Cancer and Pregnancy: Estimates in Italy from Record-Linkage Procedures between Cancer Registries and the Hospital Discharge Database.

The aim of this study is to describe the frequency and trend of pregnancy-associated cancer (PAC) in Italy, an increasingly relevant phenomenon due to postponing age at childbirth. To this purpose, a population-based retrospective longitudinal study design based on cohorts of women aged 15-49 diagnosed with cancer and concomitant pregnancy is proposed. The study uses 19 population-based Cancer Registries, covering about 22% of Italy, and linked at an individual level with Hospital Discharge Records. A total of 2,861,437 pregnancies and 3559 PAC are identified from 74,165 women of the cohort with a rate of 1.24 PAC per 1000 pregnancies. The most frequent cancer site is breast (24.3%), followed by thyroid (23.9%) and melanoma (14.3%). The most frequent outcome is delivery (53.1%), followed by voluntary termination of pregnancy and spontaneous abortion (both 12.0%). The trend of PAC increased from 2003 to 2015, especially when the outcome is delivery, thus confirming a new attitude of clinicians to manage cancer throughout pregnancy. This represents the first attempt in Italy to describe PAC from Cancer Registries data; the methodology is applicable to other areas with the same data availability. Evidence from this study is addressed to clinicians for improving clinical management of women with PAC.

Robustness analysis for quantitative assessment of vaccination effects and SARS-CoV-2 lineages in Italy.

BACKGROUND: In Italy, the beginning of 2021 was characterized by the emergence of new variants of SARS-CoV-2 and by the availability of effective vaccines that contributed to the mitigation of non-pharmaceutical interventions and to the avoidance of hospital collapse. METHODS: We analyzed the COVID-19 propagation in Italy starting from September 2021 with a Susceptible-Exposed-Infected-Recovered (SEIR) model that takes into account SARS-CoV-2 lineages, intervention measures and efficacious vaccines. The model was calibrated with the Bayesian method Conditional Robust Calibration (CRC) using COVID-19 data from September 2020 to May 2021. Here, we apply the Conditional Robustness Analysis (CRA) algorithm to the calibrated model in order to identify model parameters that most affect the epidemic diffusion in the long-term scenario. We focus our attention on vaccination and intervention parameters, which are the key parameters for long-term solutions for epidemic control. RESULTS: Our model successfully describes the presence of new variants and the impact of vaccinations and non-pharmaceutical interventions in the Italian scenario. The CRA analysis reveals that vaccine efficacy and waning immunity play a crucial role for pandemic control, together with asymptomatic transmission. Moreover, even though the presence of variants may impair vaccine effectiveness, virus transmission can be kept low with a constant vaccination rate and low restriction levels. CONCLUSIONS: In the long term, a policy of booster vaccinations together with contact tracing and testing will be key strategies for the containment of SARS-CoV-2 spread.

Effects of deprivation and age on staging of breast, colon, rectum and prostate cancer in Umbria region, Italy: a multilevel approach.

BACKGROUND: Early diagnosis of breast, colon, rectum and prostate cancers improves health outcomes. Low socioeconomic status (SES) is related to advanced stages at diagnosis; inequalities could explain differences in outcomes by age. The influence of SES, age and residence area on staging was explored in the Umbrian population. METHODS: 2001-2010 cases were geo-coded by census tract of residence. Stage distribution or Gleason score were analyzed by multilevel multinomial logistic regression with age and SES as the fixed effects and census tract as the random-effect. RESULTS: For breast and colorectal cancers, the screening age class was advantaged. For breast, age effect was modulated by deprivation and census tract. In the elderly, the richest were advantaged, the poorest disadvantaged; issues emerged for the young. For colon, age effect is modulated by census tract in early stages and deprivation in late stages. The elderly were disadvantaged; the young and the deprived had more stages IV. About rectum, age effect was modulated by deprivation in the late stages. The elderly were disadvantaged; the young and the deprived presented more stages IV. For prostate, age effect was modulated by deprivation and census tract. The intermediate age class was advantaged, the elderly disadvantaged. CONCLUSION: Age was not always the determinant of a delayed staging when SES was considered. For breast and colorectal cancers, issues of delayed diagnosis emerged in the young. If the care center was near the residence, the census tract modified the stage at diagnosis. These results are useful to reduce SES barriers by specific programs adapted to the age of the patient and area of residence.

