MiSciWriters is proud to partner with the University of Michigan Center for RNA Biomedicine to provide a live coverage of the 2nd annual symposium: “RNA in Precision Medicine.” We will live-blog the events here, and live-tweet from @MiSciWriters 9:10 am to 3:15 pm. on March 31st.
Live-blogging coverage is released as an event unfolds, placing the posts in reverse-chronological order. So if you want to read everything, start from the bottom of the page.
We hope you’ll join in the conversation by commenting below or tweeting with the hashtag #umichRNA. Enjoy!
“Sequence-based rational design of small molecules targeting RNA”
Keynote Speaker : Matt Disney, PhD
Blogger: Sarah Kearns
Editor: Ada Hagan
Through the screen that Disney developed, he was able to identify a set of miRNA motifs that respond to a certain small molecule drug. To confirm that these small molecules actually do bind and inhibit breast cancer propagation miRNAs, they show that both precursor RNA levels and the miRNAs are decreased with addition of the small molecule inhibitor within a cell. This means that the initial genome product is accumulated, but not fully developed to an miRNA.
But drug discovery is never smooth sailing. In this case, the miRNA does not have much surface area for a molecule to bind and therefore is not suitable for further studies. This leads Disney to try to optimize their small molecule.
Because their screening system easily identifies RNA motifs, they hypothesized that they could target two motifs with the same drug and essentially have double the affinity, specificity, and potency. When tested on miRNA-210, whose elevated levels have been implicated in breast cancers, their newly identified RNA-targeting molecule (named Targapemir-210), was shown to inhibit miRNA-210 only in cells that had breast cancer mutations. This implies that their molecule has a good cell environment sensitivity, i.e. it works in diseased cells but not healthy cells.
Disney gives convincing evidence that rational drug design, therefore, is possible even with complicated RNA structures that have very similar structures and motifs.
Disney’s talk was the final in a full day of speakers describing new advances in RNA discovery and technology.
Disney starts his talk by marveling at the fact that the advances in genome sequencing have rapidly outpaced Moore’s Law, which predicts a doubling off events over a decade. Most recent cost estimates are only about 1K per genome. The decrease in cost and increase in available technologies lead to an interest in looking at the proteome, the downstream products of the genome. But as previously mentioned, protein products are relatively small with respect to the products that come from DNA sequencing. Instead, he proposes that more work ought to be done on RNA targeting.
Like proteins, RNA can fold into secondary structures and like DNA, RNA can make base pairs with itself.
Disney’s lab uses a sequence-based approach to design small molecules that target RNA structures. Essentially, he wants to establish a database that identifies what type of small molecules bind to certain RNA motifs (a particular folding pattern or sequence). They were able to do this by probing both RNA space and small molecule space at the same time by incubating RNA with a small molecule of interest. Crosslinking (chemically linking two molecules together permanently) allows for identification and screening to identify an RNA motif with an affinity for a particular small molecule. Competition studies are able to give a gradient of selectivity and affinity per molecule per RNA motif. In other words, he can measure how tightly particular small molecules and RNA structures interact.
In a more applied sense, Disney turns to focus on the dysregulation of miRNA within a cell, which can happen in breast cancers. However, this turns out to be extremely tricky. He asks: do miRNAs have similar motifs? Do different miRNA have identical motifs and if so, how do we target one motif over another?
Matt Disney earned his bachelor’s in Chemistry at the University of Rochester then went on to University of Maryland for a Masters in Chemistry before returning to Rochester for his PhD in Biophysical Chemistry. Afterwards he did a postdoc at the Swiss Federal Institute of Technology and became an Assistant Professor at SUNY Buffalo. There, he was awarded the Excellent Scholar Young Investigator Award. Currently, he is a principal investigator at the Scripps Research Institute in Florida.
