A tumor deconstruction platform identifies definitive end points in the evaluation of drug responses

• Published in: Oncogene 2016-02, Vol.35 (6), p.727-737
• Main Authors: Naik, R R, Singh, A K, Mali, A M, Khirade, M F, Bapat, S A
• Format: Article
• Language: English
• Subjects: 13; 13/106; 13/31; 631/67/71; Analysis; Animals; Antineoplastic Agents - isolation & purification; Antineoplastic Agents - therapeutic use; Apoptosis; Cancer therapies; Care and treatment; Cell Biology; Cell Fractionation - methods; Cell Line, Tumor; Clone Cells; Complications and side effects; Deconstruction; Drug development; Drug discovery; Drug Discovery - methods; Drug efficacy; Drug screening; Drug Screening Assays, Antitumor - methods; Endpoint Determination - methods; Female; Flow cytometry; Flow Cytometry - methods; Human Genetics; Humans; Internal Medicine; Medicine; Medicine & Public Health; Mice; Mice, Inbred NOD; Mice, SCID; Neoplasms - drug therapy; Neoplasms - pathology; Oncology; original-article; Pharmacology; R&D; Remission; Research & development; Stem cell research; Stem cells; Treatment Outcome; Tumors; Xenograft Model Antitumor Assays
• ISSN: 0950-9232; 1476-5594
• DOI: 10.1038/onc.2015.130

Tumor heterogeneity and the presence of drug-sensitive and refractory populations within the same tumor are almost never assessed in the drug discovery pipeline. Such incomplete assessment of drugs arising from spatial and temporal tumor cell heterogeneity reflects on their failure in the clinic and considerable wasted costs in the drug discovery pipeline. Here we report the derivation of a flow cytometry-based tumor deconstruction platform for resolution of at least 18 discrete tumor cell fractions. This is achieved through concurrent identification, quantification and analysis of components of cancer stem cell hierarchies, genetically instable clones and differentially cycling populations within a tumor. We also demonstrate such resolution of the tumor cytotype to be a potential value addition in drug screening through definitive cell target identification. Additionally, this real-time definition of intra-tumor heterogeneity provides a convenient, incisive and analytical tool for predicting drug efficacies through profiling perturbations within discrete tumor cell subsets in response to different drugs and candidates. Consequently, possible applications in informed therapeutic monitoring and drug repositioning in personalized cancer therapy would complement rational design of new candidates besides achieving a re-evaluation of existing drugs to derive non-obvious combinations that hold better chances of achieving remission.