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Oxford University Creates Largest Ever Human Evolutionary Family Tree with 231 Million Ancestral Lineages

Researchers say their method can trace ancestry back 100,000 years and could lay groundwork for identifying new genetic markers for diseases that could be used in clinical laboratory tests

Cheaper, faster, and more accurate genomic sequencing technologies are deepening scientific knowledge of the human genome. Now, UK researchers at the University of Oxford have used this genomic data to create the largest-ever human family tree, enabling individuals to trace their ancestry back 100,000 years. And, they say, it could lead to new methods for predicting disease.

This new database also will enable genealogists and medical laboratory scientists to track when, where, and in what populations specific genetic mutations emerged that may be involved in different diseases and health conditions.

New Genetic Markers That Could Be Used for Clinical Laboratory Testing

As this happens, it may be possible to identify new diagnostic biomarkers and genetic indicators associated with specific health conditions that could be incorporated into clinical laboratory tests and precision medicine treatments for chronic diseases.

“We have basically built a huge family tree—a genealogy for all of humanity—that models as exactly as we can the history that generated all the genetic variation we find in humans today,” said Yan Wong, DPhil, an evolutionary geneticist at the Big Data Institute (BDI) at the University of Oxford, in a news release. “This genealogy allows us to see how every person’s genetic sequence relates to every other, along all the points of the genome.”

Researchers from University of Oxford’s BDI in London, in collaboration with scientists from the Broad Institute of MIT and Harvard; Harvard University, and University of Vienna, Austria, developed algorithms for combining different databases and scaling to accommodate millions of gene sequences from both ancient and modern genomes.

The researchers published their findings in the journal Science, titled, “A Unified Genealogy of Modern and Ancient Genomes.”

Anthony Wilder Wohns, PhD
“Essentially, we are reconstructing the genomes of our ancestors and using them to form a series of linked evolutionary trees that we call a ‘tree sequence,’” said geneticist Anthony Wilder Wohns, PhD (above), in the Oxford news release. Wohns, a postdoctoral researcher in statistical and population genetics at the Broad Institute, led the study. “We can then estimate when and where these ancestors lived. The power of our approach is that it makes very few assumptions about the underlying data and can also include both modern and ancient DNA samples.” The study may result in new genetic biomarkers that lead to advances in clinical laboratory diagnostics for today’s diseases. (Photo copyright: Harvard School of Engineering and Applied Sciences.)

Tracking Genetic Markers of Disease

The BDI team overcame the major obstacle to tracing the origins of human genetic diversity when they developed algorithms to handle the massive amount of data created when combining genome sequences from many different databases. In total, they compiled the genomic sequences of 3,601 modern and eight high-coverage ancient people from 215 populations in eight datasets.

The ancient genomes included three Neanderthal genomes, a Denisovan genome, and a family of four people who lived in Siberia around 4,600 years ago.

The University of Oxford researchers noted in their news release that their method could be scaled to “accommodate millions of genome sequences.”

“This structure is a lossless and compact representation of 27 million ancestral haplotype fragments and 231 million ancestral lineages linking genomes from these datasets back in time. The tree sequence also benefits from the use of an additional 3,589 ancient samples compiled from more than 100 publications to constrain and date relationships,” the researchers wrote in their published study.

Wong believes his research team has laid the groundwork for the next generation of DNA sequencing.

“As the quality of genome sequences from modern and ancient DNA samples improves, the tree will become even more accurate and we will eventually be able to generate a single, unified map that explains the descent of all the human genetic variation we see today,” he said in the news release.

Developing New Clinical Laboratory Biomarkers for Modern Diagnostics

In a video illustrating the study’s findings, evolutionary geneticist Yan Wong, DPhil, a member of the BDI team, said, “If you wanted to know why some people have some sort of medical conditions, or are more predisposed to heart attacks or, for example, are more susceptible to coronavirus, then there’s a huge amount of that described by their ancestry because they’ve inherited their DNA from other people.”

Wohns agrees that the significance of their tree-recording methods extends beyond simply a better understanding of human evolution.

“[This study] could be particularly beneficial in medical genetics, in separating out true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history,” he said.

The underlying methods developed by Wohns’ team could have widespread applications in medical research and lay the groundwork for identifying genetic predictors of disease risk, including future pandemics.

