Radiation-Induced Gene Expression Changes in High and Low Grade Breast Cancer Cell Types

Integrating biocomputational techniques for Breast cancer drug discovery via the HER-2, BCRA, VEGF and ER protein targets

Computational modelling remains an indispensable technique in drug discovery. With myriad of high computing resources, and improved modelling algorithms, there has been a high-speed in the drug development cycle with promising success rate compared to the traditional route. For example, lapatinib; a well-known anticancer drug with clinical applications was discovered with computational drug design techniques. Similarly, molecular modelling has been applied to various disease areas ranging from cancer to neurodegenerative diseases. The techniques ranges from high-throughput virtual screening, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) to molecular dynamics simulation. This review focuses on the application of computational modelling tools in the identification of drug candidates for Breast cancer. First, we begin with a succinct overview of molecular modelling in the drug discovery process. Next, we take note of special efforts on the developments and applications of combining these techniques with particular emphasis on possible breast cancer therapeutic targets such as estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), breast cancer gene 1 (BRCA1), and breast cancer gene 2 (BRCA2). Finally, we discussed the search for covalent inhibitors against these receptors using computational techniques, advances, pitfalls, possible solutions, and future perspectives.

Benzothiazole derivatives as p53-MDM2 inhibitors: in-silico design, ADMET predictions, molecular docking, MM-GBSA Assay, MD simulations studies

Breast cancer stands as the most prevalent malignancy among the female populace. One of the pivotal domains in the therapeutic landscape of breast cancer revolves around the precise targeting of the p53-MDM2 inhibitory pathway. The advent of p53-MDM2 inhibition in the context of developing treatments for breast cancer marks a significant stride. In the quest for enhancing the efficacy of p53-MDM2 inhibition against breast cancer, a new series of benzothiazole compounds (B1-B30) was designed through in-silico methodologies in the present work. Using Schrodinger Maestro, the compounds underwent molecular docking assessments against the p53-MDM2 target (PDB: 4OGT). Compared to reference compounds, B25 and B12 exhibited notably elevated glide scores. Extensive in-silico studies, including ADMET and toxicity evaluations, were performed to predict pharmacokinetics, drug likeness, and toxicity. All compounds adhered to Lipinski criteria, signifying favorable oral drug properties. The MM-GBSA analysis indicated consistent binding free energies. Molecular dynamics simulations for B25 over 200 ns assessed complex stability and interactions. In summary, these compounds exhibit potential for future cancer therapy medication development.Communicated by Ramaswamy H. Sarma.

Ionizing Radiation and Estrogen Affecting Growth Factor Genes in an Experimental Breast Cancer Model

Genes associated with growth factors were previously analyzed in a radiation- and estrogen-induced experimental breast cancer model. Such in vitro experimental breast cancer model was developed by exposure of the immortalized human breast epithelial cell line, MCF-10F, to low doses of high linear energy transfer (LET) α particle radiation (150 keV/μm) and subsequent growth in the presence or absence of 17β-estradiol. The MCF-10F cell line was analyzed in different stages of transformation after being irradiated with either a single 60 cGy dose or 60/60 cGy doses of alpha particles. In the present report, the profiling of differentially expressed genes associated with growth factors was analyzed in their relationship with clinical parameters. Thus, the results indicated that Fibroblast growth factor2 gene expression levels were higher in cells transformed by radiation or in the presence of ionizing radiation; whereas the fibroblast growth factor-binding protein 1gene expression was higher in the tumor cell line derived from this model. Such expressions were coincident with higher values in normal than malignant tissues and with estrogen receptor (ER) negative samples for both gene types. The results also showed that transforming growth factor alpha gene expression was higher in the tumor cell line than the tumorigenic A5 and the transformed A3 cell line, whereas the transforming growth factor beta receptor 3 gene expression was higher in A3 and A5 than in Tumor2 cell lines and the untreated controls and the E cell lines. Such gene expression was accompanied by results indicating negative and positive receptors for transforming growth factor alpha and the transforming growth factor beta receptor 3, respectively. Such expressions were low in malignant tissues when compared with benign ones. Furthermore, Fibroblast growth factor2, the fibroblast growth factor-binding protein 1, transforming growth factor alpha, the transforming growth factor beta receptor 3, and the insulin growth factor receptor gene expressions were found to be present in all BRCA patients that are BRCA-Basal, BRCA-LumA, and BRCA-LumB, except in BRCA-Her2 patients. The results also indicated that the insulin growth factor receptor gene expression was higher in the tumor cell line Tumor2 than in Alpha3 cells transformed by ionizing radiation only; then, the insulin growth factor receptor was higher in the A5 than E cell line. The insulin growth factor receptor gene expression was higher in breast cancer than in normal tissues in breast cancer patients. Furthermore, Fibroblast growth factor2, the fibroblast growth factor-binding protein 1, transforming growth factor alpha, the transforming growth factor beta receptor 3, and the insulin growth factor receptor gene expression levels were in stages 3 and 4 of breast cancer patients. It can be concluded that, by using gene technology and molecular information, it is possible to improve therapy and reduce the side effects of therapeutic radiation use. Knowing the different genes involved in breast cancer will make possible the improvement of clinical chemotherapy.

Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes

Breast cancer is a heterogeneous disease classified into four main subtypes with different clinical outcomes, such as patient survival, prognosis, and relapse. Current genetic tests for the differential diagnosis of BC subtypes showed a poor reproducibility. Therefore, an early and correct diagnosis of molecular subtypes is one of the challenges in the clinic. In the present study, we identified differentially expressed genes, long non-coding RNAs and RNA binding proteins for each BC subtype from a public dataset applying bioinformatics algorithms. In addition, we investigated their interactions and we proposed interacting biomarkers as potential signature specific for each BC subtype. We found a network of only 2 RBPs (RBM20 and PCDH20) and 2 genes (HOXB3 and RASSF7) for luminal A, a network of 21 RBPs and 53 genes for luminal B, a HER2-specific network of 14 RBPs and 30 genes, and a network of 54 RBPs and 302 genes for basal BC. We validated the signature considering their expression levels on an independent dataset evaluating their ability to classify the different molecular subtypes with a machine learning approach. Overall, we achieved good performances of classification with an accuracy >0.80. In addition, we found some interesting novel prognostic biomarkers such as RASSF7 for luminal A, DCTPP1 for luminal B, DHRS11, KLC3, NAGS, and TMEM98 for HER2, and ABHD14A and ADSSL1 for basal. The findings could provide preliminary evidence to identify putative new prognostic biomarkers and therapeutic targets for individual breast cancer subtypes.

Assays of genotoxic damage in peripheral blood lymphocytes of individuals occupationally exposed to different x-ray systems in hospital radiology departments

We obtained peripheral blood lymphocyte samples from individuals occupationally exposed to X-rays in hospital radiology departments that use different radiology systems: analog film (AF), computerized radiology (CR), or digital radiology (DR). The micronucleus test (MNT) and comet assay were performed on the samples. Micronucleus cell counts (means vs. controls, i.e., individuals not occupationally exposed to ionizing radiation) were as follows: AF, 1.96 ± 0.21 vs 1.2 ± 0.25; CR, 1.89 ± 0.15 vs 1.31 ± 0.36; and DR, 1.75 ± 0.11 vs 1.59 ± 0.32. For the comet assay, damage scores were as follows; AF, 0.84 ± 0.22 vs 0.47 ± 0.04; CR, 0.64 ± 0.26 vs 0.43 ± 0.04; and DR, 0.56 ± 0.19 vs 0.49 ± 0035. These findings were consistent with cytogenetic damage due to radiation exposure.

3D Breast Tumor Models for Radiobiology Applications

Breast cancer is a leading cause of cancer-associated death in women. The clinical management of breast cancers is normally carried out using a combination of chemotherapy, surgery and radiation therapy. The majority of research investigating breast cancer therapy until now has mainly utilized two-dimensional (2D) in vitro cultures or murine models of disease. However, there has been significant uptake of three-dimensional (3D) in vitro models by cancer researchers over the past decade, highlighting a complimentary model for studies of radiotherapy, especially in conjunction with chemotherapy. In this review, we underline the effects of radiation therapy on normal and malignant breast cells and tissues, and explore the emerging opportunities that pre-clinical 3D models offer in improving our understanding of this treatment modality.

