patient-derived xenografts and matched cell ... ·...

Translational Cancer Mechanisms and Therapy

Patient-Derived Xenografts and Matched CellLines IdentifyPharmacogenomicVulnerabilities inColorectal CancerLuca Lazzari1, Giorgio Corti2, Gabriele Picco3, Claudio Isella2, Monica Montone2,Pamela Arcella2, Erika Durinikova2, Eugenia R. Zanella2, Luca Novara2, Fabiane Barbosa4,Andrea Cassingena5, Carlotta Cancelliere2, Enzo Medico1,2, Andrea Sartore-Bianchi5,6,Salvatore Siena5,6, Mathew J. Garnett3, Andrea Bertotti1,2, Livio Trusolino1,2,Federica Di Nicolantonio1,2, Michael Linnebacher7, Alberto Bardelli1,2, and Sabrina Arena1,2

Abstract

Purpose: Patient-derived xenograft (PDX)models accurate-ly recapitulate the tumor of origin in terms of histopathology,genomic landscape, and therapeutic response, but some lim-itations due to costs associated with their maintenance andrestricted amenability for large-scale screenings still exist. Toovercome these issues, we established a platform of 2D celllines (xeno-cell lines, XL), derived from PDXs of colorectalcancer with matched patient germline gDNA available.

Experimental Design: Whole-exome and transcriptomesequencing analyses were performed. Biomarkers of responseand resistance to anti-HER therapy were annotated. Depen-dency on theWRN helicase gene was assessed in MSS, MSI-H,andMSI-like XLs using a reverse genetics functional approach.

Results:XLs recapitulated the entire spectrumof colorectalcancer transcriptional subtypes. Exome and RNA-seq analy-ses delineated several molecular biomarkers of response andresistance to EGFR and HER2 blockade. Genotype-drivenresponses observed in vitro in XLs were confirmed in vivo inthe matched PDXs. MSI-H models were dependent uponWRN gene expression, while loss ofWRN did not affect MSSXLs growth. Interestingly, one MSS XL with transcriptionalMSI-like traits was sensitive to WRN depletion.

Conclusions: The XL platform represents a preclinicaltool for functional gene validation and proof-of-conceptstudies to identify novel druggable vulnerabilities in colo-rectal cancer.

IntroductionThe knowledge that cancer is a genetic disease and the avail-

ability of genomic profiles of tumor samples have paved the wayto "precision medicine" in oncology (1).

In the last ten years, major advances in complex genomictechnologies have strongly contributed to the mapping of cancermolecular landscape (2). The need to understand the impact ofthe major drivers of cancer development and progression ontherapeutic intervention has thus become of paramount impor-tance. Functional characterization and target validation requiresthe generation of reliable cellular and animal models to under-stand the role of genomic alterations on tumor onset and evo-lution (3). Functional studies have demonstrated that the tumoris often dependent on oncogenic alterations for its growth andmaintenance, providing a strong rationale for the development oftherapies targeting cancer driver genes (4).

On these premises, modeling disease-associated alterations inmodels that reflect the clinical features of patients is vital toimplement precision medicine. So far, different cellular andanimalmodels have been generated, each presenting both advan-tages and pitfalls.

Cancer cell lines have been extensively and routinely used forbiomarker discovery and drug development. Indeed, the CancerCell Line Encyclopedia, the Genomics of Drug Sensitivity inCancer (GDSC) Sanger Institute project, the National CancerInstitute-60 (NCI-60) cancer cell line screen, and the CancerTherapeutic Response Portal (CTRP) constitute paradigmaticexamples of how coupling cell lines to systematic compoundscreening can provide an informative clinical platform for phar-macogenomic analyses (5–10).Genomic and transcriptional driftduring serial passaging, loss of molecular heterogeneity and lackof the tumor microenvironment represent the three main issues

1Department of Oncology, University of Torino, Candiolo, Torino, Italy. 2CandioloCancer Institute, FPO - IRCCS, Candiolo, Torino, Italy. 3Wellcome SangerInstitute, Cambridge, United Kingdom. 4Department of Interventional Radiolo-gy,OspedaleNiguardaCa' Granda,Milan, Italy. 5Niguarda CancerCenter, GrandeOspedale Metropolitano Niguarda, Milan, Italy. 6Department of Oncology andHemato-Oncology, Universit�a degli Studi di Milano, Milan, Italy. 7Department ofGeneral Surgery, Molecular Oncology and Immunotherapy, University ofRostock, Rostock, Germany.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

A. Bardelli and S. Arena are the co-senior authors of this article.

Current address for L. Lazzari: IFOM-FIRC Institute of Molecular Oncology, Milan,Italy.

Corresponding Author: Sabrina Arena, Department of Oncology, University ofTorino and Candiolo Cancer Institute, FPO - IRCCS, Strada Provinciale 142,Candiolo 10060, Torino, Italy. Phone: 39-011-993-3223; Fax: 39-011-993-3225;E-mail: [email protected]

Clin Cancer Res 2019;25:6243–59

doi: 10.1158/1078-0432.CCR-18-3440

�2019 American Association for Cancer Research.

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thought to make cell line models divergent from the originaltumor. For these reasons, the lack of experimental reproducibilityand the clinical relevance of cell lines have repeatedly beenquestioned (11, 12). These drawbacks may play against therecapitulation of the evolutionary nature of cancer itself, thuslimiting the translation of the in vitro results to the clinicalresponse of the tumor in the patient. In addition, the unavail-ability of matched germline tissue has often hampered the con-fident identification of somatic changes.

To partly obviate these issues and better bridge the bench-to-bedside gap, patient-derived tumor xenografts (PDXs, xenopati-ents) have been developed. Although these models had alreadybeen described in the seventies, they have become popular forassessing genotype-drug correlation response studies in the lastdecade (13). Comprehensive molecular annotation studies havedemonstrated that PDXs maintain the majority of genetic altera-tions and global pathway activity of primary tumors (14, 15).Importantly, the histologic structure and intratumor clonal het-erogeneity are usually preserved (16), although recent literaturereports the selection of specific copy-number alterations duringPDX propagation (17). In colorectal cancer, seminal studies havealready set the stage for pharmacogenomic analyses and associ-ation of PDX genotype with targeted therapy response (14, 18).PDXs have significantly contributed to shedding light on themechanisms of resistance and on identification of predictivebiomarkers of response, but large-scale screening is actuallylimited by the costs, size, and efforts for animal maintenanceand manipulation.

Models that can couple both the ease of handling of cellcultures with the preservation of intratumor heterogeneity ofPDXs have been proposed. Bruna and colleagues (5) have gen-erated a large biobank of breast cancer PDXs combined withshort-term cultures of PDX-derived cells demonstrating that thecorresponding cell models could be reliably used to assess drugresponse and to identify biomarkers of resistance in vitro, asparalleled in vivo. Similar studies have been recently performed

also in gastrointestinal and pancreatic cancer (19, 20), thusconfirming the value and applicability of this approach.

In this work, we describe the establishment of a panel of 29 celllines obtained from a cohort of 29 colorectal cancer PDXs andprovide a comprehensive genomic analysis of these models.Importantly, we show that the molecular features of xenopati-ent-derived cell lines (XL) closely mimic their matched PDXmodels. We also show that XLs constitute a valuable model toinvestigate colorectal cancer patientmolecular vulnerabilities andprovide an effective opportunity to reveal patient-specific drugresponses and implement precision oncology in colorectal cancer.

Materials and MethodsXenopatient-derived cell line establishment, culture, andauthentication

For xenopatient generation, fresh surgically resected primarycolorectal cancer andmetastases tissues or biopsies were obtainedand collected from consenting patients. All procedures wereapproved by the Italian Ministry of the Health and the EthicsCommittee of the Medical faculty of the University of Rostock, inaccordance with generally accepted guidelines for the use ofhuman material.

Tumor specimens were cut into small pieces and either frozen(biobanked) or prepared for implantation, as described previ-ously (14). For tumor implantation, 6-week-old femaleNMRInu/nu or NOD/SCID mice were used as recipients. All experimentalprocedures were carried out in strict accordance with the recom-mendations in the Guide for the Care and Use of LaboratoryAnimals of the NIH (Bethesda, MD). The protocol was approvedby the Committee on the Ethics of Animal Experiments of theUniversity of Rostock and the Internal Ethical Committee fromAnimal Experimentation of the Candiolo Cancer Center, as wellas the Italian Ministry of Health.

Established tumors from xenopatients (1,500 mm3) wereremoved and processed for in vitro culture as described below.

