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`
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`

`

`CONTENTS
`
`22 August 2013 I Vol 500 f Issue No 7463
`
`THIS WEEK
`
`NEW’S IN FOCUS
`
`C O M M E N ’1'
`
`EDITORIILS
`3?? RESEARCH
`Subject to question
`Just haw informed should informed
`
`consent actually be?
`
`
`
`lII'IJIILII IIIE‘IIIt
`379 What is to
`be done about
`Russian science?
`Mikhail Gelfand
`
`Russia's Academy of
`Sciences must reform
`but current proposals
`are in flux
`
`RESEARCH HIGHLIGHTS
`SRO SELECTIONS FROM THE
`SCIENTIFIC LITERATURE
`
`Ant vibrations / Chemical yardstick
`for tumours / Hot news / Coping with
`temptation / Ebola potency / Bacterial
`cancer/ Marine bone worm discovery
`
`SEVEN IIIYS
`382 THE NEWS IN BRIEF
`
`
`
`Meet the world's latest carnivore: the
`olinguito / Ecuador gives green light to
`drilling in the Amazon / China launches
`bribery probe / NASA calls time on
`Kepler/ Guidelines issued for naming
`planets
`
`CAREERS
`
`491 RESEARCH IMPACT
`Altmetrics make their mark
`
`Alternatives to citation analysis have a
`role in career assessment — but handle
`them with care
`
`493 TURNING POINT
`Cancer researcherJason Weber has
`propelled the issue ofscience funding
`intothe US Senate
`
`385 WATER MANAGEMENT
`
`Revamped forecasting system seeks
`to stop drinking water from silting up
`336 PIJBLISHING
`Dramatic rise in number of research
`
`papers that are free to view
`38? ENOLUTIONARYCENETICS
`Sheep lock horns over fitness
`
`
`
`388 POLICY
`Romanian science suffers as reversal
`of reforms begins to bite
`389 BIOTECHNOLOGY
`
`Researchers exploit loophole in US
`regulation of transgenic crops
`
`FEII'IIRES
`
`STEH CELLS
`
`Egg
`engmeers
`How to create sperm and egg cells
`in the laboratory PIP-E 332
`
`
`
`
`
`WW;
`
`“WWW
`IIIIII HHIHIHHIHH"Mums!"
`uuuuiuulu “"le
`WNW MRI-IN
`
`llllll
`
`395 MEDICINE
`
`Trial unpredictability yields
`predictable therapy gains
`Benjamin Djulbegovic. Ambuj Kurnai;
`Paul Glasziou. Branko Miladinovic
`& lain Chalmers
`A survey of 50 years of data shows the
`clinical trial system in a good light
`
`BOOKS aunts
`
`
`
`SCIENCE FICTION
`
`New world
`Paul Mchen on the final part of
`Margaret AMood's dystopian trilogy
`PIC! 398
`
`399 BOOKSINBRIEF
`
`CORRESPONDENCE
`dfll] Antibiotics in agriculture / Fukushima
`fallout/ REDD+ and indigenous peopie
`
`OIIITlIlIIY
`40] Michael John Momood (1950-2013)
`Richard G Roberts & Thomas Sutilrna
`
`
`FOTORES
`493 Alone
`Marks Jankow'c
`
`2‘2 AUGUST 2013
`
`IVOL 500 | NATURE ! 3?.3
`
`

