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Early detection of breast cancer using total biochemical analysis of peripheral blood components: a preliminary study

Overview of attention for article published in BMC Cancer, May 2015
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Title
Early detection of breast cancer using total biochemical analysis of peripheral blood components: a preliminary study
Published in
BMC Cancer, May 2015
DOI 10.1186/s12885-015-1414-7
Pubmed ID
Authors

Udi Zelig, Eyal Barlev, Omri Bar, Itai Gross, Felix Flomen, Shaul Mordechai, Joseph Kapelushnik, Ilana Nathan, Hanoch Kashtan, Nir Wasserberg, Osnat Madhala-Givon

Abstract

Most of the blood tests aiming for breast cancer screening rely on quantification of a single or few biomarkers. The aim of this study was to evaluate the feasibility of detecting breast cancer by analyzing the total biochemical composition of plasma as well as peripheral blood mononuclear cells (PBMCs) using infrared spectroscopy. Blood was collected from 29 patients with confirmed breast cancer and 30 controls with benign or no breast tumors, undergoing screening for breast cancer. PBMCs and plasma were isolated and dried on a zinc selenide slide and measured under a Fourier transform infrared (FTIR) microscope to obtain their infrared absorption spectra. Differences in the spectra of PBMCs and plasma between the groups were analyzed as well as the specific influence of the relevant pathological characteristics of the cancer patients. Several bands in the FTIR spectra of both blood components significantly distinguished patients with and without cancer. Employing feature extraction with quadratic discriminant analysis, a sensitivity of ~90 % and a specificity of ~80 % for breast cancer detection was achieved. These results were confirmed by Monte Carlo cross-validation. Further analysis of the cancer group revealed an influence of several clinical parameters, such as the involvement of lymph nodes, on the infrared spectra, with each blood component affected by different parameters. The present preliminary study suggests that FTIR spectroscopy of PBMCs and plasma is a potentially feasible and efficient tool for the early detection of breast neoplasms. An important application of our study is the distinction between benign lesions (considered as part of the non-cancer group) and malignant tumors thus reducing false positive results at screening. Furthermore, the correlation of specific spectral changes with clinical parameters of cancer patients indicates for possible contribution to diagnosis and prognosis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 20%
Student > Ph. D. Student 17 17%
Student > Master 16 16%
Student > Doctoral Student 6 6%
Researcher 5 5%
Other 11 11%
Unknown 24 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 22%
Medicine and Dentistry 11 11%
Engineering 8 8%
Agricultural and Biological Sciences 6 6%
Chemistry 5 5%
Other 21 21%
Unknown 26 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 27 May 2015.
All research outputs
#17,756,606
of 22,803,211 outputs
Outputs from BMC Cancer
#4,958
of 8,297 outputs
Outputs of similar age
#179,450
of 264,753 outputs
Outputs of similar age from BMC Cancer
#137
of 223 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,297 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 34th percentile – i.e., 34% 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 264,753 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.