PDX tissues were dissociated into single-cell suspension bymechanical dissociation using the Gentle MACS Dissociator(Miltenyi Biotec) and enzymatic degradation of the extracellularmatrix using theHumanTumorDissociationKit (Miltenyi Biotec)was performed according to the manufacturer's protocol. Cellsuspension was centrifuged three times and the pellet was resus-pended in DMEM/F12 medium containing 10% FBS and 2mmol/L L-glutamine. The final cell suspension was then filteredthrough a 70-mmcell strainer (Miltenyi Biotec) and cells that werenot filtered out were resuspended in DMEM/F12 medium con-taining 10% FBS, 2 mmol/L L-glutamine, antibiotics (100 U/mLpenicillin and 100 mg/mL streptomycin) and 10 mmol/L ROCKinhibitor Y-27632 (Selleck Chemicals Inc) and cultured on col-lagen-coated plates (Corning) at 37�C in a humidified atmo-sphere of 5% CO2. Medium was changed regularly every threedays. Growing cell lines were further passaged andwere subjectedto three sequential cycles of freezing and thawing to ensure thestability of the cell lines. Growing cell lines were stocked at lowpassages by cryopreservation.

For only one case (CRC0080), the cell line was established as axenosphere (21) and then adapted to grow in a 2D monolayer.The HROC cell line collection was derived by M. Linnebacher'slaboratory (University of Rostock, Rostock, Germany)_asreported previously (22).

Translational Relevance

Progress in the development of effective cancer treatments islimited by the availability of tumor models. For decades,established cancer cell lines represented the mainstay preclin-ical tumor model, but these tools have limitations, such aslimited capacity to recapitulate inter- and intratumor hetero-geneity, adaptation to grow in two-dimensional cultures andthe lack of interaction with the microenvironment. To over-come these restraints, patient-derived tumor xenografts (PDX)have been developed in recent years. Although this modelmirrors histologic and molecular features of the patient'stumor, PDXs also have limitations including maintenancecosts and unsuitability for large-scale screenings. Here wedescribe a novel platform of PDX-derived cell lines (xeno-cell lines, XL) that retain the pharmacogenomic profile of thesample of origin andoffer advantages such as reducedworkingcosts and ease of handling. In conclusion, we provide apreclinical model resource for large-scale functional genevalidation and assessment of novel therapeutic strategies incolorectal cancer.

Lazzari et al.

Clin Cancer Res; 25(20) October 15, 2019 Clinical Cancer Research6244




BT474 and SKBR3 cell lines were purchased from the ATCCandmaintained in DMEM/F12 and DMEM, respectively, containing10% FBS, 2 mmol/L L-glutamine, antibiotics (100 U/mL penicil-lin and 100 mg/mL streptomycin) and cultured at 37�C in ahumidified atmosphere of 5% CO2.

Xenopatient-derived cell lines (XL) were routinely checkedfor Mycoplasma contamination using the Venor GeM Classic Kit(Minerva Biolabs) according to the manufacturer's protocol.XLs, matched PDXs, and patient authentication was performedusing the Gene Print 10 System (Promega) through shorttandem repeats (STR) at 10 different loci (D5S818,D13S317, D7S820, D16S539, D21S11, vWA, TH01, TPOX,CSF1PO, and amelogenin). Amplicons from multiplex PCRswere separated by capillary electrophoresis (3730 DNA Ana-lyzer, Applied Biosystems) and analyzed using GeneMapperIDv.3.7 software (Life Technologies).

DNA extraction and MSI analysisGenomic DNA samples were extracted from each XL and

matched PDX using ReliaPrep gDNA Tissue Miniprep System(Promega). Germline genomicDNAobtained fromnormal tissue(liver) or PBMCs of each patient was used as the referencegenome.

The microsatellite instability (MSI) status was evaluated byusing the MSI Analysis System kit (Promega) according to man-ufacturer's protocol. The analysis requires a multiplex amplifica-tion of seven markers including five mononucleotide repeatmarkers (BAT-25, BAT-26, NR-21, NR-24, and MONO-27) andtwo pentanucleotide repeat markers (Penta C and Penta D). Theproducts were analyzed by capillary electrophoresis in a singleinjection using ABI 3730DNAAnalyzer Capillary ElectrophoresisSystem (Applied Biosystems). The results were analyzed usingGeneMapper V5.0 software. Samples with instability in two ormoremarkerswere defined asMS-instable (MSI-H). Sampleswithno detectable alterations were defined as MS-stable (MSS).

MSI events were evaluated by MSIsensor (23). Signatures werecalculated using a custom Python script.

Exome sequencing and bioinformatic analysisExome sequencing was performed in outsource, while data

analysiswere performed at theCandioloCancer Institute. Each setof DNA samples (PDX, XL, germline) was sent to GATC wherelibrary preparation, exome capture, sequencing on Illumina plat-form and data demultiplexing were performed. Whole-exomesequencing data were analyzed following procedures as describedpreviously (24).

Gene copy-number analysisReal-time PCR was performed with 10 ng of DNA per single

reaction using GoTaq QPCR Master Mix (Promega) with an ABIPRISM 7900HT apparatus (Applied Biosytems; primer sequencesare available on request). Gene copy numbers were normalized toa control diploid cell line, HCEC.

RNA extraction, analysis, and identification of cancer cell–intrinsic subtypes

RNA was extracted using miRNeasy Mini Kit (Qiagen), accord-ing to the manufacturer's protocol for both XLs and PDXs. Thequantification and quality analysis of RNA was performed on aBioanalyzer 2100 (Agilent), using RNA 6000 Nano Kit (Agilent).Total RNA extracted from XLs was processed for RNA-seq analysis

with the TruSeq RNA Library Prep Kit v2 (Illumina) followingmanufacturer's instructions and sequenced on a NextSeq500 system (Illumina). Each fastq file was aligned using MapS-plice (25). Version hg19 was used as the genome reference andGencode v19 was used as the transcriptome reference databaseand gene quantification was performed with RSEM (26).Assignments of each XL to cancer cell–intrinsic subtypes andconsensus molecular subtypes were performed as describedpreviously (27, 28). Correlation analysis of PDX and matchedXL samples was performed with Pearson correlation basedon genes with at least one RPM in either datasets for a totalof 23 pairs.

Data depositionWES and RNAseq data from PDXs and matched XLs have been

deposited in the European Nucleotide Archive (ENA) with theaccession number PRJEB33640.

Drug proliferation assaysCRC XLs were seeded at different densities (5–7� 103 cells per

well) in 100 mL complete growth medium in 96-well plasticculture plates at day 0. The next day, serial dilutions of theindicated drugs were added to the cells in serum-free mediumwhile medium-only was included as controls. Plates were incu-bated at 37�C in 5% CO2 for 5 or 6 days, after which cell viabilitywas assessed by measuring ATP content through CellTiter-GloLuminescent Cell Viability assay (Promega). Luminescence wasmeasured by SPARKM10 (Tecan) plate reader. Treated wells werenormalized to untreated/DMSO-treated wells.

For long-term proliferation assays, cells were seeded in 24-wellplates (1–2.5� 104 cells per well) and cultured in the absence andpresence of drugs as indicated. Wells were fixed with 4% para-formaldehyde (Santa Cruz Biotechnology) and stained with 1%crystal violet-methanol solution (Sigma-Aldrich) after 2 weeks.All assays were performed independently at least three times.

Cetuximab and trastuzumabwere obtained from the Pharmacyat Niguarda Cancer Center in Milan, Italy. Lapatinib was pur-chased from Selleck Chemicals.

RNA interferenceA pool of four siRNAs targetingWRN were used (Dharmacon,

L-010378-00-0005). A total of 15 XL models classified as MSS,MSI-H, andMSI-like, were grown and transfected with siRNA at afinal concentration of 20 nmol/L using the RNAiMAX (Invitro-gen) transfection reagent following the manufacturer's instruc-tions. In each experiment, mock control (transfection lipid only),as well as ON-TARGETplus Non-targeting Control Pool (Dhar-macon,D-001810-10-05) andpolo-like kinase 1 (PLK1) targetingsiRNA (Dharmacon, L-003290-00-0010) were included as nega-tive and positive controls, respectively. After 6 days, cells werecollected for CellTiter-Glo assay (Promega). CellTiter-Glo datawere read on an Envision Multiplate Reader and data werevisualized using GraphPad Prism 7 software. siRNA sequencesare the following:

Non-targeting Control Pool: UGGUUUACAUGUCGACUAA,UGGUUUACAUGUUGUGUGA, UGGUUUACAUGUUUUCUGA,UGGUUUACAUGUUUUCCUAPLK1: GCACAUACCGCCUGAGUCU, CCACCAAGGUUUUC-GAUUG, GCUCUUCAAUGACUCAACA, UCUCAAGGCCUCC-UAAUAG

PDX-Derived Cells Support Pharmacogenomic Analysis in CRC

www.aacrjournals.org Clin Cancer Res; 25(20) October 15, 2019 6245




WRN: GAUCCAUUGUGUAUAGUUA, GCACCAAAGAGCAUU-GUUA, AUACGUAACUCCAGAAUAC, GAGGGUUUCUAUCU-UACUA

Lentiviral transduction of ERBB2-amplified colorectal XL cellsThe PIK3CA p.H1047R mutation was inserted into pLenti-

PIK3CA-myc-DDK vector (Origene) using site directed mutagen-esis with the Quick Change II Site-Directed Mutagenesis kit(Agilent) according to manufacturer's instructions. Primerssequences for PIK3CA site-directed mutagenesis were the follow-ing: GAAACAAATGAATGATGCACGTCATGGTGGCTGGACAAC(PIK3CA_H1047R_F) and GTTGTCCAGCCACCATGACGTGCA-TCATTCATTTGTTTC (PIK3CA_H1047R_R). Lentiviral controlpLenti-myc-DDK vector was purchased from Origene.

