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Name

DKFZ - Protein biomarker set for personalized treatment of ERα-positive breast cancer (P-1035)

Organization name

DKFZ Deutsches Krebsforschungszentrum

Profile

Facts

  • Consistent risk classification of ER-alpha positive breast cancer specimens
  • Usage of well-established and commercially available antibodies for quantification
  • Method is applicable for reverse phase protein microarrays (RPPA) and quantitative proteomics
  • Method is cost-effective, simple to apply, and only small sample quantities are needed

Abstract

Breast cancer has been recognized as a heterogeneous disease that consists of different intrinsic subtypes, including hormone receptor positive breast cancer (also known as luminal breast cancer), which accounts for 70-80% of newly diagnosed breast tumors.

The histologic grade of luminal breast cancer is often determined by semi-quantitative methods describing morphologic features related to the differentiation states of the tumor specimen, ranging from well differentiated “grade 1” tumors, through intermediate differentiation (“grade 2”) to poorly differentiated “grade 3” tumors. Breast tumors characterized as luminal “grade 3” generally respond well to chemotherapeutic treatments, whereas patients with luminal “grade 1” tumors would be overtreated.

In order to make a clear-cut classification of luminal breast cancer as either “grade 1” (= lowrisk) or “grade 3” (= high risk) tumors, DKFZ researchers have developed a 3-protein marker set.

Development Stage

To date, 109 estrogen receptor positive human breast tumors (grades 1, 2, and 3) have been analyzed and grouped into either low risk or high risk tumors. The initial trials showed a sensitivity of 95% and a specificity of 86% (one established approach identified luminal B breast cancer with sensitivity and specificity values of 72% and 77%, respectively (1)).

The Technology

Proteome profiling was carried out for luminal breast cancer by using reverse phase protein microarrays (RPPA) as the experimental platform.

The resulting quantitative data was analyzed using a combination of different statistical classification methods aimed at a robust discrimination between low risk and high risk tumors. This approach consistently identified a protein signature comprising the following proteins: RPS6, nucleoside-diphosphate kinase (NDKA), and caveolin-1.

In high risk tumors, RPS6 and NDKA are upregulated. On the other hand caveolin-1 is significantly downregulated in high risk tumors in line with its known role in suppressing metabolic shift and tumor growth. Vice versa, low risk tumors express low levels of RPS6 and NDKA but high amounts of caveolin-1.

Commercial Opportunity and Advantages

The marker set enables appropriate clinical decisions to be made for patients with intermediate risk tumors. The method is cost-effective in comparison to mRNA-based diagnostic tools (Oncotype DX, Mammaprint) and can identify high/lowrisk tumors with improved specificity. Only small amounts of frozen tumor samples are needed, and the marker set can be quantified routinely in diagnostic laboratories using well-established commercially available antibodies.

Inventors

The inventors are Ulrike Korf, Johanna Sonntag, Christian Bender, and Stefan Wiemann DKFZ Heidelberg, Germany.

Intellectual Property

A patent “Biomarker set for identifying a severe form of cancer” EP 11 188 202.3 was filed February 10th, 2012.

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