Authors:
Laszlo David Menyhert Independent Researcher, Hungary

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Miguel Tejeda Independent Researcher, Hungary

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Abstract

In silico, we modelled the possible docking conformation of human WNT16B and the human ERBB2 TMD homodimer, resulting in a mutant complex. The ribbon structure and the C-terminal, N-terminal, and GG4-like motif structures are similar in HER2 TMD and HER TMD: we modelled the possible docking conformation of WNT16B to the HER1 TMD (ErbB), which also resulted in a mutant complex. If a strong relationship exists between TMD mutations that improve the active dimer interface or stabilizing an activated conformation and the potency with which HER2 (and possibly also HER), then the dimerization part of the TMD seems to be the ideal reagent target. The agent we tested –4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) – can connect directly into human ERBB2 TMD (HER2), to the ErbB TMD (HER1) dimer bilayer motif, and human WNT16B, ERBB2 TMD (HER2) and WNT16B ErbB TMD (HER1) mutant complex residues. We tested the agent ligand in vitro and in vivo in several tumor models, which highlighted that targeting the EGFR's TMD with an agent not only reduced treatment-induced metastasis but also radically decreased tumor growth. Because of the analogous structure of HER2 TMD and HER TMD, this dimerization motif targeting can also be successful in HER and HER2 EGFR signalling. In vitro, we reached an antiproliferation rate of 80%–94% in different tumor models, while in vivo we reached a rate of 35%–61% tumor suppression in different tumor models. The metastasis inhibition effect of the compound was between 82% and 87% in different tumor models. The referenced experiments took place in 2015 in Hungary.

Abstract

In silico, we modelled the possible docking conformation of human WNT16B and the human ERBB2 TMD homodimer, resulting in a mutant complex. The ribbon structure and the C-terminal, N-terminal, and GG4-like motif structures are similar in HER2 TMD and HER TMD: we modelled the possible docking conformation of WNT16B to the HER1 TMD (ErbB), which also resulted in a mutant complex. If a strong relationship exists between TMD mutations that improve the active dimer interface or stabilizing an activated conformation and the potency with which HER2 (and possibly also HER), then the dimerization part of the TMD seems to be the ideal reagent target. The agent we tested –4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) – can connect directly into human ERBB2 TMD (HER2), to the ErbB TMD (HER1) dimer bilayer motif, and human WNT16B, ERBB2 TMD (HER2) and WNT16B ErbB TMD (HER1) mutant complex residues. We tested the agent ligand in vitro and in vivo in several tumor models, which highlighted that targeting the EGFR's TMD with an agent not only reduced treatment-induced metastasis but also radically decreased tumor growth. Because of the analogous structure of HER2 TMD and HER TMD, this dimerization motif targeting can also be successful in HER and HER2 EGFR signalling. In vitro, we reached an antiproliferation rate of 80%–94% in different tumor models, while in vivo we reached a rate of 35%–61% tumor suppression in different tumor models. The metastasis inhibition effect of the compound was between 82% and 87% in different tumor models. The referenced experiments took place in 2015 in Hungary.

Introduction

A common feature of molecular modelling techniques is the atomistic-level description of molecular systems. This may include treating atoms as the smallest individual unit (the molecular mechanics approach) or explicitly modelling electrons of each atom (the quantum chemistry approach). Molecular modelling and synthesis encompass all the theoretical methods and computational techniques used to model or mimic the behaviour of molecules. These techniques are used in the fields of computational chemistry, drug design, computational biology, and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies. During the past decade, biodegradable polymers or oligopeptides recognised by cell-surface receptors have been shown to increase drug specificity, lowering systemic drug toxicity in contrast to small-size, fast-acting drugs [1]. The simplest calculations can be performed by hand, although computers are inevitably required for the molecular modelling of any reasonably sized system. Molecular modelling and the related computational techniques (often referred to as in silico approaches) are an integral aspect of the drug discovery and development workflow. Modelling approaches complement the development pipeline at a number of stages, but perhaps most significantly in the early phases of lead discovery and hit identification. The main objective is generally to discard those molecules less likely to be successful, hence focusing experimental work on the more valuable compounds. For this reason, in silico approaches are thought to have a highly positive economic impact on the drug discovery process. Molecular modelling projects in this area generally involve the use of molecular modelling software to design inhibitor binding models. These models generate hit compounds, which are generally tested in relevant bioassays. Chemical modifications will then usually be undertaken, with the necessary organic chemistry, biophysical measurements, and molecular biology.

The complexity of cancer and the vast amount of experimental data available have necessitated the use of computer-aided approaches. Biomolecular modelling techniques are becoming easier to use, while hardware and software are becoming more effective and cheaper. However, dialogue between theoretical and experimental scientists involved in cancer research from a molecular approach is still rare, in contrast to other fields, such as amyloid-related diseases, where molecular modelling studies are widely acknowledged.

The development of cancer cells is a process: when the normal regulation of cell division is disrupted, long series of typical mutations lead to the development of cancer. The aging of cells is a biological mechanism regulated by the p53/p21 (WAF1) stimulus pathway, and some factors are overexpressed in the fibroblasts of cells that undergo repeated phases of aging. Both p53 and the growth factor protein require the development of replicative cellular senescence, while the growth factor protein also regulates the activation of the phosphoinositide 3-kinase (PI3K)/AKT pathway activation, which is linked via the epidermal growth factor receptor [2, 3]. In a relevant number of cases, cancer cells become resistant to anticancer agents or toxins during chemotherapy. The WNT16B protein has the immoderate information of generating strong metastasis [4–6]. The relevant publications observe that the level of this growth factor protein may be up to thirty times higher in the body of a patient undergoing chemotherapy than in a healthy individual [7–10].

Deregulated HER2 is the target of many approved cancer drugs, as structural modelling and analysis have shown that TMD/JMD mutations function by improving the active dimer interface or stabilizing an activating conformation [11]. During signal transduction across the plasma membrane, ErbB receptors are involved in lateral homodimerization and heterodimerization with the proper assembly of their extracellular single-span transmembrane (TM) and cytoplasmic domains [12]. In humans, more than 70% of ErbB2-positive sporadic breast cancers harbour p53 mutations, which correlate with a poor prognosis. Moreover, the extremely high incidence of ErbB2-positive breast cancer in women with p53 germline mutations (Li-Fraumeni Syndrome) suggests the key role of mutant p53 specifically in ErbB2-mediated mammary tumorigenesis [13].

