Prognostic Significance of Carbonic Anhydrase IX Expression in Cancer Patients: A Meta-Analysis

Hypoxia is a characteristic of many solid tumors and an adverse prognostic factor for treatment outcome. Hypoxia increases the expression of carbonic anhydrase IX, an enzyme that is predominantly found on tumor cells and is involved in maintaining the cellular pH balance. Many clinical studies investigated the prognostic value of carbonic anhydrase IX expression, but most have been inconclusive, partly due to small numbers of patients included. The present meta-analysis was therefore performed utilizing the results of all clinical studies to determine the prognostic value of carbonic anhydrase IX expression in solid tumors. Renal cell carcinoma was excluded from this meta-analysis due to an alternative mechanism of upregulation. 958 papers were identified from a literature search performed in Pubmed and Embase. These papers were independently evaluated by two reviewers and 147 studies were included in the analysis. The meta-analysis revealed strong significant associations between CAIX expression and all endpoints: overall survival (HR=1.76, 95%CI 1.58 – 1.98), disease-free survival (HR=1.87, 95%CI 1.62 – 2.16), locoregional control (HR=1.54, 95%CI 1.22 – 1.93), disease-specific survival (HR=1.78, 95%CI 1.41 – 2.25), metastasis-free survival (HR=1.82, 95%CI 1.33 – 2.50), and progression-free survival (HR=1.58, 95%CI 1.27 – 1.96). Subgroup analyses revealed similar associations in the majority of tumor sites and types. In conclusion, these results show that patients having tumors with high carbonic anhydrase IX expression have higher risk of locoregional failure, disease progression, and higher risk to develop metastases, independent of tumor type or site. The results of this meta-analysis further support the development of a clinical test to determine patient prognosis based on CAIX expression and may have important implications for the development of new treatment strategies

Role of hypoxia-activated prodrugs in combination with radiation therapy: An in silico approach

Tumour hypoxia has been associated with increased resistance to various cancer treatments, particularly radiation therapy. Conversely, tumour hypoxia is a validated and ideal target for guided cancer drug delivery. For this reason, hypoxia-activated prodrugs (HAPs) have been developed, which remain inactive in the body until in the presence of tissue hypoxia, allowing for an activation tendency in hypoxic regions. We present here an experimentally motivated mathematical model predicting the effectiveness of HAPs in a variety of clinical settings. We first examined HAP effectiveness as a function of the amount of tumour hypoxia and showed that the drugs have a larger impact on tumours with high levels of hypoxia. We then combined HAP treatment with radiation to examine the effects of combination therapies. Our results showed radiation-HAP combination therapies to be more effective against highly hypoxic tumours. The analysis of combination therapies was extended to consider schedule sequencing of the combination treatments. These results suggested that administering HAPs before radiation was most effective in reducing total cell number. Finally, a sensitivity analysis of the drug-related parameters was done to examine the effect of drug diffusivity and enzyme abundance on the overall effectiveness of the drug. Altogether, the results highlight the importance of the knowledge of tumour hypoxia levels before administration of HAPs in order to ensure positive results

Some Thoughts About Appealing Directions for the Future of Fuzzy Theory and Technologies Along the Path Traced by Lotfi Zadeh

The quoted text is an interesting instance of a fuzzy object: it is currently known in slightly diversified forms, each rather different from the quoted one, which corresponds to the first known appearance in English of this adage

An orthotopic non-small cell lung cancer model for image-guided small animal radiotherapy platforms

Objective: Lung cancer is the deadliest cancer worldwide. To increase treatment potential for lung cancer, pre-clinical models that allow testing and follow up of clinically relevant treatment modalities are essential. Therefore, we developed a single-nodule-based orthotopic non-small cell lung cancer tumor model which can be monitored using multimodal non-invasive imaging to select the optimal image-guided radiation treatment plan. Methods: An orthotopic non-small cell lung cancer model in NMRI-nude mice was established to investigate the complementary information acquired from 80 kVp microcone-beam CT (micro-CBCT) and bioluminescence imaging (BLI) using different angles and filter settings. Different micro-CBCT-based radiation-delivery plans were evaluated based on their dose-volume histogram metrics of tumor and organs at risk to select the optimal treatment plan. Results: H1299 cell suspensions injected directly into the lung render exponentially growing single tumor nodules whose CBCT-based volume quantification strongly correlated with BLI-integrated intensity. Parallel-opposed single angle beam plans through a single lung are preferred for smaller tumors, whereas for larger tumors, plans that spread the radiation dose across healthy tissues are favored. Conclusions: Closely mimicking a clinical setting for lung cancer with highly advanced preclinical radiation treatment planning is possible in mice developing orthotopic lung tumors. Advances in knowledge: BLI and CBCT imaging of orthotopic lung tumors provide complementary information in a temporal manner. The optimal radiotherapy plan is tumor volume-dependent

Development and biological evaluation of 99mTc-sulfonamide derivatives for in? vivo visualization of CA IX as surrogate tumor hypoxia markers

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Criticality Analysis of Activity Networks under Interval Uncertainty

Dedicated to the memory of Professor Stefan Chanas - The extended abstract version of this paper has appeared in Proceedings of 11th International Conference on Principles and Practice of Constraint Programming (CP2005) ("Interval Analysis in Scheduling", Fortin et al. 2005)International audienceThis paper reconsiders the Project Evaluation and Review Technique (PERT) scheduling problem when information about task duration is incomplete. We model uncertainty on task durations by intervals. With this problem formulation, our goal is to assert possible and necessary criticality of the different tasks and to compute their possible earliest starting dates, latest starting dates, and floats. This paper combines various results and provides a complete solution to the problem. We present the complexity results of all considered subproblems and efficient algorithms to solve them

Hypoxia-Targeting Carbonic Anhydrase IX Inhibitors by a New Series of Nitroimidazole-Sulfonamides/Sulfamides/Sulfamates

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