A significant new frontier in medical diagnostics: “Fingerprinting” individual human cells

Associate Professor Joseph Powell & José Alquicira-Hernández

Researchers have developed a method that allows them to identify single cells with a unique genomic profile from a tissue sample.

Researchers say a new method to analyse data from individual human cells could be a step-change for diagnosing some of the most devastating diseases, including cancer and autoimmune disease.

By combining single cell analysis techniques with machine learning algorithms, a team led by researchers at the Garvan Institute of Medical Research has developed a method to ‘fingerprint’ human cells.

The method, called ‘scPred’, published in the journal Genome Biology, has the potential to allow earlier detection of cancer, identify the cells at the root of autoimmune disease, and help personalise treatments to individual patients.

“We’ve developed a new way to identify very specific types of cells, which has put us at the beginning of a significant new frontier in medical diagnostics,” says Associate Professor Joseph Powell, Director of the Garvan-Weizmann Centre for Cellular Genomics, who led the study and is now working to translate the method to diagnostic tests for clinical use.

A closer look at human cells

“For a long time we’ve mainly classified different cells in the human body based on a limited number of markers found on the cell surface or inside the cell. What we’re learning now is that underneath one ‘type’, there is a huge diversity of different cell types – for instance, even though different cancer cells could all have the same cell surface markers, only a subgroup of those cells may actually form a metastatic tumour,” explains Associate Professor Powell.

The researchers developed a new method of analysing transcripts of individual cells – a measure of which genes are active in different cells, which provides extensive information of what makes cells unique.

The team’s method scPred solved the challenge of determining what within the vast amounts of generated transcript data can provide the most useful information that defines a cell type.

“Our scPred method first collapses all the transcript data from a single cell – instead of trying to estimate 20,000 things at once it works out which patterns of those 20,000 have the most predictive power in distinguishing one cell type from another cell type.

scPred then ‘trains’ a statistical model on those patterns to test what features make a certain cell type ‘most different’ from another cell – which can be thought of as a unique fingerprint,” explains first author José Alquicira-Hernández, a PhD student at the University of Queensland.

A new dimension on diagnostics

Once a certain cell type has been ‘fingerprinted’, researchers can use the trained model to look for that same cell type in any other sample, in datasets from anywhere in the world.

The researchers have validated the scPred approach using datasets of colorectal cancer cells analysed by collaborators at Stanford University in the United States. Using scPred models, the researchers were able to identify cancer cells from a tissue sample with over 98% accuracy.

The researchers say their method adds enormous improvements in the resolution of cell types, and may uncover diseased cells that are outside the scope of current medical diagnostics.

Translation to patients

Thanks to advanced single cell sequencing methods, researchers can take snapshots of over 20,000 different pieces of information in a single cell’s transcript, and can do so for tens of thousands of cells at a time – the new method opens the technology to diagnostic applications, for the first time.

Through the Garvan-Weizmann Centre for Cellular Genomics, the researchers are now moving to the next phase of translating the method to accredited tests for clinical practice.

“Our scPred method gives us the possibility of earlier detection; it may allow us to determine the stage of a cancer patient, what potential drugs they will respond to, or whether their tumour cells have signatures that indicate resistance to chemotherapy. The potential for this new method is enormous,” says Associate Professor Powell.

Learn more: A way to ‘fingerprint’ human cells

 

 

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Lighting up cancer-causing mutations as if by magic

via Genetic Engineering and Biotechnology News

LumosVar — a name inspired by Harry Potter — could help physicians provide genomic-based treatments for their patients

By conjuring the spell “Lumos!” wizards in the mythical world of Harry Potter could light up the tip of their magic wands and illuminate their surroundings. So, too, does LumosVar, a computer program developed by the Translational Genomics Research Institute (TGen), “light up” cancer-causing genetic Var-ients, or mutations, illuminating how physicians might best treat their patients.

A study published today in the scientific journal Frontiers in Oncology describes how researchers at TGen, an affiliate of City of Hope, developed LumosVar to create a tool that can accurately identify cancer-causing mutations from patient tumor samples.

In the case of archived samples from patients for which treatment outcome results are known, these represent a treasure trove of information that could accelerate research by investigators and physicians in predicting responses of future patients to particular treatments.

“There are many open questions in precision oncology that can only be answered by collecting large amounts of patient genomic data linked to treatment response and clinical outcomes,” said Dr. Rebecca Halperin, a Research Assistant Professor in TGen’s Quantitative Medicine and Systems Biology Program.

