nrclinonc.2014.238Artigo

8/9/2019 nrclinonc.2014.238Artigo

1/15NATURE REVIEWS|CLINICAL ONCOLOGY ADVANCE ONLINE PUBLICATION | 1

Edwin L. SteeleLaboratory forTumour Biology,Massachusetts GeneralHospital and HarvardMedical School,100 Blossom Street,Cox 7, Boston,MA 02114, USA (K.N.,R.K.J.).

Correspondence to: [email protected]

Using tumour phylogenetics to identify

the roots of metastasis in humansKamila Naxerova and Rakesh K. Jain

Abstract| In cancer, much uncertainty remains regarding the origins of metastatic disease. Models of

metastatic progression offer competing views on when dissemination occurs (at an early or late stage

of tumour development), whether metastases at different sites arise independently and directly from the

primary tumour or give rise to each other, and whether dynamic cell exchange occurs between synchronously

growing lesions. Although it is probable that many routes can lead to the establishment of systemic disease,

clinical observations suggest that distinct modes of metastasis might prevail in different tumour types.

Gaining a more-comprehensive understanding of the evolutionary processes that underlie metastasis is not

only relevant from a basic biological perspective, but also has profound clinical implications. The tree of life

of metastatic cancer contains answers to many outstanding questions about the development of systemicdisease, but has only been reconstructed in a limited number of patients. Here we review available data on the

phylogenetic relationships between primary solid tumours and their metastases, and examine to what degree

they support different models of metastatic progression. We provide a description of experimental methods for

lineage tracing in human cancer, ranging from broad DNA-sequencing approaches to more-targeted techniques,

and discuss their respective benefits and caveats. Finally, we propose future research questions in the area of

cancer phylogenetics.

Naxerova, K. & Jain, R. K. Nat. Rev. Clin. Oncol. advance online publication 20 January 2015; doi:10.1038/nrclinonc.2014.238

Introduction

Gaining a deeper knowledge of heterogeneity in humancancers is becoming increasingly important for bothbasic and translational cancer research. This develop-

ment is partly fueled by an urgent need to understandand prevent or circumvent therapy resistance,1andpartly due to the realization that intratumour hetero-geneity offers a rare window into the complex evolu-tionary history of a cancer.2,3The term intratumourheterogeneity is itself subject to heterogeneity: it candescribe diversity among cells intermingling in onelocalized area; refer to differences between spatiallyseparated tumour regions; or denote variation amongmultiple noncontiguous tumours in metastatic disease,although in this setting it would perhaps be more accu-rate to speak of intracancer heterogeneity. Intratumourheterogeneity occurs on all levels of observation, many

of them nongenetic (such as phenotypic and epigeneticvariation);4nevertheless, from the point of view of aclinician considering prescribing molecularly targetedtherapies, genetic divergence between primary tumoursand metastasesthe focus of this Reviewis arguablyone of the most-relevant forms. In current practice, treat-ment strategies aimed at the eradication of metastasisare typically guided by molecular analysis of small cellpopulations from the primary tumour. However, we arebecoming increasingly aware that the genetic markers

that form the basis for allocation of many targeted treat-ments show considerable discordance both within andbetween tumours.57Additional biopsy of metastases is,

therefore, becoming advocated,8but sampling of second-ary tumours is often impractical due to surgical inaccess-ibility. The genetic traits of micrometastases are evenmore difficult to assess. Superimposed on this geneticheterogeneity of cancer cells is the heterogeneity in thetumour microenvironment, which can drive tumour pro-gression and promote treatment resistance.9Owing tothese challenges, gaining a more-general understandingof how diversity arises within the primary tumour andhow the bottleneck of metastatic dissemination modu-lates tumour heterogeneity is becoming increasinglyexpedient. Importantly, a cancers genetic landscape alsoencodes a record of its evolutionary trajectory; decod-

ing this record has the potential to reveal fundamentalprinciples of tumour biology.

The emergence of metastasis has been surroundedby mystery for a long time. The humoralist school ofthought regarded cancer as an inherently systemicdisease caused by abnormal accumulation of blackbile, one of the four humours believed to constitutethe human body.10Consequently, metastases were notconsidered a product of the primary tumour, but ratheranother independent symptom of the same underlyingpathology. For a prolonged period during his scien-tific career, even Rudolf Virchow, the father of cellularpathology, firmly believed the paradigm that primary

Competing interests

The authors declare no competing interests.

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metastasis-enabling mutations is a stochastic process,the likelihood of such mutations arising increaseswith the number of cell divisions that a tumour under-goes. Therefore, metastasis is assumed to occur shortlybefore a tumour becomes clinically detectable (after ithas undergone many cell divisions to form the detect-able tumour mass). The linear progression model pre-dicts a small evolutionary distance between primaryand secondary neoplasms, and therefore suggests thatthe primary tumour is a good surrogate for the molecularproperties of metastases.

Metastatic cascades

Loosely associated with the linear progression model, byvirtue of placing the development of metastasis in the lateststages of carcinogenesis,11is the concept that metastases,perhaps particularly those in central organs with extensivevascularization and high blood flow, such as the lung andliver, give rise to other metastases in a cascading manner,21forming showers of metastases (Figure 1a).22To accountfor the development of widespread metastases in a rela-tively short amount of timein many cases, metastaticcancer emerges 23 years after diagnosis of the primary