Disney’s research focus is on rational drug design, which is the strategy of creating new molecules with unique functionalities based on the predicted shape of the target. More specifically, his lab focuses on designing very selective drugs that are based on the genome sequence. Within a protein context, it can be very difficult to predict the 3D structure of a complex biomolecule and RNA structure predictions face a similar issue. Moreover, many RNAs can have similar folds making a selective drug hard to identify because many RNA’s with different biological functions can have similar conformations. The goal of Disney’s research is to identify unique patterns in RNA sequence that relate to the 3D structure.
Before we go much further, we must ask ourselves: is RNA a worthwhile drug target?
Historically, RNA has been labeled as “undruggable” since many different types of RNA have similar folds and little surface area for a potential drug to even bind to. Despite these complications, RNA has been implicated in many regulatory roles within the cell, suggesting that RNA has significant biological activity. Moreover, even though an enormous amount of focus is on the proteome (the entire set of proteins within a biological system), only 2% of the genome leads to any protein product. Colloquially, the remaining 98% of DNA has been labeled as junk, but recently this description has been called into question as it has been shown to have crucial roles in DNA regulation through RNAs generated from this “junk” code.
Peter Todd, MD PhD; University of Michigan
“How RNA repeats elicit unconventional translation of toxic proteins in Amyotrophic Lateral Sclerosis”
Blogger: Jimmy Brancho
Editor: Jessica Cote, Sarah Kearns
This afternoon’s symposium has mainly focused on messages sent by RNA and how they factor into cancer and disease. Researchers are learning how these RNA-based messages function with the goal of finding a way to interrupt aberrant messages to help prevent the spread of cancer and other diseases.
Dr. Peter Todd, an Associate Professor in Michigan Medicine’s Neurology Department, looks at RNA’s role in a different sphere of diseases. Fragile X syndrome and myotonic dystrophy are both neurodegenerative conditions – diseases in which the body’s nerves gradually become less effective over time. Todd thinks that RNA plays a critical role in causing these diseases.
More specifically, an error called a repeat expansion can occur while a cell builds a molecule of RNA. If the cell were typing out an RNA code on a keyboard, a repeat expansion would happen when one of the keys gets stuck downnnnnnnnnnn (and there’s no backspace key). The cell sends out the defective RNA anyway, and Todd wants to know how that affects neurodegenerative diseases like Fragile X.
Todd’s lab has taken particular interest in how the repeat expansions get translated into proteins that shouldn’t be created in the first place. Why are these proteins being made when the RNA isn’t signaling as they should be? What happens to the rogue proteins once they are made?
One of Todd’s findings is that the proteins essentially turn into cellular “junk” and form clumps of protein called aggregates. The presence of protein aggregates is associated with several diseases. Additionally, the highly-repeated RNA can coil around itself and form secondary structures. The clump of RNA can then impede the cellular machinery on its own whether the cell makes rogue proteins from it or not, and Todd’s lab has correlated this process with decreased efficiency for the cell’s protein production overall. Whether the cell tries to make “junk” protein from it or it just gets in the way, RNA with repeat expansions doesn’t appear to be benefiting our cells and may actually be actively harmful.
Ribosome Sliding on Homopolymeric A and U Sequences
Blogger: Jimmy Brancho
Editor: Ada Hagan
Our bodies rely on the tiniest of cellular machines to translate our genetic code from DNA into mRNA and then into proteins and tissues. The ribosome, colloquially referred to as the protein factory, gets the job from mRNA to protein done. Sometimes, though, the ribosome gets bad instructions, and sometimes the ribosome itself is broken. What happens then?
Dr. Kristin Koutmou, Assistant Professor of Chemistry in the University of Michigan’s Chemical Biology Doctoral Program, puts it best on her research group’s website: “What happens when the ribosome goes awry?” Koutmou looks into what happens after a ribosome attempts to process a defective RNA code, how that error might lead to disease, and how the cell cleans up after its own mistakes to keep the situation under control.
Koutmou specifically addresses the situation in which a given RNA molecule is missing an essential part: the piece that signals the end of the code sequence. This can happen in about 5-10% of RNAs. When mRNA is missing a stop codon, ribosomes try to over-incorporate the amino acid lysine into their creations; Koutmou finds that this results in decreased protein production overall.