Clinical laboratory scientists will also note that those genetic indicators may become new biomarkers for clinical laboratory diagnostics for all sorts of diseases currently plaguing mankind.

Andrea Downing Peck

Related Information:

A Unified Genealogy of Modern and Ancient Genomes

Video: A Unified Genealogy of Modern and Ancient Genomes

University of Oxford Researchers Create Largest Ever Human Family Tree

How Neanderthal DNA Affects Human Health—including the Risk of Getting COVID-19

Inferring Human Evolutionary History

We Now Have the Largest Ever Human ‘Family Tree’ with 231 Million Ancestral Lineages

An Unlikely Pandemic Pairing: Facemasks Embedded with Ostrich Antibodies That Detect COVID-19 under UV Light

Japanese scientists who developed the detection method hope to use it to create ‘easy testing kits that anyone can use’

What do ostriches and humans have in common during the current COVID-19 pandemic? The unexpected answer is that ostrich antibodies can be used to identify humans infected with COVID-19. If proven viable in healthcare settings, the possibility exists that new clinical laboratory tests could be developed based on wearable diagnostics technologies that pathologists would interpret for doctors and patients.

This insight was the result of research conducted at Japan’s Kyoto Prefectural University. The KPU scientists found that a paper facemask coated with ostrich antibodies will give off a fluorescence in the presence of the SARS-CoV-2 coronavirus under ultraviolet (UV) light.

Yasuhiro Tsukamoto, PhD

According to Study Finds, scientists at Kyoto Prefectural University in Japan have created a removable mask filter that, when sprayed with a fluorescent dye coated with antibodies extracted from ostrich eggs, will glow under UV light when COVID-19 is detected. The discovery by Yasuhiro Tsukamoto, PhD (above), President of Kyoto Prefectural University, and his researchers could lead to development of low-cost at home COVID-19 testing kits using the same ostrich-antibody-based technique. (Photo copyright: Kyoto Prefectural University/Reuters.)

The KPU scientists conducted a small study with 32 COVID-19 patients over a 10-day span. The surgical-style masks they wore later glowed around the nose and mouth areas but became dimmer over time as their viral load decreased.

“The ostrich antibody for corona placed on the mouth filter of the mask captures the coronavirus in coughing, sneezing, and water,” the researchers explained in Study Finds.

Tsukamoto himself learned he had contracted COVID-19 after wearing a prototype mask and noticing it glowed under UV light. A PCR test later confirmed his diagnosis, Kyodo News reported.

The KPU team “hopes to further develop the masks so they will glow automatically, without special lighting, if the [COVID-19] virus is detected.” Reuters noted in its coverage of the ostrich-antibody masks.

Making Medicine from Ostrich Antibodies

A profile in Audubon noted that Tsukamoto, who also serves as a veterinary medicine professor at Kyoto Prefectural University, made ostriches the focus of his research since the 1990s as he looked for ways to harness the dinosaur-like bird’s properties to fight human infections. He maintains a flock of 500 captive ostriches. Each female ostrich can produce 50 to 100 eggs/year over a 50-year life span.

Tsukamoto’s research focuses on customizing the antibodies in ostrich eggs by injecting females with inactive viruses, allergens, and bacteria, and then extracting the antibodies to develop medicines for humans. Antibodies form in the egg yolks in about six weeks and can be collected without harming the parent or young.

“The idea of using ostrich antibodies for therapeutics in general is a very interesting concept, particularly because of the advantages of producing the antibodies from eggs,” Ashley St. John, PhD, an Associate Professor in Immunology, at Duke-NUS Medical School in Singapore, told Audubon.

While more clinical studies will be needed before ostrich-antibody masks reach the commercial marketplace, Tsukamoto’s team is planning to expand their experiment to 150 participants with a goal of receiving Japanese government approval to begin selling the glowing COVID-detection masks as early as 2022. But they believe the ostrich-antibody technique ultimately may lead to development of an inexpensive COVID-19 testing kit.

“We can mass-produce antibodies from ostriches at a low cost. In the future, I want to make this into an easy testing kit that anyone can use,” Tsukamoto told Kyodo News.

