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Genomics England Increases Goal of Whole Genome Sequencing Project from 100,000 to 500,000 Sequences in Five Years

Genomic sequencing continues to benefit patients through precision medicine clinical laboratory treatments and pharmacogenomic therapies

EDITOR’S UPDATE—Jan. 26, 2022: Since publication of this news briefing, officials from Genomics England contacted us to explain the following:

  • The “five million genome sequences” was an aspirational goal mentioned by then Secretary of State for Health and Social Care Matt Hancock, MP, in an October 2, 2018, press release issued by Genomics England.
  • As of this date a spokesman for Genomics England confirmed to Dark Daily that, with the initial goal of 100,000 genomes now attained, the immediate goal is to sequence 500,000 genomes.
  • This goal was confirmed in a tweet posted by Chris Wigley, CEO at Genomics England.

In accordance with this updated input, we have revised the original headline and information in this news briefing that follows.

What better proof of progress in whole human genome screening than the announcement that the United Kingdom’s 100,000 Genome Project has not only achieved that milestone, but will now increase the goal to 500,000 whole human genomes? This should be welcome news to clinical laboratory managers, as it means their labs will be positioned as the first-line provider of genetic data in support of clinical care.

Many clinical pathologists here in the United States are aware of the 100,000 Genome Project, established by the National Health Service (NHS) in England (UK) in 2012. Genomics England’s new goal to sequence 500,000 whole human genomes is to pioneer a “lasting legacy for patients by introducing genomic sequencing into the wider healthcare system,” according to Technology Networks.

The importance of personalized medicine and of the power of precise, accurate diagnoses cannot be understated. This announcement by Genomics England will be of interest to diagnosticians worldwide, especially doctors who diagnose and treat patients with chronic and life-threatening diseases.

Building a Vast Genomics Infrastructure

Genetic sequencing launched the era of precision medicine in healthcare. Through genomics, drug therapies and personalized treatments were developed that improved outcomes for all patients, especially those suffering with cancer and other chronic diseases. And so far, the role of genomics in healthcare has only been expanding, as Dark Daily covered in numerous ebriefings.

In the US, the National Institute of Health’s (NIH’s) Human Genome Project sequenced the first whole genome in 2003. That achievement opened the door to a new era of precision medicine.

Genomics England, which is wholly owned by the Department of Health and Social Care in the United Kingdom, was formed in 2012 with the goal of sequencing 100,000 whole genomes of patients enrolled in the UK National Health Service. That goal was met in 2018, and now the NHS aspires to sequence 500,000 genomes.

Richard Scott, MD, PhD

“The last 10 years have been really exciting, as we have seen genetic data transition from being something that is useful in a small number of contexts with highly targeted tests, towards being a central part of mainstream healthcare settings,” Richard Scott, MD, PhD (above), Chief Medical Officer at Genomics England told Technology Networks. Much of the progress has found its way into clinical laboratory testing and precision medicine diagnostics. (Photo copyright: Genomics England.)

Genomics England’s initial goals included:

  • To create an ethical program based on consent,
  • To set up a genomic medicine service within the NHS to benefit patients,
  • To make new discoveries and gain insights into the use of genomics, and
  • To begin the development of a UK genomics industry.

To gain the greatest benefit from whole genome sequencing (WGS), a substantial amount of data infrastructure must exist. “The amount of data generated by WGS is quite large and you really need a system that can process the data well to achieve that vision,” said Richard Scott, MD, PhD, Chief Medical Officer at Genomics England.

In early 2020, Weka, developer of the WekaFS, a fully parallel and distributed file system, announced that it would be working with Genomics England on managing the enormous amount of genomic data. When Genomics England reached 100,000 sequenced genomes, it had already gathered 21 petabytes of data. The organization expects to have 140 petabytes by 2023, notes a Weka case study.

Putting Genomics England’s WGS Project into Action

WGS has significantly impacted the diagnosis of rare diseases. For example, Genomics England has contributed to projects that look at tuberculosis genomes to understand why the disease is sometimes resistant to certain medications. Genomic sequencing also played an enormous role in fighting the COVID-19 pandemic.

