IT201900023946A1 - Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche - Google Patents

Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche

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Publication number
IT201900023946A1
IT201900023946A1 IT102019000023946A IT201900023946A IT201900023946A1 IT 201900023946 A1 IT201900023946 A1 IT 201900023946A1 IT 102019000023946 A IT102019000023946 A IT 102019000023946A IT 201900023946 A IT201900023946 A IT 201900023946A IT 201900023946 A1 IT201900023946 A1 IT 201900023946A1
Authority
IT
Italy
Prior art keywords
algorithms
determining
long
breast cancer
cancer patients
Prior art date
Application number
IT102019000023946A
Other languages
English (en)
Inventor
Porta Caterina Anna Maria La
Stefano Zapperi
Clos Francesc Font
Original Assignee
Complexdata S R L
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Complexdata S R L filed Critical Complexdata S R L
Priority to IT102019000023946A priority Critical patent/IT201900023946A1/it
Priority to US17/773,263 priority patent/US20230145332A1/en
Priority to EP20828554.4A priority patent/EP4073803A1/en
Priority to PCT/IB2020/061014 priority patent/WO2021140373A1/en
Publication of IT201900023946A1 publication Critical patent/IT201900023946A1/it

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Data Mining & Analysis (AREA)
  • Biomedical Technology (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Primary Health Care (AREA)
  • Pathology (AREA)
  • Epidemiology (AREA)
  • Databases & Information Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Physiology (AREA)
  • Biophysics (AREA)
  • Biotechnology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
IT102019000023946A 2019-12-13 2019-12-13 Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche IT201900023946A1 (it)

Priority Applications (4)

Application Number Priority Date Filing Date Title
IT102019000023946A IT201900023946A1 (it) 2019-12-13 2019-12-13 Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche
US17/773,263 US20230145332A1 (en) 2019-12-13 2020-11-23 Method for determining a long-term survival prognosis of breast cancer patients, based on algorithms modelling biological networks
EP20828554.4A EP4073803A1 (en) 2019-12-13 2020-11-23 Method for determining a long-term survival prognosis of breast cancer patients, based on algorithms modelling biological networks
PCT/IB2020/061014 WO2021140373A1 (en) 2019-12-13 2020-11-23 Method for determining a long-term survival prognosis of breast cancer patients, based on algorithms modelling biological networks

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IT102019000023946A IT201900023946A1 (it) 2019-12-13 2019-12-13 Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche

Publications (1)

Publication Number Publication Date
IT201900023946A1 true IT201900023946A1 (it) 2021-06-13

Family

ID=70155036

Family Applications (1)

Application Number Title Priority Date Filing Date
IT102019000023946A IT201900023946A1 (it) 2019-12-13 2019-12-13 Metodo per determinare una prognosi di sopravvivenza a lungo termine di pazienti di cancro al seno, sulla base di algoritmi che modellizzano reti biologiche

Country Status (4)

Country Link
US (1) US20230145332A1 (it)
EP (1) EP4073803A1 (it)
IT (1) IT201900023946A1 (it)
WO (1) WO2021140373A1 (it)

Citations (1)

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WO2019178217A1 (en) * 2018-03-13 2019-09-19 Baylor Research Institute Methods and compositions for treating, diagnosing, and prognosing cancer

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CA2737485A1 (en) * 2008-10-10 2010-04-15 Mount Sinai Hospital Methods for classifying samples based on network modularity
SG2014015028A (en) * 2009-03-10 2014-07-30 Agency Science Tech & Res A method for identification, prediction and prognosis of cancer aggressiveness
WO2013147330A1 (ko) * 2012-03-26 2013-10-03 연세대학교 산학협력단 국소 진행형 위암에 대한 예후 예측 시스템
AU2013353839A1 (en) * 2012-12-03 2015-06-18 Almac Diagnostics Limited Molecular diagnostic test for cancer
US10679730B2 (en) * 2013-05-28 2020-06-09 The University Of Chicago Prognostic and predictive breast cancer signature
US20150331992A1 (en) * 2014-05-15 2015-11-19 Ramot At Tel-Aviv University Ltd. Cancer prognosis and therapy based on syntheic lethality
US10876167B2 (en) * 2017-01-12 2020-12-29 The Regents Of The University Of California 12-gene prognostic signature for breast cancer survival
US12062444B2 (en) * 2017-12-12 2024-08-13 The University Of Chicago Methods and compositions related to triple-negative breast cancer
CN108424969B (zh) * 2018-06-06 2022-07-15 深圳市颐康生物科技有限公司 一种生物标志物、诊断或预估死亡风险的方法

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WO2019178217A1 (en) * 2018-03-13 2019-09-19 Baylor Research Institute Methods and compositions for treating, diagnosing, and prognosing cancer

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ALTER O.BROWN P.O.BOTSTEIN D.: "Singular value decomposition for genome-wide Expression Data processing and Modeling", PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 97, no. 18, 2000, pages 10101 - 6, XP002962133, DOI: 10.1073/pnas.97.18.10101
BERRY M.DUMAIS S.O'BRIEN G.: "Using Linear Algebra for Intelligent Information retrieval", SIAM REVIEW, vol. 37, no. 4, 1995, pages 573 - 95, XP000572488, DOI: 10.1137/1037127
BISHOPCHRISTOPHER M.: "Pattern Recognition and Machine Learning", 2006, SPRINGER-VERLAG
BRIAN D. LEHMANN ET AL: "Refinement of Triple-Negative Breast Cancer Molecular Subtypes: Implications for Neoadjuvant Chemotherapy Selection", PLOS ONE, vol. 11, no. 6, 16 June 2016 (2016-06-16), pages e0157368, XP055325113, DOI: 10.1371/journal.pone.0157368 *
EVERITT B.S.DUNN G.: "Principal components Analysis. In applied Multi-variate Data Analysis", 2013, WILEY
FONT-CLOS F.ZAPPERI S.C.A.M. GATE: "Topography of Epithelial-Mesenchymal Plasticity", PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 115, no. 23, 2018, pages 5902 - 7
H BONSANG-KITZIS ET AL: "Biological network-driven gene selection identifies a stromal immune module as a key determinant of triple-negative breast carcinoma prognosis", ONCOIMMUNOLOGY, vol. 5, no. 1, 2 January 2016 (2016-01-02), US, pages e1061176, XP055719202, ISSN: 2162-4011, DOI: 10.1080/2162402X.2015.1061176 *
LEHMANN B.D.BAUER J.A.CHEN X.SANDERS M.E.CHAKRAVARTHY A.B.SHYR Y.PIETENPOL J.A.: "Identification of Human Triple-negative Breast Cancer Subtypes and Preclinical Models for Selection of targeted therapies", THE JOURNAL OF CLINICAL INVESTIGATION, vol. 121, no. 7, 2011, pages 2750 - 67, XP002690196, DOI: 10.1172/JCI45014
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VAN'T VEER LJ, HVAN DE VIJVER MJHE YDHART AA ET AL.: "gene expression profiling predicts clinical outcome of breast cancer", NATURE, vol. 415, 2002, pages 530 - 536, XP008138701, DOI: 10.1038/415530a

Also Published As

Publication number Publication date
WO2021140373A1 (en) 2021-07-15
US20230145332A1 (en) 2023-05-11
EP4073803A1 (en) 2022-10-19

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