Harvard, MIT Also Working on COVID-19 Detecting Facemask

Not to be out done, scientists at the Massachusetts Institute of Technology (MIT) and Harvard University are participating in a similar effort to create a facemask capable of detecting COVID-19.

According to Fast Company, the MIT/Harvard COVID-19-detecting masks use the same core technology as previous paper tests for Ebola and Zika that utilize proteins and nucleic acids embedded in paper that react to target molecules.

New facemask

Fast Company explained that the mask wearer launches a test by pushing a button to release a small water reservoir embedded in the mask (above). Droplets from their breath are than analyzed by the sensors in the masks, which could be adapted to test for new COVID variants or other respiratory pathogens. In addition to eliminating the use of a nasal swab, the mask-based testing system may compete with clinical laboratory-based results. (Photo copyright: Felice Frankel/MIT.)

“Our system just allows you to add on laboratory-grade diagnostics to your normal mask wearing,” Peter Q. Nguyen, PhD, lead author of a study published in Nature Biotechnology, titled, “Wearable Materials with Embedded Synthetic Biology Sensors for Biomolecule Detection.” Nguyen is a research scientist at the Wyss Institute for Bioinspired Engineering at Harvard.

“They would especially be useful in situations where local variant outbreaks are occurring, allowing people to conveniently test themselves at home multiple times a day,” he told Fast Company.

“It’s on par specificity and sensitivity that you will get in a state-of-the-art [medical] laboratory, but with no one there,” Luis Ruben Soenksen, PhD, Venture Builder in Artificial Intelligence and Healthcare at MIT and one of the co-authors of the Nature Biotechnology study, told Fast Company.

Wearable Diagnostics

This isn’t the first-time unlikely sources have led to useful diagnostic information. In “Researchers in Japan Have Developed a ‘Smart’ Diaper Equipped with a Self-powered Biosensor That Can Monitor Blood Glucose Levels in Adults,” Dark Daily reported on another Japanese research team that developed self-powered wearable biosensors in undergarments that could detect blood glucose levels in individuals with diabetes as well as “smart diapers” that detect urine changes in babies.

As the definition of “wearable diagnostic technology” broadens, pathologists and clinical laboratory scientists may see their roles expand to include helping consumers interpret data collected by point-of-care testing technology as well as performing, evaluating, and interpreting laboratory test results that come from non-traditional sources. 

Andrea Downing Peck

Related Information:

Wearable Materials with Embedded Synthetic Biology Sensors for Biomolecule Detection

Face Mask Made with Ostrich Extract Detects COVID-19 by Glowing Under UV Light

How the Biggest Birds on Earth Could Help Fend Off Epidemics

Scientists Use Ostrich Cells to Make Glowing COVID Detection Masks

Japan Researchers Use Ostrich Cells to Make Glowing COVID-19 Detection Masks

This Mask Glows If You Have COVID

This New Face Mask Tests You for COVID while Protecting You from It

Researchers in Japan Have Developed a ‘Smart’ Diaper Equipped with a Self-powered Biosensor That Can Monitor Blood Glucose Levels in Adults

Dermatopathologists May Soon Have Useful New Tool That Uses AI Algorithm to Detect Melanoma in Wide-field Images of Skin Lesions Taken with Smartphones

MIT’s deep learning artificial intelligence algorithm demonstrates how similar new technologies and smartphones can be combined to give dermatologists and dermatopathologists valuable new ways to diagnose skin cancer from digital images

Scientists at the Massachusetts Institute of Technology (MIT) and other Boston-area research institutions have developed an artificial intelligence (AI) algorithm that detects melanoma in wide-field images of skin lesions taken on smartphones. And its use could affect how dermatologists and dermatopathologists diagnose cancer.

The study, published in Science Translational Medicine, titled, “Using Deep Learning for Dermatologist-Level Detection of Suspicious Pigmented Skin Lesions from Wide-Field Images,” demonstrates that even a common device like a smartphone can be a valuable resource in the detection of disease.

According to an MIT press release, “The paper describes the development of an SPL [Suspicious Pigmented Lesion] analysis system using DCNNs [Deep Convolutional Neural Networks] to more quickly and efficiently identify skin lesions that require more investigation, screenings that can be done during routine primary care visits, or even by the patients themselves. The system utilized DCNNs to optimize the identification and classification of SPLs in wide-field images.”

