• Genomics & Informatics
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• v.4 no.3
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• pp.97-102
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• 2006

In acute leukemia patients, several successful methods of expression profiling have been used for various purposes, i.e., to identify new disease class, to select a therapeutic target, or to predict chemo-sensitivity and clinical outcome. In the present study, we tested the peripheral blood of 47 acute leukemia patients in an attempt to identify differentially expressed genes in AML and ALL using a Korean-made 10K oligo-nucleotide microarray. Methods: Total RNA was prepared from peripheral blood and amplified for microarray experimentation. SAM (significant analysis of microarray) and PAM (prediction analysis of microarray) were used to select significant genes. The selected genes were tested for in a test group, independently of the training group. Results: We identified 345 differentially expressed genes that differentiated AML and ALL patients (FWER<0.05). Genes were selected using the training group (n=35) and tested for in the test group (n=12). Both training group and test group discriminated AML and ALL patients accurately. Genes that showed relatively high expression in AML patients were deoxynucleotidyl transferase, pre-B lymphocyte gene 3, B-cell linker, CD9 antigen, lymphoid enhancer-binding factor 1, CD79B antigen, and early B-cell factor. Genes highly expressed in ALL patients were annexin A 1, amyloid beta (A4) precursor protein, amyloid beta (A4) precursor-like protein 2, cathepsin C, lysozyme (renal amyloidosis), myeloperoxidase, and hematopoietic prostaglandin D2 synthase. Conclusion: This study provided genome wide molecular signatures of Korean acute leukemia patients, which clearly identify AML and ALL. Given with other reported signatures, these molecular signatures provide a means of achieving a molecular diagnosis in Korean acute leukemia patents.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5973-5981
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• 2013

At present, the most common cause of cancer-related death in women is breast cancer. In a large proportion of breast cancers, there is the overexpression of human epidermal growth factor receptor 2 (HER2). This receptor is a 185 KDa growth factor glycoprotein, also known as the first tumor-associated antigen for different types of breast cancers. Moreover, HER2 is an appropriate cell-surface specific antigen for passive immunotherapy, which relies on the repeated application of monoclonal antibodies that are transferred to the patient. However, vaccination is preferable because it would stimulate a patient's own immune system to actively respond to a disease. In the current study, several bioinformatics tools were used for designing synthetic peptide vaccines. PEPOP was used to predict peptides from HER2 ECD subdomain III in the form of discontinuous-continuous B-cell epitopes. Then, T-cell epitope prediction web servers MHCPred, SYFPEITHI, HLA peptide motif search, Propred, and SVMHC were used to identify class-I and II MHC peptides. In this way, PEPOP selected 12 discontinuous peptides from the 3D structure of the HER2 ECD subdomain III. Furthermore, T-cell epitope prediction analyses identified four peptides containing the segments 77 (384-391) and 99 (495-503) for both B and T-cell epitopes. This work is the only study to our knowledge focusing on design of in silico potential novel cancer peptide vaccines of the HER2 ECD subdomain III that contain epitopes for both B and T-cells. These findings based on bioinformatics analyses may be used in vaccine design and cancer therapy; saving time and minimizing the number of tests needed to select the best possible epitopes.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.753-757
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• 2013

Objective: To evaluate the relationships between lymph node ratio (LNR, the ratio of positive lymph nodes in excised axillary lymph nodes) and disease-free survival (DFS) by comparing with traditional absolute positive lymph node number (pN classification) for prediction of breast cancer (BC) progrnosis. Methods and Patients: We retrospectively reviewed patients who received comprehensive therapy in Department of Breast Surgery, Hubei Cancer Hospital, China from Jan 2002 to Dec 2006 (Group A), and Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, China from Jun 2008 to May 2012 (Group B). Patients were allocated to low-risk (${\leq}0.20$), intermediate-risk (> 0.20 but ${\leq}0.65$), high-risk (>0.65) groups by LNR. The primary endpoint was 5-DFS. Results: A total of 294 patients were included in our study. LNR was verified as a negative prognostic factor for DFS (P=0.002 in Group A, P<0.0001 in Group B). Then we found the effects of pN and LNR delamination on disease-free survival (DFS) had statistical significance (P=0.012 for pN and P=0.031 for LNR stratification in Group A, both of them P<0.001 in Group B). Compared to pN staging, LNR staging displayed superior performance in prognosis, the adjusted hazard ratio of recurrence being 2.07 (95%CI, 1.07 to 4.0) for intermediate risk group (P=0.030) and 2.44 (95%CI, 1.21 to 4.92) for high risk group (P=0.013) in Group A. Conclusions: LNR stratification proved an adverse prognostic factor of DFS in lymph nodes positive invasive BC using cut-off values 0.20 and 0.65, and was more predictive than traditional pN classification for 5-DFS.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.1-9
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• 2023

Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.

