Study findings could lead to new clinical laboratory diagnostics that give pathologists a more detailed understanding about certain types of cancer
New studies proving artificial intelligence (AI) can be used effectively in clinical laboratory diagnostics and personalized healthcare continue to emerge. Scientists in the UK recently trained an AI model using machine learning and deep learning to enable earlier, more accurate detection of 13 different types of cancer.
DNA stores genetic information in sequences of four nucleotide bases: A (adenine), T (thymine), G (guanine) and C (cytosine). These bases can be modified through DNA methylation. There are millions of DNA methylation markers in every single cell, and they change in the early stages of cancer development.
One common characteristic of many cancers is an epigenetic phenomenon called aberrant DNA methylation. Modifications in DNA can influence gene expression and are observable in cancer cells. A methylation profile can differentiate tumor types and subtypes and changes in the process often come before malignancy appears. This renders methylation very useful in catching cancers while in the early stages.
However, deciphering slight changes in methylation patterns can be extremely difficult. According to the scientists, “identifying the specific DNA methylation signatures indicative of different cancer types is akin to searching for a needle in a haystack.”
Nevertheless, the researchers believe identifying these changes could become a useful biomarker for early detection of cancers, which is why they built their AI models.
“Computational methods such as this model, through better training on more varied data and rigorous testing in the clinic, will eventually provide AI models that can help doctors with early detection and screening of cancers,” said Shamith Samarajiwa, PhD (above), Senior Lecturer and Group Leader, Computational Biology and Genomic Data Science, Imperial College London, in a news release. “This will provide better patient outcomes.” With additional research, clinical laboratories and pathologists may soon have new cancer diagnostics based on these AI models. (Photo copyright: University of Cambridge.)
The researchers then used a combination of machine learning and deep learning techniques to train an AI algorithm to examine DNA methylation patterns of the collected data. The algorithm identified and differentiated specific cancer types, including breast, liver, lung and prostate, from non-cancerous tissue with a 98.2% accuracy rate. The team evaluated their AI model by comparing the results to independent research.
In their Biology Methods and Protocols paper, the authors noted that their model does require further training and testing and stressed that “the important aspect of this study was the use of an explainable and interpretable core AI model.” They also claim their model could help medical professionals understand “the underlying mechanisms that contribute to the development of cancer.”
Using AI to Lower Cancer Rates Worldwide
According to the Centers for Disease Control and Prevention (CDC), cancer ranks as the second leading cause of death in the United States with 608,371 deaths reported in 2022. The leading cause of death in the US is heart disease with 702,880 deaths reported in the same year.
Globally cancer diagnoses and death rates are even more alarming. World Health Organization (WHO) data shows an estimated 20 million new cancer cases worldwide in 2022, with 9.7 million persons perishing from various cancers that year.
The UK researchers are hopeful their new AI model will help lower those numbers. They state in their paper that “most cancers are treatable and curable if detected early enough.”
More research and studies are needed to confirm the results of this study, but it appears to be a very promising line of exploration and development of using AI to detect, identify, and diagnose cancer earlier. This type of probing could provide pathologists with improved tools for determining the presence of cancer and lead to better patient outcomes.
This AI platform has the potential to also reduce workload of radiologists, but also of anatomic pathologists and oncologists allowing them to be more productive
When the UK’s National Health Service (NHS) recently tested an artificial intelligence (AI) platform’s ability to analyze mammograms, the AI found early signs of breast cancer that “human doctors” had previously missed, the BBC reported. This level of ability by AI might soon be adapted to aid overworked anatomic pathologists and cancer doctors in the United Kingdom.
Out of 10,000 mammograms MIA analyzed, the AI platform found “tiny signs of breast cancer in 11 women” which had not been spotted during earlier examinations, the BBC noted, adding that the cancers “were practically invisible to the human eye.”
