Focal adhesion kinase splicing and protein activation in papillary thyroid carcinoma progression

Network medicine approaches for identification of novel prognostic systems biomarkers and drug candidates for papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is one of the most common endocrine carcinomas worldwide and the aetiology of this cancer is still not well understood. Therefore, it remains important to understand the disease mechanism and find prognostic biomarkers and/or drug candidates for PTC. Compared with approaches based on single-gene assessment, network medicine analysis offers great promise to address this need. Accordingly, in the present study, we performed differential co-expressed network analysis using five transcriptome datasets in patients with PTC and healthy controls. Following meta-analysis of the transcriptome datasets, we uncovered common differentially expressed genes (DEGs) for PTC and, using these genes as proxies, found a highly clustered differentially expressed co-expressed module: a 'PTC-module'. Using independent data, we demonstrated the high prognostic capacity of the PTC-module and designated this module as a prognostic systems biomarker. In addition, using the nodes of the PTC-module, we performed drug repurposing and text mining analyzes to identify novel drug candidates for the disease. We performed molecular docking simulations, and identified: 4-demethoxydaunorubicin hydrochloride, AS605240, BRD-A60245366, ER 27319 maleate, sinensetin, and TWS119 as novel drug candidates whose efficacy was also confirmed by in silico analyzes. Consequently, we have highlighted here the need for differential co-expression analysis to gain a systems-level understanding of a complex disease, and we provide candidate prognostic systems biomarker and novel drugs for PTC.

High frequency of alternative splicing variants of the oncogene Focal Adhesion Kinase in neuroendocrine tumors of the pancreas and breast

The characteristic genetic abnormality of neuroendocrine neoplasms (NENs), a heterogeneous group of tumors found in various organs, remains to be identified. Here, based on the analysis of the splicing variants of an oncogene Focal Adhesion Kinase (FAK) in The Cancer Genome Atlas datasets that contain 9193 patients of 33 cancer subtypes, we found that Box 6/Box 7-containing FAK variants (FAK6/7) were observed in 7 (87.5%) of 8 pancreatic neuroendocrine carcinomas and 20 (11.76%) of 170 pancreatic ductal adenocarcinomas (PDACs). We tested FAK variants in 157 tumor samples collected from Chinese patients with pancreatic tumors, and found that FAK6/7 was positive in 34 (75.6%) of 45 pancreatic NENs, 19 (47.5%) of 40 pancreatic solid pseudopapillary neoplasms, and 2 (2.9%) of 69 PDACs. We further tested FAK splicing variants in breast neuroendocrine carcinoma (BrNECs), and found that FAK6/7 was positive in 14 (93.3%) of 15 BrNECs but 0 in 23 non-NEC breast cancers. We explored the underlying mechanisms and found that a splicing factor serine/arginine repetitive matrix protein 4 (SRRM4) was overexpressed in FAK6/7-positive pancreatic tumors and breast tumors, which promoted the formation of FAK6/7 in cells. These results suggested that FAK6/7 could be a biomarker of NENs and represent a potential therapeutic target for these orphan diseases.

Identification of defactinib derivatives targeting focal adhesion kinase using ensemble docking, molecular dynamics simulations and binding free energy calculations

Focal adhesion kinase (FAK) belongs to the nonreceptor tyrosine kinases, which selectively phosphorylate tyrosine residues on substrate proteins. FAK is associated with bladder, esophageal, gastric, neck, breast, ovarian and lung cancers. Thus, FAK has been considered as a potential target for tumor treatment. Currently, there are six adenosine triphosphate (ATP)-competitive FAK inhibitors tested in clinical trials but no approved inhibitors targeting FAK. Defactinib (VS-6063) is a second-generation FAK inhibitor with an IC50 of 0.6 nM. The binding model of VS-6063 with FAK may provide a reference model for developing new antitumor FAK-targeting drugs. In this study, the VS-6063/FAK binding model was constructed using ensemble docking and molecular dynamics simulations. Furthermore, the molecular mechanics/generalized Born (GB) surface area (MM/GBSA) method was employed to estimate the binding free energy between VS-6063 and FAK. The key residues involved in VS-6063/FAK binding were also determined using per-residue energy decomposition analysis. Based on the binding model, VS-6063 could be separated into seven regions to enhance its binding affinity with FAK. Meanwhile, 60 novel defactinib-based compounds were designed and verified using ensemble docking. Overall, the present study improves our understanding of the binding mechanism of human FAK with VS-6063 and provides new insights into future drug designs targeting FAK.Communicated by Ramaswamy H. Sarma.

