Cancer: Building a Better Mousetrap

In this video, Jorge Soto of mirOculus gives a short presentation on building better tools for detecting cancer.
Soto: Almost a year ago, my aunt started suffering back pains. She went to a doctor and they told her that it was a normal injury for someone that has been playing tennis for almost thirty years. She went to do some therapy and she wasn’t feeling better. They did an X-ray and they discovered and injury in her lungs. And they said that they have a strain in their lung muscles and in the muscles in the ribs. They give her treatment and a few weeks later, her health was getting poorer and poorer. So they did a biopsy. Two weeks later, the results of the biopsy came and it said that he had stage 3 lung cancer. Her lifestyle was almost free of risk: she never smoked a cigarette, she never drinks alcohol, and she has been playing sports for almost half of her life. Perhaps that is why it took almost six months to a to get properly diagnosed with lung cancer.
We’re living in the twenty-first century and the majority of people still don’t have access to early cancer diagnostics. Even though we know that early cancer diagnostics is basically the closest thing we have to a silver bullet cure against cancer.
I want to imagine a near future where we don’t have to live in constant fear if we have some cancer that has gone undetected or where my loved ones do not have to wait for some symptoms to indicate that something’s wrong. Or a near future where cancer is treated very easily, because it is constantly diagnosed in the very early stages.
The previous panel talked about standing on the shoulders of these people that have been created these databases and putting it up for other people to use, and also ordinary people to get involved in biology. This team is actually a living example that when you combine the knowledge and naïveté of ordinary guys in extraordinarily different fields, you can create simple solutions that solve complex problems. And that is how, actually at BioCurious last year, we had our early test to develop a bioassay that dramatically lowers the cost of detecting cancer through the examination of microRNAs.
MicroRNAs are small RNA molecules that regulate gene expression post transcriptionally. Unlike the genome, which is mainly fixed for a given cell length, the transcriptome can vary depending on internal signals and also on environmental conditions. So a transcriptome can reflect which genes are actively expressed at any given time. That is why abnormal microRNA expressions create unique patterns for each specific type of cancer, making microRNAs a perfect mile marker.
So we thought that the knowledge was already there and we thought it was mainly an engineering problem and we’d try to crack it this way: First of all, a nurse draws the blood from a patient, approximately 8 milliliters. Then a lab technician extracts the total RNA of the blood sample and puts that blood sample in our 96-well plate. Each well has a specific biochemistry that we created that is looking for a specific microRNA, and whenever that microRNA is present, it will shine with blue light.
Then we can see all the wells that shine represent a pattern of the microRNAs that are present in the bloodstream of the patient and then we compare that sample or that pattern with the patterns of microRNAs in specific types of cancer.
The biochemistry that we created works in every lab machinery that already exists. However, we took a step further and we decided to design and 3D print a machine, a super cheap device that uses an Arduino to run the chemical reaction and a smartphone to document the reaction and process everything in the cloud, finding new patterns, new correlations, identifying which cancer the patient has, in case it has it, which stage, and the aggressiveness of the tumor, as well as other contextual information.
We’re using, basically, state-of-the-art molecular biology. We’re using open hardware. We’re using smartphones and 3D printing to try to tackle one of humanity’s toughest challenges.
The results so far have been very successful and promising. We are at very early stages, but we have been able to test our method with hepatic cancer and gastric cancer. And currently we’re deploying tests with breast cancer. We will continue doing that with colon cancer and with lung cancer.
So we want to create by the end of this year, to have a test ready that includes five different types of cancer that with one single test, in an inaccurate way, in a fast way, in a non-expensive way, you can check for different types of cancer.
Today cancer treatment and diagnostics happen mainly when symptoms appear, that is stage 3 or stage 4. We believe that is too late. It’s too expensive for the countries, it’s too expensive for humanity, it’s too expensive for the families. Cancer not only costs us billions of dollars, it also costs us the people we love.
Unfortunately, I think everybody in this room has a close story around this malady. However, I’m very positive that in the very near future, because of this and all the breakthroughs that we’re hearing tonight and today, the concepts that we see as life and death will change forever.
As they say, these are all ideas whose time has come. Thank you very much.