The palm-sized device could one day be engineered to track down explosives and gas leaks or could even be used by medical laboratories to detect disease
Here’s a technology breakthrough with many implications for diagnostics and clinical laboratory testing. Researchers at the at the University of Washington (UW) are pushing the envelope on what can be achieved by combining technology with biology. They developed “Smellicopter,” a flying drone that uses a living moth antenna to hunt for odors.
According to their published study, the UW scientists believe an odor-guided drone could “reduce human hazard and drastically improve performance on tasks such as locating disaster survivors, hazardous gas leaks, incipient fires or explosives.”
“Nature really blows our human-made odor sensors out of the water,” lead author Melanie Anderson, a UW doctoral student in mechanical engineering, told UW News. “By using an actual moth antenna with Smellicopter, we’re able to get the best of both worlds: the sensitivity of a biological organism on a robotic platform where we can control its motion.”
The researchers believe their Smellicopter is the first odor-sensing flying biohybrid robot system to incorporate a live moth antenna that capitalizes on the insect’s excellent odor-detecting and odor-locating abilities.
In their paper, titled, “A Bio-Hybrid Odor-Guided Autonomous Palm-Sized Air Vehicle,” published in the IOPscience journal Bioinspiration and Biomimetics, the researchers wrote, “Biohybrid systems integrate living materials with synthetic devices, exploiting their respective advantages to solve challenging engineering problems. … Our robot is the first flying biohybrid system to successfully perform odor localization in a confined space, and it is able to do so while detecting and avoiding obstacles in its flight path. We show that insect antennae respond more quickly than metal oxide gas sensors, enabling odor localization at an improved speed over previous flying robots. By using the insect antennae, we anticipate a feasible path toward improved chemical specificity and sensitivity by leveraging recent advances in gene editing.”
How Does it Work?
In nature, a moth uses its antennae to sense chemicals in its environment and navigate toward sources of food or a potential mate.
“Cells in a moth antenna amplify chemical signals,” said study co-author Thomas Daniel, PhD, UW Professor of Biology, in UW News. “The moths do it really efficiently—one scent molecule can trigger lots of cellular responses, and that’s the trick. This process is super-efficient, specific, and fast.”
To keep the moth antennae “alive,” scientists place Manduca sexta hawk moths (above) in a refrigerator to anesthetize them before removing their antennae. Once separated from the live moth, the antenna stays “biologically and chemically active” for up to four hours. Refrigerating the antennas further extends that time span, researchers explained in the UW News article. (Photo copyright: University of Washington.)
Because the moth antenna is hollow, researchers are able to add wires into the ends of the antenna. By connecting the antenna to an electrical circuit, they can measure the average signal from all of the cells in the antenna. When compared to a metal oxide gas sensor, the antenna-powered sensor responded more quickly to a floral scent. It also took less time to recover between tracking puffs of scent.
Anderson compared the antenna-drone circuitry to a human heart monitor.
“A lot like a heart monitor, which measures the electrical voltage that is produced by the heart when it beats, we measure the electrical signal produced by the antenna when it smells odor,” Anderson told WIRED. “And very similarly, the antenna will produce these spike-shaped pulses in response to patches of odor.”
Making a Drone Hunt Like a Moth
Anderson told WIRED her team programmed the drone to hunt for odors using the same technique moths employ to stay targeted on an odor, called crosswind casting.
“If the wind shifts, or you fly a little bit off-course, then you’ll lose the odor,” Anderson said. “And so, you cast crosswind to try and pick back up that trail. And in that way, the Smellicopter gets closer and closer to the odor source.”
However, the researchers had to figure out how to keep the commercially available $195 Crazyflie drone facing upwind. The fix, co-author and co-advisor Sawyer Fuller, PhD, UW Assistant Professor of Mechanical Engineering told UW News, was to add two plastic fins to create drag and keep the vehicle on course.
“From a robotics perspective, this is genius,” Fuller said. “The classic approach in robotics is to add more sensors, and maybe build a fancy algorithm or use machine learning to estimate wind direction. It turns out, all you need is to add a fin.”
A live moth antenna is attached to wires in an arc sharp on the “Smellicopter” drone (above), developed at the University of Washington in Seattle. The autonomous drone uses the moth antenna to navigate toward smells. By connecting the antenna to a circuit board, the UW researchers were able to study the drone’s response to a puff of floral scent. The Smellicopter tracking skills proved superior to that of a human-made sensor. (Photo copyright: University of Washington.)
