DOI: 10.31038/CST.2018323

Abstract

Tumor cell migration and invasion are critical steps in the metastatic cascade and depend on the interaction between tumor cells, the extracellular matrix (ECM) and the endothelial cells. Integrins are key receptors that link cells and ECM, acting as mechanical sensors of the cell microenvironment. Particularly, Arg-Gly-Asp (RGD)-binding integrins such as αvβ3 and α5β1 integrins are of special interest in cancer progression. Integrins also interact with growth factor receptors resulting in an important cross talking between intracellular signaling pathways. Studies have provided evidence of distinct roles for αvβ3 and α5β1 integrins during migration. Therefore, αvβ3 and α5β1 integrins became an attractive target for pharmacological inhibition in cancer therapy and metastasis prevention. Cilengitide, the first integrin inhibitor based on the RGD motif, is currently under clinical trial in cancer patients with limited success. Monoclonal antibodies to integrins also presented modest results. Therefore, efforts to achieve a better understanding on the integrin roles in cancer progression are needed. In the last few years, new mechanisms that may help to explain the lack of success of integrin inhibitors were described and are commented here.

Keywords

integrin, cancer, disintegrins

Introduction

Cancer is one of the major concerns related to human health, and metastasis, when occurs, is the main cause of deaths in patients with cancer. Despite all efforts of academic, governmental and private institutions, there are very few options to prevent or treat metastasis. [1] One of the reasons for this lack of success relays on the current limited knowledge on the cellular programs driving the process of metastasis. Recently, new mechanisms that allow prolonged tumor cell survival after loss of attachment to the ECM have been reported, including autophagy and entosis [2]. In addition to shedding some light in the knowledge of tumor progression, these mechanisms provided new targets and options for metastasis treatment. Here we review some key aspects of cell attachment/detachment to ECM by integrins in the context of tumor microenvironment. We will also comment on the results obtained so far with integrin-targeted anticancer therapy.

Tumor Microenvironment and the Integrins

In the past ten years, the microenvironment where tumor cells develop has achieved special importance mostly due to its pivotal role in tumor progression. The tumor microenvironment (TME) provides signals and several kinds of support from distinct cell types and from the extracellular matrix (ECM) [3, 4]. Signals from the TME comprise soluble factors released by stromal cells such as fibroblasts, stem and immune cells, blood vessels, products from proteolysis of ECM components and cytokines [5]. On the other hand, tumor cells release proteases, microvesicles and growth factors that affect and modify the surrounding cells and the ECM. The TME also has a key role in the resistance to therapy due to a continuous communication with tumor cells and modulation of their responses [6, 7]. Integrins are among the crucial cell surface receptors in supporting the cross talk between cells and ECM, and therefore are critically involved in tumor progression [8].

Integrins are transmembrane receptors that support the adhesion of cells to the ECM [8]. Loss of integrin adhesion usually induces cell death unless cells can find new adhesion sites. Integrin are formed by heterodimers containing one α and one β subunits with the ability to recognize ECM components such as collagen (Col), fibronectin (FN) and laminin (LM) with high affinity [9]. There are 18 α subunits and 8 β subunits that can be combined in several ways to form distinct receptors with different specificity to ECM components. For instance, α5β1 integrin is the main receptor for FN whereas vitronectin (VN) binds preferentially to αvβ3 integrin. Both α5β1 and αvβ3 integrins recognize the tripeptide RGD motif within ECM proteins; however other integrins also binds to the RGD motif such as αvβ1, αvβ5, αvβ6, αvβ8, α8β1, and the platelet fibrinogen receptor, αIIbβ3 integrin [10]. One of the most interesting feature of integrins is the fact that, despite binding the same ligand, each one has its own cell-dependent pattern of expression and plays distinct roles in cell adhesion and migration [11].

Integrins in cell adhesion and migration

Integrin clustering and activation upon ligand binding triggers intracellular signaling pathways including the activation of several kinases like the focal adhesion kinase (FAK), mitogen activated protein kinase (MAPK) and extracellular signal-regulated kinase (ERK) resulting in changes in cell behavior [8, 12]. Cell adhesion and migration are among the main cell abilities that are under strict integrin control and are crucial steps during tumor progression. Moving cells may change their integrin profile in response to modifications on the ECM milieu. In a FN-rich microenvironment, cells will depend mostly on integrins such as α5β1 and αvβ3 for motility and, despite their ability in binding to the same ligand, these two integrins have distinct and specific roles in cell migration [13].

Adhesion to fibronectin by αvβ3 integrin supports extensive actin cytoskeletal reorganization resulting in a single large lamellipod with static cell–matrix adhesions at the leading edge [14]. On the other hand, cell adhesion by α5β1 generates thin protrusions containing highly dynamic cell–matrix adhesions in multiple directions [14]. Therefore, these authors concluded that β1 integrins support random migration, whereas β3 integrins are related to persistent migration. In agreement with these data, we have demonstrated that blockage of αvβ3 integrin by a DisBa-01, a recombinant RGD-disintegrin from snake venom, resulted in loss of directionality and decrease of speed migration [15]. Despite having the RGD adhesive motif, which is recognized by both αvβ3 and α5β1 integrins, the dissociation constant of DisBa-01 for the αvβ3 integrin is 100 times higher than for α5β1 integrin [15]. These results confirm the role of αvβ3 integrin in defining directionality of the cell movement.

Rosa-Cusachs et al., 2009 also provided evidence of distinct roles for α5β1 and αvβ3 integrin during cell adhesion/migration processes, with the demonstration that α5β1 integrin is responsible for supporting high adhesion forces while αvβ3 integrin starts talin-dependent mechanotransduction. However, these effects depend on the substrate where cells attach. Fibroblasts exhibit persistence migration on FN-coated surfaces [16]. Ligand-specific activation of αvβ3 e α5β1 integrins also confirmed the distinct roles of each integrin in cell adhesion. Activation of αvβ3 integrins led to stabilization of peripheral focal adhesions while fibrillary structures were observed when α5β1 integrins are activated [17]. Moreover, αv-class of integrins such as αvβ3 were demonstrated to outcompete α5β1 integrins in FN binding; however, after engagement, αv-class integrins cooperate with α5β1 integrins to form additional adhesion sites consequently strengthening cell adhesion to FN [18].

Although they may bind the same ligand, β1 and β3 integrins have distinct and cooperative roles in mechanotransduction. By means of traction force microscopy, Millioud and colleagues demonstrated that deleting β3 subunit increases traction forces, whereas the deletion of β1 subunit results in a strong decrease of contractile forces [19].

Integrins and Growth Factor Receptors

The cross talk between integrin and growth factor receptor (GFR) signaling pathways is well documented in the literature in both normal cells and tumor cells. Endothelial cells seem to be highly sensitive to integrin activation of GFRs including the vascular endothelial growth factor receptor (VEGFR), epidermal growth factor receptor (EGFR), and the platelet-derived growth factor receptor (PDGFR). This cooperative process is crucial in physiological and tumor angiogenesis and it is considered one key factor in tumor progression. The α5β1 integrin was demonstrated to induce tumor cell proliferation by two pro-survival mechanisms including direct activation the EGFR signaling cascade and by signaling via continuous integrin-dependent activation of protein kinase B (PKB, also known as AKT) [20]. Moreover, EGFR overexpression led to inactivation of α5β1 integrin in A431 squamous carcinoma cells, which would be interesting in order to prevent cell interaction with the ECM and therefore to avoid tumor cell proliferation. However, treatment of cells with EGFR kinase inhibitor resulted in reactivation of the integrin [21]. Since GFRs are usually overexpressed in many types of cancer cells, pro-survival signaling pathways from both GFR and integrins would be more efficiently impaired upon association of anti-integrin/anti-GFR treatments than either treatment alone [22].