• Tuberculosis and Respiratory Diseases
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• v.41 no.2
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• pp.111-119
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• 1994

Background: Because of the common etiologic factor, such as smoking, lung cancer and chronic obstructive pulmonary disease are often present in the same patient. The preoperative prediction of remaining pulmonary function after the resectional surgery is very important to prevent serious complication and postoperative respiratory failure. $^{99m}Tc$-MAA perfusion scan has been used for the prediction of postoperative pulmonary function, but it may be inaccurate in case of large V/Q mismatching. We compared $^{99m}Tc$-DTPA radioaerosol inhalation scan with $^{99m}Tc$-MAA perfusion scan in predicting postoperative lung function. Method: Preoperative inhalation scan and/or perfusion scan were performed and pulmonary function test were performed preoperatively and 2 month after operation. We predicted the postoperative pulmonary functions using the following equations. Postpneurnonectomy $FEV_1$=Preop $FEV_1x%$ of total function of lung to remain Postlobectomy $FEV_1$=Preop $FEV_1{\times}$(% of total 1-function of affected lung${\times}$$\frac{Number\;of\;segments\;to\;be\;resected}{Number\;of\;segments\;of\;affected\;lung})$ Results: 1) The inhalation scan showed good correlations between measured and predicted $FEV_1$, FVC and $FEF_{25-75%}$. (correlation coefficiency; 0.94, 0.91, 0.87 respectively). 2) The perfusion scan also showed good correlations between measured and predicted $FEV_1$, FVC and $FEF_{25-75%}$. (correlation coefficiency; 0.86, 0.72, 0.87 respectively). 3) Among three parameters, $FEV_1$ showed the best correlations in the prediction by lung scans. 4) Comparison between inhalation scan and perfusion scan in predicting pulmonary function did not show any significant differneces except FVC. Conclusion: The inhalation scan and perfusion scan are very useful in the prediction of postoperative lung function and don't make a difference in the prediction of pulmonary function a1though the former showed a better correlation in FVC.

• IMMUNE NETWORK
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• v.15 no.2
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• pp.66-72
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• 2015

Currently, detecting biochemical differences before and after allogeneic stem cell transplantation (SCT) for improved prediction of acute graft-versus-host disease (aGVHD) is a major clinical challenge. In this pilot study, we analyzed the kinetics of circulating adipokine levels in patients with or without aGVHD before and after allogeneic SCT. Serum samples were obtained and stored at $-80^{\circ}C$ within 3 hours after collection, prior to conditioning and at engraftment after transplantation. A protein array system was used to measure the levels of 7 adipokines of patients with aGVHD (n=20) and without aGVHD (n=20). The resistin level at engraftment was significantly increased (p<0.001) after transplantation, regardless of aGVHD occurrence. In the non-aGVHD group, the concentrations of the hepatocyte growth factor (HGF) (mean values${\pm}$SD; $206.6{\pm}34.3$ vs. $432.3{\pm}108.9pg/ml$, p=0.040) and angiopoietin-2 (ANG-2) (mean values${\pm}$SD; $3,197.2{\pm}328.3$ vs. $4,471.8{\pm}568.4pg/ml$, p=0.037) at engraftment were significantly higher than those of the pre-transplant period, whereas in the aGVHD group, the levels of adipokines did not change after transplantation. Our study suggests that changes in serum HGF and ANG-2 levels could be considered helpful markers for the subsequent occurrence of aGVHD.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1125-1131
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• 2014

Background: Schistosomiasis is a parasitic disease causing chronic ill health in humans with a serious consequences for socio-economic development in tropical and subtropical regions. There is also evidence linking Schistosoma mansoni to colonic carcinoma occurrence. The aim of this study was to evaluate some inflammatory and oxidative stress biomarkers, as well as L-fucose as linkers between intestinal schistosomiasis and colonic dysplasia development in mice. Materials and Methods: This study was conducted upon 80 mice that were divided the control group (10 non infected mice) and infected group which was subdivided into 7 sub-groups (10 mice each) according to the time of sacrifaction in the post infection (p.i.) period, 10 mice being sacrificed every two weeks from 6 weeks p.i. to 18 weeks p.i. Tumor necrosis factor alpha (TNF-${\alpha}$), inducible nitric oxide synthase (iNOS), and pentraxin 3 (PTX3) levels were estimated by immunoassay. The L-fucose level, and thioredoxin reductase (TrxR) and lactate dehydrogenase (LDH) activities were also evaluated in colonic tissue. Results: The current study revealed statistically significant elevation in the studied biochemical markers especially at 16 and 18 weeks p.i. The results were confirmed by histopathological examination that revealed atypical architectural and cytological changes in the form of epithelial surface serration and nuclear hyper-chromatizia at 14, 16 and 18 weeks p.i. Conclusions: inflammation, oxidative stress and L-fucose together may form an important link between Schistosomal mansoni infection and colonic dysplasia and they can be new tools for prediction of colonic dysplasia development in experimental schistosomiasis.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.4113-4117
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• 2012