“The approach we outline in this study should enable researchers to use archival samples more effectively. Accurately calling, or identifying, somatic variants — those DNA changes specific to a patient’s cancer — are the first step in any analysis,” said Dr. Halperin, the study’s lead author.

However, archived tumor samples are frequently not accompanied by the patients’ normal — or germline — genetic information, making it difficult to distinguish the patient’s normal DNA variants to their mutated and cancerous DNA changes.

LumosVar is a precise enough tool that it not only can detect the cancerous DNA from a patient sample, but it also can differentiate the adjacent normal DNA that may surround the tumor in the sample. Comparing the patient’s normal DNA from a suspected cancer-causing mutation is critical to eliminating benign, non-cancerous variants in the sample — “false positives” — and ensuring that the tissue sample analysis is as accurate as possible.

A high level of accuracy is needed for physicians to use this information in precision medicine, determining what treatment each individual patient should receive.

“The sequencing of DNA from tissue adjacent to the tumor could help identify somatic, or cancer-causing, mutations when another source of normal tissue is not available,” said Dr. Sara Byron, Research Assistant Professor in TGen’s Integrated Cancer Genomics Division, and also the study’s senior author.

Learn more: AS IF BY MAGIC: TGEN DEVELOPS PROGRAM THAT LIGHTS UP CANCER-CAUSING MUTATIONS

 

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Creating a human reference genome, entirely from scratch, for less than $10,000

credit: Robert Lang
A multi-institutional team has developed a new way to sequence genomes, which can assemble the genome of an organism, entirely from scratch, dramatically cheaper and faster.

A team spanning Baylor College of Medicine, Rice University, Texas Children’s Hospital and the Broad Institute of MIT and Harvard has developed a new way to sequence genomes, which can assemble the genome of an organism, entirely from scratch, dramatically cheaper and faster.

While there is much excitement about the so-called “$1000 genome” in medicine, when a doctor orders the DNA sequence of a patient, the test merely compares fragments of DNA from the patient to a reference genome. The task of generating a reference genome from scratch is an entirely different matter; for instance, the original human genome project took 10 years and cost $4 billion. The ability to quickly and easily generate a reference genome from scratch would open the door to creating reference genomes for everything from patients to tumors to all species on earth. Today in Science, the multi-institutional team reports a method – called 3D genome assembly – that can create a human reference genome, entirely from scratch, for less than $10,000.

To illustrate the power of 3D genome assembly, the researchers have assembled the 1.2 billion letter genome of the Aedes aegypti mosquito, which carries the Zika virus, producing the first end-to-end assembly of each of its three chromosomes. The new genome will enable scientists to better combat the Zika outbreak by identifying vulnerabilities in the mosquito that the virus uses to spread.

The human genome is a sequence of 6 billion chemical letters, called base-pairs, divided up among 23 pairs of chromosomes. Despite the decline in the cost of DNA sequencing, determining the sequence of each chromosome from scratch, a process called de novo genome assembly, remains extremely expensive because chromosomes can be hundreds of millions of base-pairs long. In contrast, today’s inexpensive DNA sequencing technologies produce short reads, or hundred-base-pair-long snippets of DNA sequence, which are designed to be compared to an existing reference genome. Actually generating a reference genome and assembling all those long chromosomes involves combining many different technologies at a cost of hundreds of thousands of dollars. Unfortunately, because human genomes differ from one another, the use of a reference genome generated from one person in the process of diagnosing a different person can mask the true genetic changes responsible for a patient’s condition.

“As physicians, we sometimes encounter patients who we know must carry some sort of genetic change, but we can’t figure out what it is,” said Dr. Aviva Presser Aiden, a physician-scientist in the Pediatric Global Health Program at Texas Children’s Hospital, and a co-author of the new study. “To figure out what’s going on, we need technologies that can report a patient’s entire genome. But, we also can’t afford to spend millions of dollars on every patient’s genome.”

To tackle the challenge, the team developed a new approach, called 3D assembly, which determines the sequence of each chromosome by studying how the chromosomes fold inside the nucleus of a cell.

“Our method is quite different from traditional genome assembly,” said Olga Dudchenko, a postdoctoral fellow at the Center for Genome Architecture at Baylor College of Medicine, who led the research. “Several years ago, our team developed an experimental approach that allows us to determine how the 2-meter-long human genome folds up to fit inside the nucleus of a human cell. In this new study, we show that, just as these folding maps trace the contour of the genome as it folds inside the nucleus, they can also guide us through the sequence itself.”

