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Epistolio S, Dazio G, Zaed I, Sahnane N, Cipriani D, Polinelli F, Barizzi J, Spina P, Stefanini FM, Cerati M, Balbi S, Mazzucchelli L, Sessa F, Pesce GA, Reinert M, Cardia A, Marchi F, Frattini M. Clinical Relevance and Interplay between miRNAs in Influencing Glioblastoma Multiforme Prognosis. Cells 2024; 13:276. [PMID: 38334668 PMCID: PMC10855153 DOI: 10.3390/cells13030276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/24/2024] [Accepted: 01/26/2024] [Indexed: 02/10/2024] Open
Abstract
Glioblastoma multiforme (GBM) is usually treated with surgery followed by adjuvant partial radiotherapy combined with temozolomide (TMZ) chemotherapy. Recent studies demonstrated a better survival and good response to TMZ in methylguanine-DNA methyltransferase (MGMT)-methylated GBM cases. However, approximately 20% of patients with MGMT-unmethylated GBM display an unexpectedly favorable outcome. Therefore, additional mechanisms related to the TMZ response need to be investigated. As such, we decided to investigate the clinical relevance of six miRNAs involved in brain tumorigenesis (miR-181c, miR-181d, miR-21, miR-195, miR-196b, miR-648) as additional markers of response and survival in patients receiving TMZ for GBM. We evaluated miRNA expression and the interplay between miRNAs in 112 IDH wt GBMs by applying commercial assays. Then, we correlated the miRNA expression with patients' clinical outcomes. Upon bivariate analyses, we found a significant association between the expression levels of the miRNAs analyzed, but, more interestingly, the OS curves show that the combination of low miR-648 and miR-181c or miR-181d expressions is associated with a worse prognosis than cases with other low-expression miRNA pairs. To conclude, we found how specific miRNA pairs can influence survival in GBM cases treated with TMZ.
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Affiliation(s)
- Samantha Epistolio
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
| | - Giulia Dazio
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
| | - Ismail Zaed
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
| | - Nora Sahnane
- Unit of Pathology, Department of Medicine and Technological Innovation, University of Insubria, ASST Sette Laghi, 21100 Varese, Italy; (N.S.); (M.C.); (F.S.)
| | - Debora Cipriani
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
| | - Francesco Polinelli
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
| | - Jessica Barizzi
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
| | - Paolo Spina
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
| | - Federico Mattia Stefanini
- Department of Environmental Science and Policy, Faculty of Science and Technology-ESP, University of Milan, 20122 Milan, Italy;
| | - Michele Cerati
- Unit of Pathology, Department of Medicine and Technological Innovation, University of Insubria, ASST Sette Laghi, 21100 Varese, Italy; (N.S.); (M.C.); (F.S.)
| | - Sergio Balbi
- Division of Neurological Surgery, Department of Biotechnology and Life Sciences, University of Insubria, ASST Sette Laghi, 21100 Varese, Italy;
| | - Luca Mazzucchelli
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
- Faculty of Biomedical Sciences, Università della Svizzera italiana, 6900 Lugano, Switzerland
| | - Fausto Sessa
- Unit of Pathology, Department of Medicine and Technological Innovation, University of Insubria, ASST Sette Laghi, 21100 Varese, Italy; (N.S.); (M.C.); (F.S.)
| | - Gianfranco Angelo Pesce
- Radiation Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6501 Bellinzona, Switzerland;
| | - Michael Reinert
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
- Faculty of Medicine, University of the Southern Switzerland, 6900 Lugano, Switzerland
| | - Andrea Cardia
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
| | - Francesco Marchi
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland; (I.Z.); (D.C.); (F.P.); (M.R.); (A.C.); (F.M.)
| | - Milo Frattini
- Laboratory of Genetics and Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale (EOC), 6900 Locarno, Switzerland; (S.E.); (G.D.); (J.B.); (P.S.); (L.M.)
