A retrovirus illustration.
Even with groundbreaking advances in cancer treatment and research over the past two centuries, the problem remains that some cancer does not respond to treatment. A subset of patients experience recurrence or metastasis, even when the original tumor is detected at an early stage.
"Why do some tumors evolve into metastatic disease that is then capable of spreading, while other tumors do not?"
Moreover, doctors are not able to tell in advance which patients will respond to treatment and which will not. This means that many patients endure conventional cancer therapies, like countless rounds of chemo and radiation, that do not ultimately increase their likelihood of survival.
Researchers are beginning to understand why some tumors respond to treatment and others do not. The answer appears to lie in the strange connection between human life at its earliest stages — and retroviruses. A retrovirus is different than a regular virus in that its RNA is reverse-transcribed into DNA, which makes it possible for its genetic material to be integrated into a host's genome, and passed on to subsequent generations.
Researchers have shown that reactivation of retroviral sequences is associated with the survival of developing embryos. Certain retroviral sequences must be expressed around the 8-cell stage for successful embryonic development. Active expression of retroviral sequences is required for proper functioning of human embryonic stem cells. These sequences must then shut down at the later state, or the embryo will fail to develop. And here's where things get really interesting: If specific stem cell-associated retroviral sequences become activated again later in life, they seem to play a role in some cancers becoming lethal.
"Eight to 10 million years ago, at the time when we became primates, the population was infected with a virus."
While some retroviral sequences in our genome contribute to the restriction of viral infection and appear to have contributed to the development of the placenta, they can also, if expressed at the wrong time, drive the development of cancer stem cells. Described as the "beating hearts" of treatment-resistant tumors, cancer stem cells are robust and long-living, and they can maintain the ability to proliferate indefinitely.
This apparent connection has inspired Gennadi V. Glinsky, a research scientist at the Institute of Engineering in Medicine at UC San Diego, to find better ways to diagnose and treat metastatic cancer. Glinsky specializes in the development of new technologies, methods, and system integration approaches for personalized genomics-guided prevention and precision therapy of cancer and other common human disorders. We spoke with him about his work and the exciting possibilities it may open up for cancer patients. This interview has been edited and condensed for clarity.
What key questions have driven your research in this area?
I was thinking for years that the major mysteries are: Why do some tumors evolve into metastatic disease that is then capable of spreading, while other tumors do not? What explains some cancer cells' ability to get into the blood or lymph nodes and be able to survive in this very foreign, hostile environment of circulatory channels, and then be able to escape and take root elsewhere in the body?
"If you detect conventional cancer early, and treat it early, it will be cured. But with cancer involving stem cells, even if you diagnose it early, it will come back."
When we were able to do genomic analysis on enough early stage cancers, we arrived at an alternative concept of cancer that starts in the stem cells. Stem cells exist throughout our bodies, so in the case of cancer starting in stem cells you will have metastatic properties … because that's what stem cells do. They can travel throughout the body, they can make any other type of cell or resemble them.
So there are basically two types of cancer: conventional non-stem cell cancer and stem cell-like cancer. If you detect conventional cancer early, and treat it early, it will be cured. But with cancer involving stem cells, even if you diagnose it early, it will come back.
What causes some cancer to originate in stem cells?
Cancer stem cells possess stemness [or the ability to self-renew, differentiate, and survive chemical and physical insults]. Stemness is driven by the reactivation of retroviral sequences that have been integrated into the human genome.
Tell me about these retroviral sequences.
Eight to 10 million years ago, at the time when we became primates, the population was infected with a virus. Part of the population survived and the virus was integrated into our primate ancestors' genome. These are known as human endogenous retroviruses, or HERVs. The DNA of the host cells became carriers of these retroviral sequences, and whenever the host cells multiply, they carry the sequences in them and pass them on to future generations.
This pattern of infection and integration of retroviral sequences has happened thousands of times during our evolutionary history. As a result, eight percent of the human genome is derived from these different retroviral sequences.
We've found that some HERVs are expressed in some cancers. For example, 10-15 percent of prostate cancer is stem cell-like. But at first it was not understood what this HERV expression meant.
Gennadi V. Glinsky, a research scientist at the Institute of Engineering in Medicine at UC San Diego.
(Courtesy)
How have you endeavored to solve this in your lab?
We were trying to track down metastatic prostate cancer. We found a molecular signature of prostate cancer that made the prostate tumors look like stem cells. And those were the ones likely to fail cancer therapy. Then we applied this signature to other types of cancers and we found that uniformly, tumors that exhibit stemness fail therapy.
Then in 2014, several breakthrough papers came out that linked the activation of the retroviral sequences in human embryonic stem cells and in human embryo development. When I read these papers, it occurred to me that if these retroviral sequences are required for pluripotency in human embryonic stem cells, they must be involved in stem cell-resembling human cancer that's likely to fail therapy.
What was one of the biggest aha moments in your cancer research?
Several major labs around the U.S. took advantage of The Cancer Genome Anatomy Project, which made it possible to have access to about 12,000 individual human tumors across a spectrum of 30 or so cancer types. This is the largest set of tumors that's ever been made available in a comprehensive and state of the art way. So we now know all there is to know about the genetics of these tumors, including the long-term clinical outcome.
"When we cross-referenced these 10,713 human cancer survival genes to see how many are part of the retroviral network in human cells, we found that the answer was 97 percent!"
These labs identified 10,713 human genes that were associated with the likelihood of patients surviving or dying after [cancer] treatment. I call them the human cancer survival genes, and there are two classes of them: one whose high expression in tumors correlates with an increased likelihood of survival and one whose high expression in tumors correlates with a decreased likelihood of survival.
When we cross-referenced these 10,713 human cancer survival genes to see how many are part of the retroviral network in human cells, we found that the answer was 97 percent!
How will all of this new knowledge change how cancer is treated?
To make cancer stem cells vulnerable to treatment, you need to interfere with stemness and the stemness network. And to do this, you would need to identify the retroviral component of the network, and interfere with this component therapeutically.
The real breakthrough will come when we start to treat these early stage stem cell-like cancers with stem cell-targeting therapy that we are trying to develop. And with our ability to detect the retroviral genome activation, we will be able to detect stem cell-like cancer very early on.
How far away are we from being able to apply this information clinically?
We have two molecule [treatment] candidates. We know that they efficiently interfere with the stemness program in the cells. The road to clinical trials is typically a long one, but since we're clear about our targets, it's a shorter road. We would like to say it's two to three years until we can start a human trial.
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”
