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`7 Genome & Co. v. Univ. of Chicago
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`S UNIV. CHICAGO EX. 2025
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`| ye.
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`r , A ; C C A
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`CURRENT PERIODICALS
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`|
`
`page 1514
`
`aa
`
`POLICY FORUM
`4526 Measuring China's Circular Economy
`¥. Geng et al.
`
`PERSPECTIVES
`1528 Fungal Carbon Sequestration
`K. K.Treseder andS. R. Holden
`>> Report p. 1615
`1529 A Protease for the Ages
`§. Michaelis and C. A. Hrycyna
`>> Reports pp. 1600 and 1604
`FRETting over the Spectroscopic Ruler
`J. R. Winkler
`>> Report p. 1586
`CONTENTScontinued >>
`
`1530
`
`Explore our rich online offerings, including
`multimedia, news, Science Careers, and our
`aie ectt-FlediW (olete]oteMetfellire|
`
`and Science Translational Medicine—at
`
`DEPARTMENTS
`1487 This Week in Science
`1497. Editors’ Choice
`4502 Science Staff
`1538 AAAS News & Notes
`1630 New Products
`1631 Science Careers
`
`ONTEN
`
`SPECIAL SECTION
`Cancer Genomics
`
`INTRODUCTION
`4539 A Medical Renaissance?
`
`NEWS
`4540 Steering Cancer Genomics
`Into the Fast Lane
`1543 The Downsideof Diversity
`
`
`
`EDITORIAL
`1493 Grappling with Cancer
`Edison T. Liu
`>> Cancer Genomics section p. 1539
`NEWS OF THE WEEK
`1504 Aroundup of the week's top stories
`
`NEWS!& ANALYSIS
`1507 Return of Unexpected
`DNA Results Urged
`1508 A Midcourse Correction for
`U.S. Missile Defense System
`1510 Congress Limits NSF Funding
`for Political Science
`:
`ny
`1511 U.S. Science Agencies Finally Have
`(Reduced) Budgets for This Year
`1513 Universe's High-Def Baby Picture
`Confirms Standard Theory
`
`REVIEWS
`1546 Cancer Genome Landscapes
`B. Vogelstein et al.
`4559 Diagnostic Cancer Genome Sequencing
`and the Contribution of Germline Variants
`O. Kilpivaara and L. A. Aaltonen
`1563 Cancer Pharmacogenomics: Early Promise,
`But Concerted Effort Needed
`H. L. McLeod
`
`1567 Epigenetic Reprogramming in Cancer
`M. L. Suvd et al.
`>> Science Podcast
`
`>> Editorial p. 1493; Science Signaling;
`and Science Careers at www.sciencemag.org/
`special/cancergenomics
`
`NEWS FOCUS
`1514 Decade of the Monster
`>> Science Podcast
`4517 As Threats to Corals Grow,
`Hints of Resilience Emerge
`LETTERS
`1521 Misuseof Scientific Data in Wolf Policy
`G. Chapronet al.
`Biodiversity Depends on
`Logging Recovery Time
`F. Michalski and C. A. Peres
`14522 TECHNICAL COMMENT ABSTRACTS
`4522 CORRECTIONS AND CLARIFICATIONS
`?
`a
`1523 The BUZZ: Genetically Modified
`OrganismPolicy
`
`BOOKSETAL.
`1524 Shaky Foundations
`M. Solovey, reviewed byA. J. Wolfe
`1525 Tibet Wild
`G, B, Schaller, reviewed by H. W. Greene
`
`SKINeCe
`
`Image: Mehau Kulyk/Science Source
`
`COVER
`Humancolon cancer(at lower center) identified by a colored
`barium x-ray shown overlaid with a representation of a genetic
`sequence. Genome sequenceanalysis of human tumors has
`uncovered an arrayof genetic alterations that help drive tumor
`growth—information that may lead to more effective cancer
`therapies. See the special section beginning on page 1539.
`
`www.sciencemag.org
`
`SCIENCE VOL339
`
`29 MARCH 2013
`
`1483
`
`

`

`PhotoredoxActivation for the Direct
`B-Arylation of Ketones and Aldehydes
`M.T. Pirnotetal.
`Twocatalysts working in tandem form
`carbon-carbon bonds at a conventionally
`unreactive site.