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Valleggi L, Carella G, Perria R, Mugnai L, Stefanini FM. A Bayesian model for control strategy selection against Plasmopara viticola infections. Front Plant Sci 2023; 14:1117498. [PMID: 37546263 PMCID: PMC10399454 DOI: 10.3389/fpls.2023.1117498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 06/29/2023] [Indexed: 08/08/2023]
Abstract
Plant pathogens pose a persistent threat to grape production, causing significant economic losses if disease management strategies are not carefully planned and implemented. Simulation models are one approach to address this challenge because they provide short-term and field-scale disease prediction by incorporating the biological mechanisms of the disease process and the different phenological stages of the vines. In this study, we developed a Bayesian model to predict the probability of Plasmopara viticola infection in grapevines, considering various disease management approaches. To aid decision-making, we introduced a multi-attribute utility function that incorporated a sustainability index for each strategy. The data used in this study were derived from trials conducted during the production years 2018-2020, involving the application of five disease management strategies: conventional Integrated Pest Management (IPM), conventional organic, IPM with substantial fungicide reduction combined with host-defense inducing biostimulants, organic management with biostimulants, and the use of biostimulants only. Two scenarios were considered, one with medium pathogen pressure (Average) and another with high pathogen pressure (Severe). The results indicated that when sustainability indexes were not considered, the conventional IPM strategy provided the most effective disease management in the Average scenario. However, when sustainability indexes were included, the utility values of conventional strategies approached those of reduced fungicide strategies due to their lower environmental impact. In the Severe scenario, the application of biostimulants alone emerged as the most effective strategy. These results suggest that in situations of high disease pressure, the use of conventional strategies effectively combats the disease but at the expense of a greater environmental impact. In contrast to mechanistic-deterministic approaches recently published in the literature, the proposed Bayesian model takes into account the main sources of heterogeneity through the two group-level effects, providing accurate predictions, although precise estimates of random effects may require larger samples than usual. Moreover, the proposed Bayesian model assists the agronomist in selecting the most effective crop protection strategy while accounting for induced environmental side effects through customizable utility functions.
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Affiliation(s)
- Lorenzo Valleggi
- Department of Statistics, Computer Science, Application (DISIA), University of Florence, Florence, Italy
| | - Giuseppe Carella
- Department of Agronomy, Food, Environmental and Forestry (DAGRI), University of Florence, Florence, Italy
| | - Rita Perria
- Council for Agricultural Research and Economics, Research Centre for Viticulture and Enology, Arezzo, Italy
| | - Laura Mugnai
- Department of Agronomy, Food, Environmental and Forestry (DAGRI), University of Florence, Florence, Italy
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Epistolio S, Ramelli G, Ottaviano M, Crupi E, Marandino L, Biggiogero M, Maida PA, Ruinelli L, Vogl U, Mangan D, Pascale M, Cantù M, Ceschi A, Bernasconi E, Mazzucchelli L, Catapano C, Alimonti A, Garzoni C, Gillessen Sommer S, Stefanini FM, Franzetti-Pellanda A, Frattini M, Pereira Mestre R. P1245 Polymorphic Variants of HSD3B1 Gene Confer Different Outcome in Specific Subgroups of Patients Infected With SARS-CoV-2. Front Med (Lausanne) 2022; 8:793728. [PMID: 35874037 PMCID: PMC9302441 DOI: 10.3389/fmed.2021.793728] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/23/2021] [Indexed: 01/08/2023] Open
Abstract
Introduction: Severe respiratory syndrome coronavirus 2 (SARS-CoV-2) uses the androgen receptor (AR), through ACE2 receptor and TMPRSS2, to enter nasal and upper airways epithelial cells. Genetic analyses revealed that HSD3B1 P1245C polymorphic variant increases dihydrotestosterone production and upregulation of TMPRSS2 with respect to P1245A variant, thus possibly influencing SARS-CoV-2 infection. Our aim was to characterize the HSD3B1 polymorphism status and its potential association with clinical outcomes in hospitalized patients with COVID-19 in Southern Switzerland. Materials and Methods: The cohort included 400 patients hospitalized for COVID-19 during the first wave between February and May 2020 in two different hospitals of Canton Ticino. Genomic DNA was extracted from formalin-fixed paraffin-embedded tissue blocks, and HSD3B1 gene polymorphism was evaluated by Sanger sequencing. Statistical associations were verified using different test. Results:HSD3B1 polymorphic variants were not associated with a single classical factor related to worse clinical prognosis in hospitalized patients with SARS-CoV-2. However, in specific subgroups, HSD3B1 variants played a clinical role: intensive care unit admission was more probable in patients with P1245C diabetes compared with P1245A individuals without this comorbidity and death was more associated with hypertensive P1245A>C cases than patients with P1245A diabetes without hypertension. Discussion: This is the first study showing that HSD3B1 gene status may influence the severity of SARS-CoV-2 infection. If confirmed, our results could lead to the introduction of HSD3B1 gene status analysis in patients infected with SARS-CoV-2 to predict clinical outcome.
