Phenotype-driven precision oncology as a guide for clinical decisions one patient at a time

Autor: Patrick Tan, Giridharan Periyasamy, Matan Thangavelu Thangavelu, Judice L. Y. Koh, Hiang Khoon Tan, Shen Yon Toh, Daniel Shao-Weng Tan, Joo-Leng Low, Yan Su, Ankur Sharma, Thakshayeni Skanthakumar, Jacqueline S.G. Hwang, Alexander Lezhava, Iain Beehuat Tan, Hannes Hentze, Hui-Sun Leong, Shumei Chia, N. Gopalakrishna Iyer, Xue-Lin Kwang, Kok-Hing Lim, Xiaoqian Zhang, Ramanuj DasGupta, Siang Hui Choo, Fui-Teen Chong, Denis Bertrand
Jazyk: angličtina
Rok vydání: 2017
Předmět:
0301 basic medicine
Oncology
Cell
General Physics and Astronomy
Metastasis
Mice
Inbred NOD
Tumor Cells
Cultured
Neoplasm
Precision Medicine
lcsh:Science
Multidisciplinary
Gefitinib
Gene Expression Regulation
Neoplastic
Phenotype
Treatment Outcome
medicine.anatomical_structure
Head and Neck Neoplasms
Carcinoma
Squamous Cell
Biomarker (medicine)
Mouth Neoplasms
medicine.drug
medicine.medical_specialty
Science
Article
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
Internal medicine
Biomarkers
Tumor
medicine
Carcinoma
Animals
Humans
Adaptor Proteins
Signal Transducing
business.industry
Cancer
YAP-Signaling Proteins
General Chemistry
Phosphoproteins
medicine.disease
Xenograft Model Antitumor Assays
030104 developmental biology
Drug Resistance
Neoplasm
Quinazolines
lcsh:Q
Cisplatin
business
Ex vivo
Transcription Factors
Zdroj: Nature Communications, Vol 8, Iss 1, Pp 1-12 (2017)
Nature Communications
ISSN: 2041-1723
Popis: Genomics-driven cancer therapeutics has gained prominence in personalized cancer treatment. However, its utility in indications lacking biomarker-driven treatment strategies remains limited. Here we present a “phenotype-driven precision-oncology” approach, based on the notion that biological response to perturbations, chemical or genetic, in ex vivo patient-individualized models can serve as predictive biomarkers for therapeutic response in the clinic. We generated a library of “screenable” patient-derived primary cultures (PDCs) for head and neck squamous cell carcinomas that reproducibly predicted treatment response in matched patient-derived-xenograft models. Importantly, PDCs could guide clinical practice and predict tumour progression in two n = 1 co-clinical trials. Comprehensive “-omics” interrogation of PDCs derived from one of these models revealed YAP1 as a putative biomarker for treatment response and survival in ~24% of oral squamous cell carcinoma. We envision that scaling of the proposed PDC approach could uncover biomarkers for therapeutic stratification and guide real-time therapeutic decisions in the future.
Treatment response in patient-derived models may serve as a biomarker for response in the clinic. Here, the authors use paired patient-derived mouse xenografts and patient-derived primary culture models from head and neck squamous cell carcinomas, including metastasis, as models for high-throughput screening of anti-cancer drugs.
Databáze: OpenAIRE
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