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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A robust blood gene expression-based prognostic model for castration-resistant prostate cancer
|
|---|---|
| Published in |
BMC Medicine, August 2015
|
| DOI | 10.1186/s12916-015-0442-0 |
| Pubmed ID | |
| Authors |
Li Wang, Yixuan Gong, Uma Chippada-Venkata, Matthias Michael Heck, Margitta Retz, Roman Nawroth, Matthew Galsky, Che-Kai Tsao, Eric Schadt, Johann de Bono, David Olmos, Jun Zhu, William K. Oh |
| Abstract |
Castration-resistant prostate cancer (CRPC) is associated with wide variations in survival. Recent studies of whole blood mRNA expression-based biomarkers strongly predicted survival but the genes used in these biomarker models were non-overlapping and their relationship was unknown. We developed a biomarker model for CRPC that is robust, but also captures underlying biological processes that drive prostate cancer lethality. Using three independent cohorts of CRPC patients, we developed an integrative genomic approach for understanding the biological processes underlying genes associated with cancer progression, constructed a novel four-gene model that captured these changes, and compared the performance of the new model with existing gene models and other clinical parameters. Our analysis revealed striking patterns of myeloid- and lymphoid-specific distribution of genes that were differentially expressed in whole blood mRNA profiles: up-regulated genes in patients with worse survival were overexpressed in myeloid cells, whereas down-regulated genes were noted in lymphocytes. A resulting novel four-gene model showed significant prognostic power independent of known clinical predictors in two independent datasets totaling 90 patients with CRPC, and was superior to the two existing gene models. Whole blood mRNA profiling provides clinically relevant information in patients with CRPC. Integrative genomic analysis revealed patterns of differential mRNA expression with changes in gene expression in immune cell components which robustly predicted the survival of CRPC patients. The next step would be validation in a cohort of suitable size to quantify the prognostic improvement by the gene score upon the standard set of clinical parameters. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Unknown | 53 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 19% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Bachelor | 8 | 15% |
| Other | 6 | 11% |
| Professor > Associate Professor | 5 | 9% |
| Other | 9 | 17% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 33% |
| Biochemistry, Genetics and Molecular Biology | 9 | 17% |
| Agricultural and Biological Sciences | 5 | 9% |
| Engineering | 4 | 7% |
| Immunology and Microbiology | 3 | 6% |
| Other | 4 | 7% |
| Unknown | 11 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 August 2022.
All research outputs
#4,232,173
of 23,053,169 outputs
Outputs from BMC Medicine
#2,069
of 3,461 outputs
Outputs of similar age
#53,811
of 266,679 outputs
Outputs of similar age from BMC Medicine
#69
of 91 outputs
Altmetric has tracked 23,053,169 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,461 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,679 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.