[go: up one dir, main page]

HRP20201424T1 - Sredstva i postupci za predviđanje odgovora na liječenje pacijenta oboljelog od raka - Google Patents

Sredstva i postupci za predviđanje odgovora na liječenje pacijenta oboljelog od raka Download PDF

Info

Publication number
HRP20201424T1
HRP20201424T1 HRP20201424TT HRP20201424T HRP20201424T1 HR P20201424 T1 HRP20201424 T1 HR P20201424T1 HR P20201424T T HRP20201424T T HR P20201424TT HR P20201424 T HRP20201424 T HR P20201424T HR P20201424 T1 HRP20201424 T1 HR P20201424T1
Authority
HR
Croatia
Prior art keywords
patient
tumor
cells
cancer
sample
Prior art date
Application number
HRP20201424TT
Other languages
English (en)
Inventor
Niels Grabe
Niels Halama
Dirk JÄGER
Inka ZÖRNIG
Original Assignee
Niels Grabe
Niels Halama
Dirk JÄGER
Inka ZÖRNIG
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
Family has litigation
First worldwide family litigation filed litigation Critical https://patents.darts-ip.com/?family=44862915&utm_source=google_patent&utm_medium=platform_link&utm_campaign=public_patent_search&patent=HRP20201424(T1) "Global patent litigation dataset” by Darts-ip is licensed under a Creative Commons Attribution 4.0 International License.
Application filed by Niels Grabe, Niels Halama, Dirk JÄGER, Inka ZÖRNIG filed Critical Niels Grabe
Publication of HRP20201424T1 publication Critical patent/HRP20201424T1/hr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5011—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing antineoplastic activity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5091—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing the pathological state of an organism
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
    • G01N2333/7051—T-cell receptor (TcR)-CD3 complex
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
    • G01N2333/70517—CD8
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/914—Hydrolases (3)
    • G01N2333/948—Hydrolases (3) acting on peptide bonds (3.4)
    • G01N2333/95—Proteinases, i.e. endopeptidases (3.4.21-3.4.99)
    • G01N2333/964—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue
    • G01N2333/96425—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals
    • G01N2333/96427—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general
    • G01N2333/9643—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general with EC number
    • G01N2333/96433—Serine endopeptidases (3.4.21)
    • G01N2333/96436—Granzymes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Immunology (AREA)
  • Biomedical Technology (AREA)
  • Chemical & Material Sciences (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Molecular Biology (AREA)
  • Analytical Chemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Microbiology (AREA)
  • Biotechnology (AREA)
  • Pathology (AREA)
  • General Physics & Mathematics (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Cell Biology (AREA)
  • Biochemistry (AREA)
  • Tropical Medicine & Parasitology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Toxicology (AREA)
  • Hospice & Palliative Care (AREA)
  • Oncology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Physiology (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Compression Of Band Width Or Redundancy In Fax (AREA)

Claims (11)