Primarytumour

Livermetastasis

Lungmetastasis

a c

d

b

Primarytumour

Lungmetastasis

Livermetastasis

Primarytumour

Lungmetastasis

Livermetastasis

Primarytumour

Tumour-mass

dormancy

Tumour-cell

dormancy

Figure 1|Overview of human metastasis models. a| The linear progression and metastatic cascade model.A transformedcell divides to form an early stage primary tumour (lower panel, red cells). As the tumour proliferates (dotted lines indicate celldivisions), it undergoes clonal evolution, eventually giving rise to a fully malignant clone that has the ability to metastasize(yellow cells). Other clones might or might not coexist with the metastatic clone in the primary tumour (not shown in thisdepiction that focuses on the genetic similarity between tumour lesions as opposed to the intratumour heterogeneity withinindividual lesions). As the metastatic clone is fully malignant, it can colonize other organs efficiently (yellow cells: lungmetastasis) and spread further (yellow cells: liver metastasis) in a cascade, without having to acquire major new alterations.The anatomical cartoon (upper panel) depictsan advanced invasive breast carcinoma initiating a metastatic cascade shortlybefore clinical detection. All curved arrows indicate dissemination. b | The parallel progression model. In its early growthstages, the primary tumour (lower panel, red cells) begins to seed metastases in other organs (brown and purple panels).These cells proliferate in their respective ectopic microenvironments (dotted lines) in parallel with the primary tumour,acquiring distinct sets of mutations (green and orange cells). The anatomical cartoon shows various metastases that areseeded directly and independently from an early stage cancer. c |Tumour self-seeding. Tumour cells return from themetastatic site to the primary tumour. Self-seeding is compatible with both parallel (green cells from a liver metastasis) andlinear progression (yellow cells returning from a lung metastasis). However, the likelihood of self-seeding could potentially behigher in the case of parallel progression because metastasis and primary tumour exist synchronously for longer periods oftime. The primary tumour could also continually emit cells to a metastasis that was in fact seeded at early stages oftumorigenesis, masking evidence of parallel progression (yellow cells from the primary tumour migrating to the livermetastasis). d |Dormancy. After dissemination (curved arrows) from the primary tumour to distant organs (brown and purplepanels), single tumour cells enter a state of dormancy (tumour-cell dormancy), or persist as small microscopic lesions inwhich cell birth and cell death (red cross) are balanced (tumour-mass dormancy). In this depiction, tumour-cell disseminationoccurs early, but dormancy might also be possible in cells that leave the primary tumour at late stages of disease.

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tumour, and according to linear progression, dissemina-tion occurs shortly before clinical detectionthe cascademodel assumes a very high growth rate of metastases.11Aggressive tumours formed through rapid clonal expan-sions, perhaps due to infrequent cell death by apoptosis ornecrosis, would be expected to harbour comparatively lowlevels of diversity (unless the mutation rate in the tumourcells is increased). Consequently, the cascade model pre-dicts metastases that are relatively genetically uniformand that are more-closely related to each other than tothe primary tumour.

The invasion of the lymphatic system is a potentiallyimportant step in the metastatic cascade. Autopsy studiesshow that regional and distant lymph nodes are by far themost-common sites of metastasis. In one large autopsystudy in patients with various cancers,23at the time ofdeath, lymphatic metastases were twofold more frequentthan lesions in the next-most-common site of metastasis:the liver. Indeed, for many cancer types, the presenceof cancer cells in regional lymph nodes is a well-knownnegative prognostic indicator. Historically, lymph node

metastases were, therefore, assumed to be precursors ofdistant lesions. This belief motivated aggressive surgicalinterventions to eradicate locoregional disease, such asthe radical mastectomy and axillary lymph node dissec-tion approach pioneered in breast cancer by Halsted atthe end of the 19thcentury.24,25However, the benefit ofaxillary lymph node dissection has been questioned,26,27

and it has been argued that lymphatic lesions are unlikelyto give rise to distant metastases.28

Parallel progression

Diametrically opposed to linear progression, althoughnot strictly mutually exclusive, is the parallel progression

model (Figure 1b). This model posits that metastasisoccurs early in cancer development, potentially already ator before the carcinoma in situ stage,29and that primaryand secondary tumours evolve independently.11Parallelprogression is closely related to the alternative hypoth-esis of tumour progression (proposed by Bernard Fisher25)that regards cancer as a systemic disease from the outset.The parallel progression model assumes that cell dissemi-nation and ectopic survival do not necessarily require acomplex repertoire of mutations, and can be accomplishedby cancer cells with few genetic abnormalities. Accordingto this model, the somatic evolution of these early dissemi-nated tumour cells (DTCs) occurs predominantly at the

distant organ sites and involves extensive adaption to localmicroenvironments. Therefore, substantial genetic dis-parity between the primary tumour and its metastases, aswell as between metastases in different anatomic locations,is expected. This paradigm is in contrast to the metastaticcascade model, which postulates that metastases arisefrom each other during a rapidly fatal period of clonalexpansion that would leave less time for diversificationthan slow parallel evolution of metastases, at least underthe assumption of comparable mutation rates. Under theparallel progression model, molecular profiling of primarytumours is considered inappropriate for selecting effectivetherapeutics against (micro)metastatic disease.

Tumour self-seeding

Both the linear and the parallel progression modelsregard metastasis as a unidirectional process that beginswithin the primary neoplasm and terminates at a distantsite(s). Tumour self-seeding (Figure 1c) is a recentlyarticulated hypothesis stating that bidirectional, dynamiccell exchange exists between synchronous lesions.30Theprimary tumour is proposed to continually shed cancercells into the bloodstream, some of which pass throughthe lung capillary network to enter the arterial circula-tion, with a highly selected subset of these circulatingtumour cells (CTCs) re-entering the primary tumour todrive local progression. Cells that are shed or extrava-sate from proliferating metastases could similarly returnto the primary tumour, compounding intratumourheterogeneity. At present, we do not know whethera clinically significant degree of tumour self-seedingoccurs in humans, but if it does, this process wouldobscure evidence of independent tumour evolution atdifferent sites.