Genome-wide expression of the residual lung reacting to experimental Pneumonectomy.

BACKGROUND: Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq). RESULTS: Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of "Extrinsic apoptotic signaling pathway" (FDR q = 7.60 × 10- 3) and "Response to insulin" (FDR q = 7.60 × 10- 3) genes, along with an enrichment of genes involved as "Negative regulators of DDX58/IFIH1 signaling" (FDR q = 7.50 × 10- 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections. CONCLUSION: This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Wild-Type KRAS Allele Effects on Druggable Targets in KRAS Mutant Lung Adenocarcinomas.

KRAS mutations are one of the most common oncogenic drivers in non-small cell lung cancer (NSCLC) and in lung adenocarcinomas in particular. Development of therapeutics targeting KRAS has been incredibly challenging, prompting indirect inhibition of downstream targets such as MEK and ERK. Such inhibitors, unfortunately, come with limited clinical efficacy, and therefore the demand for developing novel therapeutic strategies remains an urgent need for these patients. Exploring the influence of wild-type (WT) KRAS on druggable targets can uncover new vulnerabilities for the treatment of KRAS mutant lung adenocarcinomas. Using commercially available KRAS mutant lung adenocarcinoma cell lines, we explored the influence of WT KRAS on signaling networks and druggable targets. Expression and/or activation of 183 signaling proteins, most of which are targets of FDA-approved drugs, were captured by reverse-phase protein microarray (RPPA). Selected findings were validated on a cohort of 23 surgical biospecimens using the RPPA. Kinase-driven signatures associated with the presence of the KRAS WT allele were detected along the MAPK and AKT/mTOR signaling pathway and alterations of cell cycle regulators. FoxM1 emerged as a potential vulnerability of tumors retaining the KRAS WT allele both in cell lines and in the clinical samples. Our findings suggest that loss of WT KRAS impacts on signaling events and druggable targets in KRAS mutant lung adenocarcinomas.

A Modeling Study on Vaccination and Spread of SARS-CoV-2 Variants in Italy.

From the end of 2020, different vaccines against COVID-19 have been approved, offering a glimmer of hope and relief worldwide. However, in late 2020, new cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started to re-surge, worsened by the emergence of highly infectious variants. To study this scenario, we extend the Susceptible-Exposed-Infectious-Removed model with lockdown measures used in our previous work with the inclusion of new lineages and mass vaccination campaign. We estimate model parameters using the Bayesian method Conditional Robust Calibration in two case studies: Italy and the Umbria region, the Italian region being worse affected by the emergence of variants. We then use the model to explore the dynamics of COVID-19, given different vaccination paces and a policy of gradual reopening. Our findings confirm the higher reproduction number of Umbria and the increase of transmission parameters due to the presence of new variants. The results illustrate the importance of preserving population-wide interventions, especially during the beginning of vaccination. Finally, under the hypothesis of waning immunity, the predictions show that a seasonal vaccination with a constant rate would probably be necessary to control the epidemic.