Breast cancer is a prevalent heterogeneous malignant disease. Gene expression profiling by DNA microarray can classify breast tumors into five different molecular subtypes: luminal A, luminal B, HER-2, basal and normal-like which have differing prognosis. Recently it has been shown that immunohistochemistry (IHC) markers including estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2), can divide tumors to main subtypes: luminal A (ER+; PR+/-; HER-2-), luminal B (ER+;PR+/-; HER-2+), basal-like (ER-;PR-;HER2-) and Her2+ (ER-; PR-; HER-2+). Some subtypes such as basal-like subtype have been characterized by poor prognosis and reduced overall survival. Due to the importance of the ER signaling pathway in mammary cell proliferation; it appears that epigenetic changes in the $ER{\alpha}$ gene as a central component of this pathway, may contribute to prognostic prediction. Thus this study aimed to clarify the correlation of different IHC-based subtypes of breast tumors with $ER{\alpha}$ methylation in Iranian breast cancer patients. For this purpose one hundred fresh breast tumors obtained by surgical resection underwent DNA extraction for assessment of their ER methylation status by methylation specific PCR (MSP). These tumors were classified into main subtypes according to IHC markers and data were collected on pathological features of the patients. $ER{\alpha}$ methylation was found in 25 of 28 (89.3%) basal tumors, 21 of 24 (87.5%) Her2+ tumors, 18 of 34 (52.9%) luminal A tumors and 7 of 14 (50%) luminal B tumors. A strong correlation was found between $ER{\alpha}$ methylation and poor prognosis tumor subtypes (basal and Her2+) in patients (P<0.001). Our findings show that $ER{\alpha}$ methylation is correlated with poor prognosis subtypes of breast tumors in Iranian patients and may play an important role in pathogenesis of the more aggressive breast tumors.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1203-1214
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• 2016

Obesity is a risk factor for various diseases as well as itself a disease and associated with socioeconomic factors. The obesity proportion has been increasing in Korea over about 15 years so that investigation of the socioeconomic factors related with obesity is important in terms of preventation of obesity. In particular, the association between obesity and socioeconomic status varies with gender and has spatial dependency. In the paper, we estimate the effects of socioeconomic factors on obesity proportion by gender, considering the spatial correlation. Here, a conditional autoregressive model under the Bayesian framework is used in order to take into account the spatial dependency. For the real applicaiton, we use the obestiy proportion dataset at 25 districts of Seoul in 2010. We compare the proposed spatial model with a non-spatial model in terms of the goodness-of-fit and prediction measures so the spatial model performs well.

• Journal of Breast Disease
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• v.6 no.2
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• pp.35-38
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• 2018

Purpose: The eighth American Joint Committee on Cancer staging system for breast cancer was recently published to more accurately predict the prognosis by adding biomarkers such as estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2. However, this system is very complicated and difficult to use by clinicians. The authors developed a program to aid in setting up the staging system and confirmed its usefulness by applying it to theoretical combinations and actual clinical data. Methods: The program was developed using the Microsoft Excel Macro. It was used for the anatomic, clinical and pathological prognostic staging of 588 theoretical combinations. The stages were also calculated the stages using 840 patients with breast cancer without carcinoma in situ or distant metastasis who did not undergo preoperative chemotherapy. Results: The anatomic, clinical and pathological prognostic stages were identical in 240 out of 588 theoretical combinations. In the actual patients' data, stages IB and IIIB were more frequent in clinical and pathological prognostic stages than in the anatomic stage. The anatomic stage was similar to the clinical prognostic stage in 58.2% and to the pathological prognostic stage in 61.9% of patients. Oncotype DX changed the pathological prognostic stage in 2.1% of patients. Conclusion: We developed a program for the new American Joint Committee on Cancer staging system that will be useful for clinical prognostic prediction and large survival data analysis.