DormancyDormancy is a loosely defined term that is used todescribe multiple distinct forms of tumour growth arrest(Figure 1d).31In the clinical setting, dormancy is invokedto explain ultra-late disease recurrence after 10 years ofdisease-free survival.12From a cell biology perspective,dormancy can either refer to a senescence-like state ofsingle DTCs after they were entrapped in foreign andpotentially hostile tissue microenvironments (that is,tumour-cell dormancy) or to the indolent behaviour ofsubclinical cancers that exhibit no net growth (tumour-mass dormancy). Dormancy is an important factorto consider when interpreting tumour phylogenies

because the mutations that are used for reconstructionof evolutionary trees typically only occur in proliferat-ing cells. A dormant tumour cell that does not divide,therefore, effectively stops its evolutionary clock. Thus,whether a metastatic lesion arose after a prolongedlatency period because it disseminated late in cancer pro-gression or because it underwent a period of dormancyat the distant site might be difficult to judge.

Biological variability

Which of these models best describes metastasis in dif-ferent patient populations is currently unknown, and abetter understanding of how systemic disease develops is

urgently needed. Personalizing treatment for metastaticdisease according to the molecular profile of the primarytumour could be adequate for cancers that follow thelinear progression model and metastasize in cascades;however, in the case of parallel progression, repeat biop-sies or analysis of CTCs or circulating tumour DNA(ctDNA) might be required to obtain up-to-date infor-mation on the genetic profile of target cells. Improvedunderstanding of modes of metastatic evolution will alsoanswer fundamental biological questions, which couldhave important implications for diagnosis, prognosis andtherapy; for example, whether the ability to metastasizeis present in cancer cells at early stages of tumorigenesis

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in a locus-speci fic manner (that is, without obtaininga full exome sequence).32The results indicated that avast majority (97%) of mutations were present in boththe metastasis and the primary tumour.32The investi-gators created a mathematical model to translate themutation data into chronological time and estimatedthat, whereas the development of the primary tumourtook approximately 25 years, metastasis occurred only3 years before diagnosis.32The findings were thusinterpreted by the investigators as consistent with the

linear progression model.32More recently, high muta-tion concordance (79%) in a set of cancer-associatedgenes in mCRC lesions was reported by Brannon andcolleagues.50In addition, this study showed that manyseemingly divergent mutations were actually present inboth the primary tumour and metastasis, but restrictedto subclones that only existed in spatially definedregions of either lesion;50these subclonal mutations werenot included in the previously stated concordance rate.These results further support a linear progression modelfor colorectal cancer.

Another index lesion sequencing study of s evenpatients with pancreatic carcinoma initially found genetic

divergence between primary tumours and metastases.33On average, 36% of mutations present in the metastaticindex lesion could not be detected in the primary tumouror other metastases.33This initial finding suggested thatmetastasis in pancreatic cancer must occur earlier thanin colorectal cancer. However, similarly to the study byBrannon and co-workers,50further analysis of spatiallydistinct regions of the primary tumour in two patientsrevealed large areas that were closely related to themetastases, demonstrating that the relevant clone wasmissed in the first round of testing.33The authors con-cluded that, as in colorectal cancer, metastasis occurslate in pancreatic cancer progression.33This study also

showed that different metastatic lesions correspondedto different subclones present in the primary tumour,33indicating that multiple genetically distinct cell popula-tions metastasized independently of each other. A studythat reconstructed pancreatic cancer phylogenies fromchromosomal rearrangements also found evidence ofindependent dissemination events in some patients;51however, in other patients studied, different metastasesrecovered from the same organ were highly similar toeach other, supporting cascading progression.51

When interpreting these results, it is important toremember that the index lesion sequencing approach thatwas common early in the next-generation sequencingera neglects the evolutionary trajectory of the primarycancer. All mutations that arise in the primary tumourafter departure of the metastatic clone remain obscureif variant discovery does not encompass both tumours(in the index lesion approach, only the metastasis isused for variant discovery). Owing to this limitation,a scenario in which the metastatic clone disseminatesearly, enters a period of dormancy (freezing the muta-tional profile of the primary tumour in time), and finallyundergoes a rapid clonal expansion without acquiring

many new alterations, could also explain genetic con-cordance observed in index-lesion sequencing studiesthat did not assess mutations specific to the primarytumour; all mutations that the primary tumour acquiredwhile the metastasis was dormant would remain invis-ible, therefore, late dissemination could erroneouslybe concluded.

In a study of metastatic prostate cancer, Liu et al.52compared the copy number profiles of multiple metasta-ses in 24 autopsy cases. Metastases and primary tumoursshared most copy-number alterations in a majority ofpatients, leading the researchers to conclude a mono-clonal origin of metastatic prostate cancer.52The primary

Table 1|Genome-wide comparisons of solid primary tumours and their metastases

Study Primary cancer Number

of

patients

Time between resection

of primary tumour

and metastasis

Genetic relationship

between primary tumour

and metastases

Evidence

of possible

metastatic

cascade*

Jones et al. (2008)32 Colon 10 Ranged from synchronousto 20 months

High similarity NA

Liu et al. (2009)52 Prostate 24 Synchronous High similarity; primary only

available in 5 cases

Yes

Shah et al. (2009)57 Breast 1 9 years Divergent NA

Campbellet al.(2010)51

Pancreas 13 Synchronous High similarity in mostpatients; primary tumour notavailable in some cases

Yes, insomepatients

Ding et al. (2010)55 Breast 1 8 months High similarity NA

Yachida et al. (2010)33 Pancreas 7 Synchronous Similarity between metastasesand localized area of primary

No

Navin et al. (2011)49 Breast 1 Not specified High similarity NA

Gerlingeret al. (2012)5 Kidney 2 Synchronous Divergent Yes

Wu et al. (2012)58 Medulloblastoma 7 Not specified Divergent Yes

Haffner et al. (2013)54 Prostate 1 17 years Similarity between metastases

and localized area of primary

Yes

*That is, metastasis giving rise to metastasis; NA for studies that did not assess multiple metastases. Abbreviation: NA, not applicable.