This is a significant development in AI’s role in healthcare. Anatomic pathologists and clinical laboratory leaders will note that ongoing advancements in AI are enabling technology developers to apply their solutions to assessing radiology images, as well as in whole slide imaging used in digital pathology. In the UK, use of AI, the BBC noted, may also help ease doctor’s workloads.
“This is just the beginning of our work with Kheiron,” said Ben Glocker, PhD (above), Professor in Machine Learning for Imaging at Imperial College London and Head of ML Research at Kheiron Medical, in a news release. “We are actively working on new methodologies for the safe deployment and continuous monitoring of MIA to support a US and UK rollout. We are working hard to make sure that as many women as possible will benefit from the use of this new technology within the next year.” AI tools such as MIA may soon take much of the load from anatomic pathologists and radiologists. (Photo copyright: Imperial College London.)
MIA Cloud-based AI Platform
Kheiron was founded in 2016 and MIA was named one of the seven biggest medical breakthroughs in 2023 by ABC News. A study conducted by Imperial College London in 2023 found that MIA “could significantly increase the early detection of breast cancers in a European healthcare setting by up to 13%,” according to an Imperial news release.
“The study was conducted over three phases (two pilot phases and a live roll-out). Overall across the three phases, the AI reader found 24 more cancers than the standard human reading—a 7% relative increase—and resulted in 70 more women recalled (0.28% relative increase),” the news release reported. “Of the additional recalls, six (initial pilot), 13 (extended pilot), and 11 (live use) additional cancers were found, increasing relative cancer detection rate by 13%, 10%, and 5% respectively. [The researchers] found that 83% of the additional cancers detected using MIA in real clinical practice were invasive, showing that MIA can detect cancers where early detection is particularly vital.”
Supported by Microsoft’s Azure Cloud, MIA came together over six years based on training encompassing millions of mammograms worldwide, Healthcare Digital reported.
“AI tools are generally pretty good at spotting symptoms of a specific disease if they are trained on enough data to enable them to be identified. This means feeding the program with as many different anonymized images of those symptoms as possible, from as diverse a range of people as possible,” Sarah Kerruish, Chief Strategy Officer, Kheiron, told Healthcare Digital.
MIA has been trained to “recognize subtle patterns and anomalies” that can point to “cancerous cells even in their earliest stages of development,” Dataconomy reported.
MIA Finds Early Cancer Signs
In the pilot study, MIA examined mammograms from 10,889 women. Each image had previously been reviewed by two radiologists, the BBC reported.
Findings include the following according to Healthcare Digital:
MIA “flagged” all people the physicians previously identified with symptoms.
The AI platform discovered 11 people with cancer the doctors did not identify.
The cancer MIA discovered—and the doctors did not—suggested cancer in early stages.
So, how did the doctors miss the cancer that MIA spotted? Gerald Lip, MD, Clinical Director for Breast Screening in North East Scotland who led the pilot study for the NHS, told Healthcare Digital, “part of the power of AI is it’s not prone to exhaustion or distraction.
“There is an element of fatigue,” he said. “You get disruptions, someone’s coming in, someone’s chatting in the background. There are lots of things that can probably throw you off your regular routine as well. And in those days when you have been distracted, you go, ‘how on earth did I miss that?’ It does happen.”
Lip is also the Chief Investigator in the Mammography Artificial Intelligence Project in the Industrial Center for Artificial Intelligence and Digital Diagnostics in Scotland.
“I see MIA as a friend and an augmentation to my practice,” he told Healthcare Digital. “MIA isn’t perfect. It had no access to patient history so [it] would flag cysts that had already been identified by previous scans and designated harmless.”
AI as a Safety Net
In the 2023 study, researchers from Imperial College London deployed MIA as an extra reader for mammograms of 25,065 women who visited screening sites in Hungary between April 2021 and January 2023, according to a news release.