One possible docking protein at the HER2 TMD homodimer receptor site is WNT16. The expression of this protein in nearby normal cells is responsible for the development of chemotherapy resistance: the body of a chemotherapy patient may contain thirty times more WNT16B than normal. The protein is glycosylated and, when associated with the cell surface or transmembrane matrix, recognises cell surface receptors. The WNT16B protein contains two transcript variants diverging at the 5′ termini. These two variants are proposed to be the products of separate promoters and not to be splice variants from a single promoter. They are differentially expressed in normal tissues, one of which (variant 2) is expressed at significant levels only in the pancreas, whereas another one (variant 1) is expressed more ubiquitously, with the highest levels in adult kidney, placenta, brain, heart, and spleen. The expression of WNT16B is regulated by the nuclear factor of κ light polypeptide gene enhancer in B cells 1 (NF-κB) after DNA damage, as can occur in normal cells during radiation or chemotherapy. Subsequently, WNT16B signals in a paracrine manner to activate Wnt expression in tumor cells.

Materials and methods

No homology model of the WNT16B isoform is available in public databases. To create a 3D homology model of human WNT16B, we used Swissmodel [14–17]. As a template homology model, we used Helobdella sp. WNT16B to transform the known sequence of human WNT16B into a model [18, 19]. Without the homology model, it is hard to create docking scripts, since the sequence does not contain the conformation information essential in the case of in silico docking methods in which the programming language of the docking procedure is capable of performing actions on large text-type datasets (e.g., C, Perl, Python etc.). The analogy between the human and the Helobdella sp. WNT16B sequence is above 90%, thus statistically the potential differences between the two homology models is below 10%. This is sufficiently low for the Helobdella sp. WNT16B model to be used for prediction, and to make the resulting human WNT16B model usable. Furthermore, the shape of the human WNT16B homology model is very similar to the human WNT3 proto-oncogene protein, which may result in the binding of human WNT16B, causing malfunction. The model was built using ProMod3 Version 1.1.0. In the event of the failure of loop modelling with ProMod3, an alternative model was built with ProMod-II, and the best result was found with BLAST [16, 20]. The model is a monomer polypeptide, with an added CYS ligand. The modelling was done in 2015 and in 2018, both effected the same result.

The docking methodology was done by Hex 8.0 spherical polar Fourier protein docking algorithm, the final sampling was calibrated to N = 30, which effected the best result [2122]. All the ligand interactions, bond- monitoring, and imaging were done in Discovery Studio 4.3.1 [23]. Hex was written mostly in C, but also uses some C++ for the GUI, the Discovery Studio uses Perl scripts. The results of the binding interactions were inserted into XML tables, which can easily be used as database tables in SQL Server 2012 with the help of SQL Server Management Studio 2012.

In vitro, the tumor cell cultures were obtained from the American Type Culture Collection and cultured with RPMI medium 1640 or Leibovitz's L-15 medium supplemented with 10% foetal calf serum. The cells were kept at 37 °C in a humidified atmosphere of 5% CO₂ and 95% air.

With respect to the statistical analyses, all the data refer to three independent experiments. Student's (two-sided) t-test was used to rate statistical significance (*, P < 0.05), while the IC50 values were calculated from normalised dose-response diagrams with the help of GraphPad Prism 5 (GraphPad Software). All dilations from the additives were defined by the combination index–isobologram equation [24].

In vivo, the tumors were implanted s.c. or were transplanted to the appropriate organs in the case of human tumors. In the case of orthotopic tumors, the tumor models were produced by transplanting cancer cells into an anatomically appropriate location in the host organism [25]. Approximately 350,000 cells were cultured in 2 ml of culture medium in a well (six-well plates were used, Greiner, Nürtingen, Germany) and incubated for 24 h with different doses of AKOS004122375 in the absence of foetal calf serum. After trypsinization and dispersion, the cells were dyed with trypan blue and counted in a haemocytometer. The therapeutic efficacy of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) in different long-term administration routes (once or twice a day for two weeks), using traditional injections (i.p., s.c.) versus infusion treatment (using an implantable Alzet-type minipump), will be investigated in the future. Histochemical analysis of the different tumors from treated and control-group animals was carried out.

During our toxicology studies, the effects of different doses of AKOS004122375 on survival and changes of body weight were tested for two weeks. The weight of different organs (heart, kidney, spleen, lung, liver, thymus, and uterus) was measured after 1- and 18-day treatments. Haematological studies, bone marrow analysis, and cytology studies of the different organs were also conducted.

A clonogenic assay is a method for determining the survival and colony-forming ability of adherent cell cultures treated with 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375). In this case, 1,000 cancer or normal cells were seeded at 70% confluence in six-well plates in the required with 10% FBS. The cells were treated with the selected agents at IC90 concentration. After three days of incubation, the medium was changed to a drug-free one and the surviving cells were cultured for 14–20 days. The cells were stained and fixed, then the number of colonies, the number of cells in each colony, and the morphology of the cells were determined by confocal microscopy. Each experiment was performed two times: the results were accepted below 10% standard deviation. The results were presented in terms of surviving fraction percentage (SF), where SF = No. of colonies after treatment/No. of colonies in untreated control x 100. The SF values of the tested agents on each cell line were complemented by the size of the colonies and the morphology of the cells. The tumor selectivity of the tested agent can be determined with the help of clonogenic assay on non-tumor (normal) cell lines.

The cytotoxicity of the compound AKOS004122375 was tested using reactions developed by our group, consisting of the following strategies: the end-point measurement, and the real-time evaluation of cell density. In the first approach, we used electronic pulse area analysis, which has an advanced ability to detect cell numbers and perform cell size analysis, while it also provides the possibility to analyse viability changes with the aid of altered permeability and electric moieties of the surface membrane. Long-term (24- to 72-h) types of impedance-based analysis are not only available for the characterisation of chemotaxis and chemokinesis but are also a dedicated tool for following changes in cell density in the test chambers. In this case, we were even able to distinguish fluctuations in cell numbers and characterise the cell cycle with a high level of confidence.

The bodyweight of the animals was measured and the tumor dimensions were measured using a microcaliper every second or third day. Tumor volume was calculated using the following formula: V= (×/6) x Lx D2 (V = tumor volume, L: longest diameter, D: diameter perpendicular to L). Survival times compared to that of the controls were recorded. Tumor volume measurements were continued until the first death in the control group. Mean values and standard deviations were calculated. The experimental data were subjected to computerised statistical analysis of variance using the Student–Newman–Keuls test; statistical significance was accepted at the level of P > 0.05.

Apoptosis consists of a cascade of events leading to the programmed dismantling of critical cell survival components and pathways. Apoptosis events were studied using fluorochrome conjugates of annexin V to monitor changes in cell membrane phospholipid asymmetry, providing a convenient tool for the detection of apoptosis cells. A distinctive feature of the early stages of apoptosis is the activation of cascade enzymes. These enzymes participate in a series of reactions that are triggered in response to pro-apoptotic signals and that result in the leverage of protein substrates, causing the disassembly of the cell. Caspase enzyme substrates and apoptosis kits can be used in studies of this kind.

