**6. Results and discussion**

#### **6.1. How does the osteochondral microRNA profile work?**

In Fig. 1, we have presented a microRNA signature, consisting of six microRNA species. These species have been selected amongst microRNAs putatively targeting one or several of 14 transcription factors (TFs) deemed important for osteoblast differentiation from stem cells or precursor cells (Gordeladze, Djouad et al. 2009). It was shown through reporter constructs, that nine of these 14 TFs were targeted by the six microRNAs. Literature studies further indicated that mir-149, and possibly also mir-24, may serve as a switch mecha‐ nism instrumental in determining whether stem cells will become osteoblasts or chondro‐ cytes by interfering with activators, inhibitors and associated proteins instrumental in modulating the effects of Sox9 and Runx2 (lee legend to Fig. 1). These two TFs oppose each other when it comes to differentiation of stem cells or progenitor cells to become mature osteoblasts and chondrocytes (Marie 2008; Gordeladze, Djouad et al. 2009).

A bioinformatics study (see Fig. 2, A-C), using the Mir@nt@n algorithm (Le Bechec, Portales-Casamar et al. 2011), showed that the microRNA species mir-149, mir-328, and mir-339 in particular seemed to serve important regulatory roles when looking at some important criteria for osteoblastogenesis. (A) JUN = transcription factor AP-1, known to be mandatory for osteoblast differentiation (Gordeladze, Djouad et al., 2009), appears to exert a major impact on mir-339, and mir-149 in a hierarchical feed-forward fashion. (B) ETS1 and SP3, two of the 14 TFs constituting the selection criteria for the osteochondral microRNA profile (Gordeladze, Reseland et al., 2011), appeared to serve as inductors of several microRNAs, among which we find the microRNA species mir-149, mir-328, and mir-339. However, ETS1 and SP3 (along with SP1 and SP7 = Osterix) are up-regulated in osteoblastic cells. Hence, the positive control exerted by ETS1 and SP3 may be counterproductive, or maybe not? (C) In a more complicated hierarchical feed-forward network, it can be noted that Sox9, an important regulator of chondrogenesis, actually serves as a master regulator of mir-149 and mir-328, which both are up-regulated in chondrocytes. When modelling the osteochondral microRNA profile with all know factors of the canonical WNT-pathway (using all factors from the KEGG's pathway), a stunningly close interaction between some of the microRNA species of the profile and factors discerning the osteoblast from the chondrocyte phenotypes emerged.

osteoblasts) and analysed for marker gene and microRNA expressions using standard Q-PCR methods (Ambion) or col‐ orimetric methods (mineralized surface visualized by Alizarin red S). **B**. The effect of exosomes-containing 100,000xg fractions of supernatants derived from activated human Th17 cells on human chondrocytes and osteoblasts in the presence and absence of osteoclasts. Differentiated osteoblasts (21 days) exposed to exosomes from Th17 cells (initial 14 days) or antago-microRNAs (initial 14 days) and osteoclasts were injected into the tibial muscle of SCID mice, and molecular markers of osteoblasts and osteoclasts (PBMCs differentiated for 10 days) were analysed by Q-PCR or colori‐ metric methods (Ca2+-analyses in HCl-extracts). All values are given related to control conditions (osteoblasts alone or

In one publication, it was shown that exosomes from healthy volunteers matched mononuclear cells and contained 420 known mature microRNAs (Hunter, Ismail et al. 2008). Hierarchical clustering of the data sets pointed to significant differences in microRNA expression between peripheral blood mononuclear cells (PBMCs) and plasma micro-vesicles. It was observed that 71 microRNAs co-expressed between micro-vesicles and PBMCs. Prediction of the gene targets and associated biological pathways regulated by the detected microRNAs demonstrated that the majority of these microRNAs expressed in the micro-vesicles from the blood were pre‐ dicted to regulate the differentiation of blood cells and their metabolic pathways (Hunter, Ismail et al. 2008). Interestingly, a small group of these microRNA species were also predicted to serve as important modulators of immune function. The microRNAs in question were hypothesized to be taken up by adjacent cells, and thus it may be asserted that exosomes from Th17 cells, known to be present in vast numbers in articular fluid of patients with rheumatoid arthritis (Adamopoulos and Bowman 2008; Nakashima and Takayanagi 2009; Raggatt and Partridge 2010; Nakashima, Hayashi et al. 2012) with rheumatoid arthritis, may disturb the