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tumour was available for comparison in only fivepatients, but in these patients, no significant divergencewas observed, a finding that would seem to support thelinear progression model. Furthermore, Liu et al.52didnot report any recurrent genetic adaptations of metasta-ses to ectopic microenvironments in different organs,a key feature of the parallel progression model. Thisfinding could conceivably be a consequence of the smallsample numbers. However, some subclonal alterationsdid exist in metastases.52Subsequent re-analysis of thedata confirmed this finding and reported several otherinteresting observations; for example, that metastasesexcised from the liver were more similar to each otherthan to other metastases, possibly indicating intrahepaticcascading metastasis.53

A more-recent analysis of metastatic prostate cancer bywhole-genome sequencing also observed that metasta-ses in different anatomical locations were highly similarto each other at the time of death,54indicating cascad-ing progression. However, in apparent contrast to thefindings of Liu and colleagues,52the bulk of the primary

tumour did not share the hallmark mutations of themetastases.54These alterations could only be identified ina single small patch of low-grade tumour tissue, suggest-ing that this isolated area gave rise to the metastatic clonethat led to the patients death 17 years after resection ofthe primary tumour. A full genome sequence of this areaof the primary tumour could not be obtained, as only alimited number of cells could be microdissected fromthe 17-year-old paraffin block. Therefore, it remainedunclear whether the metastatic precursor area con-tained a substantial number of mutations that werenot present in the metastases (indicating some degreeof parallel progression), or whether the metastasis had

inherited all mutations present in the primary tumour(indicating linear progression). Interestingly, a lymph-node metastasis that was resected along with the primarytumour also did not contain the mutations present in themetastatic clone.

That tumour cells can thrive in dramatically differ-ent microenvironments without undergoing extensivegenetic adaptation was demonstrated further by a deep-sequencing analysis of a triple-negative breast carci-noma (TNBC), an associated cerebellar metastasis anda pretreatment biopsy that was propagated as a murinexenograft.5548 out of 50 detected somatic point muta-tions were present in all three tumours.55Interestingly,

mutant allele frequencies were broadly distributed in theprimary tumour (ranging from



diverged early in the development of the tumour; sec-ondly, a discrete region of the primary tumour harboureda precursor of the metastatic clone that contained somemutations that were otherwise metastasis-specific (thatis, found in the metastases and the precursor area ofthe primary tumour, but not other parts of the primarytumour); and finally, the pretreatment biopsies of theprimary tumour and the metastasis clustered with theirpost-treatment counterparts, suggesting that treatmentwith everolimus had not substantially affected clonalcompositions (although the effectiveness of treatmentwas not reported, and could have influenced this obser-vation).5In samples from a second patient, Gerlingeret al.5found that a synchronous metastasis also formeda distinct phylogenetic branch that separated from theprimary tumour at an early stage of cancer development.These results are consistent with parallel progressionof the primary tumours and metastases. As in pros-tate cancer, individual metastases were similar to eachother, favouring a cascade scenario. Similar findingsdivergence between the primary tumour and associated

metastases, but similarity among metastaseshave beenobtained in paediatric medulloblastoma.58

In summary, a majority of the genome-wide compari-sons of paired primary tumours and metastases con-ducted to date seem to support the linear progressionmodel of metastasis, with several notable exceptions. Theextent to which these findings are generalizable remainsto be determined. The clinical course of metastatic cancercan be extremely variable, and how advanced a cancer isat the point of analysis and how aggressively it developedprobably considerably influence its genetic landscape. Forexample, as far as can be inferred from the clinical infor-mation provided, many of the studies that found genetic

concordance between primary tumours and metastasesinvolved patients with metastases that were diagnosedsynchronously or within a short period of time afterprimary tumour detection, underwent extensive treat-ment and rapidly succumbed to aggressive disease.33,52,55Samples for comparison are often easier to obtain fromsuch patients than from patients who develop metachro-nous metastases, but might not accurately represent thetrajectory of more-indolent cancers.

Smaller-scale genetics studies

Although high-resolution genome-wide or whole-exomecomparisons of primary tumours and metastases remain

rare, hundreds of such studies have been conductedusing more-restricted panels of markers or metaphaseCGH. Patient numbers in these studies are typicallylarger than in genome-wide analyses, potentially improv-ing understanding of the generalizability of the findings,and cases supporting linear and parallel progression areusually found in varying proportions in the same study.Thought-provoking examples are: deep sequencing of acancer mini-genome in primary colorectal cancers andmatched metachronous liver metastases that revealedvast differences in the number of concordant mutationsamong patients;59a CGH analysis of primary breastcarcinomas and matched metachronous metastases

demonstrating close clonal relationships in 69%, andalmost completely unrelated genomic alterations in31% of patients;60and, reports of varying frequencies ofdiscordant mutations in therapeutically or prognosti-cally important genes in lung adenocarcinoma,61mela-noma,62and colorectal63and breast cancers.8Stoeckleinand Klein64expertly reviewed many more examples.These studies suggest that the mode of metastasis variesbetween individual patients.

Interpreting comparative genetics data

The diverse results presented above illustrate that wehave yet to arrive at a definitive and coherent under-standing of metastasis in humans. Developing more-accurate models of metastatic progression will not onlyrequire more-comparative genetics analyses in the meta-static setting, but also resolution of several issues thatcomplicate interpretation of the data from these studies.

