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A Molecularly Annotated Platform of Patient-Derived Xenografts (“Xenopatients”) Identifies HER2 as an Effective Therapeutic Target in Cetuximab-Resistant Colorectal Cancer
Open accessPublished version of a preprint
Abstract
Only a fraction of patients with metastatic colorectal cancer receive clinical benefit from therapy with anti-epidermal growth factor receptor (EGFR) antibodies, which calls for the identification of novel biomarkers for better personalized medicine. We produced large xenograft cohorts from 85 patient-derived, genetically characterized metastatic colorectal cancer samples (“xenopatients”) to discover novel determinants of therapeutic response and new oncoprotein targets. Serially passaged tumors retained the morphologic and genomic features of their original counterparts. A validation trial confirmed the robustness of this approach: xenopatients responded to the anti-EGFR antibody cetuximab with rates and extents analogous to those observed in the clinic and could be prospectively stratified as responders or nonresponders on the basis of several predictive biomarkers. Genotype–response correlations indicated HER2 amplification specifically in a subset of cetuximab-resistant, KRAS/NRAS/BRAF/PIK3CA wild-type cases. Importantly, HER2 amplification was also enriched in clinically nonresponsive KRAS wild-type patients. A proof-of-concept, multiarm study in HER2-amplified xenopatients revealed that the combined inhibition of HER2 and EGFR induced overt, long-lasting tumor regression. Our results suggest promising therapeutic opportunities in cetuximab-resistant patients with metastatic colorectal cancer, whose medical treatment in the chemorefractory setting remains an unmet clinical need. Significance: Direct transfer xenografts of tumor surgical specimens conserve the interindividual diversity and the genetic heterogeneity typical of the tumors of origin, combining the flexibility of preclinical analysis with the informative value of population-based studies. Our suite of patient-derived xenografts from metastatic colorectal carcinomas reliably mimicked disease response in humans, prospectively recapitulated biomarker-based case stratification, and identified HER2 as a predictor of resistance to anti-epidermal growth factor receptor antibodies and of response to combination therapies against HER2 and epidermal growth factor receptor in this tumor setting. Cancer Discovery; 1(6); 508–23. ©2011 AACR. Read the Commentary on this article by Ciardiello and Normanno, p. 472 This article is highlighted in the In This Issue feature, p. 457
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“HER2 overexpression is a negative predictor associated with reduced efficacy of anti-EGFR therapy [31], and >36% of cetuximab-resistant mCRC with wild-type KRAS, NRAS, BRAF, and PI3K was found to display HER2 overexpression [32].”
From Recent Advances in Therapeutic Strategies to Improve Colorectal Cancer Treatment (2024) · cites this paper as [32]
In the citing paper
“A series of studies have demonstrated that HER2 gene amplification or activating mutations can mediate resistance to anti-EGFR mAbs in CRC [27,178,179].”
From Drug Resistance in Colorectal Cancer: From Mechanism to Clinic (2022) · cites this paper as [27]
In the citing paper
“Preclinical studies have shown that the combination of HER2 and EGFR blockade can lead to CRC tumor regression [27,28,29].”
From Drug Resistance in Colorectal Cancer: From Mechanism to Clinic (2022) · cites this paper as [27]
In the citing paper
“Two independent studies have recently shown that HER2 amplification is a predictor of poor sensitivity to anti-EGFR antibodies [91, 92].”
From Primary and acquired resistance to EGFR-targeted therapies in colorectal cancer: impact on future treatment strategies (2014) · cites this paper as [91]
In the citing paper
“In retrospective studies, patients with tumors featuring HER2 amplification or heregulin overexpression and treated with cetuximab or panitumumab experienced disease progression and shorter progression-free and overall survival compared with HER2 wild-type cases [91-93].”
From Primary and acquired resistance to EGFR-targeted therapies in colorectal cancer: impact on future treatment strategies (2014) · cites this paper as [91]
In the citing paper
“only the dual targeting of HER2 and EGFR by combining a small-molecule inhibitor, such as the dual EGFR/HER2 inhibitor lapatinib, with a moAb, such as cetuximab or pertuzumab, induced overt and long-lasting tumor regressions in proof-of-concept trials in HER2-amplified xenopatients [91].”
From Primary and acquired resistance to EGFR-targeted therapies in colorectal cancer: impact on future treatment strategies (2014) · cites this paper as [91]
In the citing paper
“Increased EGFR gene copy number could predict response among KRAS wild-type patients [53, 91, 111-113]”
From Primary and acquired resistance to EGFR-targeted therapies in colorectal cancer: impact on future treatment strategies (2014) · cites this paper as [91]
In the citing paper
“Strong preclinical evidence suggests that dual inhibition of ERBB2 is superior to monotherapy due to enhanced efficacy and reduced therapy resistance4648”
From Current and emerging concepts for systemic treatment of metastatic colorectal cancer (2025) · cites this paper as [46]
In the citing paper
“Bertotti et al. identified ERBB2 as a biomarker of resistance to anti-EGFR mAbs [113].”
