Purpose: Information about symptomatic toxicities of anticancer treatments is not based on direct report by patients, but rather on reports by clinicians in trials. Given the potential for under-reporting, our aim was to compare reporting by patients and physicians of six toxicities (anorexia, nausea, vomiting, constipation, diarrhea, and hair loss) within three randomized trials. Patients and Methods: In one trial, elderly patients with breast cancer received adjuvant chemotherapy; in two trials, patients with advanced non–small-cell lung cancer received first-line treatment. Toxicity was prospectively collected by investigators (graded by National Cancer Institute Common Toxicity Criteria [version 2.0] or Common Terminology Criteria for Adverse Events [version 3]). At the end of each cycle, patients completed the European Organisation for Research and Treatment of Cancer quality-of-life questionnaires, including toxicity-related symptom items. Possible answers were “not at all,” “a little,” “quite a bit,” and “very much.” Analysis was limited to the first three cycles. For each toxicity, agreement between patients and physicians and under-reporting by physicians (ie, toxicity reported by patients but not reported by physicians) were calculated. Results: Overall, 1,090 patients (2,482 cycles) were included. Agreement between patients and physicians was low for all toxicities. Toxicity rates reported by physicians were always lower than those reported by patients. For patients who reported toxicity (any severity), under-reporting by physicians ranged from 40.7% to 74.4%. Examining only patients who reported “very much” toxicity, under-reporting by physicians ranged from 13.0% to 50.0%. Conclusion: Subjective toxicities are at high risk of under-reporting by physicians, even when prospectively collected within randomized trials. This strongly supports the incorporation of patient-reported outcomes into toxicity reporting in clinical trials.

Purpose: The resistance to selective EGFR inhibitors involves the activation of alternative signaling pathways, and Akt activation and VEGF induction have been described in EGFR inhibitor–resistant tumors. Combined inhibition of EGFR and other signaling proteins has become a successful therapeutic approach, stimulating the search for further determinants of resistance as basis for novel therapeutic strategies. Experimental Design: We established human cancer cell lines with various degrees of EGFR expression and sensitivity to EGFR inhibitors and analyzed signal transducers under the control of EGFR-dependent and EGFR-independent pathways. Results: Multitargeted inhibitor vandetanib (ZD6474) inhibited the growth and the phosphorylation of Akt and its effector p70S6 kinase in both wild-type and EGFR inhibitor–resistant human colon, prostate, and breast cancer cells. We found that the resistant cell lines exhibit, as common feature, VEGFR-1/Flt-1 overexpression, increased secretion of VEGF and placental growth factor, and augmented migration capabilities and that vandetanib is able to antagonize them. Accordingly, a new kinase assay revealed that in addition to VEGF receptor (VEGFR)-2, RET, and EGFR, vandetanib efficiently inhibits also VEGFR-1. The contribution of VEGFR-1 to the resistant phenotype was further supported by the demonstration that VEGFR-1 silencing in resistant cells restored sensitivity to anti-EGFR drugs and impaired migration capabilities, whereas exogenous VEGFR-1 overexpression in wild-type cells conferred resistance to these agents. Conclusions: This study shows that VEGFR-1 contributes to anti-EGFR drug resistance in different human cancer cells. Moreover, vandetanib inhibits VEGFR-1 activation, cell proliferation, and migration, suggesting its potential utility in patients resistant to EGFR inhibitors.

The European Association for the Study of the Liver (EASL) criteria and the modified Response Evaluation Criteria in Solid Tumors (mRECIST) are currently adopted to evaluate radiological response in patients affected by HCC and treated with loco-regional procedures. Several studies explored the validity of these measurements in predicting survival but definitive data are still lacking. To conduct a systematic review of studies exploring mRECIST and EASL criteria usefulness in predictive radiological response in HCC undergoing loco-regional therapies and their validity in predicting survival. A comprehensive search of the literature was performed in electronic databases EMBASE, MEDLINE, COCHRANE LIBRARY, ASCO conferences and EASL conferences up to June 10, 2014. Our overall search strategy included terms for HCC, mRECIST, and EASL. Loco-regional procedures included transarterial embolization (TAE), transarterial chemoembolization (TACE) and cryoablation. Inter-method agreement between EASL and mRECIST was assessed using the k coefficient. For each criteria, overall survival was described in responders vs. non-responders patients, considering all target lesions response. Among 18 initially found publications, 7 reports including 1357 patients were considered eligible. All studies were published as full-text articles. Proportion of responders according to mRECIST and EASL criteria was 62.4% and 61.3%, respectively. In the pooled population, 1286 agreements were observed between the two methods (kappa statistics 0.928, 95% confidence interval 0.912–0.944). HR for overall survival (responders versus non responders) according to mRECIST and EASL was 0.39 (95% confidence interval 0.26–0.61, p<0.0001) and 0.38 (95% confidence interval 0.24–0.61, p<0.0001), respectively. In this literature-based meta-analysis, mRECIST and EASL criteria showed very good concordance in HCC patients undergoing loco-regional treatments. Objective response according to both criteria confirms a strong prognostic value in terms of overall survival. This prognostic value appears to be very similar between the two criteria.

Inhibition of a single transduction pathway is often inefficient due to activation of alternative signalling. The mammalian target of rapamycin (mTOR) is a key intracellular kinase integrating proliferation, survival and angiogenic pathways and has been implicated in the resistance to EGFR inhibitors. Thus, mTOR blockade is pursued to interfere at multiple levels with tumour growth. We used everolimus (RAD001) to inhibit mTOR, alone or in combination with anti-EGFR drugs gefitinib or cetuximab, on human cancer cell lines sensitive and resistant to EGFR inhibitors, both in vitro and in vivo. We demonstrated that everolimus is active against EGFR-resistant cancer cell lines and partially restores the ability of EGFR inhibitors to inhibit growth and survival. Everolimus reduces the expression of EGFR-related signalling effectors and VEGF production, inhibiting proliferation and capillary tube formation of endothelial cells, both alone and in combination with gefitinib. Finally, combination of everolimus and gefitinib inhibits growth of GEO and GEO-GR (gefitinib resistant) colon cancer xenografts, activation of signalling proteins and VEGF secretion. Targeting mTOR pathway with everolimus overcomes resistance to EGFR inhibitors and produces a cooperative effect with EGFR inhibitors, providing a valid therapeutic strategy to be tested in a clinical setting.

The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of “multi-omics” analysis and the use of sensors, together with the ability to acquire clinical, behavioral, and environmental information on a large scale, will allow the digitization of the state of health or disease of each person, and the creation of a global health management system capable of generating real-time knowledge and new opportunities for prevention and therapy in the individual person (high-definition medicine). Real world data-based translational applications represent a promising alternative to the traditional evidence-based medicine (EBM) approaches that are based on the use of randomized clinical trials to test the selected hypothesis. Multi-modality data integration is necessary for example in precision oncology where an Avatar interface allows several simulations in order to define the best therapeutic scheme for each cancer patient.