The MIT scientists believe their AI analysis system could aid dermatologists, dermatopathologists, and clinical laboratories detect melanoma, a deadly form of skin cancer, in its early stages using smartphones at the point-of-care.  

Luis Soenksen, PhD

“Our research suggests that systems leveraging computer vision and deep neural networks, quantifying such common signs, can achieve comparable accuracy to expert dermatologists,” said Luis Soenksen, PhD (above), Venture Builder in Artificial Intelligence and Healthcare at MIT and first author of the study in an MIT press release. “We hope our research revitalizes the desire to deliver more efficient dermatological screenings in primary care settings to drive adequate referrals.” The MIT study demonstrates that dermatologists, dermatopathologists, and clinical laboratories can benefit from using common technologies like smartphones in the diagnosis of disease. (Photo copyright: Wyss Institute Harvard University.)

Improving Melanoma Treatment and Patient Outcomes

Melanoma develops when pigment-producing cells called melanocytes start to grow out of control. The cancer has traditionally been diagnosed through visual inspection of SPLs by physicians in medical settings. Early-stage identification of SPLs can drastically improve the prognosis for patients and significantly reduce treatment costs. It is common to biopsy many lesions to ensure that every case of melanoma can be diagnosed as early as possible, thus contributing to better patient outcomes.

“Early detection of SPLs can save lives. However, the current capacity of medical systems to provide comprehensive skin screenings at scale are still lacking,” said Luis Soenksen, PhD, Venture Builder in Artificial Intelligence and Healthcare at MIT and first author of the study in the MIT press release.

The researchers trained their AI system by using 20,388 wide-field images from 133 patients at the Gregorio Marañón General University Hospital in Madrid, as well as publicly available images. The collected photographs were taken with a variety of ordinary smartphone cameras that are easily obtainable by consumers.

They taught the deep learning algorithm to examine various features of skin lesions such as size, circularity, and intensity. Dermatologists working with the researchers also visually classified the lesions for comparison.

Smartphone image of pigmented skin lesions

When the algorithm is “shown” a wide-field image like that above taken with a smartphone, it uses deep convolutional neural networks to analyze individual pigmented lesions and screen for early-stage melanoma. The algorithm then marks suspicious images as either yellow (meaning further inspection should be considered) or red (indicating that further inspection and/or referral to a dermatologist is required). Using this tool, dermatopathologists may be able to diagnose skin cancer and excise it in-office long before it becomes deadly. (Photo copyright: MIT.)

“Our system achieved more than 90.3% sensitivity (95% confidence interval, 90 to 90.6) and 89.9% specificity (89.6 to 90.2%) in distinguishing SPLs from nonsuspicious lesions, skin, and complex backgrounds, avoiding the need for cumbersome individual lesion imaging,” the MIT researchers noted in their Science Translational Medicine paper.

In addition, the algorithm agreed with the consensus of experienced dermatologists 88% of the time and concurred with the opinions of individual dermatologists 86% of the time, Medgadget reported.

Modern Imaging Technologies Will Advance Diagnosis of Disease

According to the American Cancer Society, about 106,110 new cases of melanoma will be diagnosed in the United States in 2021. Approximately 7,180 people are expected to die of the disease this year. Melanoma is less common than other types of skin cancer but more dangerous as it’s more likely to spread to other parts of the body if not detected and treated early.

More research is needed to substantiate the effectiveness and accuracy of this new tool before it could be used in clinical settings. However, the early research looks promising and smartphone camera technology is constantly improving. Higher resolutions would further advance development of this type of diagnostic tool.

In addition, MIT’s algorithm enables in situ examination and possible diagnosis of cancer. Therefore, a smartphone so equipped could enable a dermatologist to diagnose and excise cancerous tissue in a single visit, without the need for biopsies to be sent to a dermatopathologist.

Currently, dermatologists refer a lot of skin biopsies to dermapathologists and anatomic pathology laboratories. An accurate diagnostic tool that uses modern smartphones to characterize suspicious skin lesions could become quite popular with dermatologists and affect the flow of referrals to medical laboratories.