The National Institute of Oncology in Budapest, Hungary, has the modern facilities, personnel, and infrastructure necessary to carry out a research project of this kind. The activities and research interests of the Department of Experimental Pharmacology at the National Institute of Oncology are related to the following areas: the breeding of laboratory animals (about 10,000 mice per year, 60% of which are used in preclinical experiments); the maintenance of transplantable mouse and human tumor models (a “tumor bank”); and preclinical examinations (e.g., toxicological, histological, and haematological examinations, and the examination of different side effects) of new antitumor agents and biological modulators. Furthermore, the Department of Pharmacology has the facilities (two modern laboratories and three experiment rooms) and personnel (experienced researchers and support staff) necessary to carry out such experiments. The department has participated in a variety of projects over many years.

Specified pathogen free mice (SPF) breeding of the Department of Experimental Pharmacology, National Institute of Oncology, Budapest, Hungary weighing 22–24 g used for these experiments. The animals were fed with a sterilized standard diet (Biofarm) and had free access to tap water ad libitum. They were kept in macron cages at 23–25 °C (40–50% humidity), a lighting regiment of 12/12 h light/dark. The animals of this project were cared for according to the “Guideing Principles for the Care and Use of Animals” based upon the Helsinki declaration and they were approved by the local ethical committee. In our experiments we used 7-10 mice/group (treatment and control group).

Results and discussion

The human ERBB2 is a transmembrane signaling tyrosine kinase receptor of EGF, which seems a possible target of human WNT16B [26], the ErbB family contains four plasma membrane-bound receptor tyrosine kinases. ERBB2tm dimer structure (HER2 TMD) explains the biochemical and oncogenic properties of the human ERBB2 receptor and provides a basis to control its kinase activity, which is critical in many disease states, proper lateral dimerization of the transmembrane domains of receptor tyrosine kinases is required for biochemical signal transduction across the plasma membrane [27]. Additionally, specific protein-protein and protein-lipid interactions of singlespan HER transmembrane domains (TMDs) are important for proper receptor activation and mechanism(s) that reduce or enhance such interactions (e.g., by means of mutations) and can affect downstream activity independently of KD mutations [28]. Relevant publications have observed a striking relationship between the chemical nature of the TMD mutations and the potency with which they activate HER2 [11]. One such publication uses the HER2 TMD homodimer model (PDB:2JWA) as the HER TMD JM-A homodimer: the transmembrane part of the two pathways may be similar ribbon structures of the HER TMD dimers formed via the alternative C-terminal and N-terminal and GG4-like motifs, just as in the HER2 TMD homodimer [27, 29]. Thus, it is possible that TMD mutations affect both HER and HER2 in the way reviewed in this study [30].

Using expression profiling techniques, it was possible to search for secreted factors that were overexpressed in fibroblasts undergoing replicative senescence [31]. It was found that WNT16B is overexpressed in cells undergoing stress-induced premature senescence and oncogene-induced senescence in both the MRC5 cell line and the in vivo murine model of K-Ras(V12)-induced senescence. This secreted factor seemed a probable docking protein of HER2 TMD [32]. By small interfering RNA experiments, it was observed that both p53 and WNT16B are necessary for the onset of replicative senescence, and that WNT16B expression is required for the full transcriptional activation of p21 (WAF1). Moreover, WNT16B regulates the activation of the phosphoinositide 3-kinase (PI3K)/AKT pathway, thus overall, WNT16B is a new marker of senescence that regulates p53 activity and the PI3K/AKT pathway and is necessary for the onset of replicative senescence [32]. Furthermore, if the HER TMD homodimer has the same structure as the HER2 TMD homodimer, then WNT16B may affect both HER and HER2 [29].

The 3D shape of the homology model of human WNT16B is totally similar to that of human WNT3 proto-oncogene protein, despite the fact that the sequences are not homologous. This similarity between the shapes may cause the binding effects of human WNT16B that result in the malfunction of HER and HER2 TMD.

In silico, after reviewing the intermolecular bonds of the close residues of the HER2 TMD homodimer (PDB:2JWA) and human WNT16B, we found that the A:ARG77, A:GLN79, A:GLN80, A:GLN80, A:ILE82, A:ARG83, A:ARG83, A:LYS84, B:PHE171, B:ILE175, and B:LYS176 parts of the HER2 transmembrane domain are able to bind with conventional hydrogen intermolecular bonds to human WNT16B as H-donors. The A:LYS, A:LEU, A:THR and A:VAL parts of human WNT16B also behave as conventional hydrogen H-donors, which is a striking indication that they are very probably mutating. We also reviewed the carbon–hydrogen and other intermolecular bonds between HER2 TMD and human WNT16B and found that the possible intermolecular bonds between the complexes show very strong binding, docking potential (Fig. 1).

Fig. 1.
Fig. 1.

Possible conformations of human WNT16B docking into the HER2 TMD homodimer (A) and HER TMD homodimer (B) receptor sites

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

In silico, we also reviewed the intermolecular bonds of the close residues of the HER TMD homodimer (PDB: 2M0B) and human WNT16B. We found that the A:ARG, A:LEU, B:ARG, B:ILE, and B:LYS parts of the HER1 transmembrane domain are able to bind to human WNT16B as H-donors with intermolecular conventional hydrogen bonds, and that the A:THR, A:GLU, and A:ASN parts of human WNT16B behave as H-donors in conventional hydrogen bonds. We also reviewed the electrostatic and hydrophobic intermolecular bonds, and the results indicated that they are very probably mutating.

The compound AKOS004122375 (InChIKey: YTNUPDNFKZGGB-UHFFFAOYSA-N, PubChem SID: 108669579) is a form of 4-(furan-2-yl)hepta-1,6-dien-4-ol (alpha,alpha-diallylfuran-2-methanol, PubChem CID: 11206108) (Fig. 2). It has a molecular weight of 178.23 g mol−1 and the compound has one hydrogen bond donor and two hydrogen bond acceptor sites, with five rotatable bonds. The formal charge is 0. The differences between the sub-ligands of the 4-(furan-2-yl)hepta-1,6-dien-4-ol affect only the freely transforming properties of the rotatable bonds. The ERBB2 transmembrane domain (HER2 TMD) has a homodimer and a heterodimer form, it can be inactive or active conformed, in this study we reviewed only the active form of the homodimer. If the HER TMD homodimer has the same structure as the HER2 TMD homodimer, then the same interaction can probably be observed at the dimerization bilayer motif of HER TMD [29, 33].

Fig. 2.
Fig. 2.

