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microRNAs (miRNAs) are small RNAs that play key roles in regulation of cellular processes and therefore could largely contribute to solving many problems in medicine, biotechnology, and other biological sciences. As a result, the numbers of research projects and publications on miRNAs are constantly growing, which is accompanied by increasing amounts of new data and databases need to be created for data storage. There are 51 dedicated miRNA databases at the moment, what make it quite difficult for the users to find relevant data. Moreover, such problems as insufficient documentation, low quality of data or flaws in the graphical interface make the things even worse. However, there are positive signs, including standardization of database interfaces, a tendency to create integrated systems that collect data from a number of databases and present it in a uniform format, and emergence of systems for automated data search and download.

Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search for new microRNAs. We present miRNEST (http://mirnest.amu.edu.pl), a comprehensive database of animal, plant and virus microRNAs. The core part of the database is built from our miRNA predictions conducted on Expressed Sequence Tags of 225 animal and 202 plant species. The miRNA search was performed based on sequence similarity and as many as 10,004 miRNA candidates in 221 animal and 199 plant species were discovered. Out of them only 299 have already been deposited in miRBase. Additionally, miRNEST has been integrated with external miRNA data from literature and 13 databases, which includes miRNA sequences, small RNA sequencing data, expression, polymorphisms and targets data as well as links to external miRNA resources, whenever applicable. All this makes miRNEST a considerable miRNA resource in a sense of number of species (544) that integrates a scattered miRNA data into a uniform format with a user-friendly web interface.

Background: Bevacizumab (Avastin) significantly improves overall survival (OS) and progression-free survival (PFS) when combined with first-line irinotecan (IFL) plus bolus 5-fluorouracil (5-FU) and leucovorin (LV) in patients with metastatic colorectal cancer (CRC). This open-label, phase IV trial evaluated the efficacy and safety of first-line bevacizumab in combination with IFL and infusional 5-FU/LV (FOLFIRI)., Methods: Two-hundred and nine treatment-naïve metastatic CRC patients were enrolled and received bevacizumab and FOLFIRI every 2 weeks. Treatment was continued until disease progression. The primary objective was PFS, with additional determinations of OS, response and toxicity., Results: Median PFS was 11.1 months and is comparable to that observed in published phase III and community-based trials using first-line bevacizumab plus FOLFIRI, and to phase III trials using bevacizumab in combination with bolus 5-FU/LV plus IFL. Median OS was 22.2 months. Overall response rate was 53.1% and the disease control rate 85.6%. Most adverse events were grade 1/2 and were manageable. The most common grade 3/4 adverse events (> or =10%) were neutropenia, venous thromboembolic events, diarrhea, and fatigue., Conclusion: Bevacizumab combined with first-line FOLFIRI is an effective and well-tolerated therapy option for patients with metastatic CRC., (Copyright 2009 S. Karger AG, Basel.)