In Fig. 1, we have presented a microRNA signature, consisting of six microRNA species. These species have been selected amongst microRNAs putatively targeting one or several of 14 transcription factors (TFs) deemed important for osteoblast differentiation from stem cells or precursor cells (Gordeladze, Djouad et al. 2009). It was shown through reporter constructs, that nine of these 14 TFs were targeted by the six microRNAs. Literature studies further indicated that mir-149, and possibly also mir-24, may serve as a switch mecha‐ nism instrumental in determining whether stem cells will become osteoblasts or chondro‐ cytes by interfering with activators, inhibitors and associated proteins instrumental in modulating the effects of Sox9 and Runx2 (lee legend to Fig. 1). These two TFs oppose each other when it comes to differentiation of stem cells or progenitor cells to become

mature osteoblasts and chondrocytes (Marie 2008; Gordeladze, Djouad et al. 2009).

A bioinformatics study (see Fig. 2, A-C), using the Mir@nt@n algorithm (Le Bechec, Portales-Casamar et al. 2011), showed that the microRNA species mir-149, mir-328, and mir-339 in particular seemed to serve important regulatory roles when looking at some important criteria for osteoblastogenesis. (A) JUN = transcription factor AP-1, known to be mandatory for

phenotypic characteristics of osteochondral cells in inflamed joints.

**6.1. How does the osteochondral microRNA profile work?**

osteoblasts + osteoclasts).

490 Regenerative Medicine and Tissue Engineering

**6. Results and discussion**

It may therefore be postulated that the presently described osteochondral microRNA profile serves as a discriminator between osteoblasts and chondrocytes, and can be used as such in the process of cell engineering, while the microRNAs published as markers for osteoblasts by G. Stein and his collaborators distinguish osteoblasts from all other cell phenotypes in a comprehensive manner (Li, Hassan et al. 2008; Hassan, Gordon et al. 2010; Zhang, Xie et al. 2011).

#### **6.2. Summary of experiments proving the functionality of the osteochondral microRNA profile**

In Fig. 3, we list the results of some experiments where the endogenous levels of each micro‐ RNA species of the profile are altered. These experiments indicate that chondrocytes show optimal microRNA profile levels, since some 6-8 fold increase do not alter their characteristics, subsequent to differentiation from hMSCs. A reduction to 12-14% of their endogenous levels shows that mir-16, mir-125b, mir-328, and mir-339 are necessary for chondrogenesis, while mir-24 and mir-149 are not. Contrastingly, enhancing the endogenous levels of all the micro‐ RNA species in hMSCs more or less block their differentiation towards the osteoblast lineage. As expected, reducing their levels in hMSCs by a factor of 2-2.5 clearly fortified their phenotype as osteoblasts. This experiment establishes the six microRNAs as instrumental in osteochon‐ dral differentiation, while mir-24 and mir-149 play a dual role, being able to simultaneously block osteoblastogenesis and stimulate chondrogenesis. An explanation for this dual role has been sought in the information conveyed in Figs. 3A&B, looking for published data on their known targets, as well as bioinformatics profiles, i.e. positions in feed-forward interaction networks (see legend to Fig. 3).

