© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. A A full list of affiliations appears at the end of the paper. a enabled has (NGS) sequencing next-generation parallel massively throughput approaches to interrogate a single allele in a single sample, tumoracross with shared distinct types featuresgenetic efficacy of approved and investigational molecularly targeted therapies Moreover, genomically guided clinical trials have begun to evaluate the standard practice to profile tumors for recurrent targetable mutations certain tumor types, such as lung cancer and melanoma, it has become tion of clinical genomics to the diagnosis and treatment of disease Over the last decade, oncology has served as a paragon for the applica accessible. publicly are results all types, tumor and alterations rare into investigation deeper and biomarkers novel of To 11%. of discovery a at rate enable trials clinical matched genomically on enrolled were Patients types. tumor rare and common by shared were that signatures mutational and alterations, noncoding novel mutations, somatic relevant clinically identified we data, these Using annotations. clinical and pathological available and cancer advanced with patients 10,000 than more of cohort a unique from data sequence normal matched and tumor compiled have we assay, which MSK-IMPACT, through a comprehensive using initiative sequencing clinical prospective a large-scale, We established cancers. of spectrum full the across genes relevant clinically profile to approaches comprehensive and flexible demands therapies, targeted molecularly of portfolio expanding an with coupled types, tumor defined histologically distinct across alterations targetable recurrent of existence The therapeutically. targeted be can that pathways and genes in alterations genomic of identification the oncology, enabling precision of component a is fundamental profiling Tumor molecular David M Hyman Paul J Sabbatini Rona Yaeger Pedram Razavi Emmet J Jordan Darren R Feldman N Dalicia Reales Jiaojiao Wang Benjamin E Gross Alexander V Penson Tessara Baldi Jacklyn Casanova Rema Anoop Balakrishnan Abhinita S Mohanty F Deborah DeLair David A Barron Preethi Srinivasan Ahmet Zehir prospective clinical sequencing of 10,000 patients Mutational landscape of metastatic cancer revealed from nature medicine nature Received 22 December 2016; accepted 4 April 2017; published online 8 May 2017; Although molecular pathology has historically relied upon low- upon relied historically has pathology molecular Although 4 1 1 , , Jonathan Coleman 2 , , Kerry , A Kerry Mullaney 13 , , Angelica Ochoa 4

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- - - - © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. principal tumor types and >300 detailed tumor types, representa types, tumor detailed >300 and types tumor principal successfully (91%). we individuals 10,336 from samples tumor Altogether, 10,945 sequenced available. were specimens additional rate of a when 75% rescue achieving sample, a replacement sequence performance sequencing ( influenced age sample and input DNA ( criteria control ity qual post-sequencing strict meet not did that samples excluded we or DNA yield ( Fig. 2 a exhibited range of and tissue DNA ( metrics quality samples hospitals, from outside obtained material archival including ( of 12 time last of months d study,<21 this turnaround a with median the over month per cases 563 of throughput average an We achieved ( record medical electronic the in physicians and patients to reported and reviewed manually were which of all rearrangements, somatic chromosomal and CNAs detect deletions, and to insertions small mutations, NGS deep-coverage to and subjected capture was blood hybridization peripheral normal matched cases, of 98% ( sequencing MSK-IMPACT prospective for tumors individuals 11,369 12,670 from obtained we 2016, May and 2014 January Between Description of the sequencing cohort RESULTS ( Genomics Cancer for cBioPortal the through available publicly set data full the made have we efforts, profiling genomic other with integration and biomarker discovery, development of trials based clinical molecularly Totherapy. facilitate targeted molecularly to patients matching and MSK-IMPACT in determining the prevalence of actionable mutations of utility of an clinical the analysis and performed practice in clinical as encountered cancer of metastatic landscape genomic the explored to pairs we tumors, tumor–normal 10,945 of set data our Using management. matched clinical guide of sequencing clinical spective and data. with clinical advanced cancer and pathological associated of data set tumor and matched DNAnormal from patients sequences unparalleled an haveproduced we efforts, these Through sequenced. tumor every for mutations tumor-specific) (i.e., somatic definitively compilecomprehensive to ofa us tumors,enabling patient to catalog types. A key feature of our process is the use of normal controls than patients 10,000 with cancer,matched spanning a vast array of solid tumor Service laboratory, we have prospectively sequenced tumors from more Improvement Amendments (CLIA)-compliant Molecular Diagnostics genes cancer-associated 410) recently, more (and, 341 in rearrangements structural and mutations promoter selected and (CNAs), alterations that is capable of detecting all protein-coding mutations, copy number implemented MSK-IMPACT, a hybridization capture–based NGS panel contexts. clinical different in decisions therapeutic influence results molecular to which of degree the evaluation careful true clinical utility of mutation profiling remains requiring uncertain, Atlas Finally,Genome The Cancer including (TCGA). the initiatives, research through cancers untreated primary, in characterized been A  who cancer solid metastatic with patients of diversity the of tive Supplementary Fig. 1 Fig. Supplementary Supplementary Table 1 Table Supplementary upeetr Fg 4 Fig. Supplementary

Our cohort of successfully sequenced tumors encompasses 62 62 encompasses tumors sequenced successfully of cohort Our submitted, types specimen and cases the of diversity the Given pro large-scale of utility and feasibility the demonstrate we Here and developed we Center, Cancer Kettering Sloan Memorial At s e l c i t r 1 ). ). Tissues with tumor insufficient content ( 1 . Since establishing MSK-IMPACT establishing Since . Laboratory our Clinical in http://cbioportal. n = 793 samples; 6%) were as reported inadequate, and n = 604 samples; 5%) ( 5%) samples; 604 = ). ). For technical failures, we attempted to to attempted we failures, technical For ). ). DNA isolated from tumor tissue and, in in and, tissue tumor from isolated DNA ). org/msk-impac Supplementary Fig. 3 Fig. Supplementary t ) 1 2 n . = 328 samples; 3%) Supplementary Supplementary Fig. Fig. 1 ). ). ). ). - - -

coverage depth is typically limited, we found that at least 9% of all all of 9% least at that found we limited, typically is depth coverage compare them to results from whole-exome sequencing (WES), where rearrangements are which hotspot panels, most for unsuited also CNAs detecting and amplicon-based available commercially of regions target combined ( percent Eighty-one would have been missed by other approaches ( DNAnormal us allowed to important genomic that alterations detect ( proportional inversely be to rangements. The numbers of mutations and CNAs per sample tended ( 0.21 of fraction allele variant median a with mutations, nonsynonymous ( specimens low-purity and heterogeneous in alterations genomic detecting for sensitivity high had MSK-IMPACT ensure to 718×) = (mean erage panel ( 341 genes from the former panel were included in the latter, expanded 341 genes (2,809 tumors; 26%) and 410 genes (8,136 tumors; 74%); all 5 Fig. commonly, sites—most liver, lymph and node bone ( metastatic from obtained were specimens all of percent Forty-three ( institution our at treated are to the TCGA cohort. In prostate cancer alone, the frequency of frequency the alone, In cancer prostate cohort. to TCGA the lastoma and gastric cancer) in the MSK-IMPACT cohort as compared tumor types (prostate cancer, kidney chromophobe carcinoma, gliob these was among principal The cohort. MSK-IMPACT the in mutated frequently more even were studies TCGA in significant as identified originally were that We genes many that cohort. found TCGA the to compared as MSK-IMPACT the cohort in type tumor and gene each of in mutations enrichment the we calculated treatment, and/or tasis To studied. with metas the individuals mutations associated identify offeatures clinical of the distinct indicative the two cohorts, between ( detected mutations Supplementary Fig. the 10 of frequencies and identities population the of terms in concordance strong exhibiting ings, find TCGA the with consistent highly were results MSK-IMPACT types tumor common 16 from data TCGA ined exam we TCGA, by characterized tumors primary untreated from those to compared pretreated, often were who cancer metastatic or advanced with patients from derived results, our how Toinvestigate Landscape of somatically altered genes cancer. metastatic with patients of set data genomic unique and comprehensive rich, a represent results our summary, In sample. normal matched a from sequence of absence the in variants inherited rare, from distinguish (v78) database (COSMIC) Cancer in Mutations Somatic of Catalog the in reported previously not were MSK-IMPACT by detected the mutations of somatic 69% as Finally, methods. WES current from absent are that targetable gene fusions, owing to detect the inclusion of breakpoint-containing introns also can and assay the in included genes relevant signatures, mutation certain of MSK-IMPACT produces more uniform coverage across the clinically characterization the to of suited capable ter is WES bet is while and genome the Further, throughout mutations more many 150×. detecting of depth target mean a in alterations targetable cally therapeuti WES—including by missed been have would mutations The breadth and depth of MSK-IMPACT and the analysis of matched TP53 Supplementary Fig. 7 Fig. Supplementary ). Two panels were used throughout this study, encompassing encompassing study, this throughout used were Twopanels ). Supplementary Supplementary Table 3 , which was significantly enriched for mutations in four four in mutations for enriched significantly was which , Supplementary Fig. 6 Fig. Supplementary 1 advance online publication online advance 6 5 , 1 , these mutations would have been difficult to to difficult been have would mutations these , 4 . Moreover, when we downsampled our data to to data our downsampled we when Moreover, . n = 63,184) of all mutations fell outside of the the of outside fell mutations all of 63,184) = ). However, we observed important differences ), as well as 22,989 CNAs ), rear as as well 22,989 and 1,875 Supplementary Fig. 8 Fig. Supplementary Fig. 2 Fig. ). ). Tumors were sequenced to deep cov BRAF ). Altogether, we detected 78,066 78,066 detected we Altogether, ). a , , and and EGFR Supplementary Table2 Supplementary and and Supplementary Supplementary Fig. 9

