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The microRNA miR-155 plays a significant role in physiological and pathological processes in humans by blocking the functions of functionally important messenger RNAs of protein coding genes. We found that miR-155 was present in higher levels in cancers resistant to chemotherapy. By studying the association of miR-155 and tumor suppressor TP53 with cancer survival in 956 patients with lung cancer, chronic lymphocytic leukemia and acute lymphoblastic leukemia, we demonstrated that miR-155 induces resistance to multiple chemotherapeutic agents in vitro, and that blocking or down-regulating miR-155 successfully resensitizes tumors to chemotherapy in vivo. We found that high levels of miR-155 and low levels of TP53 characterize the tumors from lung cancer patients with shorter survival time. Our findings support the existence of a miR-155/TP53 feedback loop involved in resistance to chemotherapy. To target this feedback loop and effectively alter resistance to therapy, we have developed a therapeutic nanoformulation of anti-miR-155 in a lipid nanoparticle (DOPC) and have shown it to be non-toxic in vivo for further pre-clinical work.

We thank our co-authors for their work and discussions that led to this blog.

miR-155 TP53 and resistance to chemotherapy

Cancer cells actively reprogram gene expression to promote their ability to produce tumors. One way this reprogramming is carried out is by subverting the main routes of cell-to-cell communication by loading exosomes (vesicles that bud off from cells) with specific miRNAs that either promote or suppress tumors and then releasing them into the tumor microenvironment. In a Cancer Research paper published online recently (Kanlikilicer et al., 2016), we found that miR-6126, a miRNA that was reported to be correlated with better overall survival in high-grade serous ovarian cancer patients, is ubiquitously removed from ovarian cancer cells via exosomes.

miR-6126 is ubiquitously removed from ovarian cancer cells via exosomes

We found that miR-6126 suppresses tumors by directly targeting integrin ß1, a key regulator of cancer cell metastasis. Treatment of orthotopic mouse models of ovarian cancer with miR-6126 reduced tumor growth, proliferating cells, and microvessel density. Our findings provide new insights into the role of exosomes in mediating tumor progression and suggest a new therapeutic approach to disrupt the origin and growth of tumors.

Citation:
Ubiquitous release of exosomal tumor suppressor miR-6126 from ovarian cancer cells
Pinar Kanlikilicer, Mohammed Saber, Recep Bayraktar, Rahul Mitra, Cristina Ivan, Burcu Aslan, Xinna Zhang, Justyna Filant, Andreia M Silva, Cristian Rodriguez-Aguayo, Emine Bayraktar, Martin Pichler, Bulent Ozpolat, George A Calin, Anil K. Sood and Gabriel Lopez-Berestein*
Cancer Res. October 14, 2016 doi: 10.1158/0008-5472.CAN-16-0714
*Corresponding author

The concept of a hype cycle is a well-established business concept, in which novel ideas are said to have an initial wave of hype followed by disillusionment. Only after that, the novel concept takes off and become truly useful entering a so-called plateau of productivity. In biomedical science, the field of microRNAs (miRNAs) certainly had a peak of interest in the end of the last decade. This led by high impact publications (1) and characterization of both novel miRNA-entities as well as their associations to a broad range of diseases. Nonetheless, no clear pharmaceutical successes emerged: miRNA targets are being pursued as therapeutic targets, but none have as of yet successfully made it through clinical trials (2). Likewise the use of miRNA-based treatment strategies targeting regular mRNA is an area of interest (3). In this editorial we focus on a third aspect of miRNAs: the use of miRNAs as prognostic biomarkers in disease, asking the question if miRNAs are now entering this plateau of productivity in which actual benefit will be seen.

We focus on the recent paper by Bye et al.: “Circulating microRNAs predict future fatal myocardial infarction in healthy individuals – The HUNT study” (https://www.ncbi.nlm.nih.gov/pubmed/27192016).

 
The hunt for fatal myocardial infarction biomarkers: predictive circulating microRNAs.
Russo F, Rizzo M, Belling K, Brunak S, Folkersen L.

Ann Transl Med. 2016 Oct;4(Suppl 1):S1.

PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27867969

Journal: http://atm.amegroups.com/article/view/11314

As part of the Extracellular RNA Communication Consortium (ERCC) seminar series, on 30 June 2016, Dr. Janusz Rak from McGill University presented his work on “Extracellular Oncogenes as Biological Effectors and Biomarkers.”