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Affiliation(s)
- Samantha Epistolio
- Laboratory of Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale, Locarno, Switzerland
- *Correspondence: Samantha Epistolio
| | - Giulia Ramelli
- Laboratory of Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale, Locarno, Switzerland
| | - Margaret Ottaviano
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Emanuele Crupi
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Laura Marandino
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Maira Biggiogero
- Clinic Research Unit, Clinica Luganese Moncucco, Lugano, Switzerland
| | - Pier Andrea Maida
- Clinic Research Unit, Clinica Luganese Moncucco, Lugano, Switzerland
- Clinic of Internal Medicine and Infectious Diseases, Clinica Luganese Moncucco, Lugano, Switzerland
| | - Lorenzo Ruinelli
- Informatics and Communication Technology, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Ursula Vogl
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Dylan Mangan
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Mariarosa Pascale
- Clinical Trial Unit, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Marco Cantù
- Institute of Laboratory Medicine, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Alessandro Ceschi
- Clinical Trial Unit, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Division of Clinical Pharmacology and Toxicology, Institute of Pharmacological Sciences of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
- Department of Clinical Pharmacology and Toxicology, University Hospital Zürich, Zürich, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Department of Medicine, Ente Ospedaliero Cantonale, Università della Svizzera italiana, Lugano, Switzerland
- Faculty of Medicine, Division of Biomedical Sciences, University of Geneva, Geneva, Switzerland
| | - Luca Mazzucchelli
- Laboratory of Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale, Locarno, Switzerland
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
| | - Carlo Catapano
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
- Faculty of Experimental Therapeutics, Institute of Oncology Research, Università della Svizzera italiana, Bellinzona, Switzerland
| | - Andrea Alimonti
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
- Department of Molecular Oncology, Institute of Oncology Research, Università della Svizzera italiana, Bellinzona, Switzerland
| | - Christian Garzoni
- Clinic of Internal Medicine and Infectious Diseases, Clinica Luganese Moncucco, Lugano, Switzerland
| | - Silke Gillessen Sommer
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
| | - Federico Mattia Stefanini
- Department of Enviromental Science and Policy, Faculty of Science and Technology-ESP, University of Milan, Milan, Italy
| | | | - Milo Frattini
- Laboratory of Molecular Pathology, Institute of Pathology, Ente Ospedaliero Cantonale, Locarno, Switzerland
| | - Ricardo Pereira Mestre
- Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Faculty of Experimental Therapeutics, Institute of Oncology Research, Università della Svizzera italiana, Bellinzona, Switzerland
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Roesel R, Epistolio S, Molinari F, Saletti P, De Dosso S, Valli M, Franzetti-Pellanda A, Deantonio L, Biggiogero M, Spina P, Popeskou SG, Cristaudi A, Mongelli F, Mazzucchelli L, Stefanini FM, Frattini M, Christoforidis D. A Pilot, Prospective, Observational Study to Investigate the Value of NGS in Liquid Biopsies to Predict Tumor Response After Neoadjuvant Chemo-Radiotherapy in Patients With Locally Advanced Rectal Cancer: The LiBReCa Study. Front Oncol 2022; 12:900945. [PMID: 35837093 PMCID: PMC9274270 DOI: 10.3389/fonc.2022.900945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
