Bioluminescence is a phenomenon allowing certain animals, fungi and fish to glow through a chemical reaction that releases energy in the form of light. It’s characteristically deep-sea, and is probably one of the most beautiful—or frightening—experiences you’ll have on YouTube. It’s even attracted the eyes of many natural scientists, technology and medical researchers for myriad projects, from nascent ideas like glowing trees that can be used for alternative street lamps to the dream of biopixels.
But it’s in the field of cancer research and detection that bioluminescence may shine brightest. In vivo imaging is an emerging technology used by researchers to track cells and viruses in small animals. Using the green florescent protein (GFP) coded in crystal jellyfish (Aequorea victoria) to ‘tag’ and highlight protein movement in small animals, in vivo imaging is incredibly suited to many modes of research, and is especially fruitful to cancer researchers who are using small animals like rats in their experiments.
I decided to call up Dr. Nathalie Scholler, an ovarian cancer researcher at University of Pennsylvania, for key insights into how in vivo imaging is helping track ovarian cancer, the number one killer among middle-aged women.
MOTHERBOARD: Hi, Dr. Scholler. So, what kind of research are you doing?
Scholler: I’m specialized in ovarian cancer. We are using in vivo model systems to develop new treatments and new imaging modality.
How is in vivo treatment different form other approaches?
We have a problem in ovarian cancer that the regular animal models that are used do not spontaneously develop ovarian cancer. Specifically, mice never develop ovarian cancer. So that is the clear problem—to mobilize this disease in animal models.
And the animal models you are using? What are you doing with them?
Animal models are supposed to be pre-clinical. That is, to see what kind of treatments will work in humans by working as closely as possible to the human model by testing in an animal model. There are several problems with testing cancer in animal models. Take for example lung cancer. If you expose a mouse to cigarette smoke, eventually it will develop lung cancer. The risk factors for ovarian cancer, however, are not understood and mice do not develop ovarian cancer spontaneously. We have been immobilized with that question for a while.
Progressively better models have been developed, first by implanting tumor cell lines subcutaneously. The tumors growing directly under the skin can be measured with calipers, which makes it pretty easy to follow the development. But it is obviously not physiological. Where the tumor develops is critical. So we have developed novel models where we implant the tumor cells inside the ovaries of the mice. When you do that, you better mimic the human disease. But you can no longer track the tumor development because the tumors grow deep inside the peritoneal area, and thus cannot be touched or seen. You can do sonography, but sonography on animals as small as mice is not especially easy.
We have developed a better way by labeling the tumor cells implanted in the ovaries with florescent dye. This allows us to follow the development of the tumors by using in vivo imagers without harming the mice. When experimental treatments are working, you can also follow the tumor regression by in vivo imaging.
How new is this method?
It was published in 2010. It was not created out of the blue. It was created on knowledge that was already in cycle, but my lab specialized it for ovarian cancer. For ovarian cancer it’s relatively new.
For mice, do you need a specific type of imaging? A what other kinds of cancer research is this method used for. Is this versatile
It’s versatile, yes. All solid tumors in the deep organs can benefit from this method. One can also use the method of bioluminscent or bioflorescent cells to follow the biodistribution in specific types of cells. So it’s versatile.
In vivo imaging of adipose tissue
How did you adapt it specifically to the mouse and ovarian cancer?
We used ovarian cancer cells, the DNA that encode for these markers, and that was not done before to our knowledge. So we used those cells to implant human ovaries with it, which was not done before. The risk was that based on the properties with ovarian cancer would change once introduced to the markers. But no, for once, everything worked as expected. We noticed after a few weeks of growth the signal tended to diminish so it’s not optimal for long-term following of the tumors. But for a few weeks it's okay.
Why didn’t the signal last?
Well, the thing is that tumor cells tend to be unstable genetically. They tend to mutate fast and they might just get rid of the gene signal, because that’s what tumor cells do. So as long as they are still looking like they were when you injected them they do track the gene, but after many rounds of multiplication they change properties and the signalling is not as good. But to be sure that the signal would stay as good as the first day the signal would have to linked to the survival of the tumor cell. So if the tumor cells needed that fluorescent die to survive they would keep it forever. But they don’t need it, so they get rid of it after a while.
During short-term following, what kinds of things can you glean with in vivo imaging? Are there some limitations for long-term use?
Well, at this point in time you’re dealing with several levels of problems with cancer. During short-term following you can efficiently monitor immediate responses to therapeutics. Long-term following, rather, addresses tumor relapse. In humans the prevention of tumor relapse is critical and spans over years, sometimes decades.
But mice live only two or three years, so it is challenging to set up preclinical models that mimic long-term disease evolution and relapses over a long period of time, and in which cell-fluorescent labeling is maintained through tumor evolution and metastasis. So we rather test the immediate responses to treatment. The type of models we are using are fine for short-term applications where you obtain a response in typically less then 30 days.