VEGF binding to its receptors and co-receptors induce receptor homodimerization and heterodimerization, followed by activation of tyrosine kinases and signaling cascades, with the association of a set of adaptor proteins. The activation of these signaling pathways results in activation, migration and proliferation of endothelial cells, crucial steps for neoangiogenesis. In addition, mechanical forces such as shear stress may activate VEGRF2 similarly to ligand binding, leading to the activation of intracellular signaling pathways [23]. Integrins are proposed to act as co-receptors upon VEGF binding to VEGFRs, similarly to neuropilins and heparin sulfate proteoglycans in endothelial cells [24]. However, integrins seem to participate actively in the control of VEGFR signaling. Blocking αvβ3 integrin by a RGD-antagonist downregulated the expression of VEGF, VEGFR1 and VEGFR-2 in endothelial cells but not in MDA-MB-231 breast tumor cells [25]. Contrastingly, we observed an increase in VEGF protein levels by human fibroblasts after treatment with the αvβ3 integrin antagonist. In addition, we have also demonstrated that this RGD-antagonist inhibits endothelial in vitro cell migration and in vivo angiogenesis in mice [26, 27]. These results suggest that the αvβ3 integrin is not only a co-receptor; instead, it is an active partner in the control of VEGF signaling in endothelial cells.

A key role for α1β1 and α2β1 integrins in the process of angiogenesis triggered by vascular endothelial growth factor (VEGF) was previously reported. Antibody antagonism of either integrin resulted in potent inhibition of VEGF-driven angiogenesis in mouse skin, reduced tumor growth and angiogenesis of human squamous cell carcinoma xenografts. [28]

Integrins and MMPs

Matrix metalloproteases (MMP) comprise a class of zinc-dependent enzymes responsible for ECM remodeling and degradation. MMPs are also involved in the processing of growth factors, cytokines and surface transmembrane proteins. MMPs are produced as inactive zymogens that can be activated by proteolytic removal of the pro-peptide domain by furin, or by autoproteolysis. To date, more than 24 MMPs are known, including secreted or membrane anchored forms, (membrane-type MMPs, MT-MMPs) that play crucial roles in the process of MMP activation. For instance, activation of pro-MMP-2 at the cell surface involves the formation of a trimolecular complex with membrane type-1 metalloprotease (MT-1-MMP) and tissue inhibitor of metalloproteases-2 (TIMP-2). MMP-2 and MMP-9 are also known as gelatinases A and B, respectively, due to the ability to digest degraded forms of collagen. Gelatinases are characterized by the presence of a fibronectin-like domain that drives the enzyme to its ECM substrates. MMP-2 and MMP-9 are of particular interest in cell migration and consequently, in metastasis development. MMP-2 is constitutively produced by most cells; however, MMP-9 is expressed by only a few types of cells including neutrophils, macrophages and tumor cells, being induced in several pathological conditions such as tumor invasion [29, 30].

MMPs play key roles in tumor progression such as degrading ECM to allow migration of tumor cells to distant secondary sites, allowing endothelial cell migration and proliferation to produce tumor angiogenesis, and releasing growth factors from the ECM to provide constant survival and proliferation signals.

The role of integrins in controlling MMP activity is less studied. Previous studies demonstrated that interaction of fibronectin with α4β1 integrin upregulates MMP-9 expression by infiltrating leukocytes in damaged livers and the blockade of this interaction disrupted leukocyte migration [30]. MMP-2 activation upregulates VEGF-A expression in melanoma cells via an αvβ5 integrin/phosphoinositide-3-kinase-dependent pathway [31]. The αvβ3 integrin has been closely related to tumor progression and reduced patient survival rates in melanoma, colon carcinoma and breast cancer, increasing migration and invasion of tumor cells [32, 33]. Blocking αvβ3 integrin inhibited MT-1-MMP-dependent activation of MMP-2 induced by collagen I; however, cells expressing high levels of β3 integrin subunit have increased abilities of adhesion and migration [34]. Blocking αvβ3 integrin in endothelial cells by a RGD-based antagonist completely abolished MMP-2 activity; in contrast, the same treatment increased almost twice the MMP-9 levels in the conditioned media from MDA-MB-231 breast tumor cells [25]. These results demonstrated that one single specific integrin inhibitor might induce different cell-dependent effects.

Integrins and tumor progression

The correlation of expression levels of αvβ3, αvβ5, α5β1, α6β4, α4β1, αvβ6 and αvβ8 integrins with metastasis and poor patient prognosis is well documented (reviewed by Nieberler et al., 2017). [35] One of the most studied integrin in tumor progression is the α5β1 integrin. Higher levels of α5 subunit were found than in normal tissue in patients with advanced renal cell carcinoma and correlated with tumor grade, metastasis development and reduced patient survival [36]. Expression of αvβ6 is significantly associated with the progression of breast ductal carcinoma to an invasive form by a mechanism involving upregulation of MMP-9 and transforming growth factor-β (TGF-β) [37].

Previous reports associated β1 and β3 integrins with TGF-β stimulation of epithelial–mesenchymal transition (EMT) and breast tumor metastasis by means of a compensatory mechanism [38]. Inactivation of β1 integrin impairs the TGF-β effect in promoting tumor cell migration; however, a strong compensatory upregulation of β3 integrin restores the induction of the EMT phenotypes by TGF-β, indicating that the two integrins must be targeted to prevent tumor progression [38].

Integrin-targeted therapy

Cilengitide was one of the first antiangiogenic drugs directed to blockade of cell adhesion to the ECM by antagonizing αvβ3 and α5β1 integrins (IC₅₀ for inhibition of cell adhesion of 0.2 and 11 nM, respectively). In phase I studies, patients with advanced solid tumors were treated with cilengitide without consistent results [39]. In another study, cilengitide was tested in association with cediranib, an inhibitor of VEGFR-associated tyrosine kinase. The association of cilengitide with the two drugs was well tolerated, however there were no changes in the survival rates [40, 41]. Cilengitide combined with temozolomide, an oral alkylating agent, did not increase the survival rates of glioblastoma patients [42]. Among antiangiogenic drugs, only the anti-VEGF-A bevacizumab increased disease-free survival time in patients with glioblastoma [43]. Recently, 12 patients with solid tumors such as breast cancer were treated with cilengitide, with partial positive response to the treatment and 05 had stable disease as the best response [44]. In summary, after 10 years of clinical assays with cilengitide for different tumors, results are still disappointing. Reasons for the lack of success may be related to the determination of the effective doses and time of administration. [45- 47] Other reason for lack of success may be the dose-dependent opposing effects of cilengitide related to tumor angiogenesis, with low doses being pro-angiogenic in contrast with anti-angiogenic effect of higher doses [48]. However, a better comprehension on the distinct roles of integrins in the context of complexity of the tumor microenvironment is needed before discarding integrin-targeted therapy.

Volociximab, a monoclonal antibody anti-α5β1 integrin, has been tested in at least 10 phase I and II clinical trials to treat some types of tumors, including advanced non-small cell lung cancer (NSCLC) and metastatic melanoma, among others. Volociximab was used either as single therapy or in combination with classical drugs such as carboplatin and paclitaxel. Preliminary results showed modest but relevant results such as an increase in median progression-free survival of 6.3 months and decreased levels of potential biomarkers of angiogenesis or metastasis after six cycles of treatment [49].

Etaracizumab, an anti-αvβ3 integrin monoclonal antibody, decreased SKOV3ip1 ovarian tumor cell proliferation and invasion in vitro and resulted in about 50% of tumor weight decrease in mice [50]. Combination therapy with paclitaxel gave better results in decreasing tumor weight, and tumors showed reduced levels of p-Akt and p-mTOR; however, microvessel density of resected tumors after therapy were not decreased [50]. The β1 integrin subunit has been associated to therapeutic resistance to trastuzumab (anti-EGFR/HER2 monoclonal antibody) and to lapatinib (an EGFR/HER2 tyrosine kinase inhibitor) of human epidermal growth factor receptor (HER)-2-positive breast tumor cells [51].