Scott notes that COVID-19 provides an example of how sequencing can be used to deliver care. “We can see genomic influences on the risk of needing critical care in COVID-19 patients and in how their immune system is behaving. Looking at this data alongside other omics information, such as the expression of different protein levels, helps us to understand the disease process better,” he said.

What’s Next for Genomics Sequencing?

As the research continues and scientists begin to better understand the information revealed by sequencing, other areas of scientific study like proteomics and metabolomics are becoming more important.

“There is real potential for using multiple strands of data alongside each other, both for discovery—helping us to understand new things about diseases and how [they] affect the body—but also in terms of live healthcare,” Scott said.

Along with expanding the target of Genomics England to 500,000 genomes sequenced, the UK has published a National Genomic Strategy named Genome UK. This plan describes how the research into genomics will be used to benefit patients. “Our vision is to create the most advanced genomic healthcare ecosystem in the world, where government, the NHS, research and technology communities work together to embed the latest advances in patient care,” according to the Genome UK website.

Clinical laboratories professionals with an understanding of diagnostics will recognize WGS’ impact on the healthcare industry. By following genomic sequencing initiatives, such as those coming from Genomics England, pathologists can keep their labs ready to take advantage of new discoveries and insights that will improve outcomes for patients.

Dava Stewart

Related Information:

The 100,000 Genomes Project

Genome Sequencing in Modern Medicine: An Interview with Genomics England

WekaIO Accelerates Five Million Genomes Project at Genomics England

Genomics England Improved Scale and Performance for On-Premises Cluster

Whole Genome Sequencing Increases Rare Disorder Diagnosis by 31%

Genome UK: The Future of Healthcare

Common DNA Testing Method Using SNP Chips Struggles to Find Rare Variants Associated with BRCA Test, UK Researchers Find

Results of the UK study confirm for clinical laboratory professionals the importance of fully understanding the design and function of SNP chips they may be using in their labs

Here is another example of a long-established clinical laboratory test that—upon new evidence—turns out to be not as accurate as once thought. According to research conducted at the University of Exeter in Devon, UK, Single-nucleotide polymorphism (SNP) chips (aka, SNP microarrays)—technology commonly used in commercial genetic testing—is inadequate at detecting rare gene variants that can increase breast cancer risk.  

A news release announcing the results of the large-scale study states, “A technology that is widely used by commercial genetic testing companies is ‘extremely unreliable’ in detecting very rare variants, meaning results suggesting individuals carry rare disease-causing genetic variants are usually wrong.”

Why is this a significant finding for clinical laboratories? Because medical laboratories performing genetic tests that use SNP chips should be aware that rare genetic variants—which are clinically relevant to a patient’s case—may not be detected and/or reported by the tests they are running.

UK Researchers Find ‘Shockingly High False Positives’

The objective of the Exeter study published in British Medical Journal (BMJ), titled, “Use of SNP Chips to Detect Rare Pathogenic Variants: Retrospective, Population Based Diagnostic Evaluation,” was “To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population.”

The conclusion reached by the Exeter researchers, the BMJ study states, is that “SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.”  

Leigh Jackson, PhD, Lecturer in Genomic Medicine at University of Exeter and co-author of the BMJ study, said in the news release, “The number of false positives on rare genetic variants produced by SNP chips was shockingly high. To be clear: a very rare, disease-causing variant detected using [an] SNP chip is more likely to be wrong than right.” 

Caroline Wright, PhD, Professor in Genomic Medicine at the University of Exeter Medical School
In the news release, Caroline Wright, PhD (above), Professor in Genomic Medicine at the University of Exeter Medical School and senior author of the BMJ study, said, “SNP chips are fantastic at detecting common genetic variants, yet we have to recognize that tests that perform well in one scenario are not necessarily applicable to others.” She added, “We’ve confirmed that SNP chips are extremely poor at detecting very rare disease-causing genetic variants, often giving false positive results that can have profound clinical impact. These false results had been used to schedule invasive medical procedures that were both unnecessary and unwarranted.” (Photo copyright: University of Exeter.)