#### **6.3. Osteochondral cells influence osteoclasts: The impact of cytokines**

In Fig. 4A, we depict a co-culture system where hMSCs are differentiated towards osteochon‐ dral cells for 2 weeks and co-cultured with differentiated osteoclasts on dentine for a third week. The osteoclasts have been differentiated from hPBMCs for 1 week with RANK-L and M-CSF. It is clear that chondrocytes do stimulate osteoclasts to resorb bone, and that exposure of the chondrocytes to cytokines ("artificial" synovial fluid from individuals with rheumatoid arthritis = RA, i.e. growth medium containing IL-1, IL-6, IL-17A and TNFα) enhances the osteoclasts' bone resorbing potential.

#### **6.4. MicroRNA manipulation of osteochondral cells: Obliteration of the impact of cytokines**

In Figs. 4B&C it is shown that TGFβ3-stimulated hMSCs to chondrocytes or BMP2-stimulated hMSCs to osteoblasts exposed to cytokines in fact are protected against loss of phenotypes and normalize (i.e. reduce) their ability to enhance osteoblast activity upon normalization of their endogenous microRNA profile. The tables show data for Q-PCR of phenotype marker genes, RANK-L and OPG (counteracting each other), functional markers like clinical score (consti‐ tuted by chondrocyte bead histology, immunohistochemistry, distance between cells, GAGcontents), mineralizing surface, percentage of TRAP-positive cells containing ≥ 3 nuclei, eroded dentine surface (%), as well as Q-PCR of microRNAs of the osteochondral signature.

#### **6.5. In vivo model of osteochondral cells interacting with osteoclasts**

In Fig 5A, X-ray pictures and biopsy histology of tibial muscles of SCID mice are shown. Their muscle tissue has been injected with hMSCs, osteoblasts without and with the presence of differentiated osteoclasts. The osteoblasts were either loaded with antago-microRNAs of the osteochondral signature or not. Additional experiments where hMSCs or osteoblasts had been exposed to cytokines alone or cytokines and antago-microRNAs together are not shown on the figure. A similar experimental matrix was conducted (but not shown) with chondrocytes differentiated from hMSCs. The pictures indicate that mature osteoblasts and osteoclasts are able to build bone within the muscle tissue, and that a suppression of the endogenous levels of the microRNA species of the osteochondral signature lead to enhanced mineralization of osteoid produced.

When chondrocytes (see Fig. 5B) are pre-exposed to osteoblasts, it appears that the cells are able to maintain their net cartilage-building potential, possibly by down-regulating their cytokine-induced osteoclast-activating potential. The same phenomenon is also seen when osteoblasts are injected into the *m. tibialis* of SCID mice.

Cytokines induce a reduction in osteoblast functions, while also enhancing osteoclast activa‐ tion resulting in a lessened bone deposit, while introduction of antago-microRNAs reverses the action of cytokines towards maintenance of the bone-building capacity of the osteoblast (see Fig. 5C). A special attention to the Q-PCR data on osteoclast specific markers (CT receptor, TRAP, cathepsin K and CA II) analysed in the excised *de novo* bone tissue is warranted. Furthermore, it should be emphasized that the X-ray analyses of the lower legs injected with osteoblasts were corroborated analysing the Ca2+-contents in acid extracts/digests, using standard spectrophotometry.

#### **6.6. The effect of exosomes derived from activated Th17 cells**

M-CSF. It is clear that chondrocytes do stimulate osteoclasts to resorb bone, and that exposure of the chondrocytes to cytokines ("artificial" synovial fluid from individuals with rheumatoid arthritis = RA, i.e. growth medium containing IL-1, IL-6, IL-17A and TNFα) enhances the

**6.4. MicroRNA manipulation of osteochondral cells: Obliteration of the impact of cytokines**

In Figs. 4B&C it is shown that TGFβ3-stimulated hMSCs to chondrocytes or BMP2-stimulated hMSCs to osteoblasts exposed to cytokines in fact are protected against loss of phenotypes and normalize (i.e. reduce) their ability to enhance osteoblast activity upon normalization of their endogenous microRNA profile. The tables show data for Q-PCR of phenotype marker genes, RANK-L and OPG (counteracting each other), functional markers like clinical score (consti‐ tuted by chondrocyte bead histology, immunohistochemistry, distance between cells, GAGcontents), mineralizing surface, percentage of TRAP-positive cells containing ≥ 3 nuclei, eroded

dentine surface (%), as well as Q-PCR of microRNAs of the osteochondral signature.