Potential Role of Natural Products to Combat Radiotherapy and Their Future Perspectives

Cancer is the second leading cause of death in the world. Chemotherapy and radiotherapy (RT) are the common cancer treatments. In addition to these limitations, the development of adverse effects from chemotherapy and RT reduces the quality of life for cancer patients. Cellular radiosensitivity, or the ability to resist and overcome cell damage caused by ionizing radiation (IR), is directly related to cancer cells' response to RT. Therefore, radiobiological research is emphasizing chemical compounds 'radiosensitization of cancer cells so that they are more reactive in the IR spectrum. Recent years researchers have seen an increase in interest in natural products that have antitumor effects with minimal side effects. Natural products, on the other hand, are easy to recover and therefore less expensive. There have been several scientific studies done based on these compounds that have tested their ability in vitro and in vivo to induce tumor radiosensitization. The role of natural products in RT, as well as their usefulness and potential applications, is the goal of this current review.

Gene Signatures Induced by Ionizing Radiation as Prognostic Tools in an In Vitro Experimental Breast Cancer Model

Simple Summary

The present work analyzed the expression of genes involved in radiation, using an in vitro experimental breast cancer model developed by the combined treatment of low doses of high linear energy transfer (LET) radiation α particle radiation and estrogen yielding different stages in a malignantly transformed breast cancer cell model called Alpha model. Results showed important findings of genes involved in cancers of the breast, lung, and nervous system, and others. Most of those genes analyzed in these studies such as ATM, selenoproteins, GABA receptor, interleukins, epsin, and cathepsin inhibitors like stefins, and metallothioneins can be used for new prognostic tools and future therapies since they affect cancer progression and metastasis. In conclusion, gene signature demonstrated to be specific to cell line types, hence cell-dependency must be considered in future radiotherapy treatment planning since molecular and clinical features affect such results. Thus, using gene technology and molecular information is possible to improve therapies and reduction of side effects.

Abstract

This study aimed to analyze the expression of genes involved in radiation, using an Affymetrix system with an in vitro experimental breast cancer model developed by the combined treatment of low doses of high linear energy transfer (LET) radiation α particle radiation and estrogen yielding different stages in a malignantly transformed breast cancer cell model called Alpha model. Altered expression of different molecules was detected in the non-tumorigenic Alpha3, a malignant cell line transformed only by radiation and originally derived from the parental MCF-10F human cell line; that was compared with the Alpha 5 cell line, another cell line exposed to radiation and subsequently grown in the presence 17β-estradiol. This Alpha5, a tumorigenic cell line, originated the Tumor2 cell line. It can be summarized that the Alpha 3 cell line was characterized by greater gene expression of ATM and IL7R than control, Alpha5, and Tumor2 cell lines, it presented higher selenoprotein gene expression than control and Tumor2; epsin 3 gene expression was higher than control; stefin A gene expression was higher than Alpha5; and metallothionein was higher than control and Tumor2 cell line. Therefore, radiation, independently of estrogen, induced increased ATM, IL7R, selenoprotein, GABA receptor, epsin, stefin, and metallothioneins gene expression in comparison with the control. Results showed important findings of genes involved in cancers of the breast, lung, nervous system, and others. Most genes analyzed in these studies can be used for new prognostic tools and future therapies since they affect cancer progression and metastasis. Most of all, it was revealed that in the Alpha model, a breast cancer model developed by the authors, the cell line transformed only by radiation, independently of estrogen, was characterized by greater gene expression than other cell lines. Understanding the effect of radiotherapy in different cells will help us improve the clinical outcome of radiotherapies. Thus, gene signature has been demonstrated to be specific to tumor types, hence cell-dependency must be considered in future treatment planning. Molecular and clinical features affect the results of radiotherapy. Thus, using gene technology and molecular information is possible to improve therapies and reduction of side effects while providing new insights into breast cancer-related fields.

