Research Area: Cancer Biology

A new approach to modeling complex biological systems

MIT engineers’ new model could help researchers glean insights from genomic data and other huge datasets. This is potentially critical to researchers who study any kind of complex biological system, according to senior author Douglas Lauffenburger.

Anne Trafton | MIT News
November 5, 2024

Over the past two decades, new technologies have helped scientists generate a vast amount of biological data. Large-scale experiments in genomics, transcriptomics, proteomics, and cytometry can produce enormous quantities of data from a given cellular or multicellular system.

However, making sense of this information is not always easy. This is especially true when trying to analyze complex systems such as the cascade of interactions that occur when the immune system encounters a foreign pathogen.

MIT biological engineers have now developed a new computational method for extracting useful information from these datasets. Using their new technique, they showed that they could unravel a series of interactions that determine how the immune system responds to tuberculosis vaccination and subsequent infection.

This strategy could be useful to vaccine developers and to researchers who study any kind of complex biological system, says Douglas Lauffenburger, the Ford Professor of Engineering in the departments of Biological Engineering, Biology, and Chemical Engineering.

“We’ve landed on a computational modeling framework that allows prediction of effects of perturbations in a highly complex system, including multiple scales and many different types of components,” says Lauffenburger, the senior author of the new study.

Shu Wang, a former MIT postdoc who is now an assistant professor at the University of Toronto, and Amy Myers, a research manager in the lab of University of Pittsburgh School of Medicine Professor JoAnne Flynn, are the lead authors of a new paper on the work, which appears today in the journal Cell Systems.

Modeling complex systems

When studying complex biological systems such as the immune system, scientists can extract many different types of data. Sequencing cell genomes tells them which gene variants a cell carries, while analyzing messenger RNA transcripts tells them which genes are being expressed in a given cell. Using proteomics, researchers can measure the proteins found in a cell or biological system, and cytometry allows them to quantify a myriad of cell types present.

Using computational approaches such as machine learning, scientists can use this data to train models to predict a specific output based on a given set of inputs — for example, whether a vaccine will generate a robust immune response. However, that type of modeling doesn’t reveal anything about the steps that happen in between the input and the output.

“That AI approach can be really useful for clinical medical purposes, but it’s not very useful for understanding biology, because usually you’re interested in everything that’s happening between the inputs and outputs,” Lauffenburger says. “What are the mechanisms that actually generate outputs from inputs?”

To create models that can identify the inner workings of complex biological systems, the researchers turned to a type of model known as a probabilistic graphical network. These models represent each measured variable as a node, generating maps of how each node is connected to the others.

Probabilistic graphical networks are often used for applications such as speech recognition and computer vision, but they have not been widely used in biology.

Lauffenburger’s lab has previously used this type of model to analyze intracellular signaling pathways, which required analyzing just one kind of data. To adapt this approach to analyze many datasets at once, the researchers applied a mathematical technique that can filter out any correlations between variables that are not directly affecting each other. This technique, known as graphical lasso, is an adaptation of the method often used in machine learning models to strip away results that are likely due to noise.

“With correlation-based network models generally, one of the problems that can arise is that everything seems to be influenced by everything else, so you have to figure out how to strip down to the most essential interactions,” Lauffenburger says. “Using probabilistic graphical network frameworks, one can really boil down to the things that are most likely to be direct and throw out the things that are most likely to be indirect.”

Mechanism of vaccination

To test their modeling approach, the researchers used data from studies of a tuberculosis vaccine. This vaccine, known as BCG, is an attenuated form of Mycobacterium bovis. It is used in many countries where TB is common but isn’t always effective, and its protection can weaken over time.

In hopes of developing more effective TB protection, researchers have been testing whether delivering the BCG vaccine intravenously or by inhalation might provoke a better immune response than injecting it. Those studies, performed in animals, found that the vaccine did work much better when given intravenously. In the MIT study, Lauffenburger and his colleagues attempted to discover the mechanism behind this success.

The data that the researchers examined in this study included measurements of about 200 variables, including levels of cytokines, antibodies, and different types of immune cells, from about 30 animals.

The measurements were taken before vaccination, after vaccination, and after TB infection. By analyzing the data using their new modeling approach, the MIT team was able to determine the steps needed to generate a strong immune response. They showed that the vaccine stimulates a subset of T cells, which produce a cytokine that activates a set of B cells that generate antibodies targeting the bacterium.

“Almost like a roadmap or a subway map, you could find what were really the most important paths. Even though a lot of other things in the immune system were changing one way or another, they were really off the critical path and didn’t matter so much,” Lauffenburger says.

The researchers then used the model to make predictions for how a specific disruption, such as suppressing a subset of immune cells, would affect the system. The model predicted that if B cells were nearly eliminated, there would be little impact on the vaccine response, and experiments showed that prediction was correct.

This modeling approach could be used by vaccine developers to predict the effect their vaccines may have, and to make tweaks that would improve them before testing them in humans. Lauffenburger’s lab is now using the model to study the mechanism of a malaria vaccine that has been given to children in Kenya, Ghana, and Malawi over the past few years.

“The advantage of this computational approach is that it filters out many biological targets that only indirectly influence the outcome and identifies those that directly regulate the response. Then it’s possible to predict how therapeutically altering those biological targets would change the response. This is significant because it provides the basis for future vaccine and trial designs that are more data driven,” says Kathryn Miller-Jensen, a professor of biomedical engineering at Yale University, who was not involved in the study.

Lauffenburger’s lab is also using this type of modeling to study the tumor microenvironment, which contains many types of immune cells and cancerous cells, in hopes of predicting how tumors might respond to different kinds of treatment.

The research was funded by the National Institute of Allergy and Infectious Diseases.

Cancer biologists discover a new mechanism for an old drug

Study reveals the drug, 5-fluorouracil, acts differently in different types of cancer — a finding that could help researchers design better drug combinations.

Anne Trafton | MIT News
October 7, 2024

Since the 1950s, a chemotherapy drug known as 5-fluorouracil has been used to treat many types of cancer, including blood cancers and cancers of the digestive tract.

Doctors have long believed that this drug works by damaging the building blocks of DNA. However, a new study from MIT has found that in cancers of the colon and other gastrointestinal cancers, it actually kills cells by interfering with RNA synthesis.

The findings could have a significant effect on how doctors treat many cancer patients. Usually, 5-fluorouracil is given in combination with chemotherapy drugs that damage DNA, but the new study found that for colon cancer, this combination does not achieve the synergistic effects that were hoped for. Instead, combining 5-FU with drugs that affect RNA synthesis could make it more effective in patients with GI cancers, the researchers say.