From Resistance to anti-EGFR therapies in metastatic colorectal cancer: underlying mechanisms and reversal strategies (2021) · cites this paper as [113]
In the citing paper
“A total of 2–7% of unselected CRCs were found to have ERBB2/mutations, and this number was much higher in KRAS wild-type cases (13.6%) and in KRAS/NRAS/BRAF/PIK3CA quadruple wild-type cases (36% )[13, 113, 114].”
From Resistance to anti-EGFR therapies in metastatic colorectal cancer: underlying mechanisms and reversal strategies (2021) · cites this paper as [113]
In the citing paper
“Finally, using patient-derived colon cancer xenografts, Bertotti et al. identified HER2 gene amplification as a predictor of resistance to cetuximab among KRAS wild-type tumors (Bertotti et al., 2011).”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Bertotti et al., 2011
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Citations
Cites
Cunningham, D., Humblet, Y., Siena, S., Khayat, D., Bleiberg, H., Santoro, A., Bets, D., Mueser, M., Harstrick, A., Verslype, C., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa033025 · Cited by 5,035
Self-citationCetuximab and Chemotherapy as Initial Treatment for Metastatic Colorectal Cancer
Van Cutsem, E., Köhne, C.-H., Hitre, E., Zaluski, J., Chang Chien, C.-R., Makhson, A., D'Haens, G., Pintér, T., Lim, R., Bodoky, G., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0805019 · Cited by 3,877
K-ras Mutations and Benefit from Cetuximab in Advanced Colorectal Cancer
Karapetis, C. S., Khambata-Ford, S., Jonker, D. J., O'Callaghan, C. J., Tu, D., Tebbutt, N. C., Simes, R. J., Chalchal, H., Shapiro, J. D., Robitaille, S., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0804385 · Cited by 3,622
ERBB receptors and cancer: the complexity of targeted inhibitors
Hynes, N. E., & Lane, H. A. (2005) · Nature reviews. Cancer · doi:10.1038/nrc1609 · Cited by 3,379
Wild-Type KRAS Is Required for Panitumumab Efficacy in Patients With Metastatic Colorectal Cancer
Amado, R. G., Wolf, M., Peeters, M., Van Cutsem, E., Siena, S., Freeman, D. J., Juan, T., Sikorski, R., Suggs, S., Radinsky, R., et al. (2008) · Journal of Clinical Oncology · doi:10.1200/jco.2007.14.7116 · Cited by 3,207
Self-citationUmar, A., Boland, C. R., Terdiman, J. P., Syngal, S., de la Chapelle, A., Rüschoff, J., Fishel, R. A., Lindor, N. M., Burgart, L. J., Hamelin, R., et al. (2004) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djh034 · Cited by 3,181
The Genomic Landscapes of Human Breast and Colorectal Cancers
Wood, L. D., Parsons, D. W., Jones, S., Lin, J., Sjöblom, T., Leary, R. J., Shen, D., Boca, S. M., Barber, T., Ptak, J., et al. (2007) · Science · doi:10.1126/science.1145720 · Cited by 2,833
De Roock, W., Claes, B., Bernasconi, D., De Schutter, J., Biesmans, B., Fountzilas, G., Kalogeras, K. T., Kotoula, V., Papamichael, D., Laurent-Puig, P., et al. (2010) · The Lancet Oncology · doi:10.1016/s1470-2045(10)70130-3 · Cited by 2,144
Self-citationVan Cutsem, E., Peeters, M., Siena, S., Humblet, Y., Hendlisz, A., Neyns, B., Canon, J.-L., Van Laethem, J.-L., Maurel, J., Richardson, G., et al. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.08.1620 · Cited by 1,979
Self-citationCetuximab for the Treatment of Colorectal Cancer
Jonker, D. J., O'Callaghan, C. J., Karapetis, C. S., Zalcberg, J. R., Tu, D., Au, H.-J., Berry, S. R., Krahn, M., Price, T., Simes, R. J., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa071834 · Cited by 1,904
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ESMO consensus guidelines for the management of patients with metastatic colorectal cancer
Van Cutsem, E., Cervantes, A., Adam, R., Sobrero, A., Van Krieken, J. H., Aderka, D., Aranda Aguilar, E., Bardelli, A., Benson, A., Bodoky, G., et al. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw235 · Cited by 3,421
Self-citationPatient-Derived Xenograft Models: An Emerging Platform for Translational Cancer Research
Hidalgo, M. M., Amant, F. C., Biankin, A. V., Budínská, E., Byrne, A. T., Caldas, C., Clarke, R. B., de Jong, S., Jonkers, J., Mælandsmo, G. M., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0001 · Cited by 1,797
Self-citationComprehensive review of targeted therapy for colorectal cancer
Xie, Y.-H., Chen, Y.-X., & Fang, J.-Y. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-0116-z · Cited by 1,687
Gao, H., Korn, J. M., Ferretti, S., Monahan, J. E., Wang, Y., Singh, M., Zhang, C., Schnell, C., Yang, G., Zhang, Y., et al. (2015) · Nature Medicine · doi:10.1038/nm.3954 · Cited by 1,393
Patient-derived tumour xenografts as models for oncology drug development