Other Applications for Odor Detecting Robots
While any practical clinical application of this breakthrough is years away, the scientific team’s next step is to use gene editing to engineer moths with antennae sensitive to a specific desired chemical, such as those found in explosives.
“I think it is a powerful concept,” roboticist Antonio Loquercio, a PhD candidate in machine learning at the University of Zurich who researches drone navigation, told WIRED. “Nature provides us plenty of examples of living organisms whose life depends on this capacity. This could have as well a strong impact on autonomous machines—not only drones—that could use odors to find, for example, survivors in the aftermath of an earthquake or could identify gas leaks in a man-made environment.”
Could a palm-sized autonomous device one day be used to not only track down explosives and gas leaks but also to detect disease?
As clinical pathologists and medical laboratory scientists know, dogs have demonstrated keen ability to detect disease using their heightened sense of smell.
Therefore, it is not inconceivable that smell-seeking technology might one day be part of clinical laboratory testing for certain diseases.
This latest research is another example of how breakthroughs in unrelated fields of science offer the potential for creation of diagnostic tools that one day may be useful to medical laboratories.
The researchers also found that certain molecules, when added to cancer drugs, can prevent chromosome shattering from occurring in a discovery that may be useful to pathologists and oncologists
Anatomic pathologists who diagnose tissue and closely monitor advances in cancer diagnostics and therapy will be interested in a recent study into how a mutational process known as chromothripsis (chromosome shattering) can promote cancer cell growth in humans and increase resistance to cancer drug therapies.
The study, which was published in the journal Nature, titled, “Chromothripsis Drives the Evolution of Gene Amplification in Cancer,” provides insights into how cancer cells can adapt to different environments and also may suggest potential solutions to drug resistance among cancer patients.
Led by researchers from the University of California San Diego School of Medicine and the UC San Diego branch of the Ludwig Institute for Cancer Research, the discovery could open up a new field in cancer diagnostic testing, where the pathology laboratory analyzes a cancer patient’s tumor cells to determine where chromosomal damage exists. This knowledge could then inform efforts to repair damaged chromosomes or to identify which therapeutic drugs would be most effective in treating the patient, a key element of precision medicine.
“Drug resistance is the most problematic part of cancer therapy. If not for drug resistance, many cancer patients would survive,” said Ofer Shoshani, PhD (above right) postdoctoral fellow at the Cleveland Lab at UC San Diego School of Medicine and the study’s first author, in a news release. He’s shown with Don Cleveland, PhD (above left), head of the Cleveland Laboratory of Cell Biology at the Ludwig Institute for Cancer Research, another author of the study. Cleveland is also Chair of the Department of Cellular and Molecular Medicine, and Distinguished Professor of Cellular and Molecular Medicine, Medicine, and Neurosciences at UC San Diego School of Medicine. (Photo copyright: Ludwig Institute for Cancer Research.)
Shattered Chromosomes
Chromosomes that undergo chromothripsis shatter or fragment into several pieces and then are stitched back together by a DNA repair processes. However, not all of the fragments make it back into the repaired chromosome, and this can be a problem.
“During chromothripsis, a chromosome in a cell is shattered into many pieces, hundreds in some cases, followed by reassembly in a shuffled order,” Shoshani told Genetic Engineering and Biotechnology News (GEN News). “Some pieces get lost while others persist as extra-chromosomal DNA (ecDNA). Some of these ecDNA elements promote cancer cell growth and form minute-sized chromosomes called double minutes.”
Studies have shown that up to half of all cancer cells contain cancer-promoting ecDNA chromosome fragments.
Some Cancer Drugs Could be Fueling Drug Resistance
To perform their study, the UC San Diego/Ludwig scientists sequenced entire genomes of cancer cells that had developed drug resistance. Their research revealed that chromothripsis prompts and drives the formation of ecDNA and that the process can also be induced by some chemotherapeutic drugs. The researchers also discovered that the particular type of damage these drugs may cause can provide an opening for ecDNA to reintegrate back into chromosomes.
“We show that when we break a chromosome, these ecDNAs have a tendency to jump into the break and seal them, serving almost like a DNA glue,” Shoshani said in the news release. “Thus, some of the very drugs used to treat cancers might also be driving drug resistance by generating double-stranded DNA breaks.”