1. Postupak za predviđanje reagira li pacijent obolio od raka sa solidnim tumorom na liječenje kemoterapijom koji sadrži korake: • pružanje uzorka tumora koji je prethodno uzet od navedenog pacijenta, pri čemu je uzorak tumora odjeljak tumora i sadrži invazivnu marginu; i • određivanje u odjeljku tumora broja CD3 pozitivnih stanica po kvadratnom milimetru i broja CD8 pozitivnih stanica po kvadratnom milimetru ili broja Granzim B-pozitivnog ili oboje, pri čemu se broj stanica određuje imunohistokemijom i / ili imunofluorescencijom uporabom tehnologije slajdova na cijelom presjeku tkiva; pri čemu mikroskopski digitalizirani dijapozitivi koji nastaju slikanjem cijelih dijapozitiva podliježu automatskoj obradi slike; pri čemu se biološki markeri procjenjuju automatski i; pri čemu se uzorak pacijenta klasificira algoritmima prema njihovom odgovoru na liječenje kemoterapijom pri čemu je broj CD3 pozitivnih stanica po mm2 i CD8- pozitivnih stanica / mm2 i / ili Granzim B- pozitivnih stanica / mm2 iznad praga unaprijed definiranog za svaki od CD3, CD8 i Granzim B koji ukazuje da navedeni pacijent reagira na spomenutu kemoterapiju.
2. Postupak u skladu sa zahtjevom 1, naznačen time što navedeni rak je metastazirajući rak.
3. Postupak u skladu sa zahtjevom 1 ili 2, naznačen time što navedeni rak je rak debelog crijeva.
4. Postupak u skladu s bilo kojim od zahtjeva 1 do 3, naznačen time što je navedeni uzorak tumora uzorak primarnog tumora ili metastaze.
5. Postupak u skladu sa zahtjevom 4, naznačen time što uzorak tumora je uzorak metastaze u jetri.
6. Postupak u skladu sa zahtjevom 5, naznačen time što navedeni uzorak tumora sadrži (i) limfoidne otočiće u blizini tumora; (ii) limfni čvorovi smješteni u blizini tumora; i / ili (iii) susjedno normalno tkivo ili krv s periferije.
7. Postupak u skladu s patentnim zahtjevom 6, naznačen time što unaprijed definirani pragovi su 600 stanica / mm2 za CD3, 200 stanica / mm2 za CD8 i 30 stanica / mm2 za Granzim B.
8. Postupak u skladu s bilo kojim od zahtjeva 1 do 7, koji nadalje sadrži određivanje razine najmanje još jednog biološkog markera koji ukazuje na imunološki odgovor pacijenta na rak, pri čemu razina koja je iznad unaprijed određene razine ukazuje da taj pacijent reagira na kemoterapiju; pri čemu je daljnji biološki marker razina interferonske game i razina interferonske game iznad 1000 ng / ml ukazuje je indikativna za odgovor na kemoterapiju; pri čemu daljnji biološki marker je omjer interferonske game i RANTES, i pri čemu omjer interferonske gama prema RANTES veći od 1 je indikativan za odgovor na kemoterapiju; pri čemu je daljnji biološki marker VEGF i / ili IL-8 i pri čemu je koncentracija VEGF i / ili IL-8 u uzorku pacijenta koja je veća u odnosu na pacijenta koji ne boluje od raka indikativna za odgovor na kemoterapiju ; i / ili pri čemu daljnji biološki marker interferonske game, MIG, IP-10 i / ili fraktalkin i pri čemu je koncentracija interferonske game, MIG, IP-10 i / ili fraktalkina u uzorku pacijenta niža u odnosu na pacijenta koji ne boluje od raka, ukazuje da je navedeni pacijent indikativan za odgovor na kemoterapiju.
