The "digital biopsy" in non-small cell lung cancer (NSCLC): a pilot study to predict the PD-L1 status from radiomics features of [18F]FDG PET/CT.

PURPOSE: The present pilot study investigates the putative role of radiomics from [18F]FDG PET/CT scans to predict PD-L1 expression status in non-small cell lung cancer (NSCLC) patients. METHODS: In a retrospective cohort of 265 patients with biopsy-proven NSCLC, 86 with available PD-L1 immunohistochemical (IHC) assessment and [18F]FDG PET/CT scans have been selected to find putative metabolic markers that predict PD-L1 status (< 1%, 1-49%, and ≥ 50% as per tumor proportion score, clone 22C3). Metabolic parameters have been extracted from three different PET/CT scanners (Discovery 600, Discovery IQ, and Discovery MI) and radiomics features were computed with IBSI compliant algorithms on the original image and on images filtered with LLL and HHH coif1 wavelet, obtaining 527 features per tumor. Univariate and multivariate analysis have been performed to compare PD-L1 expression status and selected radiomic features. RESULTS: Of the 86 analyzed cases, 46 (53%) were negative for PD-L1 IHC, 13 (15%) showed low PD-L1 expression (1-49%), and 27 (31%) were strong expressors (≥ 50%). Maximum standardized uptake value (SUVmax) demonstrated a significant ability to discriminate strong expressor cases at univariate analysis (p = 0.032), but failed to discriminate PD-L1 positive patients (PD-L1 ≥ 1%). Three radiomics features appeared the ablest to discriminate strong expressors: (1) a feature representing the average high frequency lesion content in a spherical VOI (p = 0.009); (2) a feature assessing the correlation between adjacent voxels on the high frequency lesion content (p = 0.004); (3) a feature that emphasizes the presence of small zones with similar grey levels inside the lesion (p = 0.003). The tri-variate linear discriminant model combining the three features achieved a sensitivity of 81% and a specificity of 82% in the test. The ability of radiomics to predict PD-L1 positive patients was instead scarce. CONCLUSIONS: Our data indicate a possible role of the [18F]FDG PET radiomics in predicting strong PD-L1 expression; these preliminary data need to be confirmed on larger or single-scanner series.

Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia.

We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.

Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.

BACKGROUND: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy. METHODS: We used for training and validation an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals (Centres 1 and 2). We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as the reference standard. RESULTS: At 10-fold cross-validation, our deep learning model classified COVID-19 and non-COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74-0.81), 0.82 specificity (95% CI 0.78-0.85), and 0.89 area under the curve (AUC) (95% CI 0.86-0.91). For the independent dataset, deep learning showed 0.80 sensitivity (95% CI 0.72-0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73-0.87), and 0.81 AUC (95% CI 0.73-0.87). Radiologists' reading obtained 0.63 sensitivity (95% CI 0.52-0.74) and 0.78 specificity (95% CI 0.61-0.90) in Centre 1 and 0.64 sensitivity (95% CI 0.52-0.74) and 0.86 specificity (95% CI 0.71-0.95) in Centre 2. CONCLUSIONS: This preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of deep learning for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.

Methotrexate inhibits SARS-CoV-2 virus replication "in vitro".

In early 2020 the new respiratory syndrome COVID-19 (caused by the zoonotic SARS-CoV-2 virus) spread like a pandemic, starting from Wuhan, China, causing severe economic depression. Despite some advances in drug treatments of medical complications in the later stages of the disease, the pandemic's death toll is tragic, as no vaccine or specific antiviral treatment is currently available. By using a systems approach, we identify the host-encoded pathway, which provides ribonucleotides to viral RNA synthesis, as a possible target. We show that methotrexate, an FDA-approved inhibitor of purine biosynthesis, potently inhibits viral RNA replication, viral protein synthesis, and virus release. The effective antiviral methotrexate concentrations are similar to those used for established human therapies using the same drug. Methotrexate should be most effective in patients at the earliest appearance of symptoms to effectively prevent viral replication, diffusion of the infection, and possibly fatal complications.