Tentler, J. J., Tan, A. C., Weekes, C. D., Jimeno, A., Leong, S., Pitts, T. M., Arcaroli, J. J., Messersmith, W. A., & Eckhardt, S. G. (2012) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2012.61 · Cited by 1,277
Clonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients
Siravegna, G., Mussolin, B., Buscarino, M., Corti, G., Cassingena, A., Crisafulli, G., Ponzetti, A., Cremolini, C., Amatu, A., Lauricella, C., et al. (2015) · Nature Medicine · doi:10.1038/nm.3870 · Cited by 1,088
Self-citationERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics
Arteaga, C. L., & Engelman, J. A. (2014) · Cancer Cell · doi:10.1016/j.ccr.2014.02.025 · Cited by 1,048
Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer
Dienstmann, R., Vermeulen, L., Guinney, J., Kopetz, S., Tejpar, S., & Tabernero, J. M. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2016.126 · Cited by 1,075
Sartore-Bianchi, A., Trusolino, L., Martino, C., Bencardino, K., Lonardi, S., Bergamo, F., Zagonel, V., Leone, F., Depetris, I., Martinelli, E., et al. (2016) · The Lancet Oncology · doi:10.1016/s1470-2045(16)00150-9 · Cited by 1,016
Self-citationHER2-targeted therapies — a role beyond breast cancer
Oh, D.-Y., & Bang, Y.-J. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0268-3 · Cited by 1,081
HER kinase inhibition in patients with HER2- and HER3-mutant cancers
Hyman, D. M., Piha-Paul, S. A., Won, H., Rodon, J., Saura, C., Shapiro, G. I., Juric, D., Quinn, D. I., Moreno, V., Doger, B., et al. (2018) · Nature · doi:10.1038/nature25475 · Cited by 780
From tumour heterogeneity to advances in precision treatment of colorectal cancer
Punt, C. J. A., Koopman, M., & Vermeulen, L. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.171 · Cited by 654
Takezawa, K., Pirazzoli, V., Arcila, M. E., Nebhan, C. A., Song, X., de Stanchina, E., Ohashi, K., Janjigian, Y. Y., Spitzler, P. J., Melnick, M. A., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0108 · Cited by 710
Metastatic colorectal cancer: mechanisms and emerging therapeutics
Shin, A. E., Giancotti, F. G., & Rustgi, A. K. (2023) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2023.01.003 · Cited by 717
Amplification of the MET Receptor Drives Resistance to Anti-EGFR Therapies in Colorectal Cancer
Bardelli, A., Corso, S., Bertotti, A., Hobor, S., Valtorta, E., Siravegna, G., Sartore-Bianchi, A., Scala, E., Cassingena, A., Zecchin, D., et al. (2013) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0558 · Cited by 657
Self-citationInterrogating open issues in cancer precision medicine with patient-derived xenografts
Byrne, A. T., Alférez, D., Amant, F. C., Annibali, D., Arribas, J., Biankin, A. V., Bruna, A., Budínská, E., Caldas, C., Chang, D. K.-F., et al. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2016.140 · Cited by 683
Self-citationEGFR in Cancer: Signaling Mechanisms, Drugs, and Acquired Resistance
Uribe, M. L., Marrocco, I., & Yarden, Y. (2021) · Cancers · doi:10.3390/cancers13112748 · Cited by 604
Stromal contribution to the colorectal cancer transcriptome
Isella, C., Terrasi, A., Bellomo, S. E., Petti, C., Galatola, G., Muratore, A., Mellano, A., Senetta, R., Cassenti, A., Sonetto, C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3224 · Cited by 640
Self-citationMeric-Bernstam, F., Hurwitz, H., Raghav, K. P. S., McWilliams, R. R., Fakih, M., VanderWalde, A., Swanton, C., Kurzrock, R., Burris, H., Sweeney, C., et al. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30904-5 · Cited by 573
Resistance to anti-EGFR therapy in colorectal cancer: From heterogeneity to convergent evolution
Misale, S., Di Nicolantonio, F., Sartore-Bianchi, A., Siena, S., & Bardelli, A. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0462 · Cited by 513
Self-citationClinical management of metastatic colorectal cancer in the era of precision medicine
Ciardiello, F., Ciardiello, D., Martini, G., Napolitano, S., Tabernero, J. M., & Cervantes, A. M. R. (2022) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21728 · Cited by 556
Metastatic Colorectal Cancer: Current State and Future Directions
Fakih, M. (2015) · Journal of Clinical Oncology · doi:10.1200/jco.2014.59.7633 · Cited by 536
Pharmacologic resistance in colorectal cancer: a review
Hammond, W. A., Swaika, A., & Mody, K. (2015) · Therapeutic Advances in Medical Oncology · doi:10.1177/1758834015614530 · Cited by 544
Parikh, A. R., Leshchiner, I., Elagina, L., Goyal, L., Levovitz, C., Siravegna, G., Livitz, D., Rhrissorrakrai, K., Martin, E. E., Van Seventer, E. E., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0561-9 · Cited by 518
Self-citationEGFR Blockade Reverts Resistance to KRASG12C Inhibition in Colorectal Cancer.