The compound 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375)

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

When focusing on the intermolecular bonds of the close residues of AKOS004122375 and the HER2 TMD homodimer (PDB:2JWA), it can be seen that the 4-(furan-2-yl)hepta-1,6-dien-4-ol:O1 atom binds with a conventional hydrogen bond to HER2 TMD A:VAL64. The distance is 3.02086. Furthermore, the compound also binds with three carbon–hydrogen and two Pi-alkyl bonds to HER2 TMD. When reviewing the intermolecular bonds of the close residues between the agent compound AKOS004122375 and human WNT16B, the ligand binds with four Pi-alkyl bonds to the A:LEU and A:ALA parts of HER TMD. The distance is between 4.1 and 5.1 (Fig. 3).

Fig. 3.
Fig. 3.

Possible (A) intermolecular bonds of the close residues of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) and HER2 TMD homodimer (B) bonds of AKOS004122375 is docking into the HER2 TMD homodimer and human WNT16B mutant complex (C) bonds of AKOS004122375 is docking into the HER2 TMD homodimer

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

In silico, we tested the possible results of AKOS004122375 ligand docking into the HER2 TMD homodimer (PDB:2JWA) and human WNT16B mutant complex. Our results show that the ligand binds in the same way only when docked into the HER2 TMD. Importantly, HER2-inhibiting antibodies and small molecules can block the activity of the HER2 transmembrane domain and juxtamembrane domain mutants Our agent ligand acted exactly like an inhibitor [11]. The exact mechanism will be investigated later, but it is possible that the agent compound alters the partial and surface charge of the helix (especially in the dimerization-bilayer motif), and that causes probable malfunction in bad signaling mutations pathways.

The reagent compound (AKOS004122375) behaves as an H-acceptor when connecting to the human HER2 TMD homodimer (PDB:2JWA) A:VAL64 with a conventional hydrogen bond (distance: 3.02086; angle xda: 112.19; angle day: 125.117). The A:GLY60, B:GLY160, and B:VAL:164 parts of the HER2 TMD behave as an H-donor when binding to 4-(furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) with carbon–hydrogen bonds (three bonds with distances between 1.87114 and 3.043). Furthermore, there are two Pi-alkyl bonds between the compound and the A:VAL64 and A:LEU67 parts of the HER2 TMD, with a distance of over 3.2. The compound AKOS004122375 binds with Pi-alkyl intermolecular bonds to the A:ALA661, B:LEU657, and B:LEU658 parts of HER TMD, with a distance of between 4.1 and 5.1 (Fig. 4).

Fig. 4.
Fig. 4.

Possible docking conformations of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) into the HER2 TMD homodimer and human WNT16B mutant complex (A) and into the HER TMD homodimer and human WNT16B mutant complex (B)

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

In general, we can assert that – according to our in silico experiments – human WNT16B is very likely to dock into the HER and HER2 TMD homodimer, and this could have an impact on biochemical signal transduction across the plasma membrane. This may affect the p51, p53, and PI3K pathways and lead to the confusion of normal cell functions, possibly causing repeated phases of cell aging [2, 3]. Our theory – that a simple ligand can change the crucial binding structure of the secreted growth factor and the tyrosine kinase receptor through a strong connection into the active form of the HER and HER2 TMD dimerization motif – is demonstrated in our in vitro and in vivo experiments. We suggest that ErbB ErbB2-mediated mutant p53 has a key role in treatment-induced metastasis and also in tumor growth.

In vitro, we tested the antiproliferative efficacy of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) on different human tumor cells: in vitro, the agent inhibited the proliferation of breast carcinoma cells MCF-7 and of MDA-MD-231. Through MTT assays, the inhibitory concentration 50 (IC50) was determined at 72 h of exposure. In the case of MCF-7 cells, the IC50 was 240 ± 12.6 nM; in the case of MDA-MD-231 cells, the IC50 was 180 ± 20.6 nM; in the case of HT168-M1 cells, the IC50 was 210 + 10.0; and in the case of B16 cells, the IC50 was 175 + 19.2 nM. The antiproliferative effect of the new agent was observed in both cell lines at an exposure of 24 h. In 1.2 concentration, the antiproliferation percentage in B16 cells was 80%, in MCF-7 cells 87%, in MDA-MB 231 cells 94%, and in HT168-M1 cells 89% (Fig. 5).

Fig. 5.
Fig. 5.

In vitro results for the antiproliferation effect of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) on (A) B16 and HT168-M1 tumor cells, and (B) MCF-7 and MDA-MB 231 cells

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

The toxic effect of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) was studied in healthy mice in relation to their weight and in different organs (lung, heart, liver, spleen, kidneys), with the administration of three different doses. The new antitumor agent was not lethal for the experimental animals: it only slightly decreased the weight of the mice. The results demonstrated that the molecule was not toxic. The cytostatic and antiproliferative effect of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) was also determined by MTT assay (3-(4,5- dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide), which is based on the conversion of MTT to aformazan derivative only by the living cells [34].

The in vivo antitumor inhibitory effect of 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) was investigated in M1 human leukaemia, M1 human melanoma, B16 F10 human melanoma, S-180 sarcoma, colon-26 adenocarcinoma, MXT mammary carcinoma, and B-16 melanoma tumor models. We obtained the best results with the smallest dose. Treatment with AKOS004122375 4-(Furan-2-yl)hepta-1,6-dien-4-ol was carried out at three different doses (80 mg kg−1, 40 mg kg−1, and 10 mg kg−1) via injections, administered twice a day for two weeks [35]. It caused an average 50%–70% decrease in tumor volume in mice. The best results were obtained at a dosage of 10 mg kg−1 (the smallest dosage). We also monitored the metastasis effects, which were low.

Figures 6 and 7 present the in vivo antitumor activity of AKOS004122375 in three doses (10 mg kg−1, 20 mg kg−1, and 40 mg kg−1), administered via s.c. injection and a 14 xqd treatment schedule. Treatment with the agent started when the tumor had developed and become measurable. The mice were randomised before the beginning of the treatments. The therapeutic effect of the agent was compared and expressed in terms of tumor growth inhibition and lifespan. Figure 6A demonstrates the effect of AKOS004122375 on the colon-26 adenocarcinoma tumor model. Based on tumor growth curves and mean tumor volumes, a significant (35%) growth inhibitory efficacy against tumor development was observed at a dose of 10 mg kg−1, s.c. When AKOS004122375 was administered at 20 mg kg−1 and 40 mg kg−1, a tumor inhibitory effect of around 21% was achieved. In our experiments, we studied the antitumor effect of the compound on an M1 human leukaemia tumor model using three doses. Figure 6B shows that the different doses (10 mg kg−1, 20 mg kg−1, and 40 mg kg−1) resulted in a tumor inhibitory efficacy of 47%, 34%, and 14% tumor inhibitory effect. In Fig. 6C shows the therapeutic efficacy of the compound on an MXT mammary carcinoma tumor model. When AKOS004122375 was administered at a dose of 10 mg kg−1, s.c., the agent induced a significant (42%) tumor growth inhibitory effect against MXT mammary carcinoma tumor development. Figure 6D shows the inhibitory efficacy of the ligand on an S-180 sarcoma tumor model following doses of 10 mg kg−1, 20 mg kg−1, and 40 mg kg−1. The tumor inhibitory activity of the agent at the end of the 14-day treatment period was 47% (10 mg kg−1), 43% (20 mg kg−1), and 30% (40 mg kg−1).