9. Kemoterapijsko sredstvo odabrano od karboplatina, paklitaksela, soferaniba ili 5-FU za uporabu u liječenju pacijenta oboljelog od raka s solidnim tumorom, pri čemu uporaba sadrži (a) pružanje uzorka tumora koji je prethodno uzet od navedenog pacijenta, pri čemu je uzorak tumora odjeljak tumora i sadrži invazivnu marginu; (b) određivanje broja CD3-pozitivnih stanica po kvadratnom milimetru u odjeljku tumora i broja CD8-pozitivnih stanica po kvadratnom milimetru ili broja Granzim B-pozitivnih stanica po kvadratnom milimetru ili oboje, pri čemu se broj stanica određuje imunohistokemijom i / ili imunofluorescencija uporabom tehnologije snimanja cijelih dijapozitiva; pri čemu su mikroskopski digitalizirani dijapozitivi koji nastaju slikanjem cijelih dijapozitiva podložni automatskoj obradi slike; pri čemu se biološki markeri procjenjuju automatski i; pri čemu se uzorak pacijenta klasificira algoritmima prema njihovom odgovoru na liječenje kemoterapijom; (c) odabir navedenog pacijenta oboljelog od raka ako je broj CD3 pozitivnih stanica / mm2 i broj CD8 pozitivnih stanica / mm2 ili broj Granzim B-pozitivnih stanica / mm2 je iznad praga unaprijed definiranog za svaki od CD3, CD8 i Granzima B; i (d) davanje navedenom pacijentu terapeutski učinkovite količine kemoterapeutskog sredstva.
10. Kemoterapeutsko sredstvo za uporabu u liječenju iz zahtjeva 9, naznačeno time što navedeni rak je rak debelog crijeva i što uzorci tumora unaprijed definiranih pragova su 600 stanica / mm2 za CD3, 200 stanica / mm2 za CD8 i 30 stanica / mm2 za Granzim B.
11. Postupak probira terapeutski učinkovitog kemoterapijskog sredstva za pacijenta oboljelog od raka koji sadrži slijedeće korake: (a) pružanje tumorskih stanica iz uzorka tumora koji je prethodno uzet od navedenog pacijenta, pri čemu je navedeni uzorak tumora naznačen infiltracijom određenog broja stanica po kvadratnom milimetru pozitivno za CD3 i CD8 ili kod Granzima B iznad pragova unaprijed definiranih za svaki površinski marker stanice kako je određeno imunohistokemijom i / ili imunofluorescencijom uporabom tehnologije snimanja cijelih dijapozitiva u dijelu uzorka tumora koji sadrži invazivnu marginu; pri čemu su mikroskopski digitalizirani dijapozitivi koji nastaju slikanjem cijelih dijapozitiva podložni automatskoj obradi slike; pri čemu se biološki markeri procjenjuju automatski i; pri čemu se uzorak pacijenta klasificira algoritmima prema njihovom odgovoru na liječenje kemoterapijom; (b) kontaktiranje tumorskih stanica s jednim ili više kemoterapeutskih sredstava; i (c) procjena da li navedeno jedno ili više kemoterapeutskih sredstava utječu na stanice tumora, pri čemu navedeni rak je rak debelog crijeva, unaprijed definirani pragovi su 600 stanica / mm2 za CD3, 200 stanica / mm2 za CD8 i 30 stanica / mm2 za Granzim B.
HRP20201424TT 2010-09-24 2011-09-20 Sredstva i postupci za predviđanje odgovora na liječenje pacijenta oboljelog od raka HRP20201424T1 (hr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP10010537 2010-09-24
EP11773381.6A EP2619576B1 (en) 2010-09-24 2011-09-20 Means and methods for the prediction of treatment response of a cancer patient
PCT/EP2011/004710 WO2012038068A2 (en) 2010-09-24 2011-09-20 Means and methods for the prediction of treatment response of a cancer patient