IntroductionCirculating tumor DNA (ctDNA) correlates with the response to therapy in different types of cancer. However, in patients with locally advanced rectal cancer (LARC), little is known about how ctDNA levels change with neoadjuvant chemoradiation (Na-ChRT) and how they correlate with treatment response. This work aimed to explore the value of serial liquid biopsies in monitoring response after Na-ChRT with the hypothesis that this could become a reliable biomarker to identify patients with a complete response, candidates for non-operative management.Materials and MethodsTwenty-five consecutive LARC patients undergoing long-term Na-ChRT therapy were included. Applying next-generation sequencing (NGS), we characterized DNA extracted from formalin-fixed paraffin embedded diagnostic biopsy and resection tissue and plasma ctDNA collected at the following time points: the first and last days of radiotherapy (T0, Tend), at 4 (T4), 7 (T7) weeks after radiotherapy, on the day of surgery (Top), and 3–7 days after surgery (Tpost-op). On the day of surgery, a mesenteric vein sample was also collected (TIMV). The relationship between the ctDNA at those time-points and the tumor regression grade (TRG) of the surgical specimen was statistically explored.ResultsWe found no association between the disappearance of ctDNA mutations in plasma samples and pathological complete response (TRG1) as ctDNA was undetectable in the majority of patients from Tend on. However, we observed that the poor (TRG 4) response to Na-ChRT was significantly associated with a positive liquid biopsy at the Top.ConclusionsctDNA evaluation by NGS technology may identify LARC patients with poor response to Na-ChRT. In contrast, this technique does not seem useful for identifying patients prone to developing a complete response.
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Affiliation(s)
- Raffaello Roesel
- Department of Visceral Surgery, Regional Hospital of Lugano, Ente Ospedaliero Cantonale, Lugano, Switzerland
- *Correspondence: Raffaello Roesel, ; Samantha Epistolio,
| | - Samantha Epistolio
- Istituto Cantonale di Patologia, Ente Ospedaliero Cantonale, Locarno, Switzerland
- *Correspondence: Raffaello Roesel, ; Samantha Epistolio,
| | - Francesca Molinari
- Istituto Cantonale di Patologia, Ente Ospedaliero Cantonale, Locarno, Switzerland
| | - Piercarlo Saletti
- Clinical Research Unit, Clinica Luganese Moncucco, Lugano, Switzerland
- Medical Oncology Clinic, Clinica Luganese Moncucco, Lugano, Switzerland
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
| | - Sara De Dosso
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
- Istituto Oncologico della Svizzera Italiana, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Mariacarla Valli
- Radiation Oncology Clinic, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | | | - Letizia Deantonio
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
- Radiation Oncology Clinic, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Maira Biggiogero
- Clinical Research Unit, Clinica Luganese Moncucco, Lugano, Switzerland
| | - Paolo Spina
- Istituto Cantonale di Patologia, Ente Ospedaliero Cantonale, Locarno, Switzerland
- Department of Health Sciences, University of Eastern Piedmont, Novara, Italy
| | - Sotirios Georgios Popeskou
- Department of Visceral Surgery, Regional Hospital of Lugano, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Alessandra Cristaudi
- Department of Visceral Surgery, Regional Hospital of Lugano, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Francesco Mongelli
- Department of Visceral Surgery, Regional Hospital of Lugano, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Luca Mazzucchelli
- Istituto Cantonale di Patologia, Ente Ospedaliero Cantonale, Locarno, Switzerland
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
| | | | - Milo Frattini
- Istituto Cantonale di Patologia, Ente Ospedaliero Cantonale, Locarno, Switzerland
| | - Dimitri Christoforidis
- Department of Visceral Surgery, Regional Hospital of Lugano, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
- Department of Visceral Surgery, Lausanne University Hospital, Lausanne, Switzerland
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Marchi F, Sahnane N, Cerutti R, Cipriani D, Barizzi J, Stefanini FM, Epistolio S, Cerati M, Balbi S, Mazzucchelli L, Sessa F, Pesce GA, Reinert M, Frattini M. The Impact of Surgery in IDH 1 Wild Type Glioblastoma in Relation With the MGMT Deregulation. Front Oncol 2020; 9:1569. [PMID: 32039032 PMCID: PMC6992596 DOI: 10.3389/fonc.2019.01569] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/27/2019] [Indexed: 11/13/2022] Open