`

`ONTENTS
`
`22 August 2013 i Vol 500 i Issue No 7463
`
`RESEARCH
`
`ON THE COVER
`
`Methyl as
`The dynamic methylatio lbiidscape_
`.ofthe human genome. therraxisdeft)J
`. -roorrecpondsto the maximal obeefiie‘fl
`
`
`
`leaf-to-leaf wound signalling
`SA R Mousavi, A Chauvr‘n. F Pascaud,
`S Keiienberger& E E Farmer
`SEE N&v P. 404
`
`'
`
`
`
`
`
`LETTERS
`42? ASTRONOMY An observational
`correlation between stellar brightness
`variations and surface gravity
`FA Bastien, K G Stassun, G Basri
`&J Pepper SEE usv mos
`PHYSICS Measurement of a solid~state
`
`431
`
`triple point at the metal-insulator
`transition in V02
`J H Park et al. SEE nav P. cos
`
`435 OPTICS i'iNO PHOTONICS The role of spin
`in the kinetic control of recombination
`
`in organic photovoltaics
`A Rao et al.
`
`448
`
`CLIMATE SCIENCES Onset of deglacial
`warming in West Antarctica driven
`by local orbital forcing
`WAIS Divide Project Members
`
`445 EYO-DEYO Digit loss in archosaur
`evolution and the interplay between
`selection and constraints
`
`i
`
`
`
`BANGWONG8:MICHAELZILLER
`
`M A G de Bakker et al.
`
`MEI ECOLOGY Emergence of structural and
`dynamical properties of ecological
`mutualistic networks
`8 Suweis, F Simini, J R Banavar
`& A Maritan SEE usv P. 411
`
`453 EVOLUTIONARY GENETICS Genomic
`evidence for ameiotic evolution
`in the bdelloid rotiferAdineta vaga
`J-F Fiot et al.
`
`458
`
`NEUROSCIENCE Oxytocin enhances
`hippocampal spike transmission by
`modulating fast-spiking interneurons
`S F Owen et al.
`
`463 BIOPHYSICS Non—vesicular trafficking
`by a ceramide-l-phosphate transfer
`protein regulates eicosanoids
`D KSr'manshu et al.
`
`46H CELL BIOLOGY The histone H4 lysine 16
`acetyltransferase hMOF regulates the
`outcome of autophagy
`J Fullgrabe et al.
`
`472 BIOTECHNOLOGY Optical control of
`mammalian endogenous transcription
`and epigenetic states
`8 Konermann et al. SEE usv P. 406
`
`4?? EPICENOMICS Charting a dynamic
`DNA methylation landscape of
`the human genome
`MJZr'ller et al.
`
`482 BIOPHYSICS DNA unwinding
`heterogeneity by RecBCD results from
`static molecules able to equilibrate
`B Lin, R J Baskin & S C Kowalczykowslri
`ABC STRUCTURAL BIOLOBY Structural basis
`
`for molecular recognition of
`folic acid by folate receptors
`C Chen et al.
`
`49B CORRICENOUM Replication stress links
`structural and numerical cancer
`chromosomal instability
`RA Burreii et al.
`
`49B RETRACTION Oligosaccharide ligands
`for NKR-Pl protein activate NK cells
`and cytotoxicity
`K Bezouska et al.
`
`49B ERRATUM The importance of feldspar
`for ice nucleation by mineral dust in
`mixed-phase clouds
`J D Atkinson et al.
`
`'22 AUGUST 2013 | VOL 500 | NATURE | 3?5
`
`NEW ONLINE
`403 Papers published this week at
`naturecom
`
`NEWS & VIEWS
`404 PLANT BIOLOGY
`Electric defence
`Herbivory induces an electrical wave
`that triggers jasmonate formation
`Alexander Christmann & Envin Grill
`sEE LETTER P. 422
`
`405 ASTROPHYSICS
`
`Twinkling stars
`Correlation between stellar brightness
`variations and surface gravity
`Jorgen Christensen-Delegaard
`SEE LETTER P. 421r
`
`4GB BIOTECHNOLOGY
`
`Programming genomes with light
`Using optogenetics to regulate
`gene transcription
`Andreas Mo'giich & Peter Hegemann
`SEE LETTER P. an
`
`403 CONDENSED-MATTER PHYSICS
`
`A solid triple point
`A coexistence of two insulating phases
`and a conducting phase in \r‘O2
`Douglas Nateison
`SEE LEITER P. 431
`
`409 METABOLISM
`Sweet enticements to move
`
`4i]
`
`PFK2 activity in endothelial cells
`accelerates glycolysis and angiogenesis
`Cboisoon Jang 8: Zoltan Arany
`ECOLOGY
`Abundant equals nested
`Network nestedness is linked to
`community abundance
`Colin Fontar'ne
`SEE LE‘I'I'ER P. 449
`
`4I2 EYOLUTIONARYBIOLOCY
`
`A gut feeling for isolation
`A malfunctioning host—microbiome
`interface can cause hybrid inviability
`Gregory D D Hurst & Chris DJiggins
`
`ARTICLES
`4I5 CANCER Signatures of mutational
`processes in human cancer
`l. B Alexandrov et al.
`
`422 PLANT SCIENCES GLUTAMATE
`RECEPTOR-LIKE genes mediate
`
`
`
`

