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Internalin B–mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. Here, we propose a method based on hidden Markov modeling and explainable artificial intelligence that machine-learns the key differences in MET mobility between internalin B–treated and –untreated cells from single-particle tracking data. Our method assigns receptor mobility to three diffusion modes (immobile, slow, and fast). It discriminates between internalin B–treated and –untreated cells with a balanced accuracy of >99% and identifies three parameters that are most affected by internalin B treatment: a decrease in the mobility of slow molecules (1) and a depopulation of the fast mode (2) caused by an increased transition of fast molecules to the slow mode (3). Our approach is based entirely on free software and is readily applicable to the analysis of other membrane receptors.
Despite a high clinical need for the treatment of colorectal carcinoma (CRC) as the second leading cause of cancer-related deaths, targeted therapies are still limited. The multifunctional enzyme Transglutaminase 2 (TGM2), which harbors transamidation and GTPase activity, has been implicated in the development and progression of different types of human cancers. However, the mechanism and role of TGM2 in colorectal cancer are poorly understood. Here, we present TGM2 as a promising drug target.
In primary patient material of CRC patients, we detected an increased expression and enzymatic activity of TGM2 in colon cancer tissue in comparison to matched normal colon mucosa cells. The genetic ablation of TGM2 in CRC cell lines using shRNAs or CRISPR/Cas9 inhibited cell expansion and tumorsphere formation. In vivo, tumor initiation and growth were reduced upon genetic knockdown of TGM2 in xenotransplantations. TGM2 ablation led to the induction of Caspase-3-driven apoptosis in CRC cells. Functional rescue experiments with TGM2 variants revealed that the transamidation activity is critical for the pro-survival function of TGM2. Transcriptomic and protein–protein interaction analyses applying various methods including super-resolution and time-lapse microscopy showed that TGM2 directly binds to the tumor suppressor p53, leading to its inactivation and escape of apoptosis induction.
We demonstrate here that TGM2 is an essential survival factor in CRC, highlighting the therapeutic potential of TGM2 inhibitors in CRC patients with high TGM2 expression. The inactivation of p53 by TGM2 binding indicates a general anti-apoptotic function, which may be relevant in cancers beyond CRC.