MET nature medicine nature 16– ) Supplementary Supplementary 1 1 9 3 —when using using —when . . Overall, the the Overall, . i. 2 Fig. b TP53 and and ). ). ). ------

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. terminal domain, whereas mutations in lung cancer arose mainly in in mainly arose cancer lung in mutations whereas domain, terminal in within genes were observed among different tumor types. For example, tive selection across lineages was mutated in more than were 20 principal tumor types, indicative of posi codons mutated PIK3CA commonly most next The of all for 80% quently altered codon among the tumors sequenced (G12), accounting (44%). adenocarcinoma and colon (90%) adenocarcinoma pancreatic in prevalent most were mutations of gene (15% patients). altered frequently most second the was for of in tumor >10% altered 43 cases of types. 62 the principal Altogether, splicing. of disruption or truncation through inactivating were and largely (85%) lung cancer small-cell and (89%) serous high-grade ovarian cancer (98%), esophageal adenocarcinoma TP53 ( treatment hormone after arose that tumors metastatic in exclusively almost cancers, endometrial and breast both in hotspots recurrent inhibitors receptor androgen to resistance conferring mutations acquired as described been have of both which each), were and (ten individuals cohort L702H H875Y common most The therapy. hormone to ance resist promoting in genes these of roles known the with consistent ESR1 in including TCGA, in type cancer corresponding the in enriched not were that MSK-IMPACT in genes in alterations frequent observed between associations noted previously with consistent is which 7%), versus mutations was greater in >4-fold MSK-IMPACT than in TCGA (29% interpretation. and mining data for cBioPortal the to uploaded automatically and matching trial clinical automated facilitates that (Darwin) database institutional an to transmitted record, medical electronic the in reported are alterations Genomic accuracy. and quality for reviewed manually are they where MPath, house, in developed database variants a genomic into loaded are Results rearrangements. genomic of classes multiple detects that pipeline bioinformatics a custom through analyzed are reads paired sequencing, Following genes. rearranged recurrently of introns select and genes 410 of exons coding all targeting probes hybridization using captured and prepared are libraries sequence and protocols, automated using samples blood and tumor from extracted is DNA DNA. normal of a source as collected is sample 1 Figure nature medicine nature domain ( kinase the Supplementary Fig. 11 Fig. Supplementary The most frequently altered gene in the MSK-IMPACTgene in the altered frequently The most was cohort EGFR AR (41% of patients; (estrogen receptor) in breast cancer (11% versus 4%), which is is which 4%), versus (11% cancer breast in receptor) (estrogen (androgen receptor) in prostate cancer (18% versus 1%) and and 1%) versus (18% cancer prostate in receptor) (androgen

E545 , mutations in glioma were localized to the extracellular N- extracellular the to localized were glioma in mutations , Overview of the MSK-IMPACT clinical workflow. Patients provide informed consent for paired tumor–normal sequence analysis, and a blood a blood and analysis, sequence tumor–normal paired for consent informed provide Patients workflow. clinical MSK-IMPACT the of Overview TP53 1. Patientconsent 4. Sequencing and and KRAS status and more aggressive disease clinically BRAF

Supplementary Fig. 12 Fig. Supplementary mutations and 12% of all individuals sequenced. sequenced. individuals of all mutations 12% and advance online publication online advance Fig. 2 V600 ) 22 ( 2 , c 2 4 Supplementary Table 4 Supplementary ). 3 . Differences in the location of mutations . 2 TP53 1 . . ESR1 Rearrangements Copy numberalterations Mutations KRAS mutations occurred most often in 2. Sampleaccessioning mutations were observed at observed were mutations 5. Bioinformatics Tumor also harbored the most fre most the harbored also analysis ). AR Blood mutations in our our in mutations ), each of which which of each ),

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sign out (96.3%); they were observed in 43 principal tumor types ( types tumor principal 43 in observed were they (96.3%); the to relative bp −146 and −124 at positions substitutions G>A reports, prior with Consistent date. to reported types tumor all across moter our to knowledge, provide, the largest analysis of thus somatic mutations in the results MSK-IMPACT The analysis. WES by the because studies genomic and cell decreased death expression telomerase upregulated to leading factors, transcription family ETS for sites binding consensus novel create to shown been Mutations at two highly recurrent hotspots cancer- in the aforementioned the of genes, associated MSK-IMPACT also captures regions the promoter of coding the to addition In TERT lineage. of regardless profiling mutation broad of benefit potential the reinforcing types, tumor principal or more five in once tumors, 97% of the genes in panel were our 410-gene mutated at least hypermutated excluding Nevertheless, carcinoma. hepatocellular lar EWSR1 as such lineages, particular to ple, for in (for mutations exam only one or enriched lineages two cancer example, (for types tumor by discerned easily complex not sequencing targeted by are that produced chromoplexy, as fusions such gene processes, of suggestive were cancers, involving rearrangements cryptic of ( 2–7 exons of (deletion EGFRvIII most The were rearrangements observed (15%). commonly individuals 1,597 in reported were fusions, gene n = and 38) Although some genes were mutated at similar rates across many many across rates similar at mutated were genes some Although putative produced which of many rearrangements, Genomic TERT VHL promoter mutations - FLI1 , , transcription start site were the most common alterations alterations common most the were site start transcription APC EWSR1 in Ewing sarcoma and and and IDH1 2 - 5 FLI1 . Precision oncology Genomic variants knowledge base 26 ). Certain gene fusions were also exclusive exclusive also were fusions gene Certain ). , database ( 2 7 MPath n TP53 . . Yet, these hotspots are absent from most = 25). Additional alterations, including including alterations, = Additional 25). TERT TMPRSS2 and and TMPRSS2 promoter is typically not covered covered not typically is promoter DNAJB1 PIK3CA EGFR TMPRSS2 - ERG - detected in 23 prostate prostate 23 in detected PRKACA ; ; n ), others were highly highly were others ), TERT = 65), 65), = in prostate cancer, cancer, prostate in Investigational biomarke FD Level 3A MAF: 55 +: Aglossaryoftermsandthedescriptioniconographyusedinthisreportcanbefoundafter"TestMethodology" ERBB2 RefSeq IDsforthegeneswithreportedvariantsalongalistofall410canbefoundonlastpage α ERBB2 Somatic alterationsdetectedinthissample: FC: 2. Alteration(s) ERBB CDK1 Muta BRCA MDC1 ZFHX3 CDH1 TP53 ERBB Muta Gene Summary Date ofReceip Ref. Physician Tumor Type Gender Date ofBirth Patient Name Level : Denotesclinically/analyticallyvalidatedvariants A A Approved and/orNCCNrecommendedbiomarke interpretation Data mining matching Clinical trial Clinical report t t 2 7 2 2 1 Copy NumberAlterations Mutations 1 s e l c i t r a %

Amplificatio L755S 0 t n M Missense Mutation Missense Mutation Missense Mutation Nonsense Mutation Type W M W r 6 mutations,2copynumberalterations,nostructuralvariantsdetected.al Physician M.D. Carcinom Breast InvasiveDuctal Female John Do issense Mutation issense Mutation hole gene hole gene /0/0000 T-DM Trastuzumab+Pertuzumab Trastuzuma Lapatinib Drug(s Neratini 1 e ) b - a Memorial HospitalForCancer&AlliedDiseases b Molecular DiagnosticsService,DepartmentofPathology ERG promoter have . Amplification Amplification R951K (c.2852G>A) R2054W (c.6160C>T) A2556V (c.7667C>T S133F (c.398C>T) Q192* (c.574C>T) L755S (c.2264T>C Annotation in fibrolamel MSK-IMPAC upon drugtreatment. has beenbiologicallycharacterizedassensitizingtoneratinibevidencedbypathwayinhibition use ofneratinibinpatientswithbreastcancerharboringtheERBB2L755Smutation. ERBB2 L755Smutationisknowntobeoncogenic.Therecompellingclinicaldatasupportingthe expression invariouscancers,includingbreast,endometrialandesophagogastriccancer pro-oncogenic MAP-andPI3-kinasepathways.ERBB2isalteredbyamplificationand/orover ERBB2 encodesamemberoftheEGFRfamilyreceptortyrosinekinasesthatsignalsthrough amplification isknowntobeoncogenic. pression invariouscancers,includingbreast,endometrialandesophagogastriccancer pro-oncogenic MAP-andPI3-kinasepathways.ERBB2isalteredbyamplificationand/oroverex ERBB2 encodesamemberoftheEGFRfamilyreceptortyrosinekinasesthatsignalsthrough ca ER per D r escription nc BB tu er zuma 2

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. type–specific alteration frequency of of frequency alteration type–specific ( mutations. for enriched significantly was gene the which in TCGA in type cancer the to corresponds symbol each of color The labeled. are cohorts two the between frequency in difference a significant showed mutations which in genes and displayed, are studies TCGA in mutated significantly were that Genes ( types. tumor detailed 361 encapsulating types tumor principal 62 represented 2 Figure A  alterations. genomic