One of the most intriguing question in integrin-based anti-cancer therapy is the fact that the strong and positive results on inhibition of tumor progression in pre-clinical assays did not translate to clinical assays. Integrin inhibitors including monoclonal antibodies and synthetic molecules showed disappointed results in patient survival time, disease stabilization and the development of metastasis [42, 48, 52]. One reason for the negative results may rely on the complexity of the mechanism of action of integrins, their ability to compensate each other and inducing an even worse phenotype. Deleting β1 integrin was compensated by β3 integrin, which stimulated metastasis in murine model of breast cancer [38].

Besides the compensatory mechanism, integrin inhibition should induce cell death by anoikis, a kind of apoptotic cell death that occurs due to the loss of cell attachment to the ECM [53]. However, ECM detachment results in antiapoptotic signals, as a defense mechanism against anoikis until cells be able to find a new place to attach again. Meantime, cells undergo autophagy, a cell process mostly triggered by the loss of integrin-mediated adhesion that allow cell survival during some time. However, prolonged detachment will later induce apoptosis by anoikis [54]. One of the most critical finding is that tumor cells usually develop resistance to anoikis due to a sustained autophagic response [54].

Entosis, an even more sophisticated cell survival mechanism, was described [55]. Entosis, also referred to as cell-in cell structures, or cell cannibalism, is triggered by loss of attachment to ECM, similarly to the process of autophagy. Entotic cells have been observed in many types of tumors and may be one of the reasons for the abnormal number of chromosomes found in most tumors [2]. Engulfed cells are alive and may divide inside the host, and in case of tumor cells, such process may occur indefinitely. Such mechanisms of tumor cell survival that happen upon ECM detachment may certainly contribute for the lack of success of integrin inhibitors in clinical trials.

More recently, the mechanism of vessel co-option was described as a mediator of resistance to anti-angiogenic therapy of breast tumor liver and lung metastasis [56]. Vessel co-option is an alternative pathway of tumor cells for obtaining nutrients from blood using the pre-existing vasculature without producing new vessels. Blocking VEGF/VEGFR signaling induces co-option and tumor growth in glioblastoma patients. [57] Since there is a close reciprocal stimulatory relationship between VEGF and αvβ3 integrin [58], one might expect a role for integrin inhibition in supporting the mechanism of co-option. This possibility remains to be elucidated. These results demonstrate the complexity of the TME and its relevance in tumor progression.

New insights on integrin targeting

In spite of being extensively described, integrin inhibition in tumor microenvironment is still challenging and attractive. The failure of targeted therapies so far leads to deeper investigations about signaling pathways, endocytic trafficking and recycling of integrins [59, 60].

As a result, the attention that before was outside cell, turned to intracellular integrin fate affecting the overall cell behavior. Its known that integrin trafficking dictates the nature of Rho GTPase signaling during cytokinesis and cell migration [61]. FN binding promotes both accelerated internalization and ubiquitination of α5β1 receptors. Subsequently, alterations in pH inside endossomal compartments will define either recycling or degradation of integrins [59, 62] When α5 integrin suffers ubiquitination upon FN binding, the ESCRT machinery acts sorting this receptor to either multivesicular bodies, recycling or lysosomal degradation [59]. It was previously demonstrated that mutation on the ubiquitination site in cytoplasmic tail of α5 integrin causes a different sorting of fibronectin on cell, affecting fibroblast migration [63].

The multivesicular bodies are cell compartments containing intraluminal vesicles named exosomes that are secreted to the extracellular space by shedding from the plasma membrane, improving cell communication with the TME [64]. The presence of both integrin and FN inside multivesicular bodies had light to the hypothesis that these receptors might be present in vesicles in the extracellular environment. Sung et al demonstrated that in fact α5 integrin is secreted as an exosome cargo, and more than that, FN was also secreted in these vesicles. Thus, a new and promising science of integrins as a target has emerged from the microvesicles field. Studies on cell communication had proved that integrin transfer can occur through exosomes delivery in both TME and the pre-metastatic niche [65]. In addition, the integrin content of exosomes can change the types of integrin expression in the new tumor focus [66]. The real contribution of integrins on cell communication using cell-derived vesicles is still unclear, as well as the effects of blockage of these receptors. However, this can be the missing clue that can explain the failure of earlier integrin inhibitors in drug development.

Conclusions

Cell attachment to the ECM via integrins is a key factor for tumor progress; however, integrin inhibition may be carefully considered as a target for drug development. Combination of anti-growth factors antibodies, tyrosine kinase inhibitors and integrin inhibitors may be an interesting choice but must be first evaluated in pre-clinical assays considering all the possible escape mechanisms that tumor cells can develop. Most of the studies so far have considered the signaling in a cellular level, however, in complex organisms, several other factors might systemically interfere on integrin inhibition, making the drug development even more challenging. The integrins may have won some battles but not the war.

Acknowledgements: This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, 2013/00798-2 and 2014/18747-8) and by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq 308096/2013-4), Brazil.

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DOI: 10.31038/CST.2018322

Abstract

Introduction: The paper presents the assessment of radiation doses received by patients undergoing mammography imaging at Mulago National Referral and Teaching Hospital for a period of five months.

Materials and Methods: Mammography polymethyl methacrylate (PMMA) phantoms of different sizes were used in the determination of the doses to the breast of patients. Mean glandular doses (MGDs) of 60 patients who presented for mammography within the study period were determined from their exposure data, the tube output, and half-value layer (HVL) of the mammography unit. The  kVp, mAs, compressed breast thickness (CBT), and projection view (Mediolateral oblique projection, MLO /Cranial-caudal projection, CC) for each patient were then used to expose the phantoms simulating the different patients’ CBT. The MGD was calculated as the product of the entrance surface dose (ESD) at the surface of the phantom and the conversion factors extracted from the European protocol on dosimetry in mammography, EUR 16263, 1996. Thermoluminescent dosimeters (TLDs) were used in the measurement of the ESD.

Results: The average MGD was 1.6 ± 0.5 (range 0.8 – 2.5) mGy for CC projection and 1.7 ± 0.3 (range 1.1 – 2.4) mGy for the MLO projection. The MGD for a 4.5 cm CBT was 1.6 ± 0.1 mGy and 1.8 ± 0.01 mGy for CC and MLO projections respectively which were both less than 3.0 mGy recommended by the American College of Radiology.

Conclusion: The values of MGD found in this study were therefore acceptable and comparable to the recommended standards by the American College of Radiology.

Key words

mammography, mean glandular dose, phantom, thermoluminescent dosimeter.

Introduction

Breast cancer cases are rising worldwide especially across the developing world [1]. Women breast cancer is the main cause of cancer mortality in women globally. In Uganda, it comes third after cervical cancer and Kaposi’s sarcoma [2]. Presently, breast cancer has no effective primary prevention. Early detection of breast cancer can help treat and cure the disease. International Atomic Energy Agency (IAEA) report on radiation protection of patients shows that mammography is very good at early identification and diagnosing of breast cancer and has decreased mortality mostly in women of age 50-69 years to up to 20% – 35% reductions (IAEA-RPOP, 2014).  It therefore implies that efforts need to be made to detect breast cancer while still in its early and treatable stages [2].

Mammography helps in identifying very small breast tumors with the aim of detecting breast cancer when it is still in its treatable conditions. Mammography necessitates control over management of patient dose and reduction of possible risk since the breast glandular tissue is very sensitive to ionizing radiation [3]. Mammography calls for use of X-rays that have the potential to cause cancer, but the advantages of mammography weigh more than any possible harm that may result from radiation exposure [4]. A balance between image information and the absorbed dose to the patient’s breast always needs to be taken into account i.e. the dose should be kept as low as reasonably achievable [5].

The radiation exposure of a mammography patient is expressed in terms of the mean glandular dose (MGD). The MGD is the mean dose to the breast glandular tissue. It is taken to be an important quantity for establishing risk from different mammography procedures [6]. However, the MGD cannot be measured directly as it occurs within the breast. MGD for each patient is got from calculations involving exposure parameters used to obtain the mammogram and the measurement of tube output [6]. It is very essential that the dose experienced by patients as a result of  exposure to radiation is optimum, therefore  the MGD is pertinent ( Elsie et al., 2010) to Mammography. The American College of Radiology, 2014 recommendation on MGD for a 4.5 cm compressed breast thickness is less than 3 mGy for screen/film with grid.

