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.
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.
“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.
Newly combined digital pathology, artificial intelligence (AI), and omics technologies are providing anatomic pathologists and medical laboratory scientists with powerful diagnostic tools
Add “spatial transcriptomics” to the growing list of “omics” that have the potential to deliver biomarkers which can be used for earlier and more accurate diagnoses of diseases and health conditions. As with other types of omics, spatial transcriptomics might be a new tool for surgical pathologists once further studies support its use in clinical care.
Among this spectrum of omics is spatial transcriptomics, or ST for short.
Spatial Transcriptomics is a groundbreaking and powerful molecular profiling method used to measure all gene activity within a tissue sample. The technology is already leading to discoveries that are helping researchers gain valuable information about neurological diseases and breast cancer.
Marriage of Genetic Imaging and Sequencing
Spatial transcriptomics is a term used to describe a variety of methods designed to assign cell types that have been isolated and identified by messenger RNA (mRNA), to their locations in a histological section. The technology can determine subcellular localization of mRNA molecules and can quantify gene expression within anatomic pathology samples.
In “Spatial: The Next Omics Frontier,” Genetic Engineering and Biotechnology News (GEN) wrote, “Spatial transcriptomics gives a rich, spatial context to gene expression. By marrying imaging and sequencing, spatial transcriptomics can map where particular transcripts exist on the tissue, indicating where particular genes are expressed.”
In an interview with Technology Networks, George Emanuel, PhD, co-founder of life-science genomics company Vizgen, said, “Spatial transcriptomic profiling provides the genomic information of single cells as they are intricately spatially organized within their native tissue environment.
“With techniques such as single-cell sequencing, researchers can learn about cell type composition; however, these techniques isolate individual cells in droplets and do not preserve the tissue structure that is a fundamental component of every biological organism,” he added.
“Direct spatial profiling the cellular composition of the tissue allows you to better understand why certain cell types are observed there and how variations in cell state might be a consequence of the unique microenvironment within the tissue,” he continued. “In this way, spatial transcriptomics allows us to measure the complexity of biological systems along the axes that are most relevant to their function.”
“Although spatial genomics is a nascent field, we are already seeing broad interest among the community and excitement across a range of questions, all the way from plant biology to improving our understanding of the complex interactions of the tumor microenvironment,” George Emanuel, PhD (above), told Technology Networks. Oncologists, anatomic pathologists, and medical laboratory scientists my soon see diagnostics that take advantage of spatial genomics technologies. (Photo copyright: Vizgen.)
According to 10x Genomics, “spatial transcriptomics utilizes spotted arrays of specialized mRNA-capturing probes on the surface of glass slides. Each spot contains capture probes with a spatial barcode unique to that spot.
“When tissue is attached to the slide, the capture probes bind RNA from the adjacent point in the tissue. A reverse transcription reaction, while the tissue is still in place, generates a cDNA [complementary DNA] library that incorporates the spatial barcodes and preserves spatial information.
“Each spot contains approximately 200 million capture probes and all of the probes in an individual spot share a barcode that is specific to that spot.”
“The highly multiplexed transcriptomic readout reveals the complexity that arises from the very large number of genes in the genome, while high spatial resolution captures the exact locations where each transcript is being expressed,” Emanuel told Technology Networks.
Spatial Transcriptomics for Breast Cancer and Neurological Diagnostics
In that paper, the authors wrote “we envision that in the coming years we will see simplification, further standardization, and reduced pricing for the ST protocol leading to extensive ST sequencing of samples of various cancer types.”
Spatial transcriptomics is also being used to research neurological conditions and neurodegenerative diseases. ST has been proven as an effective tool to hunt for marker genes for these conditions as well as help medical professionals study drug therapies for the brain.
“You can actually map out where the target is in the brain, for example, and not only the approximate location inside the organ, but also in what type of cells,” Malte Kühnemund, PhD, Director of Research and Development at 10x Genomics, told Labiotech.eu. “You actually now know what type of cells you are targeting. That’s completely new information for them and it might help them to understand side effects and so on.”
The field of spatial transcriptomics is rapidly moving and changing as it branches out into more areas of healthcare. New discoveries within ST methodologies are making it possible to combine it with other technologies, such as Artificial Intelligence (AI), which could lead to powerful new ways oncologists and anatomic pathologists diagnose disease.