Lentiviral control vectors (pRLL empty and FG12 empty),pRLL-KRAS WT, pRLL-KRAS G13D, and FG12-BRAF V600E vec-tors were previously exploited (29, 30).

Lentiviral vector stocks were produced by transient transfectionof the transfer plasmids, the packaging plasmids pMDLg/pRREand pRSV.REV, and the vesicular stomatitis virus (VSV) envelopeplasmidpMD2.VSV-G (12, 5, 2.5, and3mg, respectively, for 10 cmdishes) inHEK-293T cells. Determination of the viral p24 antigenconcentration was done by ALLIANCE HIV-I P24 ELISA 2 PLATEKIT (PerkinElmer Life Science Inc.). Cells were transduced in6-well plates (3 � 105 per well in 2 mL of medium) in thepresence of polybrene (8 mg/mL; Sigma).

Western blotting analysisTotal cellular proteinswere extracted by solubilizing the cells in

boiling SDS buffer [50 mmol/L Tris-HCl (pH 7.5), 150 mmol/LNaCl, and 1% SDS]. Extracts were clarified by centrifugation andprotein concentration was determined using the BCA ProteinAssay Reagent kit (Thermo Fisher Scientific). Western blot detec-tion was performed with Enhanced Chemiluminescence System(GE Healthcare) and peroxidase-conjugated secondary antibo-dies (Amersham). The followingprimary antibodieswereused forWestern blotting (all from Cell Signaling Technology, exceptwhere indicated): anti-phospho-HER2 YY1221/1222); anti-HER2 (Santa Cruz Biotechnology); anti-phospho-EGFR(Y1068); anti-EGFR (clone 13G8, Enzo Life Science); anti-vinculin (Millipore); anti-phospho-p44/42 ERK (Thr202/Tyr204); anti-p44/42 ERK; anti-phosphoAKT (Ser473); anti-AKT;anti-PTEN; anti-KRAS (clone 3B10-2F2, Sigma-Aldrich); anti-BRAF; anti-PIK3CA; anti-HSP90 (Santa Cruz Biotechnology);anti-GAPDH (Abcam); anti-ACTIN (Santa Cruz Biotechnology);anti-MLH1 (Abcam); anti-MSH2 (Abcam); anti-MSH6 (Abcam);anti-PMS2 (Cell Marque Corporation).

Western blot analysis was employed to validate siRNA-mediated WRN knockdown. Briefly, 1 � 106 cells were seededin 10-cm–well plates and then transfected the day after with theindicated siRNAs, following the procedure presented in the RNAinterference section. Seventy-two hours posttransfection, cellswere lysed with 150 mL RIPA buffer supplemented with proteaseand phosphatase inhibitors and lysates were used for SDS–PAGEand immunoblot analysis. Primary antibodies against WRN (CellSignaling Technology) and anti-b-tubulin (Sigma-Aldrich) wereused. Anti-mouse IgG HRP-linked secondary antibody (GEHealthcare, NA931) was used as secondary antibody. Molecularweight markers included: SeeBlue Plus2 Pre-stained Protein Stan-dard (Thermo Fisher Scientific) and Precision Plus Protein Stan-dards (Bio-Rad).

In vivo treatmentEstablished tumors (average volume 400 mm3) were treated

with the following regimens, either single-agent or in combina-tion: lapatinib (Carbosynth) 100 mg/kg daily (vehicle, 0.5%methylcellulose, 0.2%Tween-80); trastuzumab(Roche)30mg/kgonce weekly (vehicle: physiologic saline). Tumor size was eval-uated weekly by caliper measurements, and the approximatevolume of the mass was calculated using the formula 4/3p(d/2)2 D/2, where d is the minor tumor axis and D is the majortumor axis. Animal procedures were approved by the EthicalCommission of the Candiolo Cancer Institute and by the ItalianMinistry of Health.

Statistical analysisResults were expressed as means � SEM or SD as indicated in

the legend. Statistical significance was evaluated by t test or two-way ANOVA using GraphPad Prism software. P < 0.05 wasconsidered statistically significant.

ResultsEstablishment of PDX-derived cell lines

We derived primary cell lines from a set of colorectal cancerPDX models with the goal of setting up in vitro colorectal cancerpreclinical models thatmore closely resembled the features of thepatient's tumor. The clinicopathologic characteristics of patientsfrom whom the PDXs were initially obtained are listed in Sup-plementary Table S1. The establishment procedure, described indetail in the "Materials and Methods" section, is schematicallyrepresented in Supplementary Fig. S1. Briefly, the PDX tumor issurgically excised and mechanically and enzymatically dissociat-ed toobtain cells that are subsequently cultured in 2Dpetri dishes.In this work, a total of 29 primary cell lines have been derivedfrom a collection of 29 PDXs established at the Candiolo CancerInstitute (n ¼ 17) and at Rostock University (Rostock, Germany;n¼ 12; refs. 14, 18, 22). Among the 29 PDXs, 10 originated fromprimary tumors and 19 from liver or peritoneummetastases of 28patients with colorectal cancer (two different metastatic lesions -IRCC-5A and IRCC-5B - were obtained from the samepatient; Fig. 1A; Supplementary Fig. S1). To underline the originof these 2D primary cell lines from xenopatients, we will refer tothem as XLs.

XLs, although presenting cell-specific morphologic features,displayed a predominant and typical epithelial pattern charac-terized by islets of compact or round shaped cells growingpredominantly as a monolayer or, in one case (HROC147), ascell-clumps in suspension (Supplementary Fig. S2A). The epithe-lial phenotype was confirmed by analysis of expression of specificepithelial markers (e.g., E-cadherin, cytokeratin 8, 18, and 19 andEpCAM) with respect to mesenchymal markers (e.g., vimentin,SNAIL, and TWIST1; Supplementary Fig. S2B).

All XLs displayed the ability of long-term propagation (mul-tiple passages) in vitro and their stability was ensured by at leastthree sequential freezing/thawing cycles prior to biobanking.Cells were maintained in culture for at least 8 passages prior tonucleic acid extraction.

XLs recapitulate the genomic landscape of matched PDXsTo assess whether the colorectal cancer molecular subtypes

that are commonly ascertained in the clinic were preserved inboth the PDXs and matched XLs, we performed genomic and

Lazzari et al.





transcriptomic analyses systematically comparing the two pre-clinical platforms.

Initially, we analyzed microsatellite markers and found that 5of 29 (17%) PDXs displayed microsatellite instability (MSI-H),while the remaining were microsatellite stable (MSS). The MSIstatus was maintained in the matched XLs (Fig. 1B).

Transcriptome profiling of XLs and their originating PDXsrevealed higher correlation between matched XL-PDX pairs thanbetween unmatched pairs (Kolmogorov–Smirnov, P < 1� 10�16;Supplementary Fig. S3A and S3B).

Next, parallel exome sequencing analyses of XLs and matchedPDXs were performed. Importantly, to identify tumor-specific

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Figure 1.

Exome sequencing analysis of XLs matches the profile of the corresponding PDX of origin. A, Site of origin of PDX samples used to generate XLs. B, Relativedistribution of microsatellite status in XL cells. C,Number of MSI events in the 29 PDX-XL pairs, stratified by the length of the repeat units identified by exomeanalysis. D,Mutational load (number of mutations per Mb) in the 29 PDX-XL pairs, as calculated by exome analysis. E, The counts of nonsynonymousmutations(blue bar) and INDELs (red bar) in the 29 PDX-XL pairs, as calculated by exome analysis. F,Mutational spectra in the 29 PDX-XL pairs, as relative proportion ofthe six different possible base-pair substitutions (nucleotide transitions and transversions). MSS and unstable (MSI-H) cases are highlighted in light blue and lightred, respectively. No., number.






somatic mutations, germline genomic DNA (gDNA) extractedfromnormal tissues (liver) or blood (PMBCs) of each correspond-ing patient was used as the reference genome.

Sampleswere sequencedwith highdepth and coverage to allowdetection of low-frequency somatic mutations in xenopatienttumors andmatched XLs despite contamination of human cancercells with murine infiltrating cells in some samples. The mediandepth achievedwas 143� and themedian coveragewas 97.8%onthe coding regions of the reference genome (assembly hg38) with90.3% of the bases covered at least 40 times.