Combining positron emission tomography/computed tomography, radiomics, and sentinel lymph node mapping for nodal staging of endometrial cancer patients.

OBJECTIVE: To evaluate the combination of positron emission tomography/computed tomography (PET/CT) and sentinel lymph node (SLN) biopsy in women with apparent early-stage endometrial carcinoma. The correlation between radiomics features extracted from PET images of the primary tumor and the presence of nodal metastases was also analyzed. METHODS: From November 2006 to March 2019, 167 patients with endometrial cancer were included. All women underwent PET/CT and surgical staging: 60/167 underwent systematic lymphadenectomy (Group 1) while, more recently, 107/167 underwent SLN biopsy (Group 2) with technetium-99m +blue dye or indocyanine green. Histology was used as standard reference. PET endometrial lesions were segmented (n=98); 167 radiomics features were computed inside tumor contours using standard Image Biomarker Standardization Initiative (IBSI) methods. Radiomics features associated with lymph node metastases were identified (Mann-Whitney test) in the training group (A); receiver operating characteristic (ROC) curves, area under the curve (AUC) values were computed and optimal cut-off (Youden index) were assessed in the test group (B). RESULTS: In Group 1, eight patients had nodal metastases (13%): seven correctly ridentified by PET/CT true-positive with one false-negative case. In Group 2, 27 patients (25%) had nodal metastases: 13 true-positive and 14 false-negative. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PET/CT for pelvic nodal metastases were 87%, 94%, 93%, 70%, and 98% in Group 1 and 48%, 97%, 85%, 87%, and 85% in Group 2, respectively. On radiomics analysis a significant association was found between the presence of lymph node metastases and 64 features. Volume-density, a measurement of shape irregularity, was the most predictive feature (p=0001, AUC=0,77, cut-off 0.35). When testing cut-off in Group B to discriminate metastatic tumors, PET false-negative findings were reduced from 14 to 8 (-43%). CONCLUSIONS: PET/CT demonstrated high specificity in detecting nodal metastases. SLN and histologic ultrastaging increased false-negative PET/CT findings, reducing the sensitivity of the technique. PET radiomics features of the primary tumor seem promising for predicting the presence of nodal metastases not detected by visual analysis.

Role of 18 F-fluoro-2-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in malignant ovarian germ cell tumors: a single-center experience with long term follow-up.

INTRODUCTION: 18F-fluoro-2-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is a diagnostic tool widely used in oncology, but to date there are no established recommendations for its use in malignant ovarian germ cell tumors. The aim of this study was to evaluate the role of 18F-FDG PET/CT in the clinical management of patients with malignant ovarian germ cell tumors. METHODS: This was a retrospective review of 18F-FDG PET/CT scans performed in patients diagnosed with malignant ovarian germ cell tumors treated at the gynecology department of San Gerardo Hospital (Monza, Italy) from June 2006 to December 2016. Data collected included clinical history, radiological, biochemical and pathological evaluation, treatment, follow-up, outcome, and clinical indication for the PET/CT scan. PET/CT findings were categorized as negative/normal (no abnormal FDG uptake or physiological uptake), positive/abnormal (FDG uptake considered to indicate active germ cell malignancy), or equivocal (FDG uptake of uncertain significance, not clearly correlated to neoplastic disease). RESULTS: A total of 69 PET/CT scans in 37 patients were evaluated. The mean age at diagnosis was 25 years (range 20-48). The majority of patients had International Federation of Gynecology and Obstetrics (FIGO) stage I (22/37) disease and had a diagnosis of dysgerminomas (18/37). Imaging indications were initial staging before treatment (4/69, 6%), staging after inadequate staging surgery (24/69, 35%), restaging after adjuvant chemotherapy (17/69, 25%), relapse suspect (9/69, 13%), and follow-up (15/69, 21%). Pathology confirmation of PET/CT results was available in 28/69 (40.5%) studies. All negative PET/CT (15/28) cases were confirmed with laparoscopy as true negative; among 13/28 positive PET cases, histopathology confirmed 7 (54%) as true positive and 6 (46%) as false positive (5 inflammatory and 1 mature teratoma implants). Patient-based analysis showed 100% sensitivity, 71% specificity, 54% positive predictive value, 100% negative predictive value, and 79% accuracy. Clinical follow-up was available in 41 (59.4%) of 69 PET/CT images: 28/41 studies were negative and 13/41 positive. A mean follow-up of 28 months (median 15, range 5-102) confirmed negative PET/CT studies. A total of 13 positive PET/CT patients underwent chemotherapy with subsequent evidence of disease response. DISCUSSION: PET/CT in malignant ovarian germ cell tumors was mainly performed for staging after inadequate staging surgery or for restaging after adjuvant chemotherapy. PET/CT was associated with high sensitivity and negative predictive value.