“Our prospective real-world usage data in Hungary provides evidence for a significant, measurable increase of early breast cancer detection when MIA is used in clinical practice,” said Peter Kecskemethy, PhD, CEO and co-founder of Kheiron Medical, in the news release.
“Our study shows that AI can act as an effective safety net—a tool to prevent subtler signs of cancer from falling through the cracks,” said Ben Glocker, PhD, Professor in Machine Learning for Imaging at Imperial College London and Head of ML Research at Kheiron Medical, in the news release.
More studies are needed before MIA can be used in clinical settings. Nevertheless, use of AI in radiology—specifically mammograms—where the AI tool can identify very small cancers typically undetectable by radiologists, would be a boon to cancer doctors and the patients they treat.
So far, the research suggests that the AI-powered MIA has benefits to deployment in breast cancer screening. Eventually, it may also make impressive contributions to medical diagnosis and patient care, particularly if MIA eventually proves to be effective at analyzing the whole slide images used by anatomic pathologists.
Meet ‘PECOTEX,’ a newly-invented cotton thread with up to 10 sensors that is washable. Its developers hope it can help doctors diagnosis disease and enable patients to monitor their health conditions
Wearable biosensors continue to be an exciting area of research and product development. The latest development in wearable biosensors comes from a team of scientists led by Imperial College London. This team created a conductive cotton thread that can be woven onto T-shirts, textiles, and face masks and used to monitor key biosignatures like heart rate, respiratory rate, and ammonia levels.
Clinical laboratory managers and pathologists should also take note that this wearable technology also can be used to diagnose and track diseases and improve the monitoring of sleep, exercise, and stress, according to an Imperial College London news release.
Should this technology make it into daily use, it might be an opportunity for clinical laboratories to collect diagnostic and health-monitoring data to add to the patient’s full record of lab test results. In turn, clinical pathologists could use that data to add value when consulting with referring physicians and their patients.
“Our research opens up exciting possibilities for wearable sensors in everyday clothing,” said Firat Güder, PhD, Principal Investigator and Chief Engineer at Güder Research Group at Imperial College London, in a news release. “By monitoring breathing, heart rate, and gases, they can already be seamlessly integrated, and might even be able to help diagnose and monitor treatments of disease in the future.” (Photo copyright: Wikipedia.)
Ushering in New Generation of Wearable Health Sensors
The researchers dubbed their new sensor thread PECOTEX. It’s a polystyrene sulfonate-modified cotton conductive thread that can incorporate more than 10 sensors into cloth surfaces, costs a mere 15 cents/meter (slightly over 39 inches), and is machine washable.
“PECOTEX is high-performing, strong, and adaptable to different needs,” stated Firat Güder, PhD, Principal Investigator and Chief Engineer at Güder Research Group, Imperial College London, in the press release.
“It’s readily scalable, meaning we can produce large volumes inexpensively using both domestic and industrial computerized embroidery machines,” he added.
The material is less breakable and more conductive than conventional conductive threads, which allows for more layers to be embroidered on top of each other to develop more complex sensors. The embroidered sensors retain the intrinsic values of the cloth items, such as wearability, breathability, and the feel on the skin. PECOTEX is also compatible with computerized embroidery machines used in the textile industry.
The researchers embroidered the sensors into T-shirts to track heart activity, into a face mask to monitor breathing, and into other textiles to monitor gases in the body like ammonia which could help detect issues with liver and kidney function, according to the news release.
“The flexible medium of clothing means our sensors have a wide range of applications,” said Fahad Alshabouna, a PhD candidate at Imperial College’s Department of Bioengineering and lead author of the study in the news release. “They’re also relatively easy to produce which means we could scale up manufacturing and usher in a new generation of wearables in clothing.”
Uses for PECOTEX Outside of Healthcare
The team plans on exploring new applications for PECOTEX, such as energy storage, energy harvesting, and biochemical testing for personalized medicine. They are also seeking partners for commercialization of the product.