Fig. 6.
Fig. 6.

In vivo results for 4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) tumor suppressor effects on (A) a colon-26 adenocarcinoma tumor model; (B) an M1 human leukaemia tumor model; (C) an MXT mammary carcinoma tumor model; and (D) an S-180 sarcoma tumor model. The solid line indicates the control group

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

Fig. 7.
Fig. 7.

In vivo results for 4-(Furan-2-yl)hepta-1,6-dien-ol (AKOS004122375) tumor suppressor effects on a B16F10 melanoma tumor model. The solid line indicates the control group

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

The antitumor effect of AKOS004122375 on a B16F10 melanoma tumor model was investigated at three doses: 10 mg kg−1, 20 mg kg−1, and 40 mg kg−1, with s.c. treatments. Based on the tumor growth curves, a significant antitumor activity of the agent was observed. The antitumor efficacy of AKOS004122375 following s.c. treatments for two weeks was 61% (at 10 mg kg−1), 31% (at 20 mg kg−1), and 18% (at 40 mg kg−1) (Fig. 7).

The metastasis inhibition effect of the compound was tested on liver metastasis formation in the case of the M1 human melanoma tumor (mean ± SEM), and on lung metastasis formation in the case of the B16F10 melanoma tumor (mean ± SEM) with the administration of three different doses (10 mg kg−1, 20 mg kg−1, and 40 mg kg−1), using i.p. injection and an 18 xpd treatment schedule. The results demonstrate that all three doses significantly inhibit the number of metastases in comparison with the untreated control group. In the case of the M1 melanoma tumor, 82% (10 mg kg−1), 63% (20 mg kg−1), and 44% (40 mg kg−1) inhibition was observed. In the case of the B16F10 tumor, we achieved 87% (10 mg kg−1), 79% (20 mg kg−1), and 72% (40 mg kg−1) lung metastases inhibition (Fig. 8).

Fig. 8.
Fig. 8.

In vivo results for 4-(Furan-2-yl)hepta-1,6-dien-ol (AKOS004122375) metastasis inhibition efficacy on (A) liver metastasis formation in the case of the M1 human melanoma tumor (mean ± SEM) and (B) lung metastasis formation in the case of the B16F10 melanoma tumor (mean ± SEM)

Citation: Developments in Health Sciences 7, 2; 10.1556/2066.2024.00066

Authors' contributions

Conceptualization: Miguel Tejeda, Laszlo David Menyhert.

Methodology: Laszlo David Menyhert, Miguel Tejeda.

Formal Analysis: Laszlo David Menyhert.

Investigation: Laszlo David Menyhert.

Writing – Original Draft Preparation: Laszlo David Menyhert.

Writing – Review & Editing: Miguel Tejeda, Laszlo David Menyhert.

Conflict of interest

The authors declare that they have no conflicts of interest.

The authors have no financial or non-financial interests in the vendors of the referenced compounds or the owners of the computational programs.

Acknowledgements

Our research was carried out with support from the National Institute of Oncology, Hungary.

References

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    Johnson LM, Price DK, Figg WD. Treatment-induced secretion of WNT16B promotes tumor growth and acquired resistance to chemotherapy: implications for potential use of inhibitors in cancer treatment. Cancer Biol Ther 2013;14:901. https://doi.org/10.4161/cbt.22636.

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    Mineev KS, Bocharov EV, Pustovalova YE, Bocharova OV, Chupin VV, Arseniev AS. Spatial structure of the transmembrane domain heterodimer of ErbB1 and ErbB2 receptor tyrosine kinases. J Mol Biol 2010;400:23143. https://doi.org/10.1016/j.jmb.2010.05.016.

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    Yallowitz AR, Li D, Lobko A, Mott D, Nemajerova A, Marchenko N. Mutant p53 amplifies epidermal growth factor receptor family signaling to promote mammary tumorigenesis. Mol Cancer Res 2015;13:74354. https://doi.org/10.1158/1541-7786.MCR-14-0360.

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    Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 2011;27:34350. https://doi.org/10.1093/bioinformatics/btq662.

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    Bertoni M, Kiefer F, Biasini M, Bordoli L, Schwede T. Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology. Sci Rep 2017;7:10480. https://doi.org/10.1038/s41598-017-09654-8.

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    Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis 2009;30:S16273. https://doi.org/10.1002/elps.200900140.

    • Search Google Scholar
    • Export Citation
  • 17.

    Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 2018;46:W296W303. https://doi.org/10.1093/nar/gky427.

    • Search Google Scholar
    • Export Citation
  • 18.

    Cho SJ, Vallès Y, Giani VC Jr, Seaver EC, Weisblat DA. Evolutionary dynamics of the wnt gene family: a lophotrochozoan perspective. Mol Biol Evol 2010;27:164558. https://doi.org/10.1093/molbev/msq052.

    • Search Google Scholar
    • Export Citation
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    McWhirter JR, Neuteboom ST, Wancewicz EV, Monia BP, Downing JR, Murre C. Oncogenic homeodomain transcription factor E2A-Pbx1 activates a novel WNT gene in pre-B acute lymphoblastoid leukemia. Proc Natl Acad Sci U S A 1999;96:114649. https://doi.org/10.1073/pnas.96.20.11464.

    • Search Google Scholar
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    Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics 2009;10:421. https://doi.org/10.1186/1471-2105-10-421.

    • Search Google Scholar
    • Export Citation
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    Ritchie DW. High order analytic translation matrix elements for real space six-dimensional, polar fourier correlations. J Appl Cryst 2005;38:80818. doi: S002188980502474X.

    • Search Google Scholar
    • Export Citation
  • 22.

    Ritchie DW, Kemp GJL. Fast computation, rotation, and comparison of low resolution spherical harmonic molecular surfaces. J Comp Chem 1999;20:38395. https://doi.org/10.1002/(SICI)1096-987X(199903)20:4<383::AID-JCC1>3.0.CO;2-M.

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    Biovia DS. Discovery studio modeling environment. Dassault Syst. Release, San Diego, 4; 2015.

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    Chou TC. Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol Rev 2006;58:62181. https://doi.org/10.1124/pr.58.3.10. Erratum in: Pharmacol Rev. 2007;59:124.