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Overview of the MSK-IMPACT cohort. ( cohort. MSK-IMPACT the of Overview c ) Recurrent somatic alterations across common tumor types. Genes with a cohort-level alteration frequency of of frequency alteration a cohort-level with Genes types. tumor common across alterations somatic ) Recurrent Soft-tissue sarcoma b a c NOTCH1 CTNNB1 Pancreatic cancer ARID1 PIK3CA KDM6A KMT2C KMT2D Frequency in MSK-IMPACT cohort GNAS 0.0 0.2 0.4 0.6 0.8 BRAF KRAS EGFR BAP1 PTEN TERT FAT1 TP53 IDH1 APC RB1 VHL NF Esophagogastric carcinoma KIT Bladder cancer Prostate cancer A Renal cellcarcinoma 1 TP53 0.0 RASA1 Glioma Non-small-cell lung cancer PTE Melanoma Colorectal cancer

Breast carcinoma N EGFR SETD2 NSD1 Colorectal cancer ( n ( ( Germ celltumor n n =490) =438) =512) Prostate cancer ( 0.2 n ARID1 ( =406) TP53 ≥ n PIK3CA

Glioma ( 30% are displayed. Bars indicate the percentage of cases within each tumor type harboring different classes of classes different harboring type tumor each within cases of percentage the indicate Bars displayed. are 30% =623) Biliary cancer n =350) Pancreatic cancer Frequency inTCGAcohort ( A n

Soft-tissue sarcoma =322) ( TP53 ( n Bladder cancer n =978) =317) 0.4 (

Melanoma n a =268) ) Distribution of tumor types among cases successfully sequenced from 10,336 patients. Cases Cases patients. 10,336 from sequenced successfully cases among types tumor of ) Distribution Renal cell carcinoma ( n Esophagogastric carcinoma =242) Germ cell tumor Biliary cancer 0.6 Thyroid cancer

Ovarian cancer Thyroid cancer

Endometrial cancer Ovarian cancer Breast carcinoma

Head and neck carcinoma Endometrial cancer 0.8

Cancer of unknown primary Head andneckcarcinoma

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Skin cancer, non melanoma n =226)

Gastrointestinal stromal tumor ( n =217) lung cancer Non-small-cell Mesothelioma Other ( n TCGA tumortypes Hepatocellular carcinoma =1,237) b ( n Stomach adenocarcinoma Prostate adenocarcinoma Lung adenocarcinoma Kidney renalclearcellcarcinoma Kidney chromophobe Head andnecksquamouscellcarcinoma Breast invasivecarcinoma Bladder urothelialcarcinoma Uveal melanoma Uterine corpusendometrialcarcinoma Thyroid carcinoma ) Frequency of gene alterations in TCGA and MSK-IMPACT cohorts. cohorts. MSK-IMPACT and TCGA in alterations gene of ) Frequency ( =211)

Salivary carcinoma n Uterine sarcoma =1,627) (

Small-cell lung cancer n =1,563) (

Appendiceal cancer n =179)

Embryonal tumor ( n Gastrointestinal neuroendocrine tumor =160) advance online publication online advance Cervical cancer Osteosarcoma 0% 10% altered withintumortype Other Gestational trophoblasticdisease Breast sarcoma Chordoma Nerve sheathtumor Ependymomal tumor Thymic tumor Sex cordstromaltumor Histiocytosis Ampullary carcinoma Adrenocortical carcinoma Meningothelial tumor Anal cancer Small-bowel cancer Chondrosarcoma Ewing sarcoma Osteosarcoma Cervical cancer Gastrointestinal neuroendocrinetumor Embryonal tumor Appendiceal cancer Small-cell lungcancer Uterine sarcoma Salivary carcinoma Hepatocellular carcinoma Mesothelioma Gastrointestinal stromaltumor Skin cancer,nonmelanoma Non-Hodgkin lymphoma Promoter Frameshif Nonsens In frame Missens Fraction ofpatient 0 0 Alteration type ( n 20% = 60) .2 ( n e 0. ( e ( n = 14) n t ( ( 0 4 n = 32) ( n = 20) ( n ( ( n n = 18) ( n = 106) ( n ( = 42) n 30% n = 37) = 47) .6 = 12) ( = 91) ( n = 76) ( ( = 36) Multiple alterations Fusion Deletion Amplification n n n ( ( ( n 0. = 104) n n ( = 35) = 15) = 79) n ( = 16) = 32) = 25) 8 s n ( = 88) n ( ( = 18) n n = 159) 40% ( = 26) = 105) n ( = 144) n = 126) ( n ≥ = 11) 5% or a tumor a tumor or 5% (

n = 53) nature medicine nature © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. our results reaffirm the high prevalence of these alterations in patients of mutations in the with altered We observed a consistent trend toward shorter survival for individuals and melanoma (49%), predominantly cutaneous melanoma ( observed in bladder cancer (70%), glioma (67%), thyroid cancer (60%) site. start scription recurrent ( site ETS-binding presumptive a site, start alone which was mutated in patients and 21 distinct created transcription the to relative bp −138 position at including mutation, However, we observed ten additional sites of recurrent WT, type. wild analysis. statistical for used was test log-rank The analysis. this from excluded were sequencing MSK-IMPACT before months 12 than more obtained were specimens where Cases obtained. was of prevalence highest ( mutation. promoter ( hotspot. individual each at mutations harboring types cancer of distribution the shows inset The bp). −138 bp, −146 bp, (−124 hotspots mutational common most three the for red in shown are sites binding factor transcription ETS presumptive to leading changes nucleotide Observed bp). (+1 3 Figure nature medicine nature disease with association an suggest and tumors solid advanced with

The spectrum of of spectrum The b ) Bar plots depicting the percentage of cases in each common principal tumor type (left) and melanoma subtype (right) harboring a harboring (right) subtype melanoma and (left) type tumor principal common each in cases of percentage the depicting plots ) Bar TERT c b a 1,000 TERT Survival probability Number of patients 0.0 0.2 0.4 0.6 0.8 0.1 Bladder cancer Percent of patients 100 250 500 750 10 50

with alteration 1 mutations were clustered within 100 bp of the tran the of bp 100 within clustered were mutations 6 0 20 40 60 80 –346 0 promoters (

TERT c

TERT TERT HepatocellularThyroid carcinoma cancer TERT Months fromprocedure ) Kaplan–Meier survival curves for the most prominent detailed tumor types belonging to the principal tumor types with the the with types tumor principal the to belonging types tumor detailed prominent most the for curves survival ) Kaplan–Meier TERT Cutaneous melanom Skin cancer, non melanomaGlioma advance online publication online advance

mutated WT Melanoma

TERT Head and neck carcinoma promoter remains incompletely understood, promoter mutations. Survival was measured starting from the date of the procedure during which the sequenced specimen specimen sequenced the which during procedure the of date the from starting measured was Survival mutations. promoter promoter mutations were most commonly commonly most were mutations promoter Log-rank ( n 12 = 41)

promoter mutations in cancer. ( cancer. in mutations promoter Renal cell carcinoma Fig. 3 ( n TCCCCGG>T TCCCCGG>TC CTCCCGG>CT CCTCCGG> CCTCCGG>C CCTCCGG>C = 123) Soft-tissue sarcoma P Supplementary Table 5 Supplementary 18 =0.219 c a Salivary carcinoma ). Although the clinical relevance Cancer of unknown primary TT A T TT 24 TCCGG TCCGG TCCGG T T

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TERT Non-small-cell lung cancer

mutated WT Biliary cancer –124C>T orC>ACC>TT ). All novel novel All ).

Osteosarcoma –138C>T orCC>T Log-rank ( promoter a –146C>T n 12 ) Location of all all of ) Location Fig. Fig. 3 =41) –146 ( n =128) Colorectal cancer –124 18 P b Appendiceal cancer =0.037 ). ).

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Esophagogastric carcinoma T a 24 in 11 additional tumor types. Further, fusions in 51 tumor 11 kinase types. we additional identified exist therapies in targeted for lung effective which cancer, were found been previously not involving fusions gene had example, For reported. they where types tumor in fusions gene ( cancers across widely occurred others lineages, particular in enriched were fusions ( the domain of kinase part or all encompassed and genes kinase involved fusions) ( 35% MSK-IMPACT, by identified fusions gene the all Of Kinase fusions and rearrangements accumulate. data clinical longitudinal as ized outcome poor and progression Uterine sarcoma Non-Hodgkin lymphoma TERT

Survival probability Other –138 –146 –124 0.0 0.2 0.4 0.6 0.8 0.1 promoter mutations relative to the transcription start site site start transcription the to relative mutations promoter –58 6 0 Pancreatic cancer 0 Glioma Colorectal cancer Bladder cancer

TERT TERT Breast carcinoma Months fromprocedure Papillary thyroidcancer Endometrial cancer 5 ′ UT mutated WT Fig. 4 Fig. Supplementary Table 6 Table Supplementary R Germ cell tumor Log-rank ( n 12 2

= 14) Prostate cancer 5 +1 a ( n ) Non-small-cell lungcancer Melanoma Head andneckcarcinoma 3 = 32) 2 . We also detected many known recurrent recurrent known many detected We also . P 18 Percent ofcases =0.297