This study aims at determining and assessing the radiation doses received by patients undergoing mammography imaging at Mulago National Referral and Teaching Hospital.

Materials and Methods

Study Design

The performance of the mammography machine was tested by investigating the accuracy and reproducibility of the kVp settings and measuring the half value layer (HVL).

Patients’ consent was sought and their data and exposure parameters used for mammography examination were recorded by the Mammographer on the exposure data form. The exposure parameters recorded included the patient’s age, Tube potential (kVp), Tube loading (mAs), compressed breast thickness (CBT), projection view, and whether the right or left breast was exposed. Since radiation exposure of humans for medical research is deemed to be unjustified [7] mammography polymethyl methacrylate (PMMA) phantoms of different sizes were used to simulate the different patient breast sizes.  The PMMA phantoms were exposed using the same exposure parameters as were used on different patients to obtain the entrance surface dose (ESD) that was received by each patient in each projection view.

Calculations were then done to determine the mean glandular doses (MGDs) that were received by the patients.

Materials

The equipment and tools used for collecting data consisted of the mammography machine, a digital kVp meter (Unfors Mult-O-Meter) type 535L, PMMA mammography phantoms that were used to evaluate radiation dose and were tested to ensure that they simulated radiographic features of the breast tissue,  Thermoluminescent dosimeters (TLD badges) that were used in measurement of entrance surface dose (ESD). Lithium Fluoride TLD 100 (LiF TLD-100) badges with two chips were used and the average reading of both chips was taken [8].

The TLD badges were calibrated using caesium 137 Irradiator, and annealed before they were exposed to radiation. The TLD badges were read from the laboratory of the Physics Department of Makerere University using the Harshaw 4500 TLD reader, which was calibrated using the Strontium-90 (Sr-90) Irradiator (model 2000) [9].

The Mammography Machine

The mammography machine used was a Philips Mammo Diagnost UC with serial number 885538968. Its focal spot size was 0.3 mm and it used a high frequency X-ray generator.  The machine’s exposure voltage ranged from 23 to 35 kV, adjustable in increments of 1 kV. The filter used was molybdenum (Mo) and the target/filter combination was Mo/Mo. The compressed breast thickness (CBT) was measured by an inbuilt device (ruler) whose accuracy was verified. Calibration and full quality control measurements were also made on the machine according to the requirements of the regulatory authority. Preliminary tests were done on the machine to ensure proper function for example testing for accuracy and reproducibility of kVp settings, and measurement of half value layer (HVL). The instrument used for these measurements was the Unfors Mult-O-Meter (Model 535L, Serial Number 147389), which was used for both half value measurements (as a dosimeter) and for kVp measurements. The Unfors Mult-O-Meter was calibrated using a Siemens Mammomat 3000 with a Mo anode and 30 µm Mo added filtration [10].

Determining Radiation Doses Received by Patients

Doses of 60 patients who presented for mammography within a period of five months were calculated from patient exposure data and from the measurements of tube output and HVL of the mammography unit. For every mammogram obtained, an assessment for image quality compliance was carried out by qualified radiologists. The MGD was determined for different patients using polymethyl methacrylate (PMMA) phantoms of different sizes, imaged using the same parameters as were used on patients. The tube output was determined as the ratio of entrance surface dose (ESD) and mAs at a distance of 0.6 m. I.e.

TLDs were used in the measurement of ESD. In measurement of ESD, the mammography machine was set up for either cranial-caudal (CC) or mediolateral oblique (MLO) projection view with the compression plate present. The MLO projection was performed at 45^o. For each patient’s breast thickness, a representative phantom was positioned on the breast support and a TLD placed on top of the phantom (at the reference point). An exposure was made using the same parameters as used clinically on patients. The TLDs were then kept away from radiation and later taken to the laboratory for reading [11-13].

The MGDs were calculated according to the European protocol on dosimetry in mammography, 1996 as;

MGD = K_PMMA × g × c

Where K_PMMA is the incident air kerma at the surface of the phantom, (K_PMMA = Tube output × Tube loading, mAs), g-factors convert air kerma into dose, c-factors correct for different glandularity than 50%, and both g- and c-factors depend on the HVL and CBT. The HVL was determined and found to be 0.42 mm.

The distribution of MGDs for both CC and MLO views for the different breast sizes was determined.

Results

The distribution of entrance surface dose (ESD) of both CC and MLO views for the different tube potentials were as shown in Table 1, and represented in a histogram in Figure 1.

Figure 1. Distribution of ESD for different tube potentials (kVp) for both CC and MLO views.

Table 1. ESD for the different tube potentials for both CC and MLO views

Table 2 shows the kVp values that were used for the different CBT. The CBT was measured as the distance between the bottom of the compression plate and the table upon which the breast rested. This was done using an in built device (ruler) whose accuracy was verified.

Table 2. kVp range used for the various CBT

The MGD per projection view for each patient was determined by multiplying the ESD by the conversion factors which are a function of half value layer (HVL) and compressed breast thickness (CBT). The conversion factors used in this study were those by Dance et al, extracted from the European protocol on dosimetry in mammography, 1996. The average value of MGD per CBT for the two projection views was determined and plotted as shown in Figure 2 below.

Figure 2. Average of MGD for the different CBT for the two projection views.

The average MGD was 1.6 ± 0.5 (range 0.8 – 2.5) mGy for the CC projection and 1.7 ± 0.3 (range 1.1 – 2.4) mGy for the MLO projection. The average MGD for a 4.5 cm CBT was found to be 1.6 ± 0.1 mGy and 1.8 ± 0.01 mGy for the CC and MLO projections respectively.

Discussion

From figure 1 above, the values of ESD for CC view for a given kVp value were found to be generally higher than those for MLO view. This is because with MLO view, more breast tissue is imaged thereby providing extra tissue without extra exposure, hence lower values of ESD.

There was some non uniformity in the distribution of kVp values for the various CBT. E.g.  Patients with 2.5 cm, 3.0 cm and 3.5 cm CBT were exposed using almost the same kVp range, some patients of 5.0 cm CBT were exposed using kVp as low as 22 kVp. This implies therefore that some patients with lower CBT could be found to have received higher MGD as compared to some with higher CBT. This was however a result of difference in patient breast density.

There was a fluctuation in the distribution of MGD for the different CBT (Figure 2). This was due to the difference in kVp used for the different CBT. The average dose values obtained of 1.6 ± 0.5 mGy for CC projection and 1.7 ± 0.3 mGy for MLO projection view were found to be less than those found in the study done in Kenya by JS Wambani et al; 2011, where the average MGD was 2.14 and 2.44 mGy for CC and MLO projection views respectively and also less than those obtained in a study done in Bulgaria by Simona and Jenia; 2008, on two mammography units where the MGD for unit 1 was 2.0 ± 1.0 mGy for CC projection and 2.6 ± 1.8 mGy for MLO, and for unit 2, the MGD was 2.1 ± 1.0 mGy and 2.2 ± 1.0 mGy for CC and MLO projection views respectively.

The MGD for CC projection was found to be less than for MLO projection as in other studies done in Kenya and Bulgaria. The MGD for a 4.5 cm CBT for CC and MLO projections of 1.6 ± 0.1 mGy and 1.8 ± 0.01 mGy respectively were both less than 3.0 mGy recommended by the American college of radiology and the U.S Food and Drug Administration, 2005.

Conclusion

The MGD for a 4.5 cm CBT of 1.6 ± 0.1 mGy and 1.8 ± 0.01 mGy for CC and MLO projections respectively were both less than 3.0 mGy recommended by the American college of radiology and the U.S Food and Drug Administration, 2005. Hence the doses obtained were acceptable. Further studies should consider carrying out the study for a longer period to have a bigger number of patients, and therefore a wider variation in parameters, and also consider mammography units of different technical characteristics from different mammography centers for the establishment of national diagnostic reference levels.