Koutmou’s experiments suggest that when the ribosome finds a sequence that would produce several lysines in a row, it gets stuck moving back and forth over the same bit of the sequence until the process grinds to a halt. She suggests that the reason behind the sticking is the high positive charge associated with lysine. This seems to occur most frequently when the codons are composed of either three adenosines (A’s) or uracils (U’s) in a row.
Muneesh Tewari, MD PhD University of Michigan
“Extracellular RNA, Biomarkers, and the Future of Disease Interception”
Blogger: Jimmy Blancho
Editor: Sarah Kearns
“Ultimately, almost all biomarkers are about prediction,” Tewari said. He clarified that how RNA informs how a disease is progressing isn’t known well enough for a wide enough range of diseases to be clinically successful. Without that wide knowledge base, predicting what will happen to a patient in a clinical setting can’t happen.
But Tewari argued that it’s not just a question of the knowledge base. Biological systems are extremely complicated and the window of opportunity for a biomarker to be useful can be very small. As a disease progresses from its beginnings, RNA might not produce biomarkers in amounts that clinicians would be suspicious of. Then, when the disease progresses to a certain point, it begins producing higher amounts of the biomarker and starts making enough noise that we know that it’s there. However, that detection point might be too late for the patient. Tewari stressed that the time dimension of disease progression is not studied well enough.
By understanding how biomarker production changes over time rather than in individual snapshots, Tewari thinks that clinicians can learn to be more precise in their suspicion of low levels of biomarkers in the bloodstream. Some ongoing efforts moving forward to solve these issues include some high-time resolution measurements that are catered both to prediction as well as preventative care.
Tewari’s group became interested early on in using RNA prevalence in the blood to determine whether a person is at risk for a disease, particularly cancer. At the time, RNA was believed to be unstable long-term in the bloodstream, making it unlikely that enough would accumulate to serve as a reliable signal that something might be going wrong. But Tewari’s group found that the presence of certain short strands of microRNA is actually associated with prostate cancer.
Not only did this finding open up the door for RNA as a new biomarker, a chemical that is used to detect a certain phenomena such as disease, but by closely examining the kinds of RNA that were found in the blood Tewari’s group found that more detailed information on the progression of the disease could be gleaned. For example, microRNAs associated with decreased blood oxygen were found in some cancer patients. This confirms what is known about cancer metabolism: when tumors are resisting therapeutic treatments they often exhibit decreased oxygen. Connecting these two dots showed Tewari that the RNA in the blood could quickly answer questions about the cancer disease state that might be harder – or, critically for a cancer patient, slower – to find otherwise.
“There’s been great progress in moving this towards the clinic,” Tewari said during his talk. The initial data’s promise pushed researchers to try to develop real-world tests and treatments for patients based on RNA in the bloodstream. But, as Tewari’s next slide stated, “clinical translation is hard!” His lab and others are working hard to make RNA-based therapies a reality outside the laboratory setting.
Your car insurance company just raised your rates again, so they need to send you some bad news. How? They package the letter up in an envelope, slap a stamp on it, and drop it in the mail, and the great beating heart of the United States Postal Service delivers the news to your doorstep. Are the cells in our bodies doing the same thing?
Dr. Muneesh Tewari, Associate Professor of Internal Medicine at Michigan Medicine’s Department of Hematology and Oncology, wants to answer that question. His laboratory studies short strips of chemicals that cells produce called microRNAs. In particular, Tewari thinks that cancer cells produce these microRNAs, package them in tiny cellular envelopes called exosomes, and send them throughout the bloodstream to promote cancer’s spread from one body part to the next.
There is a whole lot of RNA in our cells and its traditional role in cell biology is to move genetic information inside the cell from one place to another. If DNA is the blueprint our bodies, then proteins are the steel beams, bricks, glass, and electrical wiring. RNA, together with the ribosome the construction team, read from the blueprints and make the plan into a real structure. RNA that participates in this process is called coding RNA.