Publications (1)

Publication Number Publication Date
HRP20201424T1 true HRP20201424T1 (hr) 2021-02-19

Family

ID=44862915

Family Applications (1)

Application Number Title Priority Date Filing Date
HRP20201424TT HRP20201424T1 (hr) 2010-09-24 2011-09-20 Sredstva i postupci za predviđanje odgovora na liječenje pacijenta oboljelog od raka

Country Status (10)

Country Link
US (1) US9726676B2 (hr)
EP (1) EP2619576B1 (hr)
DK (1) DK2619576T3 (hr)
ES (1) ES2816625T3 (hr)
HR (1) HRP20201424T1 (hr)
HU (1) HUE051674T2 (hr)
PL (1) PL2619576T3 (hr)
PT (1) PT2619576T (hr)
SI (1) SI2619576T1 (hr)
WO (1) WO2012038068A2 (hr)

Families Citing this family (56)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
PT4209510T (pt) 2008-12-09 2024-04-02 Hoffmann La Roche Anticorpos anti-pm-l1 e a sua utilização para a melhoria do funcionamento das células t
US20120171694A1 (en) * 2010-07-30 2012-07-05 Vermillion, Inc. Predictive markers and biomarker panels for ovarian cancer
CN105861712B (zh) 2011-04-18 2021-05-14 迪阿米尔有限责任公司 使用来自体液的miRNA来早期检测和监控轻度认知障碍(MCI)和阿尔茨海默病(AD)的方法
US9760760B2 (en) 2012-01-19 2017-09-12 H. Lee Moffitt Cancer Center And Research Institute, Inc. Histology recognition to automatically score and quantify cancer grades and individual user digital whole histological imaging device
US20130203614A1 (en) 2012-02-08 2013-08-08 Jerome Galon Methods for predicting the survival time of a patient suffering from a solid cancer
CA2868159A1 (en) * 2012-03-30 2013-10-03 Sloan-Kettering Institute For Cancer Research S100a8/a9 as a diagnostic marker and a therapeutic target
US20150218650A1 (en) * 2012-08-06 2015-08-06 Inserm (Institut National De La Sante Et De La Recherche Medicale) Methods and kits for screening patients with a cancer
DK2888591T3 (da) * 2012-08-21 2019-01-02 Medetect Ab Fremgangsmåde til forbedret celleidentifikation
WO2014039654A1 (en) * 2012-09-06 2014-03-13 Joslin Diabetes Center, Inc. Isolation and characterization of muscle regenerating cells
WO2014114595A1 (en) 2013-01-23 2014-07-31 Roche Glycart Ag Predictive biomarker for cancer treatment with adcc-enhanced antibodies
WO2014173860A1 (en) * 2013-04-23 2014-10-30 INSERM (Institut National de la Santé et de la Recherche Médicale) Methods for predicting the responsiveness of a patient affected with a tumor to a treatment with a combination of iron uptake inhibitor and vitamin d receptor agonist
CA2931082C (en) 2013-11-18 2024-01-23 Diamir, Llc Methods of using mirnas from bodily fluids for detection and monitoring of parkinson's disease (pd)
WO2015117164A1 (en) * 2014-02-03 2015-08-06 Memorial Sloan-Kettering Cancer Center Tumor-associated macrophages and methods and compositions for targeting cancer therapy and identifying potential responders
EP3111221B2 (en) 2014-02-24 2022-01-19 Ventana Medical Systems, Inc. Methods, kits, and systems for scoring the immune response to cancer by simultaneous detection of cd3, cd8, cd20 and foxp3.
US11275080B2 (en) 2014-11-05 2022-03-15 The Regents Of The University Of California Methods for stratifying non-responders to therapies that block PD1/PDL1 axis
KR101751929B1 (ko) * 2015-01-05 2017-06-28 서울대학교 산학협력단 신규 간암 환자의 소라페닙 저항성 예측 마커
US20160258848A1 (en) * 2015-03-04 2016-09-08 Agilent Technologies, Inc. Methods and compositions for multiplex tissue section analyses using visible and non-visible labels
WO2016168133A1 (en) * 2015-04-17 2016-10-20 Merck Sharp & Dohme Corp. Blood-based biomarkers of tumor sensitivity to pd-1 antagonists
KR20170007181A (ko) 2015-07-10 2017-01-18 3스캔 인크. 조직학적 염색제의 공간 다중화
US11385231B2 (en) 2015-08-27 2022-07-12 Inserm (Institut National De La Sante Et De La Recherche Scientifique) Methods for predicting the survival time of patients suffering from a lung cancer
WO2017070584A1 (en) 2015-10-23 2017-04-27 Novartis Ag Computer processes behind an enhanced version of aqua
US10975436B2 (en) 2016-01-05 2021-04-13 Diamir, Llc Methods of using miRNA from bodily fluids for diagnosis and monitoring of neurodevelopmental disorders
ES2993025T3 (en) 2016-03-21 2024-12-20 Diamir Llc Methods of using mirnas from bodily fluids for detection and differentiation of neurodegenerative diseases
US11963980B2 (en) 2016-04-25 2024-04-23 Musc Foundation For Research Development Activated CD26-high immune cells and CD26-negative immune cells and uses thereof