Higher TLR7 Gene Expression Predicts Poor Clinical Outcome in Advanced NSCLC Patients Treated with Immunotherapy.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, their clinical benefit is limited to a minority of patients. To unravel immune-related factors that are predictive of sensitivity or resistance to immunotherapy, we performed a gene expression analysis by RNA-Seq using the Oncomine Immuno Response Assay (OIRRA) on a total of 33 advanced NSCLC patients treated with ICI evaluating the expression levels of 365 immune-related genes. We found four genes (CD1C, HLA-DPA1, MMP2, and TLR7) downregulated (p < 0.05) and two genes (IFNB1 and MKI67) upregulated (p < 0.05) in ICI-Responders compared to ICI-Non-Responders. The Bayesian enrichment computational analysis showed a more complex interaction network that involved 10 other genes (IFNA1, TLR4, CD40, TLR2, IL12A, IL12B, TLR9, CD1E, IFNG, and HLA-DPB1) correlated with different functional groups. Five main pathways were identified (FDR < 0.0001). High TLR7 expression levels were significantly associated with a lack of response to immunotherapy (p < 0.0001) and worse outcome in terms of both PFS (p < 0.001) and OS (p = 0.03). The multivariate analysis confirmed TLR7 RNA expression as an independent predictor for both poor PFS (HR = 2.97, 95% CI, 1.16-7.6, p = 0.023) and OS (HR = 2.2, 95% CI, 1-5.08, p = 0.049). In conclusion, a high TLR7 gene expression level was identified as an independent predictor for poor clinical benefits from ICI. These data could have important implications for the development of novel single/combinatorial strategies TLR-mediated for an efficient selection of "individualized" treatments for NSCLC in the era of immunotherapy.

Heterogeneous Off-Target Effects of Ultra-Low Dose Dimethyl Sulfoxide (DMSO) on Targetable Signaling Events in Lung Cancer In Vitro Models.

Targetable alterations in cancer offer novel opportunities to the drug discovery process. However, pre-clinical testing often requires solubilization of these drugs in cosolvents like dimethyl sulfoxide (DMSO). Using a panel of cell lines commonly used for in vitro drug screening and pre-clinical testing, we explored the DMSO off-target effects on functional signaling networks, drug targets, and downstream substrates. Eight Non-Small Cell Lung Cancer (NSCLC) cell lines were incubated with three concentrations of DMSO (0.0008%, 0.002%, and 0.004% v/v) over time. Expression and activation levels of 187 proteins, of which 137 were kinases and downstream substrates, were captured using the Reverse Phase Protein Array (RPPA). The DMSO effect was heterogeneous across cell lines and varied based on concentration, exposure time, and cell line. Of the 187 proteins measured, all were statistically different in at least one comparison at the highest DMSO concentration, followed by 99.5% and 98.9% at lower concentrations. Only 46% of the proteins were found to be statistically different in more than 5 cell lines, indicating heterogeneous response across models. These cell line specific alterations modulate response to in vitro drug screening. Ultra-low DMSO concentrations have broad and heterogeneous effects on targetable signaling proteins. Off-target effects need to be carefully evaluated in pre-clinical drug screening and testing.

High PD-L1/IDO-2 and PD-L2/IDO-1 Co-Expression Levels Are Associated with Worse Overall Survival in Resected Non-Small Cell Lung Cancer Patients.

Programmed death ligand 1 (PD-L1) expression is a predictive biomarker of the success of PD-1/PD-L1 inhibitor therapy for patients with advanced non-small cell lung cancer (NSCLC) but its role as a prognostic marker for early-stage resectable NSCLC remains unclear. We studied gene expression levels of immune-related genes PD-1, PD-L1, PD-L2, IDO-1, IDO-2 and INFγ in tumor tissue of surgically resected NSCLC and correlated the finding with clinicopathological features and patient outcomes. A total of 191 consecutive early-stage NSCLC patients who underwent curative pulmonary resection were studied. The mRNA expression levels of immune-related genes were evaluated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) using RT2 Profiler PCR Arrays (Qiagen). PD-1, PD-L2 and IDO-2 gene expression levels were significantly higher in patients with squamous histology (p = 0.001, p = 0.021 and p < 0.001; respectively). PD-1, PD-L1 and IDO-2 gene expression levels were significantly higher in patients with higher stage (p = 0.005, p = 0.048 and p = 0.002, respectively). The univariate analysis for recurrence-free survival (RFS) and overall survival (OS) showed that patients with higher levels of three-genes (PD-L1/PD-L2/INFγ) (hazard ratio (HR)) 1.90 (95% confidence interval (CI), 1.13-3.21), p = 0.015) were associated with a worse RFS, while patients with higher levels of both genes (PD-L1/IDO-2) or (PD-L2/IDO-1) were associated with a worse OS (HR 1.63 95% CI, 1.06-2.51, p = 0.024; HR 1.54 95% CI, 1.02-2.33, p = 0.04; respectively). The multivariate interaction model adjusted for histology and stage confirmed that higher levels of three genes (PD-L1/PD-L2/INFγ) were significantly associated with worse RFS (HR 1.98, p = 0.031) and higher levels of both genes (PD-L1/IDO-2) and (PD-L2/IDO-1) with worse OS (HR 1.98, p = 0.042, HR 1.92, p = 0.022). PD-L1/IDO-2 and PD-L2/IDO-1 co-expression high levels are independent negative prognostic factors for survival in early NSCLC. These features may have important implications for future immune-checkpoint therapeutic approaches.