First, meaningful comparison of cancers arising indifferent tissues might not always be straightforward, asthe number of mutations common to all cells within a

tumour could vary widely depending on the mutationalhistory of the tumour founder cell (Figure 2). The muta-tional burden of any normal cell increases continually asit divides and is exposed to environmental stresses overa patients lifetime. Current estimates are that 50% 65ormore66of the mutations found in a cancer represent thefossil record of the cell-division history of the tumourfounder cell; therefore, depending on how frequentlythe founder cell divided before it underwent transfor-mation and the extent of other stresses it was exposed to,the genetic alterations that accumulated during tumourgrowth could represent different fractions of the total.Even if two tumours and their metastases evolved in the

exact same way, the percentage of mutations that are dis-cordant between the primary tumour and its metastasiswill be smaller for the tumour that arose from a foundercell with a higher baseline mutational burden (Figure 2).These effects should be taken into consideration whencomparing results from different studies, particularlywhen the tissues under consideration have different pro-liferative histories. Gaining a greater understanding ofmutation prevalence in normal cells located in differenthuman tissues would be helpful in this regard.

Second, determining whether tumour self-seedinghas a role in human cancer progression will be impor-tant, because a substantial exchange of cells between

synchronously growing lesions would make geneticreconstruction of the evolutionary history a tumour verychallenging. Tumour self-seeding seems to be a plausibleexplanation for some phenomena observed in genome-wide comparisons. For example, in cases in which anisolated patch in the primary tumour corresponds to adistant lesion, but is distinct from the dominant clonein the primary tumour, retrograde metastasis of cellsderived from a disseminated lesion formed early in theevolution of the disease (with subsequent parallel pro-gression) might be a more parsimonious explanationthan late metastasis of this specific subclone (Figure 1c).Moreover, gene-expression profiles of bulk tumour

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tissue predict the risk of metastasis,67and this findingis difficult to reconcile with metastatic properties beingconfined to a very small portion of cells in the primary

tumour. The tumour-self seeding model predicts thatreturning seeds are more likely to inhabit the surfaceof the primary tumour,68with the surface defined asthe boundary between the tumour mass and the stroma.In addition, blood-borne cells returning to the tumourmight be depleted in areas with collapsed vessels.69Inthe future, detailed spatially stratified analysis couldshow whether this model holds true in human tumours.Alternatively, the existence of self-seeding could becorroborated by demonstrating that a metastasis con-tains definitive precursors of a clone that is also found inthe primary tumour, with an absence of such precursorsin the primary tumour itself (Figure 3). The possibility

that the precursor clones were initially present in theprimary tumour, but underwent elimination by purify-ing selection cannot be excluded; however, this type ofanalysis could at least provide tentative support for self-seeding. If a relevant degree of self-seeding does indeedoccur, it will be difficult to demonstrate early metastasisand, therefore, parallel progression, or to discover geneticvariants that are required for early adaptation to specificmicroenvironments in late-stage disease.

Other challenges limit our ability to definitively proveparallel progression. Although close genetic ties betweena primary tumour and a metastasis (corrected for themutational burden of the founder cell and in the absenceof self-seeding) provide credible evidence of late dissemi-nation, genetic divergence does not necessarily implyearly metastasis (Figure 4). Because we cannot sampleevery single part of a primary tumourin the clinicalsetting, analysing all of the tumour is de factoimpos-sible because some parts are required for diagnosticpurposesone cannot exclude the possibility that thearea harbouring the pre-metastatic clone was missed,

as shown in previous studies.33,50Similarly, if a pre-metastatic clone is intermingled with other subclones inthe sampled area, but contributes only a small fractionto the total number of tumour cells, it could escape thedetection limit of the assay.

Studying metastatic lineage

A phylogenetic marker suitable for somatic lineagetracing should ideally have several important properties:selective neutrality; a high mutation rate; and acquisi-tion of mutations that is coupled to cell division, suchthat the total mutational burden of a cell is proportionalto the number of cell divisions since the zygote. The

following section will outline experimental approachesfor somatic lineage reconstruction that meet some or al lof these demands.

Histopathology

We begin with the inspection of a cancers histopatho-logy, whichper se is not a phylogenetic method, butde factoconstitutes the oldest, and remains the most-widely used, method for lineage determination. Evenin molecular-biology-empowered clinical practice,pathologists use morphological examination to deter-mine whether a lesion is a metastasis or a new primarytumour, for example, in multifocal lung or breast cancer

cases. Prognosis and treatment can vary widely basedon the outcome of such assessments. The advantage ofthis lineage tracing by eye is mainly its convenience.However, morphological comparison might not alwaysreliably determine common descent; owing to pheno-typic convergence, comparative approaches becomemore reliable as they move from phenotype towardgenotype. For instance, in a pathological evaluation oflung squamous-cell carcinoma associated with headand neck squamous-cell carcinoma, 86% of cases werediagnosed as metastases by histopathological evaluation,whereas a molecular assay based on loss of heterozygosity(LOH) indicated that, in fact, only 43% of lung tumours

Primary tumourMetastasis

a b5

100

3 3

9

6

64% divergent(3+6 out of 14total mutations)

3 3

9

6

8% divergent(3+6 out of 109total mutations)

Figure 2|The mutational burden of the tumour founder cell might affectinterpretation of data from comparative genetics studies. a | In the example of afounder cell with a low mutational burden, the tumour arises from a cell that isdistinguished from the zygote (grey cell) by five mutations (cell divisions are impliedby dotted lines with the number of mutation acquired in the process givenalongside). The tumour follows the parallel progression route of metastasis andmetastasizes at an early stage of disease (curved arrow). When a sample from theprimary tumour (yellow cells) is analysed, 11 mutations are identified withreference to the germline (five mutations acquired before transformation plus sixmutations acquired during primary tumour development). Three different mutationsthat are not found in the primary tumour are detected in the metastasis (greencells). Of a total of 14 mutations found in the tumours (five shared, three

metastasis-specific, six primary-tumour-specific), nine (64%) are different betweenprimary tumour and metastasis, indicating a high degree of divergence andtherefore parallel evolution. b | If the founder cell has a high mutational burden,the degree of divergence might differ, suggesting a different metastasis model.For example, if the same tumour as in panel a arose from a founder cell that hasacquired 100 mutations since the zygote, a total of 109 mutations would bedetected in this cancer (100 shared, three metastasis-specific, and six primary-tumour-specific); therefore, only 8% of mutations differ between the primary tumourand the metastasis, and linear progression could be erroneously concluded basedon the low degree of divergence.