When focusing on a single cancer cell, we consider how particular mutations alter the cell’s properties, causing it to grow, replicate, evade immune detection, and do all the other things cancer cells can do. But it’s clear that cancer is more than a collection of cells operating autonomously. Perhaps the most interesting and frightening part of cancer is that tumors are complex, heterogeneous entities that operate and interact with each other and with their environment in characteristic ways. Researchers have been studying cancer cell signaling pathways for years. An example is paracrine interactions with neighboring cells that induce irregular vascular growth. What is new and exciting about Dr. Rak’s work is the focus on oncogenes as cargo in extracellular vesicles (EVs), which is a nontraditional means of communication between cancer cells and from cancer to non-cancer cells.

Dr. Rak has followed several interesting lines of research. He addresses fundamental questions; for example:

  • With which cell types do cancer-cell-derived EVs (CCEV) interact?
  • Are tumor-associated mutant proteins found on or in CCEVs?
  • Are these mutant proteins then expressed on recipient cells?

Preliminary work in these areas has led to the question: Can cancer cells transform non-cancer cells (i.e. make them cancer-like) via EV-mediated transfer of oncogenic proteins? And is this process complete and permanent? Numerous lines of inquiry, from in vitro to mouse studies, lead to the conclusion that the answer is probably no. Dr. Rak argues that such a finding is not surprising: if horizontal oncogenic transformation were occurring regularly between cell types, we would see more cancer patients with mixed tumor types. Secondly, phylogenetic approaches have been used to trace tumors back to single cell ancestors, another argument against the model of horizontal transformation. The current leading hypothesis is that CCEVs, rather than inducing oncogenic transformation, play a modulatory role, regulating interactions between cancer cells and between cancer and host cells but without changing their identity.

A better understanding of cancer EV biology has promise for improving cancer therapy and diagnosis. CCEVs and their oncogene cargo may represent interesting and novel pharmaceutical targets. They also constitute a unique reservoir of mutant molecules in blood, far away from an inaccessible tumor. Efforts are underway to advance cancer diagnosis through detection of CCEVs, particularly in tumor classes like glioblastoma multiforme (GBM) where no other methods of early detection are available. Research in humans has indicated that GBM patients can be identified by EVs in blood serum. As research such as Dr. Rak’s progresses, and EV biology is further elucidated, we will continue moving towards a future where we can utilize EVs in clinical practice to improve health outcomes.

Secreted RNAs leave the intracellular environment by associating with diverse vesicular and protein components. Secreted vesicles are heterogeneous and follow various routes of egress from the cell (1). Subclasses of such vesicles contain distinct cell surface proteins (2). In order to fully understand the diversity of vesicles that contain RNA, it is necessary to analyze and sort vesicle populations (3). One way to do this is by flow sorting such vesicles based on the presence of distinct vesicular surface proteins.

The ability to perform flow cytometric analysis and sorting of exosomes has been an ongoing area of controversy due to the small size of exosomes, which range in size from 40-130nm, near or below the diffraction limit of light. Nevertheless, a variety of groups have used this technique to analyze different subsets of small vesicles successfully (4-14), including proteomic analyses (4, 15-17). The efficacy of these flow-sorting experiments has been cross-validated by a variety of means, including western blots and co-localization of coincidently expressed factors. Fluorescence-Activated Vesicle Sorting (FAVS) uses light scattering properties of vesicles to analyze and sort individual exosomes using fluorescent labels. (See a previous blog on FAVS here.)

In the paper, “Identification and Characterization of EGF Receptor in Individual Exosomes by Fluorescence-Activated Vesicle Sorting (FAVS)”, published in the Journal of Extracellular Vesicles (JEV), Higginbotham and colleagues have used FAVS to analyze exosomal subsets that express varying amounts of EGFR in different cell-culture and in vivo contexts. This was done using DiFi cells, a human colorectal cancer (CRC) cell line, and A431, an epidermoid cancer cell line, which express approximately 5×106 and 2.5×106 EGFRs per cell, respectively (18, 19). The FAVS results showed that DiFi exosomes contain far more EGFR than do A431 exosomes, far exceeding the two-fold difference in EGFR levels present in these cell lines. Furthermore, using an antibody that recognizes an active form of EGFR, mAb806 (20-22), the amount of active EGFR was also found to be dramatically higher in DiFi exosomes than in A431 exosomes.

