Quantitative imaging for development of companion diagnostics to drugs targeting HGF/MET. (1st July 2016)

• Record Type: Journal Article
• Authors: Huang, Fangjin; Ma, Zhaoxuan; Pollan, Sara; Yuan, Xiaopu; Swartwood, Steven; Gertych, Arkadiusz; Rodriguez, Maria; Mallick, Jayati; Bhele, Sanica; Guindi, Maha; Dhall, Deepti; Walts, Ann E; Bose, Shikha; de Peralta Venturina, Mariza; Marchevsky, Alberto M; Luthringer, Daniel J; Feller, Stephan M; Berman, Benjamin; Freeman, Michael R; Alvord, W Gregory; Vande Woude, George; Amin, Mahul B; Knudsen, Beatrice S
• Is Part Of: Journal of pathology. Volume 2:Number 4(2016)
• Page Start: 210
• Page End: 222
• Publication Date: 2016-07-01
• Subjects: HGF/MET -- multi‐cancer tissue microarray -- quantitative imaging; Pathology -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.07
• DOI: 10.1002/cjp2.49
• Languages: English
• ISSNs: 2056-4538

Abstract

Abstract: The limited clinical success of anti‐HGF/MET drugs can be attributed to the lack of predictive biomarkers that adequately select patients for treatment. We demonstrate here that quantitative digital imaging of formalin fixed paraffin embedded tissues stained by immunohistochemistry can be used to measure signals from weakly staining antibodies and provides new opportunities to develop assays for detection of MET receptor activity. To establish a biomarker panel of MET activation, we employed seven antibodies measuring protein expression in the HGF/MET pathway in 20 cases and up to 80 cores from 18 human cancer types. The antibodies bind to epitopes in the extra (EC)‐ and intracellular (IC) domains of MET (MET4 EC, SP44_MET IC, D1C2_MET IC ), to MET‐pY1234/pY1235, a marker of MET kinase activation, as well as to HGF, pSFK or pMAPK. Expression of HGF was determined in tumour cells (T_HGF) as well as in stroma surrounding cancer (St_HGF). Remarkably, MET4 EC correlated more strongly with pMET ( r = 0.47) than SP44_MET IC ( r = 0.21) or D1C2_MET IC ( r = 0.08) across 18 cancer types. In addition, correlation coefficients of pMET and T_HGF ( r = 0.38) and pMET and pSFK ( r = 0.56) were high. Prediction models of MET activation reveal cancer‐type specific differences in performance of MET4 EC, SP44_MET IC and anti‐HGF antibodies. Thus, we conclude that assays to predict the response to HGF/MET inhibitors require a cancer‐type specific antibody selection and should be developed in those cancer types in which they are employed clinically.