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Find video protocols related to scientific articles indexed in Pubmed.
Ribonucleotide reductase small subunit M2B prognoses better survival in colorectal cancer.
Cancer Res.
PUBLISHED: 03-17-2011
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Ribonucleotide reductase subunit RRM2B (p53R2) has been reported to suppress invasion and metastasis in colorectal cancer (CRC). Here, we report that high levels of RRM2B expression are correlated with markedly better survival in CRC patients. In a fluorescence-labeled orthotopic mouse xenograft model, we confirmed that overexpression of RRM2B in nonmetastatic CRC cells prevented lung and/or liver metastasis, relative to control cells that did metastasize. Clinical outcome studies were conducted on a training set with 103 CRCs and a validation set with 220 CRCs. All participants underwent surgery with periodic follow-up to determine survivability. A newly developed specific RRM2B antibody was employed to carry out immunohistochemistry for determining RRM2B expression levels on tissue arrays. In the training set, the Kaplan-Meier and multivariate Cox analysis revealed that RRM2B is associated with better survival of CRCs, especially in stage IV patients (HR = 0.40; 95% CI = 0.18-0.86, P = 0.016). In the validation set, RRM2B was negatively related to tumor invasion (OR = 0.45, 95% CI = 0.19-0.99, P = 0.040) and lymph node involvement (OR = 0.48, 95% CI = 0.25-0.92, P = 0.026). Furthermore, elevated expression of RRM2B was associated with better prognosis in this set as determined by multivariate analyses (HR = 0.48, 95% CI = 0.26-0.91, P = 0.030). Further investigations revealed that RRM2B was correlated with better survival of CRCs with advanced stage III and IV tumors rather than earlier stage I and II tumors. Taken together, our findings establish that RRM2B suppresses invasiveness of cancer cells and that its expression is associated with a better survival prognosis for CRC patients.
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.