JP Schlingman

Related Information:

Software Spots Suspicious Skin Lesions on Smartphone Photos

An Artificial Intelligence Tool That Can Help Detect Melanoma

Using Deep Learning for Dermatologist-level Detection of Suspicious Pigmented Skin Lesions from Wide-field Images

Another Milestone for CRISPR-Cas9 Technology: First Trial Data for Treatment Delivered Intravenously

Unlike most other CRISPR/Cas-9 therapies that are ex vivo treatments in which cells are modified outside the body, this study was successful with an in vivo treatment

Use of CRISPR-Cas9 gene editing technology for therapeutic purposes can be a boon for clinical laboratories. Not only is this application a step forward in the march toward precision medicine, but it can give clinical labs the essential role of sequencing a patient’s DNA to help the referring physician identify how CRISPR-Cas9 can be used to edit the patient’s DNA to treat specific health conditions.

Most pathologists and medical lab managers know that CRISPR-Cas9 gene editing technology has been touted as one of the most significant advances in the development of therapies for inherited genetic diseases and other conditions. Now, a pair of biotech companies have announced a milestone for CRISPR-Cas9 with early clinical data involving a treatment delivered intravenously (in vivo).

The therapy, NTLA-2001, was developed by Intellia Therapeutics (NASDAQ:NTLA) and Regeneron Pharmaceuticals (NASDAQ:REGN) for treatment of hereditary ATTR (transthyretin) amyloidosis, a rare and sometimes fatal liver disease.  

As with other therapies, determining which patients are suitable candidates for specific treatments is key to the therapy’s success. Therefore, clinical laboratories will play a critical role in identifying those patients who would most likely benefit from a CRISPR-delivered therapy.

Such is the goal of precision medicine. As methods are refined that can correct unwelcome genetic mutations in a patient, the need to do genetic testing to identify and diagnose whether a patient has a specific gene mutation associated with a specific disease will increase.

The researchers published data from a Phase 1 clinical trial of NTLA-2001 in the New England Journal of Medicine (NEJM), titled, “CRISPR-Cas9 In Vivo Gene Editing for Transthyretin Amyloidosis.” They also presented their findings at the Peripheral Nerve Society (PNS) Annual Meeting.

What is NTLA-2001 and Why Is It Important?

Cleveland Clinic describes ATTR amyloidosis as a “protein misfolding disorder” involving transthyretin (TTR), a protein made in the liver. The disease leads to deposits of the protein in the heart, nerves, or other organs.

According to Intellia and Regeneron, NTLA-2001 is designed to inactivate the gene that produces the protein.

The interim clinical trial data indicated that one 0.3 mg per kilogram dose of the therapy reduced serum TTR by an average of 87% at day 28. A smaller dose of 0.1 mg per kilogram reduced TTR by an average of 52%. The researchers reported “few adverse events” in the six study patients, “and those that did occur were mild in grade.”

Current treatments, the companies stated, must be administered regularly and typically reduce TTR by about 80%.

“These are the first ever clinical data suggesting that we can precisely edit target cells within the body to treat genetic disease with a single intravenous infusion of CRISPR,” said Intellia President and CEO John Leonard, MD, in a press release. “The interim results support our belief that NTLA-2001 has the potential to halt and reverse the devastating complications of ATTR amyloidosis with a single dose.”

He added that “solving the challenge of targeted delivery of CRISPR-Cas9 to the liver, as we have with NTLA-2001, also unlocks the door to treating a wide array of other genetic diseases with our modular platform, and we intend to move quickly to advance and expand our pipeline.”

Daniel Anderson, PhD

“It’s an important moment for the field,” MIT biomedical engineer Daniel Anderson, PhD (above), told Nature. Anderson is Professor, Chemical Engineering and Institute for Medical Engineering and Science at the Koch Institute for Integrative Cancer Research at MIT. “It’s a whole new era of medicine,” he added. Advances in the use of CRISPR-Cas9 for therapeutic purposes will create the need for clinical laboratories to sequence patients’ DNA to help physicians determine the best uses for a CRISPR-Cas9 treatment protocol. (Photo copyright: Massachusetts Institute of Technology.)