Expression of pY397-FAK and Its miR Regulators Drive Dedifferentiation in the Thyroid Neoplasia Spectrum

Thyroid carcinomas are growing malignancies worldwide. They encompass several diagnostic categories with varying degrees of dedifferentiation. Focal adhesion kinase is involved in cellular communication and locomotion. It is regulated on a posttranscriptional level by miR-7, miR-135a, and miR-138 and on a posttranslational level by autophosphorylation at Y397 (pY397-FAK). We related regulators of FAK with histologic dedifferentiation, clinicopathological factors, and differential diagnosis in the thyroid neoplasia spectrum. We classified 82 cases into 5 groups with increasing aggressiveness: healthy tissue, follicular and classical variants of papillary thyroid carcinoma (PTC), dedifferentiated PTC, and anaplastic carcinoma. MiRs were analyzed by RT-qPCR. Protein expression of pY397-FAK was analyzed by immunohistochemistry (separately in the membrane, cytoplasm, and nuclear compartment) and Western blot. All three miRs were upregulated in healthy tissue compared to malignant, while pY397-FAK was downregulated. MiRs and pY397-FAK were not mutually correlated. MiR-135a-5p was decreasing while membranous and cytoplasmic pY397-FAK increased with dedifferentiation. Neither miR correlated with clinicopathological factors. MiR-135a-5p, miR-138-5p, and membranous and cytoplasmic pY397-FAK discriminated the follicular from the classical variant of PTC. Disturbances of FAK regulation on different levels contribute to neoplastic dedifferentiation. pY397-FAK exerts its oncogenic role in the membrane and cytoplasm. Diagnostically, miRs-135a-5p, miR-138-5p, and membranous and cytoplasmic pY397-FAK differentiated between classical and follicular PTC.

Functional and clinical characteristics of focal adhesion kinases in cancer progression

Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase and an adaptor protein that primarily regulates adhesion signaling and cell migration. FAK promotes cell survival in response to stress. Increasing evidence has shown that at the pathological level, FAK is highly expressed in multiple tumors in several systems (including lung, liver, gastric, and colorectal cancers) and correlates with tumor aggressiveness and patient prognosis. At the molecular level, FAK promotes tumor progression mainly by altering survival signals, invasive capacity, epithelial-mesenchymal transition, the tumor microenvironment, the Warburg effect, and stemness of tumor cells. Many effective drugs have been developed based on the comprehensive role of FAK in tumor cells. In addition, its potential as a tumor marker cannot be ignored. Here, we discuss the pathological and pre-clinical evidence of the role of FAK in cancer development; we hope that these findings will assist in FAK-based clinical studies.

Molecular Docking, Molecular Dynamics Simulations, and Free Energy Calculation Insights into the Binding Mechanism between VS-4718 and Focal Adhesion Kinase

Focal adhesion kinase (FAK) is a 125 kDa nonreceptor tyrosine kinase that plays an important role in many carcinomas. Thus, the targeting of FAK by small molecules is considered to be promising for cancer therapy. Some FAK inhibitors have been reported as potential anticancer drugs and have entered into clinical development; for example, VS-4718 is currently undergoing clinical trials. However, the lack of crystal structural data for the binding of VS-4718 with FAK has hindered the optimization of this anticancer agent. In this work, the VS-4718/FAK interaction model was obtained by molecular docking and molecular dynamics simulations. The binding free energies of VS-4718/FAK were also calculated using the molecular mechanics generalized Born surface area method. It was found that the aminopyrimidine group formed hydrogen bonds with the C502 residue of the hinge loop, while the D564 residue of the T-loop interacted with the amide group. In addition, I428, A452, V484, M499, G505, and L553 residues formed hydrophobic interactions with VS-4718. The obtained results therefore provide an improved understanding of the interaction between human FAK and VS-4718. Based on the obtained binding mechanism, 47 novel compounds were designed to target the adenosine 5'-triphosphate-binding pocket of human FAK, and ensemble docking was performed to assess the effects of these modifications on the inhibitor binding affinity. This work is also expected to provide additional insights into potential future target design strategies based on VS-4718.