`1597 Direct Observationsof the Evolution of
`Polar Cap lonization Patches
`Q.-H. Zhang etal.
`Observations of ionospheric perturbations
`SCIENCE PRIZE ESSAY
`after a solar burst hit Earth show how a patch
`1536
`Integrating Inquiry-Based Teaching
`of ionization formed and evolved.
`with Faculty Research
`
`I. Fukami 1600|Structure of the Integral Membrane
`Protein CAAX Protease Ste24p
`page 1534
`EVE. PryorJi. etal.
`RESEARCHARTICLES
`1572 Dust and Biological Aerosols 1604|The Structural Basis of :
`
`
`from the Sahara andAsia Influence
`ZMPSTE24-Dependent Laminopathies
`Precipitation in the Western U.S.
`A. Quigley etal,
`;
`J. M. Creameanetal.
`Structures of two transmembrane zinc
`Dust and biological aerosols from the Sahara
`ca ee a barrel of sevenhelices
`and Asia can act as ice nuclei for precipitation
`SUrToUn ing sage ANY:
`in California's Sierra Nevada.
`>> Perspective p. 1529
`
`1578 Multiple Instances of Ancient Balancing 1608|Wild Pollinators EnhanceFruit Set of
`Selection Shared Between Humans
`Crops Regardless of Honey Bee Abundance
`and Chimpanzees
`L. A. Garibaldietal.
`E. M. Leffler et al
`Flower visits by wild insects enhanced fruit
`Ganaaiewide chevea eenetic balrisepiss
`production in crops worldwide, well beyond
`between humans and chimps mostly affect
`the effect of bees.
`
`host-pathogeninteractions. 1611|Plant-Pollinator Interactions over
`120 Years: Loss of Species,
`Co-Occurrence, and Function
`sesh ay n'a North American
`landscape documenttheloss of species
`interactions in plant-pollinator networks.
`wa Demperine p. 1532
`1615 Roots and Associated Fungi Drive
`Long-Term Carbon Sequestration
`.pe bates '
`Reservoirs of carbon in borealforest soils
`are revisited in an island chronosequence,
`using modeling and molecular approaches.
`>>Perspective p. 1528
`1618 The Biological Underpinnings
`of Namib Desert Fairy Circles
`N. Juergens
`Termites alter local soil conditions
`to facilitate the growth of grasses,
`generating patterns in the desert.
`>> Science Podcast
`
`
`
`Ae
`(R)-2-Hydroxyglutarate Is Sufficient to
`Promote Leukemogenesis andItsEffects
`oe hee
`A metabolite specific to certain cancers, and
`of therapeutic interest, exists in two forms,
`only one of which is oncogenic.
`ESCRT-IIl Assembly and Cytokinetic
`Abscission Are Induced by Tension
`Releasein the Intercellular Bridge
`J. Lafaurie-Janvore et al.
`Whena daughter cell lets go, the mothercell
`cuts it loose,
`
`
`
`
`
`1593
`
`1532 The Global Plight of Pollinators
`J. M. Tylianakis
`>> Reports pp. 1608 and 1611
`1533 Toward a GreenInternet
`D. Reforgiato Recupero
`1534 Neural Stem Cells, Excited
`J. Hsieh andJ. W. Schneider
`
`1621
`
`CONTENTS|
`
`
`
`
`pages 1529, 1600, & 1604
`
`
`
`REPORTS
`1582 Topology-Driven Magnetic Quantum Phase
`Transition in TopologicalInsulators
`BeleFis dgpiliaital aind chagnetie
`quantum phasetransitions are observed
`in thin films of Bi,(Se,Te:..); doped with
`chromium.
`1586 Ultrafast Tryptophan-to-Heme Electron
`SORaot, Revealed
`rp
`: eee
`Seed photoaxctied proteia by
`electron transfer maylimit the generality
`of a commonenergy transfer—based probe.
`>> Perspective p. 1530
`1590 Tuning Selectivity in Propylene
`Epoxidation by Plasmon Mediated
`Photo-Switching of Cu Oxidation State
`A. Marimuthuetal.
`In situ visible light irradiation reverses the
`oxidative degradation of a coppercatalyst,
`thereby enhancingits viability.