References

1. Wheeler Celeste. (2003, April). The Mammography Quality Standards Act:  Misread Mammograms, Malpractice, and the Politics of Regulation.
2. Uganda Breast Cancer Working Group (2003) Breast cancer guidelines for Uganda. Afr Health Sci 3:  47–50. [crossref]
3. Rothenberg LN (1990) AAPM tutorial. Patient dose in mammography. Radiographics 10:  739–746. [crossref]
4. American Cancer Society (ACS), 2014. Mammograms and Other Breast Imaging Tests.
5. IAEA-TECDOC-1447 (2005) Optimization of Radiological Protection of the Patients:  Image Quality and Dose in Mammography. ISBN:  92-0-102305-7
6. American College of Radiology (ACR) (2014) Practice parameter for the performance of screening and diagnostic mammography
7. IAEA-TECDOC-1067 (1999) Organization and Implementation of a National Regulatory Infrastructure Governing Protection against Ionizing Radiation and Safety of Radiation Sources. ISSN 1011-4289
8. Dance DR, Skinner CL and Carlsson GA (1999) Breast dosimetry. Appl. Radiat. Isot. 50:  185–203.
9. Elsie K, Gonzaga M, Francis B, Michael K, Rebecca N, Rosemary B, Zeridah M (2010). Current knowledge, attitudes and practices of women on breast cancer and mammography at Mulago hospital. Pan African Medical Journal. 5: 9
10. IAEA Radiation Protection of Patients (RPOP).
11. JS Wambani, GK Korir, MN Shiyanguya, & IK Korir (2011). Assessment of patient doses during mammography practice at Kenyatta National Hospital. East African Medical Journal.
12. Simona Avramova-Cholakova and Jenia Vassileva.(2008). Pilot study of patient and phantom breast dose measurements in Bulgaria. Pol J Med Phys Eng 14: 21–32
13. U.S Food and Drug Administration, (2005, September). Mammography Facility Surveys, Mammography Equipment Evaluations, and Medical Physicist Qualification Requirements under MQSA.

DOI: 10.31038/CST.2018321

Abstract

In silico methods can help in identifying drug targets via bioinformatics tools. In our previous studies, a 2.34 kDa short linear peptide analogue to myxoma virus M-T5 protein was computationally designed using the resonant recognition model (RRM). Quantitative and qualitative cell cytotoxicity assays showed that the peptide analogue can induce a dose and time dependent tumoricidal effect on skin cancer cells but not on normal cells. It has been reported that the viral protein (M-T5) binds with p-Akt to regulate Akt signaling in some human cancer types. Hence in this study we investigated the effects induced by the peptide analogue RRM- MV on the Akt pathway in skin cancer and normal cells. Akt expression levels in cells treated with RRM-MV, in the presence or absence of PI3K/Akt inhibitor, were detected in mammalian skin cancer and normal cells using immunoblotting. The results revealed that different endogenous levels of p-Akt were expressed in the human melanoma and carcinoma cells following treatment with RRM-MV. Yet, it did not appear to affect the p-Akt expression in the mouse melanoma cells. Furthermore, RRM-MV treatment did not seem to affect the level of total Akt in any type of cancer cells under the same experimental conditions. Hence, the bioactive peptide RRM-MV appears to be targeting the Akt pathway in some types of skin cancer cells. Elucidating the mechanism of RRM-MV effects on other cellular apoptosis pathways requires further investigation.

Keywords

Akt, RRM-MV, Cell death pathway, Carcinoma, Melanoma, Myxoma virus.

Background

Malignant melanomas can be resistant to conventional therapies such as chemotherapy, immunotherapy, radiation therapy and/or surgery, and patient’s chances of survival often depend on early diagnosis and treatment [1]. The discovery and development of novel cancer therapeutic agents is an important research field as cancer is an international health problem with the current treatments achieving only limited success. Oncolytic virotherapy is a novel therapy that can be applied solely or in conjunction with the conventional therapies. In particular, some viruses have the ability to target and destroy malignant cancer cells without harming the normal cells [2- 5]. Myxoma virus (MYXV) is a new poxvirus oncolytic candidate that has been added to the list of oncolytic viruses used in virotherapy. MYXV is a member of Poxviridae family and the Chordopoxvirinae subfamily [6-8]. It is a rabbit-specific pathogen that causes myxomatosis in European rabbits (Oryctolagus cuniculus), which is considered as a fatal disease [8]. However, MYXV is non-pathogenic in humans and all other vertebrate species [6, 9-13].

Previously, MYXV was shown to be able to selectively kill human cancer cells [14-17]. Intense in vitro investigations have indicated that replication of MYXV in human cancer cells is associated with the hyperactivation of the serine/threonine kinase Akt in cancer cells [17-27]. In addition, human cancer cells have been grouped into three types depending on the ability of being productively infected with MYXV, and the capability of MYXV to activate Akt through the action of a M-T5 viral protein [26, 28]. M-T5 is an ankyrin-repeat host range protein that is shown to be required for virus replication in rabbit lymphocytes, and is critical for virus replication in the majority of human tumor cells [29]. M-T5 interacts with two human cellular proteins. The first cellular protein is Cullin-1, an E3 ubiquitin ligase that is involved in the progression through the cell cycle. The interaction of M-T5 with Cullin-1 inhibits MYXV- infected cells from cell cycle arrest and stress-induced cell death [30]. The second cellular protein is Akt-1/protein kinase B (PKB) that directly interacts with M-T5 [26, 31]. Akt is a serine/threonine kinase essential for normal cell processes such as programmed cell death, proliferation, cell cycle progression, angiogenesis and metabolism [22]. It is activated via the phosphorylation of its central component at ser-473/474 and thr-308/309 [32]. Akt dysregulation is commonly detected in an extensive spectrum of human cancers [23, 33-39]. It was found that many human cancer cells exhibit a high endogenous activation of Akt in vitro [18, 33, 34, 40]. Akt is a central regulator of cellular signaling; hence, it is not surprising that many viruses have developed new strategies to control the activation of Akt [41].

Therapeutic peptides have been emerging as a novel class of drugs for cancer therapy and are being intensively studied for their role in developing novel cancer therapeutics [2, 3]. This is due to the fact that peptides have a high potential to penetrate cellular membranes, interfere with enzymatic functions and protein-protein interactions within cells [4-7]. Anticancer therapeutic peptides are able to kill cancer cells due to their strong tumoricidal activity and low toxicity towards normal cells [42-47]. Peptide therapy has many promising advantages over small molecule drugs. Peptides can be designed to target any protein of interest using ‘rational’ computational methods. Due to structures and interactive partners of many oncogenic proteins being identified, peptides can be designed to inhibit these interactions by using a sequence from the interaction domain. Another advantage is that peptides are easily produced using chemical synthesis or molecular biology techniques. Unlike natural proteins, peptides are easily synthesized in bulk at relatively low cost, using automated systems. The costs of producing therapeutic proteins through genetically modified organisms and cell cultures are relatively high.

The Resonant Recognition Model (RRM) [42] is the physico-mathematical approach designed for functional and structural analysis of proteins and DNA. The RRM approach interprets a protein’s sequence linear information using signal analysis methods. In the RRM, the protein primary structure is represented as a numerical series by assigning to each amino acid in the sequence a physical parameter value relevant to the protein’s biological activity. The RRM concept is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. It has been found through an extensive research that proteins with the same biological function have a common frequency in their numerical spectra. This frequency was found then to be a characteristic feature for protein biological function or interaction [43-48]. This protein characteristic frequency can be identified from analysis of the power spectra of the selected protein sequences. In addition, from the analysis of their phase spectra, we can identify the corresponding phase for a particular frequency. Once the characteristic frequency for a particular protein function/or interaction is determined, it is possible then to predict the amino acids, the so called “hot spots” in the sequence that predominantly contribute to this frequency and consequently to the observed function. On the basis of determined RRM characteristic frequencies and phases for a particular group of protein sequences, we can design amino acid sequences (short peptides) having those specific characteristics related to a protein’s biological function. It is expected that the designed peptide will exhibit the desired biological activity [42,  49-50].

