Lung cancer, Sherlock Holmes and piano


Image of lung cancer

When we think of lung cancer we typically tend to think it’s the end result of years of smoking cigarettes. But, according to the Centers for Disease Control and Prevention, between 10 and 20 percent of cases of lung cancer (20,000 to 40,000 cases a year) happen to non-smokers, people who have either never smoked or smoked fewer than 100 cigarettes in their life. Now researchers have found that there are different genetic types of cancer for smokers and non-smokers, and that might mean the need for different kinds of treatment.

A team at the National Cancer Institute did whole genome sequencing on tumors from 232 never-smokers who had lung cancer. In an interview with STATnews, researcher Maria Teresa Landi said they called their research the Sherlock-Lung study, after the famous fictional pipe-smoking detective Sherlock Holmes. “We used a detective approach. By looking at the genome of the tumor, we use the changes in the tumors as a footprint to follow to infer the causes of the disease.”

They also got quite creative in naming the three different genetic subtypes they found. Instead of giving them the usual dry scientific names, they called them piano, mezzo-forte and forte; musical terms for soft, medium and loud.

Half of the tumors in the non-smokers were in the piano group. These were slow growing with few mutations. The median latency period for these (the time between being exposed to something and being diagnosed) was nine years. The mezzo-forte group made up about one third of the cases. Their cancers were more aggressive with a latency of around 14 weeks. The forte group were the most aggressive, and the ones that most closely resembled smokers’ cancer, with a latency period of just one month.

So, what is the role of stem cells in this research? Well, in the study, published in the journal Nature Genetics the team found that the piano subtype seemed to be connected to genes that help regulate stem cells. That complicates things because it means that the standard treatments for lung cancer that work for the mezzo-forte and forte varieties, won’t work for the piano subtype.

“If this is true, it changes a lot of things in the way we should think of tumorigenesis,” Dr. Landi said.

With that in mind, and because early-detection can often be crucial in treating cancer, what can non-smokers do to find out if they are at risk of developing lung cancer? Well, right now there are no easy answers. For example, the U.S. Preventive Services Task Force does not recommend screening for people who have never smoked because regular CT scans could actually increase an otherwise healthy individual’s risk of developing cancer.

Rare Disease, Type 1 Diabetes, and Heart Function: Breakthroughs for Three CIRM-Funded Studies

This past week, there has been a lot of mention of CIRM funded studies that really highlight the importance of the work we support and the different disease areas we make an impact on. This includes important research related to rare disease, Type 1 Diabetes (T1D), and heart function. Below is a summary of the promising CIRM-funded studies released this past week for each one of these areas.

Rare Disease

Comparison of normal (left) and Pelizaeus-Merzbacher disease (PMD) brains (right) at age 2. 

Pelizaeus-Merzbacher disease (PMD) is a rare genetic condition affecting boys. It can be fatal before 10 years of age and symptoms of the disease include weakness and breathing difficulties. PMD is caused by a disruption in the formation of myelin, a type of insulation around nerve fibers that allows electrical signals in the brain to travel quickly. Without proper signaling, the brain has difficulty communicating with the rest of the body. Despite knowing what causes PMD, it has been difficult to understand why there is a disruption of myelin formation in the first place.

However, in a CIRM-funded study, Dr. David Rowitch, alongside a team of researchers at UCSF, Stanford, and the University of Cambridge, has been developing potential stem cell therapies to reverse or prevent myelin loss in PMD patients.

Two new studies, of which Dr. Rowitch is the primary author, published in Cell Stem Cell, and Stem Cell Reports, respectively report promising progress in using stem cells derived from patients to identify novel PMD drugs and in efforts to treat the disease by directly transplanting neural stem cells into patients’ brains. 

In a UCSF press release, Dr. Rowitch talks about the implications of his findings, stating that,

“Together these studies advance the field of stem cell medicine by showing how a drug therapy could benefit myelination and also that neural stem cell transplantation directly into the brains of boys with PMD is safe.”

Type 1 Diabetes

Viacyte, a company that is developing a treatment for Type 1 Diabetes (T1D), announced in a press release that the company presented preliminary data from a CIRM-funded clinical trial that shows promising results. T1D is an autoimmune disease in which the body’s own immune system destroys the cells in the pancreas that make insulin, a hormone that enables our bodies to break down sugar in the blood. CIRM has been funding ViaCyte from it’s very earliest days, investing more than $72 million into the company.

The study uses pancreatic precursor cells, which are derived from stem cells, and implants them into patients in an encapsulation device. The preliminary data showed that the implanted cells, when effectively engrafted, are capable of producing circulating C-peptide, a biomarker for insulin, in patients with T1D. Optimization of the procedure needs to be explored further.

“This is encouraging news,” said Dr. Maria Millan, President and CEO of CIRM. “We are very aware of the major biologic and technical challenges of an implantable cell therapy for Type 1 Diabetes, so this early biologic signal in patients is an important step for the Viacyte program.”

Heart Function

Although various genome studies have uncovered over 500 genetic variants linked to heart function, such as irregular heart rhythms and heart rate, it has been unclear exactly how they influence heart function.

In a CIRM-funded study, Dr. Kelly Frazer and her team at UCSD studied this link further by deriving heart cells from induced pluripotent stem cells. These stem cells were in turn derived from skin samples of seven family members. After conducting extensive genome-wide analysis, the team discovered that many of these genetic variations influence heart function because they affect the binding of a protein called NKX2-5.

