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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A seven-gene CpG-island methylation panel predicts breast cancer progression
|
|---|---|
| Published in |
BMC Cancer, May 2015
|
| DOI | 10.1186/s12885-015-1412-9 |
| Pubmed ID | |
| Authors |
Yan Li, Anatoliy A. Melnikov, Victor Levenson, Emanuela Guerra, Pasquale Simeone, Saverio Alberti, Youping Deng |
| Abstract |
DNA methylation regulates gene expression, through the inhibition/activation of gene transcription of methylated/unmethylated genes. Hence, DNA methylation profiling can capture pivotal features of gene expression in cancer tissues from patients at the time of diagnosis. In this work, we analyzed a breast cancer case series, to identify DNA methylation determinants of metastatic versus non-metastatic tumors. CpG-island methylation was evaluated on a 56-gene cancer-specific biomarker microarray in metastatic versus non-metastatic breast cancers in a multi-institutional case series of 123 breast cancer patients. Global statistical modeling and unsupervised hierarchical clustering were applied to identify a multi-gene binary classifier with high sensitivity and specificity. Network analysis was utilized to quantify the connectivity of the identified genes. Seven genes (BRCA1, DAPK1, MSH2, CDKN2A, PGR, PRKCDBP, RANKL) were found informative for prognosis of metastatic diffusion and were used to calculate classifier accuracy versus the entire data-set. Individual-gene performances showed sensitivities of 63-79 %, 53-84 % specificities, positive predictive values of 59-83 % and negative predictive values of 63-80 %. When modelled together, these seven genes reached a sensitivity of 93 %, 100 % specificity, a positive predictive value of 100 % and a negative predictive value of 93 %, with high statistical power. Unsupervised hierarchical clustering independently confirmed these findings, in close agreement with the accuracy measurements. Network analyses indicated tight interrelationship between the identified genes, suggesting this to be a functionally-coordinated module, linked to breast cancer progression. Our findings identify CpG-island methylation profiles with deep impact on clinical outcome, paving the way for use as novel prognostic assays in clinical settings. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Unknown | 63 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 23% |
| Student > Ph. D. Student | 12 | 18% |
| Student > Master | 9 | 14% |
| Student > Bachelor | 4 | 6% |
| Other | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 14 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 22% |
| Biochemistry, Genetics and Molecular Biology | 13 | 20% |
| Agricultural and Biological Sciences | 9 | 14% |
| Computer Science | 3 | 5% |
| Engineering | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 20 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 06 January 2022.
All research outputs
#6,795,218
of 22,818,766 outputs
Outputs from BMC Cancer
#1,758
of 8,301 outputs
Outputs of similar age
#80,053
of 266,244 outputs
Outputs of similar age from BMC Cancer
#46
of 216 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 8,301 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 78% of its peers.
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 266,244 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.