A high level of correlation was found between cell lines andmatched PDXs regarding the total number of somatic non-synonymous single-nucleotide variants (SNV) and insertions ordeletions (INDELs; Pearson r ¼ 0.9870; P < 0.0001; Supplemen-tary Fig. S4A). Overall, even taking into consideration genomicvariability and tumor evolution that could occur during in vivopassages and in vitro culturing, mutation and copy-number pro-files detected in PDXs are highly preserved (i.e., shared) in XLs(Supplementary Fig. S4B).

MSI-H models showed a higher number of MSI events com-pared with MSS cases (median value MSI-H ¼ 7723.5 vs. MSS ¼263.5; Fig. 1C). Moreover, the number of MSI events is main-tained in each PDX and matched XL (Pearson r¼ 0.998), in bothMSS and MSI-H cases.

MSI-H cell lines and matched PDXs displayed a hypermutatorphenotype with a higher mutational load (number of mutations/Mb) as compared with MSS models (median value MSI-H ¼60.5 vs. MSS ¼ 5.5; Fig. 1D), reflecting a higher number ofnonsynonymous single-nucleotide variations (SNV; mutationburden; median value MSI-H ¼ 1691.5 vs. MSS ¼116; Fig. 1E). This is consistent with the reported mutationfrequency in colorectal cancer tissues and cell lines (2, 7, 31). NoMSS model was found to be hypermutated, likely reflecting thelack of mutations in POLE or POLD1, which are known togenerate mutations in the absence of MSI-H (2). Moreover, theINDEL burden was higher in MSI-H compared with MSS models(median value MSI-H ¼ 562.5 vs. MSS ¼ 7), as previouslyreported in TCGA cancers and colorectal cancer cell lines(refs. 2, 31; Fig. 1E; Supplementary Fig. S4C).

Somatic variants within the coding regions in XLs were mostlyconcordant with the matched PDX specimens for both MSS andMSI-H models, with few exceptions (CRC0078, CRC0740, andCRC0080) displaying a similar or higher number of privatemutations (found in XL and/or PDX) with respect to sharedmutations (Supplementary Fig. S4D).

In general, the allelic frequencies of alterations shared betweenXLs and corresponding PDXs were significantly correlated (Pear-son r ¼ 0.8233; Supplementary Fig. S4E).

Despite the global genetic correlation between the sets ofmodels, we also detected several divergent mutations in eitherXLs (n ¼ 4,019) or PDXs (n ¼ 1,885) (private mutations). Theputative biological significance in cancer of these private muta-tions was assessed on the basis of Cancer Gene Census and datareported from colorectal cancer analysis (32, 33). Only 7.1%(285/4,019) divergent mutations found in XLs affected cancer-related genes. Similarly, pan-cancer–related genes that were dis-cordant in the PDXs represented 6.7% (126/1,885; Supplemen-tary Table S2). The majority of these discordant mutations incancer-related genes are found in MSI-H models (97/126 ¼77.0% in PDX; 222/285 ¼ 77.9% in XL), as expected because ofthe hypermutated phenotype of these models. The remaining

discordant mutations affecting pan cancer-related genes (n ¼92) were identified in MSS models (PDX ¼ 22 SNVs þ 7INDELs; XL ¼ 50 SNVs þ 13 INDELs). Of note, among 411private alterations found in pan cancer-related genes, only 92affected colorectal cancer–related genes (CRC_CGC): 23 inPDXs and 69 in XLs. Twenty-six (13 SNVs þ 13 INDELs) outof 92 were found in MSS models (Supplementary Table S2) andthe number of private variants occurring in colorectal cancer–related genes for each MSS XL or PDX ranged from zero to three.We found that the majority of private alterations have lowervariant allele frequency (VAF) compared with shared variants,suggesting that the majority of discordant mutations found inthe matched models might be of subclonal origin (Supplemen-tary Fig. S4F). Interestingly, also a subgroup of shared altera-tions ranged with frequencies between 25% and 50% (Supple-mentary Fig. S4F), thus endowing the polyclonal architecturecharacterizing PDXs and retained in matched XLs as a uniquemodel to investigate on heterogeneity and clonal evolution incolorectal cancer.

While the SNVs spectrum was maintained between XLs andmatched PDXs, it differed significantly between the MSI-H andMSS cases, with an increased proportion of C>G/G>C transver-sions (about 5-fold) and a decrease in T>C/A>G transitions in theMSS cases (about 1.3-fold; Fig. 1F). Interestingly, MSI-H modelspresent a SNV spectrum typically associated with defective DNAmismatch repair and found in MSI-H colorectal cancers (34; ref.Supplementary Fig. S5).

Finally, exome analysis revealed that the copy-number profileof each PDX is also maintained in the corresponding derived cellline (Pearson correlation: 0.82 � r � 0.98). As expected, MSSPDXs and matched XLs displayed a higher level of loss of het-erozygosity (LOH) or copy-number variations than MSI-H mod-els, which exhibited a more stable CNV profile (Fig. 2A). In MSScases, themost commondeleted chromosomal armswere 8p, 17p(including TP53), and 18q (including SMAD4), and the mostcommon gained regions were chromosome 7, 8q (includingMYC), 13, and 20q (Fig. 2B and C).

Colorectal cancer pathway alterations are conserved in XLsIntegration of genomic data allowed for the identification

of deregulated signaling pathways, and the genes most com-monly altered in colorectal cancer (2) were all represented inour panel of PDXs and matched XLs (Fig. 3A). In particular,recurrent alterations in the DNA mismatch repair (MMR), Wnt,MAPK, PI3K/PTEN, TGFb, and p53 pathways were identified(Fig. 3A).

Mutations in MMR genes were found in MSI-H tumors. Thealterations detected were missense mutations in MSH2, MSH3,MSH6, and POLE/POLD1 genes, as well as MLH1 expressiondownregulation (Fig. 3A). Interestingly, three MSS cases dis-played alterations in MSH3, MSH6, and POLE DNA repair asso-ciated genes in both PDXs and matched XLs. These mutationswere not reported previously, nor did they fall in regions impor-tant for protein activity, suggesting that these genes are notfunctionally affected by these mutations.

The Wnt pathway is frequently altered (90%) in colorectalcancer. The most frequent alterations include inactivating muta-tions inAPC aswell as activatingmutations inCTNNB1 (2).Othervariants affecting this pathway are inactivating mutations target-ing regulators of the Wnt pathway, such as TCF7L2, FBXW7,AXIN2, and RNF43 genes.

Lazzari et al.





APC mutants were identified in 14 of 29 cases (48.3%), whileother alterations were found in the same pathway in APC wild-type APC cases, such as a FBXW7 alteration (p.R465H) in onecase, and AXIN2 downregulation ormutation (p.G495A) in threecases. Similarly, RNF43 alterations were identified in one MSSAPC wild-type cell line and in four out of five microsatelliteunstable cases, highlighting the association of these alterationswith the MSI-H phenotype, as previously reported (35). Ofinterest, multiple alterations affecting RNF43 were detected intwo APC wild-type cases.

In addition, a translocation of the Wnt-agonistic RSPO3 withPTPRK was found in one BRAF-mutated APC wild-type case, asassessed byRNA-seq analysis onXLs and validatedbyquantitativeRT-PCR (Supplementary Fig. S6A and S6B). No RSPO2 genefusions were identified in our collection of XLs.

TP53 alterations were found in 79.3% of cases (23 of 29). Inaddition, alterations inATMwere found in 10.35% (3of 29).Oneof these co-occurred with a TP53 mutation, while the remainingtwo cases were TP53 wild-type.

The TGFb signaling pathway is also frequently deregulated incolorectal cancer (2). In our dataset, we identified two TGFBR1-mutated cases and four cases carrying TGFBR2 alterations. Con-sistent with previous findings (36), all of these models were MSI-H.Moreover, alterations in SMAD4were identified in seven cases,while four other cases (CRC0781-XL, CRC0691-XL, HROC59,and HROC239) did not express SMAD4, as assessed by RNA-seqanalysis (Fig. 3A; Supplementary Fig. S6C). Lack of SMAD4expression was ascribed to LOH in three cases (Fig. 2C). Noalterations in SMAD2 and SMAD3 were detected. Three MSI-Hcases (IRCC-1-XL, HROC131, and HROC285) displayed

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Comparison of CNVs unveils gain or loss of selected genome segments in PDX-XLmatched models.A, Heatmap comparing copy-number aberrations betweenmatched PDX and XLmodels in log2 scale, as assessed by whole-exome sequencing (WES). Red colors indicate gains, while blue colors indicate losses. The bandon the left represents chromosomes 1–22. B, Plot of frequency of gains and losses for each position per group (PDX and XL) along the genome, as assessed byWES. Each horizontal dotted line represents chromosomal boundaries. C, Heatmap comparing copy number betweenmatched PDX and XL models in log2 scalefor the indicated genes.






deletions in theACVR2A gene, a TGFb familymember, knownas apotential player in colorectal cancer (2).