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    Chou LC, Tsai MT, Hsu MH, Wang SH, Way TD, Huang CH, et al. Design, synthesis, and preclinical evaluation of new 5,6- (or 6,7-) disubstituted-2-(fluorophenyl)quinolin-4-one derivatives as potent antitumor agents. J Med Chem 2010;53:804758. https://doi.org/10.1021/jm100780c.

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    Zhang J, Saba NF, Chen GZ, Shin DM. Targeting HER (ERBB) signaling in head and neck cancer: an essential update. Mol Aspects Med 2015;45:7486. https://doi.org/10.1016/j.mam.2015.07.001.

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    Bocharov EV, Lesovoy DM, Pavlov KV, Pustovalova YE, Bocharova OV, Arseniev AS. Alternative packing of EGFR transmembrane domain suggests that protein-lipid interactions underlie signal conduction across membrane. Biochim Biophys Acta 2016;1858:125461. https://doi.org/10.1016/j.bbamem.2016.02.023.

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    Ou SI, Schrock AB, Bocharov EV, Klempner SJ, Haddad CK, Steinecker G, et al. HER2 transmembrane domain (TMD) mutations (V659/G660) that stabilize homo- and heterodimerization are rare oncogenic drivers in lung adenocarcinoma that respond to Afatinib. J Thorac Oncol 2017;12:446457. https://doi.org/10.1016/j.jtho.2016.11.2224.

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    • Search Google Scholar
    • Export Citation
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    Leurs U, Mező G, Orbán E, Öhlschläger P, Marquardt A, Manea M. Design, synthesis, in vitro stability and cytostatic effect of multifunctional anticancer drug-bioconjugates containing GnRH-III as a targeting moiety. Biopolymers 2012;98:110. https://doi.org/10.1002/bip.21640.

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Structured Methods

Reagents and Tools Table

Reagent/ResourceReference or SourceIdentifier or Catalogue Number
Experimental Models

List cell lines, model organism strains, patient samples, isolated cell types etc. Indicate the species where appropriate.
In vitro cell coloniesNational Institute of Oncology, Hungaryobtained from the American Type Culture Collection, cultured with RPM1 medium 1640 or Leibovitz's L-15 medium supplemented with 10% foetal calf serum
Specific-pathogen-free (SPF) miceNational Institute of Oncology, Hungaryweighing 22–24 g
Oligonucleotides and other sequence-based reagents

For long lists of oligos or other sequences please refer to the relevant table(s) or EV table(s)
2JWA

ErbB2 transmembrane segment dimer spatial structure Homo sapiens (human), HER2 TMD homodimer
Bocharov et al., 2008 [33]pdb ID: 2JWA
PubMed: 18178548
pdb file
2M0B homodimeric transmembrane domain of the receptor tyrosine kinase ErbB1 (EGFR, HER1) in micelles, Homo sapiens (human), HER TMD homodimerBocharov et al., 2016 [27]pdb ID: 2M0B
PubMed: 26903218
pdb file
WNT16B Homo sapiens (human) sequenceMcWhirter et al., 1999 [19]UniProtKB - Q9UBV4 (WNT16_HUMAN), sequence
WNT16B Homo sapiens (human) pdbThis studypdb file
WNT16B Homo sapiens (human) docking into the active form of the ErbB2 transmembrane segment dimer spatial structure Homo sapiens (human) 2JWAThis studypdb file
4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) docking into the mutant complex of the ErbB2 transmembrane segment dimer spatial structure Homo sapiens (human) 2JWA and WNT16B Homo sapiens (human)This studypdb file
4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) docking into the ErbB2 transmembrane segment dimer spatial structure Homo sapiens (human) 2JWAThis studypdb file
WNT16B Helobdella sp. SJC-2009 sequenceCho S.J. et al., 2010 [18]UniProtKB - D6N3F7 (D6N3F7_9ANNE), sequence
WNT16B Homo sapiens (human) docking into the homodimeric transmembrane domain of the receptor tyrosine kinase ErbB1 (EGFR, HER1) in micelles, Homo sapiens (human) 2M0BThis studypdb file
4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) docking into the homodimeric transmembrane domain of the receptor tyrosine kinase ErbB1 (EGFR, HER1) in micelles, Homo sapiens (human) 2M0BThis studypdb file
4-(Furan-2-yl)hepta-1,6-dien-4-ol (AKOS004122375) docking into the mutant complex of the homodimeric transmembrane domain of the receptor tyrosine kinase ErbB1 (EGFR, HER1) in micelles, Homo sapiens (human) 2M0B and WNT16B Homo sapiens (human)This studypdb file
Chemicals, Enzymes and other reagents (e.g. drugs, peptides, recombinant proteins, dyes etc.)
4-(Furan-2-yl)hepta-1,6-dien-4-olAKos Consulting & Solutions GmbHAKos Consulting & Solutions ID: AKOS004122375
PubChem CID: 108669579
Software

Include version where applicable
Discovery Studio 4.3.1.BIOVIA DS, 2015 [23]Release 4
Hex 8.0Ritchie DW, 2005; Ritchie DW & Kemp GJL, 1999 [21, 22]Release 8
SQL Server 2012MicrosoftService pack 2 CU7
SSMS 2012MicrosoftVersion 11.0
GraphPad PrismGraphPad SoftwareVersion 5

  • 1.

    Bai KB, Láng O, Orbán E, Szabó R, Köhidai L, Hudecz F, et al. Design, synthesis, and in vitro activity of novel drug delivery systems containing tuftsin derivatives and methotrexate. Bioconjug Chem 2008;19:22609. https://doi.org/10.1021/bc800115w.

    • Search Google Scholar
    • Export Citation
  • 2.

    Shim JS, Liu JO. Recent advances in drug repositioning for the discovery of new anticancer drugs. Int J Biol Sci 2014;10:65463. https://doi.org/10.7150/ijbs.9224.

    • Search Google Scholar
    • Export Citation
  • 3.

    Hait WN. Anticancer drug development: the grand challenges. Nat Rev Drug Discov 2010;9:2534. https://doi.org/10.1038/nrd3144.

  • 4.

    Manea M, Leurs U, Orbán E, Schreier V, Pethoe, L, Schlage P, et al. Anticancer drug delivery systems containing GnRH-III as a targeting moiety. J Pept Sci 2012;18:S46–S46.

    • Search Google Scholar
    • Export Citation
  • 5.

    Schwartsmann G, Ratain MJ, Cragg GM, Wong JE, Saijo N, Parkinson DR, et al. Anticancer drug discovery and development throughout the world. J Clin Oncol 2002;20:47S-59S.

    • Search Google Scholar
    • Export Citation
  • 6.

    Weinstein JN, Buolamwini JK. Molecular targets in cancer drug discovery: cell-based profiling. Curr Pharm Des 2000;6:47383. https://doi.org/10.2174/1381612003400894.

