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1. WO2020136133 - TUMOR CLASSIFICATION BASED ON PREDICTED TUMOR MUTATIONAL BURDEN

Publication Number WO/2020/136133
Publication Date 02.07.2020
International Application No. PCT/EP2019/086781
International Filing Date 20.12.2019
IPC
G16B 20/00 2019.1
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
20ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
CPC
G16B 20/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
20ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
G16B 40/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
40ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
20Supervised data analysis
G16B 5/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
5ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
20Probabilistic models
G16H 50/30
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
30for calculating health indices; for individual health risk assessment
Applicants
  • F. HOFFMANN-LA ROCHE AG [CH]/[CH] (AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BE, BF, BG, BH, BJ, BN, BR, BW, BY, BZ, CA, CF, CG, CH, CI, CL, CM, CN, CO, CR, CU, CY, CZ, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, FR, GA, GB, GD, GE, GH, GM, GN, GQ, GR, GT, GW, HN, HR, HU, ID, IE, IL, IN, IR, IS, IT, JO, JP, KE, KG, KH, KM, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LT, LU, LV, LY, MA, MC, MD, ME, MG, MK, ML, MN, MR, MT, MW, MX, MY, MZ, NA, NE, NG, NI, NL, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SI, SK, SL, SM, SN, ST, SV, SY, SZ, TD, TG, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, UZ, VC, VN, ZA, ZM, ZW)
  • ROCHE DIAGNOSTICS GMBH [DE]/[DE] (DE)
  • ROCHE SEQUENCING SOLUTIONS, INC. [US]/[US] (US)
Inventors
  • LAM, Hugo Y. K.
  • MOHIYUDDIN, Marghoob
  • YAO, Lijing
Agents
  • FINALE, Christian Thierry
Priority Data
62/78448623.12.2018US
62/82269022.03.2019US
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) TUMOR CLASSIFICATION BASED ON PREDICTED TUMOR MUTATIONAL BURDEN
(FR) CLASSIFICATION DE TUMEUR BASÉE SUR UNE CHARGE MUTATIONNELLE TUMORALE PRÉDITE
Abstract
(EN) The present disclosure provides systems and methods of classifying and/or identifying a cancer subtype. The present disclosure also provides methods of enhancing the prediction of a tumor mutational burden by using both synonymous and non-synonymous somatic mutations in the computation method. It is believed that by increasing the number of mutations in the computation of the tumor mutational burden, a comparatively more consistent tumor mutational burden may be derived, especially for targeted-panel sequencing. It is believed that the consistent computation of the tumor mutational burden from targeted panels allows for computationally quicker and less costly analysis of sequencing data as compared with a tumor mutational burden computed from whole exome sequencing data.
(FR) La présente invention concerne des systèmes et des procédés de classification et/ou d'identification de sous-types de cancer. La présente invention concerne également des procédés d'amélioration de la prédiction d'une charge mutationnelle tumorale en utilisant à la fois des mutations somatiques synonymes et non synonymes dans le procédé de calcul. On pense que, en augmentant le nombre de mutations dans le calcul de la charge mutationnelle tumorale, une charge mutationnelle tumorale comparativement plus cohérente peut être dérivée, en particulier pour le séquençage de panels ciblés. On pense que le calcul cohérent de la charge mutationnelle tumorale à partir de panels ciblés permet une analyse par calcul plus rapide et moins coûteuse de données de séquençage par comparaison avec une charge mutationnelle tumorale calculée à partir de données de séquençage d'exome entier.
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