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n

= 268 268 = ROS1

 - , © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. fusions that were recently identified from a parallel clinical sequencing (Online Methods). These results, together with another set of 55 BRAF complextranscriptsadditionalwithassociatedfusionfour confirmed the complete kinase domain and were predicted to be in frame. We also mutations( was detected in two independent melanomas lacking other gene, clear driver fusion recurrent novel a including tumor types involving 18 distinct partner genes (10 of tumorwhich types.were Altogether,novel), we detected 33 detected. are fusions actionable therapeutically all that ensure to genes partner multiple detecting of of role capable the importance and methods functional underscoring in tumors lacking other clear driver mutations, supporting a bona fide occurred fusions these cases, In most genes. partner novel involving in observed deletions assay. using RNA–seq-based an resolved orthogonal Each red a line indicates point fusion between tumor ( types. principal across displayed domain, kinase 4 Figure A  effort RPS6KB2 c a

PRKACA FGFR3 FGFR2 Among all kinases, NTRK3 s e l c i t r ERBB2 ROS1 FGFR1 BRAF 5 5 5 5 5 5 5 5 CDK12 NTRK1 STK11 RIPK4 ′ ′ ′ ′ ′ ′ ′ ′ PLK2 AKT2 ALK RET 1 3 MET rearrangements independentanRNA-basedusing assayfusion 3 , indicate that the full spectrum of

( ( ( ( ( ( ( Ras binding Spectrum of kinase fusions identified by of MSK-IMPACT.Spectrum identified fusions kinase ( n n n n n n n ( ( ( ( ( ( ( ( ( ( ( n n n n n n n n n n n 155 = 10) = 23) = 24) = 29) = 30) = 33) = 42) = 6) = 8) = 9) = 2) = 2) = 2) = 2) = 4) = 4) = 4) = 5) Fig. 4 Fig. 227 23 19 39 Non-small-cell lung cancer 2 1 2 1 3 1 5 b 1 1 1 1 1 2 1 1 and Breast carcinoma BRAF 1 1 2 1 1 2

BRAF Colorectal cancer 457 1 1 4 Supplementary13 Fig.

Protein kinase Prostate cancer 10 1 1 4 , encompassing 5–9 of , exons upstream the the bars of encompassing Orange domain. kinase indicate location the domains. protein labeled Glioma 1 2 1 1 6 fusions occurred in the greatest number of Pancreatic cancer Soft-tissue sarcoma 1 1 2 1 Bladder cancer 1 6 1 717 Melanoma 1 1 1 4 1 766 3 3 3 3 3 3 3 3 Renal cell carcinoma ′ ′ ′ ′ ′ ′ ′ ′ BRAF 2 1 Exon 5–exon11 Exon 3–exon Exon 2–exon Exon 2–exon11 Exon 1–exon11 Exon 1–exon Exon 1–exon BRAF BRAF Esophagogastric carcinoma Germ cell tumor 1 18 1 1 1 CDK5RAP2

fusions across 11 principal Biliary cancer fusions in human cancers Thyroid cancer 2 8 3 1 1 1 ). All fusionsinvolvedAll ). Ovarian cancer 9 9 9 9 Endometrial cancer 1 2 1 1 b Melanoma Melanoma Non-small-cell lungcancer Prostate cancer Prostate cancer Colorectal cancer Bladder cancer 1

) ) List the of BRAF *, containing domain. kinase †, fusions novel partner; fusion complex Head and neck carcinoma 1 1 2 1 1

- Cancer of unknown primary BRAF 4 1 Salivary carcinoma 1 Hepatocellular carcinoma 9 a 1 1 ) Kinase genes recurrently rearranged to gene form that ) rearranged the fusions putative include genes Kinase recurrently which , Uterine sarcoma 1 BRAF Appendiceal cancer 1 Ampullary carcinoma No. fusions

10 20 30 and and one melanoma). The other four received no cases BRAF-directed adenocarcinoma colorectal one adenocarcinoma, lung (one therapy harbored of the seven cases with intragenic deletions detected by MSK-IMPACT genomic basis has previously Interestingly,been described. only three acquired resistance to RAF inhibition, to our knowledge, no underlying MAPK pathway activation. Although this is a recurrent mechanism of and dimerization BRAF RAS-independent enable isoforms splicing to BRAF inhibition in isoforms produced by aberrant splicing that were previously reported to equivalent) cases, some in (and, similar transcripts in-frame duce in tions activity with MEK inhibitors in individuals harboring profile fusions in solid tumors, especially given recent reports of clinical remains incomplete; they also highlight the need to continue to broadly Additionally, seven samples harbored intragenic multiexon dele multiexon intragenic harbored samples seven Additionally, b CDK5RAP2* CDK5RAP2* BRAF HERPUD1 PRKAR1B* PRKAR2B* FAM131B KIAA1549 KIAA1549 KIAA1549 KIAA1549 OSBPL9* ZNF207* RBM33* MKRN1 MKRN1 PHTF2* SCRIB* CCDC6 GIPC2* AGAP3 AGAP3 TNS3* TLK2* PJA2* BRAF SND1 SND1 SND1 SND1 SND1 SND1 SND1 SND1 CUL1 AGK AGK AGK AGK V600E BRAF BRAF † † † † 5 1 ′ -mutant melanomas in the setting of acquired resistance ( V600E advance online publication online advance Fig. 4 Fig. Ras binding BRAF 155 3 5 mutations and had received prior BRAF inhibitor . By eliminating the RAS-binding domain, these . domain, these By the RAS-binding eliminating 227 c and its partner.upstream ( ). All seven deletions were predicted to pro to predicted were deletions seven All ). 457 Protein kinase 717 766 3 Colorectal cancer Colorectal cancer Non-small-cell lungcancer Gliom Breast carcinoma Non-small-cell lungcancer Non-small-cell lungcancer Non-small-cell lungcancer Pancreatic cancer Pancreatic cancer Melanom Prostate cancer Melanom Biliary cancer Thyroid cancer Thyroid cancer Melanom Melanom Soft-tissue sarcom Soft-tissue sarcom Pancreatic cancer Non-small-cell lungcancer Melanom Gliom Gliom Gliom Prostate cancer Cancer ofunknownprimary Non-small-cell lungcancer Prostate cancer Prostate cancer Pancreatic cancer Pancreatic cancer Pancreatic cancer Pancreatic cancer Pancreatic cancer Thyroid cancer

c ′ ) In-frame intragenic ) intragenic In-frame nature medicine nature a a a a BRAF a a a a a fusions a a 3 4 . - - © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. immunotherapy regimen, rapid tumor regression was observed. Line charts show relative tumor size based on Response Evaluation Criteria in Solid Tumors lesion. A pathogenic germline prostate cancer with an MMR signature (19 mutations, including 6 frameshift indels) and no clear underlying somatic or germline MMR pathway samples with a high mutation burden, dominant MMR signature and inferred MSI. ( (iii) MSIsensor score, (iv) indel-to-SNV (single-nucleotide variant) ratio, (v) reported smoking status and (vi) cancer type. ( mutations explained by the major signatures (colored). Tracks below the bar charts indicate (i) ( mutation signature is shown for each principal tumor type. high mutation burden. ( ( indicates the frequency of samples with a given TMB. The red line indicates the threshold for samples with a high mutation burden (13.8 mutations/Mb). burden (TMB), defined as the number of nonsynonymous coding mutations per megabase, for common principal tumor types. The width of each plot Figure 5 dimerization that from RAF inhibit novel drugs benefit ing these harbor Patients progression. and initiation tumor of driver pendent therapy, suggesting that this alteration can also arise nature medicine nature (RECIST) criteria and serum prostate-specific antigen (PSA) levels. MRI images show the decreasing tumor size at indicated time points. Scale bars, 10 cm. d b ) Individual tumors harboring dominant mutation signatures. Bar charts display the total number of coding mutations (gray) and the fraction of ) The distribution of observed mutation rates across all tumors sequenced was used to identify a threshold of 13.8 mutations/Mb (red line), indicative of d a e Endometrial cancer Somatic mutation burden Germ cel Somatic mutation burden (mut/Mb) 100 200 300 500

(mut/Mb) Soft-tissue sarcoma 10 50 100 200 300 400 1 5 Mutational signatures derived from MSK-IMPACT targeted sequencing data. ( BRAF Esophagogastric carcinoma 0 l tumor POLE Colorectal cancer (

n Prostate cancer type Tumor =18) deletions, either acquired or acquired either deletions,

Thyroid cancer Melanom Bladder cancer ( n advance online publication online advance c =64) ) Dominant mutation signatures identified in cases with a high mutation burden. The percentage of cases harboring a dominant ( n Biliary cancer a =8)

MUTYH Ovarian cancer Renal cell carcinoma MMR Esophagogastric carcinoma Endometrial cancer Prostate cancer

variant was detected, which may contribute to the MSI phenotype. Upon initiation of treatment on an anti-PD-L1 Pancreatic cancer Small-bowel cancer Bladder cancer Ampullary carcinoma Biliary cancer ( Breast carcinoma n Breast carcinoma Head and neck carcinoma Cancer ofunknownprimary Head andneckcarcinoma =8) Non-small-cell lungcancer Pancreatic cancer Skin cancer,nonmelanoma Soft-tissue sarcoma Thyroid cancer Uterine sarcoma ( de de novo ( n Pancreatic cancer Breast carcinoma n =3) ( =5) n =1) Esophagogastric carcinoma ( ( n n ( =1) n ( =1) ( n =1) n =1) =1) ( de novo n =1) , may potentially , may potentially ( ( n ( Glioma

n POLE n =1) =1) =1) ( n Smoking =1) 3 Prostate cancer Skin cancer,nonmelanoma Endometrial cancer

