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1. (WO2019066421) DNA COPY NUMBER VARIATION-BASED PREDICTION METHOD FOR KIND OF CANCER
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Pub. No.: WO/2019/066421 International Application No.: PCT/KR2018/011286
Publication Date: 04.04.2019 International Filing Date: 21.09.2018
IPC:
G16B 20/00 (2019.01) ,G16B 30/00 (2019.01) ,G16B 40/00 (2019.01)
[IPC code unknown for G16B 20][IPC code unknown for G16B 30][IPC code unknown for G16B 40]
Applicants:
이화여자대학교 산학협력단 EWHA UNIVERSITY-INDUSTRY COLLABORATION FOUNDATION [KR/KR]; 서울시 서대문구 이화여대길 52 52, Ewhayeodae-gil Seodaemun-gu Seoul 03760, KR
Inventors:
김광현 KIM, Kwang Hyun; KR
이동환 LEE, Dong Hwan; KR
Agent:
김순웅 KIM, Soon Woong; KR
Priority Data:
10-2017-012544127.09.2017KR
Title (EN) DNA COPY NUMBER VARIATION-BASED PREDICTION METHOD FOR KIND OF CANCER
(FR) PROCÉDÉ DE PRÉDICTION BASÉ SUR LA VARIATION DU NOMBRE DE COPIES D'ADN POUR UN TYPE DE CANCER
(KO) DNA 복제수 변이 기반의 암 종 예측 방법
Abstract:
(EN) The present invention relates to a DNA copy number variation-based prediction method for kinds of cancer. By taking advantage of appropriate machine learning algorithms, a DNA copy number variation-based classification model for kinds of cancer, a prediction model for kinds of cancer, and a DNA copy number variation-based prediction method for kinds of cancer using the same model according to the present invention can predict kinds of cancer and diagnose cancer in a non-invasive manner at higher sensitivity and specificity than conventional methods. Particularly, the present invention enables prediction of various kinds of cancer and diagnosis of cancer by using one prediction model and is applicable to liquid biopsy using ideal diagnostic specimens such as urine, serum, etc., and thus will find useful applications in future in diagnosing cancer and in the genomics market.
(FR) La présente invention concerne un procédé de prédiction basé sur une variation du nombre de copies d'ADN pour des types de cancer. En tirant parti d'algorithmes d'apprentissage automatique appropriés, un modèle de classification basé sur la variation du nombre de copies d'ADN pour des types de cancer, un modèle de prédiction pour des types de cancer, et un procédé de prédiction basé sur une variation du nombre de copies d'ADN pour des types de cancer à l'aide du même modèle selon la présente invention peuvent prédire des types de cancer et diagnostiquer un cancer d'une manière non invasive avec une sensibilité et une spécificité supérieures à celles des procédés classiques. En particulier, la présente invention permet de prédire divers types de cancer et de diagnostiquer un cancer à l'aide d'un modèle de prédiction et est applicable à une biopsie liquide à l'aide d'échantillons diagnostiques idéaux tels que l'urine, le sérum, etc., et trouvera ainsi des applications utiles dans le futur dans le diagnostic du cancer et le marché du génome.
(KO) 본 발명은 DNA 복제수 변이 기반의 암 종 예측 방법에 관한 것이다. 본 발명에 따른 DNA 복제수 변이 기반의 암 종 분류 모형, 암 종 예측 모형 및 이를 이용한 DNA 복제수 변이 기반의 암 종 예측 방법은 적절한 기계학습 알고리즘을 활용함으로써 통상적인 방법보다 비침습적이며 높은 민감도 및 특이도로 암 종을 예측 및 암을 진단할 수 있다. 특히, 본 발명은 하나의 예측 모형을 이용하여 다양한 암 종의 예측 및 암의 진단을 가능하게 하며, 이상적인 진단검체인 소변, 혈액 등을 이용한 액상 생검에 적용 가능하여 향후 암 진단 및 유전체 시장에서 유용하게 활용될 수 있다.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: Korean (KO)
Filing Language: Korean (KO)