“Our work is the most definitive study to date showing that RNA incorporation of the drug, leading to an RNA damage response, is responsible for how the drug works in GI cancers,” says Michael Yaffe, a David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, and a member of MIT’s Koch Institute for Integrative Cancer Research. “Textbooks implicate the DNA effects of the drug as the mechanism in all cancer types, but our data shows that RNA damage is what’s really important for the types of tumors, like GI cancers, where the drug is used clinically.”

Yaffe, the senior author of the new study, hopes to plan clinical trials of 5-fluorouracil with drugs that would enhance its RNA-damaging effects and kill cancer cells more effectively.

Jung-Kuei Chen, a Koch Institute research scientist, and Karl Merrick, a former MIT postdoc, are the lead authors of the paper, which appears today in Cell Reports Medicine.

An unexpected mechanism

Clinicians use 5-fluorouracil (5-FU) as a first-line drug for colon, rectal, and pancreatic cancers. It’s usually given in combination with oxaliplatin or irinotecan, which damage DNA in cancer cells. The combination was thought to be effective because 5-FU can disrupt the synthesis of DNA nucleotides. Without those building blocks, cells with damaged DNA wouldn’t be able to efficiently repair the damage and would undergo cell death.

Yaffe’s lab, which studies cell signaling pathways, wanted to further explore the underlying mechanisms of how these drug combinations preferentially kill cancer cells.

The researchers began by testing 5-FU in combination with oxaliplatin or irinotecan in colon cancer cells grown in the lab. To their surprise, they found that not only were the drugs not synergistic, in many cases they were less effective at killing cancer cells than what one would expect by simply adding together the effects of 5-FU or the DNA-damaging drug given alone.

“One would have expected that these combinations to cause synergistic cancer cell death because you are targeting two different aspects of a shared process: breaking DNA, and making nucleotides,” Yaffe says. “Karl looked at a dozen colon cancer cell lines, and not only were the drugs not synergistic, in most cases they were antagonistic. One drug seemed to be undoing what the other drug was doing.”

Yaffe’s lab then teamed up with Adam Palmer, an assistant professor of pharmacology at the University of North Carolina School of Medicine, who specializes in analyzing data from clinical trials. Palmer’s research group examined data from colon cancer patients who had been on one or more of these drugs and showed that the drugs did not show synergistic effects on survival in most patients.

“This confirmed that when you give these combinations to people, it’s not generally true that the drugs are actually working together in a beneficial way within an individual patient,” Yaffe says. “Instead, it appears that one drug in the combination works well for some patients while another drug in the combination works well in other patients. We just cannot yet predict which drug by itself is best for which patient, so everyone gets the combination.”

These results led the researchers to wonder just how 5-FU was working, if not by disrupting DNA repair. Studies in yeast and mammalian cells had shown that the drug also gets incorporated into RNA nucleotides, but there has been dispute over how much this RNA damage contributes to the drug’s toxic effects on cancer cells.

Inside cells, 5-FU is broken down into two different metabolites. One of these gets incorporated into DNA nucleotides, and other into RNA nucleotides. In studies of colon cancer cells, the researchers found that the metabolite that interferes with RNA was much more effective at killing colon cancer cells than the one that disrupts DNA.

That RNA damage appears to primarily affect ribosomal RNA, a molecule that forms part of the ribosome — a cell organelle responsible for assembling new proteins. If cells can’t form new ribosomes, they can’t produce enough proteins to function. Additionally, the lack of undamaged ribosomal RNA causes cells to destroy a large set of proteins that normally bind up the RNA to make new functional ribosomes.

The researchers are now exploring how this ribosomal RNA damage leads cells to under programmed cell death, or apoptosis. They hypothesize that sensing of the damaged RNAs within cell structures called lysosomes somehow triggers an apoptotic signal.

“My lab is very interested in trying to understand the signaling events during disruption of ribosome biogenesis, particularly in GI cancers and even some ovarian cancers, that cause the cells to die. Somehow, they must be monitoring the quality control of new ribosome synthesis, which somehow is connected to the death pathway machinery,” Yaffe says.

New combinations

The findings suggest that drugs that stimulate ribosome production could work together with 5-FU to make a highly synergistic combination. In their study, the researchers showed that a molecule that inhibits KDM2A, a suppressor of ribosome production, helped to boost the rate of cell death in colon cancer cells treated with 5-FU.

The findings also suggest a possible explanation for why combining 5-FU with a DNA-damaging drug often makes both drugs less effective. Some DNA damaging drugs send a signal to the cell to stop making new ribosomes, which would negate 5-FU’s effect on RNA. A better approach may be to give each drug a few days apart, which would give patients the potential benefits of each drug, without having them cancel each other out.

“Importantly, our data doesn’t say that these combination therapies are wrong. We know they’re effective clinically. It just says that if you adjust how you give these drugs, you could potentially make those therapies even better, with relatively minor changes in the timing of when the drugs are given,” Yaffe says.

He is now hoping to work with collaborators at other institutions to run a phase 2 or 3 clinical trial in which patients receive the drugs on an altered schedule.

“A trial is clearly needed to look for efficacy, but it should be straightforward to initiate because these are already clinically accepted drugs that form the standard of care for GI cancers. All we’re doing is changing the timing with which we give them,” he says.

The researchers also hope that their work could lead to the identification of biomarkers that predict which patients’ tumors will be more susceptible to drug combinations that include 5-FU. One such biomarker could be RNA polymerase I, which is active when cells are producing a lot of ribosomal RNA.

The research was funded by the Damon Runyon Cancer Research Fund, a Ludwig Center at MIT Fellowship, the National Institutes of Health, the Ovarian Cancer Research Fund, the Holloway Foundation, and the STARR Cancer Consortium.

Study reveals the benefits and downside of fasting

Fasting helps intestinal stem cells regenerate and heal injuries but also leads to a higher risk of cancer in mice, MIT researchers report.

Anne Trafton | MIT News
August 21, 2024

Low-calorie diets and intermittent fasting have been shown to have numerous health benefits: They can delay the onset of some age-related diseases and lengthen lifespan, not only in humans but many other organisms.

Many complex mechanisms underlie this phenomenon. Previous work from MIT has shown that one way fasting exerts its beneficial effects is by boosting the regenerative abilities of intestinal stem cells, which helps the intestine recover from injuries or inflammation.

In a study of mice, MIT researchers have now identified the pathway that enables this enhanced regeneration, which is activated once the mice begin “refeeding” after the fast. They also found a downside to this regeneration: When cancerous mutations occurred during the regenerative period, the mice were more likely to develop early-stage intestinal tumors.

