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    ์ž ์žฌ๊ณ„์ธต๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2019. 2. ์ด์ข…์ˆ˜.๊ธ€๋กœ๋ฒŒ ์ „๋ ฅ์‹œ์žฅ์€ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „์„ ์ค‘์‹ฌ์œผ๋กœ ๊ธ‰๊ฒฉํ•˜๊ฒŒ ์ „ํ™˜๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ํ•œ๊ตญ ์ •๋ถ€๋„ 2030๋…„๊นŒ์ง€ ๋ฐœ์ „๋Ÿ‰์˜ 20%๋ฅผ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€๋กœ ํ™•๋Œ€ํ•˜๋Š” ํš๊ธฐ์ ์ธ ์—๋„ˆ์ง€ ์ „ํ™˜ ์ •์ฑ…์„ ์ˆ˜๋ฆฝํ•˜์˜€๋‹ค. ๊ธ€๋กœ๋ฒŒ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์˜ ํ™•๋Œ€๋Š” ๊ตญ๊ฐ€๋ณ„๋กœ ๋‹ค์†Œ ์ฐจ์ด๋Š” ์žˆ์œผ๋‚˜ ๊ตญ๋ฏผ ์ƒํ™œ ๋ฐ ์•ˆ์ „๊ณผ ๋ฐ€์ ‘ํ•œ ์ „๋ ฅ์‚ฐ์—…์ด๋ผ๋Š” ํŠน์„ฑ๊ณผ ์ •๋ถ€์˜ ์ค‘โˆ™์žฅ๊ธฐ์ ์ธ ํ™•๋Œ€ ๋ชฉํ‘œ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ณต๊ฒฉ์  ์ง€์› ์ •์ฑ…์— ์˜ํ•ด ์ถ”์ง„๋˜๋Š” ์ •๋ถ€ ์˜์กดํ˜• ์‚ฐ์—…์ด๋ผ๋Š” ์ ์—์„œ ๊ด€๋ จ ์ •์ฑ…์— ๋Œ€ํ•œ ๊ตญ๋ฏผ ์ˆ˜์šฉ์„ฑ์ด ์ ์ฐจ ์ค‘์š”ํ•˜๊ฒŒ ๋‹ค๋ค„์ง€๋Š” ๊ณตํ†ต์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋งฅ๋ฝ์—์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ •๋ถ€๊ฐ€ 2012๋…„ ๋„์ž…ํ•œ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ๊ณต๊ธ‰์˜๋ฌดํ™”(Renewable Portfolio StandardRPS) ์ •์ฑ… ์†์„ฑ์— ๋Œ€ํ•œ ๊ตญ๋ฏผ์˜ ์ด์งˆ์  ์„ ํ˜ธ์™€ ์ˆ˜์šฉ์„ฑ์„ ์ปจ์กฐ์ธํŠธ ์กฐ์‚ฌ(Conjoint Survey)์™€ ์ž ์žฌ๊ณ„์ธต๋ชจํ˜•(latent class model)์„ ํ™œ์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ดํ›„, ์ถ”์ • ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์‹œ๋‚˜๋ฆฌ์˜ค ๋ถ„์„์„ ์‚ฌ์šฉํ•˜์—ฌ, ํ•œ๊ตญ ์ •๋ถ€๊ฐ€ ์ถ”์ง„ํ•˜๋Š” ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์— ๋Œ€ํ•œ 2020๋…„, 2025๋…„ 2030๋…„ ๋‹จ๊ณ„๋ณ„ ๊ตญ๋ฏผ์˜ ๊ณ„์ธต๋ณ„ ์ˆ˜์šฉ๋ฅ ์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜์˜€๋‹ค. ์•„์šธ๋Ÿฌ, ์ •์ฑ… ์ˆ˜์šฉ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ •์ฑ… ์ธ์ง€์ˆ˜์ค€ ์š”์ธ๊ณผ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋งค์ฒด๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„์„ ํ†ตํ•ด ๊ณ„์ธต๋ณ„ ํšจ๊ณผ์ ์ธ ์ •๋ณดํš๋“ ๊ฒฝ๋กœ๋ฅผ ์‹๋ณ„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ, ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์— ๋Œ€ํ•œ ๊ตญ๋ฏผ์˜ ์„ ํ˜ธ๋Š” 2๊ฐœ์˜ ์ด์งˆ์  ๊ณ„์ธต์œผ๋กœ ์‹๋ณ„๋˜์—ˆ์œผ๋ฉฐ, ์—ฐ๊ฐ„ ์ •์ „์‹œ๊ฐ„ ๊ฐ์†Œ๋ฅผ ์„ ํ˜ธํ•˜๋Š” ํ˜„์ƒ์œ ์ง€๊ณ„์ธต๊ณผ ์˜จ์‹ค๊ฐ€์Šค ๋ฐฐ์ถœ ๊ฐ์†Œ๋ฅผ ์„ ํ˜ธํ•˜๋Š” ํ•ฉ๋ฆฌ์  ์„ ํƒ๊ณ„์ธต์œผ๋กœ ๋‚˜๋ˆ ์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์„ ํ˜ธ์˜ ์ด์งˆ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์นœ ์ •์ฑ… ์ธ์ง€ ์š”์ธ์€ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ•„์š”์„ฑ ๊ณผ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์˜ ๋น„์šฉ๊ณผ ํŽธ์ต์— ๋Œ€ํ•œ ํ‰๊ฐ€์˜€๋‹ค. ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์— ๋Œ€ํ•œ ๊ตญ๋ฏผ ์ˆ˜์šฉ๋ฅ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋Š” 2020๋…„ 63.2%, 2025๋…„ 48.95%, 2030๋…„ 38.15%๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‹จ๊ณ„์˜ ์ง„ํ–‰์— ๋”ฐ๋ฅธ ๊ตญ๋ฏผ ์ˆ˜์šฉ๋ฅ  ํ•˜๋ฝ์˜ ๊ฐ€์žฅ ํฐ ๋™์ธ์€ ์ „๊ธฐ์š”๊ธˆ ์ƒ์Šน์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ •์ฑ… ์ธ์ง€์— ์—ฐ๊ด€์„ฑ์ด ๋†’์€ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ์ฑ„๋„์€ ์ธํ„ฐ๋„ท, ์ฃผ๋ณ€์ง€์ธ, ๊ทธ๋ฆฌ๊ณ  ์‹ ๋ฌธ/์žก์ง€๋กœ ๋‘ ๊ณ„์ธต์ด ๋™์ผํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์œผ๋‚˜, ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ์ถœ์ฒ˜๋Š” ๊ณ„์ธต๋ณ„๋กœ ์ƒ์ดํ•˜๊ฒŒ ์‹๋ณ„๋˜์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ •๋ถ€์˜ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ… ์ถ”์ง„์— ๋Œ€ํ•ด ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์ •์ฑ…์  ํ•จ์˜๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ์šฐ์„ , ์ •๋ถ€๋Š” ์ •์ฑ… ์ดˆ๊ธฐ์—๋Š” ์ •์ฑ… ์†์„ฑ์— ๋Œ€ํ•œ ๊ตญ๋ฏผ์˜ ์ด์งˆ์  ์„ ํ˜ธ๋ฅผ ๋ฐ˜๋“œ์‹œ ๊ณ ๋ คํ•˜์—ฌ ์‚ฌํšŒ์  ๊ฐˆ๋“ฑ์„ ์ตœ์†Œํ™”ํ•˜์—ฌ์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ, ์ค‘์žฅ๊ธฐ์ ์œผ๋กœ๋Š” ์ „๊ธฐ์š”๊ธˆ ์ƒ์Šน์— ๋Œ€ํ•œ ๊ตญ๋ฏผ ์ˆ˜์šฉ๋ฅ  ๊ฐ์†Œ์— ๋Œ€๋น„ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ง€์†์ ์ธ ๊ธฐ์ˆ ๊ฐœ๋ฐœ์„ ํ†ตํ•ด ๊ฐ€๊ฒฉ๊ฒฝ์Ÿ๋ ฅ์„ ํ™•๋ณดํ•˜๊ณ , ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์˜ ํ‰๊ฐ€์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ์ •๋ณด ์ œ๊ณต์„ ํ†ตํ•ด ๊ตญ๋ฏผ ์ˆ˜์šฉ์„ฑ์„ ์ œ๊ณ ํ•ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ณ„์ธต๋ณ„๋กœ ํšจ๊ณผ์ ์ธ ์ •์ฑ… ์ธ์ง€์š”์ธ๊ณผ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋งค์ฒด๋ฅผ ํ™œ์šฉํ•œ ์ „๋žต์  ์ •์ฑ…ํ™๋ณด๋ฅผ ํ†ตํ•ด ์ •์ฑ…์ง‘ํ–‰์˜ ํšจ์œจ์„ฑ์„ ์ œ๊ณ ํ•ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค.The global electricity market is rapidly shifting toward renewable energy, and the Korean government has also established a landmark energy transition policy to expand the proportion of renewable energy in electricity generation to 20% by 2030. As countries around the world have actively implemented renewable energy policies, public acceptance became more important than before. This is because the renewable energy sector is a government-led policy-dependent industry and an electricity industry closely linked to people's lives and national security. In this context, this study used a conjoint survey and a latent class model to examine the publics heterogeneous preference and acceptance of the Renewable Portfolio Standard(RPS) policy adopted by the government in 2012. Furthermore, this study conducted simulation analysis based on the estimation results and possible policy scenarios to investigate the public acceptance rate of the Korean government 's renewalble energy policy as of 2020, 2025, and 2030 In addition, by analyzing the correlation between perceptions and information searching patterns of the public, the effective communication channels for information campaign were identified. As a