Citations

The mononegaviral family Filoviridae has eight members assigned to three genera and seven species. Until now, genus and species demarcation were based on arbitrarily chosen filovirus genome sequence divergence values (≈50% for genera, ≈30% for species) and arbitrarily chosen phenotypic virus or virion characteristics. Here we report filovirus genome sequence-based taxon demarcation criteria using the publicly accessible PAirwise Sequencing Comparison (PASC) tool of the US National Center for Biotechnology Information (Bethesda, MD, USA). Comparison of all available filovirus genomes in GenBank using PASC revealed optimal genus demarcation at the 55–58% sequence diversity threshold range for genera and at the 23–36% sequence diversity threshold range for species. Because these thresholds do not change the current official filovirus classification, these values are now implemented as filovirus taxon demarcation criteria that may solely be used for filovirus classification in case additional data are absent. A near-complete, coding-complete, or complete filovirus genome sequence will now be required to allow official classification of any novel “filovirus.” Classification of filoviruses into existing taxa or determining the need for novel taxa is now straightforward and could even become automated using a presented algorithm/flowchart rooted in RefSeq (type) sequences.

Abstract As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies. Clin Cancer Res; 22(2); 284–90. ©2016 AACR.

AbstractMetastatic renal cell carcinoma (RCC) is an aggressive disease refractory to most existing therapeutic modalities. Identifying new markers for disease progression and drug targets for RCC will benefit this unmet medical need. We report a subset of clear cell and papillary cell RCC aberrantly expressing the lymphocyte activation marker CD70, a member of the tumor necrosis factor superfamily. Importantly, CD70 expression was found to be maintained at the metastatic sites of RCC. Anti-CD70 antibody-drug conjugates (ADC) consisting of auristatin phenylalanine phenylenediamine (AFP) or monomethyl auristatin phenylalanine (MMAF), two novel derivatives of the anti-tubulin agent auristatin, mediated potent antigen-dependent cytotoxicity in CD70-expressing RCC cells. Cytotoxic activity of these anti-CD70 ADCs was associated with their internalization and subcellular trafficking through the endosomal-lysosomal pathway, disruption of cellular microtubule network, and G2-M phase cell cycle arrest. The efficiency of drug delivery using anti-CD70 as vehicle was illustrated by the much enhanced cytotoxicity of antibody-conjugated MMAF compared with free MMAF. Hence, ADCs targeted to CD70 can selectively recognize RCC, internalize, and reach the appropriate subcellular compartment(s) for drug release and tumor cell killing. In vitro cytotoxicity of these ADCs was confirmed in xenograft models using RCC cell lines. Our findings provide evidence that CD70 is an attractive target for antibody-based therapeutics against metastatic RCC and suggest that anti-CD70 ADCs can provide a new treatment approach for advanced RCC patients who currently have no chemotherapeutic options. (Cancer Res 2006; 66(4): 2328-37)