Preventing DNA Shattering and Reducing Drug Resistance
The scientists also discovered that ecDNA formation could be halted by pairing certain cancer drugs with molecules that prevent DNA shattering from occurring in the first place, thus reducing drug resistance.
“This means that an approach in which we combine DNA repair inhibitors with drugs such as methotrexate or vemurafenib could potentially prevent the initiation of drug resistance in cancer patients and improve clinical outcomes,” Shoshani said.
“Our identifications of repetitive DNA shattering as a driver of anticancer drug resistance and of DNA repair pathways necessary for reassembling the shattered chromosomal pieces has enabled rational design of combination drug therapies to prevent development of drug resistance in cancer patients, thereby improving their outcome,” Don Cleveland, PhD, Head of the Cleveland Laboratory of Cell Biology at the Ludwig Institute for Cancer Research and one of the authors of the paper, told GEN News.
This research from the University of California San Diego School of Medicine and the UC San Diego branch of the Ludwig Institute for Cancer Research is the latest example of how scientists have gained useful insights into how human genomes operate. More research and clinical studies are needed to solidify the advantages of this study, but the preliminary results are promising and could lead to new cancer diagnostics and therapies.
Researchers find declining antibody levels in SARS-CoV-2 patients are offset by T cells and B cells that remain behind to fight off reinfection
Questions remain regarding how long antibodies produced by a COVID-19 vaccine or natural infection will provide ongoing protection against SARS-CoV-2. However, a new study showing COVID-19 immunity may be “robust” and “long lasting” may signal important news for clinical laboratories and in vitro diagnostics companies developing serological tests for the coronavirus disease.
The LJI research team analyzed blood samples from 188 COVID-19 patients, 7% of whom had been hospitalized. They measured not only virus-specific antibodies in the blood stream, but also memory B cell infections, T helper cells, and cytotoxic (killer) T cells.
While antibodies eventually disappear from the blood stream, T cells and B cells appear to remain to fight future reinfection.
“As far as we know, this is the largest study ever for any acute infection that has measured all four of those components of immune memory,” Crotty said in a La Jolla Institute news release.
The LJI researchers found that virus-specific antibodies remained in the blood stream months after infection while spike-specific memory B cells—which could trigger an accelerated and robust antibody-mediated immune response in the event of reinfection—actually increased in the body after six months. In addition, COVID-19 survivors had an army of T cells ready to halt reinfection.
“Our data show immune memory in at least three immunological compartments was measurable in ~95% of subjects five to eight months post symptom onset, indicating that durable immunity against secondary COVID-19 disease is a possibility in most individuals,” the study concludes. The small percentage of the population found not to have long-lasting immunity following COVID-19 infection could be vaccinated in an effort to stop reinfection from occurring on the way to achieving herd immunity, the LJI researchers maintained.
Do COVID-19 Vaccines Create Equal Immunity Against Reinfection?
Whether COVID-19 vaccinations will provide the same immune response as an active infection has yet to be determined, but indications are protection may be equally strong.
“It is possible that immune memory will be similarly long lasting similar following vaccination, but we will have to wait until the data come in to be able to tell for sure,”
LJI Research Professor Daniela Weiskopf, PhD, said in the LJI statement. “Several months ago, our studies showed that natural infection induced a strong response, and this study now shows that the response lasts. The vaccine studies are at the initial stages, and so far, have been associated with strong protection. We are hopeful that a similar pattern of responses lasting over time will also emerge for the vaccine-induced responses.”
The study’s authors cautioned that people previously diagnosed with COVID-19 should not assume they have protective immunity from reinfection, the Washington Post noted. In fact, according to the LJI news release, researchers saw a “100-fold range in the magnitude of immune memory.”
Alessandro Sette, Doctor of Biological Sciences (above), an Italian immunologist, Professor at the Center for Autoimmunity and Inflammation/Center for Infectious Disease and Vaccine Research at La Jolla Institute for Immunology, and co-author of the study, told the Washington Post that people should act responsibly. “If I had COVID, I would still not throw away my masks, I would not go to rave parties … It’s like driving a car where you know you have 90% probability that the brakes work.” (Photo copyright: La Jolla Institute for Immunology.)
