Introduction: The accumulation of a multitude of subtle molecular aberrations during tumor progression limit the efficacy of anti-cancer drugs. A vast array of these variations can be assessed with Poly-Ligand Profiling (PLP), which is utilizing libraries of trillion unique ssDNA with aptamer binding properties. The aims of this study were to develop a PLP library that differentiate pancreatic cancer patients who can benefit from gemcitabine+evofosfamide (GE) or gemcitabine+placebo (G) and identify its molecular targets. Methods: Patients: locally advanced or metastatic pancreatic cancer patients randomized to G vs GE in the unsuccessful phase III MAESTRO trial (Threshold Pharmaceuticals, Merck KgaA). FFPE tissues of patients with good (OS > 13 mos) or poor (OS < 7 mos) outcome from GE were used for PLP library development. Affinity maturation and testing of library for binding FFPE tissue is done with IHC-like protocol. Assay conditions and algorithm were locked based on the training set (n = 12) and used for testing assay performance in the blinded set (n = 172, primary and metastatic sites). PLP-assay performance metrics from blinded test set served to estimate the impact on the MAESTRO study (n = 693) by performing 1000 simulations. For target ID, FFPE tissue of patients with poor outcome, stained with enriched library, was recovered, lysed, underwent affinity-based pull-downs, purified with PAGE gel and subjected to high resolution mass-spectrometry (MS). Results: 1,000 simulations of projected PLP-positive patients from MAESTRO study revealed a median OS increase of 37.6% (mean) in G+E cohort, compared to G (17.4% OS increase in MAESTRO) with mean Hazard Ratio (HR) 0.72 (0.84 in MAESTRO). 96.9% of simulated trials achieved statistical significance. For primary tumor samples the median OS increase for G+E patients was 53.4% with mean HRs of 0.64 with 100% of trials exhibiting log-rank p < 0.05. MS reliably detected 20 proteins, 11 of which have reported associations with pancreatic cancer and 6 have been associated with resistance to gemcitabine: vimentin (VIM), pyruvate kinase (PKM), endoplasmic reticulum chaperone BiP (HSPA5), heat shock protein HSP 90-alpha (HSP90AA1), Histone H3-1 (HIST1H3A), heat shock protein beta-1 (HSPB1). Vimentin is a mesenchymal marker whose expression increases during epithelial–to-mesenchymal transition (EMT) and tumor progression. EMT results in the suppression of human equilibrative/concentrative nucleoside transporter and protects tumor cells from gemcitabine. GRP78 overexpression confers resistance to gemcitabine and its knockdown sensitizes tumor cells to drug treatment. Alternative splicing of PKM promotes gemcitabine resistance in pancreatic cancer cells most likely by boosting glycolysis-fueled proliferation. Heat shock proteins regulate multiple tumor survival and progression pathways and their inhibition attenuates resistance of cancer cells to gemcitabine. Pancreatic tumors demonstrate increased histones acetylation, which was correlating with increased protection against gemcitabine. Further characterization of these candidate targets is ongoing. Conclusion: PLP is a novel platform for classifying pancreatic cancer patients according to their benefiting from GE treatment. MS of the PLP library pull-downs reveals targets associated with gemcitabine resistance. In principle, the novel PLP platform could be applied to different therapeutic regimen for the development of urgently needed companion diagnostic tests in cancer and other diseases.

An ever-expanding understanding of the molecular basis of the more than 200 unique diseases collectively called cancer, combined with efforts to apply these insights to clinical care, is forming the foundation of an era of personalized medicine that promises to improve cancer treatment. At the same time, these extraordinary opportunities are occurring in an environment of intense pressure to contain rising healthcare costs. This environment presents a challenge to oncology research and clinical care, because both are becoming progressively more complex and expensive, and because the current tools to measure the cost and value of advances in care (e.g., comparative effectiveness research, cost-effectiveness analysis, and health technology assessments) are not optimized for an ecosystem moving toward personalized, patient-centered care. Reconciling this tension will be essential to maintaining progress in a cost-constrained environment, especially because emerging innovations in science (e.g., increasing identification of molecular biomarkers) and in clinical process (implementation of a learning healthcare system) hold potential to dramatically improve patient care, and may ultimately help address the burden of rising costs. For example, the rapid pace of innovation taking place within oncology calls for increased capability to integrate clinical research and care to enable continuous learning, so that lessons learned from each patient treated can inform clinical decision making for the next patient. Recognizing the need to define the policies required for sustained innovation in cancer research and care in an era of cost containment, the stakeholder community must engage in an ongoing dialogue and identify areas for collaboration. This article reflects and seeks to amplify the ongoing robust discussion and diverse perspectives brought to this issue by multiple stakeholders within the cancer community, and to consider how to frame the research and regulatory policies necessary to sustain progress against cancer in an environment of constrained resources. Clin Cancer Res; 20(5); 1081–6. ©2014 AACR.

### AACR Staff ![Figure][1] On April 8, 2013, in an unprecedented effort to highlight the critical importance of biomedical research, the American Association for Cancer Research (AACR) joined with more than 200 organizations representing a broad spectrum of research interests and diseases