Radiomics of the primary tumour as a tool to improve 18F-FDG-PET sensitivity in detecting nodal metastases in endometrial cancer.

BACKGROUND: A radiomic approach was applied in 18F-FDG PET endometrial cancer, to investigate if imaging features computed on the primary tumour could improve sensitivity in nodal metastases detection. One hundred fifteen women with histologically proven endometrial cancer who underwent preoperative 18F-FDG PET/CT were retrospectively considered. SUV, MTV, TLG, geometrical shape, histograms and texture features were computed inside tumour contours. On a first group of 86 patients (DB1), univariate association with LN metastases was computed by Mann-Whitney test and a neural network multivariate model was developed. Univariate and multivariate models were assessed with leave one out on 20 training sessions and on a second group of 29 patients (DB2). A unified framework combining LN metastases visual detection results and radiomic analysis was also assessed. RESULTS: Sensitivity and specificity of LN visual detection were 50% and 99% on DB1 and 33% and 95% on DB2, respectively. A unique heterogeneity feature computed on the primary tumour (the zone percentage of the grey level size zone matrix, GLSZM ZP) was able to predict LN metastases better than any other feature or multivariate model (sensitivity and specificity of 75% and 81% on DB1 and of 89% and 80% on DB2). Tumours with LN metastases are in fact generally characterized by a lower GLSZM ZP value, i.e. by the co-presence of high-uptake and low-uptake areas. The combination of visual detection and GLSZM ZP values in a unified framework obtained sensitivity and specificity of 94% and 67% on DB1 and of 89% and 75% on DB2, respectively. CONCLUSIONS: The computation of imaging features on the primary tumour increases nodal staging detection sensitivity in 18F-FDG PET and can be considered for a better patient stratification for treatment selection. Results need a confirmation on larger cohort studies.

High-Intensity Focused Ultrasound- and Radiation Therapy-Induced Immuno-Modulation: Comparison and Potential Opportunities.

In recent years, high-intensity focused ultrasound (HIFU) has emerged as a new and promising non-invasive and non-ionizing ablative technique for the treatment of localized solid tumors. Extensive pre-clinical and clinical studies have evidenced that, in addition to direct destruction of the primary tumor, HIFU-thermoablation may elicit long-term systemic host anti-tumor immunity. In particular, an important consequence of HIFU treatment includes the release of tumor-associated antigens (TAAs), the secretion of immuno-suppressing factors by cancer cells and the induction of cytotoxic T lymphocyte (CTL) activity. Radiation therapy (RT) is the main treatment modality used for many types of tumors and about 50% of all cancer patients receive RT, often used in combination with surgery and chemotherapy. It is well known that RT can modulate anti-tumor immune responses, modifying micro-environment and stimulating inflammatory factors that can greatly affect cell invasion, bystander effects, radiation tissue complications (such as fibrosis), genomic instability and thus, intrinsic cellular radio-sensitivity. To date, various combined therapeutic strategies (such as immuno-therapy) have been performed in order to enhance RT success in treating locally advanced and recurrent tumors. Recent works suggested the combined use of HIFU and RT treatments to increase the tumor cell radio-sensitivity, in order to synergize the effects reaching the maximum results with minimal doses of ionizing radiation (IR). Here, we highlight the opposite immuno-modulation roles of RT and HIFU, providing scientific reasons to test, by experimental approaches, the use of HIFU immune-stimulatory capacity to improve tumor radio-sensitivity, to reduce the RT induced inflammatory response and to decrease the dose-correlated side effects in normal tissues.