Radiobiological Studies of Microvascular Damage through In Vitro Models: A Methodological Perspective

Ionizing radiation (IR) is used in radiotherapy as a treatment to destroy cancer. Such treatment also affects other tissues, resulting in the so-called normal tissue complications. Endothelial cells (ECs) composing the microvasculature have essential roles in the microenvironment's homeostasis (ME). Thus, detrimental effects induced by irradiation on ECs can influence both the tumor and healthy tissue. In-vitro models can be advantageous to study these phenomena. In this systematic review, we analyzed in-vitro models of ECs subjected to IR. We highlighted the critical issues involved in the production, irradiation, and analysis of such radiobiological in-vitro models to study microvascular endothelial cells damage. For each step, we analyzed common methodologies and critical points required to obtain a reliable model. We identified the generation of a 3D environment for model production and the inclusion of heterogeneous cell populations for a reliable ME recapitulation. Additionally, we highlighted how essential information on the irradiation scheme, crucial to correlate better observed in vitro effects to the clinical scenario, are often neglected in the analyzed studies, limiting the translation of achieved results.

Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

A Meta-Analysis of the Effects of High-LET Ionizing Radiations in Human Gene Expression

The use of high linear energy transfer (LET) ionizing radiation (IR) is progressively being incorporated in radiation therapy due to its precise dose localization and high relative biological effectiveness. At the same time, these benefits of particle radiation become a high risk for astronauts in the case of inevitable cosmic radiation exposure. Nonetheless, DNA Damage Response (DDR) activated via complex DNA damage in healthy tissue, occurring from such types of radiation, may be instrumental in the induction of various chronic and late effects. An approach to elucidating the possible underlying mechanisms is studying alterations in gene expression. To this end, we identified differentially expressed genes (DEGs) in high Z and high energy (HZE) particle-, γ-ray- and X-ray-exposed healthy human tissues, utilizing microarray data available in public repositories. Differential gene expression analysis (DGEA) was conducted using the R programming language. Consequently, four separate meta-analyses were conducted, after DEG lists were grouped depending on radiation type, radiation dose and time of collection post-irradiation. To highlight the biological background of each meta-analysis group, functional enrichment analysis and biological network construction were conducted. For HZE particle exposure at 8–24 h post-irradiation, the most interesting finding is the variety of DNA repair mechanisms that were downregulated, a fact that is probably correlated with complex DNA damage formation. Simultaneously, after X-ray exposure during the same hours after irradiation, DNA repair mechanisms continue to take place. Finally, in a further comparison of low- and high-LET radiation effects, the most prominent result is that autophagy mechanisms seem to persist and that adaptive immune induction seems to be present. Such bioinformatics approaches may aid in obtaining an overview of the cellular response to high-LET particles. Understanding these response mechanisms can consequently aid in the development of countermeasures for future space missions and ameliorate heavy ion treatments.

A pilot radiogenomic study of DIPG reveals distinct subgroups with unique clinical trajectories and therapeutic targets

An adequate understanding of the relationships between radiographic and genomic features in diffuse intrinsic pontine glioma (DIPG) is essential, especially in the absence of universal biopsy, to further characterize the molecular heterogeneity of this disease and determine which patients are most likely to respond to biologically-driven therapies. Here, a radiogenomics analytic approach was applied to a cohort of 28 patients with DIPG. Tumor size and imaging characteristics from all available serial MRIs were evaluated by a neuro-radiologist, and patients were divided into three radiographic response groups (partial response [PR], stable disease [SD], progressive disease [PD]) based on MRI within 2 months of radiotherapy (RT) completion. Whole genome and RNA sequencing were performed on autopsy tumor specimens. We report several key, therapeutically-relevant findings: (1) Certain radiologic features on first and subsequent post-RT MRIs are associated with worse overall survival, including PD following irradiation as well as present, new, and/or increasing peripheral ring enhancement, necrosis, and diffusion restriction. (2) Upregulation of EMT-related genes and distant tumor spread at autopsy are observed in a subset of DIPG patients who exhibit poorer radiographic response to irradiation and/or higher likelihood of harboring H3F3A mutations, suggesting possible benefit of upfront craniospinal irradiation. (3) Additional genetic aberrations were identified, including DYNC1LI1 mutations in a subgroup of patients with PR on post-RT MRI; further investigation into potential roles in DIPG tumorigenesis and/or treatment sensitivity is necessary. (4) Whereas most DIPG tumors have an immunologically “cold” microenvironment, there appears to be a subset which harbor a more inflammatory genomic profile and/or higher mutational burden, with a trend toward improved overall survival and more favorable radiographic response to irradiation, in whom immunotherapy should be considered. This study has begun elucidating relationships between post-RT radiographic response with DIPG molecular profiles, revealing radiogenomically distinct subgroups with unique clinical trajectories and therapeutic targets.

Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models

Cancer heterogeneity represents the main issue for defining an effective treatment in clinical practice, and the scientific community is progressively moving towards the development of more personalized therapeutic regimens. Radiotherapy (RT) remains a fundamental therapeutic treatment used for many neoplastic diseases, including breast cancer (BC), where high variability at the clinical and molecular level is known. The aim of this work is to apply the generalized linear quadratic (LQ) model to customize the radiant treatment plan for BC, by extracting some characteristic parameters of intrinsic radiosensitivity that are not generic, but may be exclusive for each cell type. We tested the validity of the generalized LQ model and analyzed the local disease-free survival rate (LSR) for breast RT treatment by using four BC cell cultures (both primary and immortalized), irradiated with clinical X-ray beams. BC cells were chosen on the basis of their receptor profiles, in order to simulate a differential response to RT between triple negative breast and luminal adenocarcinomas. The MCF10A breast epithelial cell line was utilized as a healthy control. We show that an RT plan setup based only on α and β values could be limiting and misleading. Indeed, two other parameters, the doubling time and the clonogens number, are important to finely predict the tumor response to treatment. Our findings could be tested at a preclinical level to confirm their application as a variant of the classical LQ model, to create a more personalized approach for RT planning.

Integration of Molecular Docking and In Vitro Studies: A Powerful Approach for Drug Discovery in Breast Cancer

Molecular docking in the pharmaceutical industry is a powerful in silico approach for discovering novel therapies for unmet medical needs predicting drug–target interactions. It not only provides binding affinity between drugs and targets at the atomic level, but also elucidates the fundamental pharmacological properties of specific drugs. The purpose of this review was to illustrate newer and emergent uses of docking when combined with in vitro techniques for drug discovery in metastatic breast cancer. We grouped the selected articles into five main categories; namely, systematic repositioning of drugs, natural drugs, new synthesized molecules, combinations of drugs, and drug latentiation. We focused on new promising drugs that have a good affinity with their targets, thus inducing a favorable biological response. This review suggests that the integration of molecular docking and in vitro studies can accelerate cancer drug discovery showing a good consistency of the results between the two approaches.

Molecular Investigation on a Triple Negative Breast Cancer Xenograft Model Exposed to Proton Beams

Specific breast cancer (BC) subtypes are associated with bad prognoses due to the absence of successful treatment plans. The triple-negative breast cancer (TNBC) subtype, with estrogen (ER), progesterone (PR) and human epidermal growth factor-2 (HER2) negative receptor status, is a clinical challenge for oncologists, because of its aggressiveness and the absence of effective therapies. In addition, proton therapy (PT) represents an effective treatment against both inaccessible area located or conventional radiotherapy (RT)-resistant cancers, becoming a promising therapeutic choice for TNBC. Our study aimed to analyze the in vivo molecular response to PT and its efficacy in a MDA-MB-231 TNBC xenograft model. TNBC xenograft models were irradiated with 2, 6 and 9 Gy of PT. Gene expression profile (GEP) analyses and immunohistochemical assay (IHC) were performed to highlight specific pathways and key molecules involved in cell response to the radiation. GEP analysis revealed in depth the molecular response to PT, showing a considerable immune response, cell cycle and stem cell process regulation. Only the dose of 9 Gy shifted the balance toward pro-death signaling as a dose escalation which can be easily performed using proton beams, which permit targeting tumors while avoiding damage to the surrounding healthy tissue.