But there are types of RNA in our cells that doesn’t participate at all – noncoding RNA including microRNA – and scientists like Tewari want to find out what it does. The idea that cells are communicating with one another through RNA-filled exosomes is a biomedical research frontier and can be applied to personalized medicine and early detection.
Nancy Cox, PhD; Vanderbilt
“Integrating Genome, Transcriptome and Electronic Health Records for Discovery and Translation”
Blogger: Sarah Kearns
Editor: Molly Kozminsky
A PREDICT-type Trial was done to identify, through phenome patterns, the patients who are most likely to have a reduced gene expression. Cox was able to apply this to neuropsychological phenotypes focusing on fear and phobia. She found an interesting overlap between genes related to phobia with those related to heart problems and severe allergies. Unfortunately, there was an abundance of heart problems that were potentially misdiagnosed as phobia and panic attacks, especially in young women.
With PREDICT being a personalized way to measure RNA interaction with the genome, we are able to focus in on what specific gene expression within an individual that can lead to coordinate regulations. When this data is collected, scaled up, and applied to a large biobank, the VGI is able to have an integrated data set to both raise awareness for these comorbidities as well as with discovering better medicinal treatments that are able to cover the unique pattern of expression of an individual.
Knockout studies are a technique to study a gene by effectively deleting it to see what happens. Dr. Cox’s did a knockout study with zebrafish and silenced the gene encoding for eyes. Eyes in particular have many different phenotypes and as such, this knockout could have many different effects. Afterwards, the researchers tracked to see what, if any, other effects were seen within the fish. Most notably and surprisingly, they saw a few different phenotypes. A fraction of fish ended up with only one eye, some fish had one normal eye and one small, and other fish had no eyes at all.
We’re starting to see that DNA inheritance can fall on a spectrum from classic Mendelian genetics to something much more complex. Consequently, a knockout study can yield a range of phenotypes including losses of function, deleterious function, and simply lower gene expression.
Cox went onto study these genomic overlaps in human conditions such as skin blistering and schizophrenia and was able to see associations to other similar phenotypes. This means that a person with a Mendelian disease might have features that become contributing factors to other similar biological problems. However, there is a bigger population that, instead of having an easy dominant-recessive (yes-no) phenotype for a gene, just has lower gene expression. This could mean that these patients, instead of needing pharmaceutically derived drugs, could use dietary supplements to help their body return to a non-diseased state.
Many environmental exposures can affect our epigenetics. Factors such as smoking can affect an individual’s DNA without actually changing the genome. However, using the open source software PrediXcan and GTEx, we can get a good sense of a prediction of phenotype from gene expression.
A Phenome-wide Association Study (PheWAS) takes a single gene mutation product and scans against all of the medical records that contain that gene, essentially annotating the medical genome. Researchers are trying to probe the biology of the gene, not only on an individual, but trying to scale that up to be able to predict disease state phenotypes across a population. With the databank at VGI containing 2.6 million medical records containing everything from images to pharmaceutical records, they are certainly able to get a big picture of the medical genome.
With this information they are able to map a phenotype, for example acidosis, to a specific gene. This was validated by taking a gene and checking downstream expression and subsequent predicted phenotype. However this also suggests that there are multiple gene products that lead to the same phenotype which opens the door to personalized or combinatory medicine.
Nancy Cox is a professor of medicine and director of the Division of Genetic Medicine in the Department of Medicine at Vanderbilt University. She was recruited to Vanderbilt in 2015 to lead the Vanderbilt Genetics Institute (VGI). The VGI’s mission is to “promote genomic discovery and advance understanding of the human genome” and as such, Dr. Cox develops of methods to better analyze genomic data.
The human genome is becoming easier and cheaper to obtain. However, the ability to predict which genetic variants or small mutations will cause a significant change in observable characteristics, or phenotypes, has been a very difficult task. This is partially because there is a lot of redundancy in our protein sequences to have a buffer system in place to make sure small transcriptions mistakes do not severely harm us. For example, a single nucleotide mutation will not necessarily result in an incorrect protein product.
