
• /
• 2002.08a
• /
• pp.709-710
• /
• 2002

Cancer angiogenesis is simulated using a two dimensional model. Governing equation of angiogenesis is a TAE (Tumor angiogenesis factor) conservation equation in time and space. A stochastic process model is utilized to simulate vessel formation, proliferation, and migration to a cancer pellet. Numerical results are presented especially in case of growing cancer.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.2
• /
• pp.831-836
• /
• 2015

Tumor fluid accumulation occurs in both human cancer and experimental tumor models. Solid tumors show a tendency to tumor fluid accumulation because of their anatomical and physiological features and this may be influenced by molecular factors. Fluid accumulation in the peri-tumor area also occurs in the Dunning model of rat prostate cancer as the tumor grows. In this study, the effects of tumor fluids that were obtained from Dunning prostate tumor-bearing Copenhagen rats on the strongly metastatic MAT-LyLu cell line were investigatedby examining the cell's migration and tumor fluid's toxicity and the kinetic parameters such as cell proliferation, mitotic index, and labelling index. In this research, tumor fluids were obtained from rats injected with $2{\times}10^5$ MAT-LyLu cells and treated with saline solution, and 200 nM tetrodotoxin (TTX), highly specific sodium channel blocker was used. Sterilized tumor fluids were added to medium of MAT-LyLu cells with the proportion of 20% in vitro. Consequently, it was demonstrated that Dunning rat prostate tumor fluid significantly inhibited proliferation (up to 50%), mitotic index, and labeling index of MAT-LyLu cells (up to 75%) (p<0.05) but stimulated the motility of the cells in vitro.

• Biomedical Science Letters
• /
• v.28 no.4
• /
• pp.312-316
• /
• 2022

We have previously reported that genetically modified tumor cells with 4-1BBL have anti-cancer effects in a CT26 mouse colorectal tumor model. In this study, genetically modified tumor cells with 4-1BBL were evaluated for their potential as candidates for preventive and therapeutic cancer vaccine. To identify the effect of preventive and therapeutic vaccine of genetically modified tumor cells with 4-1BBL, tumor growth pattern of CT26-4-1BBL as a cancer vaccine was examined compared to CT26-beta-gal. In therapeutic vaccination, CT26-WT was inoculated into mice and then vaccinated mice with doxorubicin (Dox)-treated CT26-beta-gal and CT26-4-1BBL (single or three times). Triple vaccination with Dox-treated tumor cell inhibited tumor growth compared to single vaccination. Vaccination with CT26-4-1BBL showed an efficient tumor growth inhibition compared to vaccination with CT26-beta-gal. For preventive vaccination, Dox-treated CT26-beta-gal and CT26-4-1BBL was vaccinated into mice with three times and then administered mice with CT26-WT. Preventive vaccination with CT26-4-1BBL showed no tumor growth. Preventive vaccination with CT26-beta-gal also led to tumor-free mice. These results suggest that genetically modified tumor cells with 4-1BBL can be used as therapeutic or preventive cancer vaccine.

• IMMUNE NETWORK
• /
• v.16 no.5
• /
• pp.305-310
• /
• 2016

In this study, we compared two different tumor cell vaccines for their induction of anti-tumor immunity; one was a tumor cell clone expressing a membrane-bound form of IL-12 p35 subunit (mbIL-12 p35 tumor clone), and the other was a tumor clone expressing heterodimeric IL-12 as a single chain (mb-scIL-12 tumor clone). The stimulatory effect of mb-scIL-12 on the proliferation of ConA-activated splenocytes was higher than that of mbIL-12 p35 in vitro. However, the stimulatory effect of mbIL-12 p35 was equivalent to that of recombinant soluble IL-12 (3 ng/ml). Interestingly, both tumor clones (mbIL-12 p35 and mb-scIL-12) showed similar tumorigenicity and induction of systemic anti-tumor immunity in vivo, suggesting that tumor cell expression of the membrane-bound p35 subunit is sufficient to induce anti-tumor immunity in our tumor vaccine model.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.1
• /
• pp.265-271
• /
• 2014

Interleukin-7 (IL-7) is a potent anti-apoptotic cytokine that enhances immune effector cell functions and is essential for lymphocyte survival. While it known to induce differentiation and proliferation in some haematological malignancies, including certain types of leukaemias and lymphomas, little is known about its role in solid tumours, including breast cancer. In the current study, we investigated whether IL-7 could enhance the in vivo antitumor activity of tumor-reactive $CD8^+$ T cells with induction of IFN-${\gamma}$ in a murine breast cancer model. Human IL-7 cDNA was constructed into the eukaryotic expression plasmid pcDNA3.1, and then the recombinational pcDNA3.1-IL-7 was intratumorally injected in the TM40D BALB/C mouse graft model. Serum and intracellular IFN-${\gamma}$ levels were measured by ELISA and flow cytometry, respectively. $CD8^+$ T cell-mediated cytotoxicity was analyzed using the MTT method. Our results showed that IL-7 administration significantly inhibited tumor growth from day 15 after direct intratumoral injection of pcDNA3.1-IL-7. The anti-tumor effect correlated with a marked increase in the level of IFN-${\gamma}$ and breast cancer cells-specific CTL cytotoxicity. In vitro cytotoxicity assays showed that IL-7-treatment could augment cytolytic activity of $CD8^+$ T cells from tumor bearing mice, while anti-IFN-${\gamma}$ blocked the function of $CD8^+$ T cells, suggesting that IFN-${\gamma}$ mediated the cytolytic activity of $CD8^+$ T cells. Furthermore, in vivo neutralization of $CD8^+$ T lymphocytes by CD8 antibodies reversed the antitumor benefit of IL-7. Thus, we demonstrated that IL-7 exerts anti-tumor activity mainly through activating $CD8^+$ T cells and stimulating them to secrete IFN-${\gamma}$ in a murine breast tumor model. Based on these results, our study points to a potential novel way to treat breast cancer and may have important implications for clinical immunotherapy.