In Part 2 of the Phase 1 trial, Intellia plans to evaluate the new therapy at higher doses. After the trial is complete, “the company plans to move to pivotal studies for both polyneuropathy and cardiomyopathy manifestations of ATTR amyloidosis,” the press release states.

Previous clinical trials reported results for ex vivo treatments in which cells were removed from the body, modified with CRISPR-Cas9 techniques, and then reinfused. “But to be able to edit genes directly in the body would open the door to treating a wider range of diseases,” Nature reported.

How CRISPR-Cas9 Works

On its website, CRISPR Therapeutics, a company co-founded by Emmanuelle Charpentier, PhD, a director at the Max Planck Institute for Infection Biology in Berlin, and inventor of CRISPR-Cas9 gene editing, explained that the technology “edits genes by precisely cutting DNA and then letting natural DNA repair processes take over.” It can remove fragments of DNA responsible for causing diseases, as well as repairing damaged genes or inserting new ones.

The therapies have two components: Cas9, an enzyme that cuts the DNA, and Guide RNA (gRNA), which specifies where the DNA should be cut.

Charpentier and biochemist Jennifer Doudna, PhD, Nobel Laureate, Professor of Chemistry, Professor of Biochemistry and Molecular Biology, and Li Ka Shing Chancellor’s Professor in Biomedical and Health at the University of California Berkeley, received the 2020 Nobel Prize in Chemistry for their work on CRISPR-Cas9, STAT reported.

It is important to pathologists and medical laboratory managers to understand that multiple technologies are being advanced and improved at a remarkable pace. That includes the technologies of next-generation sequencing, use of gene-editing tools like CRISPR-Cas9, and advances in artificial intelligence, machine learning, and neural networks.

At some future point, it can be expected that these technologies will be combined and integrated in a way that allows clinical laboratories to make very early and accurate diagnoses of many health conditions.

—Stephen Beale

Related Information

Intellia and Regeneron Announce Landmark Clinical Data Showing Deep Reduction in Disease-Causing Protein After Single Infusion of NTLA-2001, an Investigational CRISPR Therapy for Transthyretin (ATTR) Amyloidosis

CRISPR-Cas9 In Vivo Gene Editing for Transthyretin Amyloidosis

Landmark CRISPR Trial Shows Promise Against Deadly Disease

CRISPR Milestone Pushes Gene Editing Toward Its Promise

CRISPR Clinical Trials: A 2021 Update

CRISPR Gene Therapy: Applications, Limitations, and Implications for the Future

Diseases CRISPR Could Cure: Latest Updates on Research Studies and Human Trials

Faster, Better, Cheaper: The Rise of CRISPR in Disease Detection

The Potential of CRISPR-Based Diagnostic Assays and Treatment Approaches Against COVID-19

Two Female CRISPR Scientists Make History, Winning Nobel Prize in Chemistry for Genome-Editing Discovery

MIT’s New Nanoparticle-based Technology Detects Cancer by Using a Multimodal Combination of Urine Tests and Medical Imaging

Use of such precision diagnostics offer ‘early detection, localization, and the opportunity to monitor response to therapy,’ say the MIT scientists

Oncologists and medical laboratory scientists know that most clinical laboratory tests currently used to diagnose cancer are either based on medical imaging technologies—such as CT scans and mammography—or on molecular diagnostics that detect cancer molecules in the body’s urine or blood.

Now, in a study being conducted at the Massachusetts Institute of Technology (MIT), researchers have developed diagnostic nanoparticles that can not only detect cancer cells in bodily fluids but also image the cancer’s location. This is the latest example of how scientists are combining technologies in new ways in their efforts to develop more sensitive diagnostic tests that clinical laboratories and other providers can use to detect cancer and other health conditions.

The MIT researchers published their study in the peer-reviewed scientific journal Nature, titled, “Microenvironment-triggered Multimodal Precision Diagnostics.”

Precision diagnostics such as molecular, imaging, and analytics technologies are key tools in the pursuit of precision medicine.

“Therapeutic outcomes in oncology may be aided by precision diagnostics that offer early detection, localization, and the opportunity to monitor response to therapy,” the authors wrote, adding, “Through tailored target specificities, this modular platform has the capacity to be engineered as a pan-cancer test that may guide treatment decisions for numerous tumor type.”

