Year: 2017

The role of extracellular vesicles (EVs) in cancer has recently become a promising area of research. A primary function of EVs is to deliver molecules from a donor cell to regulate cellular processes in a target cell. Little research has investigated what effect departing EVs may have on the donor cell.

In cancer, EVs from tumor cells can deviate from their original purpose. Altering vesicular content could benefit tumors, for example by increasing tumor proliferation or strengthening drug resistance.
 

Exosomal Packaging
Could donor tumor cells selectively shunt cancer-fighting molecules into secreted vesicles to escape their effects? Teng et al. thought this might be the case. They hypothesized that tumor cells specifically secrete tumor suppressor miRNA, namely miR-193a, into exosomes, a class of EV secreted via the endocytic membrane transport pathway, while oncogenic miRNAs are kept.

To test this theory, they validated miR-193a’s function in a mouse model. Specifically, they found that miR-193a targets Caprin1, a cell-cycle-associated protein, and arrests the cell cycle in phase G1. Thus, secreting miR-193a from the cell in exosomes would restart the cell cycle and enable a tumor cell to proliferate.

After studying miR-193a’s primary function, the authors explored what might facilitate its secretion. They showed that MVP (major vault protein) complexes with miR-193a and that knock-down of MVP leads to higher levels of miR-193a in the cell and less miR-193a in exosomes. They concluded that MVP mediates the sorting of miR-193a into exosomes. They also found that a higher level of MVP in the cell correlates with lower levels of miR-193a and higher levels of Caprin1, indicating that MVP aids in cell proliferation. Lastly, the researchers determined in a mouse model that export of miR-193a by MVP promotes metastasis of colon cancer to the liver.

Figure 1 shows a model of these interactions. In the pre-metastatic cell, miR-193a is freely expressed. In the tumor metastatic cell, MVP has complexed with miR-193a, driving it into exosomes to be secreted.

Figure 1: Model for the mechanism of colon cancer metastasis to the liver. Tumor suppressor mir-193a is sorted into exosomes by Major Vault Protein (MVP) and then secreted from the cell.

Cancer Biomarker
This finding implicates exosomal miR-193a as a potential biomarker for colon cancer. Could higher levels of exosomal miR-193a indicate a more aggressive disease? To answer these questions, the authors applied their findings in the clinical setting. Teng et al. examined the livers of mice with metastatic colon cancer, performing an extensive characterization of the levels of tumor suppressive and oncogenic miRNAs in normal and tumor cells and in the exosomes secreted by both. From that extensive analysis, they chose three miRNAs upregulated (miR-193a, miR-126 and miR-148a) and one miRNA downregulated (miR-196b) in exosomes from tumor cells and examined the levels of those miRNAs in exosomes purified from the blood (plasma) of 40 colon cancer patients, 15 with metastasis to the liver and 25 without. They found the same upregulation and downregulation of the 4 miRNAs in the patient population, with higher levels in the population with liver metastasis.

This exciting study identifies potential biomarkers for colon cancer. The two main findings highlight the importance of exosomes in cancer proliferation. First, the authors found that tumor suppressing miRNAs are packed into exosomes, while oncogenic miRNAs remain in the cell. Next, they found that there are higher amounts of tumor suppressing miRNAs in tumor-derived exosomes relative to exosomes from healthy cells. They also found that MVP acts as a mediator of these differences between metastatic and healthy cells. Teng et al. believe that once we develop a dependable method to purify exosomes, scientists may uncover further roles for exosomes in cancer progression.

Recent research from members of the ExRNA Communication Consortium (ERCC) suggests that extracellular RNAs (exRNAs) circulating in plasma play an active role in insulin resistance (IR). Insulin resistance is an incurable but manageable syndrome where the body stops reacting efficiently to the insulin hormone, which stimulates the uptake of glucose in the blood into cells and inhibits the body from using fat for energy, resulting in high blood sugar levels. The study, by Shav et al., points to certain exRNAs, particularly miR-122 and miR-192, as indicators and active players in IR regardless of the age, sex, or BMI of a person, which suggests that they may serve as more than metabolic markers and that they perhaps have functional, trans-organ roles in mediating IR.

