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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Understanding the functional impact of copy number alterations in breast cancer using a network modeling approach
|
|---|---|
| Published in |
Molecular BioSystems, January 2016
|
| DOI | 10.1039/c5mb00655d |
| Pubmed ID | |
| Authors |
Sriganesh Srihari, Murugan Kalimutho, Samir Lal, Jitin Singla, Dhaval Patel, Peter T. Simpson, Kum Kum Khanna, Mark A. Ragan |
| Abstract |
Copy number alterations (CNAs) are thought to account for 85% of the variation in gene expression observed among breast tumours. The expression of cis-associated genes is impacted by CNAs occurring at proximal loci of these genes, whereas the expression of trans-associated genes is impacted by CNAs occurring at distal loci. While a majority of these CNA-driven genes responsible for breast tumourigenesis are cis-associated, trans-associated genes are thought to further abet the development of cancer and influence disease outcomes in patients. Here we present a network-based approach that integrates copy-number and expression profiles to identify putative cis- and trans-associated genes in breast cancer pathogenesis. We validate these cis- and trans-associated genes by employing them to subtype a large cohort of breast tumours obtained from the METABRIC consortium, and demonstrate that these genes accurately reconstruct the ten subtypes of breast cancer. We observe that individual breast cancer subtypes are driven by distinct sets of cis- and trans-associated genes. Among the cis-associated genes, we recover several known drivers of breast cancer (e.g. CCND1, ERRB2, MDM2 and ZNF703) and some novel putative drivers (e.g. BRF2 and SF3B3). siRNA-mediated knockdown of BRF2 across a panel of breast cancer cell lines showed significant reduction in cell viability for ER-/HER2+ (MDA-MB-453) cells, but not in normal (MCF10A) cells thereby indicating that BRF2 could be a viable therapeutic target for estrogen receptor-negative/HER2-enriched (ER-/HER2+) cancers. Among the trans-associated genes, we identify modules of immune response (CD2, CD19, CD38 and CD79B), mitotic/cell-cycle kinases (e.g. AURKB, MELK, PLK1 and TTK), and DNA-damage response genes (e.g. RFC4 and FEN1). siRNA-mediated knockdown of RFC4 significantly reduced cell proliferation in ER-negative normal breast and cancer lines, thereby indicating that RFC4 is essential for both normal and cancer cell survival but could be a useful biomarker for aggressive (ER-negative) breast tumours. under NetStrat. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 28% |
| Researcher | 8 | 21% |
| Student > Master | 5 | 13% |
| Other | 2 | 5% |
| Professor > Associate Professor | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 6 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 23% |
| Biochemistry, Genetics and Molecular Biology | 8 | 21% |
| Medicine and Dentistry | 8 | 21% |
| Computer Science | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 10 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 26 January 2016.
All research outputs
#15,422,552
of 25,756,911 outputs
Outputs from Molecular BioSystems
#861
of 1,773 outputs
Outputs of similar age
#205,056
of 401,844 outputs
Outputs of similar age from Molecular BioSystems
#81
of 212 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,773 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 49th percentile – i.e., 49% 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 401,844 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 212 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.