Amodio, V., Yaeger, R., Arcella, P., Cancelliere, C., Lamba, S., Lorenzato, A., Arena, S., Montone, M., Mussolin, B., Bian, Y., et al. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0187 · Cited by 504
“Taking advantage of our molecularly and therapeutically annotated CRC patient-derived bio-bank (25-27), in a cohort of more than one hundred patient-derived organoids (PDO), we selected three different KRAS G12C mutant PDOs and one KRAS G12D mutant PDO (as negative control) and tested the effects of single agents AMG5…”
MethodSelf-citationPatient-derived xenograft models in cancer therapy: technologies and applications
Liu, Y., Wu, W., Cai, C., Zhang, H., Shen, H., & Han, Y. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01419-2 · Cited by 533
Genetically engineered mouse models in oncology research and cancer medicine
Kersten, K., de Visser, K. E., van Miltenburg, M. H., & Jonkers, J. (2017) · EMBO Molecular Medicine · doi:10.15252/emmm.201606857 · Cited by 502
Tumor Organoids as a Pre-clinical Cancer Model for Drug Discovery
Weeber, F., Ooft, S., Dijkstra, K. K., & Voest, E. E. (2017) · Cell chemical biology · doi:10.1016/j.chembiol.2017.06.012 · Cited by 501
Genome-Informed Targeted Therapy for Osteosarcoma
Sayles, L. C., Breese, M. R., Koehne, A. L., Leung, S. G., Lee, A. G., Liu, H.-Y., Spillinger, A., Shah, A. T., Tanasa, B., Straessler, K., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-1152 · Cited by 452
The Genomic Landscape of Response to EGFR Blockade in Colorectal Cancer
Bertotti, A., Papp, E., Jones, S., Adleff, V., Anagnostou, V., Lupo, B., Sausen, M., Phallen, J., Hruban, C. A., Tokheim, C., et al. (2015) · Nature · doi:10.1038/nature14969 · Cited by 479
Self-citationApplications of patient-derived tumor xenograft models and tumor organoids
Yoshida, G. J. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-019-0829-z · Cited by 471
Xenograft and organoid model systems in cancer research
Bleijs, M., van de Wetering, M., Clevers, H., & Drost, J. (2019) · The EMBO Journal · doi:10.15252/embj.2019101654 · Cited by 400
Colorectal Cancer Stem Cells: From the Crypt to the Clinic
Zeuner, A., Todaro, M., Stassi, G., & Maria, R. D. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.11.012 · Cited by 384
Julien-Grille, S., Merino‐Trigo, A., Lacroix, L., Pocard, M. D., Goèré, D., Mariani, P., Landron, S., Bigot, L., Némati, F., Dartigues, P., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-0372 · Cited by 358
Advances in HER2-Targeted Therapy: Novel Agents and Opportunities Beyond Breast and Gastric Cancer
Meric‐Bernstam, F., Johnson, A. M., Dumbrava, E. E. I., Raghav, K. P. S., Balaji, K., Bhatt, M., Murthy, R. K., Rodon, J. A., & Piha-Paul, S. A. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-2275 · Cited by 348
Examining the utility of patient-derived xenograft mouse models
Aparicio, S. A. J. R., Hidalgo, M. M., & Kung, A. L. (2015) · Nature reviews. Cancer · doi:10.1038/nrc3944 · Cited by 352
Mechanisms of resistance to anti-EGFR therapy in colorectal cancer
Zhao, B., Wang, L., Qiu, H., Zhang, M., Sun, L., Peng, P., Yu, Q., & Yuan, X. (2017) · Oncotarget · doi:10.18632/oncotarget.14012 · Cited by 319
Izumchenko, E., Paz, K., Ciznadija, D., Sloma, I., Katz, A. M., Vasquez-Dunddel, D., Zvi, I. B., Stebbing, J., McGuire, W. P., Harris, W. P., et al. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx416 · Cited by 326
Patient-derived xenograft (PDX) models, applications and challenges in cancer research
Abdolahi, S., Ghazvinian, Z., Muhammadnejad, S., Saleh, M., Aghdaei, H. A., & Baghaei, K. (2022) · Journal of Translational Medicine · doi:10.1186/s12967-022-03405-8 · Cited by 340
A perspective on anti-EGFR therapies targeting triple-negative breast cancer.
