AI Article Synopsis
- The cancer stem cell model suggests tumors have a small population of cells with unlimited growth that drive tumor development, making them crucial targets for effective treatment.
- Identifying key pathways for cancer stem cell growth has been tough, but using a method called GAMMA, researchers found 50 genes that may play a role in their division.
- Of these, 21 genes inhibited growth in breast cancer stem cells, and further analysis of 6 genes highlighted 4 that significantly impact chromosome segregation, showcasing the potential of transcriptional network analysis for pinpointing cancer stem cell dependencies.
Article Abstract
The cancer stem cell model postulates that tumors are hierarchically organized with a minor population, the cancer stem cells, exhibiting unlimited proliferative potential. These cells give rise to the bulk of tumor cells, which retain a limited ability to divide. Without successful targeting of cancer stem cells, tumor reemergence after therapy is likely. However, identifying target pathways essential for cancer stem cell proliferation has been challenging. Here, using a transcriptional network analysis termed GAMMA, we identified 50 genes whose correlation patterns suggested involvement in cancer stem cell division. Using RNAi depletion, we found that 21 of these target genes showed preferential growth inhibition in a breast cancer stem cell model. More detailed initial analysis of 6 of these genes revealed 4 with clear roles in the fidelity of chromosome segregation. This study reveals the strong predictive potential of transcriptional network analysis in increasing the efficiency of successful identification of novel proliferation dependencies for cancer stem cells.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5899939 | PMC |
| http://dx.doi.org/10.1016/j.scr.2017.11.009 | DOI Listing |
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