CIRM & CZI & MOU for COVID-19

Too many acronyms? Not to worry. It is all perfectly clear in the news release we just sent out about this.

A new collaboration between the California Institute for Regenerative Medicine (CIRM) and the Chan Zuckerberg Initiative (CZI) will advance scientific efforts to respond to the COVID-19 pandemic by collaborating on disseminating single-cell research that scientists can use to better understand the SARS-CoV-2 virus and help develop treatments and cures.

CIRM and CZI have signed a Memorandum of Understanding (MOU) that will combine CIRM’s infrastructure and data collection and analysis tools with CZI’s technology expertise. It will enable CIRM researchers studying COVID-19 to easily share their data with the broader research community via CZI’s cellxgene tool, which allows scientists to explore and visualize measurements of how the virus impacts cell function at a single-cell level. CZI recently launched a new version of cellxgene and is supporting the single-cell biology community by sharing COVID-19 data, compiled by the global Human Cell Atlas effort and other related efforts, in an interactive and scalable way.

“We are pleased to be able to enter into this partnership with CZI,” said Dr. Maria T. Millan, CIRM’s President & CEO. “This MOU will allow us to leverage our respective investments in genomics science in the fight against COVID-19. CIRM has a long-standing commitment to generation and sharing of sequencing and genomic data from a wide variety of projects. That’s why we created the CIRM genomics award and invested in the Stem Cell Hub at the University of California, Santa Cruz, which will process the large complex datasets in this collaboration.”  

“Quickly sharing scientific data about COVID-19 is vital for researchers to build on each other’s work and accelerate progress towards understanding and treating a complex disease,” said CZI Single-Cell Biology Program Officer Jonah Cool. “We’re excited to partner with CIRM to help more researchers efficiently share and analyze single-cell data through CZI’s cellxgene platform.”

In March 2020, the CIRM Board approved $5 million in emergency funding to target COVID-19. To date, CIRM has funded 17 projects, some of which are studying how the SARS-CoV-2 virus impacts cell function at the single-cell level.

Three of CIRM’s early-stage COVID-19 research projects will plan to participate in this collaborative partnership by sharing data and analysis on cellxgene.   

  • Dr. Evan Snyder and his team at Sanford Burnham Prebys Medical Discovery Institute are using induced pluripotent stem cells (iPSCs), a type of stem cell that can be created by reprogramming skin or blood cells, to create lung organoids. These lung organoids will then be infected with the novel coronavirus in order to test two drug candidates for treating the virus.
  • Dr. Brigitte Gomperts at UCLA is studying a lung organoid model made from human stem cells in order to identify drugs that can reduce the number of infected cells and prevent damage in the lungs of patients with COVID-19.
  • Dr. Justin Ichida at the University of Southern California is trying to determine if a drug called a kinase inhibitor can protect stem cells in the lungs and other organs, which the novel coronavirus selectively infects and kills.

“Cumulative data into how SARS-CoV-2 affects people is so powerful to fight the COVID-19 pandemic,” said Stephen Lin, PhD, the Senior CIRM Science Officer who helped develop the MOU. “We are grateful that the researchers are committed to sharing their genomic data with other researchers to help advance the field and improve our understanding of the virus.”

CZI also supports five distinct projects studying how COVID-19 progresses in patients at the level of individual cells and tissues. This work will generate some of the first single-cell biology datasets from donors infected by SARS-CoV-2 and provide critical insights into how the virus infects humans, which cell types are involved, and how the disease progresses. All data generated by these grants will quickly be made available to the scientific community via open access datasets and portals, including CZI’s cellxgene tool.

Stem cell stories that caught our eye: update on Capricor’s heart attack trial; lithium on the brain; and how stem cells do math

Capricor ALLSTARToday our partners Capricor Therapeutics announced that its stem cell therapy for patients who have experienced a large heart attack is unlikely to meet one of its key goals, namely reducing the scar size in the heart 12 months after treatment.

The news came after analyzing results from patients at the halfway point of the trial, six months after their treatment in the Phase 2 ALLSTAR clinical trial which CIRM was funding. They found that there was no significant difference in the reduction in scarring on the heart for patients treated with donor heart-derived stem cells, compared to patients given a placebo.