result, it was found that the public's preference for renewable energy expansion policy can be classified into two heterogeneous classesone is a careful stabilizer preferring to reduce annual power outage and the other is a rational pragmatist who prefers to reduce greenhouse gas emissions. The significant factors that affect public preferences were need for renewable energy and perception of costs and benefits of renewable energy. From the simulation analysis, it was found that public acceptance for renewable energy expansion policies are 63.2% in 2020, 48.95% in 2025, and 38.15% in 2030. The biggest driver of declining public acceptance rate was the increase in electricity prices. In conclusion, based on the results of this study, the following policy implications can be provided for the government's policy of expanding renewable energy. First, the government should minimize the social conflict by considering the heterogeneous preference of the people for the policy attributes when implementing the renewable energy policy. In addition, the government needs to ensure price competitiveness through continuous technological development of renewable energy and to provide accurate information on the estimation of renewable energy in order to avoid or minimize the public resistance for the rise of electricity prices in the medium and long term. Finally, the efficiency of policy implementation should be improved through strategic Public Relation, which utilizes effective communication media for positively changing the public perceptions.์ดˆ ๋ก iii ๋ชฉ ์ฐจ v ํ‘œ ๋ชฉ์ฐจ vii ๊ทธ๋ฆผ ๋ชฉ์ฐจ viii 1. ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 3 1.3 ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ 5 2. ๋ฌธํ—Œ ์—ฐ๊ตฌ 6 2.1 ์šฐ๋ฆฌ๋‚˜๋ผ ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐ ์ •์ฑ… ํ˜„ํ™ฉ 6 2.2 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์— ๋Œ€ํ•œ ์‚ฌํšŒ์  ์ˆ˜์šฉ์„ฑ๊ณผ ์„ ํ˜ธ ์—ฐ๊ตฌ 10 2.2.1 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์— ๋Œ€ํ•œ ์‚ฌํšŒ์  ์ˆ˜์šฉ์„ฑ ์—ฐ๊ตฌ 10 2.2.2 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€์— ๋Œ€ํ•œ ์†Œ๋น„์ž ์„ ํ˜ธ ๋ถ„์„ 11 2.2.3 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ์ˆ˜์šฉ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ ์—ฐ๊ตฌ 15 2.3 ์ •์ฑ…์˜ ์ดํ•ด๋„์™€ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋งค์ฒด์™€์˜ ๊ด€๊ณ„ ์—ฐ๊ตฌ 18 2.4 ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์™€ ์—ฐ๊ตฌ ๋™๊ธฐ 19 3. ์—ฐ๊ตฌ๋ชจํ˜• ๋ฐ ๋ฐฉ๋ฒ•๋ก  23 3.1 ์—ฐ๊ตฌ์„ค๊ณ„ 23 3.2 ์ž๋ฃŒ์˜ ๊ตฌ์„ฑ 26 3.2.1 ํ‘œ๋ณธ ๊ธฐ์ดˆ ํ†ต๊ณ„๋Ÿ‰ 26 3.2.2 ์„ ํƒ์‹คํ—˜ 27 3.2.3 ๊ธฐ์ดˆ ์„ค๋ฌธ์กฐ์‚ฌ 31 3.2.4 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์˜ ๊ธฐ๋Œ€ํŽธ์ต๊ณผ ๊ธฐ๋Œ€๋น„์šฉ 36 3.3 ์‹ค์ฆ๋ชจํ˜• 45 3.3.1 ์ž ์žฌ๊ณ„์ธต๋ชจํ˜•(Latent class model) 45 3.3.2 ์ •์ฑ… ์ธ์ง€์ˆ˜์ค€๊ณผ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋งค์ฒด์™€์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 53 4. ์—ฐ๊ตฌ๊ฒฐ๊ณผ ๋ฐ ํ•ด์„ 55 4.1 ์ž ์žฌ๊ณ„์ธต๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ 56 4.1.1 ์„ ํ˜ธ ๊ณ„์ธต ๋ฐ ๊ณ„์ธต๋ณ„ ์„ ํ˜ธ๊ตฌ์กฐ ๋ถ„์„ 56 4.1.2 ๋ฏผ๊ฐ๋„ ๋ถ„์„ 61 4.2 ์‹ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์˜ ๊ตญ๋ฏผ ์ˆ˜์šฉ๋ฅ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ถ„์„ 69 4.3 ๊ณ„์ธต๋ณ„ ์ •์ฑ… ์ธ์ง€์ˆ˜์ค€๊ณผ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋งค์ฒด์™€์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 75 5. ๊ฒฐ๋ก  ๋ฐ ์‹œ์‚ฌ์  81 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 91 ๋ถ€๋ก : ์„ค๋ฌธ์ง€ 98 Abstract 109Maste

    An Intrarenal Adrenocortical Carcinoma Arising in an Adrenal Rest

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    We describe a case of a 61-year-old Korean man who was diagnosed with renal cell carcinoma that was discovered on abdominopelvic computed tomography obtained after the patient complained of back pain. A radical nephrectomy was performed, and the surgical specimen showed a relatively well-circumscribed and yellowish lobulated hard mass. Microscopically, the tumor showed sheets and nests of hypercellular pleomorphic cells with thick fibrous septation, frequent mitoses, and areas of adrenal cortical-like tissue. Immunohistochemical staining revealed that the tumor cells were positive for inhibin-ฮฑ, vimentin, synaptophysin, and melan A. It also revealed that the tumor cells were negative for pan-cytokeratin, epithelial membrane antigen, paired box 8, ฮฑ-methylacyl-coenzyme A racemase, CD10, cytokeratin 7, carbonic anhydrase 9, c-Kit, renal cell carcinoma, transcription factor E3, human melanoma black 45, desmin, smooth muscle actin, S-100, chromogranin A, CD34, anaplastic lymphoma kinase, and integrase interactor 1. Based on these histopathological and immunohistochemical findings, we diagnosed the tumor as intrarenal adrenocortical carcinoma arising in an adrenal rest. Several cases of intrarenal adrenocortical carcinoma have been reported, although they are very rare. Due to its poor prognosis and common recurrence or metastasis, clinicians and pathologists must be aware of this entity.ope

    Expression of DNA methylation-related proteins in breast phyllodes tumor

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    The purpose of this study is to research the expression of DNA methylation-related proteins in phyllodes tumors of the breast and to study the implication on patient outcomes. We generated tissue microarrays (TMAs) of 196 phyllodes tumors (PT) and performed immunohistochemical staining for 5-meC and the DNA methylationrelated proteins DNMT1 and ISL-1. The staining results were analyzed