Genetic alterations in RAS–MAPK and PI3K–PTEN pathwaysare very frequent in colorectal cancer. Activating mutations inKRAS, including the less common mutations p.Q61K (exon 3),p.K117N, and p.A146V (exon 4), and in NRAS were identifiedin 13 of 29 XLs and matched PDXs, thus reflecting the prev-alence of RAS mutations found in patients with colorectal

cancer. We identified five models harboring BRAF p.V600Emutations, two derived from MSS metastases and three fromprimary MSI-H CRC. While alterations in KRAS, NRAS, andBRAF displayed a significant pattern of mutual exclusivity, 2 of10 KRAS-mutated models also exhibited activating mutationsin the PIK3CA gene (codon 1047 and 1049). Only one PIK3CAvariant (p.H1047R) was identified in a KRAS/NRAS/BRAF wild-type case.

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Genomic landscape of deregulated signalingpathways in PDX-XL pairs and response tocetuximab treatment. A, Landscape of the genealterations found in the PDX-XL pairs; missensemutations (gray boxes), nonsense mutations (blackboxes), insertion (yellow boxes), and deletion (violetboxes) as well as co-occurrence of multiplealterations (green boxes) are displayed. Orangesquared boxes indicate gene amplification, whileblue squared boxes indicate gene downregulation.Genes are grouped according to signaling pathways;cases are grouped according to transcriptional CRISclassification of XLs (as assessed in ref. 27). Primarytumor site (right and left) for each cell line is alsoreported. MSI-H cases are also shown. Right panelshows percentage of gene alterations in PDX-XLpairs (gray bars) compared with percentage of casesreported in TCGA CRC cases (red bars). B, Caleydoview of correspondences between the CRIS versusCMS class assignments of XLs. C, Bar graphrepresenting the effect of cetuximab treatmentnormalized on control untreated cells for the XLs.Viability was assessed by measuring ATP contentafter 6 days of treatment with cetuximab at theclinically relevant dose of 10 mg/mL. Data representthe average of value obtained from at least threeindependent experiments; error bars represent SD.On the basis of their response to cetuximab, cell lineswere subdivided in three different groups: resistant(first tertile, range 100%–66%), intermediate (secondtertile, range 65%–34%), and sensitive (third tertile,range 33%–1%). MSI-H cells are highlighted in lightyellow, and for each cell line its CRIS classification isreported.

Lazzari et al.





Missense (p.A86E and p.D92Y) as well as nonsense (p.R233�)mutations affecting the PTEN gene were identified in three cases.Although bothmissensemutations fall in the proximity or withinthe WPD loop of the catalytic site, only alterations in codon 92have been reported to fully abrogate PTEN function (37). Inaddition, Western blot analysis highlighted the loss of PTENexpression in two XLs: CRC0394-XL carrying the p.R233� non-sense mutation, and HROC277 in which PTEN expression wasconsistently decreased at the transcript level due to genetic loss ofthe PTEN locus (Fig. 2C; Supplementary Fig. S6C and S6D). ThePTENp.K342Nvariant found at highVAF in theMSI-HHROC131line (Supplementary Table S2) does not affect PTEN proteinexpression (Supplementary Fig. S6D; ref. 38). Because this variantwas absent in the corresponding PDX, we speculate that thisalteration appeared in XL as either a sampling bias during theestablishment of the cell line or as an acquired randomly gener-ated mutation owing to the intrinsic hypermutator phenotype ofthis MSI-H cell line.

Alternative mechanisms of activation for the PIK3CApathway include transcriptional upregulation of IGF2 (Supple-mentary Fig. S6E). In our panel of XLs, we identified sevencases (CRC0081-XL, CRC0438-XL, HROC46, HROC278Met,HROC59, HROC239, and HROC285) overexpressing the IGF2transcript as assessed by RNA-seq analysis (log2 ratio > 1.5;Supplementary Fig. S6E). Of note, overexpression of IGF2 wasnot associated to genomic amplification of the IGF2 gene,consistent with previous reports (Fig. 2C; refs. 2, 39).

Evaluationof genetic alterations in receptors of the ERBB familyreceptors unveiled the presence of an EGFR extracellularmutation(p.G465E) in a PIK3CA-mutated case (CRC0104-XL). Of interest,this EGFR mutation was previously found to be associated withacquired resistance to anti-EGFR therapies (40, 41). Indeed, itscorresponding xenopatient was established from a liver metasta-sis of a patient who had received cetuximab treatment within6 months prior to resection (18).

Another clinically actionable ERBB family member frequentlyaltered in cancer is ERBB2 (also known as HER2). ERBB2 geneamplificationwas identified in twoMSSwild-type RAS/BRAF cases(CRC0080-XL and CRC0186-XL; Supplementary Fig. S7A). Inter-estingly, CRC0186-XL showed a remarkable increase inERBB2 gene copy number (n ¼ 33.2), while CRC0080-XL dis-played a less pronounced increase (n¼ 6.1), comparable with thatpresent in the breast cancer cell lines BT474 and SKBR3 (n ¼ 6.5and n ¼ 5.6, respectively; Supplementary Fig. S7B). In these celllines, ERBB2 gene copy-number gain led to protein overexpression(Supplementary Fig. S7C). CRC0080-XL also carried an ERBB2-activating mutation (p.L866M) affecting the intracellular kinasedomain of the receptor (ref. 42; Fig. 3A).

Mutations in the extracellular region of the ERBB2 receptor(p.S310F and p.L465V) were identified in two additional xeno-patients and matched cell lines (HROC87 and HROC112Met,respectively). Of note, ERBB2 p.S310F was copresent in a BRAF p.V600E–mutated case. Similarly, in another BRAF-mutated case(HROC131), we identified occurrence of the ERBB3 p.V104Mvariant (Fig. 3A).

Gene expression profiling revealed that molecular subtypesfound in XLs correlated with transcriptional classes identified bythe recently described colorectal cancer–intrinsic subtype (CRIS)analysis (ref. 27; Fig. 3A and 3B). In total, 26 of 29 XLs weresignificantly assigned to a specific CRIS class (SupplementaryTable S3). In particular,MSI-H andKRAS/BRAF-mutant cells were

enriched in CRIS-A, while CRIS-C included KRAS/BRAF-WT lines.In addition, two cell lines that displayed TGFb pathway alterationclustered in CRIS-B- and IGF-2–overexpressing cells were includ-ed in CRIS-D group (Fig. 3; Supplementary Table S3). A similardistribution in genetic alterations was also found for the consen-sus molecular subtypes (CMS). MSI and BRAF mutational statuswere enriched in CMS1, and KRAS-mutant lines were partiallydepleted in CMS2.

Associations between CRIS and CMS transcriptional classes arealso evident. Indeed CRIS-A samples are assigned to CMS1 andCMS3, while CRIS-C is predominantly composed of CMS2.Interestingly, in the context of stroma- depleted samples, CRIS-D samples are also classified asCMS4, likely due to the similaritiesin stem cells rewiring program in intrinsic cancer cell intrinsictraits, that is, LGR5pathway, captured by both classifiers (Fig. 3B).

Sensitivity to EGFR blockade ismaintained in xeno-derived celllines

Anti-EGFR mAbs are approved to treat metastatic colorectalcancer and achieve a 10% objective response rate in unselectedpatients treatedwith antibodymonotherapy (43). Clinical benefitof EGFR blockade increases up to 25% in cases when tumors arestratified for wild-type KRAS, NRAS, and BRAF (43). To assesswhether XLs could recapitulate this genotype–drug response, andtherefore could be exploited as a reliable platform for drug testing,we checked the entire cell platform for cetuximab sensitivity.

On the basis of the level of response to cetuximab, the cellcollection was classified in three different groups: sensitive (n ¼2), intermediate (n ¼ 5), and resistant (n ¼ 22; Fig. 3C). Asobserved in the clinic, KRAS, BRAF, orNRASmutations, as well asother genetic alterations (i.e., MAP2K1 p.K57N and EGFR p.G465E), are associated with resistance to EGFR blockade incolorectal cancer cells (Fig. 3C; refs. 18, 40, 44, 45). Similarly,ERBB2-amplified CRC0186-XL was refractory to cetuximab treat-ment, confirming previous findings obtained by preclinical andclinical data from the same patient (14, 18). Conversely, the otherERBB2-amplified and mutated CRC0080-XL cell line displayedhigher sensitivity to cetuximab treatment.