In the previous research studies, the RRM approach was used to structure–function analysis of different protein examples [42, 50], aiming at the design of peptide analogues having the same functional activity as their parent proteins. Myxoma virus (MXYV), interleukin12 (IL12) and the tumour necrosis factor (TNF-α) can significantly affect tumour progression. Based on these properties, three short bioactive peptide analogues: RRM-MV RRM-IL and RRM-TNF [51] were designed using the RRM approach [50]. These synthetic peptides were de novo designed to mimic activities of the selected therapeutic proteins. RRM–designed peptides present potential therapeutic candidates for cancer treatment whose efficacies were evaluated in our previous studies [50]. In particular, we examined the biological effects of these peptides on B16F0 cell mouse skin cancer cells and normal murine cells in vitro, and found that RRM-MV, RRM-IL and RRM-TNF treatment induced toxic effects on the mouse melanoma cells in a dose- and time-dependent manner but no cytotoxic effects were detected in normal cells [43-48, 50]. However, our initial data did not show a significant effect on the total Akt levels following treatment of the mouse melanoma cells (B16F) with the peptide analogue RRM-MV[43]. Thus, it is not known if the cytotoxic effects on cancer cells caused by the MT5-peptide analogue (RRM-MV) were generated by targeting the same cell death pathways in skin cancer cells. Therefore, in this study we tested the effect of the RRM-MV and non- bioactive (control) peptide RRM-C on the p-Akt pathway in human skin cancer and normal human skin cells.

Materials and Methods

RRM peptide sequences and synthesis

The RRM-MV is a 18 amino acid short linear peptide (MDDRWPLEYTDDTYEIPW) analogue for myxoma virus M-T5 protein which was specifically designed to exhibit anti-cancer activity [43, 44]. The RRM-C is a 22 amino acid short linear peptide (CVLQDCVLQDCVIQDCVLQDCV) designed as a control peptide that is lacking the anti- cancer activity. It was used as a negative control peptide along with the bioactive RRM-MV in the experimental evaluation presented below. The detailed description of the de novo design procedure for RRM-MV and RRM-C peptides was presented in our previous study [43]. The two peptides were synthesized with >95% purity (AUSPEP, Melbourne, Australia). RRM- MV and RRM-C were freshly prepared at different concentrations in the relevant cell culture medium immediately prior to use.

Mammalian cell culture growth conditions and treatment with the RRM peptides

Human malignant melanoma (MM96L), human squamous cells carcinoma (COLO-16) and normal human dermal fibroblast (HDF) cell lines were obtained from Dr. Terrence Piva, RMIT University, Australia. Mouse melanoma cell line (B16F0) was donated by Dr. Glen Boyle, QIMR, Australia. The MM96L, COLO-16 and B16-F0 cell lines were cultured in Roswell Park Memorial Institute medium (RPMI) 1640 (GIBCO, Australia) supplemented with 10% heat- inactivated fetal bovine serum (FBS) (Bovogen serum, Biologicals, Australia). The HDF cell line was propagated in medium 106 supplemented with 2% Low Serum Growth Supplement (LSGS) (GIBCO, Australia). The cell lines were confirmed to be mycoplasma free using a Mycofluor Detection Kit (Invitrogen, Oceania). All cell cultures were grown and maintained as monolayers in 75 m² tissue culture flasks (Greiner Bio-One, Germany) at 37°C in a humidified atmosphere and 5% CO₂ in air. The medium was changed every 3 – 4 days.

At 85–95% confluence, the cells were harvested by trypsinisation with 0.05% trypsin-EDTA (GIBCO, Australia) and centrifuged. The cell suspensions were seeded at a density of 7×10⁵ cell/mL in a six-well plate in complete growth medium with 10% FBS and incubated overnight before treatment to allow for their adherence. The peptide treatment conditions of cell lines were performed as described below:

Incubation conditions to assess Akt expression levels: To assess the influence of treatment on Akt activity MM96L, COLO-16 and HDF cell lines were incubated with 400 ng/mL RRM-M or RRM-C for 3 h in complete growth medium with 10% FBS. The mouse melanoma B16F0 cell line was incubated with 800 ng/mL RRM-MV or RRM-C for 3 h to achieve cytotoxicity levels similar to those produced in the human skin cancer cell lines within the same period of incubation as this cell line was more resistant to RRM-MV treatment [43, 44].

Treatment with the PI3 Kinase inhibitor

The influence of the RRM-MV treatment on Akt activity, after blocking the Akt pathway, was assessed to confirm if treatment with inhibitors can affect the phosphorylation of Akt at Ser-473 or Thr-308 in the presence of RRM-MV. The effect of RRM-MV and RRM-C on Akt activity was assessed in melanoma, carcinoma and normal cell lines in the presence of the PI3 Kinase inhibitor, LY294002 which blocks the Akt pathway. The cell lines were incubated with 50-100 µM of LY294002 (PI3 Kinase inhibitor) for 1 h-2 h before the RRM-MV or the RRM-C peptides were added and then incubated for 3 h, as explained earlier. This experiment was performed in the presence of a complete growth medium with 10% FBS or in serum deprivation conditions to eliminate the effect of serum on the experimental conditions.

Furthermore, Akt expression levels in MM96L and COLO-16 cell lines, following treatment with 400 ng/mL RRM-MV, were assessed in serum starvation conditions for 15 min, 30 min and 60 min.

Protein extraction for immunoblotting

Following incubation with the RRM-designed peptides (RRM-MV or RRM-C) and/or the PI3 kinase inhibitor, the cells were rinsed twice with ice-cold phosphate buffered saline (PBS) and were then lysed by PhosphoSafe Extraction Buffer (Novagen, USA) mixed with Protease Inhibitor Cocktails (Sigma-Aldrich, USA). The cells were incubated for 10 min at room temperature and were scraped and centrifuged at 16,000x g for 5 min at 4°C. The supernatants were collected and the whole-cell lysates and protein concentration of each sample was determined by Bradford method [51] using bovine serum albumin (BSA) as a standard.

Antibodies and reagents

Total Akt protein, threonine-phosphorylated Akt and serine-phosphorylated Akt were detected using rabbit polyclonal Akt (pan) (C67E7) antibody, rabbit monoclonal phospho-Akt (Thr-308) (C31E5E) antibody and rabbit monoclonal phospho-Akt (Ser-473) (D9E) XP antibody respectively. The β-actin antibody was used as a loading control. All primary antibodies and the PI3K-AKT kinase inhibitor (LY294002) were obtained from Cell Signaling Technology (Beverly MA, USA). The alkaline phosphatase-conjugated goat anti-rabbit polyclonal secondary antibody was purchased from Sapphire Bioscience, Australia.

Western blot analysis

Whole cell lysates were mixed with 5X SDS-PAGE sample buffer (3: 1), consisting of 60 mM Tris, pH 6.8, 25% glycerol, 2% sodium dodecyl sulfate (SDS), 14.4 mM 2-mercaptoethanol, and 0.1% bromophenol blue, and were boiled for 5 min. Equal amounts of protein samples (30µg per lane) were subjected to 12.5% SDS-polyacrylamide gel electrophoresis (SDS-PAGE) using Mini-PROTEAN Tetra Cell electrophoresis system (Bio-Rad, USA). iBlot Dry Blotting System (Invitrogen, USA) was used to transfer the protein from the SDS PAGE gel to the nitrocellulose membrane. Western blot analysis was carried out as described previously [43] with some modifications. In brief, the membranes were blocked with 5% non-fat dry milk in PBS-T (0.1% Tween 20 in PBS) overnight at 4°C. The membranes were then washed four times for 10 min with PBS-T, followed by incubation of the membranes with the primary antibody in (1X Tris Buffered Saline (TBS), 0.1% Tween-20 with 5% BSA) at 1: 3000 dilutions for 3 h, and washed four times for 15 min. The membranes were then incubated with the secondary antibody conjugated with Horseradish Peroxidase in (1X TBS, 0.1% Tween-20 with 0.1% non-fat dry milk) at 1: 1000 dilutions for 1h at room temperature. After washing with PBS-T four times for 15 min, detection of protein was performed using 5-Bromo-4-chloro-3-indolyl phosphate, toluidine salt / Nitro blue tetrazolium chloride (BCIP/NBT) substrate solution (Amresco, USA) mixed with detection buffer (100mM Tris, 100Mm NaCl, pH 9.5) (v/v). The membranes were incubated with the substrate until full color development was detected. The reaction was stopped by washing in distilled water for 5 min prior to being dried. The membranes were scanned to quantitate the signal using a flatbed optical scanner (Cannon, USA). Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. Each experiment was repeated at least three times and the mean of the density of the bands (densitometry signals) was used to plot the graphs in the figures.

