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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

OBJECTIVE: Technological advances in radiation therapy are evolving with the use of hadrons, such as protons, indicated for tumors where conventional radiotherapy does not give significant advantages or for tumors located in sensitive regions, which need the maximum of dose-saving of the surrounding healthy tissues. The genomic response to conventional and non conventional Linear Energy Transfer exposure is a poor investigated topic and became an issue of radiobiological interest. The aim of this work was to analyze and compare molecular responses in term of gene expression profiles, induced by electron and proton irradiation in breast cancer cell lines. METHODS: We studied the gene expression profiling differences by cDNA microarray activated in response to electron and proton irradiation with different Linear Energy Transfer values, among three breast cell lines (the tumorigenic MCF7 and MDA-MB-231 and the non tumorigenic MCF10A), exposed to the same sub-lethal dose of 9 Gy. RESULTS: Gene expression profiling pathway analyses showed the activation of different signaling and molecular networks in a cell line and radiation type-dependent manner. MCF10A and MDA-MB-231 cell lines were found to induce factors and pathways involved in the immunological process control. CONCLUSIONS: Here we describe in a detailed way the gene expression profiling and pathways activated after electron and proton irradiation in breast cancer cells. Summarizing, although specific pathways are activated in a radiation type-dependent manner, each cell line activates overall similar molecular networks in response to both these two types of ionizing radiation. Advances in knowledge: In the era of personalized medicine and breast cancer target-directed intervention, we trust that this study could drive radiation therapy towards personalized treatments, evaluating possible combined treatments, based on the molecular characterization.

CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) was the first Italian protontherapy facility dedicated to the treatment of ocular neoplastic pathologies. It is in operation at the LNS Laboratories of the Italian Institute for Nuclear Physics (INFN-LNS) and to date, 500 patients have been successfully treated. Even though proton therapy has demonstrated success in clinical settings, there is still a need for more accurate models because they are crucial for the estimation of clinically relevant RBE values. Since RBE can vary depending on several physical and biological parameters, there is a clear need for more experimental data to generate predictions. Establishing a database of cell survival experiments is therefore useful to accurately predict the effects of irradiations on both cancerous and normal tissue. The main aim of this work was to compare RBE values obtained from in-vitro experimental data with predictions made by the LEM II (Local Effect Model), Monte Carlo approaches, and semi-empirical models based on LET experimental measurements. For this purpose, the 92.1 uveal melanoma and ARPE-19 cells derived from normal retinal pigmented epithelium were selected and irradiated in the middle of clinical SOBP of the CATANA proton therapy facility. The remarkable results show the potentiality of using microdosimetric spectrum, Monte Carlo simulations and LEM model to predict not only the RBE but also the survival curves.

BackgroundPositron Emission Tomography (PET) is increasingly utilized in radiomics studies for treatment evaluation purposes. Nevertheless, lesion volume identification in PET images is a critical and still challenging step in the process of radiomics, due to the low spatial resolution and high noise level of PET images. Currently, the biological target volume (BTV) is manually contoured by nuclear physicians, with a time expensive and operator-dependent procedure.This study aims to obtain BTVs from cerebral metastases in patients who underwent L-[11C]methionine (11C-MET) PET, using a fully automatic procedure and to use these BTVs to extract radiomics features to stratify between patients who respond to treatment or not. For these purposes, 31 brain metastases, for predictive evaluation, and 25 ones, for follow-up evaluation after treatment, were delineated using the proposed method. Successively, 11C-MET PET studies and related volumetric segmentations were used to extract 108 features to investigate the potential application of radiomics analysis in patients with brain metastases. A novel statistical system has been implemented for feature reduction and selection, while discriminant analysis was used as a method for feature classification.ResultsFor predictive evaluation, 3 features (asphericity, low-intensity run emphasis, and complexity) were able to discriminate between responder and non-responder patients, after feature reduction and selection. Best performance in patient discrimination was obtained using the combination of the three selected features (sensitivity 81.23%, specificity 73.97%, and accuracy 78.27%) compared to the use of all features. Secondly, for follow-up evaluation, 8 features (SUVmean, SULpeak, SUVmin, SULpeakprod-surface-area, SUVmeanprod-sphericity, surface mean SUV 3, SULpeakprod-sphericity, and second angular moment) were selected with optimal performance in discriminant analysis classification (sensitivity 86.28%, specificity 87.75%, and accuracy 86.57%) outperforming the use of all features.ConclusionsThe proposed system is able i) to extract 108 features for each automatically segmented lesion and ii) to select a sub-panel of 11C-MET PET features (3 and 8 in the case of predictive and follow-up evaluation), with valuable association with patient outcome. We believe that our model can be useful to improve treatment response and prognosis evaluation, potentially allowing the personalization of cancer treatment plans.