In Fig 5A, X-ray pictures and biopsy histology of tibial muscles of SCID mice are shown. Their muscle tissue has been injected with hMSCs, osteoblasts without and with the presence of differentiated osteoclasts. The osteoblasts were either loaded with antago-microRNAs of the osteochondral signature or not. Additional experiments where hMSCs or osteoblasts had been exposed to cytokines alone or cytokines and antago-microRNAs together are not shown on the figure. A similar experimental matrix was conducted (but not shown) with chondrocytes differentiated from hMSCs. The pictures indicate that mature osteoblasts and osteoclasts are able to build bone within the muscle tissue, and that a suppression of the endogenous levels of the microRNA species of the osteochondral signature lead to enhanced mineralization of

When chondrocytes (see Fig. 5B) are pre-exposed to osteoblasts, it appears that the cells are able to maintain their net cartilage-building potential, possibly by down-regulating their cytokine-induced osteoclast-activating potential. The same phenomenon is also seen when

Cytokines induce a reduction in osteoblast functions, while also enhancing osteoclast activa‐ tion resulting in a lessened bone deposit, while introduction of antago-microRNAs reverses the action of cytokines towards maintenance of the bone-building capacity of the osteoblast (see Fig. 5C). A special attention to the Q-PCR data on osteoclast specific markers (CT receptor, TRAP, cathepsin K and CA II) analysed in the excised *de novo* bone tissue is warranted. Furthermore, it should be emphasized that the X-ray analyses of the lower legs injected with osteoblasts were corroborated analysing the Ca2+-contents in acid extracts/digests, using

**6.5. In vivo model of osteochondral cells interacting with osteoclasts**

osteoblasts are injected into the *m. tibialis* of SCID mice.

osteoclasts' bone resorbing potential.

492 Regenerative Medicine and Tissue Engineering

osteoid produced.

standard spectrophotometry.

Lastly, we shall address the hypothesis put forward that exosomes shedded from immune cells may affect the characteristics of osteochondral cells. Th17 cell exosomes-like particles were obtained from 100,000xg centrifugates of cultures of activated Th17 cells (Larsen, Arnaud et al. 2011). The pellets were examined for microRNAs (micro-arrays), and 55 microRNA-species were identified. Of these, hsa-mir-22- and hsa-mir-222 are especially interesting, since the exosome-fraction contained large quantities of these, and because Th17 cell clones also produced large quantities of the same microRNA species, and since osteoblasts and chondro‐ cytes expressed relatively low levels of the mir-22, and mir-222 species, respectively.

Fig. 6A depicts chondrocytes having been differentiated from hMSCs for 2 weeks receiving control medium or control medium + Th17 cells derived exosomes or pre-microRNA mir-222 on days 15-21. Q-PCR of marker genes and microRNA transcripts, as well as collagen2α1 positive surface analyses were conducted and showed that chondrocyte characteristics were suppressed. The same experiment was conducted on hMSCs differentiated towards osteo‐ blasts in the absence or presence of Th17 cell exosomes or pre-microRNA mir-22, and pheno‐ type marker analyses (i.e. Q-PCR of marker gene transcripts and mineralized surface) conducted. Not surprisingly, the osteoblast phenotype was suppressed due to both treatments. This indicates that exosomes from Th17 cells contain microRNAs detrimental to the function‐ ing of mature chondrocytes and osteoblasts, and it may well be so that engineered osteochon‐ dral cells, deposited within a joint to replace damaged tissues, should be made resilient to inflammatory cells to maintain their proper phenotypic functioning over time.