Nakai, K., Hung, M., & Yamaguchi, H. (2016) · Europe PMC (PubMed Central) · Cited by 336
Biomarker-guided therapy for colorectal cancer: strength in complexity
Sveen, A., Kopetz, S., & Lothe, R. A. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0241-1 · Cited by 320
Precision Medicine: Disease Subtyping and Tailored Treatment
Wang, R. C., & Wang, Z. (2023) · Cancers · doi:10.3390/cancers15153837 · Cited by 354
Assessment of a HER2 scoring system for colorectal cancer: results from a validation study
Valtorta, E., Martino, C., Bianchi, A. S., Penault-Llorca, F. M., Viale, G., Risio, M., Rugge, M., Grigioni, W., Bencardino, K. B., Lonardi, S., et al. (2015) · Modern Pathology · doi:10.1038/modpathol.2015.98 · Cited by 320
Self-citationThe Generation and Application of Patient-Derived Xenograft Model for Cancer Research
Jung, J., Seol, H. S., & Chang, S. (2017) · Cancer Research and Treatment · doi:10.4143/crt.2017.307 · Cited by 325
Isella, C., Brundu, F. G., Bellomo, S. E., Galimi, F., Zanella, E. R., Porporato, R., Petti, C., Fiori, A., Orzan, F., Senetta, R., et al. (2017) · Nature Communications · doi:10.1038/ncomms15107 · Cited by 304
Self-citationThe molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets
Medico, E., Russo, M., Picco, G., Cancelliere, C., Valtorta, E., Corti, G., Buscarino, M., Isella, C., Lamba, S., Martinoglio, B., et al. (2015) · Nature Communications · doi:10.1038/ncomms8002 · Cited by 302
Self-citationHER2 Activating Mutations Are Targets for Colorectal Cancer Treatment
Kavuri, S. M., Jain, N., Galimi, F., Cottino, F., Leto, S. M., Migliardi, G., Searleman, A. C., Shen, W., Monsey, J., Trusolino, L., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-1211 · Cited by 302
Self-citationThe Public Repository of Xenografts Enables Discovery and Randomized Phase II-like Trials in Mice
Townsend, E. C., Murakami, M. A., Christodoulou, A., Christie, A. L., Köster, J., DeSouza, T. A., Morgan, E. A., Kallgren, S. P., Liu, H., Wu, S.-C., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.03.008 · Cited by 295
Genomic Landscape of Cell-Free DNA in Patients with Colorectal Cancer
Strickler, J. H., Loree, J. M., Ahronian, L. G., Parikh, A. R., Niedzwiecki, D., Pereira, A. A. L., McKinney, M. S., Korn, W. M., Atreya, C. E., Banks, K. C., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-1009 · Cited by 300
One mouse, one patient paradigm: New avatars of personalized cancer therapy
Malaney, P., Nicosia, S. V., & Davé, V. (2013) · Cancer Letters · doi:10.1016/j.canlet.2013.10.010 · Cited by 290
Personalized Cancer Medicine: An Organoid Approach
Es, H. A., Montazeri, L., Aref, A. R., Vosough, M., & Baharvand, H. (2018) · Trends in biotechnology · doi:10.1016/j.tibtech.2017.12.005 · Cited by 286
Dulak, A. M., Schumacher, S. E., van Lieshout, J., Imamura, Y., Fox, C., Shim, B., Ramos, A. H., Saksena, G., Baca, S. C., Baselga, J. M., et al. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-3893 · Cited by 273
Patient-derived xenograft (PDX) models in basic and translational breast cancer research
Dobrolecki, L. E., Airhart, S., Alférez, D., Aparicio, S. A. J. R., Behbod, F., Bentires‐Alj, M., Brisken, C., Bult, C. J., Cai, S., Clarke, R. B., et al. (2016) · Cancer and Metastasis Reviews · doi:10.1007/s10555-016-9653-x · Cited by 272
Misale, S., Arena, S., Lamba, S., Siravegna, G., Lallo, A., Hobor, S., Russo, M., Buscarino, M., Lazzari, L., Sartore-Bianchi, A., et al. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3007947 · Cited by 263
Self-citationOkada, S., Vaeteewoottacharn, K., & Kariya, R. (2019) · Cells · doi:10.3390/cells8080889 · Cited by 264
Fang, J., Zhou, H., Zhang, C., Shang, L., Zhang, L., Xu, J., Zheng, L., Yuan, Y., Guo, R., Jia, W., et al. (2015) · Hepatology · doi:10.1002/hep.27760 · Cited by 260
Strickler, J. H., Cercek, A., Siena, S., André, T., Ng, K., Van Cutsem, E., Wu, C., Paulson, A. S., Hubbard, J. M., Coveler, A. L., et al. (2023) · The Lancet Oncology · doi:10.1016/s1470-2045(23)00150-x · Cited by 259