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were related to the primary head and neck tumour, withthe remainder representing independent transformations

(second primary cancers).70Furthermore, some tumourscan undergo profound histological changes in responseto treatment.71Therefore, visual inspection of tumourmorphology is not a preferred method for lineagetracing, lacking both reliability and resolution (Table 2).

Somatic copy-number alterations

A rich literature documents the use of somatic copy-number alterations (SCNAs) to study clonal relation-ships in cancer. SCNAs can be detected relatively easilyand occur in almost all cancer types (Table 2). However,whether they represent good lineage markers is debat-able because many SCNAs probably have selective

effects.72Convergent evolutionthat is, the indepen-dent occurrence of similar alteration patterns in twounrelated cellscannot be excluded, unless breakpointsare mapped in fine detail. For example, amplificationsof chromosome 7 and deletions of chromosome 10 arepresent in >80% of primary glioblastomas,73despite thefact that these tumours in different patients are obviouslynot related by descent. Some genomic rearrangementscan be induced by exogenous stimuli, such as the sharpincrease of gene fusions between TMPRSS2and ERGupon dihydrotestosterone exposure in prostate cancercells.74Some caution in the use of SCNAs for tumourphylogenetic studies is, therefore, advocated.

Single-nucleotide variants

The problem of selective forces potentially causing arte-facts in lineage reconstruction is relevant when consid-ering not only chromosomal alterations, but also exonicsingle-nucleotide variants (SNVs). The exome is the 1% ofthe genome that is under the most-intensive evolutionarypressure and is, therefore, arguably one of the least suit-able targets for lineage analysis; analogous emergence (ordisappearance) of SNVs that provide a selective advantage(or disappearance of those that are disadvantageous), couldeasily be misinterpreted as homology. The impact this issuehas on lineage analysis probably varies depending on thenumber of divergent mutations. If several dozens of SNVsdiffer between a primary tumour and associated metasta-ses, as has been reported in renal-cell carcinoma,5manyof the variants are probably neutral and are more likely toreflect lineage relationships correctly. However, in a hypo-thetical scenario in which only a few mutations (perhapslimited to cancer-related genes) are shared by multiplemetastases, but not by the primary tumour, convergentevolution of early disseminated lesions (parallel progres-

sion) cannot be as easily dismissed. Nevertheless, SNVs arecorrelated with cell division and genome-scale assessmentholds the potential for detailed lineage tracing (Table 2).75

Epigenetic approaches

X-chromosome inactivation

Epigenetic modifications have a long history as lineagemarkers; X-chromosome inactivation, the randomsilencing of one X chromosome in females during earlyembryonic development, has been used extensively to testclonality both within a tumour mass76and between differ-ent lesions.60,77X-chromosome inactivation is a randomand presumably neutral event (Table 2), thus fulfilling the

first criterion of a good lineage marker: in bulk tissue,the ratio between silenced alleles is about 1:1, arguingagainst strong selective effects.78A further advantage isthat silencing is stably heritable. If two cell populations donot share the same pattern of X-chromosome inactiva-tion, it can be concluded that they have not intermixedsince embryogenesis. However, the static nature of thismarker is also its main limitation, because it cannotprovide any information on evolutionary events thatoccurred after the transformation of a tumour foundercell. However, the inactive X chromosome acquires muta-tions at an increased rate,79and therefore might be excep-tionally useful for lineage tracing by providing a reservoir

of presumably selectively neutral somatic variation thatcould be tapped for phylogenetic analysis.

CpG methylation analysis

Methylation status of CpG dinucleotides fulfils most ofthe criteria for a good phylogenetic marker. A majorityof CpG loci are unmethylated in early development andacquire heritable cytosine methylation marks with succes-sive rounds of cell division at a rate that is several ordersof magnitude higher than the somatic nucleotide substi-tution rate.80Neutrality can be assumed when CpGs inpromoters that are not expressed in the tissue of interest(for example, heart-specific loci such as CSXin colonic

Mut A Mut AB Mut ABC

Mut D Mut DE Mut DEF

Figure 3|Using intermediate subclones to search for evidence of tumour self-seeding.In this hypothetical scenario suggesting the existence of self-seeding,a primary tumour contains a subclone characterized by mutations in genomiclocations D and E and F (dark blue cells) that are highly similar to those found ina metastasis; whereas the metastasis contains definite precursors cells that havemutations in D, or D and E (lighter blue cells), the primary tumour contains no suchprecursors. Although loss of the precursors in the primary tumour through clonalselection cannot be excluded, this scenario predominantly indicates self-seeding ofthe primary tumour by a cell(s) from the metastasis. Abbreviation: mut, mutation(s).

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tissue) are examined (Table 2). CpG methylation repre-sents a useful molecular clock,81and has been used exten-sively to study stem cell82,83and tumour8486lineages inhumans. However, an important concern is that cytosine

methylation is a reversible mark and could potentially beaffected by genome-wide methylation changes that occurduring tumorigenesis.87,88A permanent change in DNAsequence would, therefore, be preferable to methylationfor purposes of lineage tracing.