Results

The influence of RRM-MV treatment on Akt activity

To determine whether RRM-MV or RRM-C treatments modulate Akt activity in skin cancer cells and normal skin cells, the total Akt protein levels and the endogenous phosphorylated Akt levels at Thr-308 and Ser-473 were measured using Western blots. Results are presented and described in details below.

In presence or absence of serum in the growth medium: The levels of p-Akt and total Akt proteins were detected in 10% serum (FBS) or in serum starvation in MM96L human melanoma cells (Fig 1 A & B), COLO-16 human carcinoma cells (Figure. 2, A & B) and in B16F0 mouse melanoma cells (Figure3, A & B) following RRM-MV or RRM-C treatment. In MM96L cell line, the 60 kDa p-Akt bands’ intensity for Ser-473 antibodies was slightly stronger than for Thr-308 (Figure 1A) under 10% FBS growth conditions. Similarly, p-Akt band intensities were slightly stronger for Ser-473 in COLO-16 cell line under 10% FBS (Figure 2A). Although the expression levels of p-Akt (Ser-473) were slightly increased, following RRM-MV treatment in melanoma and carcinoma cell lines, the results also suggest that the expression levels of total Akt and p-Akt at Ser-473 and Thr-308 phosphorylation locations in serum starved or in complete growth medium were unaffected in the MM96L melanoma cells or the COLO 16 carcinoma cells. Interestingly, RRM-C treatment did not induce any noticeable effect on the p-Akt and total Akt protein expression levels as those remained unchanged in the MM96L cell line (Figures 1A and B, lane 2), COLO-16 cell line (Figures 2A and B, lane 3), and B16F0 cell line (Figure 3, lane 3); thus strongly indicating that the RRM-C treatment has no effect on the Akt expression in these cancer cell lines. We have previously reported that RRM-C control peptide did not cause any cytotoxic effect as opposed to the cytotoxicity induced by RRM-MV treatment on the tested skin cancer cell lines [43; 44]. The Akt expression results could be a reflection of this effect on this cell death pathway.

Figure 1. The effects of RRM designed peptides on cellular expression of Akt in melanoma cells. The MM96L cell line was plated at 5 × 10⁷ cells/mL and was treated in presence of serum (A) or in absence of serum (B). Cell lysates (20µg) were prepared and immunoblotted using p- Akt (Ser-473 and Thr-308) and total Akt antibodies. β-actin was used as a loading control. The Western blots results show that treatment with RRM-MV, but not RRM-C, slightly induces the levels of p-Akt in both conditions. Inhibition of Akt activity and then treatment with RRM-MV also affected the expression of p-Akt protein in tested cells. Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. These figures are representative of three separate Western blot experiments.

Figure 2. Cellular expression of p-Akt and total Akt in carcinoma cells after treatment with the RRM designed peptides. The COLO-16 cell line was plated at 5 × 10⁷ cells/mL and was treated in growth medium with serum (A) or in serum starvation conditions (B). Western blot analysis was used to assess the expression of Akt in treated cells using p-Akt (Ser-473 and Thr-308) and total Akt antibodies. β-actin was used as a loading control. The Western blot results show that the expressions of p-Akt in carcinoma cells slightly increased after RRM-MV treatment. Inhibition of Akt activity and then treatment with RRM-MV also affected the expression of p-Akt protein in tested cells. Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. The experiments were repeated at least three times.

Figure 3. Cellular expression of p-Akt and total Akt in mouse melanoma cells after treatment with the RRM-designed peptides. The B16F0 cell line was treated with 800 ng/mL RRM-MV or RRM-C in the presence or absence of 50 µM LY294002 or treated with 50 µM LY294002 alone for 1 h. The levels of p-Akt expression in the cells were detected by immunoblotting using p-Akt (Ser-473 and Thr-308) and total Akt antibodies. β-actin was used as a loading control. The results of Western blots show that the levels of p-Akt and total Akt in mouse skin cells were not affected by RRM-MV treatment. Inhibition of Akt activity and then treatment with RRM-MV also did not affect expression of p-Akt protein in tested cells. Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. The experiments were performed at least three times.

In normal skin cells: The levels of total Akt protein and p-Akt in the normal non-cancerous HDF cell line were detected after treatment with RRM-MV or RRM-C at the concentration of 400 ng/mL (Figure 4). There were no noticeable changes in the expression of total Akt and p-Akt following RRM-MV treatment when compared to RRM-C treated and untreated cells (Figure 3, lane 2 and 3, respectively). This result suggests that RRM-MV treatment in normal human skin cells did not have any effect on the Akt pathway. As the RRM-MV treatment had no cytotoxic effect on HDF cells [44], no change in the Akt expression levels could be attributed to the finding that RRM- MV has not shown to cause any cytotoxic effects on normal skin cells including HDF.

Figure 4. Cellular expression of p-Akt and total Akt in normal human dermal fibroblast cell line treated with the RRM designed peptides. The HDF cell line was treated with 400 ng/mL RRM-MV or RRM-C in the presence or absence of 100 µM LY294002, or treated with 100 µM LY294002 alone for 2 h. Cell lysates were prepared and immunoblotted using p-Akt (Ser-473) and total Akt antibodies. β-actin was used as a loading control. The figure shows RRM-MV treatment did not affect the expression of p-Akt or total Akt in normal human skin cells. Inhibition of Akt activity and then treatment with RRM-MV also had no effect on the expression of p-Akt protein in tested cells. Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. The blots are derived from multiple immunoblotting experiments.

The influence of PI3K Akt inhibitors on Akt activity

Furthermore, to confirm that Akt phosphorylation can be blocked by the PI3K/Akt inhibitor (LY294002) in the previously tested cell lines, cancer and normal skin cells were treated with LY294002 in the presence or absence of the RRM peptides (Figures 1-4). The results showed that incubation of MM96L cell line with 100 µM LY294002 for 1 h blocked Akt phosphorylation either under conditions of complete growth medium or serum starvation compared to untreated cells (Figure 1A and 1B, lane 8). Similar results were observed in B16F0 cell line after treatment with 50 µM of LY294002 for 1 h (Figure 3, lane 8). Nevertheless, the blocking was incomplete at Ser-473 and Thr-308 in COLO-16 cell line in growth medium with serum (Figure 2A, lane 8), yet a complete blocking in phosphorylation of Akt was observed with serum starvation (Figure 2B, lane 8), suggesting that blocking of Akt activation in carcinoma cells was affected by serum conditions. Yet in the HDF normal cell line, treatment with 50 µM LY294002 for 1 h was not sufficient to block the p-Akt pathway (data not shown), therefore, incubation with 100 µM of LY294002 for 2 h was needed to block the Akt phosphorylation (Figure 4). On the other hand, LY294002 treatment did not appear to significantly affect the total Akt expression levels in all tested cell lines.

The influence of RRM-MV treatment on Akt activity in presence of PI3K/Akt inhibitor

To determine whether PI3K Akt inhibitor would suppress Akt activity in the presence of RRM- MV under complete growth medium or serum starvation conditions, cells were treated with LY294002. The cells were then further incubated with RRM-MV and whole cell lysates were immunoblotted with the specific antibodies. The obtained results are shown below.