Self-citationZhou, J., Ji, Q., & Li, Q. (2021) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-021-02130-2 · Cited by 246
Nakamura, Y., Okamoto, W., Kato, T., Esaki, T., Kato, K., Komatsu, Y., Yuki, S., Masuishi, T., Nishina, T., Ebi, H., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01553-w · Cited by 231
Targeting the human epidermal growth factor receptor 2 (HER2) oncogene in colorectal cancer
Siena, S., Bianchi, A. S., Marsoni, S., Hurwitz, H. I., McCall, S. J., Penault-Llorca, F. M., Srock, S., Bardelli, A., & Trusolino, L. (2018) · Annals of Oncology · doi:10.1093/annonc/mdy100 · Cited by 254
Self-citationRichman, S. D., Southward, K., Chambers, P., Cross, D., Barrett, J., Hemmings, G., Taylor, M., Wood, H., Hutchins, G., Foster, J. M., et al. (2016) · The Journal of Pathology · doi:10.1002/path.4679 · Cited by 241
S3-Leitlinie – Kolorektales Karzinom
Schmiegel, W., Buchberger, B., Follmann, M., Graeven, U., Heinemann, V., Langer, T. G., Nothacker, M., Porschen, R., Rödel, C. M., Rösch, T., et al. (2017) · Zeitschrift für Gastroenterologie · doi:10.1055/s-0043-121106 · Cited by 247
Precision oncology in metastatic colorectal cancer — from biology to medicine
Nicolantonio, F. D., Vitiello, P. P., Marsoni, S., Siena, S., Tabernero, J. M., Trusolino, L., Bernards, R., & Bardelli, A. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-021-00495-z · Cited by 244
Self-citationMartinelli, E., Ciardiello, D., Martini, G., Troiani, T., Cardone, C., Vitiello, P. P., Normanno, N., Rachiglio, A. M., Maiello, E., Latiano, T., et al. (2020) · Annals of Oncology · doi:10.1016/j.annonc.2019.10.007 · Cited by 225
Wu, C. X., Wang, X. Q., Chok, K., Man, K., Tsang, S. H. Y., Chan, A. C. Y., Wing, K., Xia, W. G., & Cheung, T. T. (2018) · Theranostics · doi:10.7150/thno.25487 · Cited by 228
Basic principles of biobanking: from biological samples to precision medicine for patients
Annaratone, L., Palma, G. D., Bonizzi, G., Sapino, A., Botti, G., Berrino, E., Mannelli, C., Arcella, P., Martino, S. D., Steffan, A., et al. (2021) · Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin · doi:10.1007/s00428-021-03151-0 · Cited by 227
Self-citationGenomic evolution of cancer models: perils and opportunities
Ben‐David, U., Beroukhim, R., & Golub, T. R. (2018) · Nature reviews. Cancer · doi:10.1038/s41568-018-0095-3 · Cited by 234
The role of mouse tumour models in the discovery and development of anticancer drugs
Ireson, C. R., Alavijeh, M. S., Palmer, A. M., Fowler, E. R., & Jones, H. (2019) · British Journal of Cancer · doi:10.1038/s41416-019-0495-5 · Cited by 226
Comparative molecular analyses of left-sided colon, right-sided colon, and rectal cancers
Salem, M. E., Weinberg, B. A., Xiu, J., El‐Deiry, W. S., Hwang, J. J., Gatalica, Z., Philip, P. A., Shields, A. F., Lenz, H., & Marshall, J. L. (2017) · Oncotarget · doi:10.18632/oncotarget.21169 · Cited by 223
Nanomaterials for Cancer Precision Medicine
Wang, Y., Sun, S., Zhang, Z., & Shi, D. (2018) · Advanced Materials · doi:10.1002/adma.201705660 · Cited by 213
HER2 aberrations in cancer: Implications for therapy
Yan, M., Parker, B. A., Schwab, R. B., & Kurzrock, R. (2014) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2014.02.008 · Cited by 212
Ross, J. S., Fakih, M., Ali, S. M., Elvin, J. A., Schrock, A. B., Suh, J. H., Vergilio, J., Ramkissoon, S. H., Severson, E. A., Daniel, S., et al. (2018) · Cancer · doi:10.1002/cncr.31125 · Cited by 218
PDXNET Consortium, Woo, X. Y., EurOPDX Consortium, Giordano, J., Srivastava, A., Zhao, Z.-M., Lloyd, M. W., de Bruijn, R., Suh, Y.-S., Patidar, R., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00750-6 · Cited by 190
Self-citationMigliardi, G., Sassi, F., Torti, D., Galimi, F., Zanella, E. R., Buscarino, M., Ribero, D., Muratore, A., Massucco, P., Pisacane, A., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-2683 · Cited by 191
Self-citationPromises and challenges of organoid-guided precision medicine
Bose, S., Clevers, H., & Shen, X. (2021) · Med · doi:10.1016/j.medj.2021.08.005 · Cited by 213