Microsatellite analysis

Microsatellites, short tandem repeats of 14 bp units inDNA, arguably come as close as possible to being optimalsomatic lineage markers. Most are noncoding and showhigh levels of polymorphism.89Mutations typically occurin the form of insertions or deletions of one or multipleunits through slippage of DNA polymerase during DNA

replication,90and are thus tightly coupled to cell division(Table 2). Mutation rates vary depending on the size andlength of the repeat, but can be much higher than theaverage genome-wide mutation rate of approximately 109per base per division;91for example, the mutation rate of atypical (CA)

17dinucleotide repeat in human cells is on the

order of 107100 times higher.92

Microsatellites first entered the spotlight in cancergenetics when frequent somatic length-polymorphismsin these sequences were discovered in familial colo-rectal cancer in patients with hereditary nonpolyposiscolorectal cancer (HNPCC; Lynch syndrome).93,94Thephenomenon, coined microsatellite instability (MSI), was

also observed in 1015% of sporadic colorectal cancersand was associated with an improved prognosis comparedwith cancers lacking MSI.95Subsequently, MSI was foundto be associated with mutations in DNA mismatch repair(MMR) genes.96,97

Microsatellites have been used as molecular clocksof tumour evolution in MSI-positive human cancers.Shibata and colleagues81showed that dinucleotiderepeat-length distributions vary across tumour regionsin patients with HNPCC and suggested that intratumourheterogeneity is related to mitotic age, with older regionsdisplaying more diversity. Interestingly, this group foundthat mitotic ages in MMR-deficient adenomas and carci-nomas were similar.98Microsatellite mutations have alsobeen used to reconstruct the phylogenetic relationshipsbetween single cells in MMR-deficient mice99102andhuman leukaemia cells.103

In 2006, Salipante and Horwitz104introduced a novelmethodology for somatic lineage tracing that relied ona class of particularly mutable guanine mononucleotiderepeats: polyguanine (poly-G) tracts can reach mutation

rates of 106per base per division in human cells,92and thusmutate approximately 10100-times faster than dinucleo-tide repeats and 1000-times faster than nonrepetitive DNAsequences. Analysis of poly-G tracts was subsequentlyused to study various aspects of murine development inMMR-proficient animals.105108Importantly, this techniquewas also shown to be applicable in the human setting whenpre-neoplastic clonal expansions marked by poly-G muta-tions were identified as a prodrome of cancer developmentin patients with ulcerative colitis.109

We have recently demonstrated that poly-G profil-ing can be used for lineage tracing in metastatic coloncancer.110Interrogation of only 20 markers yielded suf-

ficient information to build robust phylogenetic treesthat reflected the evolution of metastasis in individualpatients.110Many of the biological insights gleaned fromthese trees recapitulated observations from exome orwhole-genome sequencing studies: isolated areas oflarge, diversified primary tumours giving rise to wide-spread metastasis, or genetic divergence between lymphnode and distant metastases.110Poly-G tract profiling isa simple and cost-effective PCR-based methodology thatworks well with formalin-fixed and paraffin-embeddedtissues. As such, it could easily be used to study tumourlineage in large numbers of samples that are collected aspart of routine clinical care. Importantly, in contrast to

whole-genome or exome sequencing, poly-G tract analysisdoes not produce large amounts of personal genetic infor-mation that might be associated with ethical concerns.Most institutional guidelines prohibit whole-genomeor even exome sequencing of archival tissues withoutexplicit consent due to such ethical issues; hence, the largenumbers of valuable cancer samples stored in pathologydepartments worldwide cannot be used for these purposesbecause patients would have to be contacted retrospec-tively to gain consent for new analyses. By contrast, poly-Gtract profiling can be performed under most discardedtissue protocols, thereby opening up additional tissueresources for analysis of intratumour heterogeneity.

a cb

Result:Divergence

Primary tumour

Metastasis

Result:Divergence

Result:Divergence

Figure 4|The challenge of proving the parallel progression model of metastasis. Whena primary tumour and its metastasis are compared (black boxes indicate theregion sampled) and divergent alterations are found, multiple explanations couldexist. a | Firstly, true parallel progression: dissemination (curved arrow) occurred

in early stages of tumour development (grey cells), and the primary tumour andmetastasis evolved separately, acquiring distinct genetic alterations (indicated bydifferent cell colours). b | Secondly, omission of the metastatic precursor cell duringsampling: a clone that is the proximate source of the metastasis (blue cells) doesexist in the primary tumour, but it occupies a spatially constrained region and wasmissed during sampling. c | Finally, limited assay sensitivity: the clone that is thesource of the metastasis (blue cells) does exist in the primary tumour, but at such alow frequency that it falls below the detection limit of the assay used for comparison.

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Whole-genome studies

Ultimately, of course, if informed consent has been given,whole-genome sequencing is the most-comprehensivetechnique for somatic lineage tracing in human tissuesamples. Whole-genome analyses of paired primarytumours and metastases remain rare, but the insightsinto clonal evolution that we have already gained fromsequencing the genomes of single tumour samplesprovide a glimpse of future possibilities. Whole-genomesequencing is also the only way to assess comprehensivelyand comparatively how driver and passenger mutationsevolve during cancer development and metastasis. Froma phylogenetic perspective, passenger mutations are ofgreat interest because they constitute a record of cell

division and other mutagenic processes. Driver muta-tions, on the other hand, carry the bulk of functionaland clinical relevance. These two mutation classes mightbehave very differently during disease progression. Forexample, important driver mutations might remain con-cordant (or evolve convergently), while large numbers ofpassenger mutations diverge between primary tumoursand metastases. It is important to point out here thatalthough experimental evidence suggests that replica-tion slippage mutations in normal, MMR-competentcells are correlated with cell division, this is likely notthe case for genome-wide mutation patterns because avariety of influences (carcino gen exposure,111APOBEC

activity,111,112or dr ug-treatment effects,113 amongothers) shape the mutational landscape in a ddition toreplication-induced errors.