“Having more stem cell activity is good for regeneration, but too much of a good thing over time can have less favorable consequences,” says Omer Yilmaz, an MIT associate professor of biology, a member of MIT’s Koch Institute for Integrative Cancer Research, and the senior author of the new study.

Yilmaz adds that further studies are needed before forming any conclusion as to whether fasting has a similar effect in humans.

“We still have a lot to learn, but it is interesting that being in either the state of fasting or refeeding when exposure to mutagen occurs can have a profound impact on the likelihood of developing a cancer in these well-defined mouse models,” he says.

MIT postdocs Shinya Imada and Saleh Khawaled are the lead authors of the paper, which appears today in Nature.

Driving regeneration

For several years, Yilmaz’s lab has been investigating how fasting and low-calorie diets affect intestinal health. In a 2018 study, his team reported that during a fast, intestinal stem cells begin to use lipids as an energy source, instead of carbohydrates. They also showed that fasting led to a significant boost in stem cells’ regenerative ability.

However, unanswered questions remained: How does fasting trigger this boost in regenerative ability, and when does the regeneration begin?

“Since that paper, we’ve really been focused on understanding what is it about fasting that drives regeneration,” Yilmaz says. “Is it fasting itself that’s driving regeneration, or eating after the fast?”

In their new study, the researchers found that stem cell regeneration is suppressed during fasting but then surges during the refeeding period. The researchers followed three groups of mice — one that fasted for 24 hours, another one that fasted for 24 hours and then was allowed to eat whatever they wanted during a 24-hour refeeding period, and a control group that ate whatever they wanted throughout the experiment.

The researchers analyzed intestinal stem cells’ ability to proliferate at different time points and found that the stem cells showed the highest levels of proliferation at the end of the 24-hour refeeding period. These cells were also more proliferative than intestinal stem cells from mice that had not fasted at all.

“We think that fasting and refeeding represent two distinct states,” Imada says. “In the fasted state, the ability of cells to use lipids and fatty acids as an energy source enables them to survive when nutrients are low. And then it’s the postfast refeeding state that really drives the regeneration. When nutrients become available, these stem cells and progenitor cells activate programs that enable them to build cellular mass and repopulate the intestinal lining.”

Further studies revealed that these cells activate a cellular signaling pathway known as mTOR, which is involved in cell growth and metabolism. One of mTOR’s roles is to regulate the translation of messenger RNA into protein, so when it’s activated, cells produce more protein. This protein synthesis is essential for stem cells to proliferate.

The researchers showed that mTOR activation in these stem cells also led to production of large quantities of polyamines — small molecules that help cells to grow and divide.

“In the refed state, you’ve got more proliferation, and you need to build cellular mass. That requires more protein, to build new cells, and those stem cells go on to build more differentiated cells or specialized intestinal cell types that line the intestine,” Khawaled says.

Too much of a good thing

The researchers also found that when stem cells are in this highly regenerative state, they are more prone to become cancerous. Intestinal stem cells are among the most actively dividing cells in the body, as they help the lining of the intestine completely turn over every five to 10 days. Because they divide so frequently, these stem cells are the most common source of precancerous cells in the intestine.

In this study, the researchers discovered that if they turned on a cancer-causing gene in the mice during the refeeding stage, they were much more likely to develop precancerous polyps than if the gene was turned on during the fasting state. Cancer-linked mutations that occurred during the refeeding state were also much more likely to produce polyps than mutations that occurred in mice that did not undergo the cycle of fasting and refeeding.

“I want to emphasize that this was all done in mice, using very well-defined cancer mutations. In humans it’s going to be a much more complex state,” Yilmaz says. “But it does lead us to the following notion: Fasting is very healthy, but if you’re unlucky and you’re refeeding after a fasting, and you get exposed to a mutagen, like a charred steak or something, you might actually be increasing your chances of developing a lesion that can go on to give rise to cancer.”

Yilmaz also noted that the regenerative benefits of fasting could be significant for people who undergo radiation treatment, which can damage the intestinal lining, or other types of intestinal injury. His lab is now studying whether polyamine supplements could help to stimulate this kind of regeneration, without the need to fast.

“This fascinating study provides insights into the complex interplay between food consumption, stem cell biology, and cancer risk,” says Ophir Klein, a professor of medicine at the University of California at San Francisco and Cedars-Sinai Medical Center, who was not involved in the study. “Their work lays a foundation for testing polyamines as compounds that may augment intestinal repair after injuries, and it suggests that careful consideration is needed when planning diet-based strategies for regeneration to avoid increasing cancer risk.”

The research was funded, in part, by a Pew-Stewart Trust Scholar award, the Marble Center for Cancer Nanomedicine, the Koch Institute-Dana Farber/Harvard Cancer Center Bridge Project, and the MIT Stem Cell Initiative.

New technique reveals how gene transcription is coordinated in cells

By capturing short-lived RNA molecules, scientists can map relationships between genes and the regulatory elements that control them.

Anne Trafton | MIT News
June 5, 2024

The human genome contains about 23,000 genes, but only a fraction of those genes are turned on inside a cell at any given time. The complex network of regulatory elements that controls gene expression includes regions of the genome called enhancers, which are often located far from the genes that they regulate.

This distance can make it difficult to map the complex interactions between genes and enhancers. To overcome that, MIT researchers have invented a new technique that allows them to observe the timing of gene and enhancer activation in a cell. When a gene is turned on around the same time as a particular enhancer, it strongly suggests the enhancer is controlling that gene.

Learning more about which enhancers control which genes, in different types of cells, could help researchers identify potential drug targets for genetic disorders. Genomic studies have identified mutations in many non-protein-coding regions that are linked to a variety of diseases. Could these be unknown enhancers?

“When people start using genetic technology to identify regions of chromosomes that have disease information, most of those sites don’t correspond to genes. We suspect they correspond to these enhancers, which can be quite distant from a promoter, so it’s very important to be able to identify these enhancers,” says Phillip Sharp, an MIT Institute Professor Emeritus and member of MIT’s Koch Institute for Integrative Cancer Research.

Sharp is the senior author of the new study, which appears today in Nature. MIT Research Assistant D.B. Jay Mahat is the lead author of the paper.

Hunting for eRNA

Less than 2 percent of the human genome consists of protein-coding genes. The rest of the genome includes many elements that control when and how those genes are expressed. Enhancers, which are thought to turn genes on by coming into physical contact with gene promoter regions through transiently forming a complex, were discovered about 45 years ago.