`
`
`
`1625
`
`SCIENCE (ISSN 0036-8075)is published weekly on Friday, except the last week in December, by the American Association for the Advancement of Science, 1200
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`SCIENCE VOL339
`
`29 MARCH2013
`
`1485
`
`: Clemmensenetal.5 E. ns .
`
`

`

`#225ANCERGENOMICS
`
`S www.sciencemag.org/special/cancergenomics
`
`REVIEW
`
`This material may be protected by Copyright law (Title 17 U.S. Code)
`
`Cancer Genome Landscapes
`Bert Vogelstein, Nickolas Papadopoulos, Victor E. Velculescu, Shibin Zhou,
`Luis A. Diaz Jr., Kenneth W. Kinzler*
`
`Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes
`of common forms of human cancer. For most cancer types, this landscape consists of a small
`numberof “mountains” (genesaltered in a high percentage of tumors) and a muchlarger number
`of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genesthat,
`whenaltered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor
`contains two to eight of these “driver gene” mutations; the remaining mutations are passengers
`that confer no selective growth advantage. Driver genes can beclassified into 12 signaling
`pathwaysthat regulate three core cellular processes: cell fate, cell survival, and genome
`maintenance. A better understanding of these pathwaysis one of the most pressing needsin basic
`cancer research. Even now, however, our knowledge of cancer genomesis sufficient to guide
`the development of more effective approaches for reducing cancer morbidity and mortality.
`
`T:yearsago,theideathatallofthegenes
`
`altered in cancer could be identified at
`base-pair resolution would have seemed
`like science fiction. Today, such genome-wide
`analysis, through sequencing of the exome (see
`Box 1, Glossary, for definitions of terms used in
`this Review) or of the whole genome,is routine.
`The prototypical exomic studies of cancer
`evaluated ~20 tumors at a cost of >$100,000 per
`case (J—3). Today, the cost of this sequencing
`has been reduced 100-fold, and studies reporting
`the sequencing of more than 100 tumors of a
`given type are the norm (table S1A). Although
`vast amounts of data can now bereadily ob-
`tained, deciphering this information in meaning-
`ful terms is still challenging. Here, we review
`what has been learned about cancer genomes
`from these sequencing studies—and, more im-
`portantly, what
`this information has taught us
`about cancer biology and future cancer manage-
`mentstrategies.
`
`How Many Genes Are Subtly Mutated
`in a Typical Human Cancer?
`In commonsolid tumors such as those derived
`from the colon, breast, brain, or pancreas, an
`averageof33 to 66 genes display subtle somatic
`mutations that would be expected to alter their
`protein products (Fig. 1A). About 95% of these
`mutations are single-base substitutions (such as
`C>G), whereas the remainder are deletions or
`insertions of one or a few bases (such as CTT>CT)
`(table S1B). Of the base substitutions, 90.7% re-
`sult in missense changes, 7.6% result in nonsense
`changes, and 1.7% result in alterations of splice
`sites or untranslated regions immediately adjacent
`to the start and stop codons (table S1B).
`
`
`The Ludwig Center and The Howard Hughes Medical Institute
`at Johns Hopkins Kimmel Cancer Center, Baltimore, MD
`21287, USA.
`
`*Corresponding author. E-mail: kinzlke@jhmi.edu
`
`Certain tumor types display many more or
`many fewer mutations than average (Fig. 1B).
`Notable among these outliers are melanomas
`and lung tumors, which contain ~200 nonsyn-
`onymous mutationsper tumor(table S1C), These
`larger numbers reflect the involvementofpotent
`mutagens(ultraviolet light and cigarette smoke,
`respectively) in the pathogenesis of these tumor
`types. Accordingly, lung cancers from smokers
`have 10 times as many somatic mutations as
`those from nonsmokers (4). Tumors with defects
`in DNArepair form another group of outliers
`(5). For example, tumors with mismatch repair
`defects can harbor thousands of mutations (Fig.
`1B), even more than lung tumors or melanomas.
`Recent studies have shown that high numbers
`of mutations are also found in tumors with
`genetic alterations of the proofreading domain
`of DNA polymerases POLE or POLD1 (6, 7).