Evaluation of erlotinib treatment response in non-small cell lung cancer using metabolic and anatomic criteria.

BACKGROUND: In this paper the clinical value of PET for early prediction of tumor response to erlotinib in patients with advanced or metastatic non-small cell lung cancer (NSCLC) after failure of at least one prior chemotherapy regimen is evaluated. The aim was to compare the early metabolic treatment response using European Organization for Research and Treatment of Cancer (EORTC) 1999 recommendations and PET Response Criteria in Solid Tumors (PERCIST), and the standard treatment response using Response Evaluation Criteria in Solid Tumors (RECIST). METHODS: Twenty patients with stage IV NSCLC were enrolled prospectively. PET/CT studies were performed before, then 48 hours, and 45 days after the initiation of erlotinib treatment. The lesion with the highest uptake in each patient was evaluated according to EORTC 1999 recommendations, PERCIST and RECIST to assess metabolic and anatomic response. Response classifications were compared statistically using Wilcoxon signed-rank test. Disease-free survival (DFS) and overall survival (OS) were calculated by the Kaplan-Meier Test. RESULTS: At 48 hours, the Kaplan-Meier analysis showed that EORTC proved to be a significant prognostic factor for predicting DFS and OS. At 45 days, there was a significant difference in response evaluation between RECIST and metabolic classifications. RECIST and PERCIST were significant prognostic factors for predicting DFS and OS. EORTC was not able to discriminate responder from non-responder patients. CONCLUSIONS: This study shows that, according to the EORTC protocol, the PET exam is able to provide early identification of patients who benefit from Erlotinib treatment. Used at the end of therapy, PERCIST could be considered an appropriate metabolic evaluation method to discriminate responders from non-responders.

Radio guided radical prostatectomy: evaluation of feasibility, safety and clinical outcomes.

BACKGROUND: The standard surgical treatment of PCa consists of radical prostatectomy (RP). Lymphadenectomy with removal of the sentinel lymph node (SLN) is now evolving towards the concept of radio guided surgery as an instrument for the removal of the lymph nodes of primary drainage. METHODS: From October 2012 to September 2013 laparotomic SLN dissection was performed in 43 patients during standard open radical prostatectomy. Twenty hours before surgery, 240 MBq of 99mTc nanocolloid were injected into the prostate gland under transrectal ultrasound guidance. A planar scintigraphy and a SPET/CT scan were performed 1-2 hours after the injection. Intraoperatively, all LNs detected by gamma-probe with an activity significantly higher than background were removed and classified as SLNs. We evaluated operative time, complications, postoperative outcomes and costs of the procedures of patients who underwent radio guided surgery. We measured radioactive exposure rates. RESULTS: The intraoperative detection of SLNs occurred in all 43 patients, while the scintigraphic localization was observed in 42/43 patients. A total of 77 SLNs were found, at histopathological analysis 7/77 SLNs resulted positive for metastases (4/43 patients): 3 were in the obturator fossa while the remaining SLNs were in the internal iliac chain (1), common iliac chain (1), external iliac chain (2). Global radiation exposure was not significant. CONCLUSION: Our preliminary data confirm the feasibility and the safety of SLN biopsy in nodal staging of PCa. The intraoperatively SLN detection rate resulted 100%. In 3 patients (7%) a micrometastases was found outside of obturator fossa in a not routinely sampled site.