The Economic Impact of Rectal Cancer: A Population-Based Study in Italy

Costs of cancer care are increasing worldwide, and sustainability of cancer burden is critical. In this study, the economic impact of rectal cancer on the Italian healthcare system, measured as public healthcare expenditure related to investigation and treatment of rectal cancer patients is estimated. A cross-sectional cohort of 9358 rectal cancer patients is linked, on an individual basis, to claims associated to rectal cancer diagnosis and treatments. Costs refer mainly to years 2010-2011 and are estimated by phase of care, as healthcare needs vary along the care pathway: diagnostic procedures are mainly provided in the first year, surveillance procedures are addressed to chronically ill patients, and end-of-life procedures are given in the terminal status. Clinical approaches and corresponding costs are specific by cancer type and vary by phase of care, stage at diagnosis, and age. Surgery is undertaken by the great majority of patients. Thus, hospitalization is the main cost driver. The evidence produced can be used to improve planning and allocation of healthcare resources. In particular, early diagnosis of rectal cancer is a gain in healthcare budget. Policies raising spreading of and adherence to screening plans, above all when addressed to people living in Southern Italy, should be strongly encouraged.

Mathematical Modeling and Robustness Analysis to Unravel COVID-19 Transmission Dynamics: The Italy Case.

This study started from the request of providing predictions on hospitalization and Intensive Care Unit (ICU) rates that are caused by COVID-19 for the Umbria region in Italy. To this purpose, we propose the application of a computational framework to a SEIR-type (Susceptible, Exposed, Infected, Removed) epidemiological model describing the different stages of COVID-19 infection. The model discriminates between asymptomatic and symptomatic cases and it takes into account possible intervention measures in order to reduce the probability of transmission. As case studies, we analyze not only the epidemic situation in Umbria but also in Italy, in order to capture the evolution of the pandemic at a national level. First of all, we estimate model parameters through a Bayesian calibration method, called Conditional Robust Calibration (CRC), while using the official COVID-19 data of the Italian Civil Protection. Subsequently, Conditional Robustness Analysis (CRA) on the calibrated model is carried out in order to quantify the influence of epidemiological and intervention parameters on the hospitalization rates. The proposed pipeline properly describes the COVID-19 spread during the lock-down phase. It also reveals the underestimation of new positive cases and the need of promptly isolating asymptomatic and presymptomatic cases. The results emphasize the importance of the lock-down timeliness and provide accurate predictions on the current evolution of the pandemic.

Prevalence and Spectrum of BRCA Germline Variants in Central Italian High Risk or Familial Breast/Ovarian Cancer Patients: A Monocentric Study.