The Insulin/IGF System in Colorectal Cancer Development and Resistance to Therapy
Vigneri, P. G., Tirrò, E., Pennisi, M. S., Massimino, M., Stella, S., Romano, C., & Manzella, L. (2015) · Frontiers in Oncology · doi:10.3389/fonc.2015.00230 · Cited by 192
Bianchi, A. S., Lonardi, S., Martino, C., Fenocchio, E., Tosi, F., Ghezzi, S., Leone, F., Bergamo, F., Zagonel, V., Ciardiello, F., et al. (2020) · ESMO Open · doi:10.1136/esmoopen-2020-000911 · Cited by 188
Self-citationPietrantonio, F., Vernieri, C., Siravegna, G., Mennitto, A., Berenato, R., Perrone, F., Gloghini, A., Tamborini, E., Lonardi, S., Morano, F., et al. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-1863 · Cited by 182
Self-citationPalma, M. D., & Hanahan, D. (2012) · Molecular Oncology · doi:10.1016/j.molonc.2012.01.011 · Cited by 188
KRAS gene amplification in colorectal cancer and impact on response to EGFR‐targeted therapy
Valtorta, E., Misale, S., Sartore‐Bianchi, A., Nagtegaal, I. D., Paraf, F., Lauricella, C., Dimartino, V., Hobor, S., Jacobs, B., Ercolani, C., et al. (2013) · International Journal of Cancer · doi:10.1002/ijc.28106 · Cited by 175
Self-citationArqués, O., Chicote, I., Puig, I., Tenbaum, S. P., Argilés, G., Dienstmann, R., Fernández, N., Caratù, G., Matito, J., Silberschmidt, D., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-3081 · Cited by 179
Lessons from patient-derived xenografts for better in vitro modeling of human cancer
Choi, S. Y. C., Lin, D., Gout, P. W., Collins, C. C., Xu, Y., & Wang, Y. Z. (2014) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2014.09.009 · Cited by 181
Rosfjord, E. C., Lucas, J., Li, G., & Gerber, H. (2014) · Biochemical Pharmacology · doi:10.1016/j.bcp.2014.06.008 · Cited by 178
Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and in vivo models
Linnekamp, J. F., van Hooff, S. R., Prasetyanti, P. R., Kandimalla, R., Buikhuisen, J. Y., Fessler, E., Ramesh, P., Lee, K. A. S. T., Bochove, G. G. W., de Jong, J. H., et al. (2018) · Cell Death and Differentiation · doi:10.1038/s41418-017-0011-5 · Cited by 182
Mohan, S., Heitzer, E., Ulz, P., Lafer, I., Lax, S., Auer, M., Pichler, M., Gerger, A., Eisner, F., Höefler, G., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004271 · Cited by 178
Seo, A. N., Kwak, Y., Kim, D., Kang, S., Choe, G., Kim, W. H., & Lee, H. S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098528 · Cited by 177
Yoshino, T., Di Bartolomeo, M., Raghav, K., Masuishi, T., Loupakis, F., Kawakami, H., Yamaguchi, K., Nishina, T., Wainberg, Z., Elez, E., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38032-4 · Cited by 178
Self-citationHER2 Positivity Predicts Unresponsiveness to EGFR-Targeted Treatment in Metastatic Colorectal Cancer
Bianchi, A. S., Amatu, A., Porcu, L., Ghezzi, S., Lonardi, S., Leone, F., Bergamo, F., Fenocchio, E., Martinelli, E., Borelli, B., et al. (2019) · The Oncologist · doi:10.1634/theoncologist.2018-0785 · Cited by 174
Self-citationMouse models of colorectal cancer: Past, present and future perspectives
Bürtin, F., Mullins, C. S., & Linnebacher, M. (2020) · World Journal of Gastroenterology · doi:10.3748/wjg.v26.i13.1394 · Cited by 183
Efficient Use of Patient-Derived Organoids as a Preclinical Model for Gynecologic Tumors
Maru, Y., Tanaka, N., Itami, M., & Hippo, Y. (2019) · Gynecologic Oncology · doi:10.1016/j.ygyno.2019.05.005 · Cited by 162
Ex Vivo Tumor Culture Systems for Functional Drug Testing and Therapy Response Prediction
Meijer, T. G., Naipal, K. A. T., Jager, A., & van Gent, D. C. (2017) · Future Science OA · doi:10.4155/fsoa-2017-0003 · Cited by 166
XenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data
Kluin, R. J. C., Kemper, K., Kuilman, T., de Ruiter, J. R., Iyer, V., Forment, J. V., Cornelissen‐Steijger, P., de Rink, I., ter Brugge, P., Song, J., et al. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2353-5 · Cited by 167
Patient-derived organoids in precision cancer medicine