Quantification of Dynamic [18F]FDG Pet Studies in Acute Lung Injury.

PURPOSE: This work aims to investigate lung glucose metabolism using 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) positron emission tomography (PET) imaging in acute lung injury (ALI) patients. PROCEDURES: Eleven ALI patients and five healthy controls underwent a dynamic [(18)F]FDG PET/X-ray computed tomography (CT) scan. The standardized uptake values (SUV) and three different methods for the quantification of glucose metabolism (i.e., ratio, Patlak, and spectral analysis iterative filter, SAIF) were applied both at the region and the voxel levels. RESULTS: SUV reported a lower correlation than the ratio with the net tracer uptake. Patlak and SAIF analyses did not show any significant spatial or quantitative (R(2) > 0.80) difference. The additional information provided by SAIF showed that in lung inflammation, elevated tracer uptake is coupled with abnormal tracer exchanges within and between lung tissue compartments. CONCLUSIONS: Full kinetic modeling provides a multi-parametric description of glucose metabolism in the lungs. This allows characterizing the spatial distribution of lung inflammation as well as returning the functional state of the tissues.

Staging of High-Risk Endometrial Cancer With PET/CT and Sentinel Lymph Node Mapping.

PURPOSE: The aim of this study was to evaluate the role of PET/CT and sentinel lymph node (SLN) biopsy in staging high-risk endometrial cancer patients (G2 and deep myometrial invasion, G3, serous clear cell carcinoma or carcinosarcoma) in early clinical stage. PATIENTS AND METHODS: From January 2006 to December 2012, high-risk early-stage endometrial cancer patients performing PET/CT scan followed by surgery (systematic pelvic ± aortic lymphadenectomy) were included. From December 2010, SLN mapping with Tc-albumin nanocolloid and blue dye cervical injection was included in our clinical practice and additionally performed. Histological findings were used as the reference standard. RESULTS: Ninety-three patients were included, of which 22 of 93 had both PET/CT and SLN biopsy. The median number of dissected lymph nodes (LNs) was 28. Nineteen women (20.4%) had pelvic LN metastases; 14 were correctly identified by PET/CT. Among 5 false-negative cases, 3 occurred after the introduction of SLN mapping due to detection of micrometastases by ultrastaging. On overall patient-based analysis, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PET/CT for pelvic LN metastases were 73.7%, 98.7%, 93.6%, 93.3%, 93.6%, respectively. CONCLUSIONS: PET/CT demonstrated moderate sensitivity and high specificity in detecting pelvic LN metastases; its high positive predictive value (93.3%) is useful to refer patients to appropriate debulking surgery. Sentinel LN mapping and histological ultrastaging increased the identification of metastases (incidence, 18.3%-27.3%) not detectable by PET/CT because of its spatial resolution. The combination of both modalities is promising for nodal staging purpose.

High-dose Ionizing Radiation Regulates Gene Expression Changes in the MCF7 Breast Cancer Cell Line.

