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.

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 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.