• The Korea Journal of Herbology
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• v.21 no.1
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• pp.79-87
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• 2006

Objectives : Effects of Rhodiola rosea root on cancers on stomach, breast, lung, and liver were examined. Methods : Water extracts and methanol extracts of Rhodiola rosea root were treated on cancer cells, and its effects on cancers were examined. Results : 1. Water extracts and methanol extracts of Rhodiola rosea root was less harmful in its lowest density 0.25 mg/mL (9.l%와 10.5%), but became more harmful as its density increased. 2. As for human stomach adenocarcinoma cells AGS, breast adenocarcinoma cells MCF-7, and lung carcinoma cells A549, methanol extracts showed 70-77% inhibition of cancer cells in high density(1 mg/mL), and water extracts showed 60-70% inhibition rate and its selective death rate was less than 2.5. Conclusion : Rhodiola rosea root can be used to treat cancers and to increase immunity.

• Journal of Chest Surgery
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• v.46 no.4
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• pp.295-298
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• 2013

Solitary fibrous tumor is a rare spindle cell mesenchymal tumor entity, with either benign or malignant behavior that cannot be accurately predicted by histological findings. An intrapulmonary site of origin is even rarer. We report a case of a 51-year-old woman in whom an abnormal nodule in the lower right lung was detected during staging for sigmoid adenocarcinoma. The nodule was excised and pathological examination revealed an intrapulmonary solitary fibrous tumor.

• Tuberculosis and Respiratory Diseases
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• v.58 no.6
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• pp.554-561
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• 2005

The clinical and radiographic findings of lung cancer have been well established many journals. Even if the radiographic findings of lung cancer show a typical pattern, the specific cell type of lung cancer sometimes needs to be determined prior to a pathological diagnosis. For example, the usual finding of a squamous cell carcinoma is similar to other cancer types such as an adenocarcinoma or a small cell carcinoma but with a lower incidence. Therefore, it should not be used to make a diagnosis of the cell type prior to a pathological diagnosis. Many unusual findings of lung cancer, so called atypical pattern have been reported, but atypical findings are widely accepted. The more important thing is not to diagnose a specific cell type of cancer but to differentiate it from other benign conditions such as tuberculosis, fungal infections or organizing pneumonia. This paper presents typical information of the cell type of lung cancer along with the atypical radiographic findings.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.3
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• pp.125-131
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• 2015

The discovery of activating mutations in EGFR in a subset of lung adenocarcinomas was a major advance in our understanding of lung adenocarcinoma biology, and has led to groundbreaking studies that have demonstrated the efficacy of tyrosine kinase inhibitor therapy. Cytologic specimen procedures have become increasingly popular for obtaining diagnostic material in lung carcinomas. However, frequently the small amount of material or sparseness of tumor cells obtained from cytologic preparations limit the number of specialized studies, such as mutation analysis, that can be performed. In this study we used microdissection to isolate small numbers of tumor cells to assess for EGFR mutations from 76 cytological smear slides of patients with lung adenocarcinomas. We compared our results with previous molecular assays that had been performed on either surgical or cytology specimens as part of the patient's initial clinical work-up. Not only were we able to detect the identical EGFR mutation through the pyrosequencing, but we were also able to consistently detect the mutation from as few as 25 microdissected tumor cells. Furthermore, isolating a purer population of tumor cells resulted in increased sensitivity of mutation detection as we were able to detect mutations from microdissection-enriched cases. Therefore, microdissection can not only significantly increase the number of lung adenocarcinoma patients that can be screened for EGFR mutations, but can also facilitate the use of cytologic samples in the newly emerging field of molecular-based personalized therapies.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.835-838
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• 2016

Background: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor morphology. Materials and Methods: We have made an attempt to evaluate effectiveness of machine learning algorithms in the task of lung cancer classification based on gene expression levels. We processed four publicly available data sets. The Dana-Farber Cancer Institute data set contains 203 samples and the task was to classify four cancer types and sound tissue samples. With the University of Michigan data set of 96 samples, the task was to execute a binary classification of adenocarcinoma and non-neoplastic tissues. The University of Toronto data set contains 39 samples and the task was to detect recurrence, while with the Brigham and Women's Hospital data set of 181 samples it was to make a binary classification of malignant pleural mesothelioma and adenocarcinoma. We used the k-nearest neighbor algorithm (k=1, k=5, k=10), naive Bayes classifier with assumption of both a normal distribution of attributes and a distribution through histograms, support vector machine and C4.5 decision tree. Effectiveness of machine learning algorithms was evaluated with the Matthews correlation coefficient. Results: The support vector machine method showed best results among data sets from the Dana-Farber Cancer Institute and Brigham and Women's Hospital. All algorithms with the exception of the C4.5 decision tree showed maximum potential effectiveness in the University of Michigan data set. However, the C4.5 decision tree showed best results for the University of Toronto data set. Conclusions: Machine learning algorithms can be used for lung cancer morphology classification and similar tasks based on gene expression level evaluation.