More recently, in 2010, researchers discovered that these enhancers are transcribed into RNA molecules, known as enhancer RNA or eRNA. Scientists suspect that this transcription occurs when the enhancers are actively interacting with their target genes. This raised the possibility that measuring eRNA transcription levels could help researchers determine when an enhancer is active, as well as which genes it’s targeting.

“That information is extraordinarily important in understanding how development occurs, and in understanding how cancers change their regulatory programs and activate processes that lead to de-differentiation and metastatic growth,” Mahat says.

However, this kind of mapping has proven difficult to perform because eRNA is produced in very small quantities and does not last long in the cell. Additionally, eRNA lacks a modification known as a poly-A tail, which is the “hook” that most techniques use to pull RNA out of a cell.

One way to capture eRNA is to add a nucleotide to cells that halts transcription when incorporated into RNA. These nucleotides also contain a tag called biotin that can be used to fish the RNA out of a cell. However, this current technique only works on large pools of cells and doesn’t give information about individual cells.

While brainstorming ideas for new ways to capture eRNA, Mahat and Sharp considered using click chemistry, a technique that can be used to join two molecules together if they are each tagged with “click handles” that can react together.

The researchers designed nucleotides labeled with one click handle, and once these nucleotides are incorporated into growing eRNA strands, the strands can be fished out with a tag containing the complementary handle. This allowed the researchers to capture eRNA and then purify, amplify, and sequence it. Some RNA is lost at each step, but Mahat estimates that they can successfully pull out about 10 percent of the eRNA from a given cell.

Using this technique, the researchers obtained a snapshot of the enhancers and genes that are being actively transcribed at a given time in a cell.

“You want to be able to determine, in every cell, the activation of transcription from regulatory elements and from their corresponding gene. And this has to be done in a single cell because that’s where you can detect synchrony or asynchrony between regulatory elements and genes,” Mahat says.

Timing of gene expression

Demonstrating their technique in mouse embryonic stem cells, the researchers found that they could calculate approximately when a particular region starts to be transcribed, based on the length of the RNA strand and the speed of the polymerase (the enzyme responsible for transcription) — that is, how far the polymerase transcribes per second. This allowed them to determine which genes and enhancers were being transcribed around the same time.

The researchers used this approach to determine the timing of the expression of cell cycle genes in more detail than has previously been possible. They were also able to confirm several sets of known gene-enhancer pairs and generated a list of about 50,000 possible enhancer-gene pairs that they can now try to verify.

Learning which enhancers control which genes would prove valuable in developing new treatments for diseases with a genetic basis. Last year, the U.S. Food and Drug Administration approved the first gene therapy treatment for sickle cell anemia, which works by interfering with an enhancer that results in activation of a fetal globin gene, reducing the production of sickled blood cells.

The MIT team is now applying this approach to other types of cells, with a focus on autoimmune diseases. Working with researchers at Boston Children’s Hospital, they are exploring immune cell mutations that have been linked to lupus, many of which are found in non-coding regions of the genome.

“It’s not clear which genes are affected by these mutations, so we are beginning to tease apart the genes these putative enhancers might be regulating, and in what cell types these enhancers are active,” Mahat says. “This is a tool for creating gene-to-enhancer maps, which are fundamental in understanding the biology, and also a foundation for understanding disease.”

The findings of this study also offer evidence for a theory that Sharp has recently developed, along with MIT professors Richard Young and Arup Chakraborty, that gene transcription is controlled by membraneless droplets known as condensates. These condensates are made of large clusters of enzymes and RNA, which Sharp suggests may include eRNA produced at enhancer sites.

“We picture that the communication between an enhancer and a promoter is a condensate-type, transient structure, and RNA is part of that. This is an important piece of work in building the understanding of how RNAs from enhancers could be active,” he says.

The research was funded by the National Cancer Institute, the National Institutes of Health, and the Emerald Foundation Postdoctoral Transition Award.

“Rosetta Stone” of cell signaling could expedite precision cancer medicine

An atlas of human protein kinases enables scientists to map cell signaling pathways with unprecedented speed and detail. Michael Yaffe, the David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, a member of MIT’s Koch Institute for Integrative Cancer Research, and a senior author of the new study published in Nature, is hoping to apply the comprehensive atlas of enzymes that regulate a wide variety of cellular activities to individual patients’ tumors to learn more about how the signaling states differ in cancer cancer, which could reveal new

Megan Scudellari | Koch Institute
June 3, 2024

A newly complete database of human protein kinases and their preferred binding sites provides a powerful new platform to investigate cell signaling pathways.

Culminating 25 years of research, MIT, Harvard University, and Yale University scientists and collaborators have unveiled a comprehensive atlas of human tyrosine kinases — enzymes that regulate a wide variety of cellular activities — and their binding sites.

The addition of tyrosine kinases to a previously published dataset from the same group now completes a free, publicly available atlas of all human kinases and their specific binding sites on proteins, which together orchestrate fundamental cell processes such as growth, cell division, and metabolism.

Now, researchers can use data from mass spectrometry, a common laboratory technique, to identify the kinases involved in normal and dysregulated cell signaling in human tissue, such as during inflammation or cancer progression.

“I am most excited about being able to apply this to individual patients’ tumors and learn about the signaling states of cancer and heterogeneity of that signaling,” says Michael Yaffe, who is the David H. Koch Professor of Science at MIT, the director of the MIT Center for Precision Cancer Medicine, a member of MIT’s Koch Institute for Integrative Cancer Research, and a senior author of the new study. “This could reveal new druggable targets or novel combination therapies.”

The study, published in Nature, is the product of a long-standing collaboration with senior authors Lewis Cantley at Harvard Medical School and Dana-Farber Cancer Institute, Benjamin Turk at Yale School of Medicine, and Jared Johnson at Weill Cornell Medical College.

The paper’s lead authors are Tomer Yaron-Barir at Columbia University Irving Medical Center, and MIT’s Brian Joughin, with contributions from Kontstantin Krismer, Mina Takegami, and Pau Creixell.

Kinase kingdom

Human cells are governed by a network of diverse protein kinases that alter the properties of other proteins by adding or removing chemical compounds called phosphate groups. Phosphate groups are small but powerful: When attached to proteins, they can turn proteins on or off, or even dramatically change their function. Identifying which of the almost 400 human kinases phosphorylate a specific protein at a particular site on the protein was traditionally a lengthy, laborious process.

Beginning in the mid 1990s, the Cantley laboratory developed a method using a library of small peptides to identify the optimal amino acid sequence — called a motif, similar to a scannable barcode — that a kinase targets on its substrate proteins for the addition of a phosphate group. Over the ensuing years, Yaffe, Turk, and Johnson, all of whom spent time as postdocs in the Cantley lab, made seminal advancements in the technique, increasing its throughput, accuracy, and utility.