Previous Studies Found Little Natural Immunity Against SARS-CoV-2 Reinfection
The Scientist reported that several widely publicized previous studies raised concerns that immunity from natural infection was fleeting, perhaps dwindling in weeks or months. And a United Kingdom study published in Nature Microbiology found that COVID-19 generated “only a transient neutralizing antibody response that rapidly wanes” in patients who exhibited milder infection.
Daniel M. Davis, PhD, Professor of Immunology at the University of Manchester, says more research is needed before scientists can know for certain how long COVID-19 immunity lasts after natural infection.
“Overall, these results are interesting and provocative, but more research is needed, following large numbers of people over time. Only then, will we clearly know how many people produce antibodies when infected with coronavirus, and for how long,” Davis told Newsweek.
While additional peer-reviewed studies on the body’s immune response to COVID-19 will be needed, this latest study from the La Jolla Institute for Immunity may help guide clinical laboratories and in vitro diagnostic companies that are developing serological antibody tests for COVID-19 and lead to more definitive answers as to how long antibodies confer protective immunity.
By training a computer to analyze blood samples, and then automating the expert assessment process, the AI processed months’ worth of blood samples in a single day
New technologies and techniques for acquiring and transporting biological samples for clinical laboratory testing receive much attention. But what of the quality of the samples themselves? Blood products are expensive, as hospital medical laboratories that manage blood banks know all too well. Thus, any improvement to how labs store blood products and confidently determine their viability for transfusion is useful.
One such improvement is coming out of Canada. Researchers at the University of Alberta (U of A) in collaboration with scientists and academic institutions in five countries are looking into ways artificial intelligence (AI) and deep learning can be used to efficiently and quickly analyze red blood cells (RBCs). The results of the study may alter the way donated blood is evaluated and selected for transfusion to patients, according to an article in Folio, a U of A publication, titled, “AI Could Lead to Faster, Better Analysis of Donated Blood, Study Shows.”
Improving Blood Diagnostics through Precision Medicine and Deep Learning
“This project is an excellent example of how we are using our world-class expertise in precision health to contribute to the interdisciplinary work required to make fundamental changes in blood diagnostics,” said Jason Acker, PhD, a senior scientist at Canadian Blood Services’ Centre for Innovation, Professor of Laboratory Medicine and Pathology at the University of Alberta, and one of the lead authors of the study, in the Folio article.
The research took more than three years to complete and involved 19 experts from 12 academic institutions and blood collection facilities located in Canada, Germany, Switzerland, the United Kingdom, and the US.
“Our study shows that artificial intelligence gives us better information about the red blood cell morphology, which is the study of how these cells are shaped, much faster than human experts,” said Jason Acker, PhD (above), Senior Research Scientist, Canadian Blood Services, and Professor of Laboratory Medicine and Pathology at the University of Alberta, in an article published on the Canadian Blood Services website. “We anticipate this technology will improve diagnostics for clinicians as well as quality assurance for blood operators such as Canadian Blood Services in the coming years,” he added. Clinical laboratories in the US may also benefit from this new blood viability process. (Photo copyright: University of Alberta.)
To perform the study, the scientists first collected and manually categorized 52,000 red blood cell images. Those images were then used to train an algorithm that mimics the way a human mind works. The computer system was next tasked with analyzing the shape of RBCs for quality purposes.
Removing Human Bias from RBC Classification
“I was happy to collaborate with a group of people with diverse backgrounds and expertise,” said Tracey Turner, a senior research assistant in Acker’s laboratory and one of the authors of the study, in a Canadian Blood Services (CBS) article. “Annotating and reviewing over 52,000 images took a long time, however, it allowed me to see firsthand how much bias there is in manual classification of cell shape by humans and the benefit machine classification could bring.”
According to the CBS article, a red blood cell lasts about 115 days in the human body and the shape of the RBC reveals its age. Newer, healthier RBCs are shaped like discs with smooth edges. As they age, those edges become jagged and the cell eventually transforms into a sphere and loses the ability to perform its duty of transporting oxygen throughout the body.
Blood donations are processed, packed, and stored for later use. Once outside the body, the RBCs begin to change their shape and deteriorate. RBCs can only be stored for a maximum of 42 days before they lose the ability to function properly when transfused into a patient.
Scientists routinely examine the shape of RBCs to assess the quality of the cell units for transfusion to patients and, in some cases, diagnose and assess individuals with certain disorders and diseases. Typically, microscope examinations of red blood cells are performed by experts in medical laboratories to determine the quality of the stored blood. The RBCs are classified by shape and then assigned a morphology index score. This can be a complex, time-consuming, and laborious process.