One experiment (see Fig. 6B) with osteoblasts, osteoclasts, exosomes and antago-microRNAs of the osteochondral signature was performed on SCID mice, as envisaged earlier. X-rays (not shown) and analyses on excised biopsies from the tibial muscle showed that exposure to Th17 cell exosomes hampered the development of the matrix-producing and mineralizing proper‐ ties of osteoblasts, while enhancing activating of adjacent osteoclasts. The introduction of antago-microRNAs of the osteochondral signature did, however, reinstall the osteoblasts' ability to produce bone, which was not degraded by osteoclasts. This phenomenon was corroborated through analyses of the Ca2+-contents of the biopsies taken (see also text-Fig. 5B).

#### **6.7. Other results obtained**

The present series of experiments also addressed whether certain scaffold materials and their 3D-structures were better suited to produce osteochondral cells with a "true" (*in vivo* like) phenotype being more robust and resilient towards provocations, such as chronic disease states. Whether we used scaffolds, i.e. alginate beads instead of micro-pellets, or hydroxya‐ patite instead of 2D-growth, really did not matter. However, we did not use promising scaffolds for osteoblast differentiation, like TiO2 or surfaces with an inverted profile of cellular outer membrane surface nanostructures (Muys, Alkaisi et al. 2006; De Smet, Jaecques et al. 2007; Mazzola, Bemporad et al. 2011).

#### **6.8. General discussion of the findings presented**

This report is more about experimental approaches and results speaking for themselves than a lengthy discussion of their implications from a theoretical point of view. A few issues do, nevertheless, deserve attention.

Most reports on microRNA impact on cell differentiation and phenotype development and stability focus on one microRNA species only, or they present a microRNA micro-array showing a bulk of microRNAs being up- and down-regulated subsequent to cell differentia‐ tion. Since microRNAs exert different binding kinetics when they bind to different mRNAs at various places (not only to the 3'-UTR, but also to the 5'-UTR region) (Moretti, Thermann et al. 2010), it is reasonable to believe that a minimum effective group of microRNAs is necessary and sufficient to ensure complete differentiation and stability of a certain cell phenotype (Gordeladze, Djouad et al. 2009; Iorio, Casalini et al. 2011; Schoof, Botelho et al. 2012). The osteochondral signature of microRNAs presented in this chapter may serve as such a group, discriminating between cell types, however, several other microRNA species described by G. Stein and collaborators (Li, Hassan et al. 2009; Hassan, Gordon et al. 2010; Zhang, Xie et al. 2011) may serve the same purpose. In fact, our microRNA micro-arrays obtained from osteoblastic cells in different stages of differentiation from hMSCs do overlap extensively to the ones published in recent literature (Lian, Javed et al. 2004).

Which microRNAs are to be construed as the "true" marker for osteoblasts? They may constitute more than the six species presented here, or even other than the ones we have focussed on. The main issue is how they interact with feed-forward and feed-back regulatory loops, in which transcription factors and marker genes are positioned. This issue has been addressed in the bioinformatics exercises outlined in Fig. 2. Here, mir-26b pops up as being important, and this microRNA is known to a network of factors serving as a possible target for RNA-based therapy of bone diseases (Luzi, Marini et al. 2012). The main issue is: which microRNAs out of a smaller group will be necessary and sufficient to determine or alter a certain phenotype? Our experiments with the present osteochondral microRNA signature seem to render one such microRNA group distinguishing between osteoblasts and chondro‐ cytes. A further proof of concept put forward is the fact that these microRNAs can be applied to trans-differentiate osteoblastic cells to chondrocytes and back again, and they are also able to a large extent (some 85%) substitute growth factors (TGFs and BMPs) as mandatory to obtain chondrocytes and osteoblasts from hMSCs or human adipose tissue derived stem cells (hADMSCs) (Gordeladze, JO, unpublished results).