Johnson led a massive experimental effort exposing batches of kinases to these peptide libraries and observed which kinases phosphorylated which subsets of peptides. In a corresponding Nature paper published in January 2023, the team mapped more than 300 serine/threonine kinases, the other main type of protein kinase, to their motifs. In the current paper, they complete the human “kinome” by successfully mapping 93 tyrosine kinases to their corresponding motifs.

Next, by creating and using advanced computational tools, Yaron-Barir, Krismer, Joughin, Takegami, and Yaffe tested whether the results were predictive of real proteins, and whether the results might reveal unknown signaling events in normal and cancer cells. By analyzing phosphoproteomic data from mass spectrometry to reveal phosphorylation patterns in cells, their atlas accurately predicted tyrosine kinase activity in previously studied cell signaling pathways.

For example, using recently published phosphoproteomic data of human lung cancer cells treated with two targeted drugs, the atlas identified that treatment with erlotinib, a known inhibitor of the protein EGFR, downregulated sites matching a motif for EGFR. Treatment with afatinib, a known HER2 inhibitor, downregulated sites matching the HER2 motif. Unexpectedly, afatinib treatment also upregulated the motif for the tyrosine kinase MET, a finding that helps explain patient data linking MET activity to afatinib drug resistance.

Actionable results

There are two key ways researchers can use the new atlas. First, for a protein of interest that is being phosphorylated, the atlas can be used to narrow down hundreds of kinases to a short list of candidates likely to be involved. “The predictions that come from using this will still need to be validated experimentally, but it’s a huge step forward in making clear predictions that can be tested,” says Yaffe.

Second, the atlas makes phosphoproteomic data more useful and actionable. In the past, researchers might gather phosphoproteomic data from a tissue sample, but it was difficult to know what that data was saying or how to best use it to guide next steps in research. Now, that data can be used to predict which kinases are upregulated or downregulated and therefore which cellular signaling pathways are active or not.

“We now have a new tool now to interpret those large datasets, a Rosetta Stone for phosphoproteomics,” says Yaffe. “It is going to be particularly helpful for turning this type of disease data into actionable items.”

In the context of cancer, phosophoproteomic data from a patient’s tumor biopsy could be used to help doctors quickly identify which kinases and cell signaling pathways are involved in cancer expansion or drug resistance, then use that knowledge to target those pathways with appropriate drug therapy or combination therapy.

Yaffe’s lab and their colleagues at the National Institutes of Health are now using the atlas to seek out new insights into difficult cancers, including appendiceal cancer and neuroendocrine tumors. While many cancers have been shown to have a strong genetic component, such as the genes BRCA1 and BRCA2 in breast cancer, other cancers are not associated with any known genetic cause. “We’re using this atlas to interrogate these tumors that don’t seem to have a clear genetic driver to see if we can identify kinases that are driving cancer progression,” he says.

Biological insights

In addition to completing the human kinase atlas, the team made two biological discoveries in their recent study. First, they identified three main classes of phosphorylation motifs, or barcodes, for tyrosine kinases. The first class is motifs that map to multiple kinases, suggesting that numerous signaling pathways converge to phosphorylate a protein boasting that motif. The second class is motifs with a one-to-one match between motif and kinase, in which only a specific kinase will activate a protein with that motif. This came as a partial surprise, as tyrosine kinases have been thought to have minimal specificity by some in the field.

The final class includes motifs for which there is no clear match to one of the 78 classical tyrosine kinases. This class includes motifs that match to 15 atypical tyrosine kinases known to also phosphorylate serine or threonine residues. “This means that there’s a subset of kinases that we didn’t recognize that are actually playing an important role,” says Yaffe. It also indicates there may be other mechanisms besides motifs alone that affect how a kinase interacts with a protein.

The team also discovered that tyrosine kinase motifs are tightly conserved between humans and the worm species C. elegans, despite the species being separated by more than 600 million years of evolution. In other words, a worm kinase and its human homologue are phosphorylating essentially the same motif. That sequence preservation suggests that tyrosine kinases are highly critical to signaling pathways in all multicellular organisms, and any small change would be harmful to an organism.

The research was funded by the Charles and Marjorie Holloway Foundation, the MIT Center for Precision Cancer Medicine, the Koch Institute Frontier Research Program via L. Scott Ritterbush, the Leukemia and Lymphoma Society, the National Institutes of Health, Cancer Research UK, the Brain Tumour Charity, and the Koch Institute Support (core) grant from the National Cancer Institute.

Taking RNAi from interesting science to impactful new treatments

Alnylam Pharmaceuticals is translating the promise of RNA interference (RNAi) research into a new class of powerful, gene-based therapies. These days Alnylam is not the only company developing RNAi-based medicines, but it is still a pioneer in the field. The company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

Zach Winn | MIT News
May 13, 2024

There are many hurdles to clear before a research discovery becomes a life-changing treatment for patients. That’s especially true when the treatments being developed represent an entirely new class of medicines. But overcoming those obstacles can revolutionize our ability to treat diseases.

Few companies exemplify that process better than Alnylam Pharmaceuticals. Alnylam was founded by a group of MIT-affiliated researchers who believed in the promise of a technology — RNA interference, or RNAi.

The researchers had done foundational work to understand how RNAi, which is a naturally occurring process, works to silence genes through the degradation of messenger RNA. But it was their decision to found Alnylam in 2002 that attracted the funding and expertise necessary to turn their discoveries into a new class of medicines. Since that decision, Alnylam has made remarkable progress taking RNAi from an interesting scientific discovery to an impactful new treatment pathway.

Today Alnylam has five medicines approved by the U.S. Food and Drug Administration (one Alnylam-discovered RNAi therapeutic is licensed to Novartis) and a rapidly expanding clinical pipeline. The company’s approved medicines are for debilitating, sometimes fatal conditions that many patients have grappled with for decades with few other options.

The company estimates its treatments helped more than 5,000 patients in 2023 alone. Behind that number are patient stories that illustrate how Alnylam has changed lives. A mother of three says Alnylam’s treatments helped her take back control of her life after being bed-ridden with attacks associated with the rare genetic disease acute intermittent porphyria (AIP). Another patient reported that one of the company’s treatments helped her attend her daughter’s wedding. A third patient, who had left college due to frequent AIP attacks, was able to return to school.

These days Alnylam is not the only company developing RNAi-based medicines. But it is still a pioneer in the field, and the company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

“Alnylam has published more than 250 scientific papers over 20 years,” says Sharp, who currently serves as chair of Alnylam’s scientific advisory board. “Not only did we do the science, not only did we translate it to benefit patients, but we also described every step. We established this as a modality to treat patients, and I’m very proud of that record.”