Large-Scale Study Taps UK Biobank Data

The Exeter researchers were concerned about cases of unnecessary invasive medical procedures being scheduled by women after learning of rare genetic variations in BRCA1 (breast cancer type 1) and BRCA2 (breast cancer 2) tests.

“The inherent technical limitation of SNP chips for correctly detecting rare genetic variants is further exacerbated when the variants themselves are linked to very rare diseases. As with any diagnostic test, the positive predictive value for low prevalence conditions will necessarily be low in most individuals. For pathogenic BRCA variants in the UK Biobank, the SNP chips had an extremely low positive predictive value (1-17%) when compared with sequencing. Were these results to be fed back to individuals, the clinical implications would be profound. Women with a positive BRCA result face a lifetime of additional screening and potentially prophylactic surgery that is unwarranted in the case of a false positive result,” they wrote.

Using UK Biobank data from 49,908 participants (55% were female), the researchers compared next-generation sequencing (NGS) to SNP chip genotyping. They found that SNP chips—which test genetic variation at hundreds-of-thousands of specific locations across the genome—performed well when compared to NGS for common variants, such as those related to type 2 diabetes and ancestry assessment, the study noted.

“Because SNP chips are such a widely used and high-performing assay for common genetic variants, we were also surprised that the differing performance of SNP chips for detecting rare variants was not well appreciated in the wider research or medical communities. Luckily, we had recently received both SNP chip and genome-wide DNA sequencing data on 50,000 individuals through the UK Biobank—a population cohort of adult volunteers from across the UK. This large dataset allowed us to systematically investigate the performance of SNP chips across millions of genetic variants with a wide range of frequencies, down to those present in fewer than 1 in 50,000 individuals,” wrote Wright and Associate Professor of Bioinformatics and Human Genetics at Exeter, Michael Weedon, PhD, in a BMJ blog post.

The Exeter researchers also analyzed data from a small group of people in the Personal Genome Project who had both SNP genotyping and sequencing information available. They focused their analysis on rare pathogenic variants in BRCA1 and BRCA2 genes.

The researchers found:

  • The rarer the variant, the less reliable the test result. For example, for “very rare variants” in less than one in 100,000 people, 84% found by SNP chips were false positives.
  • Low positive predictive values of about 16% for very rare variants in the UK Biobank.
  • Nearly all (20 of 21) customers of commercial genetic testing had at least one false positive rare disease-causing variant incorrectly genotyped.
  • SNP chips detect common genetic variants “extremely well.”

Advantages and Capabilities of SNP Chips

Compared to next-gen genetic sequencing, SNP chips are less costly. The chips use “grids of hundreds of thousands of beads that react to specific gene variants by glowing in different colors,” New Scientist explained.

Common variants of BRCA1 and BRCA2 can be found using SNP chips with 99% accuracy, New Scientist reported based on study data.

However, when the task is to find thousands of rare variants in BRCA1 and BRCA2 genes, SNP chips do not fare so well.

“It is just not the right technology for the job when it comes to rare variants. They’re excellent for the common variants that are present in lots of people. But the rarer the variant is, the less likely they are to be able to correctly detect it,” Wright told CNN.

SNP chips can’t detect all variants because they struggle to cluster needed data, the Exeter researchers explained.

“SNP chips perform poorly for genotyping rare genetic variants owing to their reliance on data clustering. Clustering data from multiple individuals with similar genotypes works very well when variants are common,” the researchers wrote. “Clustering becomes more difficult as the number of people with a particular genotype decreases.”

Clinical laboratories Using SNP Chips

The researchers at Exeter unveiled important information that pathologists and medical laboratory professionals will want to understand and monitor. Cancer patients with rare genetic variants may not be diagnosed accurately because SNP chips were not designed to identify specific genetic variants. Those patients may need additional testing to validate diagnoses and prevent harm.