    • Search Google Scholar
    • Export Citation
  • 7.

    Johnson LM, Price DK, Figg WD. Treatment-induced secretion of WNT16B promotes tumor growth and acquired resistance to chemotherapy: implications for potential use of inhibitors in cancer treatment. Cancer Biol Ther 2013;14:901. https://doi.org/10.4161/cbt.22636.

    • Search Google Scholar
    • Export Citation
  • 8.

    Teh MT, Blaydon D, Ghali LR, Briggs V, Edmunds S, Pantazi E, et al. Role for WNT16B in human epidermal keratinocyte proliferation and differentiation. J Cell Sci 2007;120:3309. https://doi.org/10.1242/jcs.03329.

    • Search Google Scholar
    • Export Citation
  • 9.

    Sun Y, Campisi J, Higano C, Beer TM, Porter P, Coleman I, et al. Treatment-induced damage to the tumor microenvironment promotes prostate cancer therapy resistance through WNT16B. Nat Med 2012;18:135968. https://doi.org/10.1038/nm.2890.

    • Search Google Scholar
    • Export Citation
  • 10.

    Sun Y, Zhu D, Chen F, Qian M, Wei H, Chen W, et al. SFRP2 augments WNT16B signaling to promote therapeutic resistance in the damaged tumor microenvironment. Oncogene 2016;35:432134. https://doi.org/10.1038/onc.2015.494.

    • Search Google Scholar
    • Export Citation
  • 11.

    Pahuja KB, Nguyen TT, Jaiswal BS, Prabhash K, Thaker TM, Senger K, et al. Actionable activating oncogenic ERBB2/HER2 transmembrane and juxtamembrane domain mutations. Cancer Cell 2018;34:792806.e5. https://doi.org/10.1016/j.ccell.2018.09.010.

    • Search Google Scholar
    • Export Citation
  • 12.

    Mineev KS, Bocharov EV, Pustovalova YE, Bocharova OV, Chupin VV, Arseniev AS. Spatial structure of the transmembrane domain heterodimer of ErbB1 and ErbB2 receptor tyrosine kinases. J Mol Biol 2010;400:23143. https://doi.org/10.1016/j.jmb.2010.05.016.

    • Search Google Scholar
    • Export Citation
  • 13.

    Yallowitz AR, Li D, Lobko A, Mott D, Nemajerova A, Marchenko N. Mutant p53 amplifies epidermal growth factor receptor family signaling to promote mammary tumorigenesis. Mol Cancer Res 2015;13:74354. https://doi.org/10.1158/1541-7786.MCR-14-0360.

    • Search Google Scholar
    • Export Citation
  • 14.

    Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 2011;27:34350. https://doi.org/10.1093/bioinformatics/btq662.

    • Search Google Scholar
    • Export Citation
  • 15.

    Bertoni M, Kiefer F, Biasini M, Bordoli L, Schwede T. Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology. Sci Rep 2017;7:10480. https://doi.org/10.1038/s41598-017-09654-8.

    • Search Google Scholar
    • Export Citation
  • 16.

    Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis 2009;30:S16273. https://doi.org/10.1002/elps.200900140.

    • Search Google Scholar
    • Export Citation
  • 17.

    Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 2018;46:W296W303. https://doi.org/10.1093/nar/gky427.

    • Search Google Scholar
    • Export Citation
  • 18.

    Cho SJ, Vallès Y, Giani VC Jr, Seaver EC, Weisblat DA. Evolutionary dynamics of the wnt gene family: a lophotrochozoan perspective. Mol Biol Evol 2010;27:164558. https://doi.org/10.1093/molbev/msq052.

    • Search Google Scholar
    • Export Citation
  • 19.

    McWhirter JR, Neuteboom ST, Wancewicz EV, Monia BP, Downing JR, Murre C. Oncogenic homeodomain transcription factor E2A-Pbx1 activates a novel WNT gene in pre-B acute lymphoblastoid leukemia. Proc Natl Acad Sci U S A 1999;96:114649. https://doi.org/10.1073/pnas.96.20.11464.

    • Search Google Scholar
    • Export Citation
  • 20.

    Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics 2009;10:421. https://doi.org/10.1186/1471-2105-10-421.

    • Search Google Scholar
    • Export Citation
  • 21.

    Ritchie DW. High order analytic translation matrix elements for real space six-dimensional, polar fourier correlations. J Appl Cryst 2005;38:80818. doi: S002188980502474X.

    • Search Google Scholar
    • Export Citation
  • 22.

    Ritchie DW, Kemp GJL. Fast computation, rotation, and comparison of low resolution spherical harmonic molecular surfaces. J Comp Chem 1999;20:38395. https://doi.org/10.1002/(SICI)1096-987X(199903)20:4<383::AID-JCC1>3.0.CO;2-M.

    • Search Google Scholar
    • Export Citation
  • 23.

    Biovia DS. Discovery studio modeling environment. Dassault Syst. Release, San Diego, 4; 2015.

  • 24.

    Chou TC. Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol Rev 2006;58:62181. https://doi.org/10.1124/pr.58.3.10. Erratum in: Pharmacol Rev. 2007;59:124.

    • Search Google Scholar
    • Export Citation
  • 25.

    Chou LC, Tsai MT, Hsu MH, Wang SH, Way TD, Huang CH, et al. Design, synthesis, and preclinical evaluation of new 5,6- (or 6,7-) disubstituted-2-(fluorophenyl)quinolin-4-one derivatives as potent antitumor agents. J Med Chem 2010;53:804758. https://doi.org/10.1021/jm100780c.

    • Search Google Scholar
    • Export Citation
  • 26.

    Zhang J, Saba NF, Chen GZ, Shin DM. Targeting HER (ERBB) signaling in head and neck cancer: an essential update. Mol Aspects Med 2015;45:7486. https://doi.org/10.1016/j.mam.2015.07.001.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bocharov EV, Lesovoy DM, Pavlov KV, Pustovalova YE, Bocharova OV, Arseniev AS. Alternative packing of EGFR transmembrane domain suggests that protein-lipid interactions underlie signal conduction across membrane. Biochim Biophys Acta 2016;1858:125461. https://doi.org/10.1016/j.bbamem.2016.02.023.

    • Search Google Scholar
    • Export Citation
  • 28.

    Ou SI, Schrock AB, Bocharov EV, Klempner SJ, Haddad CK, Steinecker G, et al. HER2 transmembrane domain (TMD) mutations (V659/G660) that stabilize homo- and heterodimerization are rare oncogenic drivers in lung adenocarcinoma that respond to Afatinib. J Thorac Oncol 2017;12:446457. https://doi.org/10.1016/j.jtho.2016.11.2224.

    • Search Google Scholar
    • Export Citation
  • 29.

