| Title |
∆133p53 isoform promotes tumour invasion and metastasis via interleukin-6 activation of JAK-STAT and RhoA-ROCK signalling
|
|---|---|
| Published in |
Nature Communications, January 2018
|
| DOI | 10.1038/s41467-017-02408-0 |
| Pubmed ID | |
| Authors |
Hamish Campbell, Nicholas Fleming, Imogen Roth, Sunali Mehta, Anna Wiles, Gail Williams, Claire Vennin, Nikola Arsic, Ashleigh Parkin, Marina Pajic, Fran Munro, Les McNoe, Michael Black, John McCall, Tania L. Slatter, Paul Timpson, Roger Reddel, Pierre Roux, Cristin Print, Margaret A. Baird, Antony W. Braithwaite |
| Abstract |
∆122p53 mice (a model of ∆133p53 isoform) are tumour-prone, have extensive inflammation and elevated serum IL-6. To investigate the role of IL-6 we crossed ∆122p53 mice with IL-6 null mice. Here we show that loss of IL-6 reduced JAK-STAT signalling, tumour incidence and metastasis. We also show that ∆122p53 activates RhoA-ROCK signalling leading to tumour cell invasion, which is IL-6-dependent and can be reduced by inhibition of JAK-STAT and RhoA-ROCK pathways. Similarly, we show that Δ133p53 activates these pathways, resulting in invasive and migratory phenotypes in colorectal cancer cells. Gene expression analysis of colorectal tumours showed enrichment of GPCR signalling associated with ∆133TP53 mRNA. Patients with elevated ∆133TP53 mRNA levels had a shorter disease-free survival. Our results suggest that ∆133p53 promotes tumour invasion by activation of the JAK-STAT and RhoA-ROCK pathways, and that patients whose tumours have high ∆133TP53 may benefit from therapies targeting these pathways. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| New Zealand | 1 | 33% |
| Australia | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 20% |
| Student > Bachelor | 11 | 15% |
| Student > Master | 10 | 13% |
| Researcher | 7 | 9% |
| Student > Doctoral Student | 4 | 5% |
| Other | 10 | 13% |
| Unknown | 18 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 28 | 37% |
| Agricultural and Biological Sciences | 14 | 19% |
| Medicine and Dentistry | 6 | 8% |
| Chemistry | 3 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 20 | 27% |