Non-small-cell lung cancer 6 . as an inde , POLE f

-associated hypermutation; MMR, mismatch-repair deficiency; TMZ, temozolomide. Colorectal cancer Percent change in Baseline (day0) tumor size - - (RECIST v1.1) −100 −5 Non-small-cell lungcancer Colorectal cancer dict the likelihood of response to new therapies, including immune immune including therapies, new to response of likelihood the dict mutation of presence the signatures may of inform the an etiology individual’s and disease pre mutations, somatic individual Beyond Mutation signatures and somatic hypermutation 0 0 Melanoma

5 0 Bladder cancer f ) A 55-year-old patient with castration- and enzalutamide-resistant a ) Violin plots show the distribution of the somatic tumor mutation Time (d 0 Day 38 POLE Esophagogastric carcinoma Somatic mutatio ) burden (mut/Mb) Head andneckcarcinom Glioma b c Non-small-cell lungcancer Head andneckcarcinoma

100 Density mutation status, (ii) MMR pathway mutation status, UV Soft-tissue sarcoma 0 Endometrial cancer Breast carcinoma Colorectal cancer Prostate cancer Bladder cancer n

PSA (ng/ml) Melanoma a 10 1 Glioma 0 5 Day 78 0 −150 Thyroid cancer Biliary cancer 13. 2 8 −100 2 0 Percent ofcaseswith dominant signatur 5 5 0 −5 e 0 0 Other Soft-tissue sarcoma Time (d ) Tumor type distribution for 7 0 Day 120 TM ) e 5 3 Z > 0 50 100 Indels/SNVs MSIsensor score 1 0 0 0 MMR mutationeffect POLE Reported smokingstatu n n n n n n n n n n n =255 =118 = 11 = 19 = 64 = 18 = 30 = 19 = 39 = 124 = 124 Exonuclease 2 0 Missens Unknown Never .3 100 3 0 0. mutationlocation 0 6 s e l c i t r a 4 0 .9 0 40 Signatur T e Former/current Other UV POLE TM Smoking MMR BRCA1/ APOBEC Agin Z runcatin g e Nonexonucleas 2 s g e  -

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. an orthogonal bioinformatics approach, MSIsensor microsatelliteof evidenceinstabilityaccordingsamples had(MSI),to 0.06, versus 0.46 signatures(median other or increased indel-to-substitution ratio as comparedoverall anto tumorshad with also signatures MMR with samples the Furthermore, and were associated with underlying loss-of-function somaticpredominated mutations. in colorectal cancer and endometrial cancer, respectively, lungcancer ( zolomide and cigarette smoke predominated in melanoma, glioma and Table 7 representativezolomide)in ( tumortypes orcigarette smoke) and exposure to prior therapy (for example, temo exogenousexposuretomutagensciency), (forexample,radiationUV ( withintrinsic defectsDNAin repair (forexample, DNA polymerase tures described previously each sample to constituent mutation signatures from the set of 30 signa (>13.8 mutations/megabse (Mb); nonsilent substitutions in the 994 cases (9%) with elevated mutation rates atedthat processes produce with biological mutationhigh rates. associ signatures revealing of capable potentially thus and processes firming that MSK-IMPACT results were representative of genome-wide ( correlation high a revealed cohort ( this in tumors 106 type from data WES matched cancer to Comparisons each for rates calculated mutation first of we distribution data, the capture targeted from inferred be could signatures mutation whether determine To inhibitors. checkpoint alterations. gene different of basis the on trials clinical in as defined are Colors tumor. neuroendocrine GNET, gastrointestinal types. tumor across ( displayed. is patients all across actionability of level highest the of distribution The 3B). (2B, type tumor a different or 3A) (2A, type tumor pertinent the for existed evidence the whether to according subdivided 3 were 2 and Levels 3). (level trials agents clinical in investigational to response predict or 2) (level therapies standard-of-care to response predict 1), (level biomarkers FDA-recognized are mutations whether to according varied evidence of levels Briefly, alteration. actionable most the of level the to assigned were samples and OncoKB, to according 6 Figure A  classification MSI and signature MMR dominant a both harboring POLE

a c Altogether, we identified 102 individuals across 11 tumor types types tumor 11 across individuals 102 identified we Altogether, andsilent observed nucleotideall contextpatternandUsingof the s e l c i t r

Number of patients enrolled in a Level 3B Level 3A Level 2B Level 2A Level targeted clinical trial 100 150 )-associated hypermutation or mismatch-repair (MMR) defi (MMR) mismatch-repair or hypermutation )-associated ). As expected, the signatures associated with UV radiation, temo 50

1

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Fig.5 BRAF ERBB2 drug responseinanotherindication biomarker asbeingpredictiveof Compelling clinicalevidencesupportingthe response inthesameindication biomarker asbeingpredictiveofdrug Compelling clinicalevidencesupportingthe FDA-approved druginanotherindication Standard ofcarebiomarkerforan FDA-approved druginthesameindication Standard ofcarebiomarkerforan FDA-approved druginthesameindication FDA-recognized biomarkerforan

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Other The The tumor of with proportion mutations the types highest actionable ( a predictive biomarker of drug response. Altogether, 36.7% of patients specific manner, according to the level of evidence that the mutation is ( actionability clinical of tiers into mutations all group to mutations, somatic of implications treatment and effects oncogenic the of base to Wetreatment guide decisions. OncoKB, a used knowledge curated profiling molecular of utility prospective the clinical evaluate atically we and attempted by to system broadly such anecdotes, Encouraged Clinical actionability and utility ( treatment to response marked a exhibited and has regimen immunotherapy of an anti-PD-L1 trial on a clinical causal somatic or germline lesion. As a result, the patient was enrolled an revealed unanticipated MMR signature without a clear underlying in MSK-IMPACT performed, cancer rarely is a testing MSI conventional cancer, which prostate with patient 55-year-old a of case the In cancers. bladder and prostate gastric, endometrial, colorectal, in were observed or tumor regression) disease immunotherapy radiographic-stable (i.e., to responses cohort, our in MSI showing tumors with patients the Among immunotherapy. from benefit could potentially who patients of number the expand substantially may filing trials clinical inhibitors and an ‘basket’ for enrollment criterion immuno-oncology checkpoint immune to response for biomarker a as used being ingly increas is status MSI As the burden. mutation to highest the with restricted patients is it as cohort, our in phenotype MSI the of lence MMR deficiency. Notably, this analysis may underestimate the preva ( MSIsensor by Level 2B(9% n http://oncokb.or = 3,792 patients) harbored at least one actionable alteration ( a AL Level 2A(2% ) Alterations were annotated based on their clinical actionability actionability clinical their on based annotated were ) Alterations ROS1K Level 1(7% )

RE NTRK T Fusion FGFR 3 NTRK ) a 2 . . ( 3 ) )

9 Other1 c , our results suggest that comprehensive genomic , pro that genomic comprehensive our suggest results Fig. 5 Fig. advance online publication online advance ) Number of patients enrolled on genomically matched matched genomically on enrolled patients of ) Number g b Gastrointestinal stromaltumor / ) Skin cancer,nonmelanoma Esophagogastric carcinom Cancer ofunknownprimary 4 e Non-small-cell lungcancer Head andneckcarcinoma 0 Hepatocellular carcinoma ), 45% of whom were not previously tested for tested previously not were whom of 45% ), . Mutations were classified in a tumor type– tumor a in classified were Mutations . Non-Hodgkin lymphom Small-cell lungcancer Renal cellcarcinoma b Soft-tissue sarcom Appendiceal cancer Endometrial cancer Salivary carcinoma ) Distribution of levels of actionability actionability of levels of ) Distribution Pancreatic cancer Colorectal cancer Breast carcinoma Embryonal tumor Uterine sarcoma Germ celltumor Prostate cancer Cervical cancer Ovarian cancer Bladder cancer Thyroid cancer Osteosarcoma Mesothelioma Biliary cancer Melanom Gliom GNET a a a a a 2 0 Fig. 5 Fig. Percent ofpatients