Future directions

As our knowledge of genetic heterogeneity in cancerexpands, the question of what concrete clinical advantageswe can expect to gain from an improved understandingof the lineage of metastases remains. Contemporaryclinicians might have a theoretical interest in knowingwhich cancers undergo linear or parallel progression,but they will still want to confirm, by all possible means(grid sampling of primary tumours, additional biopsy

of metastases or liquid biopsy), what actionable genetic

alterations are present in a specific tumour in indivi dualpatients. Indeed, insights from cancer phylogeneticsmight only manifest in the clinic in the mid-to-longterm, but once established are likely to have an importantimpact on patient care. Parallel progression postulatesthat the ability to metastasize is an inherent qualitativetrait that manifests in the earliest stages of tumour pro-gression. This view de-emphasizes the importance ofclonal evolution at the primary site, as mutations thatare acquired later on in tumour development are likelyto be mere instigators of local proliferation with limitedrelevance to overall disease outcome. From the perspec-tive of linear progression, these mutations are the ultimate

cause of death. As we sequence the DNA of more andmore tumour samples in search of mechanistic insightsand novel drug targets, deriving a phylogeneticallyinformed model that provides clear predictions of whichmutationsthose in the trunk of the phylogenetic treeof cancer, or those in the branches or leavesare the rootcause of systemic spread will be important.

Many more clinically relevant questions related totumour lineage await resolution. For example, a system-atic analysis of how the degree of intratumour hetero-geneity changes at different stages of disease progressionwould be instructive; few studies have been conductedin this area. High levels of heterogeneity are connected

with increased malignant potential in the early stages oftumorigenesis. For instance, clonal diversity in Barrettoesophagus, a premalignant condition, is linked with ahigher likelihood of progression to cancer.114The finalstep of systemic disease advancement, metastasis, on theother hand, seems to go hand-in-hand with a decreasein heterogeneity. This pattern makes intuitive sense, asmetastasis represents an evolutionary bottleneck, and thereduced heterogeneity in systemic disease is evident onmultiple levels of observation: narrowing of the mutant-allele frequency distribution in a breast cancer metasta-sis;55monoclonality of metastases at the time of death inprostate cancer (despite the fact that localized prostate

Table 2|Experimental approaches for studying cell lineage in human cancer

Lineage marker Advantages Disadvantages

Histopathology Fast and convenientAssessed as part of routine clinical care

Can be unreliableLimited resolution

Somaticcopy-numberalterations

Present in many cancersSpecific alterations are easy to assess(for example, FISH for HER2amplification)

Selective effects might confound interpretation (due toconvergent evolution) unless precise breakpoints are knownUnknown relationship with cell division

Single-nucleotidevariants Comprehensive and unbiased whenassessed on a genome-wide scaleAt least partially correlated with cell division

Selective effects might confound interpretation if only a limitednumber of mutations in cancer-related genes are considered

X-chromosomeinactivation

Selectively neutralRelatively easy to assess, also in situ

Limited resolutionMight be affected by DNA methylation alterations in cancer

DNA methylation Selectively neutral loci availableCorrelated with cell division

Might be affected by DNA methylation alterations in cancer

Microsatellites Selectively neutral loci availableCorrelated with cell divisionPermanent change

Hypermutable sequences can be difficult to evaluate

Abbreviation: FISH, fluorescence in situ hybridization.

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cancer is often multifocal and highly heterogeneous);52,54increased homogeneity of genomic rearrangements inDTCs derived from patients with overt metastasis versusthose with minimal residual disease;43,46and homo-geneity of metastases in comparison with the primarytumour in mCRC.110Parallel comparison of cancers atdifferent stages of progression with standardized tech-niques will elucidate further whether changes in diversityaccompany progression.

In addition, how the decline in heterogeneity thatpotentially occurs in metastatic disease relates to treat-ment response remains unclear. That genetic hetero-geneity leads to decreased treatment response is a widelyheld belief,115,116which should at least hold true in thecase of driver mutation heterogeneity. According tothe linear progression model, metastases are youngerclonal expansions than primary tumours; hence,metastases should be less diverse and more responsiveto therapy. This hypothesis seems probable for somecancer types. Clinical studies have shown that primarylung carcinomas, for example, are much less likely to

respond to chemotherapy than synchronous metasta-ses (response rates of 11.8% versus 32.8%).117For breastcancer, however, this pattern is reversed (40% versus19.8% response rate for primary tumours comparedwith metastases).117Microenvironmental cues probablyhave an important influence on the differential thera-peutic responses of primary tumours and metastases,118but more-rigorous investigation of how intratumourheterogeneity relates to treatment outcomes will also beimportant in the future.

Another interesting and unanswered question is howspatial diversificationthe presence of distinct clones

in different regions of a tumourrelates to strictly localheterogeneity (intermingling of clones), and how theseforms of diversity associate with clinical behaviour.More-invasive and motile cells might generate more-dispersed forms of genetic heterogeneity (as proliferationof subclones would be accompanied by migration). It hasfurthermore been suggested that locally coexisting clonesmight be able to develop commensal relationships.119One could, therefore, speculate that high levels of localheterogeneity are a hallmark of aggressive disease,whereas regional clonal expansions that stay delineatedfrom each other might signify more-indolent pheno-types. Currently, no data exist to corroborate or refutethis hypothesis, necessitating further studies.

Conclusions

Gaining a more-comprehensive and instructive under-standing of cancer progression includes furthering ourknowledge of when metastases are seeded and theirgenetic relationships to the primary tumour. Differentcancers probably metastasize along different paths and

timelines, and much remains to be learned about thebiology underlying these behaviours. Reconstructingthe tree of life of metastatic cancer in representativepatient populations will be important in this regard.A majority of genome-wide comparisons documentsimilar mutation profiles in primar y tumours andmetastases, but thought-provoking counterexamplesalso exist. We have outlined a variety of experimentaltechniques for the purpose of lineage tracing in humancancer. Owing to these approaches, the answers tomany crucial questions in the field of intratumourheterogeneity are now within our reach.

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