Aging, cancer and miR-17–92

It is not long ago that the first miRNA cluster has been identified with oncogenic potential and was therefore termed oncomiR-1 (He et al. 2005). Now, two recent reports have been able to pin down miR-19 as the key oncogenic miRNA of this cluster containing 6 miRNA members (Mu et al. 2009; Olive et al. 2009). Furthermore, the idea that miRNAs also play a role in aging is increasingly substantiated (Grillari and Grillari-Voglauer 2010; Bates et al. 2009). Recently, a large scale microRNA microarray analysis of 4 different cell types in replicative senescence and 3 different tissue types ex vivo representing organismal aging was performed (Hackl et al. 2010). Thereby, a common down-regulation of miR-17, 19b, 20a and miR-106a, members of the miR-17–92 and paralogous cluster, was found (see Table 1 for an overview of the clusters, their members, and their seed sequences). This indicates that this cluster represents one additional important player not only in the complex regulatory network of cell cycle and tumorigenesis, but also in aging, emphasising that these processes are intricately interwoven (Campisi 2003). Even more so, as miR-19 upregulation in cancer activates the AKT-mTOR pathway via PTEN silencing (Olive et al. 2009). It is tempting to speculate therefore, that decrease of miR-19 might lead to increased PTEN and in consequence repress AKT-mTOR, a pathway that has been clearly linked with modulation of life-span in a variety of model organisms (Kapahi et al. 2004; Blagosklonny 2007; Schieke and Finkel 2007) and even in mouse, where the mTOR inhibitor rapamycin leads to a life-span extension (Harrison et al. 2009).

Table 1 Overview on the miRNAs of the miR-17–92 cluster as well as of its paralogous clusters miR-106a–32 and miR-106b–25

Thus, understanding the regulatory network of this cluster might well increase our knowledge on why advancing age is the largest single risk factor to develop cancer. Therefore, we here want to briefly summarize the current knowledge on the regulation loops of this cluster (Fig. 1) especially in regard to senescence that has been largely accepted as tumor suppressor mechanism in vivo (reviewed in Hornsby 2007; Sedivy 2007) and aging.

Fig. 1
figure 1

Overview on transcriptional regulation and target mRNAs of the miR-17–92 cluster

Transcriptional regulation of the miR-17–92 cluster

So far, c-MYC (O’Donnell et al. 2005), E2F1 and 3 (Petrocca et al. 2008b), as well as STAT3 (Brock et al. 2009) have been identified to transcriptionally activate the miR-17–92 cluster and paralogous clusters, while p53 represses it (Yan et al. 2009). However, MYC does not seem to change in senescence (Chang and Chen 1988; Seshadri and Campisi 1990), even though tumour cells enter senescence upon MYC inactivation (Wu et al. 2007). Similarly, STAT3 seems not to be involved, even if it might be expected to rise with senescence in response to the senescence-dependent increase of secreted IL-6 and IL-8 (Acosta et al. 2008) which are upstream activators of STAT3. Why in turn the miR-17–92 cluster is decreased instead of activated is unclear. STAT3 might be blocked at the post-translational level, since it is very susceptible to oxidation and is easily S-glutathionylated. In consequence of this modification, it is not activated by JAK anymore and does not translocate to the nucleus (Xie et al. 2009). High levels of S-glutathionylated, and thus inhibited STAT3 might be possible due to high levels of S-glutathione transferase P that are known to be present in senescent cells (Chang et al. 2005).

Thus, two responsible transcriptional regulators remain to most probably account for less miR-17–92 in senescence. Less E2F family members have been observed in senescent cells (Dimri et al. 1994), and p53, which is a decisive switch in aging and tumorigenesis (Rodier et al. 2007; Schmid et al. 2007) is increasingly active in senescence (Atadja et al. 1995; Kulju and Lehman 1995) and might thus contribute by actively repressing miR-17–92 (Yan et al. 2009).

Targets of the miR-17–92 cluster

Around 30 mRNA targets have been experimentally confirmed so far (Table 2), among them BCL2L11 (Bim), IRF, JNK2/MAPK9, MYCN, PKD1, PKD2, GAB1, RBL1, TSG101 (Cloonan et al. 2008), p63 (Manni et al. 2009), STAT3 and p38/Mapk14 (Carraro et al. 2009), the TGFβ signal pathway (Petrocca et al. 2008a), HIF-1α (Taguchi et al. 2008), or Rbl2/p130 (Wang et al. 2008), p57, p27 and p21 all involved in tumorigenesis and cell cycle control. Especially p21 transcription is well correlated with miR-17, 19b, 20a and miR-106a in the replicative and organismal aging model systems described above (Hackl et al. 2010).

Table 2 Published mRNA targets of the miR-17–92 cluster members

Indeed, miR-17–92 suppression induces complete growth arrest in an anaplastic thyroid cancer cell model (Takakura et al. 2008). In contrast, overexpression of one of its members in mouse embryonic fibroblasts, miR-20a, induces senescence by reducing Leukemia/lymphoma Related Factor (LRF) levels (Poliseno et al. 2008), indicating that cell type specific responses are possible in response to miR-17–92. This is consistent with the notion that overexpression of miR-106a that derives from a paralogous cluster, targets p21 in human fibroblasts and trabecular meshwork cells (Li et al. 2009). Finally, overexpression of miR-17–92 inhibits generation of ROS and DNA damage in RB mutated tumor cells (Ebi et al. 2009).

It will be exciting to see if the opposite, reduction of miR-17–92 will result in more ROS and DNA damage, as well as block of tissue repair by inhibition of stem cell self renewal. All of these are well accepted driving forces of age-related functional decline.


It is still unclear, how and why miR-17–92 is downregulated during aging and senescence. Future work will have to reveal if it is cause or consequence and to what extent its downregulation functionally contributes to aging or even to tumor suppression during aging. In any case, members of this cluster might represent novel biomarkers of aging and the link between miR-17–92 and AKT/mTOR via PTEN might provide a novel regulatory loop of life span modulation.