High-sensitive clinical diagnostic method for PTPRZ1-MET and the characteristic protein structure contributing to ligand-independent MET activation

Abstract

Background: PTPRZ1-MET (ZM) is a critical genetic alteration driving the progression of lower-grade glioma. Glioma patients harboring ZM could benefit from MET inhibitors. According to the remarkable role of ZM as a driver of glioma progression and indicator of MET inhibitor sensitivity, it is necessary to detect this alteration even when it presents in glioma with relatively fewer copies.

Methods: Herein, we proposed that ZM could be detected with a high-sensitive method of reverse transcriptase PCR with 50 amplification cycles. Via this newly proposed detection method, we depicted the incidence preference of ZM fusion in a cohort of 485 glioma patients. To further explore the oncogenic nature of ZM, we predicated the protein structure alteration of MET kinase brought by its fusion partner.

Results: The incidence of ZM fusions was much higher than previous report. ZM fusions exhibited a striking preference in lower-grade glioma and secondary glioblastoma. By contrast, none of patients with primary glioblastoma was detected harboring ZM fusion. In each of the four variants of ZM, the fusion partner segment of MET contained a remarkable coiled-coil motif. In glioma cells expressing ZM, MET kinase could be activated in a ligand-independent manner, which might be contributed by the special coiled-coil structure brought by the fusion partner. Corresponding to the 3D structural analysis and cell line experiment, the ZM positive clinical specimens showed hyperactivations of MET signaling.

Conclusions: ZM fusions are critical drivers of glioma progression and effective target of MET inhibitor. Early detection could be performed with a high-sensitive method of reverse transcriptase PCR. The hyperactivations of MET signaling driving glioma progression might be contributed by a ligand-independent activation enabled by the protein structure modification of extracellular domain of MET in ZM fusions.

Keywords: MET inhibitor; coiled-coil structure; glioma progression; receptor tyrosine kinase.

FIGURE 1

Illustration of the PCR‐sequencing diagnostic method. Glioma tissue RNA was abstracted after surgery. RT‐PCR of 50 amplification cycles then was performed with the primers designed based on the PTPRZ1 and MET segments that are common to all the four ZM fusion variants. The PCR products of different ZM variants were of different sizes. All the PCR product bands on agarose gel were purified and sequenced via Sanger sequencing. The sequencing reads were aligned to the known ZM fusion sequences. The existence and the variant of ZM fusions then was confirmed and clinically reported.

FIGURE 2

Demonstration of the specificity and robustness of ZM fusions segments amplification using reverse transcriptase PCR of 50 amplification cycles. A, Model of the ideal amplification method of ZM by RT‐PCR. The primers should be specific for ZM fusions and would not product any specific bands from control tissue such as the peripheral blood of the patients harboring ZM, or the glioma tissue from the patients without ZM. The quantity of ZM fragments should grow firmly along with increase in the number of amplification cycles. The number of amplification cycles at which the PCR products will not increase markedly anymore should be adopted as the amplification number used in an ideal detection method. B, The specificity of the amplification approach was evaluated through comparing ZM+ glioma tissue with ZM− glioma tissue, peripheral blood of the patients harboring ZM, and peripheral blood of the patients without ZM via RT‐PCR with 30 or 50 amplification cycles separately. A star indicates a non‐specific band of smaller size than the specific bands of ZM fusions. C, RT‐PCR amplifying ZM was separately performed with number of amplification cycles as 30, 40, 50, or 60. D, All the PCR product bands on agarose gel were purified and sequenced via Sanger sequencing and the fusion point of PTPRZ1 and MET segment was confirmed. E, Growth curve of the sums of the gray intensity value of the PCR product bands derived from ten ZM+ glioma tissues at each cycle number in panel C.

FIGURE 3

Distribution characteristics of ZM variants. A, Incidence of ZM fusions in gliomas of different WHO grades. B, Incidence of ZM fusions in histological subgroups of glioma (A: astrocytoma, grade II; OA: oligoastrocytomas, grade II; O: oligodendroglioma, grade II; AA: anaplastic astrocytoma, grade III; AOA: anaplastic oligoastrocytomas, grade III; AO: anaplastic oligodendroglioma, grade III). C, Proportion of the four ZM fusion variants. The percentages show the relative frequencies of each ZM fusion variant in all ZM fusions identified in this study. D, Kaplan‐Meier curve of overall survival (OS) for patients with sGBM with (N = 21) or without (N = 53) ZM fusion. E, Kaplan‐Meier curve of progression‐free survival (PFS) for patients with sGBM with (N = 16) or without (N = 46) ZM fusion.

FIGURE 4

The correlations of ZM fusion incidence with the 2016 WHO classification of glioma. A, The landscape of ZM fusions and the critical histology and molecular features counted in the definition of 2016 WHO classification of glioma. B, Distribution of ZM fusions in tumors with 2016 WHO classification of glioma. (the specimens do not fit into any narrowly defined classifications which were labeled as “NOS” were not counted). NOS: not otherwise specified.

FIGURE 5

The clinical features of sGBM patients harboring ZM fusion. A, The incidence of ZM fusions in younger (Age <40) or older (Age ≥40) patients. B, The incidence of ZM fusions in patients with sGBM progressed from LGG of WHO grade II or III. C, The occurrence rates of seizure in patients with sGBM harboring ZM fusions or not before surgical resection. D, The occurrence rates of seizure in patients with sGBM harboring ZM fusions or not after surgical resection.

FIGURE 6

Coiled‐coil structures in ZM contribute to ligand‐independent MET activation. A, Diagram that MET is modified by PTPRZ1 fragment adding to SEMA domain. B, The 3D protein structure predicated using QUARK algorithm. The predicated structure of the first 200 amino acids added to MET in ZM variant 4 (exon8 of PTPRZ1 binding to exon2 of MET) is shown in yellow, and the PTPRZ1 segments in ZM variant 1, 2, and 3 are separately highlighted in blue. C, ZM fusion leads to MET hyperactivation in a ligand‐independent manner. Following 12 h of serum starvation and HGF blocking with 6 μg/ml of HGF antibody, MET hyperactivation caused by adenoviral vector‐mediated transient expression of ZM fusion (variant 1 or 2) in U87 MG cells was not impaired. VE: vector control. D, Immunoblottings show strong phosphorylation of MET and its down‐stream signaling in ZM fusion‐positive glioma compared with normal brain tissue (NBT) and ZM‐free glioma. CGGA_P24, CGGA_1685, and CGGA_P5 were diagnosed as ZM fusion positive via the detection method with 50 amplification cycles (indicated by asterisk). HMU: ID for patients from Harbin Medical University. E, The gray intensity of the immunoblotting bands in (D). *p < 0.05, **p < 0.01, ns: no statistically significant.