In skin cancer cells: The MM96L and COLO-16 cell lines were incubated with 100 µM LY294002 for 1 h and then further incubated with 400 ng/mL RRM-MV for 3 h. The Western blot results showed that Akt becomes activated at Ser-473 after RRM-MV treatment in MM96L cells but no p-Akt band was detected at Thr-308 under complete growth medium conditions (Figure 1A, lane 5). Moreover, similar results were found with cells incubated under serum starvation conditions (Figure 1B, lane 5). When Akt activation was blocked in the COLO-16 cell line and then treated with RRM- MV, p-Akt activation was restored at both Ser-473 and Thr-308 under complete growth medium (Figure 2A, lane 5) and under serum starvation conditions (Figure 2B, lane 5). Similar results were obtained with B16F0 cell line treated with 50 µM LY294002 for 1 h and then further incubated with 800 ng/mL RRM-MV for 3 h (Figure 3, lane 5). However, inhibition of Akt phosphorylation followed by treatment with RRM-MV did not have an effect on the expression of total Akt protein in these skin cancer cell lines. The findings of this experiment suggest that LY294002 was not able to block Akt phosphorylation in the presence of RRM-MV in all tested cancer cell lines; thus, confirming RRM-MV treatment interferes with inhibition of Akt signaling pathway.

In normal skin cells: The HDF cell line was incubated with 100 µM of LY294002 for 2 h and then further incubated with 400 ng/mL RRM-MV for 3 h. The Western blot results showed that RRM-MV treatment did not restore p-Akt activation after inhibition with LY294002 (Figure 3, lane 5). This data demonstrate that RRM-MV does not interfere with the p-Akt pathway in normal cells and was unable to restore Akt phosphorylation after inhibition with LY294002.

The influence of different incubation times on Akt expression in cancer cells after RRM- MV treatment

In our previous studies we concluded that the cytotoxic effects of RRM-MV on cancer cells are time- and dose-dependent [43; 44]. To evaluate if time can influence the Akt phosphorylation pathway after RRM-MV treatment leading to cell death in MM96L and COLO-16, p-Akt expression levels were assessed when cancer cells were incubated with 200 ng/mL of RRM-MV for 15 min, 30 min and 60 min under serum starvation conditions. Western blots results showed that in MM96L cell line, the p-Akt S-473 expression was unaffected after 15 min of treatment (Figure 5A, lane 2), but it at was slightly enhanced at 30 min and 60 min (Figure 5A, lane 4 and 6, respectively). As expected, the total Akt expression did not seem to be affected during different incubation times (Figure 5A). Similarly, RRM-MV treatment in COLO-16 did not affect the p-Akt protein levels (Thr-308 and Ser-473) after 15 min (Figure 5B, lane 2); however, phosphorylated Akt was increased slightly at both Thr-308 and Ser-473 after 30 min and 60 min (Figure 5B, lane 4 and 6) respectively. The intensity of total Akt band was unaffected during times course (Figure 5B). These findings indicate that RRM-MV treatment enhanced Akt phosphorylation in a time-dependent manner in melanoma and carcinoma cells.

Figure 5. Akt expression levels in melanoma and carcinoma cells during the first hour after RRM-MV treatment. MM96L cell line in (A) and COLO-16 cell line in (B) were treated with 400 ng/mL with RRM-MV for 15 min, 30 min and 60 min. Whole cells extracts were prepared and immunoblotted using p-Akt (Ser-473 and Thr-308) and total Akt antibodies. β-actin was used as a loading control. Western blots show that treatment with RRM-MV induced the levels of p-Akt in a time dependent manner in melanoma and carcinoma cells. Densitometry of protein spot signals were detected and quantified with the Quantity One Analysis 4.3.0 software. The experiments were repeated at least three times.

Discussion

Akt, also known as protein kinase B (PKB), plays a crucial role in the regulation of multiple cellular processes including programmed cell death and it is believed that the regulation of Akt activation is impaired in cancer cells [26]. It was previously shown that M-T5 of myxoma virus binds to p-Akt to regulate Akt signaling in some infected human cancer cells and pharmacological manipulation of AKT phosphorylation, significantly increased MYXV replication in some semipermissive/nonpermissive human cancer cells [26]. It was previously found that RRM-MV, the peptide analogue of the MYXV M-T5 protein, is able to induce apoptotic/ necrotic effects in different skin cancer cell lines but produced no cytotoxic effects on normal non-cancerous cells [43, 44]. In the current study, we investigated the influence of RRM-MV and RRM-C synthetic peptides, on the Akt activation pathway in treated skin cancer cells and in normal skin cells to detect a possible cell death pathway.

One of the findings of the present study is that the expression levels of total Akt protein in all types of tested cells were not affected by the RRM-MV treatment. In addition, a higher level of phosphorylated Akt was detected in RRM-MV treated B16F0 cells, than the p-Akt levels expressed by MM96L and COLO-16 cells at both Ser-473 and Thr-308. This result corroborates with the previous studies [24, 25] indicating that infected MYXV cancer cells expressed measurable phosphorylated Akt levels either high, low or very low levels but some cancer cells did not express any levels of p-Akt. As an example, melanoma (SK-MEL5) cell line expressed total Akt protein but did not express p-Akt (both Ser-473 and Thr-308) [26]. Another example of high levels of Akt is in B16F10 cell line, which correlates with permissiveness to MV [55].

The Western blot results also showed that p-Akt expression was slightly higher at Ser-473 following the RRM-MV treatment, suggesting that RRM-MV may interact with the Ser-473 component of the Akt [56-59]. The RRM-MV treatment did not produce an effect on p-Akt activation in B16F0 cells confirming our previous observations [43].

Our study also showed that different incubation times affected Akt expression in melanoma and carcinoma cells after the RRM-MV treatment. The band’s intensity of p-Akt was unchanged at 15 min of incubation time with RRM-MV while it started to increase after 30 min and 60 min. However, there was no change in the intensity of total Akt band detected during the course of treatment, indicating that Akt phosphorylation was induced by RRM-MV treatment in a time- dependent manner in both melanoma and carcinoma cells. It has been demonstrated that exposure of cells to various chemotherapies and cytotoxic agents leads to changes in the p-Akt expression [60-62] and this also could be the case in RRM-MV treatment. Wang et al. [26] reported that the Akt phosphorylation in MYXV infected permissive cancer cells can be activated by forming a complex between M-T5 and Akt molecule. .

LY294002, which is a potent and specific inhibitor of PI3K that can blocks downstream pathways of PI3K including Akt activation [63-65], blocked p-Akt in tested melanoma and carcinoma cells but it was less effective in normal human skin cells as higher doses and longer incubation time were needed to induce a partial blockage. Also LY294002 was unable to block the total Akt protein levels in all tested cell lines.

We also found that LY294002 did not suppress Akt activity in the presence of RRM-MV in melanoma and carcinoma cells. This result suggests that PI3K kinase inhibitor is unable to block Akt activation following RRM-MV treatment; thus, it is suggested that the RRM-MV has a unique capacity to modulate Akt activation either directly at the Akt level or down-stream the inhibitor binding site in the PI3K pathway [66]. This finding indicated that RRM-MV is able to specifically interact with Akt and that this (RRM-MV-Akt) interaction is required for enhancement of the Akt activation. The findings are in agreement with previous studies by Dhawan et al., [67] and Wang et al., [26] who reported that MYXV infection leads to an increased Akt activation in the presence of LY294002. Hence, it can be concluded that RRM- MV treatment could activate Akt by the phosphorylation of the Ser-473 site. Further work will focus on binding of RRM-MV with tumor specific biomarkers to achieve targeted delivery.

List of abbreviations: B16F0, mouse skin melanoma cell line; COLO-16, human squamous cell carcinoma cell line; HDF, normal human dermal fibroblast cell line; MM96L, human malignant melanoma cell line; MYXV, myxoma virus.

Authors’ contribution: NMA performed experiments and wrote the first draft of the manuscript. TSI and EP designed the experiments and revised the manuscript.

Conflict Of Interest: The authors declare that they have no conflict of interest.

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