Triadic closure as a basic generating mechanism of communities in complex networks

R.K.D. and S.F. gratefully acknowledge MULTIPLEX, Grant No. 317532 of the European Commission

Edge based stochastic block model statistical inference

Community detection in graphs often relies on ad hoc algorithms with no clear specification about the node partition they define as the best, which leads to uninterpretable communities. Stochastic block models (SBM) offer a framework to rigorously define communities, and to detect them using statistical inference method to distinguish structure from random fluctuations. In this paper, we introduce an alternative definition of SBM based on edge sampling. We derive from this definition a quality function to statistically infer the node partition used to generate a given graph. We then test it on synthetic graphs, and on the zachary karate club network

Estimates of the incidence of infection-related cancers in Italy and Italian regions in 2018

Introduction. Chronic infections and infestations represent one of the leading causes of cancer. Eleven agents have been categorized by the International Agency for Research on Cancer (IARC) in Group 1, 3 in Group 2A and 4 in Group 2B. We previously estimated that the incidence of cancers associated with infectious agents accounted for the 8.5% of new cancer cases diagnosed in Italy in 2014. Methods. In the present study we evaluated the incidence of cancer in Italy and in the 20 Italian regions in 2018, based on the data of Cancer Registries, and calculated the fraction attributable to infectious agents. Results. Cancers of infectious origin contributed to the overall burden of cancer in Italy with more than 27,000 yearly cases, the 92% of which was attributable to Helicobacter pylori, human papillomaviruses, and hepatitis B and C viruses. With the exception of papillomavirus-related cancers, the incidence of cancers of infectious origin was higher in males (16,000 cases) than in females (11,000 cases). There were regional and geographical variations of cancers depending on the type of cancer and on the gender. Nevertheless, the overall figures were rather similar, the infection-related cancers accounting for the 7.2, 7.6, and 7.1% of all cancers in Northern, Central, and Southern Italy, respectively. Conclusions. The estimate of the incidence of cancers attributable to infectious agents in Italy in 2018 (7.3% of all cancer cases) is approximately half of the worldwide burden, which has been estimated by IARC to be the 15.4% of all cancer cases in 2012

Regional indices of socio-economic and health inequalities: a tool for public health programming

Abstract OBJECTIVES. The aim was to provide an affordable method for computing socio-economic deprivation indices at regional level, to reveal the specific aspects of the relationship between socio-economic (SE) inequalities and health outcomes. The Umbria region Socio-Health Index (USHI) was computed and compared to the Italian National Deprivation Index at Umbria region level (NDI-U).METHODS. The USHI was computed by applying factor analysis to census tract SE variables correlated to the general mortality and validated in comparison with the NDI-U.RESULTS. Overall mortality presented linear positive USHI trends, while trends for NDI-U resulted non-linear or not-significant. Similar and relevant results were obtained for specific causes of death by deprivation groups, gender and age.CONCLUSIONS. The USHI better describes a local population by SE health-related status. Therefore, policy makers could adopt this method to obtain a better picture of SE-associated health conditions in regional population and target strategies for reducing inequalities in health

Cancer burden trends in Umbria region using a joinpoint regression

Introduction. The analysis of the epidemiological data on cancer is an important tool to control and evaluate the outcomes of primary and secondary prevention, the effectiveness of health care and, in general, all cancer control activities. Materials and methods. The aim of the this paper is to analyze the cancer mortality in the Umbria region from 1978 to 2009 and incidence from 1994-2008. Sex and sitespecific trends for standardized rates were analyzed by “joinpoint regression”, using the surveillance epidemiology and end results (SEER) software. Results. Applying the jointpoint analyses by sex and cancer site, to incidence spanning from 1994 to 2008 and mortality from 1978 to 2009 for all sites, both in males and females, a significant joinpoint for mortality was found; moreover the trend shape was similar and the joinpoint years were very close. In males standardized rate significantly increased up to 1989 by 1.23% per year and significantly decreased hereafter by -1.31%; among females the mortality rate increased in average of 0.78% (not significant) per year till 1988 and afterward significantly decreased by -0.92% per year. Incidence rate showed different trends among sexes. In males was practically constant over the period studied (not significant decrease 0.14% per year), in females significantly increased by 1.49% per year up to 2001 and afterward slowly decreased (-0.71% n.s. estimated annual percent change − EAPC). Conclusions. For all sites combined trends for mortality decreased since late ’80s, both in males and females; such behaviour is in line with national and European Union data. This work shows that, even compared to health systems that invest more resources, the Umbria public health system achieved good health outcomes

Gene identification for risk of relapse in stage I lung adenocarcinoma patients. A combined methodology of gene expression profiling and computational gene network analysis

Risk assessment and treatment choice remains a challenge in early non-smallcell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR. From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS). Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy

MYC and human telomerase gene (TERC) copy number gain in early-stage non-small cell lung cancer

Objectives: We investigated the frequency of MYC and TERC increased gene copy number (GCN) in early-stage non-small cell lung cancer (NSCLC) and evaluated the correlation of these genomic imbalances with clinicopathologic parameters and outcome. Materials and Methods: Tumor tissues were obtained from 113 resected NSCLCs. MYC and TERC GCNs were tested by fluorescence in situ hybridization (FISH) according to the University of Colorado Cancer Center (UCCC) criteria and based on the receiver operating characteristic (ROC) classification. Results: When UCCC criteria were applied, 41 (36%) cases for MYC and 41 (36%) cases for TERC were considered FISH-positive. MYC and TERC concurrent FISH-positive was observed in 12 cases (11%): 2 (17%) cases with gene amplification and 10 (83%) with high polysomy. By using the ROC analysis, high MYC (mean ≥2.83 copies/cell) and TERC (mean ≥2.65 copies/cell) GCNs were observed in 60 (53.1%) cases and 58 (51.3%) cases, respectively. High TERC GCN was associated with squamous cell carcinoma (SCC) histology (P=0.001). In univariate analysis, increased MYC GCN was associated with shorter overall survival (P=0.032 [UCCC criteria] or P=0.02 [ROC classification]), whereas high TERC GCN showed no association. In multivariate analysis including stage and age, high MYC GCN remained significantly associated with worse overall survival using both the UCCC criteria (P=0.02) and the ROC classification (P=0.008). Conclusions: Our results confirm MYC as frequently amplified in early-stage NSCLC and increased MYC GCN as a strong predictor of worse survival. Increased TERC GCN does not have prognostic impact but has strong association with squamous histology

Percolation in the classical blockmodel

Classical blockmodel is known as the simplest among models of networks with community structure. The model can be also seen as an extremely simply example of interconnected networks. For this reason, it is surprising that the percolation transition in the classical blockmodel has not been examined so far, although the phenomenon has been studied in a variety of much more complicated models of interconnected and multiplex networks. In this paper we derive the self-consistent equation for the size the global percolation cluster in the classical blockmodel. We also find the condition for percolation threshold which characterizes the emergence of the giant component. We show that the discussed percolation phenomenon may cause unexpected problems in a simple optimization process of the multilevel network construction. Numerical simulations confirm the correctness of our theoretical derivations.Comment: 7 pages, 6 figure

Concomitant high gene copy number and protein overexpression of IGF1R and EGFR negatively affect disease-free survival of surgically resected non-small-cell-lung cancer patients

BACKGROUND: Insulin-like growth factor 1 receptor (IGF1R) represents a novel molecular target in non-small-cell-lung cancer (NSCLC). IGF1R and epidermal growth factor receptor (EGFR) activation are essential to mediate tumor cell survival, proliferation, and invasion. This study investigates the prognostic role of IGF1R and EGFR in surgically resected NSCLC. MATERIALS AND METHODS: IGF1R and EGFR copy number gain (CNG) were tested by fluorescence in situ hybridization (FISH) and protein expression by immunohistochemistry (IHC) in 125 stage I-II-IIIA NSCLC patients. RESULTS: Fourty-six tumors (40.3 %) were IGF1R FISH-positive (FISH+), and 76 (67.2 %) were EGFR FISH+. Tumors with concomitant IGF1R/EGFR FISH+ were observed in 34 cases (30.1 %). IGF1R and EGFR FISH+ were associated with SCC histology (p = 0.01 and p = 0.04, respectively). IGF1R and EGFR protein over-expression (IHC+) were detected in 45 (36.0 %) and 69 (55.2 %) cases, respectively. Tumors with concomitant IGF1R/EGFR IHC+ were detected in 31 (24.8 %) patients. IGF1R/EGFR FISH+ and IGF1R/EGFR IHC+ were significantly associated (χ(2) = 4.02, p = 0.04). Patients with IGF1R/EGFR FISH+ and IGF1R/EGFR IHC+ were associated with shorter disease-free survival (DFS) (p = 0.05 and p = 0.05, respectively). Patients with concomitant IGF1R/EGFR FISH+/IHC+ had a worse DFS and overall survival (p = 0.005 and p = 0.01, respectively). The multivariate model confirmed that IGF1R/EGFR FISH+/IHC+ (hazard ratio (HR), 4.08; p = 0.01) and tumor stage (II-III vs I) (HR, 4.77; p = 0.003) were significantly associated with worse DFS. CONCLUSIONS: IGF1R/EGFR FISH+ correlates with IGF1R/EGFR IHC+. IGF1R/EGFR FISH+/IHC+ is an independent negative prognostic factor for DFS in early NSCLC. These features may have important implications for future anti-IGF1R therapeutic approaches