Abstract
Object: The treatment of choice in glioblastoma (GBM) is the maximal surgical extent of resection (EOR) followed by adjuvant chemo-radiotherapy. Furthermore, methylguanine-DNA methyltransferase (MGMT) promoter methylation is associated with prolonged overall survival (OS) and progression free survival (PFS). The objective of the present study is correlate the biomolecular aspects in relation with EOR. Materials and methods: We analyzed a series of 116 patients with IDH-1 wild type GBM and different EOR (Gross Total Resection—GTR-, Partial Resection—PR- and Biopsy), treated with adjuvant chemo-radiotherapy. The MGMT status was analyzed in terms of promoter methylation and protein expression. Results: When GTR was possible, OS and PFS were significantly better compared to the other two groups (p = 0.001 and p = 0.035, respectively). MGMT methylation was significantly associated with better OS in the biopsy group (p = 0.022) and better OS and PFS in PR (p = 0.02 and p = 0.012, respectively), but not in the GTR group (p = 0.252 for OS, p = 0.256 for PFS) nor the PFS in the biopsy group (p = 0.259). MGMT protein expression levels do not show any association with OS and PFS, regardless of the type of surgery. Conclusions: Our study confirms the positive association of a safe maximal EOR with better OS and PFS, and indicates a positive prognostic value of MGMT methylation status only in case of the presence of residual tumor tissue. MGMT protein expression seems not to play a clinical role in relation with the type of surgery.
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Affiliation(s)
- Francesco Marchi
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Lugano, Switzerland
| | - Nora Sahnane
- Unit of Pathology, Department of Medicine and Surgery, University of Insubria-ASST Sette Laghi, Varese, Italy
| | - Roberta Cerutti
- Unit of Pathology, Department of Medicine and Surgery, University of Insubria-ASST Sette Laghi, Varese, Italy
| | - Debora Cipriani
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Lugano, Switzerland
| | | | | | | | - Michele Cerati
- Unit of Pathology, Department of Medicine and Surgery, University of Insubria-ASST Sette Laghi, Varese, Italy
| | - Sergio Balbi
- Division of Neurological Surgery, Department of Biotechnology and Life Sciences, University of Insubria-ASST Sette Laghi, Varese, Italy
| | | | - Fausto Sessa
- Unit of Pathology, Department of Medicine and Surgery, University of Insubria-ASST Sette Laghi, Varese, Italy
| | | | - Michael Reinert
- Service of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Lugano, Switzerland.,Faculty of Medicine, University of Bern, Bern, Switzerland
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Abstract
Univariate conditional models are of core importance in supporting medical reasoning, as they allow to decompose a joint probability distribution using the chain rule. Although several methods are available for the elicitation of the joint prior distribution of parameters when the response is a medical categorical variable, the case of a medical continuous response is typically difficult to address, because its sample space is often bounded to an interval and its relationship with explanatory variables may be not linear. In these situations, the elicitation of an informative prior distribution on parameters of a univariate conditional model is challenging, because some level of statistical training is required to a medical expert for interpreting parameters and for retrieving appropriate quantitative information about them. The task can be eased and made efficient by recognizing that physicians typically distinguish among values involving medically normal and pathological patient conditions on the grounds of their personal clinical experience. In this paper, we propose a Generalized Beta regression where parameter elicitation is performed by establishing a correspondence among measured values expressed as relative positions within intervals with a clinical interpretation, regardless the original scales of variables. Software implementing the elicitation procedure is freely available.