EP3455631B1 (en) * 2016-05-09 2020-06-24 INSERM (Institut National de la Santé et de la Recherche Médicale) Methods for classifying patients with a solid cancer
CN106084114B (zh) * 2016-06-08 2017-11-10 渤海大学 一种恩诺沙星适配体/分子印迹杂化型上转换荧光探针的制备方法
US9990713B2 (en) * 2016-06-09 2018-06-05 Definiens Ag Detecting and visualizing correlations between measured correlation values and correlation reference values of a pathway
EA201990530A1 (ru) * 2016-08-19 2019-07-31 БРУКЛИН ИММУНОТЕРАПЬЮТИКС ЭлЭлСи Пути применения ингибиторов pd-1/pd-l1 и/или ингибиторов ctla-4 с биологическим средством, содержащим несколько цитокиновых компонентов, для лечения рака
WO2018058125A1 (en) * 2016-09-26 2018-03-29 Ensemble Group Holdings Methods of assessing and treating cancer in subjects having dysregulated lymphatic systems
US11644467B2 (en) * 2016-12-01 2023-05-09 Yale University Prediction of response to immune-modulatory therapies
US12226479B2 (en) 2017-05-11 2025-02-18 The General Hospital Corporation Methods and compositions of use of CD8+ tumor infiltrating lymphocyte subtypes and gene signatures thereof
WO2018231772A1 (en) * 2017-06-13 2018-12-20 Bostongene Corporation Systems and methods for identifying responders and non-responders to immune checkpoint blockade therapy
US10704093B2 (en) * 2017-07-05 2020-07-07 The Regents Of The Universtiy Of California Assay for pre-operative prediction of organ function recovery
US10781487B2 (en) 2017-07-24 2020-09-22 Diamir, Llc miRNA-based methods for detecting and monitoring aging
US10950424B2 (en) * 2017-09-25 2021-03-16 Bruker Daltonik, Gmbh Method for monitoring the quality of mass spectrometric imaging preparation workflows
US12276664B2 (en) 2017-11-30 2025-04-15 Singapore Health Services Pte. Ltd. Method for classifying cancer patients into appropriate hepatocellular carcinoma treatment groups and compounds for treating the patient
US12331320B2 (en) 2018-10-10 2025-06-17 The Research Foundation For The State University Of New York Genome edited cancer cell vaccines
EP3887548A1 (en) * 2018-11-30 2021-10-06 GBG Forschungs GmbH Method for predicting the response to cancer immunotherapy in cancer patients
CN109655624A (zh) * 2019-02-11 2019-04-19 臻和（北京）科技有限公司 一种用于预测癌症免疫治疗效果的标志物及其应用、试剂盒和试剂盒的制备方法
SG11202112712RA (en) * 2019-06-03 2021-12-30 Inst Nat Sante Rech Med Methods for modulating a treatment regimen
WO2021003246A1 (en) * 2019-07-01 2021-01-07 Accure Health Inc. Predictive liquid markers for cancer immunotherapy
KR20210068304A (ko) * 2019-11-29 2021-06-09 의료법인 성광의료재단 면역 세포 치료제에 대한 치료 반응성 예측용 바이오마커
CN110895280B (zh) * 2019-12-03 2022-11-18 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） 用于预测鼻咽癌转移的免疫评分及其应用
WO2021156360A1 (en) * 2020-02-05 2021-08-12 INSERM (Institut National de la Santé et de la Recherche Médicale) Methods for discontinuing a treatment with a tyrosine kinase inhibitor (tki)
EP4100962A1 (en) 2020-02-07 2022-12-14 Sanofi Systems and methods for predicting patient responses
US20210277345A1 (en) * 2020-03-06 2021-09-09 Tomoyuki Aratani Cell-containing container, method for evaluating test substance, and method for manufacturing cell-containing container
US12270048B2 (en) 2020-03-23 2025-04-08 Ricoh Company, Ltd. Manufacturing method for substrate on which nerve cells are arranged
US20250271430A1 (en) * 2021-04-06 2025-08-28 Industry Foundation Of Chonnam National University Method for predicting prognosis and responsiveness to anticancer therapy of cancer patients
KR102865613B1 (ko) 2021-04-06 2025-09-30 전남대학교산학협력단 암환자의 예후 및 항암 치료에 대한 반응성 예측 방법
CN113358872B (zh) * 2021-06-03 2022-10-21 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） 用于评估肿瘤免疫治疗疗效的标志物组及系统
CN114622023A (zh) * 2021-09-09 2022-06-14 四川省肿瘤医院 一种预测肿瘤化疗联合免疫治疗疗效的标志物及其应用
CN114019163B (zh) * 2021-11-02 2024-07-23 复旦大学附属中山医院 基于活化b细胞表达的结肠癌预后诊断用标记物及其用途
AU2024239150A1 (en) 2023-03-21 2025-10-02 Biograph 55, Inc. Cd19/cd38 multispecific antibodies
WO2024215562A1 (en) * 2023-04-13 2024-10-17 Board Of Regents, The University Of Texas System Pre-treatment prediction of the response of cancer to neoadjuvant therapy
WO2025034967A1 (en) * 2023-08-10 2025-02-13 Scipher Medicine Corporation A network-based framework to discover treatment-response-predicting biomarkers for complex diseases
WO2025038289A1 (en) * 2023-08-17 2025-02-20 H. Lee Moffitt Cancer Center And Research Institute Inc. Using 12 chemokine signature to select sting agonist and til treatments for solid tumors