“One of the amazing things about machine learning is that it allows us to see relationships we wouldn’t otherwise be able to see,” Acker said. “We categorize the cells into the buckets we’ve identified, but when we categorize, we take away information.”
Human analysis, apparently, is subjective and different professionals can arrive at different results after examining the same blood samples.
“Machines are naive of bias, and AI reveals some characteristics we wouldn’t have identified and is able to place red blood cells on a more nuanced spectrum of change in shape,” Acker explained.
The researchers discovered that the AI could accurately analyze and categorize the quality of the red blood cells. This ability to perform RBC morphology assessment could have critical implications for transfusion medicine.
“The computer actually did a better job than we could, and it was able to pick up subtle differences in a way that we can’t as humans,” Acker said.
“It’s not surprising that the red cells don’t just go from one shape to another. This computer showed that there’s actually a gradual progression of shape in samples from blood products, and it’s able to better classify these changes,” he added. “It radically changes the speed at which we can make these assessments of blood product quality.”
More Precision Matching Blood Donors to Recipients
According to the World Health Organization (WHO), approximately 118.5 million blood donations are collected globally each year. There is a considerable contrast in the level of access to blood products between high- and low-income nations, which makes accurate assessment of stored blood even more critical. About 40% of all blood donations are collected in high-income countries that home to only about 16% of the world’s population.
More studies and clinical trials will be necessary to determine if U of A’s approach to using AI to assess the quality of RBCs can safely transfer to clinical use. But these early results promise much in future precision medicine treatments.
“What this research is leading us to is the fact that we have the ability to be much more precise in how we match blood donors and recipients based on specific characteristics of blood cells,” Acker stated. “Through this study we have developed machine learning tools that are going to help inform how this change in clinical practice evolves.”
The AI tools being developed at the U of A could ultimately benefit patients as well as blood collection centers, and at hospitals where clinical laboratories typically manage the blood banking services, by making the process of matching transfusion recipients to donors more precise and ultimately safer.
The remarkably low number of influenza diagnoses makes it possible for clinical laboratories to stay focused on COVID-19
One positive note for clinical laboratories this winter is the fact that the number of biological samples being submitted for influenza (flu) testing have dropped significantly. This has given medical laboratories more resources for processing COVID-19 tests.
According to a feature published in Nature, the number of samples being submitted to medical laboratories for flu testing has dropped by 61%. More surprisingly, the number of positives has dropped by 98%. The combined flu/COVID-19 “twindemic” that some medical experts feared could crush our healthcare system has not materialized—yet, the Washington Examiner reported.
“In any given winter, hospitals are taxed by the flu,” Brian Garibaldi, MD, a pulmonologist and critical care specialist and Medical Director of the Johns Hopkins Biocontainment Unit told the Washington Examiner. “There’s always a concern that our emergency departments will be overwhelmed, and ICU capacity will be strained [due to the concurrence of flu and COVID-19 outbreaks], particularly with people who have coexisting conditions that then get influenza.”
The 2019-2020 flu season ended earlier than usual, likely because of precautions put in place in the spring to combat the coronavirus pandemic. Most years, the seasonal flu in the US peaks in February and trails off by May, Nature reported in “How Coronavirus Lockdowns Stopped Flu in Its Tracks.”
“Seasonal flu cases in the northern hemisphere usually peak in February and tail off by the end of May,” Nature wrote. “This year, unusually, lab-confirmed cases of influenza dropped precipitously in early April, a few weeks after the coronavirus pandemic was declared on 11 March. The data comes from tests of more than 150,000 samples from national influenza laboratories in 71 countries that report data to FluNet, a global surveillance system.”
Government Leaders and Health Experts Remain Concerned
Despite that encouraging data point, public health experts and political leaders were still concerned. In September, Arizona Governor Doug Ducey said, “The overlap of COVID-19 and flu season presents a perfect storm, and we aren’t taking any chances. We are approaching this fall with a proactive mindset and plan of action to limit the impact of the flu and preserve hospital resources,” the Washington Examiner reported.
The caution was certainly warranted. A normal flu season strains resources, but a severe flu season coupled with a global pandemic could have been disastrous. Luckily, Ducey’s “perfect storm” did not materialize.
Data from the World Health Organization’s FluNet Global Influenza Surveillance and Response System was used by Nature to develop the graphic above. It illustrates how the number of positive Influenza specimens in 2019-2020 declined compared to the previous two years. Some experts believe this is due to protocols implemented to combat the COVID-19 coronavirus by hospitals and clinical laboratories. (Graphic copyright: Nature.)
Why Is There Less Influenza?
So, why is there less flu and other respiratory infections?
Epidemiologist Lisa Lockerd Maragakis, MD, MPH, Associate Professor of Medicine and Senior Director of Infection Prevention at Johns Hopkins Health System, told U.S. News, widespread business and school closures provide fewer opportunities for influenza to spread. “We commonly see flu spread in communities, schools, businesses and through travel each year, so those changes are likely keeping the flu away.”
However, this may have a negative effect as well. Eili Klein, PhD, Associate Professor of Emergency Medicine at Johns Hopkins School of Medicine, warns that “Because of the current restrictions and precautions everyone is taking this season, far fewer people will be infected or exposed to the flu virus, and therefore won’t become immune to certain strains of the virus. So, the number of people who may have more severe infections next year is likely to be greater because immunity will be lower,” the Washington Examiner reported.
Other Viral Infections Also in Decline Due to COVID-19 Precautions, Vaccines
Masking, frequent handwashing, and social distancing certainly played a role in reducing the number of cases of flu reported this year. But influenza is not the only disease that saw reductions. “In Hong Kong, compared with previous years, the number of chickenpox cases dropped by about half to three-quarters,” Nature reported. “In April, cases of measles and rubella were their lowest, globally, since at least 2016, according to data available so far.”
Early in the COVID-19 pandemic, some public health officials were concerned that the decline in influenza cases was actually related to a lack of testing. “However, renewed efforts by public health officials and clinicians to test samples for influenza resulted in adequate numbers tested and detection of little to no influenza virus,” the Centers for Disease Control and Prevention (CDC) reported.
Another factor in the lower numbers of flu cases could be due to the fact that more people have gotten vaccinated this year. More than 188 million flu vaccines were distributed in 2020, an increase compared to the 169 million given in 2019.
“Flu vaccination in the community started earlier this year, as recommended by the CDC, and our community physicians report that vaccine uptake has been higher than usual,” Marie-LouiseLandry, MD, Clinical Virologist, Professor of Laboratory Medicine and of Medicine (Infectious Diseases), and Director of the Clinical Virology Laboratory at Yale School of Medicine, told Healthline.
It may also be that influenza diagnoses are fewer because people are not seeking treatment. Hospitals at or beyond capacity due to the pandemic, or fear of contracting COVID-19, may have motivated people with flu-like symptoms to stay home rather than seek treatment. However, most healthcare experts agree that public health measures to fight COVID-19 are likely the larger reason there is less flu.
“Public health measures such as movement restrictions, social distancing, and increased personal hygiene likely had an effect on decreasing influenza and other respiratory virus transmissions,” the World Health Organization (WHO) told Nature.
What About the Next Flu Season?
Experts are more conflicted regarding what all of this means for coming flu seasons. Some experts think that because there’s less flu this year, there will be less immunity next year, and severe illness will result. Others are more optimistic and hope that some strains of flu will disappear, which could mean less flu in the immediate future. It’s not a simple prediction to make.
Even if the low flu numbers this year mean some strains do not survive, it is unlikely that will remain the case. “I am sure that flu will come back with a vengeance at some stage in the future,” Robert Ware, PhD, a biostatistician, clinical epidemiologist, and Professor of Biostatistics with Griffith University in Queensland, Australia, told Nature.
Thus, clinical laboratories should remain vigilant for future influenza outbreaks. Hopefully by then the COVID-19 pandemic will have peaked and labs will be able to reallocate testing resources appropriately.
Such a test, if proved safe and accurate for clinical use, could be a useful diagnostic tool for anatomic pathologists
What would it mean to anatomic pathology if breast cancer could be diagnosed in an hour from a fine needle aspiration (FNA) rather than a core biopsy? A new test created by researchers affiliated with Massachusetts General Hospital in Boston may be just such a game changer. Especially in remote locations where clinical laboratory resources are in short supply.
Regardless of how the next round of research and clinical studies turn out, one reason this development is significant is that it demonstrates how newer technologies and analytical software are being combined to create a faster diagnostic test for different types of cancer.