Obviously this is disappointing news for everyone involved, but we know that not all clinical trials are going to be successful. CIRM supported this research because it clearly addressed an unmet medical need and because an earlier Phase 1 study had showed promise in helping prevent decline in heart function after a heart attack.

Yet even with this failure to repeat that promise in this trial,  we learned valuable lessons.

In a news release, Dr. Tim Henry, Director of the Division of Interventional Technologies in the Heart Institute at Cedars-Sinai Medical Center and a Co-Principal Investigator on the trial said:

“We are encouraged to see reductions in left ventricular volume measures in the CAP-1002 treated patients, an important indicator of reverse remodeling of the heart. These findings support the biological activity of CAP-1002.”

Capricor still has a clinical trial using CAP-1002 to treat boys and young men developing heart failure due to Duchenne Muscular Dystrophy (DMD).

Lithium gives up its mood stabilizing secrets

As far back as the late 1800s, doctors have recognized that lithium can help people with mood disorders. For decades, this inexpensive drug has been an effective first line of treatment for bipolar disorder, a condition that causes extreme mood swings. And yet, scientists have never had a good handle on how it works. That is, until this week.

evan snyder

Evan Snyder

Reporting in the Proceedings of the National Academy of Sciences (PNAS), a research team at Sanford Burnham Prebys Medical Discovery Institute have identified the molecular basis of the lithium’s benefit to bipolar patients.  Team lead Dr. Evan Snyder explained in a press release why his group’s discovery is so important for patients:

“Lithium has been used to treat bipolar disorder for generations, but up until now our lack of knowledge about why the therapy does or does not work for a particular patient led to unnecessary dosing and delayed finding an effective treatment. Further, its side effects are intolerable for many patients, limiting its use and creating an urgent need for more targeted drugs with minimal risks.”

The study, funded in part by CIRM, attempted to understand lithium’s beneficial effects by comparing cells from patient who respond to those who don’t (only about a third of patients are responders). Induced pluripotent stem cells (iPSCs) were generated from both groups of patients and then the cells were specialized into nerve cells that play a role in bipolar disorder. The team took an unbiased approach by looking for differences in proteins between the two sets of cells.

The team zeroed in on a protein called CRMP2 that was much less functional in the cells from the lithium-responsive patients. When lithium was added to these cells the disruption in CRMP2’s activity was fixed. Now that the team has identified the molecular location of lithium’s effects, they can now search for new drugs that do the same thing more effectively and with fewer side effects.

The stem cell: a biological calculator?

math

Can stem cells do math?

Stem cells are pretty amazing critters but can they do math? The answer appears to be yes according to a fascinating study published this week in PNAS Proceedings of the National Academy of Sciences.

Stem cells, like all cells, process information from the outside through different receptors that stick out from the cells’ outer membranes like a satellite TV dish. Protein growth factors bind those receptors which trigger a domino effect of protein activity inside the cell, called cell signaling, that transfers the initial receptor signal from one protein to another. Ultimately that cascade leads to the accumulation of specific proteins in the nucleus where they either turn on or off specific genes.

Intuition would tell you that the amount of gene activity in response to the cell signaling should correspond to the amount of protein that gets into the nucleus. And that’s been the prevailing view of scientists. But the current study by a Caltech research team debunks this idea. Using real-time video microscopy filming, the team captured cell signaling in individual cells; in this case they used an immature muscle cell called a myoblast.

goentoro20170508

Behavior of cells over time after they have received a Tgf-beta signal. The brightness of the nuclei (circled in red) indicates how much Smad protein is present. This brightness varies from cell to cell, but the ratio of brightness after the signal to before the signal is about the same. Image: Goentoro lab, CalTech.

To their surprise the same amount of growth factor given to different myoblasts cells led to the accumulation of very different amounts of a protein called Smad3 in the cells’ nuclei, as much as a 40-fold difference across the cells. But after some number crunching, they discovered that dividing the amount of Smad3 after growth factor stimulation by the Smad3 amount before growth stimulation was similar in all the cells.

As team lead Dr. Lea Goentoro mentions in a press release, this result has some very important implications for studying human disease:

“Prior to this work, researchers trying to characterize the properties of a tumor might take a slice from it and measure the total amount of Smad in cells. Our results show that to understand these cells one must instead measure the change in Smad over time.”