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The development of molecular targeted drugs with radiation and chemotherapy is critically important for improving the outcomes of patients with hard-to-treat, potentially curable cancers. However, too many preclinical studies have not translated into successful radiation oncology trials. Major contributing factors to this insufficiency include poor reproducibility of preclinical data, inadequate preclinical modeling of intertumoral genomic heterogeneity that influences treatment sensitivity in the clinic, and a reliance on tumor growth delay instead of local control (TCD50) endpoints. There exists an urgent need to overcome these barriers to facilitate successful clinical translation of targeted radiosensitizers. To this end, we have used 3-dimensional (3D) cell culture assays to better model tumor behavior in vivo. Examples of successful prediction of in vivo effects with these 3D assays include radiosensitization of head and neck cancers by inhibiting epidermal growth factor receptor or focal adhesion kinase signaling, and radioresistance associated with oncogenic mutation of KRAS. To address the issue of tumor heterogeneity, we leveraged institutional resources that allow high-throughput 3D screening of radiation combinations with small-molecule inhibitors across genomically characterized cell lines from lung, head and neck, and pancreatic cancers. This high-throughput screen is expected to uncover genomic biomarkers that will inform the successful clinical translation of targeted agents from the National Cancer Institute Cancer Therapy Evaluation Program portfolio and other sources. Screening "hits" need to be subjected to refinement studies that include clonogenic assays, addition of disease-specific chemotherapeutics, target/biomarker validation, and integration of patient-derived tumor models. The chemoradiosensitizing activities of the most promising drugs should be confirmed in TCD50 assays in xenograft models with or without relevant biomarker and using cl

Aims: An Arctic Vegetation Classification (AVC) is needed to address issues related to rapid Arctic-wide changes to climate, land-use, and biodiversity. Location: The 7.1 million km2 Arctic tundra biome. Approach and conclusions: The purpose, scope and conceptual framework for an Arctic Vegetation Archive (AVA) and Classification (AVC) were developed during numerous workshops starting in 1992. The AVA and AVC are modeled after the European vegetation archive (EVA) and classification (EVC). The AVA will use Turboveg for data management. The AVC will use a Braun-Blanquet (Br.-Bl.) classification approach. There are approximately 31,000 Arctic plots that could be included in the AVA. An Alaska AVA (AVA-AK, 24 datasets, 3026 plots) is a prototype for archives in other parts of the Arctic. The plan is to eventually merge data from other regions of the Arctic into a single Turboveg v3 database. We present the pros and cons of using the Br.-Bl. classification approach compared to the EcoVeg (US) and Biogeoclimatic Ecological Classification (Canada) approaches. The main advantages are that the Br.-Bl. approach already has been widely used in all regions of the Arctic, and many described, well-accepted vegetation classes have a pan-Arctic distribution. A crosswalk comparison of Dryas octopetala communities described according to the EcoVeg and the Braun-Blanquet approaches indicates that the non-parallel hierarchies of the two approaches make crosswalks difficult above the plantcommunity level. A preliminary Arctic prodromus contains a list of typical Arctic habitat types with associated described syntaxa from Europe, Greenland, western North America, and Alaska. Numerical clustering methods are used to provide an overview of the variability of habitat types across the range of datasets and to determine their relationship to previously described Braun-Blanquet syntaxa. We emphasize the need for continued maintenance of the Pan-Arctic Species List, and additional plot data to

BACKGROUND: Duligotuzumab, a novel dual-action humanized IgG1 antibody that blocks ligand binding to epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 3 (HER3), inhibits signaling from all ligand-dependent HER dimers, and can elicit antibody-dependent cell-mediated cytotoxicity. High tumor-expression of neuregulin 1 (NRG1), a ligand to HER3, may enhance sensitivity to duligotuzumab. METHODS: This multicenter, open-label, randomized phase II study (MEHGAN) evaluated drug efficacy in patients with recurrent/metastatic (R/M) squamous cell carcinoma of the head and neck (SCCHN) progressive on/after chemotherapy and among patients with NRG1-high tumors. Patients received duligotuzumab (1100 mg IV, q2w) or cetuximab (400 mg/m2 load, 250 mg/m2 IV, q1w) until progression or intolerable toxicity. Tumor samples were assayed for biomarkers [NRG1, ERBB3, and human papillomavirus (HPV) status]. RESULTS: Patients (N = 121) were randomized (duligotuzumab:cetuximab; 59:62), median age 62 years; ECOG 0-2. Both arms (duligotuzumab vs. cetuximab, respectively) showed comparable progression-free survival [4.2 vs. 4.0 months; HR: 1.23 (90% confidence interval (CI): 0.89-1.70)], overall survival [7.2 vs. 8.7 months; HR 1.15 (90% CI: 0.81-1.63)], and objective response rate (12 vs. 14.5%), with no difference between patients with NRG1-high tumors or ERBB3-low tumors. Responses in both arms were confined to HPV-negative patients. Grade ≥3 adverse events (AEs) (duligotuzumab vs. cetuximab, respectively) included infections (22 vs. 11.5%) and GI disorders (17 vs. 7%), contributing to higher rates of serious AEs (41 vs. 29.5%). Metabolic disorders were less frequent with duligotuzumab (10 vs. 16%); any grade rash-related events were less with duligotuzumab (49 vs. 67%). CONCLUSION: While several lines of preclinical evidence had supported the premise that the blockade of HER3 in addition to that of EGFR may improve outcomes for patients with R/M SCCHN overall

Predictive biomarkers are urgently needed for individualization of radiation therapy and treatment with radiosensitizing anticancer agents. Genomic profiling of human cancers provides us with unprecedented insight into the mutational landscape of genes directly or indirectly involved in the response to radiation-induced DNA damage. However, to what extent this wealth of structural information about the cancer genome produces biomarkers of sensitivity to radiation remains to be seen. Investigators are increasingly studying the subnuclear accumulation (ie, foci) of proteins in the DNA damage response (DDR), such as gamma-H2AX, 53BP1, or RAD51, as a surrogate of treatment sensitivity. Recent findings from preclinical studies have demonstrated the predictive potential of DDR foci by correlating foci with clinically relevant end points such as tumor control probability. Therefore, preclinical investigations of DDR foci responses are increasingly moving into cells and tissues from patients, which is the major focus of this review. The advantage of using DDR foci as functional biomarkers is that they can detect alterations in DNA repair due to various mechanisms. Moreover, they provide a global measurement of DDR network function without needing to know the identities of all the components, many of which remain unknown. Foci assays are thus expected to yield functional insight that may complement or supersede genomic information, thereby giving radiation oncologists unique opportunities to individualize cancer treatments in the near future.