Systems analysis of protein signatures predicting Cetuximab responses in KRAS, NRAS, BRAF and PIK3CA wild-type patient-derived xenograft models of metastatic colorectal cancer
journal contributionposted on 2021-12-07, 16:01 authored by Andreas Ulrich Lindner, Steven Carberry, Naser Monsefi, Ana Barat, Manuela Salvucci, Robert O'Byrne, Eugenia R Zanella, Mattia Cremona, Bryan HennessyBryan Hennessy, Andrea Bertotti, Livio Trusolino, Jochen PrehnJochen Prehn
Antibodies targeting the human epidermal growth factor receptor (EGFR) are used for the treatment of RAS wild-type metastatic colorectal cancer. A significant proportion of patients remains unresponsive to this therapy. Here, we performed a reverse-phase protein array-based (phospho)protein analysis of 63 KRAS, NRAS, BRAF and PIK3CA wild-type metastatic CRC tumours. Responses of tumours to anti-EGFR therapy with cetuximab were recorded in patient-derived xenograft (PDX) models. Unsupervised hierarchical clustering of pretreatment tumour tissue identified three clusters, of which Cluster C3 was exclusively composed of responders. Clusters C1 and C2 exhibited mixed responses. None of the three protein clusters exhibited a significant correlation with transcriptome-based subtypes. Analysis of protein signatures across all PDXs identified 14 markers that discriminated cetuximab-sensitive and cetuximab-resistant tumours: PDK1 (S241), caspase-8, Shc (Y317), Stat3 (Y705), p27, GSK-3β (S9), HER3, PKC-α (S657), EGFR (Y1068), Akt (S473), S6 ribosomal protein (S240/244), HER3 (Y1289), NF-κB-p65 (S536) and Gab-1 (Y627). Least absolute shrinkage and selection operator and binominal logistic regression analysis delivered refined protein signatures for predicting response to cetuximab. (Phospo-)protein analysis of matched pretreated and posttreated models furthermore showed significant reduction of Gab-1 (Y627) and GSK-3β (S9) exclusively in responding models, suggesting novel targets for treatment.
Associazione Italiana per la Ricerca sul Cancro, Grant/Award Numbers: 21091, 22795, 22802
Health Research Board, Grant/Award Number: 16/US/3301
Science Foundation Ireland and the Health Research Board, Grant/Award Numbers: 3/IA/1881, 14/IA/2582, 15/ERACSM/3268 and 16/US/3301
Fondazione Piemontese per la Ricerca sul Cancro-ONLUS and 5x1000 Ministero della Salute 2014, 2015 and 2016.
CommentsThis is the peer reviewed version of the following article:, Lindner AU, Carberry S, Monsefi N, Barat A, Salvucci M, O'Byrne R, Zanella ER, Cremona M, Hennessy BT, Bertotti A, Trusolino L, Prehn JHM. Systems analysis of protein signatures predicting Cetuximab responses in KRAS, NRAS, BRAF and PIK3CA wild-type patient-derived xenograft models of metastatic colorectal cancer. Int J Cancer. 2020;147(10):2891-2901, which has been published in final form at https://doi.org/10.1002/ijc.33226. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Published CitationLindner AU. et al. Systems analysis of protein signatures predicting Cetuximab responses in KRAS, NRAS, BRAF and PIK3CA wild-type patient-derived xenograft models of metastatic colorectal cancer. Int J Cancer. 2020;147(10):2891-2901.
Publication Date23 July 2020
- Beaumont Hospital
- Centre for Systems Medicine
- Molecular Medicine
- Physiology and Medical Physics
- Accepted Version (Postprint)
Colorectal NeoplasmsLiver NeoplasmsGTP PhosphohydrolasesProto-Oncogene Proteins B-rafMembrane ProteinsPhosphoproteinsCluster AnalysisXenograft Model Antitumor AssaysProteomicsCell ProliferationProto-Oncogene Proteins p21(ras)Class I Phosphatidylinositol 3-KinasesCetuximabUnsupervised Machine Learninganti-EGFRapoptosisdeterministic modellingmetastatic colorectal cancermolecular subtypingproliferationreverse-phase protein arrayOncology and CarcinogenesisCancerSystems Biology