“We demonstrated applications in monitoring cardiac activity and breathing, and sensing gases,” Fahad added. “Future potential applications include diagnosing and monitoring disease and treatment, monitoring the body during exercise, sleep, and stress, and use in batteries, heaters, and anti-static clothing.”
Wearable healthcare devices have enormous potential to perform monitoring for diagnostic, therapeutic, and rehabilitation purposes and support precision medicine.
Further studies and clinical trials need to occur before PECOTEX will be ready for mass consumer use. Nevertheless, it could lead to new categories of inexpensive, wearable sensors that can be integrated into everyday clothes to provide data about an individual’s health and wellbeing.
If this technology makes it to clinical use, it could provide an opportunity for clinical laboratories to collect diagnostic data for patient records and help healthcare professionals track their patients’ medical conditions.
As infectious bacteria become even more resistant to antibiotics, chronic disease patients with weakened immune systems are in particular danger
Microbiologists
and clinical
laboratory managers in the United States may find it useful to learn that
exceptionally virulent strains of bacteria are causing increasing numbers of cancer
patient deaths in India. Given the speed with which infectious diseases spread
throughout the world, it’s not surprising that deaths due to similar hospital-acquired
infections (HAIs) are increasing in the US as well.
Recent news reporting indicates that an ever-growing number
of cancer patients in the world’s second most populous nation are struggling to
survive these infections while undergoing chemotherapy and other treatments for
their cancers.
In some ways, this situation is the result of more powerful antibiotics. Today’s modern antibiotics help physicians, pathologists, and clinical laboratories protect patients from infectious disease. However, it’s a tragic fact that those same powerful drugs are making patients with chronic diseases, such as cancer, more susceptible to death from HAIs caused by bacteria that are becoming increasingly resistant to those same antibiotics.
India is a prime example of that devastating dichotomy. Bloomberg
reported that a study conducted by Abdul
Ghafur, MD, an infectious disease physician with Apollo Hospitals in Chennai, India,
et al, concluded that “Almost two-thirds of cancer patients with a
carbapenem-resistant infection are dead within four weeks, vs. a 28-day
mortality rate of 38% in patients whose infections are curable.”
This news should serve as an alert to pathologists, microbiologists,
and clinical laboratory leaders in the US as these same superbugs—which resist
not only antibiotics but other drugs as well—may become more prevalent in this
country.
‘We Don’t Know
What to Do’
The dire challenge facing India’s cancer patients is due to escalating
bloodstream infections associated with carbapenem-resistant
enterobacteriaceae (CRE), a particularly deadly bacteria that has become
resistant to even the most potent carbapenem antibiotics, generally
considered drugs of last resort for dealing with life-threatening infections.
Lately, the problem has only escalated. “We are facing a
difficult scenario—to give chemotherapy and cure the cancer and get a
drug-resistant infection and the patient dying of infections.” Ghafur told Bloomberg.
“We don’t know what to do. The world doesn’t know what to do in this scenario.”
Ghafur added, “However wonderful the developments in the
field of oncology, they are not going to be useful, because we know cancer
patients die of infections.”
Abdul Ghafur, MD (above), an infectious disease physician with Apollo Hospitals in Chennai, India, told The Better India that, “Indians, are obsessed with antibiotics and believe that they can cure almost all infections, including viral infections! Moreover, at least half of the prescriptions by Indian doctors include an antibiotic. Sadly, the public believes that whenever we get cold and cough, we need to swallow antibiotics for three days along with paracetamol [acetaminophen]! This is a myth that urgently needs to disappear!” (Photo copyright: Longitude Prize.)
The problem in India, Bloomberg reports, is
exacerbated by contaminated food and water. “Germs acquired through ingesting
contaminated food and water become part of the normal gut microbiome, but they can
turn deadly if they escape the bowel and infect the urinary tract, blood, and
other tissues.” And chemotherapy patients, who likely have weakened digestive
tracts, suffer most when the deadly germs reach the urinary tract, blood, and surrounding
tissues.