Pioneering RNAi development

MIT’s involvement in RNAi dates back to its discovery. Before Andrew Fire PhD ’83 shared a Nobel Prize for the discovery of RNAi in 1998, he worked on understanding how DNA was transcribed into RNA, as a graduate student in Sharp’s lab.

After leaving MIT, Fire and collaborators showed that double-stranded RNA could be used to silence specific genes in worms. But the biochemical mechanisms that allowed double-stranded RNA to work were unknown until MIT professors Sharp, Bartel, and Ruth Lehmann, along with Zamore and Tuschl, published foundational papers explaining the process. The researchers developed a system for studying RNAi and showed how RNAi can be controlled using different genetic sequences. Soon after Tuschl left MIT, he showed that a similar process could also be used to silence specific genes in human cells, opening up a new frontier in studying genes and ultimately treating diseases.

“Tom showed you could synthesize these small RNAs, transfect them into cells, and get a very specific knockdown of the gene that corresponded to that the small RNAs,” Bartel explains. “That discovery transformed biological research. The ability to specifically knockdown a mammalian gene was huge. You could suddenly study the function of any gene you were interested in by knocking it down and seeing what happens. … The research community immediately started using that approach to study the function of their favorite genes in mammalian cells.”

Beyond illuminating gene function, another application came to mind.

“Because almost all diseases are related to genes, could we take these small RNAs and silence genes to treat patients?” Sharp remembers wondering.

To answer the question, the researchers founded Alnylam in 2002. (They recruited Schimmel, a biotech veteran, around the same time.) But there was a lot of work to be done before the technology could be tried in patients. The main challenge was getting RNAi into the cytoplasm of the patients’ cells.

“Through work in Dave Bartel and Phil Sharp’s lab, among others, it became evident that to make RNAi into therapies, there were three problems to solve: delivery, delivery, and delivery,” says Alnylam Chief Scientific Officer Kevin Fitzgerald, who has been with the company since 2005.

Early on, Alnylam collaborated with MIT drug delivery expert and Institute Professor Bob Langer. Eventually, Alnylam developed the first lipid nanoparticles (LNPs) that could be used to encase RNA and deliver it into patient cells. LNPs were later used in the mRNA vaccines for Covid-19.

“Alnylam has invested over 20 years and more than $4 billion in RNAi to develop these new therapeutics,” Sharp says. “That is the means by which innovations can be translated to the benefit of society.”

From scientific breakthrough to patient bedside

Alnylam received its first FDA approval in 2018 for treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis, a rare and fatal disease. It doubled as the first RNAi therapeutic to reach the market and the first drug approved to treat that condition in the United States.

“What I keep in mind is, at the end of the day for certain patients, two months is everything,” Fitzgerald says. “The diseases that we’re trying to treat progress month by month, day by day, and patients can get to a point where nothing is helping them. If you can move their disease by a stage, that’s huge.”

Since that first treatment, Alnylam has updated its RNAi delivery system — including by conjugating small interfering RNAs to molecules that help them gain entry to cells — and earned approvals to treat other rare genetic diseases along with high cholesterol (the treatment licensed to Novartis). All of those treatments primarily work by silencing genes that encode for the production of proteins in the liver, which has proven to be the easiest place to deliver RNAi molecules. But Alnylam’s team is confident they can deliver RNAi to other areas of the body, which would unlock a new world of treatment possibilities. The company has reported promising early results in the central nervous system and says a phase one study last year was the first RNAi therapeutic to demonstrate gene silencing in the human brain.

“There’s a lot of work being done at Alnylam and other companies to deliver these RNAis to other tissues: muscles, immune cells, lung cells, etc.,” Sharp says. “But to me the most interesting application is delivery to the brain. We think we have a therapeutic modality that can very specifically control the activity of certain genes in the nervous system. I think that’s extraordinarily important, for diseases from Alzheimer’s to schizophrenia and depression.”

The central nervous system work is particularly significant for Fitzgerald, who watched his father struggle with Parkinson’s.

“Our goal is to be in every organ in the human body, and then combinations of organs, and then combinations of targets within individual organs, and then combinations of targets within multi-organs,” Fitzgerald says. “We’re really at the very beginning of what this technology is going do for human health.”

It’s an exciting time for the RNAi scientific community, including many who continue to study it at MIT. Still, Alnylam will need to continue executing in its drug development efforts to deliver on that promise and help an expanding pool of patients.

“I think this is a real frontier,” Sharp says. “There’s major therapeutic need, and I think this technology could have a huge impact. But we have to prove it. That’s why Alnylam exists: to pursue new science that unlocks new possibilities and discover if they can be made to work. That, of course, also why MIT is here: to improve lives.”

Scientists develop a rapid gene-editing screen to find effects of cancer mutations

With the new technique, MIT researchers hope to identify mutations that could be targeted with new cancer therapies.

Anne Trafton | MIT News
March 12, 2024

Tumors can carry mutations in hundreds of different genes, and each of those genes may be mutated in different ways — some mutations simply replace one DNA nucleotide with another, while others insert or delete larger sections of DNA.

Until now, there has been no way to quickly and easily screen each of those mutations in their natural setting to see what role they may play in the development, progression, and treatment response of a tumor. Using a variant of CRISPR genome-editing known as prime editing, MIT researchers have now come up with a way to screen those mutations much more easily.

The researchers demonstrated their technique by screening cells with more than 1,000 different mutations of the tumor suppressor gene p53, all of which have been seen in cancer patients. This method, which is easier and faster than any existing approach, and edits the genome rather than introducing an artificial version of the mutant gene, revealed that some p53 mutations are more harmful than previously thought.

This technique could also be applied to many other cancer genes, the researchers say, and could eventually be used for precision medicine, to determine how an individual patient’s tumor will respond to a particular treatment.

“In one experiment, you can generate thousands of genotypes that are seen in cancer patients, and immediately test whether one or more of those genotypes are sensitive or resistant to any type of therapy that you’re interested in using,” says Francisco Sanchez-Rivera, an MIT assistant professor of biology, a member of the Koch Institute for Integrative Cancer Research, and the senior author of the study.

MIT graduate student Samuel Gould is the lead author of the paper, which appears today in Nature Biotechnology.

Editing cells

The new technique builds on research that Sanchez-Rivera began 10 years ago as an MIT graduate student. At that time, working with Tyler Jacks, the David H. Koch Professor of Biology, and then-postdoc Thales Papagiannakopoulos, Sanchez-Rivera developed a way to use CRISPR genome-editing to introduce into mice genetic mutations linked to lung cancer.