BACKGROUND: Intraoperative electron radiation therapy (IOERT) is a therapeutic technique which administers a single high dose of ionizing radiation immediately after surgical tumor removal. IOERT induces a strong stress response: both tumor and normal cells activating pro- and antiproliferative cell signaling pathways. Following treatment, several genes and factors are differently modulated, producing an imbalance in cell fate decision. However, the contribution of these genes and pathways in conferring different cell radiosensitivity and radioresistance needs to be further investigated, in particular after high-dose treatments. Despite the documented and great impact of IOERT in breast cancer care, and the trend for dose escalation, very limited data are available regarding gene-expression profiles and cell networks activated by IOERT or high-dose treatment. The aim of the study was to analyze the main pathways activated following high radiation doses in order to select for potential new biomarkers of radiosensitivity or radioresistance, as well as to identify therapeutic targets useful in cancer care. MATERIALS AND METHODS: We performed gene-expression profiling of the MCF7 human breast carcinoma cell line after treatment with 9- and 23-Gy doses (conventionally used during IOERT boost and exclusive treatments, respectively) by cDNA microarrays. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR), immunofluorescence and immunoblot experiments were performed to validate candidate IOERT biomarkers. We also conducted clonogenic tests and cellular senescence assays to monitor for radiation-induced effects. RESULTS: The analyses highlighted a transcriptome dependent on the dose delivered and a number of specific key genes that may be proposed as new markers of radiosensitivity. Cell and molecular traits observed in MCF7 cells revealed a typical senescent phenotype associated with cell proliferation arrest after treatments with 9- and 23-Gy doses. CONCLUSION: In this study, we report genes and cellular networks activated following high-dose IOERT. The selected validated genes were used to design two descriptive models for each dose delivered. We believe that this study could contribute to the understanding over the complex mechanisms which regulate cell radiosensitivity and radioresistance in order to improve personalized radiotherapeutic treatment.

Caveolin-1, breast cancer and ionizing radiation.

Breast cancer (BC) recovery has increased in recent years thanks to efforts of Omics-based research in this field. However, despite the important results obtained, BC remains a complex multifactorial pathology that is difficult to treat appropriately. Caveolin-1 (CAV1), the basic constituent protein of specialized plasma membrane invaginations called caveolae, is emerging as a potential therapeutic biomarker in BC. This factor may modulate BC response to chemotherapy and radiation therapy. In addition, recent reports describe the key role of CAV1 during cell response to oxidative stress. The aim of the present review was to describe the biological roles of CAV1 in BC considering its contrasting dual functions as an oncogene and as a tumor suppressor. In addition, we report on how CAV1 may contribute to tumor cell response to ionizing radiation treatment. Finally, new roles of CAV1 in BC both on epithelium and stroma may be useful as prognostic indicators for patient treatment and help clinicians in the selection of the best personalized therapy.

Gene Expression Profiling of MCF10A Breast Epithelial Cells Exposed to IOERT.

BACKGROUND/AIM: Intraoperative electron radiation therapy (IOERT) is a therapeutic approach that delivers a single high dose of ionizing radiation (IR) directly to the tumor bed during cancer surgery. The main goal of IOERT is to counteract tumor growth by acting on residual cancer cells as well as to preserve healthy surrounding tissue from the side-effects of radiation therapy. The radiobiology of the healthy tissue response to IR is a topic of interest which may contribute to avoiding impairment of normal tissue and organ function and to reducing the risks of secondary cancer. The purpose of the study was to highlight cell and gene expression responses following IOERT treatment in the human non-tumorigenic MCF10A cell line in order to find new potential biomarkers of radiosensitivity/radioresistance. MATERIAL AND METHODS: Gene-expression profiling of MCF10A cells treated with 9 and 23 Gy doses (IOERT boost and exclusive treatment, respectively), was performed by whole-genome cDNA microarrays. Real-time quantitative reverse transcription (qRT-PCR), immunofluorescence and immunoblot experiments were carried out to validate candidate IOERT biomarkers. Clonogenic tests and morphological evaluations to examine cellular effects induced by radiation were also conducted. RESULTS: The study revealed a dose-dependent gene-expression profile and specific key genes that may be proposed as novel markers of radiosensitivity. Our results show consistent differences in non-tumorigenic cell tolerance and in the molecular response of MCF10A cells to different IOERTs. In particular, after 9 Gy of exposure, the selection of a radioresistant cell fraction was observed. CONCLUSION: The possibility of clarifying the molecular strategies adopted by cells in choosing between death or survival after IR-induced damage opens-up new avenues for the selection of a proper personalized therapy schedule.

Portrait of inflammatory response to ionizing radiation treatment.

