8 | OCTOBER 2001 | VOLUME 1 www.nature.com/reviews/cancer

RIZ1 — a suspected protein methyltransferase— has long been thought to possess tumour-suppressor activity: its gene maps to a regionthat is frequently deleted in human cancers,and reintroducing the gene into tumours causesapoptosis and growth suppression in animaltumour models. Definitive proof has, however,not been available until now. Steele-Perkins etal., in the September issue of Genes &Development, show that mice deleted for Riz1develop a range of tumours, and that severalhuman tumours contain mutations in RIZ1.RIZ1 is therefore the founding member of anew class of tumour suppressors.

RIZ1 was initially isolated as an RB-bindingprotein and a transcriptional co-activator. Itpossesses two important motifs — an RB-binding motif and a nuclear hormone receptorbinding motif — in addition to the PRdomain, which places it within the PR subfamilyof protein methyltransferases. RIZ1’s substratesare a complete mystery, but the gene is deletedin many human cancers, and mRNA expres-

sion is also decreased or lost in many more,probably by epigenetic silencing. So, is RIZ1 atumour suppressor?

Riz1–/– mice developed normally, but had ashorter lifespan than Riz1+/– and Riz1+/+ mice,owing to an increase in tumour burden. In fact,80% of Riz1–/– mice had tumours at 20 months(compared with 30% of Riz1+/+ mice), andalmost half of these had tumours in severalorgans. The predominant tumour type inRiz1–/– mice is malignant B-cell lymphoma,with a histology similar to diffuse large B-celllymphoma (DLBL). Mutation of Riz1 in aTrp53+/– background also increased tumourformation compared with Riz1–/– and Trp53+/–

mice, indicating a cooperative effect on tumori-genesis and confirming that Riz1 acts as atumour suppressor in mice.

So, does RIZ1 also participate in tumori-genesis in humans? Single-strand conformationpolymorphism analysis of RIZ1 in 35 humanDLBL tumours revealed that ten of these hadan abnormal band, corresponding to a singlebase substitution, C-terminal to the PR domain.Not one of the other 432 tumours tested had amutation in this region.

The authors also found other mutations inthis region of RIZ1, either within or C-terminal

to the PR domain. Using its ability to stimulateoestrogen-receptor function in activating targetgene promoters as a functional assay, the authorsshowed that none of the RIZ1 mutations discussed were active.

RIZ1 therefore represents the first in a newclass of tumour suppressors — the identifica-tion of many more will surely follow. Discoveryof RIZ1’s substrates should elucidate how thisclass acts.

Emma Greenwood

References and linksORIGINAL RESEARCH PAPER Steele-Perkins, G. et al. Tumorformation and inactivation of RIZ1, an Rb-binding member of anuclear protein–methyltransferase superfamily. Genes Dev. 15,2250–2262 (2001) WEB SITEShi Huang’s lab: www.burnham.org/reports/6.Huang.97.html

A new class?

T U M O U R S U P P R E S S O R S

The molecular determinants of metastasisare one of the great unsolved mysteries ofcancer research. But expression analysisusing microarrays is exposing some of thedaemons that lurk within this black box.Tobey MacDonald and colleagues,reporting in the October issue of NatureGenetics, have used microarrays to identifyconsistent changes in gene expression inmetastatic medulloblastoma — a braincancer that most commonly affectschildren. The genes identified leave aremarkably consistent trail that might leaddown some new therapeutic avenues.

The authors used some statistical methodsthat are fast becoming the gold standard forthe molecular characterization of cancer.Having measured the expression levels of over1900 transcripts for 10 metastatic and 13 non-metastatic medulloblastoma samples usingcommercially available oligonucleotidemicroarrays, they identified 85 genes — thepredictor set — that differed significantlybetween metastatic and non-metastatic

tumours. To determine the ability of thesegenes to categorize a tumour as metastatic ornon-metastatic, the expression profile for eachtumour was compared against those of theother 22 — a technique known as the ‘leaveone out’ approach. The predictor set got itright for 90% of the non-metastatic tumours,but only for 50% of the metastatic ones,leading the authors to speculate that theremight be subsets with different expressionprofiles within the metastatic group.Nevertheless, it correctly predicted theoutcomes for four of another five blindedtumour samples, but categorized only one ofthree metastatic cell lines — the Daoy cell line— as metastatic.

But more exciting than the predictor’s mixedsuccesses was the finding that many of thegenes that are overexpressed in the metastaticgroup are in the same growth-factorsignalling pathway: the platelet-derivedgrowth factor receptor PDGFRA was over-expressed in 85% of metastatic, but no non-metastatic tumours. Migration assaysrevealed that PDGFA (PDGFRA’s ligand)stimulated movement of Daoy cells onfibronectin matrices, and this was blocked byneutralizing antibodies to PDGFRA.Activation of PDGFRA increased thephosphorylation of the mitogen-activatedprotein kinases MAPK1 and MAPK3, and

their upstream kinases, MAPKK1 andMAPKK2. The antibodies blocked thisincrease in MAPK signalling, andpretreatment with a specific inhibitor of theseMAPKKs, U0126, blocked PDGFA-mediatedmigration and MAPK activation in these cells.

Children with medulloblastoma are givenradiotherapy to prevent or treat metastasis,but this has serious neurologicalconsequences. Identifying individuals at lowrisk of metastasis would allow clinicians totailor this aggressive therapy to children forwhom the benefits would outweigh the risks.The prospect of treating metastatic medullo-blatoma with tyrosine kinase inhibitors suchas STI-571 (Gleevec), which inhibitsPDGFRA’s kinase activity as well as ABL’s,is another potential outcome of this work.Further analysis of gene-expression patternsin metastatic medulloblastoma will doubtlessimprove the predictor set, perhaps yieldingfurther promising therapeutic targets.

Cath Brooksbank

References and linksORIGINAL RESEARCH PAPER MacDonald, T. J. et al.Nature Genet. 29, 143–152 (2001) FURTHER READING Quackenbush, J. Computationalanalysis of microarray data. Nature Rev. Genet. 2, 418–427(2001) WEB SITEChildren’s National Medical Center Microarray Center:http://microarray.cnmcresearch.org/microarray.html

Peering into ablack box

M E TA S TA S I S

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