FAVS was also used to sort EGFR/CD9 double-positive and double-negative exosome populations, allowing enrichment of both subsets by post-sort analysis as well as western blot validation of the sorted exosomes (see Figure). Using human-specific reagents, FAVS was able to detect DiFi exosomes in the plasma of mice bearing DiFi xenografts. FAVS was also used to demonstrate that EGFR and one of its ligands, amphiregulin (AREG) are present in the plasma of normal individuals.

 

Results from the JEV paper derived from Fig 2. DiFi exosomes were flow sorted using antibodies to EGFR and CD9. Sorted purified double-negative vesicles (blue box/arrow) and double-positive vesicles (red box/arrow) were probed by western blot for markers as shown. These results validate the flow sorting enrichment of these different classes of vesicles.  Also shown is a STORM image of an individual flow sorted double-positive vesicle.

Results from the JEV paper derived from Fig 2. DiFi exosomes were flow sorted using antibodies to EGFR and CD9. Sorted purified double-negative vesicles (blue box/arrow) and double-positive vesicles (red box/arrow) were probed by western blot for markers as shown. These results validate the flow sorting enrichment of these different classes of vesicles. Also shown is a STORM image of an individual flow sorted double-positive vesicle.

 

This work joins flow-sorting work done by other labs using somewhat different techniques (6-14) and has implications for similar kinds of work done by other members of this consortium (23-25). Common to all these techniques was the use of lipid and/or specific extracellular vesicle markers to identify classes of secreted vesicles. Unlike FAVS, many sorting methods trigger vesicular events based on fluorescence rather than scatter. In all of these cases, analysis of secreted vesicle populations was performed. In some cases vesicle sorting was also achieved.

Thus, FAVS appears to be a promising technique to identify and purify distinct subsets of exosomes for discovery studies. It also holds promise for the detection of biomarkers in disease states including subsets of associated secreted RNAs.

References

1. Yang JM, Gould SJ. The cis-acting signals that target proteins to exosomes and microvesicles. Biochem Soc Trans (2013) 41:277-82. PMID 23356297.

2. Kowal J, et al. Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes. Proc Natl Acad Sci USA (2016) 113:E968-77. PMID 26858453.

3. Lunavat TR, et al. Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells–Evidence of unique microRNA cargos. RNA Biol (2015) 12:810-23. PMID 26176991.

4. Cao Z, et al. Use of fluorescence-activated vesicle sorting for isolation of Naked2-associated, basolaterally targeted exocytic vesicles for proteomics analysis. Mol Cell Proteomics (2008) 7:1651-67. PMID 18504258.

5. Higginbotham JN, et al. Amphiregulin exosomes increase cancer cell invasion. Curr Biol (2011) 21:779-86. PMID 21514161.

6. Poncelet P, et al. Standardized counting of circulating platelet microparticles using currently available flow cytometers and scatter-based triggering: Forward or side scatter? Cytometry A (2016) 89:148-58. PMID 25963580.

7. Erdbrugger U, Lannigan J. Analytical challenges of extracellular vesicle detection: A comparison of different techniques. Cytometry A (2016) 89:123-34. PMID 26651033.

8. Chandler WL, Yeung W, Tait JF. A new microparticle size calibration standard for use in measuring smaller microparticles using a new flow cytometer. J Thromb Haemost (2011) 9:1216-24. PMID 21481178.

9. van der Pol E, et al. Single vs. swarm detection of microparticles and exosomes by flow cytometry. J Thromb Haemost (2012) 10:919-30. PMID 22394434.

10. Arraud N, Gounou C, Turpin D, Brisson AR. Fluorescence triggering: A general strategy for enumerating and phenotyping extracellular vesicles by flow cytometry. Cytometry A (2016) 89:184-95. PMID 25857288.

11. Pospichalova V, et al. Simplified protocol for flow cytometry analysis of fluorescently labeled exosomes and microvesicles using dedicated flow cytometer. J Extracell Vesicles (2015) 4:25530. PMID 25833224.

12. Nolte-‘t Hoen EN, et al. Quantitative and qualitative flow cytometric analysis of nanosized cell-derived membrane vesicles. Nanomedicine (2012) 8:712-20. PMID 22024193.

13. van der Vlist EJ, et al. Fluorescent labeling of nano-sized vesicles released by cells and subsequent quantitative and qualitative analysis by high-resolution flow cytometry. Nat Protoc (2012) 7:1311-26. PMID 22722367.