Another benefit to this research is that it may utilize simpler, less expensive instruments. In fact, the researchers said this test can be performed for about $5. For these reasons, pathologists may want to follow the progress of these researchers as they work to improve this test so it can be used in clinical care.
Affordable Image Cytometry of FNA Specimens
Though still in development, the new image cytometry system, dubbed CytoPAN, has demonstrated the ability to diagnose breast cancer within a one-hour time frame, and, according to the study published in Science Translational Medicine, “is devoid of moving parts for stable operations, harnesses optimized antibody kits for multiplexed analysis, and offers a user-friendly interface with automated analysis for rapid diagnoses.”
The international researcher team included scientists from:
“Here, we report the development and validation of an affordable image cytometry system that allows automated and same-day molecular analyses of fine needle aspiration (FNA) specimens. Termed CytoPAN, for portable fluorescence-based image cytometry analyzer, the system performs multichannel imaging for cancer diagnosis and subtyping,” the researchers wrote.
The CytoPAN technique is minimally invasive, they note, and only requires a few cellular specimens to determine if breast cancer cells are present, with results available in one hour.
The researchers are hopeful the CytoPAN diagnostic tool (above) can be a valuable resource in developing countries and remote areas where patients face long wait times before receiving a cancer diagnosis. In these areas, diagnoses typically come after advanced symptoms, such as palpable mass lesions and malaise, become present, which can have a negative impact on patientoutcomes. And anatomic pathologists worldwide would benefit greatly from such an advance in cancer diagnostics. (Photo copyright: Jouha Min, Lip Ket Chin Center for Systems Biology, Massachusetts General Hospital.)
“Unfortunately, in many low- and middle-income countries, [breast cancer] diagnosis often takes an extraordinarily long time—up to a few months—due to a lack of specialists and limited laboratory infrastructure,” Hyungsoon Im, PhD, Assistant Professor at Harvard Medical School and one of the researchers involved in the project, told United Press International (UPI).
“From a public health aspect, it is critically important to develop new diagnostic methods that overcome these barriers,” he added.
Because FNA testing is less invasive than surgical biopsy collection, it has fewer complications and is generally considered safe. Thus, it is “feasible to be performed even in resource-limiting settings at much lower costs,” Im told UPI. “This could lead to earlier treatment and accelerate new drug testing in clinical trials.”
CytoPAN Testing and Additional Trials
The researchers tested CytoPAN on 68 breast cancer patients in South Korea.
“To determine the clinical utility of the approach,” they wrote in the published study, “we next conducted a prospective clinical study in which the FNA could be directly compared to conventional pathology results. We enrolled treatment-native patients at the Kyungpook National University Chilgok Hospital (Daegu, South Korea) and who were referred for primary surgery. All patients consented to have a preoperative breast FNA before clinically indicated surgery. The breast masses were visualized by ultrasound or computed tomography, and a coaxial needle was introduced through which FNA samples (CytoPAN) and core biopsies were obtained. Surgical specimens and/or core biopsies were processed by routine pathology and served as the gold standard.”
The CytoPAN platform detected the presence of breast cancer cells with a 100% accuracy, using as few as 50 harvested cells per collected specimen.
The test also successfully identified two key breast cancer biomarkers:
“We are also preparing additional trials in the US and other countries,” Im told UPI. “The success in those trials will (hopefully) accelerate … widespread adoption of the technology.”
The researchers are currently testing CytoPAN on a larger number of patients in Botswana, with funding from the US federal National Institutes of Health (NIH).
According to the American Cancer Society (ACS), approximately 300,000 individuals are diagnosed with breast cancer annually in the US. The Union for International Cancer Control (UICC) states on their website that, globally, there are more than two million new cases of breast cancer diagnosed each year. And more than 600,000 people died from breast cancer worldwide in 2018. A disproportionate number of those deaths occurred in developing countries that have limited resources to diagnose and treat the disease.
Additional Research for Other Applications in Cancer Testing and Pathology
The new CytoPAN technology requires minimal training, according to the researchers, and only costs about $5 per test kit. This is substantially less expensive than the price associated with other tests available on the market, UPI noted.
Though additional research and clinical trials are needed before CytoPAN will be available for widespread clinical use, a cost-effective, relatively non-invasive test that can accurately diagnose cancer within an hour would be transformational for anatomic pathology and, potentially, could save many lives.
