APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project

High Risk of Secondary Infections Following Thrombotic Complications in Patients With COVID-19

Background. This study’s primary aim was to evaluate the impact of thrombotic complications on the development of secondary infections. The secondary aim was to compare the etiology of secondary infections in patients with and without thrombotic complications. Methods. This was a cohort study (NCT04318366) of coronavirus disease 2019 (COVID-19) patients hospitalized at IRCCS San Raffaele Hospital between February 25 and June 30, 2020. Incidence rates (IRs) were calculated by univariable Poisson regression as the number of cases per 1000 person-days of follow-up (PDFU) with 95% confidence intervals. The cumulative incidence functions of secondary infections according to thrombotic complications were compared with Gray’s method accounting for competing risk of death. A multivariable Fine-Gray model was applied to assess factors associated with risk of secondary infections. Results. Overall, 109/904 patients had 176 secondary infections (IR, 10.0; 95% CI, 8.8–11.5; per 1000-PDFU). The IRs of secondary infections among patients with or without thrombotic complications were 15.0 (95% CI, 10.7–21.0) and 9.3 (95% CI, 7.9–11.0) per 1000-PDFU, respectively (P = .017). At multivariable analysis, thrombotic complications were associated with the development of secondary infections (subdistribution hazard ratio, 1.788; 95% CI, 1.018–3.140; P = .043). The etiology of secondary infections was similar in patients with and without thrombotic complications. Conclusions. In patients with COVID-19, thrombotic complications were associated with a high risk of secondary infections

sFEra APP: description and usability of a novel tablet application for executive functions training

Executive functions include functions such as planning, working memory, inhibition, mental flexibility, action monitoring and initiation, and are essential to carry out an independent everyday life. Individuals suffering from brain injury, such as a stroke, very commonly experience executive deficits that reduce the capacity to regain functional independence. In recent years, there has been a growing interest in developing tablet computer-based cognitive training programs for stroke patients. In this respect, we described and evaluated the usability of a novel tablet application (app) for executive function training, developed in the context of the MEMORI-net project, a cross-border Italy-Slovenia program for the rehabilitation of stroke patients. We conducted a pilot study with a non-clinical sample of 16 participants to obtain information about the usability of the app. Our descriptive analyses suggest that most users were satisfied with the overall experience and the app was highly usable, even with little previous experience with tablet applications. Acceptability and effectiveness will need to be evaluated in a clinical randomized controlled study

The Role of Diet and Lifestyle in Early-Onset Colorectal Cancer: A Systematic Review

The incidence of early-onset colorectal cancer, defined as colorectal cancer occurring in young adults under the age of 50, is increasing globally. Knowledge of the etiological factors in young adults is far from complete. Questionable eoCRCs’ exogenous factors are represented by processed meat, sugary drinks, alcohol, Western dietary pattern, overweight and obesity, physical inactivity, and smoking, though with heterogeneous results. Therefore, we performed a systematic review to summarize the current evidence on the role of diet and lifestyle as eoCRC risk factors. We systematically searched PubMed, Scopus, and EMBASE up to July 2021, for original studies evaluating diet, alcohol, physical activity, BMI, and smoking in eoCRC and included twenty-six studies. Indeed, the exogenous factors could represent modifiable key factors, whose recognition could establish areas of future interventions through public health strategies for eoCRC primary prevention. Additionally, we discussed the role of additional non-modifiable risk factors, and of epigenetic regulation and microbiota as mediators of the eoCRC triggered by diet and lifestyle

Production of Profibrotic Cytokines by Invariant NKT Cells Characterizes Cirrhosis Progression in Chronic Viral Hepatitis

Abstract Invariant (inv)NKT cells are a subset of autoreactive lymphocytes that recognize endogenous lipid ligands presented by CD1d, and are suspected to regulate the host response to cell stress and tissue damage via the prompt production of cytokines. We investigated invNKT cell response during the progression of chronic viral hepatitis caused by hepatitis B or C virus infection, a major human disease characterized by a diffused hepatic necroinflammation with scarring fibrotic reaction, which can progress toward cirrhosis and cancer. Ex vivo frequency and cytokine production were determined in circulating and intrahepatic invNKT cells from controls (healthy subjects or patients with nonviral benign or malignant focal liver damage and minimal inflammatory response) or chronic viral hepatitis patients without cirrhosis, with cirrhosis, or with cirrhosis and hepatocellular carcinoma. invNKT cells increase in chronically infected livers and undergo a substantial modification in their effector functions, consisting in the production of the type 2 profibrotic IL-4 and IL-13 cytokines, which characterizes the progression of hepatic fibrosis to cirrhosis. CD1d, nearly undetectable in noncirrhotic and control livers, is strongly expressed by APCs in cirrhotic ones. Furthermore, in vitro CD1d-dependent activation of invNKT cells from healthy donors elicits IL-4 and IL-13. Together, these findings show that invNKT cells respond to the progressive liver damage caused by chronic hepatitis virus infection, and suggest that these cells, possibly triggered by the recognition of CD1d associated with viral- or stress-induced lipid ligands, contribute to the pathogenesis of cirrhosis by expressing a set of cytokines involved in the progression of fibrosis

The Peptide ERα17p Is a GPER Inverse Agonist that Exerts Antiproliferative Effects in Breast Cancer Cells