and compared with clinicopathologic parameters. A total of 196 cases were included in this study, of which 153 were benign, 27 were borderline, and 16 were malignant. The levels of DNMT1, 5 meC, and ISL-1 in the stromal component of tumors increased with increasing grade (P<0.001). Especially, high stromal positivity of DNMT1 and ISL-1 were associated with increased distant metastasis (P=0.001, and P=0.013, respectively). Univariate analysis for factors associated with decreased disease free survival and overall survival identified DNMT1 high positivity (P=0.002 and P<0.001, respectively) and stromal ISL-1 high positivity (P<0.001 and P<0.001, respectively). Among borderline phyllodes tumors, stromal DNMT1 high positivity was associated with decreased OS (P=0.015). In conclusion, DNA methylation and expression of methylation-related proteins in the stromal component increased with increasing histologic grade in phyllodes tumors. In addition, overexpression stromal expression of DNMT1 and ISL-1 was associated with poor prognosis.ope

    The value of phosphohistone H3 as a proliferation marker for evaluating invasive breast cancers: A comparative study with Ki67

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    BACKGROUND: Established measurements of proliferation in breast cancer are Ki67 and mitotic-activity-index (MAI), with problems in reproducibility and prognostic accuracy. Phosphohistone H3 (PHH3), a relatively novel IHC marker is specific for mitosis with good reproducibility. We hypothesized that PHH3 would be more reproducible and better represent proliferation than Ki67. RESULTS: PHH3 identified easily-missed mitosis by MAI, as demonstrated by upgrading M grade at diagnosis (n = 29/218, evenly distributed). PHH3 accurately found hot-spots, supported by mitotic count agreement between low-power and 10HPFs (R2 = 0.999; P = 0.001). PHH3 was more reproducible than Ki67, measured by five-rater inter-class correlation coefficient (0.904 > 0.712; P = 0.008). Finally, despite a relatively short follow-up (median 46 months; 7 recurrences) PHH3 was the only variable correlated with disease-free survival (P = 0.043), while all other conventional clinicopathologic variables, including Ki67 (P = 0.356), did not. MATERIALS AND METHODS: We compared Ki67 and PHH3 for 218 breast cancer surgical cases diagnosed from 2012 to 2013 at Severance hospital. The most representative invasive breast cancer surgical slides were immunohistochemically stained for Ki67 and PHH3. CONCLUSIONS: Poor reproducibility and inadequate representation of proliferation of Ki67 and MAI may be improved by PHH3, allowing better accuracy in breast cancer diagnostics.ope

    Study on Korean atists studied in Paris in the 1920s and 1930s