In chapter 2 of the book "Regenerative Medicine and Tissue Engineering: Cells and BioMate‐ rials" (Gordeladze 2011), we introduced a concept of compatibility score between microRNA micro-arrays and transcriptomes obtained from chondrocytes and osteoblasts differentiated from precursor cells of stem cell origin (ref). We still believe that a proper way to ensure "correct" phenotype is to correlate consensus micro-arrays of marker gene transcripts with microRNA micro-arrays; however, such analyses were not performed on the present manip‐ ulated biological material. Due to relative meticulous experimentation consuming a lot of manpower, biological material and costly analyses, it was not performed. However, microarrays analysed at certain intervals during a differentiation process may seem necessary to be able to arrive at the superior microRNA profiles describing a certain cell phenotype to be distinguished from other phenotypes.

**6.8. General discussion of the findings presented**

the ones published in recent literature (Lian, Javed et al. 2004).

(hADMSCs) (Gordeladze, JO, unpublished results).

nevertheless, deserve attention.

494 Regenerative Medicine and Tissue Engineering

This report is more about experimental approaches and results speaking for themselves than a lengthy discussion of their implications from a theoretical point of view. A few issues do,

Most reports on microRNA impact on cell differentiation and phenotype development and stability focus on one microRNA species only, or they present a microRNA micro-array showing a bulk of microRNAs being up- and down-regulated subsequent to cell differentia‐ tion. Since microRNAs exert different binding kinetics when they bind to different mRNAs at various places (not only to the 3'-UTR, but also to the 5'-UTR region) (Moretti, Thermann et al. 2010), it is reasonable to believe that a minimum effective group of microRNAs is necessary and sufficient to ensure complete differentiation and stability of a certain cell phenotype (Gordeladze, Djouad et al. 2009; Iorio, Casalini et al. 2011; Schoof, Botelho et al. 2012). The osteochondral signature of microRNAs presented in this chapter may serve as such a group, discriminating between cell types, however, several other microRNA species described by G. Stein and collaborators (Li, Hassan et al. 2009; Hassan, Gordon et al. 2010; Zhang, Xie et al. 2011) may serve the same purpose. In fact, our microRNA micro-arrays obtained from osteoblastic cells in different stages of differentiation from hMSCs do overlap extensively to

Which microRNAs are to be construed as the "true" marker for osteoblasts? They may constitute more than the six species presented here, or even other than the ones we have focussed on. The main issue is how they interact with feed-forward and feed-back regulatory loops, in which transcription factors and marker genes are positioned. This issue has been addressed in the bioinformatics exercises outlined in Fig. 2. Here, mir-26b pops up as being important, and this microRNA is known to a network of factors serving as a possible target for RNA-based therapy of bone diseases (Luzi, Marini et al. 2012). The main issue is: which microRNAs out of a smaller group will be necessary and sufficient to determine or alter a certain phenotype? Our experiments with the present osteochondral microRNA signature seem to render one such microRNA group distinguishing between osteoblasts and chondro‐ cytes. A further proof of concept put forward is the fact that these microRNAs can be applied to trans-differentiate osteoblastic cells to chondrocytes and back again, and they are also able to a large extent (some 85%) substitute growth factors (TGFs and BMPs) as mandatory to obtain chondrocytes and osteoblasts from hMSCs or human adipose tissue derived stem cells

In chapter 2 of the book "Regenerative Medicine and Tissue Engineering: Cells and BioMate‐ rials" (Gordeladze 2011), we introduced a concept of compatibility score between microRNA micro-arrays and transcriptomes obtained from chondrocytes and osteoblasts differentiated from precursor cells of stem cell origin (ref). We still believe that a proper way to ensure "correct" phenotype is to correlate consensus micro-arrays of marker gene transcripts with microRNA micro-arrays; however, such analyses were not performed on the present manip‐ ulated biological material. Due to relative meticulous experimentation consuming a lot of

