Bortezomib/docetaxel combination therapy in patients with anthracycline-pretreated advanced/metastatic breast cancer: a phase I/II dose-escalation study

The aim of this study was to determine the dose-limiting toxicities (DLTs) and maximum tolerated dose (MTD) of bortezomib plus docetaxel in patients with anthracycline-pretreated advanced/metastatic breast cancer. Forty-eight patients received up to eight 21-day cycles of docetaxel (60–100 mg m−2 on day 1) plus bortezomib (1.0–1.5 mg m−2 on days 1, 4, 8, and 11). Pharmacodynamic and pharmacokinetic analyses were performed in a subset of patients. Five patients experienced DLTs: grade 3 bone pain (n=1) and febrile neutropenia (n=4). The MTD was bortezomib 1.5 mg m−2 plus docetaxel 75 mg m−2. All 48 patients were assessable for safety and efficacy. The most common adverse events were diarrhoea, nausea, alopecia, asthenia, and vomiting. The most common grade 3/4 toxicities were neutropenia (44%), and febrile neutropenia and diarrhoea (each 19%). Overall patient response rate was 29%. Median time to progression was 5.4 months. In patients with confirmed response, median time to response was 1.3 months and median duration of response was 3.2 months. At the MTD, response rate was 38%. Pharmacokinetic characteristics of bortezomib/docetaxel were comparable with single-agent data. Addition of docetaxel appeared not to affect bortezomib inhibition of 20S proteasome activity. Mean alpha-1 acid glycoprotein concentrations increased from baseline at nearly all time points across different bortezomib dose levels. Bortezomib plus docetaxel is an active combination for anthracycline-pretreated advanced/metastatic breast cancer. The safety profile is manageable and consistent with the side effects of the individual agents

Inhibition of IGF-1 Signalling Enhances the Apoptotic Effect of AS602868, an IKK2 Inhibitor, in Multiple Myeloma Cell Lines

Multiple myeloma (MM) is a B cell neoplasm characterized by bone marrow infiltration with malignant plasma cells. IGF-1 signalling has been explored as a therapeutic target in this disease. We analyzed the effect of the IKK2 inhibitor AS602868, in combination with a monoclonal antibody targeting IGF-1 receptor (anti-IGF-1R) in human MM cell lines. We found that anti-IGF-1R potentiated the apoptotic effect of AS602868 in LP1 and RPMI8226 MM cell lines which express high levels of IGF-1R. Anti-IGF-1R enhanced the inhibitory effect of AS602868 on NF-κB pathway signalling and potentiated the disruption of mitochondrial membrane potential caused by AS602868. These results support the role of IGF-1 signalling in MM and suggest that inhibition of this pathway could sensitize MM cells to NF-κB inhibitors

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Application of salivary noncoding microRNAs for the diagnosis of oral cancers.

Oral cancer is on the rise globally and survival rates, despite improvements in clinical care, have not significantly improved. Early detection followed by immediate intervention is key to improving patient outcomes. The use of biomarkers has changed the diagnostic landscape for many cancers. For oral cancers, visual inspection followed by a tissue biopsy is standard practice. The discovery of microRNAs as potential biomarkers has attracted clinical interest but several challenges remain. These microRNAs can be found in bodily fluids such as blood and saliva which have been investigated as potential sources of biomarker discovery. As oral cancer is localized within the oral cavity, saliva may contain clinically relevant molecular markers for disease detection. Our review provides an outline of the current advances for the application of salivary microRNAs in oral cancer. We also provide a technical guide for the processing of salivary RNAs to ensure accurate clinical measurement and validation