Multiple Protein Biomarkers as Highly Specific Early Diagnostic Medicine for Breast Cancer


According to recent study conducted by a molecular diagnostics company, Provista Diagnostics, diagnosis of multiple types of protein biomarkers together, present in blood provide a technological advancement in the sensitive and specific detection of breast cancer at an early stage.

Provista DiagnosticsIn a comparative study, combinatorial as well as individual ability of Serum Protein Biomarkers (SPBs) and Tumor-Associated Autoantibodies (TAAbs) were studied for early detection of breast cancer. The research is published in PLOS ONE Journal.

The study is a part of broader pipeline of research studies focused on investigating the use of the biomarkers (SPB and TAAbs) in novel blood-based diagnostic test named “Videssa® Breast” designed by Provista Diagnostics which is scheduled to be published in 2016.


Figure 1. Provista’s ProteoMark Technology Platform (photo credit:  Provista Diagnostics).

Videssa® Breast is a first of its kind protein based blood test to provide highly specific and accurate detection of breast cancer in early stages.


Figure 2. Biomarker assay score (photo credit:  Provista Diagnostics).

In the research study conducted, 210 serum samples were obtained prior to biopsy and retrospective study was done to evaluate the Protein Biomarkers (SPB and TAAbs) in the comparative study.

Results obtained were based on the statistical models developed by using the data obtained from the expression of SPB, TAAb, and combination of SPB and TAAb to distinguish between breast cancer patients and non breast cancer patients.

Serum Protein Biomarkers plos one

Figure 3. SPB Expression across Patient Groups. (photo credit: PLoS ONE 11(8): e0157692. doi: 10.1371/journal.pone.0157692).

Independently developed SPB statistical model data recorded clinical sensitivity and specificity of 74.7% and 77.0% respectively and independently developed TAAb statistical model data recorded 72.2% and 70.8% respectively. However, combination of SPB and TAAb improved the clinical sensitivity and specificity for detection of breast cancer and the resulted percentage observed was an increased value of 81.0% and 78.8% respectively. Thereby, confirming the fact that Combinatorial Proteomic Approaches provides better detection and should further be used for developing novel techniques.

Breast Cancer is one of the most commonly detected cancers in females and is the primary reason for cancer mortality in women. Although several techniques like mammographic screening, Multi-modality screenings have developed lately but the procedures provide accurate results only in high risk patients. In addition, the cost of these test are relatively high and less feasible because of the diagnostic challenges with imaging in low risk patients.

The American College of Radiology has created a standardized quality assurance approach named BI-RADS® (Breast Imaging–Reporting and Data System) to study the breast imaging reports and divided it into several categories from level 1 to level 5. Every level has a different probability of breast cancer along with the possible steps to be taken if detected in any of the levels.

Imaging Diagnostic challenges are especially difficult in level 3 (benign finding) and 4 (suspicious finding) When women are found in these categories with abnormal mammography results the patients and doctors has to decide the best possible way to proceed further which either include additional imaging or biopsy. The decision is often very difficult. But the protein- based technique can find the abnormalities in earlier stages and can provide better diagnostic approach thereby reducing the imaging diagnostic problems.

According to David E. Reese,Ph.D., President and CEO of Provista Diagnostics “This study demonstrates clearly that we can offer better diagnostic technologies to not only detect breast cancer at its earliest, most treatable stage, but also reduce the rate of benign biopsies, which is important in improving care for women who do not have breast cancer.”

Featured Image Credit: Provista Diagnostics

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