Integration of multi-layer data also revealed a positive corre-lation with the transcriptional classes obtained from the cancercell–intrinsic classifier (Supplementary Table S3). As reportedpreviously, CRIS-A resulted enriched in both MSI-H and KRAS/BRAF–mutated cases (IRCC-1-XL, HROC50, HROC277,HROC147, CRC0438-XL, and CRC0781-XL) with marked resis-tance to cetuximab treatment (Fig. 3B and 3C), and CRIS-Cdepleted for KRAS-mutant cells (IRCC-5A-XL, IRCC-5B-XL,CRC0078-XL, CRC0080-XL, and CRC0394-XL), showingsensitivity to anti-EGFR treatment. Confirming previousreports (27, 46), both CRIS-C and CMS2 transcriptional classesare enriched for cetuximab responsive models (SupplementaryTable S4).

Expression analysis identifies therapeutic targets in xeno-derived cell lines

RNA-seq data analysis unveiled potentially actionable targetsin the XL platform. Because receptor tyrosine kinases (RTK) areoften implicated in cancer and are ideally suited for pharmaco-logic inhibition, the analysis was focused on this class of proteins.Overall, 30 distinct RTKs passed the filtering process during RNA-seq analysis due to their expression level in our XL collection.Outlier expression analysis identified 10 (log2 ratio � 3.5)






overexpressed RTK genes including ERBB2, AXL, FGFR1, NTRK1,NTRK2, ROR2,RET, EPHA4, EPHB1, andEPHB6 in individual XLs(Fig. 4A).

Among these, only two RTKs were overexpressed in RAS/RAFwild-type cells ("WT-specific" RTKs), namely NTRK1 (TRKA) andERBB2 (HER2). Integrated analysis showed that the observedoverexpression is associated with different molecular alterations,namely gene translocation (NTRK1) or gene amplification(ERBB2; Figs. 3A and 4B; Supplementary Figs. S6F, S7A, and S7B).

In the TRKA-overexpressed case, we identified a genetic rear-rangement involving exon 10 or 11 of LMNA and exon 11 ofNTRK1 genes (47). The two distinct splice variants encodingexons 1–10 or 1–11 of LMNA gene fused to exons 11–16 ofNTRK1 gene reported in the donor patient were identified byRNA-seq analysis in the matched XL (Supplementary Fig. S6F).Remarkably, the pharmacologic response of these xeno-cellsresembled the one observed in the corresponding PDX uponentrectinib treatment (47).

To validate ERBB2 amplification as an actionable target, wefirstevaluated biochemical pathway activation. In contrast toCRC0186-XL, CRC0080-XL showed lower level of HER2 protein,but still an active downstream pathway due to the presence of theL866M mutation (Supplementary Fig. S7C).

This analysis confirmed that overexpression and constitutivesignaling, as well as downstream pathway activation of HER2,paralleled the extension of ERBB2 gene amplification.

To validate overexpressed ERBB2 as putative target for phar-macologic inhibition (14), we challenged our in vitromodels withrational combinations of drugs. We initially tested the effect ofdrugs (lapatinib and trastuzumab) that have previously shownactivity on HER2þ patients with metastatic colorectal can-cer (14, 48). While monotherapy showed no or mild effects, bothlines (CRC0080-XL and CRC0186-XL) displayed significant sen-sitivity to the combinatorial treatment (Fig. 4C) in short-termproliferation assays.WeperformedWestern blot analysis showingthat the biological effect of the drugs on ERBB2-amplified colo-rectal cancer cell lines is matched by the quenching of HER2biochemical downstream signals (Fig. 4D). Of note, similarresults were also obtained in vivo, when the correspondingERBB2-amplified xenopatients were challenged with the sametreatments for 28–35 days (ref. 49; Fig. 4E), thus confirming theXL as a valuable preclinical model to assess drug response and todissect biochemical pathway activation.

Combinatorial treatment with lapatinib and trastuzumab ofHER2þ patients has been exploited in the recently completedproof-of-concept clinical trial named HERACLES (48). Our pre-vious work based on liquid biopsy analysis has shown that 32 of35 patients treatedwith anti-HER2 inhibitors relapsed after initialresponse revealing the presence of molecular mechanisms poten-tially responsible for resistance (primary or acquired) to HER2blockade (50). In particular, either KRAS or BRAF-mutated cloneswere preferentially found in patients who were initially refractoryto anti-HER2 treatment (primary resistance), while PIK3CAmuta-tions were detected at progression in patients who had respondedto lapatinib þ trastuzumab combinatorial treatment and thenrelapsed (acquired resistance). To validate these genetic players asputative drivers of resistance, we transduced HER2þ colorectalcancer XL cells by means of lentiviral vectors and performedpharmacologic and biochemical analysis of treated cells. Wefound that overexpression of mutant alleles of KRAS, BRAF, andPIK3CA conferred resistance to combinatorial treatment (Fig. 5A;

Supplementary Fig. S7D), due to sustained ERK and/or AKTactivation (Fig. 5B; Supplementary Fig. S7E). Consistent with thisdata, the combination of lapatinib and trastuzumab was ineffec-tive in lines lacking ERBB2 amplification and naturally bearingRAS/BRAF/PIK3CA mutations (Supplementary Fig. S8).

WRNis a target inMSI and in selectedMSI-like colorectal cancerXL cells

We then exploited our XL cell models to explore novel depen-dencies in colorectal cancer. We focused on theWRN gene whichencodes a RecQ helicase involved in Werner syndrome. MSI-Hcolorectal cancers were recently found to have a synthetic-lethaldependency on theWRN gene for cell fitness and viability, whileMSS colorectal cancers were not dependent on WRNexpression (51–54). It is presently unknown whether MSI-likecolorectal cancer cells, which are genetically MSS but are tran-scriptionally defined as MSI-H (55), also rely on WRN geneexpression for their survival.

To address this issue, we selected a subgroup of 15 XLs,including 5 MSI-H (HROC50, IRCC-1-XL, HROC87, HROC285,HROC131), 5 MSS with predicted MSI-like features (CRC0438-XL, CRC0781-XL, HROC80, CRC0558-XL, and HROC278Met)and 5 MSS (CRC0080-XL, IRCC-5A-XL, HROC59, CRC0778-XL,CRC0104-XL), recapitulating the CMS and CRIS transcriptionalsubgroups.

The MSI-like phenotype of the selected PDX-derived cell lineswere defined as follows: (i) classification into the CMS1 subgroup(CRC0438-XL, CRC0781-XL, HROC80) or (ii) classificationthrough the algorithm described by Tian and colleagues (ref. 55;CRC0558-XL and HROC278Met).

The panel of 15 XL cell lines was subjected to siRNA-mediatedWRN knockdown to assess their dependency on WRN. Effectivetargeting of WRN was verified by Western blot analysis (Supple-mentary Fig. S9A).

As expected, WRN depletion selectively reduced the fitness ofall 5 MSI-H cells, whereas none of the MSS models were sensitive(Fig. 6). Four of the MSI-like XLs were insensitive to WRNknockdown; notably, however, one model (CRC0781-XL) washighly sensitive toWRN depletion. To confirm that CRC0781-XLwas indeed MSS we repeated the microsatellite and MMR proteinanalysis, which confirmed that thismodel isMSS both geneticallyand biochemically (Supplementary Fig. S9B and S9C).

DiscussionHuman cancer cell lines represent a tool extensively exploited

in the last half century to study the biology of different tumortypes and for extensive drug screening efforts. Exceptional efforts,such as the generation of the Cancer Cell Line Encyclopedia (7),have been pivotal for unveiling novel genomic predictors of drugsensitivities in 36 tumor types, thus coupling cell line genomicannotation to individual pharmacologic profiles.

We have previously described a bowel cancer cell line col-lection including 151 established cell lines (56). This platformcan recapitulate the majority of colorectal cancer molecular andtranscriptional subtypes previously defined in patients. Geno-mic analysis has allowed for the identification of novel outliersin response to selected targeted agents. Yet infrequent molec-ular subtypes or tumors carrying rare genetic lesions may beunder-represented or completely absent in the abovemen-tioned colorectal cancer cell lines' collection. For instance,

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while ERRB2-amplified cell line models have been widelyemployed for breast and gastric cancer studies (57, 58), noneof the models in the 151 colorectal cancer cell line collectionwere found to carry this alteration. In this work, we provide anaccurate characterization of two novel cancer cell lines ofcolorectal origin bearing ERRB2 amplification, which could beused in the future to further dissect the role of ERBB2 oncogenicsignaling in the context of gut pathophysiology. Testing drug–genotype correlations in the pertinent tissue is necessary sincethe same molecular alteration could result in dissimilarresponses to the same drug, as exemplified by the discrepantantiproliferative effects of BRAF inhibitors in BRAF-mutantmelanoma versus colorectal cancer (59).