14. Groot Kormelink T, et al. Prerequisites for the analysis and sorting of extracellular vesicle subpopulations by high-resolution flow cytometry. Cytometry A (2016) 89:135-47. PMID 25688721.

15. Demory Beckler M, et al. Proteomic analysis of exosomes from mutant KRAS colon cancer cells identifies intercellular transfer of mutant KRAS. Mol Cell Proteomics (2013) 12:343-55. PMID 23161513.

16. McConnell RE, et al. The enterocyte microvillus is a vesicle-generating organelle. J Cell Biol (2009) 185:1285-98. PMID 19564407.

17. Shifrin DA, et al. Enterocyte microvillus-derived vesicles detoxify bacterial products and regulate epithelial-microbial interactions. Curr Biol (2012) 22:627-31. PMID 22386311.

18. Gross ME, et al. Cellular growth response to epidermal growth factor in colon carcinoma cells with an amplified epidermal growth factor receptor derived from a familial adenomatous polyposis patient. Cancer Res (1991) 51:1452-9. PMID 1847663.

19. Kawamoto T, et al. Growth stimulation of A431 cells by epidermal growth factor: identification of high-affinity receptors for epidermal growth factor by an anti-receptor monoclonal antibody. Proc Natl Acad Sci USA (1983) 80:1337-41. PMID 6298788.

20. Walker F, et al. Ligand binding induces a conformational change in epidermal growth factor receptor dimers. Growth Factors (2012) 30:394-409. PMID 23163584.

21. Gan HK, et al. Targeting of a conformationally exposed, tumor-specific epitope of EGFR as a strategy for cancer therapy. Cancer Res (2012) 72:2924-30. PMID 22659454.

22. Reilly EB, et al. Characterization of ABT-806, a Humanized Tumor-Specific Anti-EGFR Monoclonal Antibody. Mol Cancer Ther (2015) 14:1141-51. PMID 25731184.

23. Stoner SA, et al. High sensitivity flow cytometry of membrane vesicles. Cytometry A (2016) 89:196-206. PMID 26484737.

24. Nolan JP. Flow Cytometry of Extracellular Vesicles: Potential, Pitfalls, and Prospects. Curr Protoc Cytom (2015) 73:13.4.1-6. PMID 26132176.

25. Danielson KM, et al. Diurnal Variations of Circulating Extracellular Vesicles Measured by Nano Flow Cytometry. PLoS ONE (2016) 11:e0144678. PMID 26745887.

Members of the Extracellular RNA Communication Consortium have recently elucidated a mechanism through which hypoxia leads to increased tumor aggressiveness and metastasis. Anil Sood and his group at University of Texas MD Anderson Cancer Center have identified a miRNA that downregulates the very pathway responsible for miRNA biogenesis, a finding that should generate excitement due to the identification of a potential new way of treating cancers: through miRNA or RNA interference-based gene targeting.

The development of tumors is a complex process that involves the cooperation of cancer cells with non-cancer cells, together making up the tumor microenvironment that is vital for tumor survival. As tumors grow and become dense, they begin signaling for the formation of new blood vessels to bring oxygen and nutrients to their core, a process called angiogenesis. Inhibiting angiogenesis is thus a highly attractive therapeutic avenue and is typically accomplished through the targeting of vascular endothelial growth factor (VEGF) and the subsequent induction of hypoxia, or a condition of low oxygen, in the tumor. Hypoxia, however, comes with its own set of problems.

The recent study suggests that hypoxia itself can lead to an increase in the aggressiveness and metastatic potential of a tumor (Rupaimoole et al, 2016). Previous studies have found that hypoxic conditions lead to the downregulation of Drosha and Dicer, two components of the miRNA biogenesis pathway, and that this decrease in expression is associated with poor clinical outcomes through a decrease in the pool of miRNA present in the tumor. In investigating the root cause of Dicer downregulation, Sood and his team identified a miRNA, miR-630, that is upregulated during hypoxia and that targets the 3’ UTR of Dicer. The study validated this targeting by monitoring Dicer mRNA and protein levels both in cells and in vivo in mouse models. Mice that had miR-630 delivered to them via nanoliposomes developed larger tumors and metastases in more places than control mice.

Of particular importance, the researchers treated mice with a combination of anti-miR-630 or anti-VEGF therapy (bevacizumab). Mice that were treated with both bevacizumab and anti-miR-630 developed smaller tumors and fewer metastatic nodules compared with mice treated with bevacizumab alone; Dicer expression was rescued upon treatment with anti-miR-630.