`

`nature
`
`
`
`22 August 2013 71701500 1 Issue No. 7463
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`375 I NATURE | VOL 500 | 22 AUGUST 2013
`
`4————#
`
`

`

`This material may be protected by Copyright law (Title 17 U.S. Code)
`
`
`doi:1_0_._2l.038fna_t_u_re124?7
`
`Signatures of mutational processes in
`human cancer
`
`A list of authors and their affiliations appears at the end of the paper
`
`All cancers are caused by somatic mutations; however, understanding of the biological processes generating these
`mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational
`processes that have been Operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than
`20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC
`family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated
`with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of
`cryptic origin. In addition to these genome—wide mutational signatures, hypermutation localized to small genomic
`regions, ‘kataegis’, is found in many cancer types. The results reveal the diversity of mutational processes underlying
`the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.
`
`Somatic mutations found in cancer genomes1 may be the consequence
`of the intrinsic slight infidelity of the DNA replication machinery,
`exogenous or endogenous mutagen exposures, enzymatic modifica-
`tion of DNA, or defective DNA repair. In some cancer types, a sub-
`stantial proportion of somatic mutations are known to be generated
`by exposures, for example, tobacco smoking in lung cancers and
`ultraviolet light in skin cancersz, or by abnormalities of DNA main-
`tenance,
`for example, defective DNA mismatch repair in some
`colorectal cancers’. However, our understanding of the mutational
`processes that cause somatic mutations in most cancer classes is
`remarkably limited.
`Different mutational processes often generate different combinations
`of mutation types, termed ‘signatures’. Until recently, mutational sig-
`natures in human cancer have been explored through a small number
`
`of frequently mutated cancer genes, notably ’l'PS3 (ref. 4). Although
`informative, these studies have limitations. To generate a mutational
`signature, a single mutation from each cancer sample is entered into a
`mutation set aggregated from several cases of a particular cancer type. A
`signature that contributes the large majority of somatic mutations in the
`tumour class is accurately reported. However, if multiple mutational
`processes are operative, a jLunbled composite signature is generated.
`Furthermore, because such studies are based on ‘driver' mutations”,
`signatures ofselection are superimposed on the signatures of mutational
`processes.
`
`Recent advances in sequencing technology have overcome past limi—
`tations of scale'. Thousands of somatic mutations can now be iden~
`
`tified in a single cancer sample, offering the possibility of deciphering
`mutational signatures even when several mutational processes are
`
`
`
`
`
`
`
`(numbermutationspermegabase)
`
`
`
`
`
`Somaticmutationprevalence
`
`Figure l I The prevalence of somatic mutations across human cancer types.
`Every dot represents a sample whereas the red horizontal lines are the median
`numbers ofmutations in the respective cancer types. The vertical axis (log
`scaled} shows the number of mutations per megabase whereas the different
`
`cancer types are ordered on the horizontal axis based on their median numbers
`of somatic mutations. We thank G. Getz and colleagues for the design of this
`figure“. ALL, acute lymphoblastic leukaemia; AML, acute Inyeloid leukaemia;
`CLI., chronic lymphocytic leukaemia.
`
`22 AUGUST 2013 ' VOL 500 l NATURE l 415
`
`