Hereditary breast and ovarian cancers are mainly linked to variants in BRCA1/2 genes. Recently, data has shown that identification of BRCA variants has an immediate impact not only in cancer prevention but also in targeted therapeutic approaches. This prospective observational study characterized the overall germline BRCA variant and variant of uncertain significance (VUS) frequency and spectrum in individuals affected by breast (BC) or ovarian cancer (OC) and in healthy individuals at risk by sequencing the entire BRCA genes. Of the 363 probands analyzed, 50 (13.8%) were BRCA1/2 mutated, 28 (7.7%) at BRCA1 and 23 (6.3%) at BRCA2 gene. The variant c.5266dupC p.(Gln1756Profs) was the most frequent alteration, representing 21.4% of the BRCA1 variants and 12.0% of all variants identified. The variant c.6313delA p.(Ile2105Tyrfs) of BRCA2 was the most frequent alteration observed in 6 patients. Interestingly, two new variants were identified in BRCA2. In addition, 25 different VUS were identified; two were reported for the first time in BRCA1 and two in BRCA2. The number of triple-negative BCs was significantly higher in patients with the pathogenic BRCA1/2-variant (36.4%) than in BRCA1/2 VUS (16.0%) and BRCA1/2 wild-type patients (10.7%) (p < 0.001). Our study reveals that the overall frequency of BRCA germline variants in the selected high-risk Italian population is about 13.8%. We believe that our results could have significant implications for preventive strategies for unaffected BRCA-carriers and effective targeted treatments such as PARP inhibitors for patients with BC or OC.

Patterns of care and cost profiles of women with breast cancer in Italy: EPICOST study based on real world data.

OBJECTIVES: To estimate total direct health care costs associated to diagnosis and treatment of women with breast cancer in Italy, and to investigate their distribution by service type according to the disease pathway and patient characteristics. METHODS: Data on patients provided by population-based Cancer Registries are linked at individual level with data on health-care services and corresponding claims from administrative databases. A combination of cross-sectional approach and a threephase of care decomposition model with initial, continuing and final phases-of-care defined according to time occurred since diagnosis and disease outcome is adopted. Direct estimation of cancer-related costs is obtained. RESULTS: Study cohort included 49,272 patients, 15.2% were in the initial phase absorbing 42% of resources, 79.7% in the continuing phase absorbing 44% of resources and 5.1% in the final phase absorbing 14% of resources. Hospitalization was the most important cost driver, accounting for over 55% of the total costs. CONCLUSIONS: This paper represents the first attempt in Italy to estimate the economic burden of cancer at population level taking into account the entire disease pathway and using multiple current health care databases. The evidence produced by the study can be used to better plan resources allocation. The model proposed is replicable to countries with individual health care information on services and claims.

Application of conditional robust calibration to ordinary differential equations models in computational systems biology: a comparison of two sampling strategies.

Mathematical modelling is a widely used technique for describing the temporal behaviour of biological systems. One of the most challenging topics in computational systems biology is the calibration of non-linear models; i.e. the estimation of their unknown parameters. The state-of-the-art methods in this field are the frequentist and Bayesian approaches. For both of them, the performance and accuracy of results greatly depend on the sampling technique employed. Here, the authors test a novel Bayesian procedure for parameter estimation, called conditional robust calibration (CRC), comparing two different sampling techniques: uniform and logarithmic Latin hypercube sampling. CRC is an iterative algorithm based on parameter space sampling and on the estimation of parameter density functions. They apply CRC with both sampling strategies to the three ordinary differential equations (ODEs) models of increasing complexity. They obtain a more precise and reliable solution through logarithmically spaced samples.

What has changed in the epidemiology of skin melanoma in central Italy during the past 20 years?

The aim was to evaluate changes in skin melanoma incidence and mortality at a population level in central Italy over the past two decades. Skin melanoma incidence rate from 1994 to 2014, were retrieved from the Umbrian Cancer Registry (about 900 000 inhabitants). Changes from 1994-1999 to 2010-2014 in tumour and patient characteristics - sex, age (0-44, 45-64, ≥ 65 years), site (head and neck, trunk, limbs), morphology (superficial spreading, nodular, other), thickness (≤ 1, 1-2, 2-4, > 4) and stage I-II, III-IV - were evaluated. Trends in age-standardized incidence and mortality rates were evaluated as annual percent change. During the past two decades, melanoma incidence significantly increased in both sexes (+6%/year among men and +4%/year among women) and in all ages (0-44 years: + 4.7 and + 4.3; 45-64 years: + 6.1 and + 4.4; ≥65 years: + 6.6 and + 1.7), morphologies, except nodular, and stages. Mortality was stable among men and women. In the area, incidence increased for thin and thick melanoma, showing a true increase, whereas mortality did not increase. Therefore, although improvements in treatment and downstaging effect of early diagnosis have to be considered, a certain degree of overdiagnosis cannot be ruled out.