—Donna Marie Pocius

Related Information:

Large-scale Study Finds Genetic Testing Technology Falsely Detects Very Rare Variants

Use of SNP Chips to Detect Rare Pathogenic Variants: Retrospective, Population-Based Diagnostic Evaluation

The Home DNA Kits “Falsely Warning of High Risk of Cancer”: DIY Genetic Tests are “Extremely Unreliable” at Detecting Rare Genetic Variants, Major New Study Warns

SNP Chips Perform Poorly for Detecting Rare Genetic Variants

Chip-based DNA Testing Wrong More than Right for Very Rare Variants

Common Genetic Tests Often Wrong When Identifying Rare Disease-Causing Variants Such as BRCA1and BRCA2, Study Says

Scientists at St. Jude Children’s Research Hospital Create 3D Map of Mouse Genome to Study How Genes Respond to Disease

The scientist also employed machine learning “to gauge how easily accessible genes are for transcription” in research that could lead to new clinical laboratory diagnostic tests

Anatomic pathologists and clinical laboratories are of course familiar with the biological science of genomics, which, among other things, has been used to map the human genome. But did you know that a three-dimensional (3D) map of a genome has been created and that it is helping scientists understand how DNA regulates its organization—and why?

The achievement took place at St. Jude Children’s Research Hospital (St. Jude) in Memphis, Tenn. Scientists there created “the first 3D map of a mouse genome” to study “the way cells organize their genomes during development,” a St. Jude news release noted.

Some experts predict that this new approach to understanding how changes happen in a genome could eventually provide new insights that anatomic pathologists and clinical laboratory scientists could find useful when working with physicians to diagnose patients and using the test results to identify the most appropriate therapy for those patients.

The St. Jude researchers published their findings in the journal Neuron in a paper titled “Nucleome Dynamics during Retinal Development.” 

Machine Learning Provides Useful Genomic Data

In addition to 3D modeling, the researchers applied machine learning to data from multiple sources to see how the organization of the genome changed at different times during development. “The changes are not random, but part of the developmental program of cells,” Dyer said in the news release.

The St. Jude study focused on the rod cells in a mouse retina. That may seem like a narrow scope, but there are more than 8,000 genes involved in retinal development in mice, during which those genes are either turned on or off.

To see what was happening among the cells, the researchers used HI-C analysis, an aspect of ultra-deep chromosome conformation capture, in situ. They found that the loops in the DNA bring together regions of the genome, allowing them to interact in specific ways.

Until this study, how those interactions took place was a mystery.

“Understanding the way cells organize their genomes during development will help us to understand their ability to respond to stress, injury and disease,” Michael Dyer, PhD (above), Chair of St. Jude’s Developmental Neurobiology Department, co-leader of the Developmental Biology and Solid Tumor Program, and Investigator at Howard Hughes Medical Institute (HHMI), said in the news release. (Photo copyright: St. Jude Children’s Research Hospital.)

The scientists also discovered there were DNA promoters, which encourage gene expression, and also DNA enhancers that increase the likelihood gene expression will occur.

“The research also included the first report of a powerful regulator of gene expression, a super enhancer, that worked in a specific cell at a specific stage of development,” the news release states. “The finding is important because the super enhancers can be hijacked in developmental cancers of the brain and other organs.”

St. Jude goes on to state, “In this study, the scientists determined that when a core regulatory circuit super-enhancer for the VSX2 gene was deleted, an entire class of neurons (bipolar neurons) was eliminated. No other defects were identified. Deletion of the VSX2 gene causes many more defects in retinal development, so the super-enhancer is highly specific to bipolar neurons.”

The St. Jude researchers developed a genetic mouse model of the defect that scientists are using to study neural circuits in the retina, the news release states.

Research Technologist Victoria Honnell (left); Developmental Neurobiologist Jackie Norrie, PhD (center); and Postdoctoral Researcher Marybeth Lupo, PhD (right), work in the St. Jude clinical laboratory of Michael Dyer, PhD, using 3D genomic mapping to study gene regulation during development and disease. (Photo copyright: St. Jude Children’s Research Hospital.)