`At the other end of the spectrum, pediatric tu-
`mors and leukemias harbor far fewer point mu-
`tations: on average, 9.6 per tumor(table S1C). The
`basis for this observation is considered below.
`
`Mutation Timing
`When do these mutations occur? Tumors evolve
`from benign to malignant lesions by acquiring
`a series of mutations over time, a process that
`has beenparticularly well studied in colorectal
`tumors (8, 9). The first, or “gatekeeping,” mu-
`tation provides a selective growth advantage
`to a normalepithelial cell, allowing it to out-
`grow the cells that surround it and become a
`microscopic clone (Fig. 2). Gatekeeping muta-
`tions in the colon mostoften occur in the APC
`gene (/0). The small adenomathatresults from
`this mutation grows slowly, but a second mu-
`tation in another gene, such as KRAS, unleashes
`a second round of clonal growth that allows
`an expansion ofcell number (9). The cells with
`only the APC mutation maypersist, but their cell
`numbers are small compared with the cells that
`
`have mutations in both genes. This process of
`mutation followed by clonal expansion contin-
`ues, with mutations in genes such as PIK3CA,
`SMAD4, and TP53, eventually generating a ma-
`lignant tumorthat can invade through the under-
`lying basement membrane and metastasize to
`lymph nodes and distant organs such as the
`liver (//). The mutations that confer a selec-
`tive growth advantage to the tumorcell are called
`“driver” mutations.
`It has been estimated (/2)
`that each driver mutation provides only a small
`selective growth advantage to the cell, on the
`order of a 0.4% increase in the difference be-
`tweencell birth and cell death. Over many years,
`however, this slight increase, compounded once
`or twice per week, can result in a large mass,
`containing billions ofcells.
`The numberof mutations in certain tumors of
`selfrenewing tissues is directly correlated with
`age (/3). When evaluated through linear regres-
`sion, this correlation implies that more than half
`of the somatic mutations identified in these tu-
`mors occur during the preneoplastic phase; that
`is, during the growth of normalcells that con-
`tinuously replenish gastrointestinal and genito-
`urinary epithelium and othertissues. All of these
`pre-neoplastic mutations are “passenger” muta-
`tions that have no effect on the neoplastic pro-
`cess. This result explains why a colorectal tumor
`in a 90-year-old patient has nearly twice as many
`mutations as a morphologically identical colorec-
`tal tumor in a 45-year-old patient. This finding
`also partly explains why advanced brain tumors
`(glioblastomas) and pancreatic cancers (pancre-
`atic ductal adenocarcinomas) have fewer mu-
`tations than colorectal
`tumors; glial cells of
`the brain and epithelial cells of the pancreatic
`ducts do not replicate, unlike the epithelial cells
`lining the crypts of the colon. Therefore, the gate-
`keeping mutation in a pancreatic or brain can-
`cer is predicted to occur in a precursorcell that
`contains many fewer mutations than are present
`in a colorectal precursor cell. This line of rea-
`soning also helps to explain why pediatric can-
`cers have fewer mutations than adult tumors.
`Pediatric cancers often occur in non-self-renewing
`tissues, and those that arise in renewing tissues
`(such as leukemias) originate from precursor
`cells that have not renewed themselves as often
`as in adults. In addition, pediatric tumors, as well
`as adult leukemias and lymphomas, may require
`fewer rounds ofclonal expansion than adult solid
`tumors (8,
`/4). Genome sequencing studies of
`leukemia patients support the idea that muta-
`tions occur as random events in normal precur-
`sor cells before these cells acquire an initiating
`mutation (/5).
`When during tumorigenesis do the remaining
`somatic mutations occur? Because mutations in
`tumors occur at predictable and calculable rates
`(see below), the number of somatic mutations in
`tumors provides a clock, much like the clock
`used in evolutionary biology to determine species
`
`SCIENCE
`29 MARCH 2013 VOL 339
`1546
`
`www.sciencemag.orgnnnemma
`
`

`

`
`
`Glioblastoma (14)
`~*+Medulloblastoma(8)
`
`Glioblastoma (35)4=—=
`
`SPECIALSECTION
`
`Ovarian odncer
`a
`c
`
`(42)
`
`+ 4.