• Journal of Korea Multimedia Society
• /
• v.24 no.12
• /
• pp.1614-1623
• /
• 2021

In this paper, the purpose is evaluation of the effect of using fractal feature in machine learning based pancreatic tumor classification. We used the data that Pancreas CT series 469 case including 1995 slice of benign and 1772 slice of malignant. Feature selection is implemented from 109 feature to 7 feature by Lasso regularization. In Fractal feature, fractal dimension is obtained by box-counting method, and hurst coefficient is calculated range data of pixel value in ROI. As a result, there were significant differences in both benign and malignancies tumor. Additionally, we compared the classification performance between model without fractal feature and model with fractal feature by using support vector machine. The train model with fractal feature showed statistically significant performance in comparison with train model without fractal feature.

• Journal of Pharmaceutical Investigation
• /
• v.34 no.5
• /
• pp.393-399
• /
• 2004

For the efficient determination of activity against solid tumors, an in vitro tumor model that resembles the condition of in vivo solid tumors, is required. The purpose of this study was to establish a rapid culture method and viability assay for an in vitro 3-dimensional tumor model, multicellular spheroid (MCS). Among 12 human cancer cell lines, a few cell lines including DLD-1 (human colorectal carcinoma cells) formed fully compact MCS which was adequate for in vitro viability assay. DLD-1 MCS showed steady growth reaching $700\;{\mu}m$ diameter after 11 day culture. DLD-1 cells grown as MCS showed significant increase in $G_0/G_1$ phase compared to the monolayer cells (73.9% vs 45.7%), but necrotic regions or apoptotic cells were not observed. The cells cultured as MCS showed resistance to 5-FU (10.3 fold higher $IC_{50}$) compared to monolayers, however, tirapazamine (a hypotoxin) showed similar activity in both culture systems. In summary, MCS may be a valid in vitro model for activity screening of anticancer agents against human solid tumors and also exploitable for studying molecular markers of drug resistance in human solid tumors.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.14 no.4
• /
• pp.69-77
• /
• 2018

The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.10
• /
• pp.2788-2808
• /
• 2023

Brain tumors are one of the most threatening malignancies for humans. Misdiagnosis of brain tumors can result in false medical intervention, which ultimately reduces a patient's chance of survival. Manual identification and segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans can be difficult and error-prone because of the great range of tumor tissues that exist in various individuals and the similarity of normal tissues. To overcome this limitation, the Amended Convolutional Neural Network (ACNN) model has been introduced, a unique combination of three techniques that have not been previously explored for brain tumor detection. The three techniques integrated into the ACNN model are image tissue preprocessing using the Kalman Bucy Smoothing Filter to remove noisy pixels from the input, image tissue segmentation using the Isotonic Regressive Image Tissue Segmentation Process, and feature extraction using the Marr Wavelet Transformation. The extracted features are compared with the testing features using a sigmoid activation function in the output layer. The experimental findings show that the suggested model outperforms existing techniques concerning accuracy, precision, sensitivity, dice score, Jaccard index, specificity, Positive Predictive Value, Hausdorff distance, recall, and F1 score. The proposed ACNN model achieved a maximum accuracy of 98.8%, which is higher than other existing models, according to the experimental results.

• Korean Journal of Radiology
• /
• v.20 no.4
• /
• pp.580-588
• /
• 2019

Objective: To evaluate the impact of energy and access methods on extrahepatic tumor spreading and the ablation zone in an ex vivo subcapsular tumor mimic model with a risk of extrahepatic tumor spreading. Materials and Methods: Forty-two tumor-mimics were created in bovine liver blocks by injecting a mixture of iodine contrast material just below the liver capsule. Radiofrequency (RF) ablations were performed using an electrode placed parallel or perpendicular to hepatic surface through the tumor mimic with low- and high-power protocols (groups 1 and 2, respectively). Computed tomography (CT) scans were performed before and after ablation. The presence of contrast leak on the hepatic surface on CT, size of ablation zone, and timing of the first roll-off and popping sound were compared between the groups. Results: With parallel access, one contrast leak in group 1 (1/10, 10%) and nine in group 2 (9/10, 90%) (p < 0.001) were identified on post-ablation CT. With perpendicular access, six contrast leaks were identified in each group (6/11, 54.5%). The first roll-off and popping sound were significantly delayed in group 1 irrespective of the access method (p = 0.002). No statistical difference in the size of the ablation zone of the liver specimen was observed between the two groups (p = 0.247). Conclusion: Low-power RF ablation with parallel access is proposed to be effective and safe from extrahepatic tumor spreading in RF ablation of a solid hepatic tumor in the subcapsular location. Perpendicular placement of an electrode to the capsule is associated with a risk of extrahepatic tumor spreading regardless of the power applied.