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

Shumei Chia, Joo-Leng Low, Xiaoqian Zhang, Xue-Lin Kwang, Fui-Teen Chong, Ankur Sharma, Denis Bertrand, Shen Yon Toh, Hui-Sun Leong, Matan T. Thangavelu, Jacqueline S. G. Hwang, Kok-Hing Lim, Thakshayeni Skanthakumar, Hiang-Khoon Tan, Yan Su, Siang Hui Choo, Hannes Hentze, Iain B. H. Tan, Alexander Lezhava, Patrick Tan, Daniel S. W. Tan, Giridharan Periyasamy, Judice L. Y. Koh, N. Gopalakrishna Iyer () and Ramanuj DasGupta ()
Additional contact information
Shumei Chia: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Joo-Leng Low: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Xiaoqian Zhang: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Xue-Lin Kwang: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Fui-Teen Chong: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Ankur Sharma: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Denis Bertrand: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Shen Yon Toh: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Hui-Sun Leong: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Matan T. Thangavelu: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Jacqueline S. G. Hwang: Singapore General Hospital
Kok-Hing Lim: Singapore General Hospital
Thakshayeni Skanthakumar: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Hiang-Khoon Tan: Singapore General Hospital
Yan Su: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Siang Hui Choo: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Hannes Hentze: Biological Resource Centre (BRC), A*STAR
Iain B. H. Tan: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Alexander Lezhava: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Patrick Tan: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Daniel S. W. Tan: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Giridharan Periyasamy: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
Judice L. Y. Koh: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology
N. Gopalakrishna Iyer: National Cancer Centre Singapore, Cancer Therapeutics Research Laboratory
Ramanuj DasGupta: Genome Institute of Singapore, A*STAR, Cancer Therapeutics & Stratified Oncology, PerkinElmer-GIS Centre for Precision Oncology

Nature Communications, 2017, vol. 8, issue 1, 1-12

Abstract: Abstract 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.

Date: 2017
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DOI: 10.1038/s41467-017-00451-5

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