One question pertaining to the assurance of a reproducible process of establishing engineered cells with the "correct" phenotype is: Why play with microRNAs, is it not enough to manip‐ ulate using growth factors and the 3D-structure, in which the precursor cells are grown? Firstly, it is important to know the interplay between factors able to induce a certain cell phenotype and/or trans-differentiate phenotypes. In this respect, it seems fruitful to concentrate on several microRNAs, and not only on one microRNA species. But, it is also reasonable to play with the expression of certain transcription factors (TFs) being positioned in key places in a regulatory network constituted by TFs, activators, inhibitors or associated proteins, as well as functional marker genes. Sox9, a TF deemed sufficient and necessary for chondrocyte development (see legend to Fig. 2C) may be over-expressed or suppressed to engineer chondrocytes or osteo‐ blasts, since it affects the expression of important microRNAs and marker genes in a hierarch‐ ical fashion. Apparently, so do ETS1 and SP3, or MYC and JUN (see legend to Figs. 2B&A).

However, it seems reasonable to believe that, at least during a shorter, critical period of time, externally added growth factors and the selection of biologically "correct" scaffold structures and materials will aid in the process of proper phenotype acquisition for tissue replacement purposes. It has also been pointed out that it is vital, for a proper tissue to be generated, to use cell material which can differentiate into several cell types constituting a certain tissue, or that the engineered cell material is able to recruit cells from the ambiance to produce a correctly functioning tissue *in vivo*. A good example of this seems to be an artificially made tracheal epithelium, using collagen vitrigel-sponge scaffolds containing bFGF as growth factor and chemotactic agent (Tani, Tada et al. 2012).

We are now seeking to produce polycistronic constructs containing pre-microRNAs or antago-microRNAs to be temporarily activated in order to test whether the microRNAbased concept of cell engineering may function in an *in vivo* animal model of rheuma‐ toid arthritis, where articular joints are inflamed and contain immune cells (i.e. Th17 cells). Hence, we will be able to find out whether osteochondral cells may be engineered to withstand the detrimental effect of cytokines and exosomes containing (amongst many bioactive molecules) unwanted microRNA species. Promising small animal models to start with are collagen-induced arthritis in the mouse, and the senescence mouse (Aigner, Rose et al. 2004; Manolagas and Almeida 2007) prior to the testing in larger animals (i.e. sheep model systems) (Gordeladze, Reseland et al. 2009).

Lastly, the present experiments confirm the complexity of bone remodelling in the healthy individual and in patients with diseases affecting cartilage and bone structure. Not only hormones, like active vitamin D (calcitriol) and PTH affect bone turnover, via their dual effects on osteoblasts and osteoclasts. The interaction with the immune system directly interfering with the balance between RANK-L and OPG (Adamopoulos, Sabokbar et al. 2006; Nakashima, Hayashi et al. 2012), as well as cell-to-cell communication through exosomes, containing a plethora of bioactive molecules, urges new research approaches to unravel the intricate mechanisms ensuring bone and cartilage health before and after the onset of disease states damaging the tissues in question. We have here confirmed that chondrocytes, in fact, do affect osteoclasts directly (Xiong, Onal et al. 2011), and that cytokines obtained from Th-cells, and Th17 cells in particular, are detrimental to the osteochondral phenotypes, with an additional activation of osteoclasts.

The present experimental setting also show that exosomes from Th17 cells may interfere with both the chondrocytic and osteoblastic phenotypes in a negative fashion (i.e. phenotype acquisition and matrix deposition), while also speeding up bone remodelling via overactivation of osteoclasts embedded in the bone adjacent to the cartilage lining. These findings are consistent with the development of cartilage loss and the appearance of osteophytes (newly formed bone in disarray) in arthritic joints due to the progressing autoimmune process characteristic of rheumatoid arthritis (Hayashi, Xu et al. 2012).