Apart from furthering our understanding of Dicer regulation during cancer, this research demonstrates the potential of treating cancers with anti-miRNA therapies, which would be particularly useful in situations where antibodies or chemical agents are not able to reach a target.

In previous studies in humans, measurement of extracellular RNAs (exRNAs) have primarily focused on microRNAs (miRNAs) or studied a small handful of subjects. The specific question of how large numbers of exRNAs are expressed in broader, non-diseased populations has remained. To examine this question, several groups from multiple institutions collaborated to measure exRNAs in the blood plasma of participants from the Framingham Heart Study, an observational cohort study based in Framingham, MA. In their recent publication (1), they first analyzed RNA sequencing data from the plasma of 40 individuals and identified over a thousand human exRNAs including miRNAs, piwi-interacting RNA (piRNAs), and small nucleolar RNAs (snoRNAs).

Study Design

Study Design

Although miRNAs have been commonly observed in the circulation and plasma, little is known about the presence of other common varieties of small human RNAs such as piRNAs and snoRNAs, known to be key components of molecular interactions and gene regulation in eukaryotes. Using a targeted RT-qPCR approach in an additional 2,763 individuals, the groups then characterized almost 500 of the most abundant extracellular RNA transcripts. The presence in plasma of many non-microRNA small RNAs was confirmed in this independent cohort. The findings show that diverse classes of circulating non-cellular small RNAs, beyond miRNAs, are consistently present in plasma from multiple human populations. Further work will determine how the presence of these exRNAs in the circulation correlates with the presence and progression of a broad number of human traits and diseases.

1. Freedman JE, Gerstein M, Mick E, Rozowsky J, Levy D, Kitchen R, Das S, Shah R, Danielson K, Beaulieu L, Navarro FCP, Wang Y, Galeev TR, Holman A,, Kwong RY, Murthy V, Tanriverdi SE, Koupenova-Zamor M, Mikalev E, Tanriverdi K. Diverse Human Extracellular RNAs are Widely Detected in Plasma. Nature Communications. Published online 26 April 2016.

Overly active KRAS leads to increased serine phosphorylation of Ago2 downstream of MEK and ERK. Phosphorylated Ago2 associates more with P-bodies than with multivesicular endosomes, which reduces the sorting of Ago2 and miRNAs into exosomes bound for export from the cell.

Source: Cell Reports

 

miRNA release into extracellular vesicles (EVs) is a mechanism to control the gene expression and cellular phenotypes of neighboring cells. A key question is how specific miRNAs are sorted into EVs. Active sorting of RNAs to extracellular carriers such as EVs likely depends on binding to specific RNA binding proteins. As a key member of the RNA-induced silencing complex (RISC) machinery that directly binds miRNA, Argonaute 2 (Ago2) has been a strong candidate as a miRNA carrier in EVs. However, the presence of Ago2 in EVs has been controversial.

In a new paper, we show that Ago2 is carried in both microvesicles and exosomes. Using isogenic cell lines for mutant oncogenic KRAS, we show that Ago2 sorting to exosomes is specifically down-regulated by KRAS-MEK-ERK signaling at late endosomes. Tests of three candidate miRNAs showed that this mechanism can regulate sorting of miRNAs to exosomes. Overall, these data indicate that Ago2 sorting to exosomes is a regulated event and may control miRNA sorting. Furthermore, previous studies that were performed in the presence of serum or growth factors in the media may have detected little Ago2 in exosomes due to growth factor activation of KRAS-MEK-ERK signaling. We hypothesize that this may be a mechanism for cells to sense the growth factor milieu and send that information to other cells via alterations in Ago2 and miRNA secretion.

McKenzie et al. “KRAS-MEK signaling controls Ago2 sorting into exosomes.” Cell Reports AOP 21 April 2016.

TGEN_LOGO

This blog post is adapted from a TGen press release, found here.

Uncovering the genetic makeup of patients using DNA sequencing has in recent years provided physicians and their patients with a greater understanding of how best to diagnose and treat the diseases that plague humanity. This is the essence of precision medicine.

Now, researchers at the Translational Genomics Research Institute (TGen) are showing how an even more detailed genetic analysis using RNA sequencing can vastly enhance that understanding, providing doctors and their patients with more precise tools to target the underlying causes of disease and help recommend the best course of action.

