Identification of Pathway Deregulation – Gene Expression Based Analysis of Consistent Signal Transduction

<div><p>Signaling pathways belong to a complex system of communication that governs cellular processes. They represent signal transduction from an extracellular stimulus via a receptor to intracellular mediators, as well as intracellular interactions. Perturbations in signaling cascade often lead to detrimental changes in cell function and cause many diseases, including cancer. Identification of deregulated pathways may advance the understanding of complex diseases and lead to improvement of therapeutic strategies. We propose Analysis of Consistent Signal Transduction (ACST), a novel method for analysis of signaling pathways. Our method incorporates information regarding pathway topology, as well as data on the position of every gene in each pathway. To preserve gene-gene interactions we use a subject-sampling permutation model to assess the significance of pathway perturbations. We applied our approach to nine independent datasets of global gene expression profiling. The results of ACST, as well as three other methods used to analyze signaling pathways, are presented in the context of biological significance and repeatability among similar, yet independent, datasets. We demonstrate the usefulness of using information of pathway structure as well as genes’ functions in the analysis of signaling pathways. We also show that ACST leads to biologically meaningful results and high repeatability.</p></div

The plot presents all consistent relations and stand for any sign statistics which reflect the direction of expression changes between the analyzed conditions of genes and expresses the type of interaction.

<p>The plot presents all consistent relations and stand for any sign statistics which reflect the direction of expression changes between the analyzed conditions of genes and expresses the type of interaction.</p

The plot presents scores of positions of found consistent subgraphs.

<p>Both figures present the same artificial graph but with marked different expression changes. The expression changes were marked with colors. The red color marks overexpression in the tested group (with regard to control), while the blue color represents underexpression. The nodes are marked with their distance (see the definitions and notations subsection) to leaves of the graph. The green arrows represent consistent relations.</p

ACST results on Breast Cancer.

<p>ACST results on Breast Cancer.</p

ACST results on four colorectal cancer datasets.

<p>ACST results on four colorectal cancer datasets.</p

ACST results on Renal Cell Cancer.

<p>ACST results on Renal Cell Cancer.</p

ACST results on VIN.

<p>ACST results on VIN.</p

Radioresistance of Brain Tumors

Radiation therapy (RT) is frequently used as part of the standard of care treatment of the majority of brain tumors. The efficacy of RT is limited by radioresistance and by normal tissue radiation tolerance. This is highlighted in pediatric brain tumors where the use of radiation is limited by the excessive toxicity to the developing brain. For these reasons, radiosensitization of tumor cells would be beneficial. In this review, we focus on radioresistance mechanisms intrinsic to tumor cells. We also evaluate existing approaches to induce radiosensitization and explore future avenues of investigation