DNA Loops May Matter to Pathology Sooner Rather than Later

Previous researcher studies primarily used genomic sequencing technology to locate and investigate alterations in genes that lead to disease. In the St. Jude study, the researchers examined how DNA is packaged. If the DNA of a single cell could be stretched out, it would be more than six feet long. To fit into the nucleus of a cell, DNA is looped and bundled into a microscopic package. The St. Jude scientists determined that how these loops are organized regulates how the cell functions and develops.

Scientists around the world will continue studying how the loops in DNA impact gene regulation and how that affects the gene’s response to disease. At St. Jude Children’s Research Hospital, Dyer and his colleagues “used the same approach to create a 3D genomic map of the mouse cerebellum, a brain structure where medulloblastoma can develop. Medulloblastoma is the most common malignant pediatric brain tumor,” noted the St. Jude’s news release.

In addition to providing an understanding of how genes function, these 3D studies are providing valuable insight into how some diseases develop and mature. While nascent research such as this may not impact pathologists and clinical laboratories at the moment, it’s not a stretch to think that this work may lead to greater understanding of the pathology of diseases in the near future.

—Dava Stewart

Related Information:

Researchers Move Beyond Sequencing and Create a 3D Genome

Nucleome Dynamics During Retinal Development

Whole Genome Sequencing

HiPiler: Visual Exploration of Large Genome Interaction Matrices with Interactive Small Multiples

Reorganization of 3D Genome Structure May Contribute to Gene Regulatory Evolution in Primates

An Overview of Methods for Reconstructing 3D Chromosome and Genome Structures from Hi-C Data

Saarland University Researchers Use Blood Samples from Zoo Animals to Help Scientists Find Biomarkers That Speed Diagnoses in Humans

Using animal blood, the researchers hope to improve the accuracy of AI driven diagnostic technology

What does a cheetah, a tortoise, and a Humboldt penguin have in common? They are zoo animals helping scientists at Saarland University in Saarbrücken, Germany, find biomarkers that can help computer-assisted diagnoses of diseases in humans at early stages. And they are not the only animals lending a paw or claw.

In their initial research, the scientists used blood samples that had been collected during routine examinations of 21 zoo animals between 2016 and 2018, said a news release. The team of bioinformatics and human genetics experts worked with German zoos Saarbrücken and Neunkircher for the study. The project progresses, and thus far, they’ve studied the blood of 40 zoo animals, the release states.

This research work may eventually add useful biomarkers and assays that clinical laboratories can use to support physicians as they diagnose patients, select appropriate therapies, and monitor the progress of their patients. As medical laboratory scientists know, for many decades, the animal kingdom has been the source of useful insights and biological materials that have been incorporated into laboratory assays.

“Measuring the molecular blood profiles of animals has never been done before this way,” said Andreas Keller, PhD, Saarland University Bioinformatics Professor and Chair for Clinical Bioinformatics, in the news release. The Saarland researchers published their findings in Nucleic Acids Research, an Oxford Academic journal.

“Studies on sncRNAs [small non-coding RNAs] are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens,” the article states.

Can Animals Improve the Accuracy of AI to Detect Disease in Humans?

In their research, Saarland scientists rely on advanced next-generation sequencing (NGS) technology and artificial intelligence (AI) to sequence RNA and microRNA. Their goal is to better understand the human genome and cause of diseases.

However, the researchers perceived an inability for AI and machine learning to discern real biomarker patterns from those that just seemed to fit.

“The machine learning methods recognize the typical patterns, for example for a lung tumor or Alzheimer’s disease. However, it is difficult for artificial intelligence to learn which biomarker patterns are real and which only seem to fit the respective clinical picture. This is where the blood samples of the animals come into play,” Keller states in the news release.

“If a biomarker is evolutionarily conserved, i.e. also occurs in other species in similar form and function, it is much more likely that it is a resilient biomarker,” Keller explained. “The new findings are now being incorporated into our computer models and will help us to identify the correct biomarkers even more precisely in the future.”

Andreas Keller, PhD (left), and zoo director Richard Francke (right), hold a pair of radiated tortoises that participated in the Saarland University study. (Photo copyright: Oliver Dietze/Saarland University.)