Ionizing radiation (IR) activates both pro-and anti-proliferative signal pathways producing an imbalance in cell fate decision. IR is able to regulate several genes and factors involved in cell-cycle progression, survival and/or cell death, DNA repair and inflammation modulating an intracellular radiation-dependent response. Radiation therapy can modulate anti-tumour immune responses, modifying tumour and its microenvironment. In this review, we report how IR could stimulate inflammatory factors to affect cell fate via multiple pathways, describing their roles on gene expression regulation, fibrosis and invasive processes. Understanding the complex relationship between IR, inflammation and immune responses in cancer, opens up new avenues for radiation research and therapy in order to optimize and personalize radiation therapy treatment for each patient.

DVWA gene polymorphisms and osteoarthritis.

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.

Genetic, clinical and radiographic signs in knee osteoarthritis susceptibility.

INTRODUCTION: Osteoarthritis (OA) is considered to be a multifactorial and polygenic disease and diagnosis is mainly clinical and radiological. Correlation between radiographic data and clinical status has been reported. However, very few studies, especially in Caucasian people, describe the association between the Kellgren and Lawrence OA grading scale (KL) and genetic alterations to better understand OA etiopathogenesis and susceptibility. In order to update the knee OA grading, in this study we assessed the associations between KL grade, clinical features such as American Knee Society Score (AKSS), age, and polymorphisms in the principal osteoarthritis susceptibility (OS) genes in Sicilian individuals. METHODS: In 66 Sicilian individuals affected by primary knee OA, the clinical and radiographic evaluation was performed using 2 sub-scores of AKSS (knee score (KS) and function score (FS)) and KL. The patients were also classified according to age. Online Mendelian Inheritance in Man (OMIM) and Database of Single Nucleotide Polymorphisms (dbSNP) Short Genetic Variations databases were used to select gene regions containing the following polymorphisms to analyze: FRZB rs288326 and rs7775, MATN3 rs77245812, ASPN D14 repeats, PTHR2 rs76758470, GDF5 rs143383 and DVWA rs11718863. Patient genotypes were obtained using Sanger DNA sequencing analysis. RESULTS: In our cohort of patients a statistical association between the variables analyzed was reported in all associations tested (KL versus KS, FS and age). We observed that a mild to severe OA radiographic grade is related to severe clinical conditions and loss of articular function and that the severity of symptoms increases with age. Concerning the genotyping analysis, our results revealed a significant statistical association between KL grading and GDF5 rs143383 and DVWA rs11718863 genetic alterations. The latter was also associated with a more severe radiographic grade, displaying its predictive role as OA marker progression. Statistically significant association between clinical, radiographic and genetic signs observed, suggests extending the actual grading of knee OA based mainly on X-ray features. CONCLUSIONS: This work represents a multidisciplinary and translational medicine approach to study OA where clinical, radiological, and OS5 and OS6 SNPs evaluation could contribute to better define grading and progression of OA and to the development of new therapies.

Gene expression profiling of epithelial-mesenchymal transition in primary breast cancer cell culture.

BACKGROUND/AIM: Epithelial-mesenchymal transition (EMT) is a process co-opted by cancer cells to invade and form metastases. In the present study we analyzed gene expression profiles of primary breast cancer cells in culture in order to highlight genes related to EMT. MATERIALS AND METHODS: Microarray expression analysis of primary cells isolated from a specimen of a patient with an infiltrating ductal carcinoma of the breast was performed. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) analyses validated microarray gene expression trends. RESULTS: Thirty-six candidate genes were selected and used to generate a molecular network displaying the tight relationship among them. The most significant Gene Ontology biological processes characterizing this network were involved in cell migration and motility. CONCLUSION: Our data revealed the involvement of new genes which displayed tight relationships among them, suggesting a molecular network in which they could contribute to control of EMT in breast cancer. This study may offer a basis for understanding complex mechanisms which regulate breast cancer progression and for designing individualized anticancer therapies.