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6711283B1 (en) * 2000-05-03 2004-03-23 Aperio Technologies, Inc. Fully automatic rapid microscope slide scanner
US7596249B2 (en) * 2002-02-22 2009-09-29 Olympus America Inc. Focusable virtual microscopy apparatus and method
EP2947160B1 (en) 2004-04-09 2017-07-12 Genomic Health, Inc. Gene expression markers for predicting response to chemotherapy
EP1777523A1 (en) * 2005-10-19 2007-04-25 INSERM (Institut National de la Santé et de la Recherche Médicale) An in vitro method for the prognosis of progression of a cancer and of the outcome in a patient and means for performing said method
GB0601509D0 (en) * 2006-01-26 2006-03-08 Maddison John Method And Apparatus For Aligning Microscope Images

Also Published As

Publication number Publication date
SI2619576T1 (sl) 2021-03-31
EP2619576A2 (en) 2013-07-31
ES2816625T3 (es) 2021-04-05
WO2012038068A2 (en) 2012-03-29
HUE051674T2 (hu) 2021-03-29
WO2012038068A3 (en) 2012-05-31
DK2619576T3 (da) 2020-09-07
US20130330325A1 (en) 2013-12-12
PL2619576T3 (pl) 2021-07-05
WO2012038068A8 (en) 2013-11-28
PT2619576T (pt) 2020-09-14
US9726676B2 (en) 2017-08-08
EP2619576B1 (en) 2020-06-10

Similar Documents

Publication Publication Date Title
HRP20201424T1 (hr) Sredstva i postupci za predviđanje odgovora na liječenje pacijenta oboljelog od raka
Fisher et al. Cancer heterogeneity: implications for targeted therapeutics
Klintrup et al. Inflammation and prognosis in colorectal cancer
Jamal-Hanjani et al. Tracking genomic cancer evolution for precision medicine: the lung TRACERx study
Stintzing et al. Prognostic value of cetuximab‐related skin toxicity in metastatic colorectal cancer patients and its correlation with parameters of the epidermal growth factor receptor signal transduction pathway: Results from a randomized trial of the GERMAN AIO CRC Study Group
Field et al. Recent developments in prognostic and predictive testing in uveal melanoma
Brustugun et al. BRAF-mutations in non-small cell lung cancer
Kilday et al. Copy number gain of 1q25 predicts poor progression-free survival for pediatric intracranial ependymomas and enables patient risk stratification: a prospective European clinical trial cohort analysis on behalf of the Children's Cancer Leukaemia Group (CCLG), Societe Francaise d'Oncologie Pediatrique (SFOP), and International Society for Pediatric Oncology (SIOP)
Fotheringham et al. Challenges and solutions in patient treatment strategies for stage II colon cancer
Xia et al. Prognostic value, clinicopathologic features and diagnostic accuracy of interleukin-8 in colorectal cancer: a meta-analysis
Yu et al. Pharmacogenomic modeling of circulating tumor and invasive cells for prediction of chemotherapy response and resistance in pancreatic cancer
Wu et al. Histologic features and genomic alterations of primary colorectal adenocarcinoma predict growth patterns of liver metastasis
Kulasinghe et al. Impact of label-free technologies in head and neck cancer circulating tumour cells
Kuboki et al. Circulating tumor cell (CTC) count and epithelial growth factor receptor expression on CTCs as biomarkers for cetuximab efficacy in advanced colorectal cancer
Li et al. Aneuploidy of chromosome 8 in circulating tumor cells correlates with prognosis in patients with advanced gastric cancer
Sakabe et al. Expression of cancer stem cell-associated DKK1 mRNA serves as prognostic marker for hepatocellular carcinoma
Guan et al. 18F-FDG uptake for prediction EGFR mutation status in non-small cell lung cancer
Kim et al. Prediction models of hepatocellular carcinoma recurrence after liver transplantation: a comprehensive review
Thomas et al. The canary in the coal mine: the growth of patient-derived tumorgrafts in mice predicts clinical recurrence after surgical resection of pancreatic ductal adenocarcinoma
Fumagalli et al. The long tail of molecular alterations in non-small cell lung cancer: a single-institution experience of next-generation sequencing in clinical molecular diagnostics
Nel et al. Role of circulating tumor cells and cancer stem cells in hepatocellular carcinoma
Naso et al. Tumor infiltrating neutrophils and gland formation predict overall survival and molecular subgroups in pancreatic ductal adenocarcinoma
Hashimoto et al. Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay
Chu et al. Clinicopathological significance and predictive value of high intratumoral tumor budding in patients with breast carcinoma treated with neoadjuvant chemotherapy
Jin et al. Combinatory statuses of tumor stromal percentage and tumor infiltrating lymphocytes as prognostic factors in stage III colorectal cancers