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New software diagnoses cancer cells

by Lauren Dubinsky, Senior Reporter | July 16, 2014
Dr. Lukas Kenner
Scientists at Vetmeduni Vienna, the Medical University of Vienna, the Ludwig Boltzmann Institute for Cancer Research, and the company Tissuegnostics, came together to create software that reliably diagnoses cancer cells by specifically identifying cell structures and proteins. They conducted a study using the software and it was recently published in the journal Plos One.

When deciding what cancer therapy a patient needs, a pathologist usually analyzes organs and tissues under a microscope, but two independent pathologists agree with each other for only one out of every three diagnoses, according to the study. “We observed a relatively high user dependent variation despite the fact that the pathologists were excellently trained experts in the field,” Dr. Lukas Kenner, one of the chief investigators in the study, wrote to DOTmed News.

The software — Histoquest 4.0 — is not intended to replace pathologists but instead act as a supplemental technology to improve the reliability of the diagnosis.
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For the study, the scientists analyzed 30 liver cell carcinomas with the software on the TissueFAXs imaging system and assigned them to either “negative” or “highly positive” categories. The software uses algorithms and highly sensitive digital photography, which makes it better able to show the matrix of cells and the cell nucleus compared to the human eye, with a microscope.

“We believe that this improvement in accuracy of diagnosis can be used to improve treatment decisions and even more importantly avoid treatment cycles with drugs that are inadequate,” wrote Kenner. “Thereby, the patients will receive as first choice the best suitable drug, and the tumor or disease has much less time and chance to escape.”

He thinks that this software will be revolutionary for personalized medicine for cancer and will benefit from the growing number of specific drugs that can target single molecules.

“This new generation of drugs frequently targets proteins involved in molecular mechanisms such as cell cycle, immune receptors or growth factor receptors and is highly effective when used properly, and provided the target molecule is expressed by tumor or tumor stromal cells,” said Kenner.

The information that the software provides on a “cell to cell basis” is needed in order to design the individual combination of drugs to cover the whole range of a tumor specific transformation, he said.

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