In a press release by UCSD, Dr. Frazer elaborated on the important role this protein plays by stating that,

“NKX2-5 binds to many different places in the genome near heart genes, so it makes sense that variation in the factor itself or the DNA to which it binds would affect that function. As a result, we are finding that multiple heart-related traits can share a common mechanism — in this case, differential binding of NKX2-5 due to DNA variants.”

The full results of this study were published in Nature Genetics.

Computer “Magic” Helps Scientists Morph One Cell’s Identity Into Another

Mogrify. Sounds like one of Harry Potter’s spells, doesn’t it? In reality, it’s something cooler than that. As reported on Tuesday in Nature Genetics, Mogrify is a new research tool that uses the magic of mathematics and computer programming to help stem cell scientists determine the necessary ingredients to convert one human cell type into another.


It may sound like a magical spell but Mogrify is based on real science to help researchers predict what factors are needed to convert a given cell into another. Image credit: Warner Bros.

Now, make no mistake, the stem cell field already has the knowhow to manipulate the identity of cells and stem cells in order to study human disease and work toward cell therapies. Got a human embryonic stem cell? Scientists can specialize, or differentiate, that into an insulin-producing pancreatic cell or a beating heart muscle cell to name just two examples. Got a skin cell from an autistic patient? Using the induced pluripotent stem cell (iPS) technique, researchers have worked out the steps to transform that skin cell into an embryonic stem cell-like state and then differentiate it to a nerve cell – providing new insights into the disorder. This iPS technique can even be skipped altogether to directly convert a skin cell into, say, a liver cell through a technique called transdifferentiation.

But these methods require trial and error to pinpoint the right combination of genetic on/off switches to “flip” in the cells. These switches are called transcription factors, proteins that bind to DNA and activate or repress genes. The interaction between transcription factors and genes that give a cell it’s specific identity is extremely complex. To mimic these interactions in a lab dish, scientists use their expert knowledge and make educated guesses about which combinations of genes to modulate to generate certain cell types. Still, trial and error is a necessary part of the workflow which can require months and even years of work. And with about 2000 transcription factors and 400 cell types in humans, there’s an enormous number of possible combinations to potentially test.

Meet Mogrify
This is where Mogrify, a computational algorithm developed by a collaboration between scientists at the University of Bristol in the UK and Monash University in Australia, comes into the picture. Without lifting a pipette, Mogrify appears to be able to determine the most likely combination of transcription factors to transdifferentiate a given cell type into another without forcing the cell back to an embryonic stem cell state.

Mogrify was applied to FANTOM5, a dataset created by a large international effort to describe gene activity networks in all the cell types of the human body. With Mogrify and FANTOM5 in hand, the team first validated their algorithm by making predictions for transdifferentiation recipes that have already been established in scientific publications. For example, Mogrify correctly predicted that the transcription factor, MYOD1, could directly convert a skin cell to a muscle cell, one of the early examples of transdifferentiated cells described back in the 1980’s by the lab of Harold Weintraub. Altogether these “in silico” validation experiments recovered the correct published transcription factors at a rate of 84% compared to 31% and 51% for two other computer algorithms published by independent groups. And in 6 out of the 10 conversion experiments, Mogrify predicted 100% of the required transcription factors. As the team points out in their research article, had Mogrify been available to these scientists, they would have saved a lot of time:

“If Mogrify had been used in the original studies, the experiments could have been a success the first time.”

In addition to these validation tests, the team also tried out Mogrify in lab experiments without the help of previous publications. In one of the experiments they asked Mogrify to suggest transdifferentiation factors for converting adult fibroblasts, which are collagen-producing cells, into keratinocytes, the cells that make up the outer layer of our skin.  The algorithm predicted a set of five transcription factors which were then introduced into the fibroblasts in the lab. Within three weeks, most of the fibroblasts had converted into cells resembling keratinocytes – they had the appropriate protein markers on their surface and had taken on the typical shape seen in keratinocytes.


The image shows the results of converting fibroblasts (collagen producing cells) to keratinocytes (skin cells) using the Mogrify algorithm. In the image it can be seen that the converted keratinocytes, which are stained green, have a ‘cobble-stone’ pattern while fibroblasts have a long thin morphology. Credit: Nature Genetics & Rackham et al.

Insights and Questions
I think Mogrify is a fascinating example of how machines and human brain power together can push the envelope of biological discoveries. Through laboratory research, scientists gradually build mental models of various cellular processes. These mental models are sources of thought experiments that they test in the lab. Yet, the countless interactions between genes, proteins and cells is so complex that the intuition of even the greatest scientific minds breaks down at some point. That’s where researchers can leverage the insight of tools like Mogrify.

Will Mogrify be a breakthrough game-changer in the world of stem cell science? Only time will tell as more scientists around the world put it to use. And thanks to the team, one can start using it right now because it’s available to anyone online. Just select your starting and finishing cell types from a pull down menu to begin.


Screenshot from Just select your desired starting and finishing cell types and Mogrify recommends which transcription factors to use for your cell conversion. 

Will Mogrify completely eliminate the need to do some trial and error? Not likely, as the authors knowledge, but it’s a great starting point. If scientists can dramatically shorten the time needed to generate the cells related to their particular disease of interest, then they can more quickly move on to the hard work ahead: gaining a deeper understanding of the disease and developing cures. Julian Gough, professor of bioinformatics at the University of Bristol and one of the senior researchers on the report, spoke of the potential impact of Mogrify in a university press release:

“The ability to produce numerous types of human cells will lead directly to tissue therapies of all kinds, to treat conditions from arthritis to macular degeneration, to heart disease. The fuller understanding, at the molecular level of cell production leading on from this, may allow us to grow whole organs from somebody’s own cells.”