Tong, L., Cui, W., Zhang, B., Fonseca, P., Zhao, Q. C., Zhang, P., Xu, B., Zhang, Q., Li, Z., Seashore-Ludlow, B. A., et al. (2024) · Med · doi:10.1016/j.medj.2024.08.010 · Cited by 192
Martin, V, Landi, L., Molinari, F., Fountzilas, G., Geva, R., Riva, A., Saletti, P., De Dosso, S., Spitale, A., Tejpar, S., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.4 · Cited by 156
Meraz, I. M., Majidi, M., Meng, F., Shao, R., Ha, M. J., Neri, S., Fang, B., Lin, S. H., Tinkey, P. T., Shpall, E. J., et al. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0874 · Cited by 165
Drug Resistance in Colorectal Cancer: From Mechanism to Clinic
Wang, Q., Shen, X., Chen, G., & Du, J. (2022) · Cancers · doi:10.3390/cancers14122928 · Cited by 160
Acquired resistance to EGFR‐targeted therapies in colorectal cancer
Emburgh, B. O. V., Bianchi, A. S., Nicolantonio, F. D., Siena, S., & Bardelli, A. (2014) · Molecular Oncology · doi:10.1016/j.molonc.2014.05.003 · Cited by 162
Self-citationAfrăsânie, V.-A., Marinca, M. V., Alexa‐Stratulat, T., Gafton, B., Păduraru, M., Adavidoaiei, A. M., Miron, L., & Rusu, C. (2019) · Radiology and Oncology · doi:10.2478/raon-2019-0033 · Cited by 164
Radiologic and Genomic Evolution of Individual Metastases during HER2 Blockade in Colorectal Cancer
Siravegna, G., Lazzari, L., Crisafulli, G., Bianchi, A. S., Mussolin, B., Cassingena, A., Martino, C., Lanman, R. B., Nagy, R. J., Fairclough, S. R., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.06.004 · Cited by 159
Self-citation
Metadata
- Authors
- Bertotti, A., Migliardi, G., Galimi, F., Sassi, F., Torti, D., Isella, C., Corà, D., Di Nicolantonio, F., Buscarino, M., Petti, C., Ribero, D., Russolillo, N., Muratore, A., Massucco, P., Pisacane, A., Molinaro, L., Valtorta, E., Sartore-Bianchi, A., Risio, M., Capussotti, L., Gambacorta, M., Siena, S., Medico, E., Sapino, A., Marsoni, S., Comoglio, P. M., Bardelli, A., & Trusolino, L.
- Affiliations
- IFOM (IT)
- Authors' Affiliations: 1Laboratory of Molecular Pharmacology, 2Laboratory of Oncogenomics, 3Laboratory of Systems Biology, 4Laboratory of Molecular Genetics, 5Division of Surgical Oncology, 6Unit of Pathology, 7Clinical Coordination Unit, and 8Molecular Clinical Oncology, Institute for Cancer Research and Treatment, Torino; Departments of 9Oncological Sciences and 10Biomedical Sciences and Human Oncology, University of Torino Medical School, Torino; 11Department of Surgery, Mauriziano Umberto I Hospital, Torino; 12FIRC Institute of Molecular Oncology, Milano; 13Division of Pathology, 14Falck Division of Medical Oncology, Ospedale Niguarda Ca' Granda, Milano; and 15Southern Europe New Drug Organization Foundation, Milano, Italy
- ORCID
- Venue
- Cancer Discovery
- Published
- 2011-11-01
- Volume
- 1
- Issue
- 6
- Pages
- 508-523
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- OpenAlex
- W1987443121
- Cited by
- 939
- References
- 56
- Citations by year
- 2026: 24 · 2025: 42 · 2024: 46 · 2023: 79 · 2022: 72 · 2021: 74 · 2020: 71 · 2019: 86 · 2018: 86 · 2017: 90 · 2016: 71 · 2015: 62 · 2014: 60 · 2013: 48 · 2012: 23
- FWCI
- 21.44
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
- Funders
- Ministero dell’Istruzione, dell’Università e della Ricerca
- Associazione Italiana per la Ricerca sul Cancro
- Regione Piemonte
- Genentech
- Topics
- Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Keywords
- patient-derived xenografts, metastatic colorectal cancer, cetuximab resistance, HER2 amplification, anti-EGFR therapy, predictive biomarkers, combination therapy, KRAS wild-type, BRAF wild-type, treatment resistance, tumor heterogeneity
- MeSH terms
- Cetuximab, Aged, Aged, 80 and over, Animals, Antibodies, Monoclonal, Female, Humans, Male, Mice, Inbred C57BL, Mice, Transgenic, Middle Aged, Prospective Studies, Biomarkers, Tumor, Colorectal Neoplasms, ras Proteins, Receptor, ErbB-2, Erb-b2 Receptor Tyrosine Kinases, Drug Resistance, Neoplasm, Xenograft Model Antitumor Assays, Mice, Molecular Targeted Therapy, Antibodies, Monoclonal, Humanized, ErbB Receptors
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