PNAS - Lunaphore Technologies
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Clinical Data


PAPER REVIEW: “Microfluidic processor allows rapid HER2 immunohistochemistry of breast carcinomas and significantly reduces ambiguous (2+) read-outs.” PNAS.

What does that mean?

Tissues extracted from the body of a cancer patient are analyzed in order to assess the stage of the tumor, its origin or any other features required to reach a diagnosis.

The most widely used cancer biomarker test in tissues is called immunohistochemistry (IHC). With this technique, a marker such as HER2 used on breast cancer samples, is tested and results will show how much this protein is overexpressed, serving as an indicator of the type of cancer it is. The pathologist obtains the results by looking at the stained sample under the microscope and he will classify what he sees under 3 different categories: A result of 0 or 1+ means the over-expression of HER2 is considered negative. 2+ results will be classified as ambiguous and 3+ will be considered positive. Ambiguous cases will require further genetic testing, which will take several additional days and will be more costly than a standard IHC test.

What does these data suggest?

We have performed a test with 76 samples of breast cancer patients, comparing the results of standard automation equipment in hospitals to our technology. Pathologists have been blindly assessing the scores of the different samples and the results show a 90% decrease in the total number of ambiguous results using Lunaphore’s technology. In addition, the 3 remaining ambiguous cases matched the results of the genetic testing.

What is the impact of such results on patients?

Targeted therapies are often used to treat cancer patients. A biomarker like HER2, if over-expressed on a sample (3+), indicates that the patient will benefit from a targeted treatment. On the other side, a negative result (0, 1+) means the patient cannot benefit from this treatment. Therefore, classifying ambiguous results correctly is crucial to avoid false positives or false negatives, given that if a patient’s sample was wrongly diagnosed as HER2 positive, then the patient may get the side effects of the treatment but not its benefits.

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