In that study, the researchers showed that they could delete genes that are often lost in lung tumor cells, and the resulting tumors were similar to naturally arising tumors with those mutations. However, this technique did not allow for the creation of point mutations (substitutions of one nucleotide for another) or insertions.

“While some cancer patients have deletions in certain genes, the vast majority of mutations that cancer patients have in their tumors also include point mutations or small insertions,” Sanchez-Rivera says.

Since then, David Liu, a professor in the Harvard University Department of Chemistry and Chemical Biology and a core institute member of the Broad Institute, has developed new CRISPR-based genome editing technologies that can generate additional types of mutations more easily. With base editing, developed in 2016, researchers can engineer point mutations, but not all possible point mutations. In 2019, Liu, who is also an author of the Nature Biotechnology study, developed a technique called prime editing, which enables any kind of point mutation to be introduced, as well as insertions and deletions.

“Prime editing in theory solves one of the major challenges with earlier forms of CRISPR-based editing, which is that it allows you to engineer virtually any type of mutation,” Sanchez-Rivera says.

When they began working on this project, Sanchez-Rivera and Gould calculated that if performed successfully, prime editing could be used to generate more than 99 percent of all small mutations seen in cancer patients.

However, to achieve that, they needed to find a way to optimize the editing efficiency of the CRISPR-based system. The prime editing guide RNAs (pegRNAs) used to direct CRISPR enzymes to cut the genome in certain spots have varying levels of efficiency, which leads to “noise” in the data from pegRNAs that simply aren’t generating the correct target mutation. The MIT team devised a way to reduce that noise by using synthetic target sites to help them calculate how efficiently each guide RNA that they tested was working.

“We can design multiple prime-editing guide RNAs with different design properties, and then we get an empirical measurement of how efficient each of those pegRNAs is. It tells us what percentage of the time each pegRNA is actually introducing the correct edit,” Gould says.

Analyzing mutations

The researchers demonstrated their technique using p53, a gene that is mutated in more than half of all cancer patients. From a dataset that includes sequencing information from more than 40,000 patients, the researchers identified more than 1,000 different mutations that can occur in p53.

“We wanted to focus on p53 because it’s the most commonly mutated gene in human cancers, but only the most frequent variants in p53 have really been deeply studied. There are many variants in p53 that remain understudied,” Gould says.

Using their new method, the researchers introduced p53 mutations in human lung adenocarcinoma cells, then measured the survival rates of these cells, allowing them to determine each mutation’s effect on cell fitness.

Among their findings, they showed that some p53 mutations promoted cell growth more than had been previously thought. These mutations, which prevent the p53 protein from forming a tetramer — an assembly of four p53 proteins — had been studied before, using a technique that involves inserting artificial copies of a mutated p53 gene into a cell.

Those studies found that these mutations did not confer any survival advantage to cancer cells. However, when the MIT team introduced those same mutations using the new prime editing technique, they found that the mutation prevented the tetramer from forming, allowing the cells to survive. Based on the studies done using overexpression of artificial p53 DNA, those mutations would have been classified as benign, while the new work shows that under more natural circumstances, they are not.

“This is a case where you could only observe these variant-induced phenotypes if you’re engineering the variants in their natural context and not with these more artificial systems,” Gould says. “This is just one example, but it speaks to a broader principle that we’re going to be able to access novel biology using these new genome-editing technologies.”

Because it is difficult to reactivate tumor suppressor genes, there are few drugs that target p53, but the researchers now plan to investigate mutations found in other cancer-linked genes, in hopes of discovering potential cancer therapies that could target those mutations. They also hope that the technique could one day enable personalized approaches to treating tumors.

“With the advent of sequencing technologies in the clinic, we’ll be able to use this genetic information to tailor therapies for patients suffering from tumors that have a defined genetic makeup,” Sanchez-Rivera says. “This approach based on prime editing has the potential to change everything.”

The research was funded, in part, by the National Institute of General Medical Sciences, an MIT School of Science Fellowship in Cancer Research, a Howard Hughes Medical Institute Hanna Gray Fellowship, the V Foundation for Cancer Research, a National Cancer Institute Cancer Center Support Grant, the Ludwig Center at MIT, a Koch Institute Frontier Award, the MIT Research Support Committee, and the Koch Institute Support (core) Grant from the National Cancer Institute.

How phase separation is revolutionizing biology

Postdocs from Whitehead Institute Member Richard A. Young's lab found that imaging and molecular manipulation reveal how biomolecular condensates form and offer clues to the role of phase separation in health and disease.

February 27, 2024
News brief: Calo Lab

How do cells respond to disruptions in splicing?

Lillian Eden | Department of Biology
March 4, 2024

New research from the Calo Lab in the Department of Biology has identified the protein Mdm2 generating a form that activates a cascade of cellular stress responses when splicing is disrupted.

To create proteins, DNA is transcribed into RNA, and that RNA is then “translated” into protein. Between the creation of the RNA and the translation to protein is often a step called splicing. During splicing, segments called introns are removed, and the remaining pieces, called exons, are joined together to form the blueprint for translation. By splicing together different exons, the cell can create different proteins from the same section of genetic code. When splicing goes awry, it can lead to diseases and cancers. 

New research recently published in Disease Models & Mechanisms from the Calo Lab in the Department of Biology at MIT has identified the mechanism for how cells respond to disruptions in splicing, which involves activating a cellular stress response. The stress response, once activated, causes widespread effects, including changes to cell metabolism. 

Researchers have discovered cellular stress responses for other core cellular processes, such as ribosome biogenesis. However, this is the first time researchers have identified how cells respond to perturbing the splicing process.

A particular protein acts as a kind of canary in a coal mine: Mdm2, which responds to a broad range of splicing disruptions. Mdm2 does not cause a stress response by itself. Rather, Mdm2 is itself spliced differently in response to splicing disruptions. Downstream, the alternative splicing of Mdm2 leads to the activation of a protein called p53, which is known to orchestrate a cascade of responses to stress.

Researchers have long wondered why some cell types seem more sensitive to splicing disruptions than others. For example, some disorders caused by mutations in proteins that perform RNA splicing, despite affecting the whole organism, induce more noticeable changes in tissues derived from the neural crest—a collection of stem cells that contributes to the formation of the face, jaw, retinas, limbs, and heart during development. Certain splicing inhibitors have also increased the effectiveness of some cancer treatments, but the mechanism is unknown. 