By carefully tracing the genome as it folds, the team found that they could stitch together hundreds of millions of short DNA reads into the sequences of entire chromosomes. Since the method only uses short reads, it dramatically reduces the cost of de novo genome assembly, which is likely to accelerate the use of de novo genomes in the clinic. “Sequencing a patient’s genome from scratch using 3D assembly is so inexpensive that it’s comparable in cost to an MRI,” said Dudchenko, who also is a fellow at Rice University’s Center for Theoretical Biological Physics. “Generating a de novo genome for a sick patient has become realistic.”

Unlike the genetic tests used in the clinic today, de novo assembly of a patient genome does not rely on the reference genome produced by the Human Genome Project. “Our new method doesn’t depend on previous knowledge about the individual or the species that is being sequenced,” Dudchenko said. “It’s like being able to perform a human genome project on whoever you want, whenever you want.”

“Or whatever you want,” said Dr. Erez Lieberman Aiden, director of the Center for Genome Architecture at Baylor and corresponding author on the new work. “Because the genome is generated from scratch, 3D assembly can be applied to a wide array of species, from grizzly bears to tomato plants. And it is pretty easy. A motivated high school student with access to a nearby biology lab can assemble a reference-quality genome of an actual species, like a butterfly, for the cost of a science fair project.”

The effort took on added urgency with the outbreak of Zika virus, which is carried by the Aedes aegypti mosquito. Researchers hoped to use the mosquito’s genome to identify a strategy to combat the disease, but the Aedes genome had not been well characterized, and its chromosomes are much longer than those of humans.

“We had been discussing these ideas for years – writing a chunk of code here, doing a proof-of-principle assembly there,” said Lieberman Aiden, also assistant professor of molecular and human genetics at Baylor, computer science at Rice and a senior investigator at the Center for Theoretical Biological Physics. “So we had assembly data for Aedes aegypti just sitting on our computers. Suddenly, there’s an outbreak of Zika virus, and the genomics community was galvanized to get going on Aedes. That was a turning point.”

“With the Zika outbreak, we knew that we needed to do everything in our power to share the Aedes genome assembly, and our methods, as soon as possible,” Dudchenko said. “This de novo genome assembly is just a first step in the battle against Zika, but it’s one that can help inform the community’s broader effort.”

The team also assembled the genome of the Culex quinquefasciatus mosquito, the principal vector for West Nile virus. “Culex is another important genome to have, since it is responsible for transmitting so many diseases,” said Lieberman Aiden. “Still, trying to guess what genome is going to be critical ahead of time is not a good plan. Instead, we need to be able to respond quickly to unexpected events. Whether it is a patient with a medical emergency or the outbreak of an epidemic, these methods will allow us to assemble de novo genomes in days, instead of years.”

Learn more: Scientists assemble Zika virus mosquito genome from scratch

 

 

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Genomics takes a leap forward after finding the delete button on DNA

via EurekAlert!

Until recently, genomics was a «read-only» science. But scientists led by Rory Johnson at the University of Bern and the Centre for Genomic Regulation in Barcelona, have now developed a tool for quick and easy deletion of DNA in living cells.

This software will boost efforts to understand the vast regions of non-coding DNA, or «Dark Matter», in our DNA and may lead to discovery of new disease-causing genes and potential new drugs.

Genomics is the field of research studying how our «genome», or entire DNA sequence, specifies a human being, and how errors in this sequence give rise to diseases. Genomics was recently a «read-only» endeavour: researchers used powerful technology to read genomes’ sequence and their regulatory layers. However until recently, there was no way to edit or delete DNA for either basic research objectives, or for potential therapeutic interventions.

Just a few years ago, this outlook changed dramatically with the discovery of a revolutionary technique for editing genomes: «CRISPR-Cas9». CRISPR-Cas9 is a molecular tool composed of two simple components: a molecular barcode, called «sgRNA», which is designed by the researcher to recognise one precise location in the genome; and a protein, Cas9, that binds to a structured loop in the sgRNA. By introducing these two units, researchers may perform a wide range of operations on specific pieces of genomic DNA, from introducing small mutations, to regulating gene activity, to tagging it with small sequences. Until recently most studies employing CRISPR-Cas9 were aimed at silencing protein-coding genes, the best-studied part of our genome.

However our genome consists of 99% of DNA that does not encode any protein. Often described as the «Dark Matter» of the genome, this «non-coding DNA» is recognised to be crucially important for understanding all aspects of human biology, including disease and evolution. Until recently, the experimental tools to study this have not been available.