International audienceThe inhibition of the G protein-coupled estrogen receptor (GPER) offers promising perspectives for the treatment of breast tumors. A peptide corresponding to part of the hinge region/AF2 domain of the human estrogen receptor α (ERα17p, residues 295-311) exerts anti-proliferative effects in various breast cancer cells including those used as triple negative breast cancer (TNBC) models. As preliminary investigations have evoked a role for the GPER in the mechanism of action of this peptide, we focused our studies on this protein using SkBr3 breast cancer cells, which are ideal for GPER evaluation. ERα17p inhibits cell growth by targeting membrane signaling. Identified as a GPER inverse agonist, it co-localizes with GPER and induces the proteasome-dependent downregulation of GPER. It also decreases the level of pEGFR (phosphorylation of epidermal growth factor receptor), pERK1/2 (phosphorylation of extracellular signal-regulated kinase), and c-fos. ERα17p is rapidly distributed in mice after intra-peritoneal injection and is found primarily in the mammary glands. The N-terminal PLMI motif, which presents analogies with the GPER antagonist PBX1, reproduces the effect of the whole ERα17p. Thus, this motif seems to direct the action of the entire peptide, as highlighted by docking and molecular dynamics studies. Consequently, the tetrapeptide PLMI, which can be claimed as the first peptidic GPER disruptor, could open new avenues for specific GPER modulators

Treatment Sequencing and Outcome of Chronic Lymphocytic Leukemia Patients Treated at Fondazione Policlinico Universitario Agostino Gemelli IRCCS: A Thirty-Year Single-Center Experience

Background: This monocentric retrospective study describes the treatment patterns and outcomes of chronic lymphocytic leukemia (CLL) patients. Methods: Adult CLL patients treated between 1992 and 2022 were included. The time to next treatment (TTNT) was defined as the time from the treatment’s start to the start of a subsequent therapy or death. The time to next treatment failure or death (TTNTF) was defined as the time from treatment discontinuation to the discontinuation of a subsequent therapy or death. Results: Of 637 registered patients, 318 (49.9%) received treatment. We evaluated 157 cBTKi-exposed, 34 BCL2i-exposed cBTKi-naïve, and 26 double-exposed patients. The five-year TTNT values in the cBTKi-exposed patients were 80% (median NR), 40% (median 40 months), and 21% (median 24 months) months in the first line (1L), second line (2L), and beyond the second line (>2L), respectively (p 2L, respectively (p = 0.185). The median TTNTF was 9 months (range 1–87) after cBTKi and 17 months (range 8–49) after both a cBTKi and BCL2i. Conclusions: This study suggests that, in CLL patients, the earlier we used targeted therapies, the better was the outcome obtained. Nonetheless, the poor outcomes in the advanced lines of therapy highlight the need for more effective treatments

GPER Mediates a Feedforward FGF2/FGFR1 Paracrine Activation Coupling CAFs to Cancer Cells Toward Breast Tumor Progression

The FGF2/FGFR1 paracrine loop is involved in the cross-talk between breast cancer cells and components of the tumor stroma as cancer-associated fibroblasts (CAFs). By quantitative PCR (qPCR), western blot, immunofluorescence analysis, ELISA and ChIP assays, we demonstrated that 17β-estradiol (E2) and the G protein estrogen receptor (GPER) agonist G-1 induce the up-regulation and secretion of FGF2 via GPER together with the EGFR/ERK/c-fos/AP-1 signaling cascade in (ER)-negative primary CAFs. Evaluating the genetic alterations from METABRIC and TCGA datasets, we then assessed that FGFR1 is the most frequently amplified FGFRs family member and its amplification/expression associates with shorter survival rates in breast cancer patients. Therefore, in order to assess the functional FGF2/FGFR1 interplay between CAFs and breast cancer cells, we generated the FGFR1-knockout MDA-MB-231 cells using CRISPR/Cas9 genome editing strategy. Using conditioned medium from estrogen-stimulated CAFs, we established that the activation of FGF2/FGFR1 paracrine signaling triggers the expression of the connective tissue growth factor (CTGF), leading to the migration and invasion of MDA-MB-231 cells. Our findings shed new light on the role elicited by estrogens through GPER in the activation of the FGF2/FGFR1 signaling. Moreover, our findings may identify further biological targets that could be considered in innovative combination strategies halting breast cancer progression

CT and MRI radiomic features of lung cancer (NSCLC): comparison and software consistency

Abstract Background Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques. Methods Contrast-enhanced CT and MRI images of 35 patients affected with non-small cell lung cancer (NSCLC) were manually segmented and preprocessed using three different methods. Sixty-six Image Biomarker Standardisation Initiative-compliant features common to the considered platforms, PyRadiomics and LIFEx, were extracted. The correlation among features with the same mathematical definition was analyzed by comparing PyRadiomics and LIFEx (at fixed imaging technique), and MRI with CT results (for the same software). Results When assessing the agreement between LIFEx and PyRadiomics across the considered resampling, the maximum statistically significant correlations were observed to be 94% for CT features and 95% for MRI ones. When examining the correlation between features extracted from contrast-enhanced CT and MRI using the same software, higher significant correspondences were identified in 11% of features for both software. Conclusions Considering NSCLC, (i) for both imaging techniques, LIFEx and PyRadiomics agreed on average for 90% of features, with MRI being more affected by resampling and (ii) CT and MRI contained mostly non-redundant information, but there are shape features and, more importantly, texture features that can be singled out by both techniques. Relevance statement Identifying and selecting features that are stable cross-modalities may be one of the strategies to pave the way for radiomics clinical translation. Key points • More than 90% of LIFEx and PyRadiomics features contain the same information. • Ten percent of features (shape, texture) are stable among contrast-enhanced CT and MRI. • Software compliance and cross-modalities stability features are impacted by the resampling method. Graphical Abstrac