“I think it’s going to be tricky for pathologists to look at that data,” Kühnemund said. “I think this will go hand in hand with the digital pathology revolution where computers are doing the analysis and they spit out an answer. That’s a lot more precise than what any doctor could possibly do.”
Spatial transcriptomics certainly is a new and innovative way to look at tissue biology. However, the technology is still in its early stages and more research is needed to validate its development and results.
Nevertheless, this is an opportunity for companies developing artificial intelligence tools for analyzing digital pathology images to investigate how their AI technologies might be used with spatial transcriptomics to give anatomic pathologists a new and useful diagnostic tool.
Researchers are discovering it’s possible to determine a person’s age based on the amount of protein in the blood, but the technology isn’t always correct
Mass spectrometry is increasingly finding its way into clinical laboratories and with it—proteomics—the study of proteins in the human body. And like the human genome, scientists are discovering that protein plays an integral part in the aging process.
This is a most interesting research finding. Might medical laboratories someday use proteomic biomarkers to help physicians gauge the aging progression in patients? Might this diagnostic capability give pathologists and laboratory leaders a new product line for direct-to-consumer testing that would be a cash-paying, fast-growing, profitable clinical laboratory testing service? If so, proteomics could be a boon to clinical laboratories worldwide.
When research into genomics was brand-new, virtually no one imagined that someday the direct-to-consumer lab testing model would offer genetic testing to the public and create a huge stream of revenue for clinical laboratories that process genetic tests. Now, research into protein and aging might point to a similar possibility for proteomics.
For example, through proteomics, researchers led by Benoit Lehallier, PhD, Biostatistician, Instructor of Neurology and Neurological Sciences, and senior author Tony Wyss-Coray, PhD, Professor of Neurology and Neurological Sciences and co-director of the Stanford Alzheimer’s Disease Research Center at Stanford University in California, gained an understanding of aging that suggest intriguing possibilities for clinical laboratories.
In their study, published in Nature, titled, “Undulating Changes in Human Plasma Proteome Profiles Across the Lifespan,” the scientists stated that aging doesn’t happen in a consistent process over time, reported Science Alert.
The Stanford researchers also found that they can accurately
determine a person’s age based on the levels of certain proteins in his or her
blood.
Additionally, the study of proteomics may finally explain why blood from young people can have a rejuvenating effect on elderly people’s brains, noted Scientific American.
Each of these findings is important on its own, but taken
together, they may have interesting implications for pathologists who follow
the research. And medical laboratory leaders may find opportunities in mass
spectrometry in the near future, rather than decades from now.
Three Distinct Stages in Aging and Other Findings
The Stanford study found that aging appears to happen at
three distinct points in a person’s life—around the ages 34, 60, and 78—rather
than being a slow, steady process.
The researchers measured and compared levels of nearly 3,000
specific proteins in blood plasma taken from healthy people between the ages of
18 and 95 years. In the published study, the authors wrote, “This new approach
to the study of aging led to the identification of unexpected signatures and
pathways that might offer potential targets for age-related diseases.”
Along with the findings regarding the timeline for aging, the researchers found that about two-thirds of the proteins that change with age differ significantly between men and women. “This supports the idea that men and women age differently and highlights the need to include both sexes in clinical studies for a wide range of diseases,” noted a National Institutes of Health (NIH) report.
“We’ve known for a long time that measuring certain proteins in the blood can give you information about a person’s health status—lipoproteins for cardiovascular health, for example,” stated Wyss-Coray in the NIH report. “But it hasn’t been appreciated that so many different proteins’ levels—roughly a third of all the ones we looked at—change markedly with advancing age.”
Tony Wyss-Coray, PhD (above), Professor of Neurology and Neurological Sciences at Stanford University, was senior author of the proteomics study that analyzed blood plasma from 4,263 people between the ages 18-95. “Proteins are the workhorses of the body’s constituent cells, and when their relative levels undergo substantial changes, it means you’ve changed, too,” he said in a Stanford Medicine news article. “Looking at thousands of them in plasma gives you a snapshot of what’s going on throughout the body.” (Photo copyright: Stanford University.)
