
doi: 10.1002/jcb.22794
pmid: 20677215
AbstractCell invasiveness is essential for cancer metastasis. Many proteins, and more recently also non‐coding RNAs, particularly microRNAs (miRNAs), have been reported to affect the cell invasiveness of various cancers. There is an apparent gap between the high number of these macromolecules and the low number of signaling pathways experimentally verified to control cancer invasiveness. We have brought together these various proteins and RNAs because we could not find any publication that filled this important gap. We have noted 589 proteins, 28 miRNAs, and 1 long non‐coding RNA that are reported to modulate invasiveness in cells of various cancers. Interestingly, 44 proteins enhance invasiveness in cells of some cancers, but suppress it in cells of others. Almost all of the proteins that show experimentally verified activation/inhibition effects on, or binding interactions with, each other are linked together in a single network, in a “hub‐and‐spoke” architecture. The accumulated data show trends that point to anticipated future results and highlight gaps in what is known about invasiveness signaling. Identification of cancer invasiveness signaling networks is important for combination and personalized targeted therapies of cancers. J. Cell. Biochem. 111: 791–796, 2010. © 2010 Wiley‐Liss, Inc.
Cell Movement, Humans, Neoplasm Invasiveness, Databases, Protein, Neoplasm Proteins, Protein Binding, Signal Transduction
Cell Movement, Humans, Neoplasm Invasiveness, Databases, Protein, Neoplasm Proteins, Protein Binding, Signal Transduction
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