`@—_ Prostate cancer(44),
`4
`:
`
`‘
`
`B 1500
`1000
`500
`250
`
`225
`
`200
`
`175
`
`150
`
`125
`
`
`
`Lung(SCLC)
`
`
`
`Lung(NSCLC)~
`
`
`
`Colorectal(MSI)
`
`divergence time. The number of mutations has
`been measured in tumors representing progressive
`stages ofcolorectal and pancreatic cancers (//, 16).
`Applying the evolutionary clock modelto these
`data leads to two unambiguousconclusions:First,
`
`it takes decades to develop a full-blown, meta-
`static cancer. Second,virtually all ofthe mutations
`
`in metastatic lesions were already present in a
`large numberofcells in the primary tumors.
`4
`Non-Hodgkin
`___
`
`Rhabdoid—lymphoma(74)——
`cancer(4)
`The timing of mutations is relevant to our
`
`understanding of metastasis, which is responsible
`
`___|_ EsoLung -(smallcell)(163)
`for the death of most patients with cancer. The
`
`
`Ihageal adenocarcinoma(57)
`primary tumorcan be surgically removed, but the
`Breast cancer (33)—
`a
`J
`Esop
`
`
`hageal squamous
`residual metastatic lesions—often undetectable and
`p
`carcinoma(79)
`widespread—remain and eventually enlarge, com-
`promising the function of the lungs, liver, or other
`organs. From a genetics perspective,
`it would
`seem that there must be mutations that convert a
`primary cancer to a metastatic one, just as there
`are mutations that convert a normal cell to a be-
`nign tumor, or a benign tumorto a malignant one
`(Fig. 2). Despite intensive effort, however, con-
`sistent genetic alterationsthat distinguish cancers
`that metastasize from cancers that have not yet
`metastasized remain to be identified.
`Onepotential explanation invokes mutations
`or epigenetic changes that are difficult to iden-
`tify with currenttechnologies (see section on “dark
`matter” below). Another explanation is that meta-
`static lesions have not yet been studied in suf
`ficient detail to identify these genetic alterations,
`particularly if the mutations are heterogeneous
`in nature. But another possible explanation is
`that there are no metastasis genes. A malignant
`primary tumor can take many years to metasta-
`size, but this process is, in principle, explicable
`by stochastic processes alone (/7, /8). Advanced
`tumors release millions of cells into the circula-
`tion each day, but these cells have short half-lives,
`and only a miniscule fraction establish metastatic
`lesions (/9). Conceivably, these circulating cells
`may, in a nondeterministic manner,
`infrequently
`and randomly lodge in a capillary bed in an organ
`that provides a favorable microenvironment for
`growth. The bigger the primary tumor mass, the
`more likely that this process will occur. In this
`scenario, the continual evolution of the primary
`tumor would reflect local selective advantages
`rather than future selective advantages. The idea
`that growth at metastatic sites is not dependent on
`additional genetic alterations is also supported by
`recent results showing that even normal cells,
`when placed in suitable environments such as
`lymph nodes,can grow into organoids, complete
`with a functioning vasculature (20).
`
`
`
`
`-Non-synonymousmutationspertumor
`
`(median+/-onequartile)
`
`Chroniclymphocyticleukemia—|
`
`
`
`Acutemyeloidleukemia-)
`
`
`‘CREDIT:FIG.1A,E.COOK
`
`Mutagens
`Adi
`nors
`Liquid
`diatr
`Fig. 1. Number of somatic mutations in representative human cancers, detected by genome-
`wide sequencing studies. (A) The genomesof a diverse group of adult (right) and pediatric (left)
`cancers have been analyzed. Numbers in parentheses indicate the median number of nonsynonymous
`mutations per tumor. (B) The median numberof nonsynonymous mutations per tumorin a variety of
`tumor types. Horizontal bars indicate the 25 and 75% quartiles. MSI, microsatellite instability; SCLC,
`smallcell lung cancers; NSCLC, non-small cell lung cancers; ESCC, esophageal squamouscell carcinomas;
`MSS, microsatellite stable; EAC, esophageal adenocarcinomas. The published data on whichthisfigure is
`based are provided in table S1C.
`
`Other Types of Genetic Alterations in Tumors
`Though therate of point mutations in tumors is
`similar to that of normalcells, the rate of chro-
`mosomal changes in cancer is elevated (2/).