Microsampling Aids Blood Collection at Zoos

The researchers used a Neoteryx Mitra blood collection kit to secure samples from the animals and volunteers. Dark Daily previously reported on this microsampling technology in, “Innovations in Microsampling Blood Technology Mean More Patients Can Have Blood Tests at Home, and Clinical Laboratories May Advance Toward Precision Medicine Goals,” November 28, 2018.

“Because blood can be obtained in a standardized manner and miRNA expression patterns are technically very stable, it is easy to accurately compare expression between different animal species. In particular, dried blood spots or microsampling devices appear to be well suited as containers for miRNAs,” the researchers wrote in Nucleic Acids Research.

Animal species that participated in the study include:

Additionally, human volunteers contributed blood specimens for a total of 19 species studied. The scientists reported success in capturing data from all of the species. They are integrating the information into their computer models and have developed a public database of their findings for future research.

“With our study, we provide a large collection of small RNA NGS expression data of species that have not been analyzed before in great detail. We created a comprehensive publicly available online resource for researchers in the field to facilitate the assessment of evolutionarily conserved small RNA sequences,” the researchers wrote in their paper.         

Clinical Laboratory Research and Zoos: A Future Partnership?

This novel involvement of zoo animals in research aimed at improving the ability of AI driven diagnostics to isolate and identify human disease is notable and worth watching. It is obviously pioneering work and needs much additional research. At the same time, these findings give evidence that there is useful information to be extracted from a wide range of unlikely sources—in this case, zoo animals.

Also, the use of artificial intelligence to search for useful patterns in the data is a notable part of what these researchers discovered. It is also notable that this research is focused on sequencing DNA and RNA of the animals involved with the goal of identifying sequences that are common across several species, thus demonstrating the common, important functions they serve.

In coming years, those clinical laboratories doing genetic testing in support of patient care may be incorporating some of this research group’s findings into their interpretation of certain gene sequences.

—Donna Marie Pocius

Related Information:

Blood Samples from the Zoo Help Predict Diseases in Humans

The sncRNA Zoo: A Repository for Circulating Small Noncoding RNAs in Animals

ASRA Public Database of Small Non-Coding RNAs

Innovations in Microsampling Blood Technology Mean More Patients Can Have Blood Tests at Home and Clinical Laboratories May Advance Toward Precision Medicine Goals

University of Queensland Researches May Have Found a Universal Biomarker That Identifies Cancer in Various Human Cells in Just 10 Minutes!

This research could lead to a useful liquid biopsy test that would be a powerful new tool for clinical laboratories and anatomic pathologists

Cancer researchers have long sought the Holy Grail of diagnostics—a single biomarker that can quickly detect cancer from blood or biopsied tissue. Now, researchers in Australia may have found that treasure. And the preliminary diagnostic test they have developed reportedly can return results in just 10 minutes with 90% accuracy.

In a news release, University of Queensland researchers discussed identifying a “simple signature” that was common to all forms of cancer, but which would stand out among healthy cells. This development will be of interest to both surgical pathologists and clinical laboratory managers. Many researchers looking for cancer markers in blood are using the term “liquid biopsies” to describe assays they hope to develop which would be less invasive than a tissue biopsy.

“This unique nano-scaled DNA signature appeared in every type of breast cancer we examined, and in other forms of cancer including prostate, colorectal, and lymphoma,” said Abu Sina, PhD, Postdoctoral Research Fellow at the Australian Institute for Bioengineering and Nanotechnology (AIBN), University of Queensland (UQ), in the news release.

“We designed a simple test using gold nanoparticles that instantly change color to determine if the three-dimensional nanostructures of cancer DNA are present,’ said Matt Trau, PhD, Professor of Chemistry at the University of Queensland, and Deputy Director and Co-Founder of UQ’s AIBN, in the news release.

The team’s test is preliminary, and more research is needed before it will be ready for Australia’s histopathology laboratories (anatomic pathology labs in the US). Still, UQ’s research is the latest example of how increased knowledge of DNA is making it possible for researchers to identify new biomarkers for cancer and other diseases.