Previous research has demonstrated that exRNAs have different functions in pathways relating to metabolic syndrome, which is a series of conditions that increase the risk of heart disease, stroke, and diabetes. For example, there is measurable miRNA dysregulation in obesity and in the progression of cardiometabolic disease. Other miRNAs are involved in brown/white fat specification, adipose tissue inflammation (Karbiener and Scheideler, 2014), and hepatic steatosis (fatty liver disease, Becker et al., 2015). Although these studies have identified specific exRNAs and miRNA networks that also have roles in IR, they have had either small sample sizes and lack validation in large populations or have been carried out in non-human models. In order to validate these data, the authors carried out a large-scale human translational study in which they analyzed detailed obesity-related phenotypic data from over 2,500 participants (most of whom were non-diabetic) from the Framingham Heart Study (FHS), an unrelated cardiovascular disease study (Feinleib et al., 1975).

To begin, the investigators analyzed blood samples from 2,317 non-diabetic study participants and quantified the plasma extracellular circulating exRNAs. They looked at RNAs [including piwi-interacting RNA (piRNA) and small nucleolar RNA (snoRNA)] expressed above a threshold level and excluded RNAs that were not found in at least 100 participants. From the resulting panel of 391 exRNAs, the investigators identified 16 microRNAs (miRNA), 1 piRNA, and 1 snoRNA that were associated with insulin after controlling for age, sex, and BMI. Of note, the abundance of miR-122 was shown to increase in a stepwise fashion as levels of insulin increased across the population. Higher levels of both miR-122 and miR-192 in the plasma were also consistently associated with a series of metabolic phenotypes, such as greater BMI and waist circumference, visceral fat quantity and quality, and liver attenuation. On the other hand, neither miRNA was associated with subcutaneous fat. These results were consistent whether the analysis included only the non-diabetic participants or the entire FHS population.

miRNAs function to regulate gene expression, so the authors conducted a pathway analysis to determine the targets of the 16 identified miRNAs. Almost unsurprisingly, all 16 miRNAs target insulin signaling pathways such that there is ample crosstalk and targeting of multiple IR-related genes by multiple miRNAs. This analysis validated findings from previous studies that implicated several miRNA target genes in the pathogenesis of IR, notably protein tyrosine phosphatase, nonreceptor type 1 (PTP1B) (Stull et al., 2012), mitogen-activated protein kinases (MAPKs) (Wang, Goalstone & Draznin, 2004), and 5′ adenosine monophosphate-activated protein kinase (AMPK) (Ruderman et al., 2013).

For the second part of the study, the investigators determined whether the miR-122 and miR-192 associations to age, sex, and BMI held true in a separate study population, a cohort of 90 overweight or obese young adults involved in the POOL study. Analyses of the youths’ plasma samples indicated that miR-122 (but not miR-192) was associated with greater IR after adjusting for age, sex, and BMI, and that this association remained even after the miRNA was analyzed independently of age, sex, BMI, or metabolite profile.

This study provides additional evidence and translational support for the role of exRNAs in IR. The findings indicate not only an association of exRNAs with insulin levels, but that the exRNAs may be playing an active role in the development or sustainment of IR. It is therefore critical to conduct further mechanistic investigations into the role of exRNAs in the metabolic architecture of IR.

The study of RNAs that do not produce proteins, so-called noncoding RNAs, has been an active area of research for many years. Recently, new kinds of non-coding RNAs have been described that have poorly defined activities. Circular RNA (circRNAs) are one of these more enigmatic biomolecules. They are formed when the 5′ head and 3′ tail of a messenger RNA precursor are spliced together. Next-generation sequencing studies have recently shown that circRNAs are abundant and widely expressed in mammals. While other non-coding RNAs have been shown to play critical roles in cancer, the association between circRNAs and cancer is largely unknown. In addition, the degree to which circRNAs are secreted outside the cell has not been well explored.

To study the presence and regulated release of circRNAs during colorectal cancer (CRC) progression, we used three related colon cancer cell lines that differ only in the mutation status of KRAS, an enzyme that acts at the beginning of a wide array of cellular signaling pathways. The parental cell line (DLD-1) contains both wild-type and G13D mutant KRAS alleles, whereas the derivative cell lines contain only a mutant KRAS (DKO-1) or wild-type KRAS (DKs-8) allele (Shirasawa et al. 1993). The G13D mutation locks KRAS into an active state. KRAS mutations occur in approximately 34–45% of CRCs and have been associated with a wide range of tumor-promoting effects (Vogelstein et al. 1988, Wong and Cunningham 2008). We performed deep RNA-Seq analysis of ribosomal RNA-depleted total RNA libraries to characterize circRNA expression in these cell lines and in the exosomes they release. The results from this study were recently published in the journal Scientific Reports (Dou et al. 2016).

Using a unique pipeline developed by our group, we identified hundreds of high-quality candidate circRNAs in each cell line. Remarkably, circRNAs were significantly down-regulated at a global level in the cell lines with mutant KRAS alleles (DLD-1 and DKO-1) compared to wild type (DKs-8), indicating a widespread effect of mutant KRAS on circRNA abundance (see Figure 1). This finding was confirmed in another pair of cell lines. In all of these cell lines, circRNAs were found associated with secreted exosomes, and circRNAs were more abundant there than in cells. Although circRNAs were down-regulated in cell lines with mutant KRAS alleles, it is difficult to conclude that KRAS directly regulates circRNAs. Nevertheless, our analysis did show that down-regulation of circRNAs in KRAS mutant cells was not caused by their increased export to exosomes.
 

Figure 1. The blue highlight shows that expression of most circRNAs is lower in the KRAS-mutant cell lines than in the KRAS wild-type cell line.
FDR = False Discovery Rate; a higher number indicates a more confident prediction of a difference in expression.

There are complex regulatory mechanisms for expression of both circRNA and the host genes from which they derive. Figure 2 shows that lower expression of circRNA in the mutant KRAS vs. wild-type cell lines was not matched by a similar lower expression of host gene mRNA. We found a similar lack of correlation in circRNA and host gene mRNA expression level in all the exosome populations we studied. These results imply that regulation of circRNAs can occur independent of their host genes, and different regulatory processes might direct secretion of circRNA and host gene mRNA.
 

Figure 2. The blue highlight shows that while expression of most circRNAs is lower in the KRAS-mutant than in the wild-type cell line, host gene mRNA expression shows no such pattern.

To further delineate how circRNA biogenesis could be affected by mutant KRAS, we also examined the expression levels of the RNA-editing enzyme ADAR and the RNA-binding protein QKI, which have been reported as circRNA regulators (Ivanov et al. 2015, Conn et al. 2015) (see Figure 3). Here we obtained contradictory results. The level of ADAR was decreased in the KRAS mutant cells; reduced ADAR activity could lead to an increase of circRNAs. QKI was also down-regulated in KRAS mutant cells, which could lead to a decrease of circRNAs.
 

Figure 3. Effect of ADAR and QKI on pre-mRNA circularization

More broadly, we studied the expression levels of all RNA-binding proteins within the RBPDB database (Cook et al. 2011). Six were found to be significantly differentially expressed in KRAS mutant cell lines compared with wild-type KRAS cell lines (ELAVL2, RBMS3, BICC1, MSI1, RBM44, and LARP6). These genes may serve as candidate circRNA regulators. However, our previous work shows that the correlation between mRNA and protein expression level is low for RNA-binding proteins (Zhang et al. 2014), and thus RNA levels for these RNA-binding proteins might not reflect their true protein levels. Further investigation will be needed to precisely define how circRNAs are regulated. Nevertheless, our results show that oncogenic mutations can change circRNA composition in cells and exosomes and suggest that circRNAs may serve as promising cancer biomarkers.

References

Conn, S.J., et al. The RNA binding protein Quaking regulates formation of circRNAs. Cell (2015) 160: 1125-1134. PMID 25768908.

Cook, K.B., et al. RBPDB: a database of RNA-binding specificities. Nucleic Acids Res (2011) 39: D301-D308. PMID 21036867.

Dou, Y., et al. Circular RNAs are down-regulated in KRAS mutant colon cancer cells and can be transferred to exosomes. Sci Rep (2016) 6: 37982. PMID 27892494.

Ivanov, A., et al. Analysis of intron sequences reveals hallmarks of circular RNA biogenesis in animals. Cell Rep (2015) 10:170-177. PMID 25558066.

Shirasawa et al. Altered growth of human colon cancer cell lines disrupted at activated Ki-ras. Science (1993) 260:85-88. PMID 8465203.

Vogelstein, B., et al. Genetic alterations during colorectal-tumor development. N Engl J Med (1988) 319:525-532. PMID 2841597.

Wong, R. and Cunningham, D. Using predictive biomarkers to select patients with advanced colorectal cancer for treatment with Epidermal Growth Factor Receptor antibodies. J Clin Oncol (2008) 26:5668-5670. PMID 19001346.

Zhang, B., et al. Proteogenomic characterization of human colon and rectal cancer. Nature (2014) 513:382-387. PMID 25043054.