In their review, published recently in the journal Nature Reviews Genetics, TGen scientists highlight the many advantages of using RNA-sequencing in the detection and management of everything from cancer to infectious diseases such as Ebola and the rapidly spreading Zika virus.

RNA’s principal role is to act as a messenger carrying instructions from DNA for the synthesis of proteins. Building on the insights provided by DNA profiling, the analysis of RNA provides an even more precise look at how cells behave and how medicine can intervene when things go wrong.

Dr. Sara Byron

Dr. Sara Byron

“RNA is a dynamic and diverse biomolecule with an essential role in numerous biological processes,” said Dr. Sara Byron, Research Assistant Professor in TGen’s Center for Translational Innovation and the review’s lead author. “From a molecular diagnostic standpoint, RNA-based measurements have the potential for broad application across diverse areas of human health, including disease diagnosis, prognosis, and therapeutic selection.”

DNA (deoxyribonucleic acid) sequencing spells out — in order — the billions of chemical letters that make up the genes that drive all of our biologic make-up and functions, from hair and eye color to whether an individual may be predisposed to cancer or other diseases.

RNA (ribonucleic acid) sequencing provides information on the genes that are actively being made into RNA in a cell and are important for cell function. While more complex, RNA holds the promise of more precise measurement of the human physical condition.

There are more forms of RNA than of DNA present in the body, explains Dr. Byron. “RNA sequencing provides a deeper view of a patient’s genome, revealing detailed information on the diverse spectrum of RNAs being expressed.”

One of the most promising aspects of RNA-based measurements is the potential of using extracellular RNA (exRNAs) as a non-invasive diagnostic indicator of disease. Monitoring exRNA simply takes a blood sample, as opposed to doing a tumor biopsy, which is essentially a minor surgery with greater risks and costs.

“The investigation of exRNAs in biofluids to monitor disease is an area of diagnostic research that is growing rapidly,” said Dr. Kendall Van Keuren-Jensen, TGen Associate Professor of Neurogenomics, Co-Director of TGen’s Center for Noninvasive Diagnostics, and one of the review’s authors. “Measurement of exRNA is appealing as a non-invasive method for monitoring disease. With increased access to biofluids, more frequent sampling can occur over time.”

The first clinical test to measure exRNA was released earlier this year, the review said. The test is for use in evaluating lung cancer progression, and the potential for using RNA-seq in other cancers is expanding rapidly. Commercial RNA-seq tests are now available, providing the opportunity for clinicians to more comprehensively profile cancer and use this information to guide treatment selection for their patients, the review said.

In addition, the authors reported on several recent applications for RNA-seq in the diagnosis and management of infectious diseases, such as monitoring for drug-resistant populations during therapy and tracking the origin and spread of the Ebola virus.

Using examples from discovery and clinical research, the authors also describe how RNA-seq can guide interpretation of genomic DNA sequencing results. The use of integrative sequencing strategies in research studies is growing across a broad range of health applications, which promises to drive the incorporation of RNA-seq into clinical medicine as well, the review said.

The paper, Translating RNA-sequencing into Clinical Diagnostics: Opportunities and Challenges, was published online recently in the journal Nature Reviews Genetics. Authors Kendall Van Keuren-Jensen and David W. Craig are participants in the Extracellular RNA Communication consortium.

Source: Translational Genomics Research Institute

The exRNA pathway portal at WikiPathways was created in 2014 and now includes 50 exRNA-related pathways, including 19 from publications by the Extracellular RNA Communication consortium. We are committed to capturing every published pathway figure from the consortium as a properly modeled pathway at WikiPathways. If your work involves pathways, especially if you are publishing it, look into contributing to WikiPathways.

The latest pathways to be curated from consortium publications are:

  1. ApoE and miR-146 in inflammation and atherosclerosis
  2. miR-148a/miR-31/FIH1/HIF1α-Notch signaling in glioblastoma
  3. mir-124 predicted interactions with cell cycle and differentiation
  4. miR-517 relationship with ARCN1 and USP1

The goal of the Wikipathways exRNA portal is to build a collection of pathway models for exRNA researchers to use for illustration, data visualization, and analysis. Each pathway is a self-contained data model that connects to identifier and annotation databases. In addition to providing static images for figures and presentations, these pathways can also be used by bioinformatics and network analysis packages such as Cytoscape and PathVisio. Furthermore, as a wiki, anyone can sign up to improve and grow the content. We invite you all to edit, fix, and add to the pathway models in the exRNA pathway portal at WikiPathways.