A clinical study assessing the tolerability and biological effects of infliximab, a TNF-alpha inhibitor, in patients with advanced cancer

BACKGROUND: Tumour necrosis factor-alpha (TNF-alpha) is an important regulator of the chronic inflammation contributing to tumour progression. Infliximab, an anti-TNF-alpha monoclonal antibody was investigated in this trial of patients with advanced cancer. The primary objectives were to determine the safety profile and biological response of infliximab in a cancer population. Clinical response was a secondary objective. PATIENTS AND METHODS: Forty-one patients received infliximab at 5 mg/kg (n = 21) or 10 mg/kg (n = 20) i.v. at 0 and 2 weeks and then every 4 weeks. Post-treatment samples were measured for changes in plasma and serum TNF-alpha, CCL2, IL-6 and C-reactive protein (CRP). RESULTS: Infliximab was well tolerated with no dose-limiting toxic effects. At both doses of infliximab, neutralisation of serum TNF-alpha was observed after 1 h while plasma CCL2, IL-6 and serum CRP were decreased 24 and 48 h following infliximab administration. Seven patients experienced disease stablisation (range 10-50+ weeks). There was no evidence of disease acceleration in any patient. CONCLUSIONS: Infliximab treatment was safe and well tolerated in patients with advanced cancer. There was evidence of biological activity with baseline TNF-alpha and CCL2 being correlated with infliximab response.     

Multispectral analysis of magnetic resonance images

Magnetic resonance (MR) imaging systems produce spatial distribution estimates of proton density, relaxation time, and flow, in a two dimensional matrix form that is analogous to that of the image data obtained from multispectral imaging satellites. Advanced NASA satellite image processing offers sophisticated multispectral analysis of MR images. Spin echo and inversion recovery pulse sequence images were entered in a digital format compatible with satellite images and accurately registered pixel by pixel. Signatures of each tissue class were automatically determined using both supervised and unsupervised classification. Overall tissue classification was obtained in the form of a theme map. In MR images of the brain, for example, the classes included CSF, gray matter, white matter, subcutaneous fat, muscle, and bone. These methods provide an efficient means of identifying subtle relationships in a multi-image MR study.