Cell lines may have intrinsic limitations that hamper repre-sentation of the whole tumor disease in the patient. Commonimmortalized cell lines have been adapted to growing onplastic for decades and this may have caused genetic drifts andthe acquisition of phenotypic features different from originalcancers in patients. It is now evident that colorectal cancer isindeed a heterogeneous disease and that colorectal cancerdevelopment and progression relies on continuous evolutionof multiple clones under environmental and pharmacologicpressure (60). For this reason, precision medicine, which isbased on the design of personalized treatments, requires arepertoire of preclinical models that mirror the in vivo tumormore closely than conventional cancer cell lines. Derivation oflong-term culture directly from tumor samples has proven to bedifficult and inefficient, at least in colorectal cancer, not onlybecause of contaminations but also due to failure to adhere tothe culture dish or loss of proliferative capacity after fewpassages (61). Establishment of short-term tumor cell culturehas proven to be successful (62), but long-term experiments aswell as gene editing by lentiviral transduction for experimentalneeds might not be feasible.

Establishment of 3D cultures (organoids, tumoroids, spher-oids, etc.) has provided significant advancements for the iden-tification of personalized therapeutic options by integratingdetailed genomic information with high-throughput pharma-cologic screenings for patients with advanced disease (63–67).These types of cultures have been able to provide importantcorrelations between tumor genomics and response to chemo-therapy or targeted drugs within short intervals from theirderivation. One of the main limitations for organoid genera-tion is due to the necessity of acquiring a significant amount offresh tissue with viable tumor cells, and is often not possiblewhen only very small tissue biopsies are available. In our work,we have chosen to use small amounts of available tissuematerial to generate PDXs to expand the quantity of tumortissue for subsequent preclinical model derivation for genomicand drug response studies.

Generation of PDX models has contributed to the identi-fication and validation of biomarkers of response andresistance to current anticancer therapies (18). However, thismodel presents some important shortcomings such aslong time for establishment and expansion, cumbersomemanipulation, and cost-ineffective experiments, especially ifused on a large scale.

Here we present a complementary approach based on PDX-derived cell lines (XL). We have established 29 cell lines fromPDXs originally derived from samples of primary or metastaticcolorectal cancer tissue. Initially, to assess whether passage from

3D/in vivo to 2D/in vitro growing condition did not select forgenomic alterations that may compromise the biology of thetumor, we performed genetic and transcriptomic analyses tocompare matched samples. Whole-exome sequencing confirmedpreservation of the PDX main genetic features in 2D-derived celllines. High concordance in genetic variation was evident betweenthe two platforms when considering cancer-related genes,although we identified a variable range of private variants in eachPDX-XL pair. Although the majority of private alterations wasfound in MSI-H models, likely due to their hypermutator phe-notype (68), a small number of private mutations in colorectalcancer–related genes were also identified at subclonal levels inMSS PDX or XL models. This variation could either reflect theenrichment/depletion of a subclonal population or the acquisi-tion of additional mutations during derivation or propagation ofthe XL cells with respect to the matched xenopatient. Our resultsare in linewith recentfindings unveiled by barcoding experimentsshowing that cell line evolution may occur as a result of positiveclonal selection under culture conditions (12). Few shared var-iants were also identified at subclonal levels in the MSS models,thus fueling heterogeneity in these colorectal cancer models. Thishighlights PDXs and matched XLs as unique preclinical tools toinvestigate in vitro and in vivo clonal evolution in response totherapies in colorectal cancer.

Although a certain degree of drifting may occur, gene expres-sion profiles of matched XLs and PDX models were highlycorrelated, suggesting that in vitro propagation may have a min-imal impact on transcriptional traits. Themolecular classificationof cell lines based on transcriptional traits did reproduce thepattern observed in the original tumor, and conserved the distinctgenetic, molecular, and pharmacologic characteristics. Indeed,despite the small size of our dataset, we could confirm theassociation between CRIS-C assignment and higher probabilityof response to anti-EGFR treatment, as well as the associationbetween CRIS-A and MSI status (27).

Of note, comparing the classification of CMS and CRIS in thecontext of cell models we unveiled correspondence in classifica-tion of CMS4 and CRIS-D, likely emerging due to absence ofstromal cells in the cancer cell profiles and similarities in intrinsictraits, such as the LGR5 stem-like signature detected in bothsubtypes (28, 69).

We next assessed whether these preclinical colorectal cancermodels could represent a reliable tool for biomarker validationand pharmacologic screening. The identification of genomicplayers that may confer sensitivities or resistance to selectedtherapies is of paramount importance for the design of effectivetherapeutic strategies. As a proof of concept, we have shown twoindependent examples in which the results observed with the XLshighly mirrored what was previously observed in PDXs. Wefocused our attention on anti-HER therapies, which are approvedor used as investigational agents for patients with RAS wild-typeand HER2-overexpressing colorectal cancer tumors. When wechallenged XLs with the anti-EGFR mAb cetuximab, we observeda distribution of responses that closely correlatedwith genetic andnongenetic biomarkers of resistance identified in the correspond-ing PDXs (18).

As a second paradigmatic example, we have identified in ourcohort two XLs harboring HER2 receptor overexpression due toERBB2 gene amplification. When these cells where challengedwith a rational combination of HER inhibitors, we observed thatcell proliferation was severely impaired, as previously seen with






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Identification of overexpressed RTKs in colorectal cancer XLs and effects of HER blockade in ErBB2-amplified cell models. A, Heatmap showing the relativeexpression (log2 ratio FPKM) of receptor tyrosine kinases (RTK) as identified by RNA-seq analysis of 29 XLs. RTKs listed here (n¼ 32) represent the onlymembers of this class of protein passing the filtration process during RNA-seq analysis. KRAS, BRAF and NRASmutational status is also indicated. (Continuedon the following page.)

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the matched PDXs treated with the same drugs. This furtherconfirms that the XL platform is a valuable tool for genotype–drug correlation studies. Moreover, we have validated moleculardeterminants of resistance to dual HER2 blockade in colorectalcancer, as emerged from the HERACLES trial (50), suggesting that

combinatorial treatment with other targeting agents might bebeneficial for HER2þ patients (49).

We have exploited our XL collection to assess if WRN depen-dency, which has been recently reported as a new syntheticlethality trait in MSI-H cancers (51–54), could also apply to

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Figure 5.

Constitutive expression of mutant RAS/BRAF/PIK3CA mediates resistance to lapatinib þ trastuzumab combinatorial treatment in ErBB2-amplified cells. A, Long-term viability assay showing the effect of different indicated doses of lapatinib in absence or in presence of doses of 25 mg/mL of trastuzumab on ERBB2-amplified CRC0186-XL transduced with lentiviral vector overexpressing BRAF V600E, KRAS G13D, or PIK3CA H1047R mutants. Cells transduced with emptylentiviral vector were used as control (CTRL). Cell viability was assessed by crystal violet staining after 15 days of treatment. Representative wells werephotographed and reported. B, Activation status/phosphorylation of HER2 receptor and downstream pathway in CRC0186-XL transduced with lentiviral vectoroverexpressing the indicated alleles. Cells transduced with empty lentiviral vector were used as control. Cells were treated with the combination of 500 nmol/L oflapatinib and 10 mg/mL of trastuzumab (L þ T) for 4 hours. Cell extracts were immunoblotted with the indicated antibodies. Vinculin was used as loading control.

(Continued.) B, Scatter plot displaying the correlation between absolute ERBB2 expression (FPKM, x-axis) and relative ERBB2 copy-number variation (CNV,log2ratio) in the 29 XLs, as assessed by RNA-seq andWES analyses, respectively. ERBB2-overexpressing and amplified XLs (CRC0080-XL and CRC01086-XL)are indicated. C, Short-term viability assay showing the effects of single dose of trastuzumab (TMAB, 25 mg/mL), lapatinib (LAP, 120 nmol/L), and combination oflapatinib and trastuzumab (LAPþTMAB) on ERBB2-amplified CRC0186-XL (left) and CRC0080-XL (right). Viability was assessed by measuring ATP contentafter 6 days of treatment. Data represent the values obtained from at least three independent experiments in triplicate, normalized on control DMSO-treatedcells; error bars indicate SD (lapatinib vs. lapatinibþ trastuzumab in CRC0186-XL: �� , P¼ 0.001; lapatinib vs. lapatinibþ trastuzumab: �� , P¼ 0.0036 inCRC0080-XL; unpaired Student t test). IC50 values were calculated from dose inhibition curves using GraphPad Prism software. D,Activation status/phosphorylation of HER2 receptor and downstream pathway in dose–response experiments in CRC0186-XL. Cells were treated with the indicated concentrationsof trastuzumab (TMAB), lapatinib (Lap), or the combination of both drugs for 4 hours. Cell extracts were immunoblotted with the indicated antibodies. HSP90was used as loading control. E, In vivo tumor growth curves of CRC0186-PDX (n¼ 6) and CRC0080-PDX (n¼ 6) treated with the indicated modalities. Datarepresent the mean of tumor volume at each time point; error bars indicate SEM (lapatinib vs. lapatinibþ trastuzumab: �� , P < 0.001 by two-way ANOVA test).Response curves for both models were previously reported in ref. 49 and are reshown here for comparative purposes.