Differential miRNAs expression pattern of irradiated breast cancer cell lines is correlated with radiation sensitivity

Radiotherapy is a fundamental step in the treatment of breast cancer patients. The treatment efficiency is however reduced by the possible onset of radiation resistance. In order to develop the effective treatment approach, it is important to understand molecular basis of radiosensitivity in breast cancer. The purpose of the present study was to investigate different radiation response of breast cancer cell lines, and find out if this response may be related to change in the microRNAs expression profile. MDA-MB-231 and T47D cells were subjected to different doses of radiation, then MTT and clonogenic assays were performed to assess radiation sensitivity. Cytofluorometric and western blot analysis were performed to gain insight into cell cycle distribution and protein expression. MicroRNA sequencing and bioinformatics prediction methods were used to identify the difference in microRNAs expression between two breast cancer cells and the related genes and pathways. T47D cells were more sensitive to radiation respect to MDA-MB-231 cells as demonstrated by a remarkable G2 cell cycle arrest followed by a greater reduction in cell viability and colony forming ability. Accordingly, T47D cells showed higher increase in the phosphorylation of ATM, TP53 and CDK1 (markers of radiation response) and faster and more pronounced increase in RAD51 and γH2AX expression (markers of DNA damage), when compared to MDA-MB-231 cells. The two cell lines had different microRNAs expression profiles with a confirmed significant differential expression of miR-16-5p, which targets cell cycle related genes and predicts longer overall survival of breast cancer patients, as determined by bioinformatics analysis. These results suggest a possible role for miR-16-5p as radiation sensitizing microRNA and as prognostic/predictive biomarker in breast cancer.

In Silico Discovery of Candidate Drugs against Covid-19

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

Transcriptomic and proteomic approaches reveal biological basis of intraoperative radiotherapy-treated tumor bed modification in breast cancer patients: A pilot study

AIM

Intraoperative electron Radiotherapy, herein referred to, as IOeRT is a novel approach in breast cancer (BC) treatment. This study designed to investigate short-term molecular effects of 12Gy as Boost versus 21Gy as Radical dose of IOeRT using high throughput approaches.

MATERIALS AND METHODS

Six BC patients as a pilot study were treated with IOeRT following two separate strategies, including Boost and Radical doses. Approximately 100 mg of tumor bed tissue retrieved from each patient (before IOeRT,immediately, 24 h post-treatment). mRNA sequencing also Isobaric tag for relative and absolute quantitation (iTRAQ) were performed to study the transcriptome and proteome profile of IOeRT-treated tumor bed.

RESULTS

Using NGS, ~6 Giga base (GB) clean data per individual samples were generated. Moreover, by iTRAQ for proteome quantification, in total, 1,045,410 spectrums were generated, likewise 5860 proteins were identified (FDR <0.01).

CONCLUSION

Functional annotation and gene ontology (GO) indicated that significant enrichment in molecular pathways on BC treatment is somehow single high dose-independent. This means that, key molecular pathways in radiotherapy (RT) are equally enriched by both Boost and Radical doses. Generally, by modification of the Radical dose, with the same effectiveness, it is possible to reduce single high dose irradiation in BC.

Gene Expression Profiles Induced by High-dose Ionizing Radiation in MDA-MB-231 Triple-negative Breast Cancer Cell Line

BACKGROUND/AIM

Radiation therapy (RT) represents a therapeutic option in breast cancer (BC). Even if a great number of BC patients receive RT, not all of them report benefits, due to radioresistance that gets activated through several factors, such as the hormone receptor status. Herein, we analyzed the gene expression profiles (GEP) induced by RT in triple-negative BC (TNBC) MDA-MB-231, to study signalling networks involved in radioresistance.

MATERIALS AND METHODS

GEP of MDA-MB-231 BC cells treated with a high dose of radiation, went through cDNA microarray analysis. In addition, to examine the cellular effects induced by RT, analyses of morphology and clonogenic evaluation were also conducted.