Dr. Cox studies the interaction between the genome, the full DNA sequence, and the transcriptome, the gene products that are actually formed. This is difficult to study, especially in humans, because: 1) each individual has a unique DNA sequence, and 2) depending on modifications, it may or may not be possible for a specific gene to be transcribed.
Mapping DNA and transcription products can be done with genome-wide association studies (GWAS), which is an examination of all the genetic variants of different individuals across an entire genome to see if variants are associated with a trait. For an example, a study might focus in on a certain DNA mutation and see if it correlates to a phenotype, or an observable characteristic, in a person. The Cox lab in particular has developed a method called PrediXcan that is able to predict the amount of gene expression based on an individual profile.
Laura Scott, PhD: University of Michigan
“The genetic regulatory signature of type 2 diabetes in pancreatic islets”
Blogger: David Mertz
Editor: Sarah Kearns
Dr. Laura Scott, a professor and researcher in Michigan’s own School of Public Health, studies type II diabetes (T2D). Dr. Scott’s research aims to understand the genetics that give rise to T2D as well as how the pertinent genes are regulated in the pancreatic islet cells. These islets are regions within the pancreas that produce insulin for the body and are crucial for metabolism.
She has been able to use a specialized assay, called ATAC-seq, to identify transcription factors that interact with genes of interest. One such gene is RFX, which, in islet cells, directs insulin secretion. When 420 islet cells were sequenced for RNA, these RFX genes were not differentially expressed between a healthy genome and T2D genome. However, when studying the genes affected by the RFX transcription factor, her research group noticed a substantial difference, confirming that an RNA footprint could be used to study differences between healthy-functioning pancreatic cells and ones associated with disease.
Yan Zhang, PhD; University of Michigan
“The Biology and Molecular Mechanism of the Neisseria meningtidis CRISPR-Cas9 Pathway”
Blogger: David Mertz
Editor: Irene Park
Dr. Zhang shares how this mechanism has been identified in different strains of bacteria in nature, where it was first discovered, as a mechanism to defend bacteria against hijacking by bacteriophage genetic material. But, bacteriophage viruses have become smarter too, to become better predators. To accompany the single-strand DNA which they inject into bacteria, the viruses can also add Cas-9 inhibitors, preventing the bacteria from being able to cleave foreign virus sequences from its own DNA.
Professor Yan Zhang of Michigan’s Biological Chemistry department introduces the role of RNA is CRISPR-Cas9 (CC9) gene editing. CC9 has generated excitement in many areas of biomedical research for its precision in identifying specific gene sequences in cells and altering them. This specificity is enabled by RNA guidance of a Cas9 enzyme, which, when reaching the DNA sequence matched to the guide RNA, cleaves the DNA segment from the genome, deleting it from the sequence.
Thomas Tuschl PhD; HHMI & Rockefeller University
“RNA Sequencing Analysis and its Diagnostic Potential”
Blogger: Shweta Ramdas
Editor: Molly Kozminsky
Dr. Tuschl briefly talks about generation of a human reference transcriptome and large scale RNA-seq data management, analysis, and reporting using ANVESANA (in collaboration with Manjunath Kustagi). With such large datasets, indexing and storing data becomes an important component of data organization. Dr. Tuschl talks about the data storage facility at Rockefeller University used to store and analyse > 70000 RNA-Seq datasets (this facility, with 1.3 petabyte storage, comprises 15% of the supercomputing facilities at Rockefeller University!).
Dr. Tuschl moves on to talk about creating reference extracellular RNA (exRNA) profiles of healthy controls. Can we identify expression signatures specific to individuals, or that correlated with biological covariates like sex or age?
Plasma is full of secreted DNases and RNases, enzymes which break down DNA and RNA, respectively; this makes recovery of nucleic acids from extracellular plasma particularly difficult. We need specialized protocols to obtain DNA/RNA that is not degraded. Dr. Tuschl’s group has developed such protocols. RNA and DNA is sequentially isolated from the same sample; small RNA libraries are created using barcodes for small RNAs. They obtained reads from plasma of 13 healthy individuals and serum from six of the same individuals.