5 5 f nature medicine nature ). 7 0 5 Fig. 6

100 a ). - - - -

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. resource for identifying novel biomarkers to inform prognosis and and prognosis inform to biomarkers novel identifying for resource outcome,and disease-specific this data set will prove a transformative response of treatment annotation clinical With maturing mutations. actionable clinically unanticipated and uncommon of detection the the of prevalence driver alterations across all cancers and allowing for of an understanding improved providing types, tumor detailed >300 encompasses cohort our Further, therapies. targeted molecularly for considered be to likely most population the of representative were and treated, who heavily who were frequently disease, with advanced patients of exclusively almost composed was cohort our efforts, tion characteriza genome tumors large-scale most Unlike patients. 10,945 10,336 from in rearrangements genomic and CNAs mutations, reviewed manually of set data expansive an generated have we tive, initia this Through results. of utilization and interpretation clinical panel is feasible and achievable within a turnaroundcancer time that permits comprehensive a using samples blood matched and tumors of sequencing enterprise-scale that demonstrate We malignancies. tumor solid all spanning tumors with for patients therapies matched genomically of selection the guide to effort sequencing clinical tive We of prospec a large experience institution-wide, the overall report DISCUSSION types. tumor across profiling molecular broad of importance the and contexts clinical diverse in therapies targeted of efficacy tial and those with melanoma was identical (71%), the reaffirming poten patients these among measurement by radiographic assessed benefit rate the was smaller, of than clinical inhibitors BRAF receiving melanoma other type tumor a with patients of proportion the Although trial. on or off therapy BRAF-targeted received (36%) patients of the 75 of which histologies, nonmelanoma with patients 211 in detected Moreover, immunotherapy. first-line ing single a as receiv largely patients remaining inhibitors the with combination, BRAF in or agent with treated were (53%) 41 these patients, Among biomarkers. (FDA)-approved Administration Drug are mutations and US Food these for which melanoma, with patients example, an IMPACT. As MSK- by revealed as genotype patient of basis the on administered ( genes separate >50 in alterations of basis the on to trials were matched patients pathways, signaling and PI3K MAPK at our institution. Although the most common targets belonged to the their in tumor on at agents targeted 1 least aberration of involving molecularly 197 trials target a of basis the on enrolled 527 patients were (11%) There analysis. this before year 1 least by at tested MSK-IMPACT patients 5,009 considered we course, treatment full their during therapy targeted receive eventually may patients many how to assess has elapsed that time not enough Acknowledging genotype. on tumor based trials clinical matched on of genomically enrollment rate the examined first we the testing, MSK-IMPACT of evaluate utility to clinical begin To considerations. logistical and medical to owing therapy, matched genomically receive would alterations able in acknowledging the current limited ability to intervene therapeutically investigation under modalities ment analyses other in able in such oncogenes, additional as ( (58%) melanoma and (61%) cancer were gastrointestinal stromal tumor (76%), thyroid cancer (61%), breast nature medicine nature therapy.to resistance and response predict We next considered additional cases where standard therapy was was therapy standard where cases additional considered Wenext action potentially with of patients a subset only that We expected KRAS mutations with drugs presently available in the clinic. the in available presently drugs with mutations advance online publication online advance 41 , 4 2 and may soon become targetable by treat by targetable become soon may and BRAF KRAS V600 mutations were detected in 77 77 in detected were mutations 43 Fig. 6 Fig. , , have action considered been , 4 4 , we used stricter criteria, criteria, stricter used we , BRAF b ). Although mutations mutations Although ). V600 Fig. 6 Fig. mutations were were mutations

c ). ------

geographical accessibility of relevant trials, as well as patient pref patient as well as trials, relevant of accessibility geographical and availability the in shortcomings systemic reflects gap This trial. MSK-IMPACT receive testing were on enrolled subsequently a to matched genomically clinical patients 5,009 first the of 11% and tion, altera relevant clinically a harbored patients of 37% that observed to ability treatment influence decisions and improve its outcomes for to patients. We according measured is sequencing clinical spective of pro value true the and metastasis, progression cancer govern that mutations patients to with selected studies their pertinent and areclinicians automaticallyin real time to alerted the presence of data and forpharmacological database integration clinical other with institutional an MSK-IMPACT to all transmitted are whereby results process a established have we institution, our at trials clinical guided text evaluate the degree to which responses are determined by disease con tion, irrespective of their histology, have emerged as an efficient way to patients in which are altera on genetic enrolled of the basis a specific trials Basket types. cancer different in therapies targeted molecularly of efficacy the test to needed are designs trial clinical flexible Novel, patients with the opportunity to receive a genomically matched therapy. actionable mutations, broad molecular profiling is necessary to provide all data sets. To this end, we have deposited our full data set into the the that into expectation and It hope our is set Genomics. Cancer for data cBioPortal full our deposited have we end, this To sets. data resulting of the potential discovery full the to realize order in mount para is sequencing tumor in engaged institutions and across laboratories sharing data Additionally, follow-up. longitudinal detailed, require will studies These outcomes. patient on genomics cancer cal of clini effects long-term the to assess more are needed studies systematic sequencing, tumor prospective large-scale of impact clinical information. this receive to wish who patients to reported are sis whereby variants pathogenic by inherited detected MSK-IMPACT review board (IRB)-approved process for prospective germline analy members family their in susceptibility cancer suggest and defects) repair DNA with patients in PARP inhibition example, (for patients in therapy to response ate medi may which alleles, germline pathogenic reveal can tissue mal nor from DNA of analysis direct Moreover, immunotherapy. from benefit to stood who patients highly identifying in thereby tumors, signatures mutated mutation distinct detect and patient each for burden mutation overall the determine us to accurately allowed This of the through elimination rare variants and germline specificity able to unambiguously somatic call mutations with greater sensitivity By DNAsequencing from both the tumor and normal we blood, were sion of patient-matched normal DNA for tumor every that is profiled. testing. of time turnaround the in reductions and therapies targeted novel of approval the trials, cal continue to increase with the proliferation of molecularly driven clini will sequencing clinical prospective broad, of utility clinical the that We trials. FDA-approved of outside clinical therapies expect targeted received who patients additional hundred for several not do account trials profiling tumor NGS-based clinical following on enrollment of rates lower reporting studies prior of light in encouraging are results our Nevertheless, protocols. ment receive later targeted therapymay continued who to benefit from conventionalothers treat conversely, and, trial, clinical a for qualify to debilitated too been have may patients many Additionally, erences. Although our results provide insights into the biological processes processes into biological the insights provide our results Although potentially harbor can that types tumor the of diversity the Given Although this study represents a first step toward evaluating the the evaluating toward step first a represents study this Although inclu the is approach our of utility clinical the enriching Further 5 . To facilitate patient identification and enrollment for genomically 5 0 . We have thus established an institutional institutional an We. established thus have 9 , 41 , 46 , 4 7 . Further, these results results these Further, . s e l c i t r a 4 5 . 48 , 4 9  ------.

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. 12. 11. 10. 9. 8. 7. 6. 5. 4. 3. 2. 1. claims jurisdictional in published maps and affiliations. institutional reprints/index.htm at online available is information permissions and Reprints The authors declare no competing interests.financial the institutional molecular profiling protocol. All authors reviewed the manuscript. for the MSK-IMPACT sequencing initiative. D.M.H.M.E.R., and D.B.S. developed J. Coleman, B.B., G.J.R., L.B.S., H.I.S., P.J.S., D.S.K., J.B. and D.B.S. provided support tools and systems to support data analysis, annotation and dissemination. Z.J.H.,R.K., H.-W.C., S.P., H.Z., J.W., A.O., B.S.T. and N.S. created bioinformatics A.Z., A.S., J. Gao, D.C., D.T.C., M.P., M.H.S., A.B.R., Z.Y.L., A.A.A., A.V.P., B.E.G., P.R., A.N.S., N.S., T.E.S., A.M.V., R.Y., D.M.H. and D.B.S. provided clinical data. M.M.G., A.A.H., J.J.H., G.I., Y.Y.J., E.J.J., C.M.K., M.A.L., L.G.T.M., A.M.O., N.R., J.W., M.E., S.B.T., S.M.G., D.N.R., J. Galle, R.D., R. Cambria, W.A., A.C., D.R.F., reviewed and analyzed the genomic data. M.D.H., D.A.B., A.M.S., H.A.-A., E.V., P.J., N.C., M.T.C., H.H.W., B.S.T., N.S., D.M.H., M.E.A., D.B.S., M.L. and M.F.B. D.F.D., J.Y., D.L.M., D.T.C., R. Chandramohan, A.S.M., R.N.P., G.J., K.N., L.B., A.Z., R. Benayed, S.M., P.S.,R.H.S., H.R.K., S.M.D., M.H., S.D., D.S.R., J.F.H., R. Bacares, I.J.K., J.B.S.,A.R., L.S., T.B. and K.A.M. generated the genomic data. A.Z., R. Benayed and M.F.B. wrote the manuscript. R. Benayed, J.S., J. Casanova, Center for Molecular Oncology. the Survival, Farmer Family Foundation, and the Marie-Josée and Henry R. Kravis supported by the MSK Cancer Center Support Grant (P30 CycleCA008748), for E. Paraiso and J. Rudolph for their important contributions. This study was C. Ho, S. Naupari, J. Arlequin, C. L. Carvajal, Tovar Ramirez, J. P.Bakas, Sukhadia, G. Jour, N. Sadri, K. Tian, C. Pagan, J.K. Killian, D. Alex, J. Gomez-Gelvez, E. Gallagher, I. Rijo, N. Mensah, G. Lukose, T. Mitchell, A. Yannes, Y. Chekaluk, We gratefully acknowledge C. England, J. Somar, T. Malbari, P. Salazar, S. Islam, online version of the pape Note: Any Supplementary Information and Source Data files are available in the pape the the in available are references, and codes accession statements of including Methods, and data availability any associated M cancer. with patients more benefit to options treatment effective more of extension and development the and targets drug of promising identification the enable will efforts data-sharing other and this A 1 COMPETING FINANCIAL INTERESTS FINANCIAL COMPETING AUTHOR CONTRIBUTIONS A 0 cknowledgments

et

s e l c i t r

Cerami, E. Cerami, D.T. Cheng, L.M. Sholl, H. Beltran, G.M. Frampton, Roychowdhury,S. R.R. Singh, Hyman, D.M. P.B.Chapman, N.I. Lindeman, biology genome through Berger,M.F.oncology & clinical A.M. Varghese,Advancing paradigm. emerging an for framework oncology: Genomics-driven Garraway,L.A. multidimensional cancer genomics data. genomics cancer multidimensional oncology. next- Diagn. molecular tumor capture–based solid for hybridization assay clinical sequencing a generation (MSK-IMPACT): targets cancer actionable population. cancer unselected response. treatment (2013). 1023–1031 profiling test based on massively parallel DNAsequencing. parallel onmassively based test profiling study. pilot a sequencing: mutationalhotspotscancer-related 46in genes. mutations. mutation. V600E Pathology. Molecular for Association and Cancer, Lung of Study the for Association International Pathologists, College American the of from guideline inhibitors: kinase tyrosine ALK and EGFR for patients technology. and Oncol. Clin. h ods