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siRNA-mediatedWRN depletion assay in 15 selected XLs. Dot plots represent the normalized viability data obtained upon siRNA-mediatedWRN depletion (reddots) in 5 MSS (top), 5 MSI (middle), and 5 MSI-like phenotypes (bottom). Nontargeting (gray dots) and PLK1 (blue dots) siRNAs were used as negative andpositive controls, respectively. Dots represent mean�SD of 3 independent experiments with 5 technical replicates each. Statistical significance was calculatedcomparingWRN siRNA versus nontargeting siRNA: ns, not significant; � , P < 0.05; �� , P < 0.01; �� , P < 0.001 (Welch t test).

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MSI-like colorectal tumors. MSI-like colorectal cancer models aregenetically MSS, but bear intrinsic transcriptional features thatresemble MSI-H cancers (55). MSI-like colorectal cancers havelimited therapeutic options and are currently excluded fromimmune-based regimens but might benefit from alternative ther-apy regimens. We therefore hypothesized that they could bereliant upon theWRN gene. Bymeans of a siRNA-mediatedWRNdepletion assay, we discovered thatMSI-like colorectal cancers aregenerally not dependent on WRN downregulation. Interestingly,however, we found one MSI-like XL cell line (CRC0781-XL)sensitive to WRN suppression. Future analysis should be per-formed to uncover the mechanistic basis of this findings usinglarger cohort of MSI-like colorectal cancer models.

In summary, we have established a compendiumof 29 XLs thatsubstantially recapitulate the genomic features of matched PDXswith the great advantage of providing ease of handling andamenability for high-throughput compound screening. This maysignificantly accelerate the translation of drug response informa-tion from in vitro testing to clinical practice.

Another notable advantage provided by this approach is thepossibility of generating cell lines with genotypes that are eithermissing or rare in common commercial repositories (i.e., ERBB2-amplified or NRAS Q61-mutated cell lines), as well as increasingthe number ofMSS colorectal cancer cell lines, which are typicallyunderrepresented in existing cell line collections (31, 56). Weproposed that generation of a large cohort of XLs will provide anovel tool to help researchers better understand and model themolecular mechanisms that contribute to colorectal cancer het-erogeneity. In addition, we believe that our XL collection offerssignificant advantageswith respect to commercially available cellsfor several reasons. First, the PDX-XL pairs provide a new strategyfor pharmacogenomics studies: XLs could be exploited as anin vitro surrogate of matched PDXs in biomarker-based preclinicaldrug screening studies, and the selected drug target can be furthervalidated in the corresponding PDX model. Second, clinical andpharmacologic will be available for the majority of the patients,thus making this cell line collection a unique annotated tool toperform screenings with other agents of interest in the context ofchemoresistance/sensitivity. Moreover, the subclonal architectureidentified in PDXs and XLs provides opportunities to investigatehow heterogeneity and evolution affect response to therapeuticagents in colorectal cancer models closely paralleling the clinicalsetting. Third, for all patients from whom matched normalgenomic DNA is provided, comparison between normal and XLsamples will enable the confident identification of somatic altera-tions. Fourth, some of the patient models have matched PBMCsand tumor-infiltrating lymphocytes, thus rendering this XL col-lection a unique resource to perform coculture assays or to studygenotype–drug correlations that may be dependent upon theimmune microenvironment.

In conclusion, we present a novel preclinical platform that,owing to its reliability, large-scale use, and proximity to originalpatient tumors, could offer easier and more rapid access to thedissection of genetic and patient-selective therapeutic vulnerabil-ities, thus leading to the design of novel effective treatmentstrategies.

Disclosure of Potential Conflicts of InterestA. Sartore-Bianchi reports receiving speakers bureau honoraria from and is a

consultant/advisory board member for Amgen, Bayer, and Sanofi. L. Trusolinoreports receiving commercial research grants from Symphogen, Pfizer, Merus,

and Servier, and reports receiving speakers bureau honoraria from Eli Lilly,AstraZeneca, and Merck KGaA. A. Bardelli holds ownership interest (includingpatents) in Neophore and Phoremost, and is a consultant/advisory boardmember for Guardant Health, Roche, Illumina, Third Rock, HorizonDiscovery,Kither, and Biocartis. S. Siena is a consultant/advisory board member forAmgen, Bayer, BMS, CheckmAb, Celgene, Clovis, Daiichi-Sankyo, Incyte,Merck, Novartis, Roche-Genentech, and Seattle Genetics. No potential conflictsof interest were disclosed by the other authors.

Authors' ContributionsConception and design: L. Lazzari, A. Bardelli, S. ArenaDevelopment of methodology: L. Lazzari, E. MedicoAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): L. Lazzari, G. Picco, M. Montone, E. Durinikova,A. Cassingena, C. Cancelliere, E. Medico, A. Sartore-Bianchi, S. Siena,M.J. Garnett, A. Bertotti, L. Trusolino, M. LinnebacherAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): L. Lazzari, G. Corti, G. Picco, C. Isella, L. Novara,E. Medico, S. Siena, M.J. Garnett, A. Bardelli, S. ArenaWriting, review, and/or revision of the manuscript: L. Lazzari, G. Corti,C. Isella, F. Barbosa, A. Cassingena, E. Medico, S. Siena, M.J. Garnett,A. Bertotti, L. Trusolino, F.D.Nicolantonio,M. Linnebacher, A. Bardelli, S. ArenaAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): P. Arcella, E.R. Zanella, A. Cassingena,C. CancelliereStudy supervision: S. Siena, A. Bardelli, S. Arena

AcknowledgmentsThe authors thank all the members of Molecular Oncology Laboratory at

Candiolo Cancer Institute for critically reading the manuscript and, in partic-ular, Mariangela Russo, Giulia Siravegna, Benedetta Mussolin, Francesca Lodi,Riccardo Volta, and Gaia Grasso for their help with experiments and construc-tive discussion, Daniela Cantarella from the Oncogenomics laboratory fortechnical assistance in RNAseq data generation, Francesco Galimi from theMolecular Pharmacology laboratory for providing RNA from PDXs, and Esm�eevan Vliet from M.J.G.'s lab for assistance with WRN dependency experiments.The authors also thankDr. Paolo Luraghi for providing CRC0080-XL and for hishelpful discussion on cell line derivation. The research leading to these resultshas received funding from AIRC under MFAG 2017 -ID 20236 project -P.I.Arena Sabrina; the research leading to these results has received funding fromFondazione AIRC under 5 per Mille 2018 - ID. 21091 program - P.I. BardelliAlberto, G.L. (group leader) Medico Enzo, G.L. Siena Salvatore, G.L. BertottiAndrea, G.L Trusolino Livio, G.L. Di Nicolantonio Federica. This work was alsosupported by European Community's Seventh Framework Programme undergrant agreement no. 602901MErCuRIC (toA. Bardelli); H2020 grant agreementno. 635342-2MoTriColor (to A. Bardelli and S. Siena); IMI contract no. 115749CANCER-ID (to A. Bardelli); AIRC IG 2018 - ID. 21923 project - principalinvestigator A. Bardelli; AIRC IG no. 17707 and IG no. 21407 (to F. DiNicolantonio); AIRC IG no. 20685 (to S. Siena); Terapia Molecolare Tumoriby Fondazione Oncologia Niguarda Onlus (to A. Sartore-Bianchi and S. Siena);Genomic-Based Triage for Target Therapy in Colorectal Cancer Ministero dellaSalute, Project no. NET 02352137 (to A. Sartore-Bianchi, A. Bardelli, andS. Siena). TRANSCAN-2 JTC 2014 contract no. TRS-2015-00000060 INTRACO-LOR (to S. Arena); TRANSCAN-2 JTC 2014 TACTIC (to L. Trusolino); EuropeanResearchCouncil ConsolidatorGrant 724748 -BEAT (toA. Bertotti); AIRC IGn.18532 (to L. Trusolino); AIRC IG n. 20697 (to A. Bertotti); AIRC-CRUK-FCAECC Accelerator Award contract 22795 (to A. Bardelli); Fondazione Piemon-tese per la Ricerca sul Cancro-ONLUS 5 per mille 2014 e 2015 Ministero dellaSalute (to A. Bardelli and E. Medico). Work in M.J. Garnett lab is supported bythe Wellcome Trust (grant no: 206194).

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received October 20, 2018; revised June 13, 2019; accepted July 29, 2019;published first August 2, 2019.






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2019;25:6243-6259. Published OnlineFirst August 2, 2019.Clin Cancer Res Luca Lazzari, Giorgio Corti, Gabriele Picco, et al. Pharmacogenomic Vulnerabilities in Colorectal CancerPatient-Derived Xenografts and Matched Cell Lines Identify

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