RESULTS

A descriptive report of GEP and pathways induced by IR is reported from our microarray data. Moreover, the MDA-MB-231 Radioresistent Cell Fraction (RCF) selected, included specific molecules able to drive radioresistance.

CONCLUSION

In summary, our data highlight, the RT response of TNBC MDA-MB-231 cell line at a transcriptional level, in terms of activating radioresistance in these cells, as a model of late-stage BC.

Nutraceutical Compounds as Sensitizers for Cancer Treatment in Radiation Therapy

The improvement of diagnostic techniques and the efficacy of new therapies in clinical practice have allowed cancer patients to reach a higher chance to be cured together with a better quality of life. However, tumors still represent the second leading cause of death worldwide. On the contrary, chemotherapy and radiotherapy (RT) still lack treatment plans which take into account the biological features of tumors and depend on this for their response to treatment. Tumor cells' response to RT is strictly-connected to their radiosensitivity, namely, their ability to resist and to overcome cell damage induced by ionizing radiation (IR). For this reason, radiobiological research is focusing on the ability of chemical compounds to radiosensitize cancer cells so to make them more responsive to IR. In recent years, the interests of researchers have been focused on natural compounds that show antitumoral effects with limited collateral issues. Moreover, nutraceuticals are easy to recover and are thus less expensive. On these bases, several scientific projects have aimed to test also their ability to induce tumor radiosensitization both in vitro and in vivo. The goal of this review is to describe what is known about the role of nutraceuticals in radiotherapy, their use and their potential application.

Proton Therapy and Src Family Kinase Inhibitor Combined Treatments on U87 Human Glioblastoma Multiforme Cell Line

Glioblastoma Multiforme (GBM) is the most common of malignant gliomas in adults with an exiguous life expectancy. Standard treatments are not curative and the resistance to both chemotherapy and conventional radiotherapy (RT) plans is the main cause of GBM care failures. Proton therapy (PT) shows a ballistic precision and a higher dose conformity than conventional RT. In this study we investigated the radiosensitive effects of a new targeted compound, SRC inhibitor, named Si306, in combination with PT on the U87 glioblastoma cell line. Clonogenic survival assay, dose modifying factor calculation and linear-quadratic model were performed to evaluate radiosensitizing effects mediated by combination of the Si306 with PT. Gene expression profiling by microarray was also conducted after PT treatments alone or combined, to identify gene signatures as biomarkers of response to treatments. Our results indicate that the Si306 compound exhibits a radiosensitizing action on the U87 cells causing a synergic cytotoxic effect with PT. In addition, microarray data confirm the SRC role as the main Si306 target and highlights new genes modulated by the combined action of Si306 and PT. We suggest, the Si306 as a new candidate to treat GBM in combination with PT, overcoming resistance to conventional treatments.

Proton-irradiated breast cells: molecular points of view

Breast cancer (BC) is the most common cancer in women, highly heterogeneous at both the clinical and molecular level. Radiation therapy (RT) represents an efficient modality to treat localized tumor in BC care, although the choice of a unique treatment plan for all BC patients, including RT, may not be the best option. Technological advances in RT are evolving with the use of charged particle beams (i.e. protons) which, due to a more localized delivery of the radiation dose, reduce the dose administered to the heart compared with conventional RT. However, few data regarding proton-induced molecular changes are currently available. The aim of this study was to investigate and describe the production of immunological molecules and gene expression profiles induced by proton irradiation. We performed Luminex assay and cDNA microarray analyses to study the biological processes activated following irradiation with proton beams, both in the non-tumorigenic MCF10A cell line and in two tumorigenic BC cell lines, MCF7 and MDA-MB-231. The immunological signatures were dose dependent in MCF10A and MCF7 cell lines, whereas MDA-MB-231 cells show a strong pro-inflammatory profile regardless of the dose delivered. Clonogenic assay revealed different surviving fractions according to the breast cell lines analyzed. We found the involvement of genes related to cell response to proton irradiation and reported specific cell line- and dose-dependent gene signatures, able to drive cell fate after radiation exposure. Our data could represent a useful tool to better understand the molecular mechanisms elicited by proton irradiation and to predict treatment outcome.