• Tuberculosis and Respiratory Diseases
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• v.75 no.4
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• pp.140-149
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• 2013

Background: Plasminogen activator inhibitor type 1 (PAI-1), an important regulator of plasminogen activator system which controls degradation of extracellular membrane and progression of tumor cells, and PAI-1 gene polymorphic variants have been known as the prognostic biomarkers of non-small cell lung cancer patients. Recently, experimental in vitro study revealed that transforming growth factor-${\beta}1$ initiated PAI-1 transcription through epithelial growth factor receptor (EGFR) signaling pathway. However, there is little clinical evidence on the association between PAI-1 A15T gene polymorphism and prognosis of Korean population with pulmonary adenocarcinoma and the influence of activating mutation of EGFR kinase domain. Methods: We retrospectively reviewed the medical records of 171 patients who were diagnosed with pulmonary adenocarcinoma and undergone EGFR mutation analysis from 1995 through 2009. Results: In all patients with pulmonary adenocarcinoma, there was no significant association between PAI-1 A15T polymorphic variants and prognosis for overall survival. However, further subgroup analysis showed that the group with AG/AA genotype had a shorter 3-year survival time than the group with GG genotype in patients with EGFR mutant-type pulmonary adenocarcinoma (mean survival time, 24.9 months vs. 32.5 months, respectively; p=0.015). In multivariate analysis of 3-year survival for patients with pulmonary adenocarcinoma harboring mutant-type EGFR, the AG/AA genotype carriers had poorer prognosis than the GG genotype carriers (hazard ratio, 7.729; 95% confidence interval, 1.414-42.250; p=0.018). Conclusion: According to our study of Korean population with pulmonary adenocarcinoma, AG/AA genotype of PAI-1 A15T would be a significant predictor of poor short-term survival in patients with pulmonary adenocarcinoma harboring mutant-type EGFR.

• Journal of Digestive Cancer Research
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• v.10 no.2
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• pp.112-116
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• 2022

Idiopathic inflammatory myopathy (IIM) is known for its association with malignant diseases. Moreover, various solid organ malignancies, such as ovarian, breast, lung, esophageal, stomach, and colorectal cancers, have been reported to occur with IIM. Furthermore, its relationship with hematologic malignancies, including non-Hodgkin lymphoma, myeloma, and leukemia, has been reported. However, to date, IIM related to pancreatic cancer has scarcely been reported, particularly in patients with polymyositis (PM). Therefore, here we report a case of PM developed immediately after the diagnosis of pancreatic ductal adenocarcinoma.

• Tuberculosis and Respiratory Diseases
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• v.46 no.4
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• pp.455-465
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• 1999

Background: Even though lung cancer has become a major cancer in Korea, national survey for lung cancer has not been available except several reports from individual hospitals. Methods: Korean Academy of Tuberculosis and Respiratory Diseases retrospectively investigated the characteristics of lung cancer diagnosed from January 1997 to December 1997 at general hospitals over 400 beds. Results: Among 3,794 patients, 76.8% are smokers and 89.8% of male patients are smokers. Squamous cell carcinoma is the leading type of lung cancer(44.7%) followed by adenocarcinoma(27.9%). Smoking rate in adenocarcinoma was significantly lower than in squamous cell carcinoma and small cell cancer. Cough is the most common symptom, however, 7.2% are asymptomatic. Bronchoscopic biopsy has a main role in the diagnosis of squamous cell carcinoma and small cell cancer but percutaneous needle biopsy has more important role in adenocarcinoma. Two-thirds of NSCLC patients were found in unresectable advanced stages. Conclusion: In contrast to other countries, squamous cell carcinoma is still the most frequent type of lung cancer. High proportions of smoker and advanced, unresectable lung cancer urge us to develop the program for cessation of smoking and early detection.

• Journal of Chest Surgery
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• v.10 no.2
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• pp.183-189
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• 1977

There has been an alarming rise in the incidence of carcinoma of the lung in the world. The increase of the disease has been greater in men than in women, but even in women the rate has doubled in the last 20 years. During the 20 year period 1957 through 1976, 33 women with proven primary carcinoma of the lung were treated at Department of Thoracic Surgery, Seoul National University Hospital. During the period of survey, 170 consecutive cases of primary bronchogenic carcinoma were encountered in men, a male to female ratio of 5.2: 1. Ages of patients with bronchogenic carcinoma in women ranged from twenty-seven to sixty-eight years and most of them were over 40 years of age. The duration between the onset of symptoms and admission was about 9 months and the most common complaints were cough [66.6%], chest pain [60.6%], hemoptysis [48.4%] and dyspnea [45.4%]. Bronchogenic carcinoma developed most frequently in the upper lobes, and twelve [36.3%] of cases were squamous cell type, nine [27.2%] were anaplastic cell type, six [18.2%] were adenocarcinoma, one was alveolar cell type and five were unclassified type, in contrast to the usual predominence of adenocarcinoma among women in other reports. One half of the patients were inoperable and resection was feasible in only 24.2 per cent of the patients. There was no operative mortality but one case had bronchopleural fistula after pneumonectomy. Most patients with bronchogenic carcinoma in women were from large cities. Cigarette smoking appeared to be related to the occurrence of the squamous cell and anaplastic cell carcinoma because all heavy smokers had squamous cell or anaplastic cell carcinoma.

• Annual Conference of KIPS
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• 2021.11a
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• pp.779-782
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• 2021

Survival time analysis is one of the main methods used by the pathologist to prognosis for cancer patients. In this paper, we strive to estimate the individual survival time of Adenocarcinoma (ADC) lung cancer patients from pathological images by adopting the convolutional neural network called the SurvPatchV1 model. First, we extracted tissue patches from the whole-slide images (WSI) to deal with extremely large dimensions of WSI. Then the survival time of each patch is estimated through the SurvPatchV1 model. Finally, the individual survival time of each patient is computed. The proposed method is trained and tested on the subset of the NLST dataset for ADC lung cancer. The result demonstrates that our model can obtain all tissue information in lieu of only tumor information in a whole pathological image to estimate the individual survival time.