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์„œ์–‘ํ™”๊ณผ ๋ฏธ์ˆ ์ด๋ก ์ „๊ณต, 2011.8. ์ •ํ˜•๋ฏผ.Maste

    ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•์— ๋”ฐ๋ฅธ ์œ ๋ฐฉ์•” ๋Œ€์‚ฌ ํŠน์„ฑ

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    In the breast cancer which characteristically produces tumor stroma, reverse Warburg effect is suggested as its tumor metabolism. It is the theory that the metabolic interaction between tumor cells and stromal cells plays an important role in survival and growth of tumor. Cancer-associated fibroblast (CAF), the stromal cell which plays a key role in the theory, is the most important component of tumor microenvironment (TME) and it is recently classified into several subtypes (FAP, S100A4, PDGFRฮฑ, and PDGFRฮฒ), each of which has separate functional characteristics. In this study, we aimed to investigate differences in metabolic interaction between tumor cells and stromal cells depending on subtypes of CAF and investigate impacts of tumor stroma-targeted material on tumorigenesis and growth of tumor depending on subtypes of CAF and finally recognize the possibility of tumor stroma-targeted material as a targeted therapy of breast cancer. We produced four cancer-associated fibroblast (CAF) subtype cell lines, which were stably expressing each CAF marker (FAP, S100A4, PDGFRฮฑ, and PDGFRฮฒ) and analyzed differences in metabolic interaction of each CAF subtype with breast cancer molecular subtypes. We also examined migration assay and invasion assay to investigate the effect of each CAF subtype on metastasis and invasion ability of cancer cells. Then, we produced a tumor xenograft model using BALB/C nude mice to confirm cell line studies. Among four CAF subtypes, we identified that FB-PDGFRฮฒ activated glycolysis, mitophagy, and autophagy of MDA-MB-231 and FB-FAP activated glycolysis and autophagy of triple negative breast cancer (TNBC) cell lines. FB-FAP especially played an important role in cancer behavior of TNBC cells; MDA-MB-231 and MDA-MB-468. Also, in mice xenograft model, it showed that FB-FAP activated glycolysis and autophagy metabolism of TNBC cell lines. In inhibition study with knocked down fibroblasts, FB-siPDGFRฮฒ and FB-siFAP cells, the tumor metabolism and its behavior of MDA-MB-231, MDA-MB-468, and mice xenograft models was consistent with the results from studies of TNBC cell lines and mice xenograft models co-cultured with FB-PDGFRฮฒ and FB-FAP. In conclusion, CAF has heterogeneous characteristic in that each breast cancer molecular subtype shows differences in the expression of metabolic related markers and different cancer behavior depending on co-cultured CAF subtype. Among CAF subtypes, FB-FAP seems to promote tumor formation and growth through glycolysis and autophagy of TNBC