“Ten years ago, carbapenem-resistant superbug infections
were rare. Now, infections such as carbapenem-resistant klebsiella bloodstream
infection, urinary infection, pneumonia, and surgical site infections are a
day-to-day problem in our (Indian) hospitals. Even healthy adults in the
community may carry these bacteria in their gut in Indian metropolitan cities;
up to 5% of people carry these superbugs in their intestines,” Ghafur told The
Better India.
“These patients receive chemotherapy during treatment, which
lead to severe mucositis
of gastrointestinal tract and myelosuppression.
It was hypothesized that the gut colonizer translocate into blood circulation
causing [bloodstream infection],” the AIIMS paper states.
US Cases of C. auris Also Linked to CRE
Deaths in the US involving the fungus Candida auris (C. auris)
have been linked to CRE as well. And, people who were hospitalized outside the
US may be at particular risk.
The CDC reported on
a Maryland resident who was hospitalized in Kenya with a
carbapenemase-producing infection, which was later diagnosed as C. auris. The CDC
describes C. auris as “an emerging drug-resistant yeast of high public concern
… C auris frequently co-occurs with carbapenemase-producing organisms like
CRE.”
The graphic above, developed by the NYT from CDC data, shows that Candida auris is found globally and not restricted to poor or resource-strapped nations. “The fungus seems to have emerged in several locations at once, not from a single source,” the NYT reports. This means clinical laboratories can expect to be processing more tests to identify the deadly fungus. (Graphic copyright: New York Times/CDC.)
Drug-resistant germs are a public health threat that has
grown beyond overuse of antibiotics to an “explosion of resistant fungi,”
reported the New
York Times (NYT).
“It’s an enormous problem. We depend on being able to treat
those patients with antifungals,” Matthew Fisher, PhD,
Professor of Fungal Disease Epidemiology at Imperial College London, told the NYT.
The NYT article states that “Nearly half of patients
who contract C. auris die within 90 days, according to the CDC. Yet the world’s
experts have not nailed down where it came from in the first place.”
Cases of C. auris in the US are showing up in New York, New
Jersey, and Illinois and is arriving on travelers from many countries,
including India, Pakistan, South Africa, Spain, United Kingdom, and
Venezuela.
“It is a creature from the black lagoon,” Tom Chiller, MD,
Chief of the Mycotic
Diseases Branch at the CDC told the NYT. “It bubbled up and now it
is everywhere.”
Since antibiotics are used heavily in agriculture and
farming worldwide, the numbers of antibiotic-resistant infections will likely
increase. Things may get worse, before they get better.
Pathologists, microbiologists, oncologists, and clinical
laboratories involved in caring for patients with antibiotic-resistant
infections will want to fully understand the dangers involved, not just to
patients, but to healthcare workers as well.
Use of synthetic genetics to replicate an infectious disease agent is a scientific accomplishment that many microbiologists and clinical laboratory managers expected would happen
Microbiologists and infectious disease doctors are quite familiar with Escherichia coli (E. coli). The bacterium has caused much human sickness and even death around the globe, and its antibiotic resistant strains are becoming increasingly difficult to eradicate.
Now, scientists in England have created a synthetic “recoded” version of E. coli bacteria that is being used in a positive way—to fight disease. Their discovery is being heralded as an important breakthrough in the quest to custom-alter DNA to create synthetic forms of life that one day could be designed to fight specific infections, create new drugs, or produce tools to diagnose or treat disease.
Scientists worldwide working in the field of synthetic genomics are looking for ways to modify genomes in order to produce new weapons against infection and disease. This research could eventually produce methods for doctors—after diagnosing a patient’s specific strain of bacteria—to then use custom-altered DNA as an effective weapon against that patient’s specific bacterial infection.
