A scientist works on a blood test in the Ajay Goel Lab, one of many labs that are developing blood tests to screen for different types of cancer.
Soon it may be possible to find different types of cancer earlier than ever through a simple blood test.
Among the many blood tests in development, researchers announced in July that they have developed one that may screen for early-onset colorectal cancer. The new potential screening tool, detailed in a study in the journal Gastroenterology, represents a major step in noninvasively and inexpensively detecting nonhereditary colorectal cancer at an earlier and more treatable stage.
In recent years, this type of cancer has been on the upswing in adults under age 50 and in those without a family history. In 2021, the American Cancer Society's revised guidelines began recommending that colorectal cancer screenings with colonoscopy begin at age 45. But that still wouldn’t catch many early-onset cases among people in their 20s and 30s, says Ajay Goel, professor and chair of molecular diagnostics and experimental therapeutics at City of Hope, a Los Angeles-based nonprofit cancer research and treatment center that developed the new blood test.
“These people will mostly be missed because they will never be screened for it,” Goel says. Overall, colorectal cancer is the fourth most common malignancy, according to the U.S. Centers for Disease Control and Prevention.
Goel is far from the only one working on this. Dozens of companies are in the process of developing blood tests to screen for different types of malignancies.
Some estimates indicate that between one-fourth and one-third of all newly diagnosed colorectal cancers are early-onset. These patients generally present with more aggressive and advanced disease at diagnosis compared to late-onset colorectal cancer detected in people 50 years or older.
To develop his test, Goel examined publicly available datasets and figured out that changes in novel microRNAs, or miRNAs, which regulate the expression of genes, occurred in people with early-onset colorectal cancer. He confirmed these biomarkers by looking for them in the blood of 149 patients who had the early-onset form of the disease. In particular, Goel and his team of researchers were able to pick out four miRNAs that serve as a telltale sign of this cancer when they’re found in combination with each other.
The blood test is being validated by following another group of patients with early-onset colorectal cancer. “We have filed for intellectual property on this invention and are currently seeking biotech/pharma partners to license and commercialize this invention,” Goel says.
He’s far from the only one working on this. Dozens of companies are in the process of developing blood tests to screen for different types of malignancies, says Timothy Rebbeck, a professor of cancer prevention at the Harvard T.H. Chan School of Public Health and the Dana-Farber Cancer Institute. But, he adds, “It’s still very early, and the technology still needs a lot of work before it will revolutionize early detection.”
The accuracy of the early detection blood tests for cancer isn’t yet where researchers would like it to be. To use these tests widely in people without cancer, a very high degree of precision is needed, says David VanderWeele, interim director of the OncoSET Molecular Tumor Board at Northwestern University’s Lurie Cancer Center in Chicago.
Otherwise, “you’re going to cause a lot of anxiety unnecessarily if people have false-positive tests,” VanderWeele says. So far, “these tests are better at finding cancer when there’s a higher burden of cancer present,” although the goal is to detect cancer at the earliest stages. Even so, “we are making progress,” he adds.
While early detection is known to improve outcomes, most cancers are detected too late, often after they metastasize and people develop symptoms. Only five cancer types have recommended standard screenings, none of which involve blood tests—breast, cervical, colorectal, lung (smokers considered at risk) and prostate cancers, says Trish Rowland, vice president of corporate communications at GRAIL, a biotechnology company in Menlo Park, Calif., which developed a multi-cancer early detection blood test.
These recommended screenings check for individual cancers rather than looking for any form of cancer someone may have. The devil lies in the fact that cancers without widespread screening recommendations represent the vast majority of cancer diagnoses and most cancer deaths.
GRAIL’s Galleri multi-cancer early detection test is designed to find more cancers at earlier stages by analyzing DNA shed into the bloodstream by cells—with as few false positives as possible, she says. The test is currently available by prescription only for those with an elevated risk of cancer. Consumers can request it from their healthcare or telemedicine provider. “Galleri can detect a shared cancer signal across more than 50 types of cancers through a simple blood draw,” Rowland says, adding that it can be integrated into annual health checks and routine blood work.
Cancer patients—even those with early and curable disease—often have tumor cells circulating in their blood. “These tumor cells act as a biomarker and can be used for cancer detection and diagnosis,” says Andrew Wang, a radiation oncologist and professor at the University of Texas Southwestern Medical Center in Dallas. “Our research goal is to be able to detect these tumor cells to help with cancer management.” Collaborating with Seungpyo Hong, the Milton J. Henrichs Chair and Professor at the University of Wisconsin-Madison School of Pharmacy, “we have developed a highly sensitive assay to capture these circulating tumor cells.”
Even if the quality of a blood test is superior, finding cancer early doesn’t always mean it’s absolutely best to treat it. For example, prostate cancer treatment’s potential side effects—the inability to control urine or have sex—may be worse than living with a slow-growing tumor that is unlikely to be fatal. “[The test] needs to tell me, am I going to die of that cancer? And, if I intervene, will I live longer?” says John Marshall, chief of hematology and oncology at Medstar Georgetown University Hospital in Washington, D.C.
Ajay Goel Lab
A blood test developed at the University of Texas MD Anderson Cancer Center in Houston helps predict who may benefit from lung cancer screening when it is combined with a risk model based on an individual’s smoking history, according to a study published in January in the Journal of Clinical Oncology. The personalized lung cancer risk assessment was more sensitive and specific than the 2021 and 2013 U.S. Preventive Services Task Force criteria.
The study involved participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial with a minimum of a 10 pack-year smoking history, meaning they smoked 20 cigarettes per day for ten years. If implemented, the blood test plus model would have found 9.2 percent more lung cancer cases for screening and decreased referral to screening among non-cases by 13.7 percent compared to the 2021 task force criteria, according to Oncology Times.
The conventional type of screening for lung cancer is an annual low-dose CT scan, but only a small percentage of people who are eligible will actually get these scans, says Sam Hanash, professor of clinical cancer prevention and director of MD Anderson’s Center for Global Cancer Early Detection. Such screening is not readily available in most countries.
In methodically searching for blood-based biomarkers for lung cancer screening, MD Anderson researchers developed a simple test consisting of four proteins. These proteins circulating in the blood were at high levels in individuals who had lung cancer or later developed it, Hanash says.
“The interest in blood tests for cancer early detection has skyrocketed in the past few years,” he notes, “due in part to advances in technology and a better understanding of cancer causation, cancer drivers and molecular changes that occur with cancer development.”
However, at the present time, none of the blood tests being considered eliminate the need for screening of eligible subjects using established methods, such as colonoscopy for colorectal cancer. Yet, Hanash says, “they have the potential to complement these modalities.”
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.”