Differentiating Aging from Disease
Previous research studies also found it is indeed possible
to measure a person’s age from his or her “proteomic signature.”
The researchers published their findings in Aging Cell, a peer-reviewed open-access journal of the Anatomical Society in the UK, titled, “Plasma Proteomic Signature of Age in Healthy Humans.” In it, the authors wrote, “Our results suggest that there are stereotypical biological changes that occur with aging that are reflected by circulating proteins.”
The fact that chronological age can be determined through a
person’s proteomic signature suggests researchers could separate aging from
various diseases. “Older age is the main risk factor for a myriad of chronic
diseases, and it is invariably associated with progressive loss of function in
multiple physiological systems,” wrote the researchers, adding, “A challenge in
the field is the need to differentiate between aging and diseases.”
Can Proteins Cause Aging?
Additionally, the Stanford study found that changes in protein levels might not simply be a characteristic of aging, but may actually cause it, a Stanford Medicine news article notes.
“Changes in the levels of numerous proteins that migrate
from the body’s tissues into circulating blood not only characterize, but quite
possibly cause, the phenomenon of aging,” Wyss-Coray said.
Can Proteins Accurately Predict Age? Not Always
There were, however, some instances where the protein levels inaccurately predicted a person’s age. Some of the samples the Stanford researchers used were from the LonGenity research study conducted by the Albert Einstein College of Medicine, which investigated “why some people enjoy extremely long life spans, with physical health and brain function far better than expected in the 9th and 10th decades of life,” the study’s website notes.
That study included a group of exceptionally long-lived Ashkenazi Jews, who have a “genetic proclivity toward exceptionally good health in what for most of us is advanced old age,” according to the Stanford Medicine news article.
“We had data on hand-grip strength and cognitive function
for that group of people. Those with stronger hand grips and better measured
cognition were estimated by our plasma-protein clock to be younger than they
actually were,” said Wyss-Coray. So, physical condition is a factor in
proteomics’ ability to accurately prediction age.
Although understanding the connections between protein in
the blood, aging, and disease is in early stages, it is clear additional
research is warranted. Not too long ago the idea of consumers having their DNA
sequenced from a home kit for fun seemed like fantasy.
However, after multiple FDA approvals, and the success of
companies like Ancestry, 23andMe, and the clinical laboratories that serve them,
the possibility that proteomics might go the same route does not seem so
far-fetched.
Experts list the top challenges facing widespread adoption of proteomics in the medical laboratory industry
Year-by-year, clinical
laboratories find new ways to use mass spectrometry to
analyze clinical specimens, producing results that may be more precise than
test results produced by other methodologies. This is particularly true in the
field of proteomics.
However, though mass spectrometry is highly accurate and
fast, taking only minutes to convert a specimen into a result, it is not fully
automated and requires skilled technologists to operate the instruments.
Thus, although the science of proteomics is advancing
quickly, the average pathology laboratory isn’t likely to be using mass
spectrometry tools any time soon. Nevertheless, medical
laboratory scientists are keenly interested in adapting mass spectrometry
to medical lab test technology for a growing number of assays.
Molly Campbell, Science Writer and Editor in Genomics, Proteomics, Metabolomics, and Biopharma at Technology Networks, asked proteomics experts “what, in their opinion, are the greatest challenges currently existing in proteomics, and how can we look to overcome them?” Here’s a synopsis of their answers:
Lack of High Throughput Impacts Commercialization
Proteomics isn’t as efficient as it needs to be to be
adopted at the commercial level. It’s not as efficient as its cousin genomics. For it to become
sufficiently efficient, manufacturers must be involved.
John Yates
III, PhD, Professor, Department of Molecular Medicine at Scripps Research California
campus, told Technology
Networks, “One of the complaints from funding agencies is that you can
sequence literally thousands of genomes very quickly, but you can’t do the same
in proteomics. There’s a push to try to increase the throughput of proteomics
so that we are more compatible with genomics.”
For that to happen, Yates says manufacturers need to
continue advancing the technology. Much of the research is happening at
universities and in the academic realm. But with commercialization comes
standardization and quality control.
“It’s always exciting when you go to ASMS [the conference for the American Society
for Mass Spectrometry] to see what instruments or technologies are going to be
introduced by manufacturers,” Yates said.