    Jura N, Endres NF, Engel K, Deindl S, Das R, Lamers MH, et al. Mechanism for activation of the EGF receptor catalytic domain by the juxtamembrane segment. Cell 2009;137:1293307. https://doi.org/10.1016/j.cell.2009.04.025. Erratum in: Cell. 2009;138:604.

    • Search Google Scholar
    • Export Citation
  • 30.

    Cymer F, Schneider D. Transmembrane helix-helix interactions involved in ErbB receptor signaling. Cell Adh Migr 2010;4:299312. https://doi.org/10.4161/cam.4.2.11191.

    • Search Google Scholar
    • Export Citation
  • 31.

    Smolich BD, McMahon JA, McMahon AP, Papkoff J. Wnt family proteins are secreted and associated with the cell surface. Mol Biol Cell 1993;4:126775. https://doi.org/10.1091/mbc.4.12.1267.

    • Search Google Scholar
    • Export Citation
  • 32.

    Binet R, Ythier D, Robles AI, Collado M, Larrieu D, Fonti C, et al. WNT16B is a new marker of cellular senescence that regulates p53 activity and the phosphoinositide 3-kinase/AKT pathway. Cancer Res 2009;69:918391. https://doi.org/10.1158/0008-5472.CAN-09-1016.

    • Search Google Scholar
    • Export Citation
  • 33.

    Bocharov EV, Mineev KS, Volynsky PE, Ermolyuk YS, Tkach EN, Sobol AG, et al. Spatial structure of the dimeric transmembrane domain of the growth factor receptor ErbB2 presumably corresponding to the receptor active state. J Biol Chem 2008;283:69506. https://doi.org/10.1074/jbc.M709202200.

    • Search Google Scholar
    • Export Citation
  • 34.

    Leurs U, Mező G, Orbán E, Öhlschläger P, Marquardt A, Manea M. Design, synthesis, in vitro stability and cytostatic effect of multifunctional anticancer drug-bioconjugates containing GnRH-III as a targeting moiety. Biopolymers 2012;98:110. https://doi.org/10.1002/bip.21640.

    • Search Google Scholar
    • Export Citation
  • 35.

    Tejeda M, Gaal D, Schwab RE, Pap A, Keri G. In vivo antitumor activity of TT-232 a novel somatostatin analog. Anticancer Res 1999;19:32658.

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Senior Editors

Editor-in-Chief: Zoltán Zsolt NAGY
Vice Editors-in-Chief: Gabriella Bednárikné DÖRNYEI, Ákos KOLLER
Managing Editor: Johanna TAKÁCS
Associate Managing Editor: Katalin LENTI FÖLDVÁRI-NAGY LÁSZLÓNÉ

 

Editorial Board

  • Zoltán BALOGH (Department of Nursing, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Klára GADÓ (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • István VINGENDER (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Attila DOROS (Department of Imaging and Medical Instrumentation, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Judit Helga FEITH (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Mónika HORVÁTH (Department of Physiotherapy, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Illés KOVÁCS (Department of Clinical Ophthalmology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Ildikó NAGYNÉ BAJI (Department of Applied Psychology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Tamás PÁNDICS (Department for Epidemiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • József RÁCZ (Department of Addictology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Lajos A. RÉTHY (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • János RIGÓ (Department of Clinical Studies in Obstetrics and Gynaecology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Andrea SZÉKELY (Department of Oxyology and Emergency Care, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Márta VERESNÉ BÁLINT (Department of Dietetics and Nutritional Sicences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gyula DOMJÁN (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Péter KRAJCSI (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • György LÉVAY (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Csaba NYAKAS (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Vera POLGÁR (Department of Morphology and Physiology, InFaculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • László SZABÓ (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin TÁTRAI-NÉMETH (Department of Dietetics and Nutrition Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin KOVÁCS ZÖLDI (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gizella ÁNCSÁN (Library, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • András FALUS (Department of Genetics, Cell- and Immunbiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary)
  • Zoltán UNGVÁRI (Department of Public Health, Faculty of medicine, Semmelweis University, Budapest, Hungary)
  • Romána ZELKÓ (Faculty of Pharmacy, Semmelweis University, Budapest, Hungary)
  • Mária BARNAI (Faculty of Health Sciences and Social Studies, University of Szeged, Szeged, Hungary)
  • László Péter KANIZSAI (Department of Emergency Medicine, Medical School, University of Pécs, Pécs, Hungary)
  • Bettina FŰZNÉ PIKÓ (Department of Behavioral Sciences, Faculty of Medicine, University of Szeged, Szeged, Hungary)
  • Imre SEMSEI (Faculty of Health, University of Debrecen, Debrecen, Hungary)
  • Teija-Kaisa AHOLAAKKO (Laurea Universities of Applied Sciences, Vantaa, Finland)
  • Ornella CORAZZA (University of Hertfordshire, Hatfield, Hertfordshire, United Kingdom)
  • Oliver FINDL (Department of Ophthalmology, Hanusch Hospital, Vienna, Austria)
  • Tamás HACKI (University Hospital Regensburg, Phoniatrics and Pediatric Audiology, Regensburg, Germany)
  • Xu JIANGUANG (Shanghai University of Traditional Chinese Medicine, Shanghai, China)
  • Paul GM LUITEN (Department of Molecular Neurobiology, University of Groningen, Groningen, Netherlands)
  • Marie O'TOOLE (Rutgers School of Nursing, Camden, United States)
  • Evridiki PAPASTAVROU (School of Health Sciences, Cyprus University of Technology, Lemesos, Cyprus)
  • Pedro PARREIRA (The Nursing School of Coimbra, Coimbra, Portugal)
  • Jennifer LEWIS SMITH (Collage of Health and Social Care, University of Derby, Cohehre President, United Kingdom)
  • Yao SUYUAN (Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China)
  • Valérie TÓTHOVÁ (Faculty of Health and Social Sciences, University of South Bohemia, České Budějovice, Czech Republic)
  • Tibor VALYI-NAGY (Department of Pathology, University of Illonois of Chicago, Chicago, IL, United States)
  • Chen ZHEN (Central European TCM Association, European Chamber of Commerce for Traditional Chinese Medicine)
  • László FÖLDVÁRI-NAGY (Department of Morphology and Physiology, Semmelweis University, Budapest, Hungary)

Developments in Health Sciences
Publication Model Online only Gold Open Access
Submission Fee none
Article Processing Charge none
Subscription Information Gold Open Access

Developments in Health Sciences
Language English
Size A4
Year of
Foundation
2018
Volumes
per Year
1
Issues
per Year
2
Founder Semmelweis Egyetem
Founder's
Address
H-1085 Budapest, Hungary Üllői út 26.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2630-9378 (Print)
ISSN 2630-936X (Online)

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