Background: There is extensive scientific evidence that radiation therapy (RT) is a crucial treatment, either alone or in combination with other treatment modalities, for many types of cancer, including breast cancer (BC). BC is a heterogeneous disease at both clinical and molecular levels, presenting distinct subtypes linked to the hormone receptor (HR) status and associated with different clinical outcomes. The aim of this study was to assess the molecular changes induced by high doses of ionizing radiation (IR) on immortalized and primary BC cell lines grouped according to Human epidermal growth factor receptor (HER2), estrogen, and progesterone receptors, to study how HR status influences the radiation response. Our genomic approach using in vitro and ex-vivo models (e.g., primary cells) is a necessary first step for a translational study to describe the common driven radio-resistance features associated with HR status. This information will eventually allow clinicians to prescribe more personalized total doses or associated targeted therapies for specific tumor subtypes, thus enhancing cancer radio-sensitivity. Methods: Nontumorigenic (MCF10A) and BC (MCF7 and MDA-MB-231) immortalized cell lines, as well as healthy (HMEC) and BC (BCpc7 and BCpcEMT) primary cultures, were divided into low grade, high grade, and healthy groups according to their HR status. At 24 h post-treatment, the gene expression profiles induced by two doses of IR treatment with 9 and 23 Gy were analyzed by cDNA microarray technology to select and compare the differential gene and pathway expressions among the experimental groups. Results: We present a descriptive report of the substantial alterations in gene expression levels and pathways after IR treatment in both immortalized and primary cell cultures. Overall, the IR-induced gene expression profiles and pathways appear to be cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to HR status. Conclusions: Genomic biomarkers and gene-signatures of specific tumor subtypes, selected according to their HR status and molecular features, could facilitate personalized biological-driven RT treatment planning alone and in combination with targeted therapies.

The goal of radiation therapy (RT) is to deliver the therapeutic dose to target tissues minimizing the risks of normal tissue complication. Nowadays, technological advances in radiation delivery and the introduction of particle therapies have strongly limited the amount of dose distributed to normal tissues and enhanced the tumor killing capacity. Here, we discuss about the state of art in RT treatment modalities, tumor sensitivity and radiation toxicity. A special insight is dedicated to the role of tumor heterogeneity, cancer stem cells (CSCs) and hypoxia. In addition, in this review we provide an overview of the most recently studies evaluating the potential role of “omic” biomarkers for a personalized biological-driven treatment planning, useful to maximize the radiotherapy success without normal tissues complications.

Aim of this work is the study of the preliminary steps to perform a particle treatment of cancer cells inoculated in small animals and to realize a preclinical hadrontherapy facility. A well-defined dosimetric protocol was developed to explicate the steps needed in order to perform a precise proton irradiation in small animals and achieve a highly conformal dose into the target. A precise homemade positioning and holding system for small animals was designed and developed at INFN-LNS in Catania (Italy), where an accurate Monte Carlo simulation was developed, using Geant4 code to simulate the treatment in order to choose the best animal position and perform accurately all the necessary dosimetric evaluations. The Geant4 application can also be used to realize dosimetric studies and its peculiarity consists in the possibility to introduce the real target composition in the simulation using the DICOM micro-CT image. This application was fully validated comparing the results with the experimental measurements. The latter ones were performed at the CATANA (Centro di AdroTerapia e Applicazioni Nucleari Avanzate) facility at INFN-LNS by irradiating both PMMA and water solid phantom. Dosimetric measurements were performed using previously calibrated EBT3 Gafchromic films as a detector and the results were compared with the Geant4 simulation ones. In particular, two different types of dosimetric studies were performed: the first one involved irradiation of a phantom made up of water solid slabs where a layer of EBT3 was alternated with two different slabs in a sandwich configuration, in order to validate the dosimetric distribution. The second one involved irradiation of a PMMA phantom made up of a half hemisphere and some PMMA slabs in order to simulate a subcutaneous tumour configuration, normally used in preclinical studies. In order to evaluate the accordance between experimental and simulation results, two different statistical tests were made: Kolmogorov test and gamma index test. This work represents the first step towards the realization of a preclinical hadrontherapy facility at INFN-LNS in Catania for the future in vivo studies.