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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. (R. Chandramohan). (R. Chandramohan). New York, New York, USA. 10 Memorial Sloan Kettering Cancer Center, New York, New York, USA. New York, New York, USA. Memorial Sloan Kettering Cancer Center, New York, New York, USA. New York, New York, USA. Memorial Sloan Kettering Cancer Center, New York, New York, USA. 1 nature medicine nature Department Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Department Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 13

These These authors contributed equally to this work. should Correspondence be addressed to M.F.B. ( advance online publication online advance 12 7 4 Information Information Systems, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Present Present addresses: Illumina, Inc., San Francisco, California, USA (D.T.C.) and Baylor College of Medicine, Houston, Texas, USA

3 9 6 Department Department of Epidemiology and Memorial Biostatistics, Sloan Kettering Cancer Center, Department Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, 2 Marie-Josée Marie-Josée and Henry R. Kravis Center for Molecular Oncology, 11 Department Department of Pediatrics, Memorial Sloan Kettering Cancer Center, 8 [email protected] Clinical Clinical Research Administration, 5 Department Department of Radiation Oncology, ). s e l c i t r a

11 © 2017 Nature America, Inc., part of Springer Nature. All rights reserved. used to recalibrate base-quality scores base-quality recalibrate to used GenomeAnalysisToolkitthementand artifacts, (GATK; BroadInstitute) was based realigner (ABRA) was used to realign reads around indels to reduce align werehumanalignedtothe genome (hg19) using BWA MEM initiates the analysis pipeline upon the end of the sequencing run. Sequence reads Tumor samples were to sequenced a mean unique depth of coverage of 718×. ments were onsequenced an Illumina HiSeq 2500 as paired-end 100-bp reads. using custom-designed biotinylated probes (NimbleGen). Captured DNA frag mal samples were combined in pools of 24–36 libraries for multiplexed capture and low-cycle PCR amplification (Kapa Biosystems). Tumor and matched nor ing shearing, end-repair, A-base addition, ligation of barcoded sequenceies wereadaptors prepared on the Biomek FX (Beckman Coulter) before shearing on the Covaris instrument. Sequence librar 55 preparation and sequencing. clinical next-generation sequencing laboratory for further quality the to control, transferred then wereDNA samples Extracted elution.library subsequent and allowing for the high-affinity binding of nucleic acids to M-PVA magnetic beads STAR DNA Tissue-10 and Chemagic STAR DNA Blood-400 kits (PerkinElmer), the breakdown of proteins.detrimental DNA was isolated using the Chemagic and blood samples were lysed, followed by digestion with a protease to catalyze deparaffinized using mineral oil followed by digestion with were tissues FFPE proteinase (PerkinElmer). technology bead magnetic chemagen Kusing enzyme, formalin-fixed, paraffin-embedded (FFPE) tumors and matched normal blood extraction was performed on the chemagic STAR instrument (Hamilton)DNA from Genomic extraction. nucleic before necessary was region tumor cated indi the of macrodissection whether and tumor purity tumorincludingtype, fellow and pathology annotatedmolecular for relevant information, specimen a by reviewed was slide H&E-stained an accessioned, Once (MRN). number were paired for simultaneous sequencing using a patient-unique medical record samples blood normal Tumormatched recorded. and was sections unstained detailed description of the specimen was submitted and the number number, ofaccession a molecular unique a submittedlaboratory,wereassigned they where Service Diagnostics Molecular CLIA-compliant the by accessioned were ing for MSK-IMPACTsamplesreceived All genes. rearranged recurrently 17 test of promoter the genes, target of exons coding in used this study. Synthetic DNA probes were to designed capture protein-all MSK-IMPACT panels containing 341 genes and, more recently, 410 genes were Evaluation Laboratory of Program. HealthDepartment TwoClinical different YorkNew the by Stateuse approvedclinical andfor validated been has it and rearrangements, structural select and alterations number copy deletions, and insertions small mutations, sequence detecting of capable is MSK-IMPACT mutations). germline and (somatic cancer human in genes mutated quently at Memorial trials cal Sloan Kettering Center (MSKCC),Cancer as well as fre clini in investigated being therapies experimental of targets are or therapies tion capture–based assay encompassing all genes that are druggable by approved MSK-IMPACT workflow. sequencing OncoTree ( system, of nomenclature tumor types, tumors wereuniform annotated according ensure to Toan institutional classification 2016. May and 2014 January between types tumor principal 62 across patients unique 11,369 for requested was ing test MSK-IMPACT total, In DNA. (germline) normal matched of source a as drawn was blood and obtained were samples tumor new or archival either consent, Following funds. philanthropic and institutional using for paid was MSK-IMPACT testing that was not submitted for reimbursement by insurance All research. for specimens banked of characterization genomic broader and (MSKCC; in on >85% of enrolled IRB-approved protocol an research cases, institutional or,form consent a clinical signed MSK-IMPACT testing undergoing Patients relevant genomic alterations that could potentially clinically inform treatment decisions. identify to physician treating the by ordered was cancer advanced accrual. and consent Patient ONLINE MET nature medicine nature Sequencers were monitored by an automated data management system, which in diluted and input of ng 50–250 yield to normalized were samples DNA µ l of TE buffer on the Biomek FX Biomek the on buffer TE of l NCT0177507 H ODS http://www.cbioport 2 ) permitting return of results from clinical sequencing MSK-IMPACT testing for patients with with patients for testing MSK-IMPACT P through a series of enzymatic steps includ P 52 MSK-IMPACT custom a is hybridiza Laboratory Automation WorkstationAutomation Laboratory , al.org/oncotree 5 3 . Duplicate reads were marked for marked were reads Duplicate . TERT and selected introns of introns selected and / ). 5 1 . Theassembly-. ------

owing to the risk of false negatives. In total, 10,945 cases were successfully successfully were cases forsequenced a assayfinal success rate10,945 of 86%. total, In negatives. false of risk the to owing <200×, was coverage sequence unique average the or <20% was purity tumor able alterations (including silent mutations) were also excluded if the estimated coverage (<50×) and evidence of sample contamination. Samples with no detect one of multiple quality control metrics, including low average unique sequence Of the extraction. that11,549 cases for qualified 604 sequencing, failed at least DNAfollowing ng) (<50 DNAyield low and review histopathology on based were deemed insufficient for sequencing according to low tumor purity (<10%) ted for MSK-IMPACT sequencing between January 2014 and May 2016. Cases protocol and bioinformatics analysis were described previously physiciansand electronicrecord.laboratorymedicalthroughdetailedthe The patients to back reported and database clinical-grade a in stored were results hgvs.org compliant with the Human Genome Variation Society (HGVS; separately were merged and represented properly, and mutationreviewed annotationsto ensure werethat no false positives manuallywere was pipeline the byreported, alterationidentified DNA.Each blood matched complex events identified Delly using fied using an algorithm developed in house, and structural variants wereincluding detectedSNVs and short and long indels. Copy number alterations were identi jected to automated filtering to generate a complete list of somatic callsmutation made bycalls, MuTect removal, and the resulting BAM files were used for variant discovery. The union of specimen was collected and the date of death or last follow-up.tumor the when dateOnly procedure the cases between wheretime the as defined was survival rank test and tumorKaplan–Meier within select Overall types. curves survival somatic survival. and status mutation promoter TERT ( types cant. Residual sum of square (RSS) values were calculated for individual tumor and greater than five individual patients in either cohort were reported as adjusted signifi an below fell that Genes method. Benjamini–Hochberg the using performed was testing multiple-hypothesis for Correction results. TCGA IMPACT and MSK- between frequencies alteration gene-level compare to performed were alteration frequencies for each of the genes in the MSK-IMPACT panel. considered. gene-level obtain to aggregated were were samples patient individual Mutations in mutations silent excluding indels and mutations Coding results were compared to TCGA studies for the corresponding tumor subtypes. Comparison to the mutational landscape of primary tumors. variant ofallele fraction 0.05. minimum a and reads unique 8× ofcoverage mutant minimum allele a reads, unique 20× of coverage total minimum a required we filters, calling variant for mutation. each determined To matchof our MSK-IMPACT stringency the were simulated. Downsampled total coverage and mutated allele coverage were 100× and 150× 200×, 250×, of300×, samplecoverage). Exomecoverage levels sample coverage/mean (simulated factor: following the MSK-IMPACTbyby identified mutation each supporting reads sequence underlying the sampled bined target region. com the within fell location its whether to according IMPACT classified was Cancer Hotspot Panel (v2) was considered. mutationEach byidentified MSK- of all targets of the Illumina TruSeq Amplicon Cancer Panel and Ion AmpliSeq union the assays, sequencing amplicon-based from attainable those to results Comparison to other tumor-profiling strategies. and capture was 75%. sequencing preparation, library extraction, DNA repeating of by rate cases rescue failed overall The available. if block, different a from initial or the in extraction used block surgical same the from either obtained were mens speci New possible. whenever attempted was contamination sample obvious A total of 12,670 tumor samples from 11,369 unique patients were submitwere patients unique 11,369 from samplestumor 12,670 of total A To compare MSK-IMPACT results to those attainable from WES, we down or (<50×) coverage low either to owing failed that cases of Resequencing Supplementary Supplementary Fig. 10 TERT / P ). Following curation and review of MSK-IMPACTof review Followingsequencingandcurationdata, ). -value cutoff of 0.05 and were altered in greater than 1% of patientsof 1% than greater in werealtered and 0.05 of cutoff -value 5 6 . Germline variants were eliminated through the use of patient- of use the through eliminated were variants Germline . promoter mutations and overall survival was evaluated by the log- 5 4 , Pindel 5 ). 5 and Somatic Indel Detector To compare MSK-IMPACT The association between between association The doi: 5 2 were further sub 10.1038/nm.4333 h 1 ttp://varnomen. MSK-IMPACT 1 . χ 2 tests ------

