Automated analysis of fish and immunohistochemistry images: a review

Fluorescent in-situ hybridization (FISH) and immunohistochemistry (IHC) constitute a pair of complimentary techniques for detecting gene amplification and overexpression, respectively. The advantages of IHC include relatively cheap materials and high sample durability, while FISH is the more accurate and reproducible method. Evaluation of FISH and IHC images is still largely performed manually, with automated or semiautomated techniques increasing in popularity. Here, we provide a comprehensive review of a number of (semi-) automated FISH and IHC image processing systems, focusing on the algorithmic aspects of each technique. Our review verifies the increasingly important role of such methods in FISH and IHC; however, manual intervention is still necessary in order to resolve particularly challenging or ambiguous cases. In addition, large-scale validation is required in order for these systems to enter standard clinical practice

Evaluation of fish image analysis system on assessing her2 amplification in breast carcinoma cases

HER2-positive breast cancer is characterized by aggressive growth and poor prognosis. Women with metastatic breast cancer with over-expression of HER2 protein or excessive presence of HER2 gene copies are potential candidates for Herceptin (Trastuzumab) targeted treatment that binds to HER2 receptors on tumor cells and inhibits tumor cell growth. Fluorescence in situ hybridization (FISH) is one of the most widely used methods to determine HER2 status. Typically, evaluation of FISH images involves manual counting of FISH signals in multiple images, a time consuming and error prone procedure. Recently, we developed novel software for the automated evaluation of FISH images and, in this study, we present the first testing of this software on images from two separate research clinics. To our knowledge, this is the first concurrent evaluation of any FISH image analysis software in two different clinics. The evaluation shows that the developed FISH image analysis software can accelerate evaluation of HER2 status in most breast cancer cases

State-of-the-Art Neural Networks Applications in Biology

Artificial neural networks (ANNs) are a well-established computational method inspired by the structure and function of biological central nervous systems. Since their conception, ANNs have been utilized in a vast variety of applications due to their impressive information processing abilities. A vibrant field, ANNs have been utilized in bioinformatics, a general term for describing the combination of informatics, biology and medicine. This article is an effort to investigate recent advances in the area of bioinformatical applications of ANNs, with emphasis in disease diagnosis, genetics, proteomics, and chemoinformatics. The combination of neural networks and game theory in some of these application is also discussed.</p

THE BREAST Evaluation of FISH image analysis system on assessing HER2 amplification in breast carcinoma cases

Abstract HER2-positive breast cancer is characterized by aggressive growth and poor prognosis. Women with metastatic breast cancer with over-expression of HER2 protein or excessive presence of HER2 gene copies are potential candidates for Herceptin (Trastuzumab) targeted treatment that binds to HER2 receptors on tumor cells and inhibits tumor cell growth. Fluorescent in situ hybridization (FISH) Q1 is one of the most widely used methods to determine HER2 status. Typically, evaluation of FISH images involves manual counting of FISH signals in multiple images, a time consuming and error prone procedure. Recently, we developed novel software for the automated evaluation of FISH images and, in this study, we present the first testing of this software on images from two separate research clinics. To our knowledge, this is the first concurrent evaluation of any FISH image analysis software in two different clinics. The evaluation shows that the developed FISH image analysis software can accelerate evaluation of HER2 status in most breast cancer cases.

Cell Cycle Status of CD34+ Hemopoietic Stem Cells Determines Lentiviral Integration in Actively Transcribed and Development-related Genes

Gene therapy utilizing lentiviral-vectors (LVs) is postulated as a dynamic therapeutic alternative for monogenic diseases. However, retroviral gene transfer may cause insertional mutagenesis. Although, such risks had been originally estimated as extremely low, several reports of leukemias or clonal dominance, have led to a re-evaluation of the mechanisms operating in insertional mutagenesis. Therefore, unraveling the mechanism of retroviral integration is mandatory toward safer gene therapy applications. In the present study, we undertook an experimental approach which enabled direct correlation of the cell cycle stage of the target cell with the integration profile of LVs. CD34(+) cells arrested at different stages of cell cycle, were transduced with a GFP-LV. LAM-PCR was employed for integration site detection, followed by microarray analysis to correlate transcribed genes with integration sites. The results indicate that ~10% of integration events occurred in actively transcribed genes and that the cell cycle stage of target cells affects integration pattern. Specifically, use of thymine promoted a safer profile, since it significantly reduced integration within cell cycle-related genes, while we observed increased possibility for integration into genes related to development, and decreased possibility for integration within cell cycle and cancer-related genes, when transduction occurs during mitosis

Cell Cycle Status of CD34+Hemopoietic Stem Cells Determines Lentiviral Integration in Actively Transcribed and Development-related Genes

Gene therapy utilizing lentiviral-vectors (LVs) is postulated as a dynamic therapeutic alternative for monogenic diseases. However, retroviral gene transfer may cause insertional mutagenesis. Although, such risks had been originally estimated as extremely low, several reports of leukemias or clonal dominance, have led to a re-evaluation of the mechanisms operating in insertional mutagenesis. Therefore, unraveling the mechanism of retroviral integration is mandatory toward safer gene therapy applications. In the present study, we undertook an experimental approach which enabled direct correlation of the cell cycle stage of the target cell with the integration profile of LVs. CD34+ cells arrested at different stages of cell cycle, were transduced with a GFP-LV. LAM-PCR was employed for integration site detection, followed by microarray analysis to correlate transcribed genes with integration sites. The results indicate that similar to 10% of integration events occurred in actively transcribed genes and that the cell cycle stage of target cells affects integration pattern. Specifically, use of thymine promoted a safer profile, since it significantly reduced integration within cell cycle-related genes, while we observed increased possibility for integration into genes related to development, and decreased possibility for integration within cell cycle and cancer-related genes, when transduction occurs during mitosis