`Therefore, most solid tumors display widespread
`changes in chromosome number (aneuploidy),
`as well as deletions,
`inversions, translocations,
`
`www.sciencemag.org
`
`SCIENCE VOL 339
`
`29 MARCH 2013
`
`1547
`
`

`

`s#:=CANCERGENOMICS
`
`5 www.sciencemag.org/special/cancergenomics
`a5
`
`Pies)
`
`}
`pel
`Law
`Neral colonicee
`Small naenorna
`Carcinoma
`Largeadenoma
`50-70
`Patient age (years)
`30-50
`
`Fig. 2. Genetic alterations and the progression of colorectal cancer.
`The majorsignaling pathways that drive tumorigenesis are shown at the transi-
`tions between each tumorstage. Oneofseveral driver genes that encode compo-
`
`nents of these pathways can be altered in any individual tumor. Patient age indicates
`the time intervals during which the driver genes are usually mutated. Note that
`this model may not apply to all tumortypes. TGF-B, transforming growth factor—B.
`
`mutations, as well as the numerous epigenetic
`changes found in cancers, will be discussed later.
`
`Drivers Versus Passenger Mutations
`Though it is easy to define a “driver gene muta-
`tion” in physiologic terms (as one conferring a
`selective growth advantage), it is more difficult
`to identify which somatic mutations are drivers
`and which are passengers. Moreover, it is im-
`portant to point out that there is a fundamental
`difference between a driver gene and a driver
`gene mutation. A driver gene is one that con-
`tains driver gene mutations. But driver genes
`may also contain passenger gene mutations. For
`example, APC is a large driver gene, but only
`
`those mutations that truncate the encoded protein
`within its N-terminal 1600 aminoacids are driver
`gene mutations. Missense mutations throughout
`the gene, as well as protein-truncating mutations in
`the C-terminal 1200 amino acids, are passenger
`gene mutations.
`Numerous statistical methods to identify driver
`genes have been described. Some are based on
`the frequency of mutations in an individual gene
`compared with the mutation frequency of other
`genes in the same or related tumors after correc-
`tion for sequence context and genesize (22, 23).
`Other methodsare based on the predicted effects
`of mutation on the encoded protein, as inferred
`from biophysical studies (24-26). All of these
`methods are useful for prioritiz-
`ing genes that are most likely
`to promote a selective growth ad-
`
`vantage when mutated. When
`
`® Translocations
`lf Deletions
`5
`@ Amplifications
`5
`5
`i Indels
`
`@ SBS
`
`and other genetic abnormalities. When a large
`part of a chromosomeis duplicated or deleted,it
`is difficult to identify the specific “target” gene(s)
`on the chromosome whose gain or loss confers a
`growth advantage to the tumorcell. Target genes
`are more easily identified in the case of chro-
`mosome translocations, homozygous deletions,
`and gene amplifications. Translocations generally
`fuse two genes to create an oncogene (such as
`BCR-ABLin chronic myelogenous leukemia) but,
`in a small numberof cases, can inactivate a tumor
`suppressor gene by truncating it or separating it
`from its promoter. Homozygousdeletions often
`involve just one or a few genes,andthetarget is
`always a tumor suppressor gene. Amplifications
`contain an oncogene whoseprotein productis
`abnormally active simply because the tumor
`cell contains 10 to 100 copies of the gene per
`cell, compared with the two copies present in
`normal cells.
`Most solid tumors have dozens oftranslo-
`cations; however, as with point mutations, the
`majority of translocations appear to be passen-
`gers rather than drivers. The breakpoints of the
`translocations are often in “gene deserts” devoid
`of known genes, and manyofthe translocations
`and homozygousdeletions are adjacentto frag-
`ile sites that are prone to breakage, Cancer cells
`can, perhaps, survive such chromosome breaks
`more easily than normal cells because they con-
`tain mutations that incapacitate geneslike T7P53,
`which would normally respond to DNA damage
`by triggering cell death. Studies to date indicate
`that there are roughly 10 times fewer genes af-
`fected by chromosomal changes than by point
`mutations. Figure 3 shows the types and distri-
`bution of genetic alterations that affect protein-
`coding genes in five representative tumortypes.