and we suggest it has a potential role as a therapeutic target for TNBC. ์ข…์–‘ ๊ธฐ์งˆ์„ ํŠน์ง•์ ์œผ๋กœ ํ˜•์„ฑํ•˜๋Š” ์œ ๋ฐฉ์•”์—์„œ๋Š” ์ข…์–‘ ๋Œ€์‚ฌ๋กœ ๋ฆฌ๋ฒ„์Šค ์™€๋ฒ„๊ทธ ํšจ๊ณผ๊ฐ€ ์ œ์‹œ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์ข…์–‘ ์„ธํฌ์™€ ๊ธฐ์งˆ ์„ธํฌ ๊ฐ„ ๋Œ€์‚ฌ ์ƒํ˜ธ์ž‘์šฉ์ด ์žˆ์œผ๋ฉฐ, ์ข…์–‘์˜ ์ƒ์กด ๋ฐ ์„ฑ์žฅ์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ์ด๋ก ์ด๋‹ค. ๋ฆฌ๋ฒ„์Šค ์™€๋ฒ„๊ทธ ํšจ๊ณผ ์ด๋ก ์—์„œ ํ•ต์‹ฌ ์—ญํ• ์„ ํ•˜๋Š” ๊ธฐ์งˆ ์„ธํฌ์ธ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ๋Š” ์ข…์–‘ ๋ฏธ์„ธ ํ™˜๊ฒฝ์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ฐ€์žฅ ์ค‘์š”ํ•œ ๊ตฌ์„ฑ ์š”์†Œ๋กœ, ์ตœ๊ทผ ์ด๊ฒƒ์ด ์—ฌ๋Ÿฌ ๊ฐœ์˜ ์•„ํ˜• (FAP, S100A4, PDGFRฮฑ, and PDGFRฮฒ) ์œผ๋กœ ๋ถ„๋ฅ˜๋˜๋ฉฐ ๊ทธ๊ฒƒ๋“ค ๊ฐ๊ฐ์€ ์„œ๋กœ ๋‹ค๋ฅธ ๊ธฐ๋Šฅ์„ฑ ํŠน์„ฑ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์กŒ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ, ์šฐ๋ฆฌ๋Š” ์œ ๋ฐฉ์•”์—์„œ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ์˜ ์•„ํ˜•์— ๋”ฐ๋ฅธ ์ข…์–‘ ์„ธํฌ์™€ ๊ธฐ์งˆ ์„ธํฌ ๊ฐ„ ๋Œ€์‚ฌ ์ƒํ˜ธ ์ž‘์šฉ์˜ ์ฐจ์ด๋ฅผ ๊ทœ๋ช…ํ•˜๊ณ , ์ข…์–‘ ๊ธฐ์งˆ ํ‘œ์  ๋ฌผ์งˆ์ด ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ์˜ ์•„ํ˜•์— ๋”ฐ๋ผ ์ข…์–‘์˜ ๋ฐœ์ƒ ๋ฐ ์„ฑ์žฅ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์กฐ์‚ฌํ•˜์—ฌ, ์ตœ์ข…์ ์œผ๋กœ๋Š” ์ข…์–‘ ๊ธฐ์งˆ ํ‘œ์  ๋ฌผ์งˆ์˜ ์œ ๋ฐฉ์•” ํ‘œ์  ์น˜๋ฃŒ์ œ๋กœ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ์กฐ์‚ฌํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•˜์˜€๋‹ค. ๊ฐ๊ฐ ์•ˆ์ •์ ์œผ๋กœ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ํ‘œ์ง€์ž (FAP, S100A4, PDGFRฮฑ, and PDGFRฮฒ) ๋ฅผ ๋ฐœํ˜„ํ•˜๋Š” ๋„ค ์ข…๋ฅ˜์˜ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•๋“ค์„ ์ œ์ž‘ํ•˜์—ฌ, ๊ฐ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•๊ณผ ๊ฐ ์œ ๋ฐฉ์•” ๋ถ„์ž ์•„ํ˜•๋ณ„ ์„ธํฌ ๊ฐ„ ๋Œ€์‚ฌ ์ƒํ˜ธ์ž‘์šฉ์˜ ์ฐจ์ด๋ฅผ ์•Œ์•„๋ณด์•˜๋‹ค. ๋˜ํ•œ ์ด๋™ ๋ถ„์„๊ณผ ์นจ์œค ๋ถ„์„์„ ํ†ตํ•ด ๊ฐ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•์ด ์•”์„ธํฌ์˜ ์ „์ด ๋ฐ ์นจ์œค ๋Šฅ๋ ฅ์— ๋ผ์น˜๋Š” ์˜ํ–ฅ์„ ์•Œ์•„๋ณด์•˜๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋‚˜์„œ๋Š” BALB/C ๋ˆ„๋“œ ๋งˆ์šฐ์Šค๋ฅผ ์ด์šฉํ•˜์—ฌ ์ข…์–‘ ์ด์ข… ์ด์‹ ๋ชจ๋ธ์„ ์ œ์ž‘ํ•˜์—ฌ ์„ธํฌ์ฃผ ์‹คํ—˜๋“ค์„ ํ™•์ธํ•ด ๋ณด์•˜๋‹ค. ์ œ์ž‘ํ•œ ๋„ค ๊ฐ€์ง€ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ  ์•„์„ธํฌ ์•„ํ˜• ์ค‘์—์„œ, FB-PDGFRฮฒ๊ฐ€ MDA-MB-231์„ธํฌ์˜ ํ•ด๋‹น์ž‘์šฉ, ๋ฏธํ† ํŒŒ์ง€, ์ž๊ฐ€ํฌ์‹ ํ™œ์„ฑ์„ ์ฆ๊ฐ€์‹œํ‚ค๊ณ  FB-FAP๋Š” ์‚ผ์ค‘ ์Œ์„ฑ ์œ ๋ฐฉ์•” ์„ธํฌ์ฃผ์˜ ํ•ด๋‹น์ž‘์šฉ๊ณผ ์ž๊ฐ€ํฌ์‹ ํ™œ์„ฑ์„ ์ฆ๊ฐ€์‹œํ‚ด์„ ํ™•์ธํ•˜์˜€๋‹ค. FB-FAP๋Š” ํŠนํžˆ ์‚ผ์ค‘ ์Œ์„ฑ ์œ ๋ฐฉ์•” ์„ธํฌ์ธ MDA-MB-231๊ณผ MDA-MB-468์˜ ์ข…์–‘ ์„ธํฌ ํŠน์„ฑ์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋งˆ์šฐ์Šค ์ด์ข… ์ด์‹ ๋ชจ๋ธ์—์„œ๋„ FB-FAP๊ฐ€ MDA-MB-231๊ณผ MDA-MB-468 ์„ธํฌ์˜ ํ•ด๋‹น์ž‘์šฉ๊ณผ ์ž๊ฐ€ํฌ์‹ ๋Œ€์‚ฌ ๊ธฐ์ „์„ ํ™œ์„ฑํ™” ์‹œํ‚ด์„ ํ™•์ธํ•˜์˜€๋‹ค. Knocked down ์„ฌ์œ ์•„์„ธํฌ์ธ FB-siPDGFRฮฒ์™€ FB-siFAP ์„ธํฌ๋ฅผ ์ด์šฉํ•œ ์–ต์ œ ์‹คํ—˜์—์„œ, MDA-MB-231, MDA-MB-468 ๋ฐ ๋งˆ์šฐ์Šค ์ด์ข… ์ด์‹ ๋ชจ๋ธ์˜ ์ข…์–‘ ๋Œ€์‚ฌ ๋ฐ ์ข…์–‘ ์„ธํฌ ํŠน์„ฑ์€ FB-PDGFRฮฒ ์™€ FB-FAP๋ฅผ ํ•จ๊ป˜ ๋ฐฐ์–‘ํ•œ ์‚ผ์ค‘ ์Œ์„ฑ ์œ ๋ฐฉ์•” ์„ธํฌ์ฃผ ๋ฐ ๋งˆ์šฐ์Šค ์ด์ข… ์ด์‹ ๋ชจ๋ธ ์—ฐ๊ตฌ์—์„œ ๋ณด์—ฌ์ค€ ๊ฒฐ๊ณผ์™€ ์ผ๊ด€๋˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ข…ํ•ฉํ•˜๋ฉด, ๊ฐ ์œ ๋ฐฉ์•” ๋ถ„์ž ์•„ํ˜•์ด ํ•จ๊ป˜ ๋ฐฐ์–‘ํ•œ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•์— ๋”ฐ๋ผ ๋Œ€์‚ฌ ๊ด€๋ จ ํ‘œ์ง€์ž์˜ ๋ฐœํ˜„ ๋ฐ ์ข…์–‘ ์„ธํฌ ํŠน์„ฑ์— ์ฐจ์ด๋ฅผ ๋ณด์ธ๋‹ค๋Š” ์žˆ๋‹ค๋Š” ์ ์—์„œ ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ๋Š” ์ด์งˆ์ ์ธ ํŠน์„ฑ์„ ๊ฐ€์ง„๋‹ค. ์ข…์–‘ ์—ฐ๊ด€ ์„ฌ์œ ์•„์„ธํฌ ์•„ํ˜•๋“ค ์ค‘, FB-FAP ๋Š” ์‚ผ์ค‘ ์Œ์„ฑ ์œ ๋ฐฉ์•” ์„ธํฌ์ฃผ์—์„œ ํ•ด๋‹น์ž‘์šฉ๊ณผ ์ž๊ฐ€ํฌ์‹์„ ํ†ตํ•ด ์ข…์–‘์˜ ํ˜•์„ฑ ๋ฐ ์„ฑ์žฅ์„ ์ด‰์ง„ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•˜์˜€๊ณ , ์ด๊ฒƒ์ด ์‚ผ์ค‘ ์Œ์„ฑ ์œ ๋ฐฉ์•”์˜ ์น˜๋ฃŒ ํ‘œ์ ์œผ๋กœ์„œ ์ž ์žฌ์ ์ธ ์—ญํ• ์ด ์žˆ์Œ์„ ์ œ์•ˆํ•œ๋‹ค.open๋ฐ•

    A Study on issue management strategy in policy decision making process : focused on building policy for a radioactive waste repository

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› :ํ–‰์ •ํ•™๊ณผ(ํ–‰์ •ํ•™์ „๊ณต),2007.Maste

    ๊ฑฐ๋ฆฌํ–‰๋ ฌ์„ ์ด์šฉํ•œ ๋‹ค์ฐจ์› ์ฒ™๋„๋ฒ•๊ณผ Twitter ๋„คํŠธ์›Œํฌ ์ž๋ฃŒ์—์˜ ์‘์šฉ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ†ต๊ณ„ํ•™๊ณผ, 2013. 2. ์ž„์š”ํ•œ.Multidimensional scaling is applied in varied fields such as marketing, genetics, ecology, molecular biology, psychology and social networks. In majority, multidimensional scaling has its main purpose to verify the relationship between individuals by embedding high-dimensional observations on a sphere to points on a lower-dimensional sphere. Simply put, multidimensional scaling makes it possible to look through the large data by illustrating them with a simple plot. In the process of applying multidimensional scaling to the data, we need to define a dissimilarity matrix, which reflects the distance between the each pair of the entities. Under the certain restrictions, there can be a variety of distance measures to construct the dissimilarity matrix. In this paper, we introduce several different distance measures possibly used for multidimensional scaling and categorize those measures so that they can be used in an appropriate circumstance. An application to the actual data has been done with the network data from Twitter. By implementing different types of measures to the specific data, we would like to show the importance of selecting an appropriate distance measure for the data.1. Introduction 2. Review of Literature 3. Multidimensional Scaling 4. Application to Twitter Network Data 5. ConclusionMaste
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