`

`ARTICLE
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`Figure 2 | Validated mutational signatures found in human cancer. Each
`signature is displayed according to the 96 substitution classification defined by
`the substitution class and sequence context immediately 3' and 5’ to the
`mutated base. The probability bars for the six types of substitutions are
`displayed in different colours. The mutation types are on the horizontal axes.
`
`whereas vertical axes depict the percentage of mutations attributed to a specific
`mutation type. All mutational signatures are displayed on the basis of the
`trinucleotide frequency of the human genome. A higher resolution of each
`panel is found respectively in Supplementary Figs 2-23. Asterisk indicates
`mutation type exceeding 20%.
`
`operative. Moreover, because most mutations in cancer genomes are
`‘passengers" they do not bear strong imprints of selection.
`We recently developed an algorithm to extract mutational signa-
`tures from catalogues of somatic mutations and applied it to 21 breast
`cancer whole-genome sequences”. Novel and known signatures were
`revealed, with the contribution of each signature to each cancer sample
`and the timing ofits activity estimated“. Further studies have demon—
`strated that the approach can also be applied, albeit with less power, to
`mutational catalogues from sequences of all coding exons (exo1nes)5.
`Global sequencing initiatives are now yielding catalogues of somatic
`mutations from thousands of cancers“. We have therefore applied this
`method to survey the repertoire of mutational signatures and processes
`operating across the spectrum of human neoplasia.
`
`Mutational catalogues
`We compiled 4,938,362 somatic substitutions and small insertions.Ir
`deletions (indels) from the mutational catalogues of 7,042 primary
`cancers of 30 different classes (507 from whole genome and 6,535 from
`exome sequences) (Supplementary Fig. 1). In all cases, normal DNA
`416 | NATURE | VOL 500 : 22 AUGUST 2013
`
`from the same individuals had been sequenced to establish the somatic
`origin of variants.
`The prevalence of somatic mutations was highly variable between
`and within cancer classes, ranging from about 0.001 per megabase
`(Mb) to more than 400 per Mb (Fig. 1). Certain childhood cancers
`carried fewest mutations whereas cancers related to chronic mutagenic
`exposures such as lung (tobacco smoking) and malignant melanoma
`(exposure to ultraviolet light) exhibited the highest prevalence. This
`variation in mutation prevalence is attributable to differences between
`cancers in the duration of the cellular lineage between the fertilized egg
`and the sequenced cancer cell andior to differences in somatic muta-
`tion rates during the whole or parts of that cellular lineage‘.
`
`The landscape of mutational signatures
`In principle, all classes of mutation (such as substitutions, indels, rear—
`rangements) and any accessory mutation characteristic, for example, the
`sequence context of the mutation or the transcriptional strand on which
`it occurs, can be incorporated into the set of features by which a muta-
`tional signature is defined. In the first instance, we extracted mutational
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`Figure 3 I The presence of mutational signatures across human cancer
`types. Cancer types are ordered alphabetically as columns whereas mutational
`signatures are displayed as rows. ‘Other’ indicates mutational signatures for
`which we were not able to perform validation or for which validation failed
`(Supplementary Figs 24—28}. Prevalence in cancer samples indicates the
`
`percentage ofsamples from our data set 0172042 cancers in which the signature
`contributed significant number of somatic mutations. For most signatures,
`significant number of mutations in a sample is defined as more than 100
`substitutions or more than 25% of all mutations in that sample. MMR,
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`
`signatures using base substitutions and additionally included informa-
`tion on the sequence context of each mutation. Because there are six
`classes of base substitution—~C3A, CbG, C>T, T>A, T> C, T>G (all
`substitutions are referred to by the pyrimidine of the mutated Watson—
`Crick base pairJ—and as we incorporated information on the bases
`immediately 5’ and 3’ to each mutated base, there are 96 possible muta-
`tions in this classification. This 96 substitution classification is particu-
`larly useful for distinguishing mutational signatures that cause the same
`substitutions but in different sequence contexts.