“We certainly don’t know yet whether it’s the holy grail for all cancer diagnostics, but it looks really interesting as an incredibly simple universal marker of cancer, and as an accessible and inexpensive technology that doesn’t require complicated lab-based equipment like DNA sequencing,” Trau added.

Such a diagnostic test would be a boon to clinical laboratories and anatomic pathology groups involved in cancer diagnosis and the development of precision medicine treatments.

One Test, 90% Accuracy, Many Cancers

The UQ researchers published their study in the journal Nature Communications. In it, they noted that “Epigenetic reprogramming in cancer genomes creates a distinct methylation landscape encompassing clustered methylation at regulatory regions separated by large intergenic tracks of hypomethylated regions. This methylation landscape that we referred to as ‘Methylscape’ is displayed by most cancer types, thus may serve as a universal cancer biomarker.”

While methyl patterning is not new, the UQ researchers say they were the first to note the effects of methyl pattern in a particular solution—water. With the aid of transmission electron microscopy, the scientists saw DNA fragments in three-dimensional structures in the water. But they did not observe the signature in normal tissues in water.

Methylation are marks that indicate whether pieces of DNA should be read,” Dino DiCarlo, PhD, Professor in the Department of Bioengineering and Biomedical Engineering, University of California Los Angeles (UCLA) and Director of Cancer Nanotechnology at UCLA’s Jonsson Comprehensive Cancer Center, told USA Today.


“To date, most research has focused on the biological consequences of DNA Methylscape changes, whereas its impact on DNA physicochemical properties remains unexplored,” UQ scientists Matt Trau, PhD (left), Abu Sina, PhD (center), and Laura Carrascosa (right), wrote in their study. “We exploit these Methylscape differences to develop simple, highly sensitive, and selective electrochemical or colorimetric one-step assays for the detection of cancer.” (Photo copyright: University of Queensland.)

Their test averaged 90% accuracy during the testing of 200 human cancer samples. Furthermore, the researchers found the DNA structure to be the same in breast, prostate, and bowel cancers, as well as lymphomas, noted The Conversation.

“We find that DNA polymeric behavior is strongly affected by differential patterning of methylcytosine leading to fundamental differences in DNA solvation and DNA-gold affinity between cancerous and normal genomes,” the researchers wrote in NatureCommunications.“We exploit these methylscape differences to develop simple, highly sensitive, and selective electrochemical or one-step assays for detection of cancer.”

Next Steps for the “Gold Test”

“This approach represents an exciting step forward in detecting tumor DNA in blood samples and opens up the possibility of a generalized blood-based test to detect cancer, Ged Brady, PhD, Cancer Research UK Manchester Institute, told The Oxford Scientist. “Further clinical studies are required to evaluate the full clinic potential of the method.”

Researchers said the next step is a larger clinical study to explore just how fast cancer can be detected. They expressed interest in finding different cancers in body fluids and at various stages. Another opportunity they envision is to use the cancer assay with a mobile device.

DiCarlo told USA Today that such a mobile test could be helpful to clinicians needing fast answers for people in rural areas. However, he’s also concerned about false positives. “You don’t expect all tumors to have the same methylation pattern because there’s so many different ways that cancer can develop,” he told USA Today. “There are some pieces that don’t exactly align logically.”

The UQ researchers have produced an intriguing study that differs from other liquid biopsy papers covered by Dark Daily. While their test may need to be used in combination with other diagnostic tests—MRI, mammography, etc.—it has the potential to one day be used by clinical laboratories to quickly reveal diverse types of cancers.  

—Donna Marie Pocius

Related Information:

Nano-Signature Discovery Could Revolutionize Cancer Diagnosis

Epigentically Reprogrammed Methylation Landscape Drives the DNA Self-Assembly and Serves as a Universal Cancer Biomarker

One Test to Diagnose Them All: Researchers Exploit Cancers’ Unique DNA Signature

Cancer Researchers in Australia Develop Universal Blood Test

Universal 10-Minute Cancer Test in Sight

A 10-Minute, Universal Blood Test for Cancer

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