© 2017 Nature America, Inc., part of Springer Nature. All rights reserved. mutations explained by each given signature. A sample was determined to of have percentage the to corresponded that weight a assigned was signature each described previously been had that signatures 30 from built tion approxima the and signaturesample the between minimized was divergence Kullback–Leibler the which in analysis decomposition to subjected then and times 1,000 resampled were mutations These subtypes. mutation possible 96 T>C, T>G) and the bases immediately 5 according to distribution of the six substitution classes (C>A, C>G, C>T, T>A, burden of mutation a with Samples range. interquartile the is IQR where IQR(TMB), × 2 + median(TMB) formula: following the mutationalusing ofsignatures, tion identifica the for suitable tumors mutated highly considering for threshold signatures. Mutational mutations were reported, according to the version of the assay that was used. mutations reported by the MSK-IMPACT assay by the total genomic area where TMBfrom MSK-IMPACT by was calculated dividing number the of sequence length of the total genomic target region captured with the exomewas calculated asassay. the total number Similarly,of nonsynonymous mutations divided by the TMB artifacts. systematic known coverage,and allele-level and total normals, were filtered for various criteria, including recurrence in previously sequenced found at MuTectusing GATKtified be and can HaplotypeCaller.pipeline analysis The processing using the Picard MarkDuplicates tool and GATK. Variants were were aligned to the iden human genome (hg19) using BWA MEM, followed by post- reads Sequencing 240×. of coverageaverage an to 2500 HiSeq Illumina an on tumor samples were recaptured using the Agilent Exome Kit (v3) and sequenced Comparison of mutation rates for MSK-IMPACT and WES. Laboratory Evaluation Program. for clinical use at MSKCC by the New York State Department of Health Clinical Archer Software (v4.0.10). This custom assay has validated been and approved using analyzed were Data MiSeq. Illumina an on sequenced were amplicons specific primers, enriched for known and novel fusion transcripts. Final targeted involved in chromosomal rearrangements. GSPs, in combination with adaptor- primers (GSPs) were to designed target exonsspecific in 35 genes known to be next-generation sequencing to detect gene fusions. Unidirectional gene-specific technology (AMP) PCR MultiplexAnchored Archer utilizes that panel was analyzed using the MSK-Solid Fusion assay, a custom-targeted, RNA-based the fusion partner gene was not clear, total RNA from extracted FFPE material RNA fusion detection. with respect to the breakpoint at which the structural variant was called. and UniProt was used to determine the genomic location of the kinase domain UCSC table browser fusions, we downloaded the RefSeq and UniProt sideredtracks for GRCh37/hg19 fromcon were kinases theprotein 521 fusions, kinase of analysis the For known. was fusion database be found at reviewed using the Integrative Genomics Viewer manually and tools in-house using annotated wererearrangements structural harbored discordant reads with mapping quality of harbored tumor the if or rearrangements) recurrent known of (sites reads mapping quality of harbored tumor the if review manual for flagged sions were removed if the length was <500 bp. Candidate rearrangements were inver and duplications Deletions, rearrangement. underlying the supporting (v0.6.1) Delly by rearrangements. genomic Novel included in the analysis. the procedure occurred less than 1 year before MSK-IMPACT sequencing were doi: Contributions of different mutation signatures were identified for each sample ToCOSMIC(v77)novelidentifyused fusion partners,we 10.1038/nm.4333 5 9 https://gi . To determine the involvement of kinase domains in predicted kinase ≤ ≥ 1 discordant read (novel rearrangement sites). All candidate somatic 13.8 13.8 nonsynonymous mutations/Mb were analyzed. https://gith 5 8 5 , as well as literature review thub.com/soccin/BIC- 6 on the basis of the detection of read pairs and split reads reads split and pairs read of detection the of basis the on ≥ 6 5 5 and the matched normal sample harbored 0 . RefSeq was used to determine the transcript orientation, For complex DNA rearrangements where the identity of ub.com/rhshah/IMPACT-S The overall TMB distribution was used to identify a identify to used was distribution TMB overall The Somatic structural variants were identified identified were variants structural Somatic variants_pipelin ′ and 3 ≥ 20 20 and the matched normal sample 3 3 , to determine whether a partner ′ of the mutated base, producing 5 7 . The current framework can V ≥ . 3 discordant reads with a with reads discordant 3 e . Candidate mutations 1 Libraries for 106 5 and the TCGA theand ≤ 3 3 3 discordant 7 , such that such , 6 1 and ≥ 5 - - - - -

dence dence for any mutation byidentified MSK-IMPACT Tumor evi of3B). (2B, level highest the sampleswereannotatedto according exists evidence for the pertinent tumor type (2A, 3A) or a different tumor type (level 3). in 2 Levels trials clinical and 3 were accordingsubdivided to whether standard-of-care therapies (level 2) or predict response to investigational agents ing to whether they are FDA-recognized biomarkers (level 1), predict predictiveresponse biomarkerto of drug response. Briefly, mutations were classified accord manner,type–specific according that toof mutation level the the evidence is a somatic mutations ( a curated knowledge base of the oncogenic effects and treatment implications of mutations, copy number alterations and rearrangements according to OncoKB, byMSK-IMPACT, mutationsof detected actionability annotatedsequence we trials. clinical to matching and assessment Clinical genome as compared to its matched normal. tumor the in unstable are that loci microsatellite of percentage the identifies to SNVs. We analyzed each also sample using the MSIsensor algorithm, which smoking status from our institutional database and calculated the ratio of indels tionsin ture 10); and TMZ (signature 11). For each sample, we identified somatic muta (signature 3); MMR (signatures 6, 15, 20 and 26); UV (signature 7); (signature 1); APOBEC (signatures 2 and 13); smoking (signature 4), that signature. to attributable were mutations observed the of >40% if signature dominant a 52. 51. com/soccin/BIC-variants_pipelin tion-si signature decomposition code can be found at can foundbe at http://cbio at Genomics forCancer cBioPortal the availablein studyarepublically this in Data availability. the MMR signature were evaluated using the Wilcoxon test. signed-rank samples. Comparisons of indel-to-SNV WES and MSK-IMPACTratios between between TMB samplesof correlation with Pearson and the without calculate different between groups.stratified The cor.test() fromfunction R was to used to calculate ‘survival’using with the R (v3.2) performed package. test A log-rank was used Statistical analyses. the initiation of therapy. from months 3 near or at regression tumor or disease radiographic-stable as therapydirected chart bywerereview. detailed assessed was defined Response remaining matches onbased the results of prior molecular testing. the MSK-IMPACT with the issued, after were reports matchesoccurred all of 72% target. drug the matching alterations genomic harbored (11%) 527 and agent targeted a with trial clinical a on enrolled were (16%) 811 trial, clinical any on enrolled were (38%) 1,894 2015, July MSK-IMPACTbefore by tested may notfor occur many months (or longer) after testing. Of the 5,009 patients regimens treatment to changes and results profiling molecular of utilization that given considered, were 2015) July (before IMPACTinitiative sequencing patients whose tumors were sequenced during the first 18 months of the MSK- be a target for at least one onclinical trial which the patient was enrolled. Only ‘matched’ to onealteration considered be atto harbored least ered orshe he if clinical trials were deemed to have a targeted aberration. A patient was consid 850 the of therapy, 197 each of action of mechanism and criteria enrollment by MSK-IMPACT was ever enrolled up to September 2016. After reviewing the obtained a list of 850 clinical trials open at MSKCC on which any patient tested For analyses in the manuscript, we focused on eight main signatures: aging aging signatures: main eight on focused manuscript,we the in Foranalyses Clinical responses for patients receiving immunotherapy and targeted BRAF- To determine the rate of enrollment to genomically matched clinical trials, we

cen, A. McKenna, Burrows–Wheeler with alignment read short accurate and Fast R. Durbin, & H. Li, (2010). data. sequencing DNA next-generation analyzing transform. gnature POLE portal.org/msk-impac P values, and Kaplan–Meier were to compareused curves survival Bioinformatics and mutations pathway MMR in automatically genes, retrieved s . . The WES data analysis pipeline can be found at https://github.com t al. et All genomic results and associated clinical data for all patients http://oncokb.org Survival analyses based on h Gnm Aayi Tokt a aRdc faeok for framework MapReduce a Toolkit: Analysis Genome The

25 , 1754–1760 (2009). 1754–1760 , t e . The MSK-IMPACT data analysis pipeline pipeline analysis data MSK-IMPACT The . /rhshah/IMPACT-Pipel . / ) 4 0 . . Mutations were classified in a tumor https://github.c TERT eoe Res. Genome 6 promoter mutations were 2 . To assess the clinical clinical the assess To nature medicine nature in e om/mskcc/muta . . The mutational

20 https://git POLE 1297–1303 , BRCA1 (signa hub. / 2 ------

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