This latest milestone is the result of a five-year quest by researchers at the Medical Research Council Laboratory of Molecular Biology (MRC-LMB) in Cambridge, England, to create a man-made version of the intestinal bacteria by redesigning its four-million-base-pair genetic code.
The MRC-LMB lab’s success marks the first time a living
organism has been created with a compressed genetic code.
The researchers published their findings in the journal Nature.
“This is a landmark in the emerging field of synthetic
genomics and finally applies the technology to the laboratory’s workhorse
bacterium,” they wrote. “Synthetic genomics offers a new way of life, while at
the same time moving synthetic biology towards a future in which genomes can be
written to design.”
All known forms of life on Earth contain 64 codons—a specific sequence of three consecutive nucleotides that corresponds with a specific amino acid or stop signal during protein synthesis. Jason Chin, PhD, Program Lead at MRC-LMB, said biologists long have questioned why there are 20 amino acids encoded by 64 codons.
“Is there any function to having more than one codon to encode each amino acid?” Chin asked during an interview with the Cambridge Independent. “What would happen if you made an organism that used a reduced set of codons?”
The MRC-LMB research team took an important step toward
answering that question. Their synthetic E. coli strain, dubbed Syn61,
was recoded through “genome-wide substitution of target codons by defined
synonyms.” To do so, researchers mastered a new piece-by-piece technique that
enabled them to recode 18,214 codons to create an organism with a 61-codon
genome that functions without a previously essential transfer RNA.
“Our synthetic genome implements a defined recoding and refactoring scheme–with simple corrections at just seven positions–to replace every known occurrence of two sense codons and a stop codon in the genome,” lead author Julius Fredens, PhD, a post-doctoral research associate at MRC, and colleagues, wrote in their paper.
Science Alert reports that the laboratory-created version of E. coli (above) “isn’t quite a dead ringer for its ancestor. The cells are a touch longer, and they reproduce 1.6 times slower. But the edited E. coli seems healthy and produces the same range and quantity of proteins as the non-edited versions.” (Photo copyright: Jason Chin/STAT.)
Joshua Atkinson, PhD, a postdoctoral research associate at Rice University in Houston, labeled the breakthrough a “tour de force” in the field of synthetic genomics. “This achievement sets a new world record in synthetic genomics by yielding a genome that is four times larger than the pioneering synthesis of the one-million-base-pair Mycoplasma mycoides genome,” he stated in Synthetic Biology.
“Synthetic genomics is enabling the simplification of
recoded organisms; the previous study minimized the total number of genes and
this new study simplified the way those genes are encoded.”
Manmade Bacteria That are Immune to Infections
Researchers from the J.
Craig Venter Institute in Rockville, Maryland, created the first synthetic
genome in 2010. According to an article in Nature,
the Venter Institute successfully synthesized the Mycoplasma mycoides genome
and used it “reboot” a cell from a different species of bacterium.
The MRC-LMB team’s success may prove more significant.
“This new synthetic E. coli should not be able to decode DNA from any other organism and therefore it should not be possible to infect it with a virus,” the MRC-LMB stated in a news release heralding the lab’s breakthrough. “With E. coli already being an important workhorse of biotechnology and biological research, this study is the first time any commonly used model organism has had its genome designed and fully synthesized and this synthetic version could become an important resource for future development of new types of molecules.”
Because the MRC-LMB team was able to remove transfer RNA and
release factors that decode three codons from the E. coli bacteria,
their achievement may be the springboard to designing manmade bacteria that are
immune to infections or could be turned into new drugs.
“This may enable these codons to be cleanly reassigned and
facilitate the incorporation of multiple non-canonical amino acids. This
greatly expands the scope of using non-canonical amino acids as unique tools
for biological research,” the MRC-LMB news release added.
Though synthetic genomics impact on clinical laboratory diagnostics is yet to be known, medical laboratory leaders should be mindful of the potential for rapid innovation in this field as proof-of-concept laboratory innovations are translated into real-world applications.