There are signs that commercialization isn’t far off. SomaLogic, a privately-owned American protein
biomarker discovery and clinical diagnostics company located in Boulder, Colo.,
has reached the commercialization stage for a proteomics assay platform called SomaScan. “We’ll be
able to supplant, in some cases, expensive diagnostic modalities simply from a
blood test,” Roy
Smythe, MD, CEO of SomaLogic, told Techonomy.
The graphic above illustrates the progression mass spectrometry took during its development, starting with small proteins (left) to supramolecular complexes of intact virus particles (center) and bacteriophages (right). Because of these developments, today’s medical laboratories have more assays that utilize mass spectrometry. (Photo copyright: Technology Networks/Heck laboratory, Utrecht University, the Netherlands.)
Achieving the Necessary Technical Skillset
One of the main reasons mass spectrometry is not more widely
used is that it requires technical skill that not many professionals possess.
“For a long time, MS-based proteomic analyses were technically demanding at
various levels, including sample processing, separation science, MS and the
analysis of the spectra with respect to sequence, abundance and
modification-states of peptides and proteins and false discovery rate
(FDR) considerations,” Ruedi
Aebersold, PhD, Professor of Systems Biology at the Institute of Molecular Systems Biology (IMSB) at
ETH Zurich, told Technology
Networks.
Aebersold goes on to say that he thinks this specific
challenge is nearing resolution. He says that, by removing the problem created
by the need for technical skill, those who study proteomics will be able to
“more strongly focus on creating interesting new biological or clinical
research questions and experimental design.”
Yates agrees. In a paper titled, “Recent Technical Advances in
Proteomics,” published in F1000 Research, a peer-reviewed open research
publishing platform for scientists, scholars, and clinicians, he wrote, “Mass
spectrometry is one of the key technologies of proteomics, and over the last
decade important technical advances in mass spectrometry have driven an
increased capability of proteomic discovery. In addition, new methods to
capture important biological information have been developed to take advantage
of improving proteomic tools.”
No High-Profile Projects to Stimulate Interest
Genomics had the Human Genome Project
(HGP), which sparked public interest and attracted significant funding. One of
the big challenges facing proteomics is that there are no similarly big,
imagination-stimulating projects. The work is important and will result in
advances that will be well-received, however, the field itself is complex and difficult
to explain.
Emanuel
Petricoin, PhD, is a professor and co-director of the Center for Applied
Proteomics and Molecular Medicine at George
Mason University. He told Technology
Networks, “the field itself hasn’t yet identified or grabbed onto a
specific ‘moon-shot’ project. For example, there will be no equivalent to the
human genome project, the proteomics field just doesn’t have that.”
He added, “The equipment needs to be in the background and
what you are doing with it needs to be in the foreground, as is what happened
in the genomics space. If it’s just about the machinery, then proteomics will
always be a ‘poor step-child’ to genomics.”
Democratizing Proteomics
Alexander
Makarov, PhD, is Director of Research in Life Sciences Mass Spectrometry
(MS) at Thermo Fisher
Scientific. He told Technology
Networks that as mass spectrometry grew into the industry we have today,
“each new development required larger and larger research and development teams
to match the increasing complexity of instruments and the skyrocketing
importance of software at all levels, from firmware to application. All this
extends the cycle time of each innovation and also forces [researchers] to
concentrate on solutions that address the most pressing needs of the scientific
community.”
Makarov describes this change as “the increasing democratization of MS,” and says that it “brings with it new requirements for instruments, such as far greater robustness and ease-of-use, which need to be balanced against some aspects of performance.”
One example of the increasing democratization of MS may be
several public proteomic datasets available to scientists. In European
Pharmaceutical Review, Juan
Antonio Viscaíno, PhD, Proteomics Team Leader at the European Bioinformatics Institute (EMBL-EBI)
wrote, “These datasets are increasingly reused for multiple applications, which
contribute to improving our understanding of cell biology through proteomics
data.”
Sparse Data and Difficulty Measuring It
Evangelia
Petsalaki, PhD, Group Leader EMBL-EBI, told Technology
Networks there are two related challenges in handling proteomic data.
First, the data is “very sparse” and second “[researchers] have trouble
measuring low abundance proteins.”