Use of Electronic Administrative Databases to Measure Quality Indicators of Breast Cancer Care: Experience of Five Regional Oncology Networks in Italy.

PURPOSE: Assuring quality of care, while maintaining sustainability, in complex conditions such as breast cancer (BC) is an important challenge for health systems. Here, we describe a methodology to define a set of quality indicators, assess their computability from administrative data, and apply them to a large cohort of BC cases. MATERIALS AND METHODS: Clinical professionals from the Italian Regional Oncology Networks identified 46 clinically relevant indicators of BC care; 22 were potentially computable using administrative data. Incident cases of BC diagnosed in 2016 in five Italian regions were identified using administrative databases from regional repositories. Each indicator was calculated through record linkage of anonymized individual data. RESULTS: A total of 15,342 incident BC cases were identified. Nine indicators were actually computable from administrative data (two structure and seven process indicators). Although most indicators were consistent with guidelines, for one indicator (blood tumor markers in the year after surgery, 44.2% to 64.5%; benchmark ≤ 20%), deviation was evident throughout the five regions, highlighting systematic overlooking of clinical recommendations. Two indicators (radiotherapy within 4 months after surgery if no adjuvant chemotherapy; 42% to 83.8%; benchmark ≥ 90%; and mammography 6 to 18 months after surgery, 55.1% to 72.6%; benchmark ≥ 90%) showed great regional variability and were lower than expected, possibly as result of an underestimation in indicator calculation by administrative data. CONCLUSION: Despite highlighting some limitations in the use of administrative data to measure health care performance, this study shows that evaluating the quality of BC care at a population level is possible and potentially useful for guiding quality improvement interventions.

Geospatial analysis of the influence of family doctor on colorectal cancer screening adherence.

BACKGROUND: Despite the well-recognised relevance of screening in colorectal cancer (CRC) control, adherence to screening is often suboptimal. Improving adherence represents an important public health strategy. We investigated the influence of family doctors (FDs) as determinant of CRC screening adherence by comparing each FDs practice participation probability to that of the residents in the same geographic areas using the whole population geocoded. METHODS: We used multilevel logistic regression model to investigate factors associated with CRC screening adherence, among 333,843 people at their first screening invitation. Standardized Adherence Rates (SAR) by age, gender, and socioeconomic status were calculated comparing FDs practices to the residents in the same geographic areas using geocoded target population. RESULTS: Screening adherence increased from 41.0% (95% CI, 40.8-41.2) in 2006-2008 to 44.7% (95% CI, 44.5-44.9) in 2011-2012. Males, the most deprived and foreign-born people showed low adherence. FD practices and the percentage of foreign-born people in a practice were significant clustering factors. SAR for 145 (21.4%) FDs practices differed significantly from people living in the same areas. Predicted probabilities of adherence were 31.7% and 49.0% for FDs with low and high adherence, respectively. DISCUSSION: FDs showed a direct and independent effect to the CRC screening adherence of the people living in their practice. FDs with significantly high adherence level could be the key to adherence improvement. IMPACT: Most deprived individuals and foreigners represent relevant targets for interventions in public health aimed to improve CRC screening adherence.

CRA toolbox: software package for conditional robustness analysis of cancer systems biology models in MATLAB.