Researchers studying non-coding DNA have been particularly excited about the discovery of CRISPR-Cas9 because it can be used as a powerful tool for studying non-coding DNA for the first time. Prof Rory Johnson, at the Centre for Genomic Regulation (CRG) in Barcelona, Spain and now at the National Center of Competence in Research (NCCR) RNA & Disease and Department of Clinical Research of the University of Bern, recently created a tool based on CRISPR-Cas9, called «DECKO», which can be used to delete any desired piece of non-coding DNA. The unique advantage of DECKO is that it uses two individual sgRNAs, acting like two molecular scissors that snip out a piece of DNA. Numerous researchers worldwide have adopted this approach, attracted by its simplicity and effectiveness.

While working on DECKO, Johnson and colleagues realised that no software was available for designing the pairs of sgRNAs that are required, meaning that designing deletion experiments was time-consuming. To overcome this, Johnson recruited Masters student Carlos Pulido to design a software pipeline called CRISPETa. They were assisted by a team of laboratory researchers including co-first authors of this paper Estel Aparicio and Carme Arnan, who carried out experiments to validate the software’s predictions.

CRISPETa is a powerful and flexible solution for designing CRISPR deletion experiments. The user tells CRISPETa what region they wish to delete, and the software returns a set of optimised pairs of sgRNAs that can directly be used by experimental researchers. One of the key features is that it can create designs at high scales, with future screening experiments in mind. Importantly, CRISPETa is designed for use by non-experts, and is available in a user friendly website, making CRISPR deletion available to the widest possible number of scientific and biomedical researchers.

In the CRISPETa study, the researchers also introduce a new version of DECKO, which is cheaper and faster than the previous one. The researchers showed that CRISPETa designs efficiently delete their desired targets in human cells. Most importantly, in those regions that give rise to RNA molecules, the researchers showed that the RNA molecules also carry the deletion.

CRISPETa will be useful for scientific researchers, from even the most modest experimental laboratory. These users may, for example, delete a suspected functional region of non-coding DNA, and test the outcome on cellular or molecular activity. This software will also be potentially valuable for groups aiming to utilise CRISPR deletion for therapeutic purposes, by for example, deleting a region of non-coding DNA that is suspected to cause a disease state. Therefore CRISPETa will be a valuable tool for the hundreds of research teams worldwide who are using CRISPR deletion.

«We hope that this new software tool will allow the greatest possible number of researchers to harness the power of CRISPR deletion in their research», says Carlos Pulido, the student who wrote the CRISPETa software.

«Ultimately, we expect that CRISPR deletion and other genome engineering tools to lead to a revolution in our ability to understand the genomic basis of disease, particularly in the 99% of DNA that does not encode proteins. Apart from being used as a basic research tool, CRISPR may even be used in the future as a powerful therapeutic to reverse disease-causing mutations», adds Rory Johnson.

Learn more: Genome Editing: Pressing the Delete Button on DNA

 

 

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Precision Medicine: Can We Afford it? Can We afford Not to Explore it?

via liveclinic.com

via liveclinic.com

Imagine that the next time your doctor orders a round of tests, in addition to cholesterol and vitamin D, she also orders a genome sequence. It sounds like science fiction, but the day might come sooner than you think.

Precision medicine—in which each patient’s prevention and treatment decisions are tailored for them—has been a buzzword in the health care industry recently. President Barack Obama launched his Precision Medicine Initiative, and other countries have similar projects underway.

With concerns about the cost of health care, though, can we afford precision medicine?

In certain instances, precision medicine can actually save money. For example, if patients can be screened for drug hypersensitivity before being prescribed certain drugs, they won’t have to be treated later, which is better for patients and cuts down on costs. A similar approach works for choosing treatments.

“When you use a therapy to target only the individuals who will benefit, you avoid wasting drugs or other resources on people who you know won’t get any benefit, and who might actually be harmed,” said David Threadgill, Ph.D., professor and holder of the Tom and Jean McMullin Chair of Genetics at the Texas A&M Health Science Center College of Medicine and director of the Texas A&M Institute for Genome Sciences and Society.

Of course, it’s not quite that simple. “Whether the economics works out in favor of precision medicine depends on two things: the difficulty and the cost of finding the best candidates who will benefit from specific, tailored treatments,” said Robert L. Ohsfeldt, Ph.D., health economist and professor in the Department of Health Policy & Management at the Texas A&M School of Public Health. “You have to know a lot about the disease process and how individual characteristics—genetics and environmental factors like diet or exposure to toxins—mediate the treatment response.”

Learn more: Precision Medicine: Can We Afford it?  Can We afford Not to Explore it?

 

 

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