Development of Multimodal Diagnostics

The MIT scientists are developing a “multimodal” diagnostic that uses molecular screening combined with imaging techniques to locate where a cancer began in the body and any metastases that are present.

“In principle, this diagnostic could be used to detect cancer anywhere in the body, including tumors that have metastasized from their original locations,” an MIT new release noted.

“This is a really broad sensor intended to respond to both primary tumors and their metastases,” said biological engineer Sangeeta Bhatia, MD, PhD (above), in the news release. Bhatia is the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science at MIT and senior author of the study.

“It can trigger a urinary signal and also allow us to visualize where the tumors are,” she added. Bhatia previously worked on the development of cancer diagnostics that can produce synthetic biomarkers which are detectable in urine samples.

Sangeeta Bhatia, MD, PhD

“The vision is that you could use this in a screening paradigm—alone or in conjunction with other tests—and we could collectively reach patients that do not have access to costly screening infrastructure today,” said Sangeeta Bhatia, MD, PhD (above), in the MIT news release. “Every year you could get a urine test as part of a general check-up. You would do an imaging study only if the urine test turns positive to then find out where the signal is coming from. We have a lot more work to do on the science to get there, but that’s where we would like to go in the long run.” (Photo copyright: NBC News.)  

Precision Diagnostic Assists Assessment of Response to Cancer Therapy

For their research, the scientists added a radioactive tracer known as copper-64 to the nanoparticles. This enabled the particles to be used for positron emission tomography (PET) imaging. The particles were coated with a peptide that induced them to accumulate at tumor sites and insert themselves into cell membranes, producing a strong imaging signal for tumor detection.

The researchers tested their diagnostic nanoparticles in mouse models of metastatic colon cancer where tumor cells had traversed to the liver or the lungs. After treating the cancer cells with a chemotherapy regimen, the team successfully used both urine and imaging to determine how the tumors were responding to the treatment.

Bhatia is hopeful that this type of diagnostic could be utilized in assessing how patients are responding to treatment therapies and the monitoring of tumor recurrence or metastasis, especially for colon cancer.

What is unique about the approach used by Bhatia’s team is that one application of the copper-64 tracer can be used in vivo, in combination with imaging technology. The other application of the copper-64 tracer is in vitro in a urine specimen that can be tested by clinical laboratories.

“Those patients could be monitored with the urinary version of the test every six months, for instance. If the urine test is positive, they could follow up with a radioactive version of the same agent for an imaging study that could indicate where the disease had spread,” Bhatia said in the news release. “We also believe the regulatory path may be accelerated with both modes of testing leveraging a single formulation.”

Multimodal nanosensors graphic

The graphic above, taken from the MIT news release, shows how “multimodal nanosensors (1) are engineered to target and respond to hallmarks in the tumor microenvironment. The nanosensors provide both a noninvasive urinary monitoring tool (2) and an on-demand medical imaging agent (3) to localize tumor metastasis and assess response to therapy,” the news release states. (Photo and caption copyright: Massachusetts Institute of Technology.)

Precision Medicine Cancer Screening Using Nano Technologies

Bhatia hopes that the nanoparticle technology may be used as a screening tool in the future to detect any type of cancer.

Her previous research with nanoparticle technology determined that a simple urine test could diagnose bacterial pneumonia and indicate if antibiotics could successfully treat that illness, the news release noted.

Nanoparticle-based technology might be adapted in the future to be part of a screening assay that determines if cancer cells are present in a patient. In such a scenario, clinical laboratories would be performing tests on urine samples while imaging techniques are simultaneously being used to diagnose and monitor cancers.

Surgical pathologists may also want to monitor the progress of this research, as it has the potential to be an effective tool for monitoring cancer patients following surgery, chemotherapy, or radiation therapy.

—JP Schlingman

Related Information

Microenvironment-triggered Multimodal Precision Diagnostics

A Noninvasive Test to Detect Cancer Cells and Pinpoint their Location

With These Nanoparticles, a Simple Urine Test Could Diagnose Bacterial Pneumonia

Researchers Create Nanoparticle That Targets Cancer to Optimize MRI Scanning; New Technology Has Potential to Reduce Number of Tissue Biopsies and Pathology Testing

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