Petsalaki notes, “every time we take a measurement, we
sample different parts of the proteome or phosphoproteome and
we are usually missing low abundance players that are often the most important
ones, such as transcription
factors.” She added that in her group they take steps to mitigate those
problems.
“However, with the advances in MS technologies developed by
many companies and groups around the world … and other emerging technologies
that promise to allow ‘sequencing’ proteomes, analogous to genomes … I expect
that these will not be issues for very long.”
So, what does all this mean for clinical laboratories? At the
current pace of development, its likely assays based on proteomics could become
more common in the near future. And, if throughput and commercialization ever
match that of genomics, mass spectrometry and other proteomics tools could
become a standard technology for pathology laboratories.
This new atlas of leukemia proteomes may prove useful for medical laboratories and pathologists providing diagnostic and prognostic services to physicians treating leukemia patients
Researchers at the University of Texas at San Antonio (UTSA) and the University of Texas MD Anderson Cancer Center created the online atlases—categorized into adult and pediatric datasets—to “provide quantitative, molecular hallmarks of leukemia; a broadly applicable computational approach to quantifying heterogeneity and similarity in molecular data; and a guide to new therapeutic targets for leukemias,” according to the Leukemia Atlases website.
In building the Leukemia Proteome Atlases, the researchers identified and classified protein signatures that are present when patients are diagnosed with AML. Their goal is to improve survival rates and aid scientific research for this deadly disease, as well as develop personalized, effective precision medicine treatments for patients.
To perform the study, the scientists looked at the proteomic screens of 205
biopsies of patients with AML and analyzed the genetic, epigenetic, and
environmental diversity in the cancer cells. Their analysis “revealed 154 functional
patterns based on common molecular pathways, 11 constellations of correlated
functional patterns, and 13 signatures that stratify the outcomes of patients.”
Amina Qutub, PhD, Associate Professor at UTSA and one of the authors of the research, told UTSA Today, “Acute myelogenous leukemia presents as a cancer so heterogeneous that it is often described as not one, but a collection of diseases.”
“To decipher the clues found in proteins from blood and bone marrow of leukemia patients, we developed a new computer analysis—MetaGalaxy—that identifies molecular hallmarks of leukemia,” noted Amina Qutub, PhD (above), UTSA Professor of Biomedical Engineering and one of the UTSA study’s authors. “These hallmarks are analogous to the way constellations guide navigation of the stars: they provide a map to protein changes for leukemia,” she concluded. (Photo copyright: UTSA.)
To better understand the proteomic levels associated with AML, and share their work globally with other scientists, the researchers created the Leukemia Proteome Atlases web portal. The information is displayed in an interactive format and divided into adult and pediatric databases. The atlases provide quantitative, molecular hallmarks of AML and a guide to new therapeutic targets for the disease.
The NCI predicts there will be approximately 21,540 new
cases of AML diagnosed this year. They will account for about 1.2% of all new
cancer cases. The disease will be responsible for approximately 10,920 deaths in
2019, or 1.8% of all cancer deaths. In 2016, there were an estimated 61,048
people living with AML in the US.
“Our ‘hallmark’ predictions are being experimentally tested
through drug screens and can be ‘programmed’
into cells through synthetic manipulation of proteins,” Qutub continued. “A
next step to bring this work to the clinic and impact
patient care is testing whether these signatures lead to the aggressive growth
or resistance to chemotherapy observed in
leukemia patients.
“At the same time, to rapidly accelerate research in
leukemia and advance the hunt for treatments,
we provide the hallmarks in an online compendium [LeukemiaAtlas.org] where fellow
researchers and oncologists worldwide can build from the resource, tools, and
findings.”
By mapping AML patients from the proteins present in their
blood and bone marrow, the researchers hope that healthcare professionals will
be able to better categorize patients into risk groups and improve treatment
outcomes and survival rates for this aggressive form of cancer.
The Leukemia Proteome Atlases are another example of the
trend where researchers work together to compile data from patients and share
that information with other scientists and medical professionals. Hopefully, having
this type of data readily available in a searchable database will enable
researchers—as well as clinical laboratory scientists and pathologists—to gain
a better understanding of AML and benefit cancer patients through improved
diagnosis, treatment, and monitoring.