One of the p53-induced stress responses includes changing the metabolism of cells and how they use sugars, which may explain why some cells are more sensitive to splicing disruptions than others. Inhibiting glycolysis, the reactions that extract energy from glucose, can affect how cells divide and migrate. 

The way cells divide and migrate is critical during development; in experiments, zebrafish treated with glycolysis inhibitors exhibited similar changes to craniofacial features as those where splicing was disrupted. Cancerous cells, too, are known to require high levels of sugar metabolism and, therefore, may be especially sensitive to treatments that induce changes in the splicing pathway. 

The researchers knocked down genes to mimic milder splicing disruptions instead of knocking them out entirely. Splicing is so essential that knocking out the splicing machinery can lead to extreme responses like cell death. In organismal models like zebrafish, those severe phenotypes don’t accurately reflect how splicing disruptions present in human diseases.

First author Jade Varineau, a graduate student in the Calo lab, was drawn to the project because it allowed her to explore what was happening at the RNA and cellular level while also observing how splicing perturbations were affecting the whole organism. 

“I think this data can help us reframe the way we think about diseases and cancers that are impacted by splicing—that a treatment that works for one may work for another because all the symptoms may stem from the same cellular response,” Varineau says. 

Although the results indicate how cells broadly respond to splicing perturbations, the mechanism for how disruptions in splicing induce the alternate splicing of Mdm2 remains unclear. Senior author Eliezer Calo says the lab is also exploring how splicing mechanisms may be altered for things like cancer. Their work, he says, opens the door for further exploration of cell-type specificity of genetic disorders and improvements in cancer treatments using splicing inhibitors. 

 “We know that the sensor is encoded in the gene Mdm2—what are the molecules that allow Mdm2 to act as a sensor, and how does the sensor malfunction for things like cancer?” Calo says. “The next step is to find out how the sensor works.”  

How early-stage cancer cells hide from the immune system

A new study finds precancerous colon cells turn on a gene called SOX17, which helps them evade detection and develop into more advanced tumors.

Anne Trafton | MIT News
February 28, 2024

One of the immune system’s primary roles is to detect and kill cells that have acquired cancerous mutations. However, some early-stage cancer cells manage to evade this surveillance and develop into more advanced tumors.

A new study from MIT and Dana-Farber Cancer Institute has identified one strategy that helps these precancerous cells avoid immune detection. The researchers found that early in colon cancer development, cells that turn on a gene called SOX17 can become essentially invisible to the immune system.

If scientists could find a way to block SOX17 function or the pathway that it activates, this may offer a new way to treat early-stage cancers before they grow into larger tumors, the researchers say.

“Activation of the SOX17 program in the earliest innings of colorectal cancer formation is a critical step that shields precancerous cells from the immune system. If we can inhibit the SOX17 program, we might be better able to prevent colon cancer, particularly in patients that are prone to developing colon polyps,” says Omer Yilmaz, an MIT associate professor of biology, a member of MIT’s Koch Institute for Integrative Cancer Research, and one of the senior authors of the study.

Judith Agudo, a principal investigator at Dana-Farber Cancer Institute and an assistant professor at Harvard Medical School, is also a senior author of the study, which appears today in Nature. The paper’s lead author is MIT Research Scientist Norihiro Goto. Other collaborators include Tyler Jacks, a professor of biology and a member of MIT’s Koch Institute; Peter Westcott, a former Jacks lab postdoc who is now an assistant professor at Cold Spring Harbor Laboratory; and Saori Goto, an MIT postdoc in the Yilmaz lab.

Immune evasion

Colon cancer usually arises in long-lived cells called intestinal stem cells, whose job is to continually regenerate the lining of the intestines. Over their long lifetime, these cells can accumulate cancerous mutations that lead to the formation of polyps, a type of premalignant growth that can eventually become metastatic colon cancer.

To learn more about how these precancerous growths evade the immune system, the researchers used a technique they had previously developed for growing mini colon tumors in a lab dish and then implanting them into mice. In this case, the researchers engineered the tumors to express mutated versions of cancer-linked genes Kras, p53, and APC, which are often found in human colon cancers.

Once these tumors were implanted in mice, the researchers observed a dramatic increase in the tumors’ expression of SOX17. This gene encodes a transcription factor that is normally active only during embryonic development, when it helps to control development of the intestines and the formation of blood vessels.

The researchers’ experiments revealed that when SOX17 is turned on in cancer cells, it helps the cells to create an immunosuppressive environment. Among its effects, SOX17 prevents cells from synthesizing the receptor that normally detects interferon gamma, a molecule that is one of the immune system’s primary weapons against cancer cells.

Without those interferon gamma receptors, cancerous and precancerous cells can simply ignore messages from the immune system, which would normally direct them to undergo programmed cell death.

“One of SOX17’s main roles is to turn off the interferon gamma signaling pathway in colorectal cancer cells and in precancerous adenoma cells. By turning off interferon gamma receptor signaling in the tumor cells, the tumor cells become hidden from T cells and can grow in the presence of an immune system,” Yilmaz says.

Without interferon gamma signaling, cancer cells also minimize their production of molecules called MHC proteins, which are responsible for displaying cancerous antigens to the immune system. The cells’ insensitivity to interferon gamma also prevents them from producing immune molecules called chemokines, which normally recruit T cells that would help destroy the cancerous cells.

Targeting SOX17

When the researchers generated colon tumor organoids with SOX17 knocked out, and implanted those into mice, the immune system was able to attack those tumors much more effectively. This suggests that preventing cancer cells from turning off SOX17 could offer a way to treat colon cancer in its earliest stages.

“Just by turning off SOX17 in fairly complex tumors, we were able to essentially obliterate the ability of these tumor cells to persist,” Goto says.

As part of their study, the researchers also analyzed gene expression data from patients with colon cancer and found that SOX17 tended to be highly expressed in early-stage colon cancers but dropped off as the tumors became more invasive and metastatic.

“We think this makes a lot of sense because as colorectal cancers become more invasive and metastatic, there are other mechanisms that create an immunosuppressive environment,” Yilmaz says. “As the colon cancer becomes more aggressive and activates these other mechanisms, then there’s less importance for SOX17.”

Transcription factors such as SOX17 are considered difficult to target using drugs, in part because of their disorganized structure, so the researchers now plan to identify other proteins that SOX17 interacts with, in hopes that it might be easier to block some of those interactions.

The researchers also plan to investigate what triggers SOX17 to turn on in precancerous cells.

The research was funded by the MIT Stem Cell Initiative via Fondation MIT, the National Institutes of Health/National Cancer Institute, and a Koch Institute-Dana Farber Harvard Cancer Center Bridge Project grant.