Purpose: Ionizing radiation (IR) treatment activates inflammatory processes causing the release of a great amount of molecules able to affect the cell survival. The aim of this study was to analyze the cytokine signature of conditioned medium produced by non-tumorigenic mammary epithelial cell line MCF10A, as well as MCF7 and MDA-MB-231 breast cancer cell lines, after single high doses of IR in order to understand their role in high radiation response. Materials and methods: We performed a cytokine profile of irradiated conditioned media of MCF10A, MCF7 and MDA-MB-231 cell lines treated with 9 or 23 Gy, by Luminex and ELISA analyses. Results: Overall, our results show that both 9 Gy and 23 Gy of IR induce the release within the first 72 h of cytokines and growth factors potentially able to influence the tumor outcome, with a dose-independent and cell-line dependent signature. Moreover, our results show that the cell-senescence phenomenon does not correlate with the amount of ‘senescence-associated secretory phenotype’ (SASP) molecules released in media. Thus, additional mechanisms are probably involved in this process. Conclusions: These data open the possibility to evaluate cytokine profile as useful marker in modulating the personalized radiotherapy in breast cancer care.

Background: Osteoarthritis (OA) is a degenerative joints disorder influenced by genetic predisposition. We reported that rs11718863 DVWA SNP was represented in Sicilian with a more severe Kellgren and Lawrence (KL) radiographic grade, displaying its predictive role as OA marker progression. Here, we describe the DVWA SNPs: rs11718863, rs7639618, rs7651842, rs7639807 and rs17040821 probably able to induce protein functional changes. Findings: Sixty-one Sicilian patients with knee OA and 100 healthy subjects were enrolled. Clinical and radiographic evaluation was performed using AKSS scores and KL. Linkage Disequilibrium (LD) analyses were performed in order to verify whether the SNPs segregate as haplotype. All DVWA SNPs'MinorAllele Frequencies (MAF) were greater than in the European. The rs7639618 SNP showed a statistical association with KL. Our analyses show that a LD exists among rs11718863 and rs7639618, as well as between rs7651842, rs7639807 and rs17040821 SNPs. We also observed that three out of the 161 individuals investigated were simultaneously homozygous carriers of the rs7651842, rs7639807 and rs17040821 MAF alleles. Conclusions: In summary, the purpose of this preliminary research was to highlight possible associations between DVWA SNPs and OA clinical and radiographic data. This work represents a multidisciplinary medicine approach to study OA where clinical, radiological and genetic evaluation could contribute to better define OA grading.

Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.

Brain-derived neurotrophic factor (BDNF) is a neurotrophin that influences neuronal plasticity throughout life. Emergence from a vegetative state (VS) after a traumatic brain injury (TBI) implies that the brain undergoes plastic changes. A common polymorphism in the BDNF gene—BDNF Val66Met (referred to herein as BDNFMet)—impairs cognitive function in healthy subjects. The aim of this study was to determine whether the BDNFMet polymorphism plays a role in the recovery of consciousness and cognitive functions in patients in a VS after a TBI. Fifty-three patients in a VS 1 month after a TBI were included in the study and genotyped for the BDNFMet polymorphism. Scores of levels of cognitive functioning (LCF) at 1, 3, 6, and 12 months post-TBI were retrospectively compared in patients without (Val group), and with (Met group), the BDNFMet polymorphism. The BDNFMet polymorphism was detected in 20 out of the 53 patients. The mean LCF scores in the Val and Met groups were 1.6 – 0.5 and 1.4 – 0.5 at 1 month, 2.3 – 0.7 and 2.5 – 1.2 at 3 months, 3.3 – 1.7 and 3.5 – 1.7 at 6 months, and 4 – 1.9 and 3.9 – 1.8 at 12 months, respectively ( p > 0.05). The percentages of patients in the Val and Met groups who emerged from the VS were 36.4% and 30% at 3 months, 66.3% and 70% at 6 months, and 70% and 87.5% at 12 months ( p > 0.05), respectively. These findings provide evidence that the BDNFMet polymorphism is not involved in cognitive improvement in patients with a VS following TBI. Future studies should focus on the role of other BDNF polymorphisms in the recovery from a VS.