Boost to cancer cell diagnosis
14 Jul 2014
Technology developed in Europe could pave the way for better cancer cell diagnosis.
A recent study led by scientists from the Medical University of Vienna (MUV) found that two independent pathologists were only able to agree on around 33% of cancer cell diagnoses.
To combat this, MUV researchers have developed new software that is designed to boost diagnostic certainty to around double that of current standards.
“The new program of course does not make pathologists redundant
MUV researcher Lukas Kenner
The results have been published in the journal PlosOne.
In pathology, cells and cell nuclei are usually examined using a microscope for bio-marker expressions in tumours.
Unfortunately, the certainty of the diagnosis depends greatly on the individual pathologist.
Now, however, using the newly developed software, MUV researchers claim to have investigated and analysed 30 liver cell carcinomas - accurately classifying them into categories ranging from ’negative’ to ’strongly positive’.
The study measured the expression of the proteins STAT5AB and JUNB in an aggressive T-cell lymphoma.
The software is designed to use certain algorithms and sensitive digital photography, enabling it to represent the matrix of cells and the cell nucleus in more detail than under a microscope.
STAT5 plays an important role in the development of leukaemia and liver cancer. The JUNB gene is involved in the development of tumours in lymph gland tissue.
Lead researcher Lukas Kenner said: “The new program of course does not make pathologists redundant; however it is a supplementary method that considerably increases diagnostic certainty.”
Looking forward, the MUV researchers anticipate the technology could be used to aid the development of more detailed cancer cell categorisation.
According to Kenner,in the future it may be possible to create much more detailed cancer cell categories, giving clinicians a further tool with which to choose the correct and tailored therapy option.
“Cancer therapies are expensive. This new software will also help us to assess more effectively where expensive therapy is justified, but also which cases do not need it, thereby also sparing the patient,” Kenner said.