`Protein-coding genes accountfor only ~1.5% of
`the total genome, and the number ofalterations
`in noncoding regions is proportionately higher
`than the number affecting coding regions. The
`vast majority of the alterations in noncoding re-
`gions are presumably passengers. These noncoding
`
`
`
`
`
`the number of mutations in a gene
`is very high, as with 7P53 or
`KRAS, any reasonable statistic
`will indicate that the gene is ex-
`tremely likely to be a driver gene.
`These highly mutated genes have
`been termed “mountains” (/). Un-
`fortunately, however, genes with
`more than one,butstill relatively
`few mutations (so called “hills”)
`numerically dominate cancer ge-
`nome landscapes (/).
`In these
`cases, methods based on muta-
`tion frequency and context alone
`cannot
`reliably indicate which
`genes are drivers, because the
`background rates of mutation
`vary so much amongdifferent pa-
`tients and regions of the genome.
`Recent studies of normal cells
`have indicated that the rate of
`mutation varies by more than
`100-fold within the genome (27).
`In tumorcells, this variation can
`be higher and may affect whole
`
`Fig. 3. Total alterations affecting protein-coding genes in
`selected tumors. Average number and types of genomic altera-
`tions per tumor, including single-base substitutions (SBS), small
`insertions and deletions (indels), amplifications, and homozygous
`deletions, as determined by genome-wide sequencing studies. For
`colorectal, breast, and pancreatic ductal cancer, and medulloblastomas,
`translocations are also included. The published data on which this
`figure is based are provided in table $1D.
`
`
`
`CREDIT:FIG.2,E.COOK
`
`1548
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`SCIENCE www.sciencemag.org
`
`

`

`SPECIALSECTION
`
`Box 1. Glossary
`
`Adenoma:A benign tumor composed of epithelialcells.
`
`Alternative lengthening of telomeres (ALT): A process
`of maintaining telomeres independent of telomerase, the
`enzyme normally responsible for telomere replication.
`
`Amplification: A genetic alteration producing a large
`number of copies of a small segment (less than a few
`megabases) of the genome.
`
`Angiogenesis: the process of forming vascular con-
`duits, including veins, arteries, and lymphatics.
`
`Benign tumor: An abnormal proliferation of cells
`driven by at least one mutation in an oncogene or tumor
`suppressor gene. These cells are not invasive (i.e., they
`cannot penetrate the basement membranelining them),
`which distinguishes them from malignant cells.
`
`Humanleukocyte antigen (HLA): A protein encoded by
`genes that determine an individual's capacity to respond to
`specific antigens or reject transplants from other individuals.
`
`Passenger mutation (passenger): A mutation that
`has no direct or indirect effect on the selective growth
`advantageof the cell in which it occurred.
`
`Homozygous deletion: Deletion of both copies of a
`gene segment(the one inherited from the mother, as
`well as that inherited from the father).
`
`Primary tumor: The original tumor at the site where
`tumor growth wasinitiated. This can be defined for solid
`tumors, but not for liquid tumors.
`
`Indel: A mutation due to small insertion or deletion of
`one or a few nucleotides.
`
`Promoter: A region within or near the gene that
`helps regulate its expression.
`
`Karyotype: Display of the chromosomes ofa cell on a
`microscopic slide, used to evaluate changes in chromosome
`number as well as structural alterations of chromosomes.
`
`Rearrangement: A mutation that juxtaposes nucleo-
`tides that are normally separated, such as those on two
`different chromosomes.
`
`Kinase: A protein that catalyzes the addition of phos-
`phate groups to other molecules, such as proteins or
`lipids. These proteins are essential to nearly all signal
`transduction pathways.
`
`Selective growth advantage(s): The difference between
`birth and death in a cell population.
`In normal adult
`cells in the absence of injury, s = 0.000000.
`
`Carcinoma:A type of malignant tumor composed of
`epithelial cells.
`
`Clonal mutation: A mutation that exists in the vast
`
`majority of the neoplastic cells within a tumor.
`
`Liquid tumors: Tumors composed of hematopoietic (blood)
`cells, such as leukemias. Though lymphomas generally form
`solid masses in lymph nodes, they are often classified as
`liquid tumors because of their derivation from hemato-
`poietic cells and ability to travel through lymphatics.
