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| Status |
Public on Sep 01, 2014 |
| Title |
RECK Controls Breast Cancer Metastasis by Modulating a Convergent, STAT3-dependent Neoangiogenic Switch |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Metastasis leads to the majority of deaths in breast cancer patients. Here we investigated the molecular and biochemical signaling pathways altered by RECK, a major metastasis suppressor gene in breast cancer. We overexpressed RECK in 2 highly invasive cell lines and knocked-down RECK expression in 2 poorly invasive cell lines. IPA analysis of differentially expressed genes revealed IL-6, and IL8 signaling alteration with RECK pertubation. This lead us to discover that RECK suppresses metastasis and neoangiogenesis at secondary sites by inhibiting STAT3 dependent VEGF & uPA regulating. This finding is significant because it reveals the biology behind a major metastasis suppressor gene in cancer.
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| Overall design |
Cell lines were obtained from the ATCC or were generous gifts from Dr Joan Massague (MSKCC). Invasive cell lines were stably infected with a constitutively expressing RECK construct or and Empty Vector control. Poorly invasive cell lines were transfected with a Scramble siRNA or siRNA targeting the RECK gene. RNA was extracted using the RNeasy kit (Qiagen) as per the manufacturer’s instructions. Expression analysis was performed using the Affymetrics U133 2.0 microarray (Affymetrix). Affymetrix CEL files were imported into the Partek Genomics Suite (Partek).
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| Contributor(s) |
Walsh LA, Roy DM, Reyngold M, Giri D, Snyder A, Turcan S, Badwe CR, Lyman J, Bromberg J, King TA, Chan TA |
| Citation(s) |
24931164 |
| Submission date |
Apr 17, 2014 |
| Last update date |
Dec 06, 2018 |
| Contact name |
Logan A Walsh |
| E-mail(s) |
walshl@mskcc.org
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| Phone |
6468882783
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| Organization name |
Memorial Sloan Kettering Cancer Center
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| Department |
Human Oncology and Pathogenesis Program
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| Lab |
Timothy Chan
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| Street address |
1275 York Ave
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| City |
New York |
| State/province |
NY |
| ZIP/Postal code |
10065 |
| Country |
USA |
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| Platforms (1) |
| GPL571 |
[HG-U133A_2] Affymetrix Human Genome U133A 2.0 Array |
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| Samples (16)
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| Relations |
| BioProject |
PRJNA244880 |
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