Source: TN

Michele Wilson PhD

Science Writer

 

Immuno-transcriptomics is a field of study focused on analyzing gene expression modifications (mRNA signatures) induced by the immune response to various triggers, such as the onset of cancer.

 

Through deep neural network and machine learning, Novigenix are generating mathematical models based on these mRNA signature analyses to predict the onset and progression of disease – in particular, colorectal cancer.

 

To find out more about immuno-transcriptomics and colorectal cancer screening, we spoke to Dr. Jan Groen, CEO of Novigenix.

 

Michele Wilson (MW): Can you tell us about the global availability of diagnostic tests for colorectal cancer?

 

Jan Groen (JG): The gold standard for colon cancer screening is colonoscopy, an invasive procedure that needs to be done every five years for individuals over the age of 55. The most widely used test is the stool-based FIT (Facel Immuno Chemical) test ($15-25/test), a relatively cheap home collection test that needs to be submitted to a lab. In the US, one of the upcoming new tests is the stool-based FDA approved Cologuard (~$500/test) from Exact Sciences.

 

In a study published in BMC Gastroenterology in 2014, it was clearly demonstrated that people prefer blood-based testing over stool-based testing. The only FDA approved blood-based test on the market is EpiProcolon from Epigenomics, a German company. Today the Cologuard test is one of the most sensitive and specific multiplex diagnostic tests on the market for colorectal cancer (CRC) detection. At Novigenix, we have developed and commercialized a CE marked, blood-based CRC test Colox, which outperforms the EpiProcolon blood test, FIT test and the Cologuard test for the detection of advanced adenomas.

 

MW: What would you like people to know about colorectal cancer screening?

 

JG: After lung cancer, CRC is the second deadliest cancer in the world, but at the same time it can be eradicated if people are screened for this disease. It is important for healthy individuals to be screened on a regular basis after the age of 55 years.

 

MW: Can you expand on the above definition of immuno-transcriptomics?

 

JG: Yes, the Immuno-transcriptomic platform is very well positioned for the early detection of colon cancer because it measures the host immune response against an early trigger within the human body.

Most other tests mainly rely on signals coming from the tumor (proteins or DNA) and therefore are quite often more tuned towards later stages of the disease. As stated before, early detection is key to cure patients.

 

MW: How can you be sure that certain changes in gene expression are induced by cancer?

 

JG: At Novigenix we have analyzed the gene expression profile from over 600 white blood cell samples from CRC patients (confirmed by colonoscopy) and aged matched healthy samples. Through bioinformatic analysis and machine learning we were able to develop a CRC specific algorithm to screening people for the presence and absence of CRC with a negative predictive value of 99.8%.

 

MW: Recently, Novigenix launched its first blood-based molecular diagnostic product, Colox ®, for the early detection of colon cancer. Can you tell us about its validation, launch, and what you have learnt since the launch?

 

JG: This test was validated in about 800 patients and initially launched as a LDT (laboratory developed test) on the Swiss self-pay market through licensing agreements with Unilabs Switzerland and Dr. Risch Laboratories. This test cost CHF 275. Today nearly 4,000 individuals have been tested. A post market study has shown an increase of 60% for the detection of advanced adenomas. The company is in the process of obtaining reimbursement for the test in Switzerland, scheduled for the second half of 2019.

 

MW: What sort of information is fed into the algorithm?

 

JG: Our technology platform is called BITseq™. It stands for Blood ImmunoTranscriptomics sequencing platform and provides actionable insights by analysing the gene expression modifications (mRNA signatures) induced by the host immune response to various triggers, such as the onset of cancer. Disease-specific predictive algorithms leverage machine learning and artificial intelligence to analyze mRNA signatures associated with clinical and medical parameters for early cancer detection and precision medicine.

 

MW: Colox® is based on the analysis of peripheral blood mononuclear cells (PBMCs). Can you explain why PBMCs are the sample of choice for this test?

 

JG: The host response is the first defence mechanism of the human body that gets alerted by an unknown trigger within the body. The cells responsible for the first line of defence are the white blood cells, including the peripheral blood mononuclear cells. The information exchange between the onset of a disease and the white blood cells is mainly taking place at the mRNA level. Being able to encode and read this information provides the earliest information possible to detect for example cancer. Most other diagnostic systems rely on the biological information coming from the tumor e.g. proteins, ctDNA and circulating tumor cells (CTC) released in the blood stream, which is quite often at a later-stage of the cancer.

 

MW: Who should get a Colox® test? How long does it take for a result to be generated, once a sample has been taken? What (if any) follow-up tests are required if a positive result is found?

 

JG: Colox is for healthy individuals above the age of 55 to be screened for the presence of colon cancer. Colon cancer is a slow growing cancer and when diagnosed based on clinical symptoms the survival rate is significantly lower compared to early diagnosis. The hands-on time in the lab is about 5-7 hours. In practice, from going to a doctor to collect the blood and receive the results is about 5-7 days. When a person is positive for Colox this patient needs to be followed-up with a colonoscopy.

 

MW: What role do you expect immuno-transcriptomics to play in the future of clinical diagnostics?

 

JG: Sequencing the immuno-transcriptome has enabled a paradigm shift away from looking at cell morphology under a microscope to define early cancer by its genetic drivers. The sequence data enables the doctor to diagnose the cancer earlier, but also whether the patients has an aggressive cancer and guides to those treatments that will be more effective for later-stage cancers.

 

In the near future, the cancer survival rate will increase and more cancers will be cured compared to the current standard of care through these disease algorithms, where we look at the immuno-transcriptomic sequence combined with machine learning and artificial intelligence.