I would even say that short term experiments are ethically more sound. Keep in mind that these mice are caged all their life, and that we modify their physiology, implant cancer in them, and give them treatments I’m sure are not pleasant. Do we need to elongate their misery? Personally I’m fine with short experimental set up that give quick answers.
Right. So what is done to the mice after the imaging?
There are very strong ethical committees that trace very carefully what happens to the mice and every experiment is tightly regulated. if a mice is part of an experiment even just as a control, at the end of the experiment, they all go. They are not maintained in the animal facilities, and it's very costly also just to maintain the animal life in the facility. So they are bred for the experiment. They enter the experiment when they are about 6 – 12 weeks. Rarely 12 weeks. And after that everybody goes. So long-term maintenance of the florescent dye in some tumors is not really needed. We know where the limits of the system are.
Since the mice live such shorter lives, do you have regression models that will permit you to translate your results in mice to those of a human?
Well thats a good question. Actually, no, we are still struggling with those concepts. The fact of the matter is that ovarian cancer is a disease of aging women, but we don’t use aging mice to test it. We know that our old models are flawed, but at this point in time we do the best we can with the tools we have. Interestingly enough, we know now that chickens actually develop ovarian cancer spontaneously.
Yes after two years of intensive laying, an effect of the incredible cruelty of the farm industry, accelerated growth of chickens triggers ovarian cancer in the chicken. It’s horrifying. It would be a better animal model to use; it would help everybody, but the tools are not ready. So we know that we are flawed, the science is flawed and there are plenty of modalities for growth.
Right. But observing with the in vivo imaging makes the disease much more transparent.
Yes, it;s helping a lot. It minimizes the amount of mice used in the experiments, because you don’t need to cut them open to see what’s inside. You can follow them and all the cohorts over several weeks and look at the development of the tumors at the regular pace, whereas previously we had to have very large cohorts to look at the disease at different time points.And the only way to do so was to cut open the mice. It’s not all the answers, but its an improvement.
So would you describe your specialty as prevention medicine?
No, it's more basic than that--prevention medicine is already knowing what you’re looking for, whereas in ovarian cancer research we don’t konw what we are looking for. We don’t know how to prevent it because we did not understand the coding of ovarian cancer. In short, we cannot prevent it.
So I'm trying to understand the coding of ovarian cancer and if one day I can, then prevention will be possible. But you cannot prevent something you can’t understand.
You're tracking the behavior of ovarian cancer.
Yes. It seems that in ovarian cancer the most important factor is the permissive environment. That means that somehow the body, at some point, gave up and stopped fighting the disease and the disease exploded. And that’s what I really want to understand: Why did the body allow the virus to grow?
Don’t all viruses effectively trick the cell into replicating its own DNA with phage? Does this have anything to do wtih ovarian cancer?
Yes, thats right. That has to do with cervical cancer, which is attached to some strains to herpes. And it’s exactly what happens.
But because it's a virus, it's not hidden. While the virus triggers cell multiplicaton at the same time it puts some very serious antigens at the cell surface, which makes it possible for the immune system to spot it and kill it, which is why vaccination is working. That's the best case scenario becuase you can mount an immune response that is very efficient against the cancer early on. So all the cancers that are derived from herpes viruses are totally within our reach, now, using those anti herpes vaccinations.
Your generation was the first generation to take advantage of this. It's a very large part of cancer worldwide--for example, throat cancer and cervical cancer. Those are almost fully preventable. Unfortnately for Ovarian cancer we did not find any virus that triggers the transformation. It does not seem to be exogenic.
h5. An orthotopic model of serous ovarian cancer in immunocompetent mice for in vivo tumor imaging and monitoring of tumor immune responses (Connolly / Nunez-Cruz / Scholler, 2010)
Does that mean it's invisible to the body?
No, it’s actually worse than that. Not only is it not rejected by the immune system, it’s actually encouraged to grow. It's very subversive. It’s an abnormal animal cell that for some reason found a way to talk to the environment and say, 'Please feed me, let me grow,' and for some reason the body will work against it's own interest and help it grow. It's true perversion.
What other kinds of cancer does that? What kinds will the body specifically help to grow?
The most violent ones are like pancreatic cancer. Those are the ones that are killing the fastest. Really, it's the body that is self destructing.
So you know that in vivo will help you better understand where the cancer will proliferate?
No. Ovarian cancer is contained in the lower abdomen, and thats it. Its enough to kill you--it doesnt need to spread.
Okay, so what does invivo imaging do for you?
You will see the tumor developing early on. In fact you will see the tumor, which is already helpful. For ovarian cancer, the spreading is not an issue. In breast cancer it would be more interesting. But for us, essentially we need to see the tumor very deep inside the organs and how it interacts with the environment.
So what kind of gives you a huge terrain to test for ways that cancer cells interact with the environment? Do you work on a specific timeline, or have a checklist that you are aiming towards?
When I set up an experiment? Or in genreal?
I guess in general. How far along do you think you have to go to track cancer until you know it's behavior?
You want me to predict how long it will take to cure cancer?
No. Just ovarian cancer
I might get lucky. Might happen tomorrow.