`Applying this approach to the 30 cancer types revealed 21 distinct
`validated mutational signatures (Supplementary Table l and Sup—
`plementary Figs 2—28). These show substantial diversity (Fig. 2 and
`Supplementary Figs 2—23). There are signatures characterized by
`prominence of only one or two of the 96 possible substitution muta-
`tions, indicating remarkable specificity ofmutation type and sequence
`context (signature 10). By contrast, others exhibit a ntore-or—less equal
`representation of all 96 mutations (signature 3). There are signatures
`characterized predominantly by C>T (signatures lAlB, 6, 7, 11, 15,
`19), C>A (4, 8, 18), T>C (5, 12, 16, 21) and TfiG mutations (9, 17),
`with others showing distinctive combinations of mutation classes
`(2, 13, 14).
`Signatures 1A and 18 were observed in 25 out of 30 cancer classes
`(Fig. 3). Both are characterized by prominence of C>T substitutions
`at NprG trinucleotides. Because they are almost mutually exclusive
`among tumour types they probably represent the same underlying
`process, with signature 1B representing less efficient separation from
`other signatures in some cancer types. Signature lAfB is probably
`related to the relatively elevated rate of spontaneous deamination
`of 5—methyl-cytosine which results in C>T transitions and which
`predominantly occurs at NpEpG trinucleotides”. This mutational
`process operates in the germ line, where it has resulted in substantial
`depletion of NprG sequences, and in normal somatic cells'”.
`Signature 2 is characterized primarily by C> T and C>G mutations
`at TpgpN trinucleotides and was found in 16 out of30 cancer types
`
`(Fig. 3). On the basis of similarities in mutation type and sequence
`context we previously proposed that signature 2 is due to over activity
`of members of the APOBEC family of cytidine deaminases, which
`convert cytidine to uracil, coupled to activity of the base excision
`repair and DNA replication machineriesb'“.
`In most cancer classes at least two mutational signatures were
`observed, with a maximum of six in cancers of the liver, uterus and
`stomach. Although these differences may, in part, be attributable to
`differences in the power to extract signatures, it seems likely that some
`cancers have a more complex repertoire of mutational processes than
`others.
`
`Most individual cancer genomes exhibit more than one mutational
`signature and many different combinations ofsignatures were observed
`(Fig. 4 and Supplementary Figs 29—88). The patterns of contribution to
`individual cancer samples vary markedly between signatures. Signature
`lAr'B contributes relativelysimilar numbers ofmutations to most cancer
`cases whereas other signatures contribute overwhelming numbers of
`mutations to some cancer samples but very few to others of the same
`cancer class, for example, signatures 2, 3, 4, 6, 7, 9, 10, ll, 13 (Fig. 4).
`
`Mutational signatures and age of cancer diagnosis
`We examined each cancer type for correlations between age of dia-
`gnosis and the number of mutations attributable to each signature in
`each sample. Signature 1MB exhibited strong positive correlations
`with age in the majority of cancer types of childhood and adulthood
`(Supplementary Table 2). No other mutational signature showed a
`consistent correlation with age of diagnosis.
`The mutations in a cancer genome may be acquired at any stage in
`the cellular lineage from the fertilized egg to the sequenced cancer cell.
`The correlation with age ofdiagnosis is consistent with the hypothesis
`that a substantial proportion of signature lAr‘B mutations in cancer
`genomes have been acquired over the lifetime ofthe cancer patient, at
`a relatively constant rate that is similar in different people. probably in
`normal somatic tissues. The absence of consistent correlation of all
`
`————————¥
`
`22 AUGUST 2013 | VOL 500 .' NATURE l 41?
`
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`of selected cancer types. Each bar represents a typical selected sample from the
`respective cancer type and the vertical axis denotes the number of mutations
`per megabase. Contributions across all cancer samples could be found in
`Supplementary Figs 29—58. Summary of the total contributions for all operative
`mutational processes in a cancer type can be found in Supplementary Figs 59—
`88. ‘Other’ indicates mutational signatures for which we were not able to
`perform validation or for which validation failed (Supplementary Figs 24—28].
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`other signatures with age suggests t