The steps of performing a protocol can sometimes introduce biases or influence data sets, because of differences in the ways small differences in the execution of each step can lead to differences in the result. Dr. Tuschl talks about the importance of avoiding technical biases; he strongly advises against using different protocols to deplete platelets, or to perform this procedure in different centers. He cautions that batch effects in these protocols can strongly affect results.
Unsupervised clustering of small RNA profiles revealed differences between serum and plasma. However, we also capture a majority of the red blood cell signatures (as the background) which has to be removed. Dr. Tuschl’s lab asked if we identify differences between males and females from exRNA signatures? It turns out the answer is yes! Some high-abundant small RNAs also show high fold change between the sexes.
Lupus patients have the signature the signaling molecule interferon and in fact, interferon-related genes are found to be differentially expressed in lupus keratinocytes. Tubular interferon response scores are found to be correlated with clinical readouts such as proteinuria, chronicity and glomerular IgG deposition: i.e., the higher your interferon score, the worse your disease condition.
One way to get more sequencing information with the same cost is to sequence only one type of end (the 3’ ends) of transcripts. This allows us to get more information on mRNA abundance (though we lose information on alternative ways RNA is pieced together) Differential expression analysis followed by pathway analysis in tubular cells (in responders versus non-responders to therapy) shows the involvement of the extracellular matrix.
A technology called Fluidigm allows biopsies of multiple tissue types from the same patient, in this case the skin and kidney. Comparing results from the two cell types reveals that skin cells may provide a proxy of gene expression in the kidney as the keratinocytes reveal interferon-induced gene expression signatures.
Thomas Tuschl – Main summary:
- Single-cell RNA-seq analysis of lupus nephritis patient kidney and skin tissue biopsies
- Extracellular small RNA reference profiles in plasma and serum
- Generation of a human reference transcriptome and large-scale RNA-Seq data management, analysis and reporting
Single-cell RNA-seq on patient material. Dr. Tuschl talks about the rapid changes in sequencing technology: a project can begin to feel outdated soon after it begins!
Through the Multi-Ethnic Translational Research Optimization (METRO) Lupus Cohort (NYU), Dr. Tuschl is asking if we can identify gene expression changes in patients with lupus nephritis. They start with a few milligrams of tissue (taken from a biopsy), followed by mRNA sequencing and several assays on chips. Thirty-four biopsies yielded ~900 cells passing quality control, highlighting the low return on investment in current single-cell technologies. To look at cells that have similar levels of expression of certain genes, they can be grouped together through clustering. Clustering of cells by their expression profiles reveals clustering of cells by their cell types: cells belonging to the same cell type (example: kidney cells) cluster together.
Dr. Tuschl talks about the technical difficulties of single-cell RNA-Sequencing. The yield of transcripts is quite low. There is also the issue of contamination/mixing-up of barcodes between different cells, which can confound clustering results.
Differentially expressed genes can reveal the lineage of the cell type. We can also identify lineage-specific marks. For example, the gene SPP1 can be used to distinguish tubular cells, while PECAM1 can be used to identify endothelial cells. Moreover, gene expression patterns can separate sub-populations within tubular cells. This catalog will become more interesting with deeper sequencing (reading regions multiple times) and more cells being sequenced.
Mats Ljungman, PhD; University of Michigan
“Role of miRNA in cellular reprogramming”
Blogger: Shweta Ramdas
Editor: Irene Park
In one study, the researchers converted human fibroblasts to iPSCs (Induced Pluripotent Stem Cells), and then the rate of transcription and RNA degradation were measured in both the fibroblasts and iPSCs to identify differences between the two.
Bru-Seq confirms reprogramming of the cells: 3,000 genes are up-regulated and ~3,000 genes are downregulated. What about post-transcriptional changes (which can’t be detected using RNA-Seq alone) BruChase-Seq can help identify these changes. Two genes, MAPK6 and HMGA2, show post-transcriptional differences between the two cell types.
788 genes post-transcriptionally up-regulated, and 1,069 genes are down-regulated significantly in iPSC (n=4).
Cell-stage specific miRNAs can also be detected using these techniques. For instance, miR-205 is heavily transcribed in iPSCs but not in fibroblasts. There is a massive reorganization of miRNAs as the cell is reprogrammed to iPSC. 134 miRNAs are up-regulated and 124 miRNAs are down-regulated (at least by 10 fold!) miRNAs could play a major role in post-transcriptional reprogramming: Dr. Ljungman hypothesis that miRNA clusters act as “Velcro” to stabilize the cellular state laid down by transcription factors.
Dr. Ljungman generously offers his lab’s techniques to analyze other labs’ samples for them.
RNA-Seq, a technique that sequences all RNAs in the cell, looks at the “steady state” of RNA, which does not necessarily look at RNAs as they are being produced. Two other techniques help measure rates of RNA synthesis and RNA degradation, called Bru-Seq and BruChase-Seq, respectively.
One major different between the two processes is that Bru-Seq shows reveals introns and exons (Bru-Seq). On the other hand, in BruChase-Seq, when the researchers let the RNA to “age,” there were no introns in the final data.
Jiaqi Shi, MD/PhD; University of Michigan
“A MicroRNA Links TGF-β Signaling Pathway to Histone Modification”
Blogger: David Mertz
Editor: Irene Park
One specific signal induced by a protein called TGFb, reduces one type of histone modification, as it turns out, by increasing transcription of a micro-RNA. This micro-RNA interferes with the RNA messenger to create histone modifier proteins.
As the true relationship between these players: cell signaling, micro-RNAs, and histone modification is resolved, she may be able to elucidate some of the early origins of cancer formation.
Dr. Shi is a research clinician in University of Michigan’s Pathology Department who opens by sharing a relationship between cell signaling, chromatin modification, and pancreatic cancer. Chromatin is the substance found in the nucleus of the cell, which includes DNA, but also several proteins that interact with it. These proteins, which include a type called histones, organize DNA, controlling how it is expressed. Signals from outside the cells can affect chromatin, modifying the histone and controlling the gene’s expression.
Frank Slack, PhD; Harvard Medical School
“MicroRNA-based therapeutics in cancer”
Blogger: Molly Kozminsky
Editor: Irene Park
Additionally, the role of miR-34 is not only regulated by its presence: miR-34 amount in the cell can have variable levels of activity. Dr. Slack has been able to show different levels of miR-34 activity based on different stresses and treatments applied to cells. This has led the lab to question the importance of the miRNA amount as opposed to the level of activity of those miRNAs present.
Dr. Slack ended by touching upon the goals of Harvard Medical School with respect to RNA medicine as well as the strategies to promote bench to bedside success. To achieve these goals, they hope to make, move, and use discoveries in the field of miRNA and ultimately initiate clinical trials to take these discoveries to the clinic. The initiatives will hopefully lead to the integration of ncRNAs into patient care. Dr. Slack is excited about the rapid progress of this field, both from his center as well as from the community at large.
Dr. Slack addressed some future directions in the Q&A session, talking about concerns about off-target effects of these molecules given their multiple roles as well as the desire to improve targeted delivery to decrease the requisite doses in therapeutics.
Dr. Slack shows a slide contrasting lungs taken from mouse models of cancer. The one without treatment in incredibly sickly in appearance, while the lung from the mouse that had undergone treatment had a significantly lower tumor burden. While there were concerns about the high number of targets affected by miR-34 leading to conflicting results or unwanted effects, the mice generally responded well to treatment.
The promising results in led to a company with which Dr. Slack collaborated initiating a clinical trial delivering this miRNA using a nanoparticle to liver cancer; however, it was discontinued due to side effects, possibly due to a negative immune response. Dr. Slack is hopeful about future trials, though, because we now are more knowledgeable about miRNA chemistries that could be used in therapeutics.
In addition to applications in liver cancer, miR-34 may also be used in a particularly dangerous form of breast cancer. There were additional challenges in this system as it was harder to deliver the therapeutic to breast cancer than liver cancer.
Additionally, the role of miR-34 is not only regulated by its presence: miR-34 extent in the cell can have variable levels of activity. Dr. Slack has been able to show different levels of miR-34 activity based on different stresses and treatments applied to cells. This has led the lab to question the importance of levels of miRNAs as opposed to the level of activity of those miRNAs present.
Because of their many roles, miRNAs can serve as targeted therapeutics as well as the target of therapeutics. To study miRNAs as therapeutic targets, Dr. Slack’s lab designed a mouse model of cancer. The team was able to induce cancer in these mice by overexpressing a specific miRNA (this miRNA was expressed more in these mice compared to normal mice), which implies that cancer could be treated using a specific molecule that works against that miRNA.
In addition to fighting the miRNAs to fight cancer, the Slack lab is also exploring delivering miRNA as a therapeutic. The miRNA in question, miR-34, was originally discovered in a model organism. Among several known roles, one role of miR-34 is acting as a tumor suppressor, meaning that it could potentially be used to using it to interfere with the processes that lead to cancer in patients.
Aside from the length, miRNAs and coding RNAs are produced differently too, as miRNAs do not follow the “central dogma” of molecular biology. However, some of the typical biological events that can affect the function of coding RNAs can affect miRNAs as well.
Many of the miRNAs implicated in cancer have their origin in the genomic regions associated with cancer, which can lead to their misexpression. Mutations in the enzymes that participate in miRNA biogenesis can lead to cancer, but the role of miRNAs in cancer can also result from their regulation of oncogenes (genes that can promote cancer) or tumor suppressor genes (genes that suppress cancer). As a result of this role, miRNAs are also being explored therapeutically, some ideas leading to clinical trials to treat cancer.
Humans have approximately 5,000 miRNAs, which comprise the majority of ncRNAs. Recent research has revealed new types and shapes of ncRNAs, and as the speaker mentioned, the complexity can be “daunting.” And we’ve only been studying some of them since 1993.
The importance of these ncRNAs is underscored by their importance in nearly every type of human disease, such as heart disease, immune diseases, and cancer. Dr. Slack’s talk focuses on a subset of ncRNAs: microRNAs (miRNAs). As you may suspect from the name, miRNAs are some of the smallest RNAs transcribed from the genome, about 22 base pairs in length. To put this in perspective, coding RNAs are about 2,200 base pairs long on average.
Your DNA provides the information your cells need to function, but there are many steps between the DNA and the action. DNA is first copied into RNA, which allows it to propagate its message. Some RNA is ultimately transcribed into proteins, but scientists are increasingly interested in the RNA that doesn’t code for proteins and was previously disregarded as “junk.” Of these non-coding RNAs, the short non-coding RNAs called microRNAs (miRNAs) play important roles in both development as well as disease. Consequently, researchers are excited about their potential not only as the targets of new therapeutics but their ability to serve as the therapeutics themselves.
This is where our first speaker comes in. Frank Slack, PhD, has been instrumental in discovering and studying the function of microRNAs as well as developing therapeutics that exploit them. He is currently Director of the Institute for RNA Medicine, Beth Israel Deaconess Medical Center and the Shields Warren Mallinckrodt Professor, Department of Pathology, Harvard Medical School. While Dr. Slack’s research spans miRNAs in multiple diseases and biological functions, today he will be focusing on miRNA-based therapeutics in cancer.
Non-coding RNAs (ncRNAs) have sparked excitement both among traditional science publications as well as those targeted to lay audiences. These ncRNAs might contribute to biological complexity not previously explained by those RNAs that ultimately yield proteins. Although they don’t code proteins, the ncRNAs serve roles in gene regulation and could play critical roles in diagnostics and therapeutics.