BACKGROUND: In cancer research, robustness of a complex biochemical network is one of the most relevant properties to investigate for the development of novel targeted therapies. In cancer systems biology, biological networks are typically modeled through Ordinary Differential Equation (ODE) models. Hence, robustness analysis consists in quantifying how much the temporal behavior of a specific node is influenced by the perturbation of model parameters. The Conditional Robustness Algorithm (CRA) is a valuable methodology to perform robustness analysis on a selected output variable, representative of the proliferation activity of cancer disease. RESULTS: Here we introduce our new freely downloadable software, the CRA Toolbox. The CRA Toolbox is an Object-Oriented MATLAB package which implements the features of CRA for ODE models. It offers the users the ability to import a mathematical model in Systems Biology Markup Language (SBML), to perturb the model parameter space and to choose the reference node for the robustness analysis. The CRA Toolbox allows the users to visualize and save all the generated results through a user-friendly Graphical User Interface (GUI). The CRA Toolbox has a modular and flexible architecture since it is designed according to some engineering design patterns. This tool has been successfully applied in three nonlinear ODE models: the Prostate-specific Pten-/- mouse model, the Pulse Generator Network and the EGFR-IGF1R pathway. CONCLUSIONS: The CRA Toolbox for MATLAB is an open-source tool implementing the CRA to perform conditional robustness analysis. With its unique set of functions, the CRA Toolbox is a remarkable software for the topological study of biological networks. The source and example code and the corresponding documentation are freely available at the web site: http://gitlab.ict4life.com/SysBiOThe/CRA-Matlab .

Assessment of TILs, IDO-1, and PD-L1 in resected non-small cell lung cancer: an immunohistochemical study with clinicopathological and prognostic implications.

Several cancers, especially non-small cell lung cancer (NSCLC), are able to escape the immunosurveillance of tumor-infiltrating lymphocytes (TILs); among the molecules involved, the indoleamine 2,3-dioxygenase 1 (IDO-1) and the programmed cell death ligand-1 (PD-L1) play a crucial role. These aspects are of great interest in the current immunotherapeutic era, therefore the current study analyses the TILs, IDO-1, and PD-L1 interactions and their correlations with clinicopathological parameters and prognosis in NSCLC. One hundred ninety-three NSCLC surgical specimens, formalin-fixed, and paraffin-embedded were assessed for TILs density, TILs localization, IDO-1 (clone 4.16H1), and PD-L1 (clone E1L3N) immunohistochemical expressions. This data was correlated with clinicopathological parameters, disease free, and overall survivals. IDO-1 and PD-L1 high expressions were related to the solid pattern of adenocarcinomas (respectively p = 0.036 and p = 0.026); high PD-L1 expression was correlated with squamous histotype (p = 0.048). IDO-1 overexpression correlated with former smokers (p = 0.041), higher adenocarcinoma stages (p = 0.039), and with both higher TILs density and PD-L1 expression (respectively p = 0.025 and p = 0.0003). A better prognosis was associated with TILs intratumoral or mixed localizations (p = 0.029). TILs localization affects NSCLC prognosis; the higher expression of IDO-1 and PD-L1 in poorly differentiated and more aggressive lung adenocarcinomas, as well as the correlation between high PD-L1 expression and squamous cell histotype, confirm the more efficient immunoescaping of these NSCLC subgroups.

Immigration, screening, and cervical cancer incidence: an application of Age-Period-Cohort analysis.

Cervical cancer (CC) control is based on the implementation of effective screening programs. In the coming years, human papilloma virus vaccination coverage will contribute considerably toward cancer prevention. In Italy, where an organized screening program has been implemented, immigration from low/middle-income countries with a high prevalence of human papilloma virus infections has increased steadily over the last decades. To assess the impact of screening efforts in counteracting background changes, we analyzed the incidence trends of cervical intraepithelial neoplasia grade 3 carcinomas in situ (CIS) and invasive CC from 1994 to 2013 through an Age-Period-Cohort model using data of a regional population-based registry. Moreover, using Joinpoint regression, we compared the incidence of cervical lesions in native women with that observed in foreign-born women, highlighting the differences in age and screening status. The results indicate that the CC incidence trend decreased in Italian women (annual percent change = -2.7*%, 95% confidence interval = -4.3; -1.1), but increased (APC = 12.2*%, 95% confidence interval = 7.6; 17.0) in immigrants. For CIS, incidence rates show a growing trend in both groups, especially in women born abroad. For cancer, no marked changes in period-specific incidence rate ratios were detected until around 2000, when we found a slight decrease, followed by an increase. For CIS, we estimate an important upward trend in cohort-specific risks. The favorable effect of screening in preventing an increase in CC incidence has been counteracted by the progressive increase in immigrants from high-risk countries, where it is of increasing relevance to extend the use of vaccination.