`
`Driver gene mutation (driver): A mutation that
`directly or indirectly confers a selective growth advantage
`to the cell in which it occurs.
`
`Driver gene: A gene that contains driver gene mutations
`(Mut-Driver gene) or is expressed aberrantly in a fashion
`that confers a selective growth advantage (Epi-Driver gene).
`
`Epi-driver gene: A gene that is expressed aberrantly in
`cancersin a fashion that confers a selective growth advantage.
`
`Epigenetic: Changes in gene expression orcellular
`phenotype caused by mechanismsother than changes
`in the DNA sequence.
`
`Exome:The collection of exons in the human genome.
`Exome sequencing generally refers to the collection of
`exons that encode proteins.
`
`Gatekeeper: A gene that, when mutated, initiates tumori-
`genesis. Examples include RB, mutations of which ini-
`tiate retinoblastomas, and VHL, whose mutationsinitiate
`renal cell carcinomas.
`
`Germline genome:An individual's genome,as inherited
`from their parents.
`
`Germline variants: Variations in sequences observed in
`different individuals. Two randomly chosen individuals
`differ by ~20,000 genetic variations distributed through-
`out the exome.
`
`Self-renewing tissues: Tissues whose cells normally
`repopulate themselves,
`such as those lining the
`gastrointestinal or urogenital tracts, as well as blood
`cells.
`
`Single-base substitution (SBS): A single-nucleotide
`substitution (e.g., C to T) relative to a reference sequence
`or,
`in the case of somatic mutations,
`relative to the
`germline genome of the person with a tumor.
`
`Solid tumors: Tumorsthat form discrete masses, such
`as carcinomas or sarcomas.
`
`Malignant tumor: An abnormal proliferation of cells
`driven by mutations in oncogenes or tumor suppressor
`genes that has already invaded their surrounding stroma.
`It is impossible to distinguish an isolated benign tumorcell
`from an isolated malignant tumor cell. This distinction can
`be made only through examination oftissue architecture.
`
`Metastatic tumor: A malignant tumorthat has migrated
`away from its primary site, such as to draining lymph
`nodes or another organ.
`
`Somatic mutations: Mutations that occur in any non—
`germ cell of the body after conception, such as those that
`initiate tumorigenesis.
`
`Methylation: Covalent addition of a methyl group to a
`protein, DNA, or other molecule.
`
`Splice sites: Small regions of genes that are juxtaposed
`to the exons and direct exon splicing.
`
`Missense mutation:A single-nucleotide substitution (e.g.,
`C to T) that results in an amino acid substitution (e.g.,
`histidine to arginine).
`
`Mut-driver gene: A gene that contains driver gene
`mutations.
`
`Stem cell: An immortal cell that can repopulate a par-
`ticular cell type.
`
`Subclonal mutation: A mutation that exists in only a
`subset of the neoplastic cells within a tumor.
`
`Nonsense mutation: A single-nucleotide substitution
`(e.g., C to T) that results in the production of a stop codon.
`
`Nonsynonymous mutation: A mutation thatalters the
`encoded amino acid sequence of a protein. These include
`missense, nonsense,splice site, translation start, transla-
`tion stop, and indel mutations.
`
`Translocation: A specific type of rearrangement where
`regions from two nonhomologous chromosomes are
`joined.
`
`Tumor suppressor gene: A gene that, when inacti-
`vated by mutation, increases the selective growth ad-
`vantage of the cell in which it resides.
`
`Oncogene: A genethat, when activated by mutation, in-
`creases the selective growth advantage ofthe cell in which
`it resides.
`
`Untranslated regions: Regions within the exons
`at the 5’ and 3’ ends of the gene that do not encode
`amino acids.
`
`www.sciencemag.org
`
`SCIENCE VOL 339
`
`29 MARCH 2013
`
`1549
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`

`

`=CANCERGENOMICS
`= ww.sciencemag.org/special/cancergenomics
`
`¥ = Missense mutation
`A = Truncating mutation
`
`|
`
`PIK3CA
`
`1068 aa
`
`IDH1
`
`414 aa
`
`
`
`RBI
`
`
`
`Fig. 4. Distribution of mutations in two oncogenes (P/K3CA and IDH1)
`and two tumorsuppressor g