The Adnectin CT-322 is a novel VEGF receptor 2 inhibitor that decreases tumor burden in an orthotopic mouse model of pancreatic cancer

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer continues to have a 5-year survival of less than 5%. Therefore, more effective therapies are necessary to improve prognosis in this disease. Angiogenesis is required for tumor growth, and subsequently, mediators of angiogenesis are attractive targets for therapy. Vascular endothelial growth factor (VEGF) is a well-characterized mediator of tumor angiogenesis that functions primarily by binding and activating VEGF receptor 2 (VEGFR2). In this study, we evaluate the use of CT-322, a novel biologic (Adnectin). This small protein is based on a human fibronectin domain and has beneficial properties in that it is fully human, stable, and is produced in bacteria. CT-322 binds to and inhibits activation of VEGFR2.</p> <p>Methods</p> <p>The efficacy of CT-322 was evaluated <it>in vivo </it>using two orthotopic pancreatic tumor models. The first model was a human tumor xenograft where MiaPaCa-2 cells were injected into the tail of the pancreas of nude mice. The second model was a syngeneic tumor using Pan02 cells injected into pancreas of C57BL/6J mice. In both models, therapy was initiated once primary tumors were established. Mice bearing MiaPaCa-2 tumors were treated with vehicle or CT-322 alone. Gemcitabine alone or in combination with CT-322 was added to the treatment regimen of mice bearing Pan02 tumors. Therapy was given twice a week for six weeks, after which the animals were sacrificed and evaluated (grossly and histologically) for primary and metastatic tumor burden. Primary tumors were also evaluated by immunohistochemistry for the level of apoptosis (TUNEL), microvessel density (MECA-32), and VEGF-activated blood vessels (Gv39M).</p> <p>Results</p> <p>Treatment with CT-322 was effective at preventing pancreatic tumor growth and metastasis in orthotopic xenograft and syngeneic models of pancreatic cancer. Additionally, CT-322 treatment increased apoptosis, reduced microvessel density and reduced the number of VEGF-activated blood vessels in tumors. Finally, CT-322, in combination with gemcitabine was safe and effective at controlling the growth of syngeneic pancreatic tumors in immunocompetent mice.</p> <p>Conclusion</p> <p>We conclude that CT-322 is an effective anti-VEGFR2 agent and that further investigation of CT-322 for the treatment of pancreatic cancer is warranted.</p

Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800–1800 cm−1 can be acquired from gastric tissue within 5 s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200–1500 cm−1 and 1600–1800 cm−1, which contained signals related to amide III and amide I of proteins, CH3CH2 twisting of proteins/nucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875 cm−1 to the peak intensity at 1450 cm−1 gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules

Raman spectroscopy and advanced mathematical modelling in the discrimination of human thyroid cell lines

Raman spectroscopy could offer non-invasive, rapid and an objective nature to cancer diagnostics. However, much work in this field has focused on resolving differences between cancerous and non-cancerous tissues, and lacks the reproducibility and interpretation to be put into clinical practice. Much work is needed on basic cellular differences between malignancy and normal. This would allow the establishment of a clinically relevant cellular based model to translate to tissue classification. Raman spectroscopy provides a very detailed biochemical analysis of the target material and to 'unlock' this potential requires sophisticated mathematical modelling such as neural networks as an adjunct to data interpretation. Commercially obtained cancerous and non-cancerous cells, cultured in the laboratory were used in Raman spectral measurements. Data trends were visualised through PCA and then subjected to neural network analysis based on self-organising maps; consisting of m maps, where m is the number of classes to be recognised. Each map approximates the statistical distribution of a given class. The neural network analysis provided a 95% accuracy for identification of the cancerous cell line and 92% accuracy for normal cell line. In this preliminay study we have demonstrated th ability to distinguish between "normal" and cancerous commercial cell lines. This encourages future work to establish the reasons underpinning these spectral differences and to move forward to more complex systems involving tissues. We have also shown that the use of sophisticated mathematical modelling allows a high degree of discrimination of 'raw' spectral data

Raman spectroscopy in head and neck cancer

In recent years there has been much interest in the use of optical diagnostics in cancer detection. Early diagnosis of cancer affords early intervention and greatest chance of cure. Raman spectroscopy is based on the interaction of photons with the target material producing a highly detailed biochemical 'fingerprint' of the sample. It can be appreciated that such a sensitive biochemical detection system could confer diagnostic benefit in a clinical setting. Raman has been used successfully in key health areas such as cardiovascular diseases, and dental care but there is a paucity of literature on Raman spectroscopy in Head and Neck cancer. Following the introduction of health care targets for cancer, and with an ever-aging population the need for rapid cancer detection has never been greater. Raman spectroscopy could confer great patient benefit with early, rapid and accurate diagnosis. This technique is almost labour free without the need for sample preparation. It could reduce the need for whole pathological specimen examination, in theatre it could help to determine margin status, and finally peripheral blood diagnosis may be an achievable target

Raman Spectroscopy and Regenerative Medicine: A Review

The field of regenerative medicine spans a wide area of the biomedical landscape—from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool