New RNA Nanoparticle Helps Deliver RNA to Fight Cancer
Attaching RNA nanoparticles to containers that shuttle back forth between cells may help deliver therapeutics to destroy cancer cells. RNAs are key molecules in many cellular processes, ranging from gene regulation to protein synthesis to signaling between cells. Recent research has also used RNA as structural decoys to look like other normal parts of cells, such as binding motifs or gene regulators. These “RNA nanoparticles” are part of promising efforts to fight cancer development and progression. However, several major hurdles remain before this becomes a clinical reality; one challenge is targeting the right cells and another is escaping natural defense mechanisms. The following study from the Extracellular RNA Communication Program, brings us one step closer to overcoming these challenges and unlocking the transformative potential of this new area of research for human health, disease diagnosis, and treatment.
Using new nanotechnologies, researchers decorated the outside of extracellular vesicles (EVs) – containers that shuttle back and forth between cells – with RNA nanoparticles made to look like a normal antibody. This provided an effective signal to find and bind certain cancer cells. The EVs were engineered to contain another RNA that was able to get inside the cancer cells, bind to specific DNA targets, and stop cells from dividing and making more cancer cells. Most importantly, this delivery system was able to ensure that the RNA avoided “endosome traps,” – part of natural defense mechanisms that can destroy the RNA before it has a chance to act. While this study used cells grown in the lab and animal models, it offers a promising roadmap for future clinical studies.
Nanoparticle orientation to control RNA loading and ligand display on extracellular vesicles for cancer regression. Binzel, P. F., et al. Nature Nanotechnology. 2017 Dec 11. doi: 10.1038/s41565-017-0012-z.
Fish Proteins for Human Blood Typing
Glycans are types of sugar molecules that carry out many critical functions in the body through interactions with proteins. Glycans are difficult to study because they have complex compositions and structures. This has created a need for research tools to make, detect, and analyze these sugars. Proteins that bind to specific glycans are used by scientists for glycan detection. One use for glycan-binding proteins is in blood-typing. People with different blood types have different glycans on the surface of their red blood cells. Currently, a glycan-binding protein that comes from a plant is used to detect one of the major glycans on Type O blood cells, called H-trisaccharide type II. Blood cells that have this glycan on their surface are identified as having Type O blood. However, while this plant protein can bind H-trisaccharide, it also binds to other, unrelated glycans.
A team of researchers, including Glycoscience Program-funded researcher Richard Cummings, explored the function and structure of several other glycan-binding proteins for the ability to specifically bind H-trisaccharide. They isolated several antibody-like proteins from the immune cells of lampreys (a type of jawless fish) that had been exposed to Type O blood cells. They then studied the H-trisaccharide-binding abilities and structure of the lampreys’ antibodies. One of the antibodies, which they called O13, has strong binding to H-trisaccharide and is less likely to bind to other glycans than the plant protein currently being used for blood typing. The researchers compared the structure of O13 to other H-trisaccharide-binding proteins from the lamprey that were less specific (they still bound other glycans). By doing so, they were able to identify the parts of the antibodies that had the greatest effect on specificity for H-trisaccharide. They used this knowledge to modify key parts of the O13 structure, making it bind even more specifically to H-trisaccharide. This study indicates that lampreys could serve as a valuable resource for producing glycan-specific antibodies that can be modified to enhance their use as tools in biomedical research and medical diagnosis and treatment.
Reference: Structural Insights into VLR Fine Specificity for Blood Group Carbohydrates. Collins, BC, Gunn, RJ, McKitrick, TR, Cummings, RD, Max D. Cooper, Brantley R. Herrin, Ian A. Wilson. Structure. 7 November 2017. 25(11): 1667-1678.e4.
Opioid Deaths in Hospitals Quadruple
Between 1993 and 2014, opioid-caused deaths during hospital stays quadrupled in the United States while deaths from other kinds of drug overdoses remained unchanged. Zirui Song, a 2017 Early Independence awardee, started the study to better understand the patients he was treating. What he found was striking—the number of patients dying from opioid-related causes in hospitals rose from 0.43 percent in the year 2000 to 2.02 percent by 2014. And while the number of black and Hispanic patients admitted to hospitals for opioid poisoning remained stable, the rate among white patients doubled and were the largest and fastest-growing proportion of hospitalizations. Patients of opioid poisoning were most likely to be between 50-64 years old, of low income, and Medicare recipients with disabilities. Song’s study doesn’t explain why more people are dying from opioids at the hospital, but he hypothesizes that the increased use of the deadlier, less expensive fentanyl and heroin over oxycodone may be driving it, as well as increased efforts to treat people in the field or at clinics and urgent care facilities, which could leave hospitals with higher-risk patients with more severe cases. With more than 35,000 deaths caused by opioid overdoses last year, Song wants his study to raise awareness of the plight of hospitals, which need help responding to the increasing severity of opioid cases coming through their doors from primarily vulnerable populations.
Reference: Mortality Quadrupled Among Opioid-Driven Hospitalizations, Notably Within Lower-Income and Disabled White Populations. Song Z. Health Affairs. 2017 Dec;36(12):2054-2061.
In the News:
- Deaths During Opioid-Driven Hospital Stays Have Quadrupled
- Death Rate Among People Hospitalized for Opioids Quadrupled Since 2000 — With Medicare Patients Big Driver
- Deaths After Opioid-Driven Hospitalizations Have Quadrupled, New Study Says
- Four-Fold Jump in Deaths in Opioid-Driven Hospitalizations
The Connectivity Map: An Online Public Resource for Gene Activity Profiles
One common method for profiling the state of a cell is to measure levels of gene expression, the process by which the information within our genes is used to make a gene product. Cells control expression of genes as a way to adapt to their environment.
Researchers at the LINCS Transcriptomics Center have released an updated version of the Connectivity Map (CMap) which now contains over 1.3 million gene expression profiles from treating numerous types of human cells with over 42,000 agents that disrupt cellular function (perturbagens). This extremely large set of data is based on the L1000 assay which allows for inexpensive and large-scale analysis of gene expression.
CMap is a freely available public resource that any research scientist can use and already has more than 18,000 registered users. For example, researchers can gain insight regarding how a small-molecule drug works in a cell by determining the changes in gene expression it produces. Alternatively, they can find a molecule from all those that have been screened that has a desired effect in cells to aid in the design of new therapeutics.
One example of the utility of the L1000 assay is a collaboration within the LINCS Consortium in which gene expression data were combined with a method for cell growth and survival measurements developed at the Harvard Medical School LINCS Center. These measures were used to profile the effects of 109 small-molecule drugs on six different breast cancer cell lines. This study showed there is substantial variability in how certain drugs affect the cell growth and survival certain types of breast cancer cells. These differences can be explored to help us understand why some patients respond better to breast cancer treatments than others. LINCS researchers also demonstrated that gene expression results could be used to predict combinations of drugs that are effective in preventing growth of the breast cancer cells, which could potentially be used to design combination therapies.
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Subramanian A, Narayan R, Corsello SM, Peck DD, Natoli TE, Lu X, Gould J, Davis JF, Tubelli AA, Asiedu JK, Lahr DL, Hirschman JE, Liu Z, Donahue M, Julian B, Khan M, Wadden D, Smith IC, Lam D, Liberzon A, Toder C, Bagul M, Orzechowski M, Enache OM, Piccioni F, Johnson SA, Lyons NJ, Berger AH, Shamji AF, Brooks AN, Vrcic A, Flynn C, Rosains J, Takeda DY, Hu R, Davison D, Lamb J, Ardlie K, Hogstrom L, Greenside P, Gray NS, Clemons PA, Silver S, Wu X, Zhao WN, Read-Button W, Wu X, Haggarty SJ, Ronco LV, Boehm JS, Schreiber SL, Doench JG, Bittker JA, Root DE, Wong B, Golub TR. Cell. 2017 Nov 30; 171(6): 1437-1452.
Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling. Niepel M, Hafner M, Duan Q, Wang Z, Paull EO, Chung M, Lu X, Stuart JM, Golub TR, Subramanian A, Ma'ayan A, Sorger PK. Nat Commun. 2017 Oct 30; 8(1): 1186.
GTEx Creates a Reference Data Set to Study Genetic Changes and Gene Expression
Research studies have identified links between many genetic variants (a change in DNA sequence) and common diseases (e.g. cancer, diabetes, hypertension, Alzheimer's disease). We are now aware that genetic variants can regulate genes being turned on or off, which may contribute to complex diseases. However, which genes are turned on or off varies a lot in healthy people depending on which tissue type (e.g. heart, lung, brain, etc.) is being examined, and this makes it even harder to link a specific genetic variant to disease. The NIH Common Fund’s Genotype-Tissue Expression (GTEx) project has developed a reference data set for studying genetic variants and gene activity in multiple healthy tissues. This catalogue has stimulated research that will enrich our understanding of how differences in our DNA sequence contribute to health and disease, and make us different from everyone else.
GTEx researchers, Eric Gamazon, Nancy Cox, and Hae Kyung Im used the GTEx reference data set to design a statistical method called PrediXcan that estimates how much of gene activity (whether a gene is turned on or off) is due to differences in DNA sequence.1 PrediXcan then links this estimate with observable traits as a way to identify genes associated with disease. The authors used this method to identify specific genes associated with five diseases: bipolar disorder, coronary artery disease, Crohn's disease, rheumatoid arthritis and type 1 diabetes. In another study, researchers used GTEx data to mathematically measure gene activity changes associated with a given genetic variant. This is a significant approach for investigating how genetic variants affect cellular processes.2 All GTEx data are publicly available at the GTEx Portal, which gives researchers everywhere access to the reference data set. Access to the data set will create new opportunities to study links between genetics and disease and to investigate possible advanced treatment options.
 A Gene-Based Association Method for Mapping Traits using Reference Transcriptome Data. Gamazon ER, Wheeler HE, Shah KP, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC; GTEx Consortium, Nicolae DL, Cox NJ, Im HK. Nat Genet. 2015 Sep;47(9):1091-8.
 Quantifying the Regulatory Effect Size of Cis-Acting Genetic Variation using Allelic Fold Change. Mohammadi P, Castel SE, Brown AA, Lappalainen T. Genome Res. 2017 Nov;27(11):1872-1884.
Loop Loss in the Human Genome
DNA is organized in the small nucleus of a cell in the form of a DNA-protein complex called chromatin. The protein “cohesin" helps maintain DNA organization by tethering two regions of DNA on the same chromosome to form loops. The loops have long been thought to regulate which genes are turned on by controlling the distance between DNA promoters and enhancers. Promoters are regions of DNA that generally occur before a gene and serve as a landing space for the molecular machinery needed to activate the gene. Enhancers are regions of DNA that can increase gene activity when in close contact with the target gene’s promoter.
In one study, a group of researchers led by 4D Nucleome program-funded investigator Erez Lieberman Aiden used a technique called chromosome conformation capture (Hi-C) to map the formation of DNA loops throughout the genome at 20-minute intervals during the loss and recovery of cohesin. They found that cohesin removal led to the loss of loops. However, this surprisingly had modest effects on gene activity, with only a few genes experiencing significant changes in activity. They also observed formation of a separate group of cohesin-independent loops and links between different chromosomes. The results suggest that cohesin-dependent loops play only a modest role in regulating interactions between promoters and enhancers. Based on these results, the team proposes a revised model in which a combination of cohesin-dependent and -independent loops regulate gene activity.
In another study led by 4DN-funded researcher Leonid Mirny and Transformative Collaborative Project Awardee Francois Spitz, the protein responsible for loading cohesin onto chromatin, Nipbl, was deleted in a mouse model. The resulting changes in chromatin organization were then identified using a Hi-C technique. Nipbl deletion led to significant changes in chromatin organization, including loss of cohesin-dependent loops and enhancement of compartments made up of chromatin regions with similar activity. The loss of cohesin-dependent loops allowed formation of smaller chromatin compartments with fewer contacts between active and inactive chromatin regions. The results contradict a model of chromatin organization in which DNA loops combine to form larger compartments. Instead, the authors propose a revised model in which genomic compartment formation is interrupted by cohesin-dependent loops that can bring regions of different chromatin activities together to drive gene activity. Although these studies, used different approaches, they led to similar conclusions. Understanding how the 3-dimensional structure of chromatin is controlled over time and affects gene activity can lead to better treatment of human diseases linked to abnormal chromatin organization.
Cohesin Loss Eliminates All Loop Domains. Rao, SSP, Huang, S, St Hilaire, BG, Engreitz, JM, Perez, EM, Kieffer-Kwon, K, Sanborn, AL, Johnstone, SE, Bascom, GD, Bochkov, ID, Huang, X, Shamim, MS, Shin, J, Turner, D, Ye, Z, Omer, AD, Robinson, JT, Schlick, T, Bernstein, BE, Casellas, R, Lander, ES, and Lieberman Aiden, E. Cell (171), 305-320. 2017 October 5.
Two independent modes of chromatin organization revealed by cohesin removal. Schwarzer, W, Abdennum, n, Goloborodko, A, Pekowska, A, Fudenberg, G, Moe-Mie, Y, Fonesca, NA, Huber, W, Haering, CH, Mirny, L, and Spitz, F. Nature (551), 51-56. 2017 November 2.
In the News: Watch the human genome fold itself in four dimensions, Science News
Dynamic DNA Loops Affect How Cells Become Specialized
Genomic DNA is packaged and organized in the tiny nucleus of the cell as chromatin (a complex of DNA and histone proteins). The 3-dimensional organization of chromatin in the nucleus affects which genes are expressed and at what times. A complex network of chromatin loops is involved in coordinating changes in transcription during cell development. Chromatin loops can bring enhancers (sections of DNA that promote transcription when bound by proteins called transcription factors) closer to their target genes in the genome. How chromatin architecture changes as cells differentiate into specialized cell types and how these changes affect cell-type-specific gene expression and cellular function are not well understood.
A team of researchers, including 4DN program-funded researcher Erez Lieberman Aiden, used a technique called in situ chromosome conformation capture (Hi-C) to create high-resolution genome-wide looping maps to compare the chromatin structure of cells before and after differentiation to become specialized immune cells (macrophages). Hi-C is a method of detecting frequencies of contact between all mappable regions of the human genome. Following differentiation, they found genes at loops that were newly formed (“gained loops”) or newly activated by changes in chromatin architecture (“activated loops”) have increased expression. The gained and activated loops form multi-loop activation “hubs” that create long-range interactions between active enhancers and promoters and have increased binding of transcriptional regulators, thus facilitating transcription. The multi-loop hubs occur at genes known to play a role in macrophage development and function, indicating a role in regulating gene transcription during cell differentiation. This study could have broader implications for how chromosome organization instructs transcription in other cellular contexts and throughout human development.
Reference: Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development. Phanstiel, DH, Van Bortle, K, Spacek, D, Hess, GT, Shamim, MS, Machol, I, Love, MI, Lieberman Aiden, E, Bassik, MC, Snyder, MP. Molecular Cell. 2017 September 21. 67(6): 1037-1048.
Survey Shows Highly Transferable Skills and High Job Satisfaction for Science PhDs in Diverse Careers
Recently, BEST researchers supported by the Strengthening the Biomedical Workforce program, analyzed a survey of science and engineering PhD graduates. Their goal was to determine if skills needed for chosen careers of PhD graduates matched well with skills they developed in PhD training. The original academic training model was designed as an apprenticeship; students earning a PhD in science or engineering acquired highly specialized skills and knowledge, which was commonly understood to prepare for them for independent academic positions. The assumptions regarding the natural progression of PhD scientists into faculty careers are now rapidly changing to reflect today’s job market and variety of career choices. Many PhD graduates choose non-research-intensive careers; therefore, it is important to understand if current training systems are adequately preparing them for this option. Encouragingly, the researchers found that PhD training develops many transferrable skills crucial to success in a wide range of careers, including both research-intensive and non-research-intensive careers. This suggests that current training systems prepare PhD graduates for broad careers. However, some key differences did emerge. For example, respondents who rated themselves as proficient in creativity/innovation, career planning/awareness, and ability to work with others outside the organization, were more likely to be employed in research-intensive careers. On the other hand, respondents who had high ratings for project management, learning quickly, and time management skills were more likely employed in non-research-intensive careers. Importantly, job satisfaction in both research-intensive and non-research-intensive careers was relatively high, meaning that most respondents were satisfied or very satisfied with their chosen career path. This is good news for many graduate programs, as it indicates that PhD graduates are equipped with many transferable skills for a variety of career paths and they are happy in these positions. However, there are areas for improvement. For example, career planning and awareness ranked the lowest of all skills, suggesting an area for targeted growth in graduate education.
An evidence-based evaluation of transferrable skills and job satisfaction for science PhDs. Sinche M, Layton RL, Brandt PD, O'Connell AB, Hall JD, Freeman AM, Harrell JR, Cook JG, Brennwald PJ. PLoS One. 2017 Sep 20; Vol. (9).
New Genes to Explore in Fight Against Hearing Loss
More than 360 million people have some form of hearing impairment. We know that half of these cases are due to genetics, but the vast majority of genes responsible for many hearing loss syndromes are unknown. Now, research from the Knockout Mouse Phenotyping Program (KOMP2), part of the International Mouse Phenotyping Consortium (IMPC), shows that many more genes are involved in deafness than previously known. Because mice and humans share most genes, findings from mouse genes may tell us a lot about human hearing loss. Researchers tested over 3006 genetically modified mutant mice for hearing problems, exploring nearly 15% of the mouse genome. Hearing thresholds of the mice were measured with rising volumes of sound at different frequencies. While the study detected many genes already known to be involved in hearing loss, 52 of the genes were newly associated with hearing loss. These genes coded for many different types of proteins, from structural proteins to transcription factors, reflecting the complexity of the auditory system. Also, 41 of the 52 these genes were not even part of previously known networks of genes affecting hearing – highlighting potentially unexplored pathways of hearing loss. This information provides a large and unexplored genetic landscape that may help researchers understand more about hearing loss and develop better treatments.
A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction. Bowl MR, Simon MM, Ingham NJ, Greenaway S, Santos L, Cater H, Taylor S, Mason J, Kurbatova N, Pearson S, Bower LR, Clary DA, Meziane H, Reilly P, Minowa O, Kelsey L, Tocchini-Valentini GP, Gao X, Bradley A, Skarnes WC, Moore M, Beaudet AL, Justice MJ, Seavitt J, Dickinson ME, Wurst W, de Angelis MH, Herault Y, Wakana S, Nutter LMJ, Flenniken AM, McKerlie C, Murray SA, Svenson KL, Braun RE, West DB, Lloyd KCK, Adams DJ, White J, Karp N, Flicek P, Smedley D, Meehan TF, Parkinson HE, Teboul LM, Wells S, Steel KP, Mallon AM, Brown SDM. Nature Communications. 2017 Oct 12;8 (886).
Read Press Release Here
Visualizing the Nucleus in 3D
How DNA is packaged in the nucleus determines how it is used and how genes are expressed. DNA is condensed and packaged as chromatin (a complex of DNA and proteins called histones), which constantly changes as genes are expressed. Understanding chromatin packaging may reveal the structural code for how genes are turned on or off in human health and disease. For example, understanding chromatin packaging could be used to make cancer cells with abnormally structured chromatin “remember” how to be healthier through repackaging chromatin. Toward understanding chromatin packaging in the nucleus, 4D Nucleome (4DN) program grantee Dr. Clodagh O’Shea collaborated with fellow 4DN grantee Dr. Mark Ellisman to develop a new approach to visualize chromatin in 3D space. This method, called ChromET, combines electron microscopy tomography (EMT) and a labeling method that enhances the visualization of DNA in human cell lines. An electron microscope uses a beam of electrons to create an image of a sample and is capable of seeing much smaller objects than a traditional light microscope. The 4DN researchers used ChromET to show that chromatin is flexibly disordered and packed together at different concentrations in the nucleus. This is different from the textbook model of rigid higher-order chromatin folding. This new model of diverse chromatin structures – able to bend at various lengths and achieve different packing concentrations – is important because it provides an explanation for how different parts of the genome could be fine-tuned to make different structures, at different times, with different functions. This research brings us one step closer to discovering how the structural code of our genomes could be used to advance medical care.
Reference: ChromEMT: Visualizing 3D chromatin structure and compaction of the human genome in interphase and mitotic cells. Ou, HD, Phan S, Deerinck TJ, Thor A, Ellisman, MH, O’Shea CC. Science. 2017 July 28.
Mouse Study Reveals Important Differences Between Males and Females
Historically, most researchers didn’t often study both sexes in their experiments, they assumed that results from male animals would be the same as female animals. However, we now know that sex influences the frequency, progression, and severity of the majority of common diseases and disorders, including cardiovascular and autoimmune diseases. Because of this, the NIH has mandated exploring sex as a biological variable, meaning researchers must consider sex as a biological variable in the design and analysis of their animal studies.
As part of the International Mouse Phenotyping Consortium (IMPC), Knockout Mouse Phenotyping Program (KOMP2) researchers supported by the Common Fund have explored how physical characteristics, vary by sex in normal and genetically modified mice. In the largest study of its kind, they analyzed 234 different physical characteristics in more than 50,000 mice. They found that the sex of the mice influenced many traits. For example, after accounting for weight, a known sexually dimorphic variable, 9.9% of categorical traits (things that can be put into categories, such as glucose tolerance) exhibited sexual dimorphism in normal mice. For continuous traits (things that can be measured on a scale, such as cholesterol levels), a far higher proportion exhibited sexual dimorphism at 56.6%. While some traits were expected to show differences in males and females, such as glucose levels and cardiac phenotypes, others were surprising and could not have been predicted. For example, vision abnormalities from the cornea were surprisingly found more often in female mice than males.
Not only did they study normal mice, but they also measured sexual dimorphism in many different genetically modified mice. To do this, they ”knocked out” different genes and measured whether any differences in the resulting physical traits depended on the sex. Unsurprisingly, some mutations only had effects in female mice, or vice versa. For example, only males and not females with the Usp47 gene knocked out, had high cholesterol levels, which would be important to consider in studies of heart disease or other diseases in which cholesterol is involved. The results have implications for the design of future animal studies which underpin research into treatments for human diseases. This study is a major step in highlighting the impact of sex differences in biomedicine and will help in accounting for those differences in the future biomedical studies.
Prevalence of sexual dimorphism in mammalian phenotypic traits. Karp NA, Mason J, Beaudet AL, Benjamini Y, Bower L, Braun R E, Brown S DM, Chesler EJ, Dickinson ME, Flenniken AM, Fuchs H, de Angelis MH, Gao X, Guo S, Greenaway S, Heller R, Herault Y, Justice MJ, Kurbatova N, Lelliott CJ, Lloyd KC, Mallon A, Mank JE, Masuya H, McKerlie, TF Meehan, RF Mott, SA Murray, H Parkinson, R Ramirez-Solis, Santos, JR Seavitt, D Smedley C, Sorg T, Speak A O, Steel KP, Svenson L, The International Mouse Phenotyping Consortium, Wakana S, West D, Wells S, Westerberg H, Yaacoby S, White JK . Nature Communications. 2017 June 26;8 (15475).
Read Press Release Here
New Study Offers Promise for the Safety of RNA Therapeutics
Researchers supported by the Common Fund’s Extracellular RNA Communication (ERC) program at The Ohio State University are studying the safety of delivering RNA in extracellular vesicles (EVs) as a possible disease treatment. RNA is a biological molecule that make protein. Proteins perform a variety of essential functions, from providing structure to our bodies to protecting us from bacteria. RNA is found primarily inside cells and only recently has been found outside of cells and considered as a potential treatment option. For example, some recent evidence has suggested that RNAs can be developed as therapeutics for cancer or multiple sclerosis. The natural ability of EVs to transfer biologic materials like RNA throughout the human body is an exciting system to harness. Many current efforts, including those of the ERC program, are exploring whether EVs containing RNA could be effective therapeutics or if EVs can be vehicles for drug delivery to treat diseases like cancers or brain disorders. However, scientists are working to understand the potential harmful side effects or unintended immune complications of EVs and their RNA cargo. While proving a treatment has a desired effect is critical in early preclinical studies, it can be even more critical to know if a potential treatment could have toxic side effects or may elicit a dangerous immune response.
In this study, the researchers used normal cells, which naturally produce EVs, as well as cells engineered to make EVs carrying a specific type of RNA inside them. They treated mice with EVs collected from both cell types for a three-week period and carefully monitored if normal EVs or engineered EVs caused any toxic or immune responses. They used many ways to assess this, including visual examination of mice, measuring blood chemistry profiles, dissecting organs, and measuring immune markers. Overall, using these assays they found no potential for harm coming from the EVs of normal and engineered cells, though small changes in immune responses may require further study. Next steps will determine if higher doses of EVs or a longer dosing period would be as safe, if EVs from different cell types act differently, and if EVs from human cells are immunogenic or toxic in other animal models. This study shows early promising signs for the safe use of EVs containing RNAs, and presents a standard framework for comprehensive study of immune effects and toxicity for future studies.
Comprehensive toxicity and immunogenicity studies reveal minimal effects in mice following sustained dosing of extracellular vesicles derived from HEK293T cells. X. Zhu, M. Badawi, S. Pomeroy, D.S. Sutaria, Z. Xie, A. Baek, J. Jiang, O. A. Elgamal, X. Mo, K. La Perle, J. Chalmers, T. D. Schmittgen, and M.A. Phelps. Journal of Extracellular Vesicles. Vol. 6, Iss. 1,2017.
Read more at exRNA.org
Promising New Treatment for Multiple Sclerosis
A new drug based on a compound originally discovered in a Common Fund program has passed a late phase clinical trial demonstrating its effectiveness in treating Relapsing Multiple Sclerosis (RMS). RMS is the most common form of MS and is characterized by acute attacks of impaired neurological function followed by periods of recovery. This new drug, ozanimod, is derived from one of the compounds discovered by Dr. Hugh Rosen and colleagues at the NIH Molecular Libraries Probe Production Center at The Scripps Research Institute. The research was part of the Common Fund’s Molecular Libraries and Imaging Program which discovered multiple compounds that have been developed into candidate drugs that are now in clinical trials for a variety of diseases.
In this recent phase III clinical trial involving 1,346 RMS patients, ozanimod was shown to reduce the number of relapses over a twelve month treatment period compared to a standard treatment with an interferon based therapy. The findings of this study suggest that ozanimod may prove to be an effective therapy for patients dealing with RMS. Celgene, the company currently developing ozanimod, expects to seek FDA approval for this potential new treatment towards the end of 2017.
BEST Researchers Study Career Outcomes of Postdocs
Postdoctoral scholars (or “postdocs”) are often thought of as the engine that drives scientific research. They are highly educated and trained researchers, pursuing additional training and mentoring after their PhD training. They conduct much of the day-to-day work of biomedical research. And presumably they are aiming to move on to be independent faculty researchers, though reports suggest that only a minority actually end up in those positions. If this is true, where do postdocs really find employment? Researchers in the NIH BEST Consortium are beginning to find out by tracking career outcomes of postdocs from the University of California, San Francisco (UCSF).
From their tracking and analysis, the researchers found differences in employment outcome based on whether a postdoc had a PhD versus an MD/PhD, or whether they were employed in the United States or another country. For example, around one-quarter of postdocs went on to work in other nations, but only about half of these individuals gained faculty positions in research or teaching. UCSF postdocs with both an MD and a PhD were also more likely to work in faculty positions than in non-faculty positions, either in or outside the United States. Variations in outcomes were also found to be dependent on the lab in which postdocs trained. Knowing any of this type of information ahead of time could help prospective postdocs when they consider which labs might be best for their additional training time and their future career goals.
The UCSF researchers also found general confusion with understanding of “tenure-track” positions, which are jobs on track to be a permanent academic position and not temporary or conditional. Postdocs searching for jobs are often unaware that the term “tenure-track” is over-applied. The classification of “tenure-track” versus “non-tenure-track” in job descriptions is often incorrect and fails to acknowledge many nuances. This ends up misleading postdocs as they weigh their options for employment. Many who think they are in, or are applying to, a classical “tenure-track” position really are not. Interestingly, only 21% of the postdocs who attain faculty positions at UCSF were in a bona fide tenure track position. Overall more data are needed to inform postdocs and graduate students considering a postdoc position about the realities of career opportunities, according to the UCSF researchers. These data could enhance career development experiences that would better suit the actual careers the postdocs are ending up in and that are available. More data are also needed for better transparency, giving postdocs timely and relevant information to enable them the agency to prepare for their futures.
Tracking Career Outcomes for Postdoctoral Scholars: A Call to Action. Silva EA, Des Jarlais C, Lindstaedt B, Rotman E, Watkins ES. PLOS BIOLOGY. 2016 May 14(5)e1002458. doi: 10.1371/journal.pbio.1002458
Combining Anti-RNA Treatments with Chemotherapy May Offer Benefits for Lung Cancer Patients
Chemotherapy is a standard treatment for many cancers. However, resistance to chemotherapy can develop over time, which causes cancer cells to lose the ability to respond effectively to treatment. It is unknown how this resistance develops. Researchers from the Common Fund’s Extracellular RNA Communication program have begun to examine the role extracellular RNAs may play in this resistance by studying a particular RNA called miR-155. MiR-155 is found at increased levels in many cancers. In forms of cancer that are particularly aggressive and resistant to treatment, miR-155 is found at even higher levels. The potential role of miR-155 in cancer and resistance to chemotherapy is not well-understood. Does miR-155 influence resistance to chemotherapy? Can available drugs targeted against miR-155 (“anti-miR-155”) be used to stop or reverse chemotherapy resistance? To address these questions, researchers explored how miR-155 works in lung cancer and evaluated if a treatment to inhibit miR-155 could help stop resistance to chemotherapy.
Interestingly, they showed that increased levels of miR-155 induce resistance to many different types of chemotherapeutic agents. They also demonstrated that miR-155 partners with TP53, a well-known tumor suppressor, to promote resistance. Furthermore, when they added a drug that blocks miR-155, they found resistance lessened. This means that even though resistance developed, it can be reversed and the chemotherapeutic drugs can become effective at killing cancerous cells again. Excitingly, this anti-miR-155 treatment had no toxic side effects in mice, suggesting the treatment has potential to be used in clinical trials in combination with standard chemotherapy regimens.
Combining anti-miR-155 with chemotherapy for the treatment of lung cancers. Van Roosbroeck, K., F. Fanini, T. Setoyama, C. Ivan, C. Rodriguez-Aguayo, E. Fuentes-Mattei, L. Xiao, I. Vannini, R. Redis, L. D'Abundo, X. Zhang, M. S. Nicoloso, S. Rossi, V. Gonzalez-Villasana, R. Rupaimoole, M. Ferracin, F. Morabito, A. Neri, P. Ruvolo, V. R. Ruvolo, C. V. Pecot, D. Amadori, L. Aruzzo, S. Calin, X. Wang, M. J. You, A. Ferrajoli, R. Z. Orlowski, W. Plunkett, T. Lichtenberg, R. V. Davuluri, I. Berindan-Neagoe, M. Negrini, Wistuba, II, K. Hagop, A. K. Sood, G. Lopez-Berestein, M. J. Keating, M. Fabbri and G. A. Calin. Clinical Cancer Research. 2016 November 20. doi: 10.1158/1078-0432.CCR-16-1025.
For more information see the exRNA Consortium blog!
A Guiding Light to Study Protein Assembly in Living Cells
4D Nucleome grantee Dr. Clifford Brangwynne and collaborators have developed a new tool that uses light to manipulate matter inside living cells. Called optoDroplet, this tool helps explain the physics and chemistry behind how cells assemble a mysterious structure called a membraneless organelle. An organelle is a specialized part of a cell having some specific function. For example, the nucleus is an organelle that holds most of the cell’s genetic information. Organelles like the nucleus are walled off from the rest of the cell by a membrane. The cell also uses membraneless organelles that resemble liquid droplets and exhibit dynamic behavior, such as rapid assembly and disassembly of protein building blocks that make up the organelle. When these mechanisms go awry, aggregates of the protein building blocks can form. Protein aggregation is associated with a number of diseases, including amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease) and Alzheimer's disease. Understanding the process by which proteins condense into these droplet-like, membraneless organelles may be used to develop of interventions and treatments for diseases connected with protein aggregation. To better understand this process, Dr. Brangwynne’s group developed optoDroplet. This new tool relies on optogenetics, which involves proteins whose behavior can be altered by exposure to light. Using mouse and human cells, researchers showed that they could create membraneless organelles by switching on the light-activated proteins. They were also able to use this tool to generate protein aggregates, similar to those found in some diseases. The optoDroplet system will help researchers understand the basic mechanisms that underlie self-assembly of membraneless organelles in healthy living cells and may reveal how cells become diseased when this process goes awry.
Reference: Spatiotemporal Control of Intracellular Phase Transitions Using Light-Activated optoDroplets. Shin Y, Berry J, Pannucci N, Haataja MP, Toettcher JE, Brangwynne CP. Cell. 2017 Jan 12;168(1-2):159-171.e14. doi: 10.1016/j.cell.2016.11.054. Epub 2016 Dec 29.
Looking at Type 2 Diabetes from Different Viewpoints
Type 2 diabetes (T2D) is a complex disease that affects more than 29 million Americans, a number that is expected to increase in the coming decades. T2D risk factors include, but are not limited to, genetic mutations, obesity, physical inactivity, and increased age. These numerous risk factors highlight how both genetics and environmental influences can contribute to T2D. In order to develop better methods for early detection and disease treatment, scientists need a better understanding, at both the research and clinical levels, of how this disease occurs and progresses.
To gain a better appreciation of T2D, the research community must study it from different viewpoints. This concept is exemplified by the NIH Common Fund, which strives to support research relevant to multiple diseases and conditions, developing tools and resources from different biological perspectives that others can apply to specific questions. Several different scientific fields have used support from the Common Fund to deepen our understanding of T2D.
Inherited risks, such as genetic mutations, as well as environmental risks, such as obesity, physical inactivity, and age, have all been linked to T2D. Due to the complexity of factors contributing to T2D, a single type of drug or treatment procedure is likely to be ineffective, and a more personalized approach to treat specific underlying causes is needed. A recent study, supported by the Common Fund’s Illuminating the Druggable Genome program, used advanced genetic and computer analysis methods to determine three distinct subgroups of 11,210 patients with T2D based on their clinical and genetic histories. Patients were pooled based on other medical conditions, such as heart disease, cancer, and kidney disease. The study found distinct patterns of clinical characteristics as well as unique genetic markers for each subgroup. These types of results will allow doctors to create better, more detailed treatment plans for T2D patients by targeting specific risks that may be connected to the disease and may help doctors develop an early warning system for T2D in patients with other medical conditions. In addition, these results highlight the value of precision medicine and show an approach that can be applied to other complex, multifactorial diseases to develop better treatment plans and improved patient outcomes. More information on the study can be found here.
In T2D, the body does not use insulin correctly, which increases the amount of glucose (sugar) present in the bloodstream. Insulin is a hormone made by the pancreas which moves around the body and allows your cells to use glucose properly. Currently, researchers look for changes in blood glucose levels in order to monitor how certain cells of the pancreas work. This method can be insensitive and is a poor marker for how pancreatic cells are working. It can also be invasive, resulting in poor quality data and loss of patient involvement. Recent work supported by the Common Fund’s New Innovator Award Program has developed a noninvasive, high resolution system to monitor how individual cells work in real time in biological tissue. Previous methods which used cells in a culture dish, which is a poor representation of biological tissue. What makes this technology even more powerful is that the method allows researchers to study cell growth and other biological functions in addition to glucose production. Knowledge of pancreatic cell roles will allow researchers to develop better T2D treatments by monitoring improvements in pancreatic cell function in a much more detailed, real-time, and less invasive way. The full study can be found here.
A new clinical study involving the Common Fund’s Human Microbiome Project aims to examine the microbiome of 100 at-risk individuals for T2D. Microscopic study of the healthy human body has demonstrated that microbial cells outnumber human cells by about ten to one. Until recently though, this abundant community of human-associated microbes remained largely understudied, leaving their influence upon human development, physiology, immunity, and nutrition almost entirely unknown. Researchers have found that there are differences in the gut microbiome between diabetics and healthy individuals, and have also shown that the microbiome can influence glucose levels in mice. The study is expected to reveal global changes in the microbiome of T2D at-risk individuals in great detail over time. This will allow researchers to not only better understand how the microbial cells in our bodies influence our health, but also identify new molecular targets to help diagnose, treat, or potentially prevent T2D in humans. More information on the clinical study can be found here.
It is clear that there are many factors that can contribute to developing T2D. By helping support research to develop different biological tools that answer difficult biological questions, Common Fund programs are helping researchers better understand complex diseases like T2D, and ultimately, helping many patients.
This page last reviewed on January 12, 2018