Antibody Algorithm for Tumor Diagnostics

A new tool is designed to help pathologists select relevant antibody panels and provides an overview of the available and relevant markers for the subclassification of tumors.

Correct tumor classification is often difficult and always critical for proper patient management. If tumors are misclassified, patients are exposed to therapies that do not help them and may cause serious side effects. Called the Antibody Algorithm for tumor diagnostics, the new tool comprises tables of typical tumor immunophenotypes to aid the identification of phenotypic staining patterns for a given tumor.

The Antibody Algorithm was developed by DakoCytomation (Copenhagen, Denmark), which notes that it may serve as an inspiration to pathologists that are planning antibody panels for the classification of neoplastic lesions. The algorithm was created by pathologists, is based on well-established knowledge, and will be updated continuously, says the company. It is currently available on the Danish DakoCytomation website.



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