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Forcella M, Callegaro G, Melchioretto P, Gribaldo L, Frattini M, Stefanini FM, Fusi P, Urani C. Cadmium-transformed cells in the in vitro cell transformation assay reveal different proliferative behaviours and activated pathways. Toxicol In Vitro 2016; 36:71-80. [PMID: 27432484 DOI: 10.1016/j.tiv.2016.07.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 06/28/2016] [Accepted: 07/13/2016] [Indexed: 12/11/2022]
Abstract
The in vitro Cell Transformation Assay (CTA) is a powerful tool for mechanistic studies of carcinogenesis. The endpoint is the classification of transformed colonies (foci) by means of standard morphological features. To increase throughput and reliability of CTAs, one of the suggested follow-up activities is to exploit the comprehension of the mechanisms underlying cell transformation. To this end, we have performed CTAs testing CdCl2, a widespread environmental contaminant classified as a human carcinogen with the underlying mechanisms of action not completely understood. We have isolated and re-seeded the cells at the end (6weeks) of in vitro CTAs to further identify the biochemical pathways underlying the transformed phenotype of foci. Morphological evaluations and proliferative assays confirmed the loss of contact-inhibition and the higher proliferative rate of transformed clones. The biochemical analysis of EGFR pathway revealed that, despite the same initial carcinogenic stimulus (1μM CdCl2 for 24h), transformed clones are characterized by the activation of two different molecular pathways: proliferation (Erk activation) or survival (Akt activation). Our preliminary results on molecular characterization of cell clones from different foci could be exploited for CTAs improvement, supporting the comprehension of the in vivo process and complementing the morphological evaluation of foci.
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Affiliation(s)
- M Forcella
- Department of Biotechnology and Biosciences, University of Milan Bicocca, Piazza della Scienza 3, 20126 Milan, Italy
| | - G Callegaro
- Department of Earth and Environmental Sciences, University of Milan Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - P Melchioretto
- Department of Earth and Environmental Sciences, University of Milan Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - L Gribaldo
- Institute for Health and Consumer Protection, DG JRC, European Commission, Via Enrico Fermi 2749, 21027 Ispra, Varese, Italy
| | - M Frattini
- Istituto Cantonale di Patologia, Via in Selva 24, 6601 Locarno, Switzerland
| | - F M Stefanini
- Department of Statistics, Computer Science, Applications, University of Florence, Viale Morgagni 59, 50100 Florence, Italy
| | - P Fusi
- Department of Biotechnology and Biosciences, University of Milan Bicocca, Piazza della Scienza 3, 20126 Milan, Italy.
| | - C Urani
- Department of Earth and Environmental Sciences, University of Milan Bicocca, Piazza della Scienza 1, 20126 Milan, Italy.
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Callegaro G, Stefanini FM, Colacci A, Vaccari M, Urani C. An improved classification of foci for carcinogenicity testing by statistical descriptors. Toxicol In Vitro 2015; 29:1839-50. [DOI: 10.1016/j.tiv.2015.07.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 07/01/2015] [Accepted: 07/13/2015] [Indexed: 11/16/2022]
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Turco E, Vizzuso C, Franceschini S, Ragazzi A, Stefanini FM. The in vitro effect of gossypol and its interaction with salts on conidial germination and viability of Fusarium oxysporum sp. vasinfectum isolates. J Appl Microbiol 2008; 103:2370-81. [PMID: 18045422 DOI: 10.1111/j.1365-2672.2007.03503.x] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
AIMS To assess the effect of different concentrations of gossypol (0, 2, 4, 10 and 20 mg l(-1)) in combination with NaCl and Na(2)SO(4) (20 mS cm(-1)) on the conidial germination and viability of Fusarium oxysporum f.sp. vasinfectum (Fov). METHODS AND RESULTS A multinomial logistic model was developed to estimate the germination probability of Fov. The inhibitory effect was markedly evident at the two highest concentrations of gossypol; it varied among the isolates tested and with time, and it was attenuated by the presence of sodium salts. The inhibition was temporary as the germination probability increased after 8 h. Fluorescent staining revealed that gossypol either killed the conidia or retarded the elongation of the germ tubes. CONCLUSION Fov showed the ability to overcome gossypol inhibition over time, and the inhibitory effect is reduced under saline conditions. Differential responses among Fov isolates to the presence of gossypol suggest that gossypol tolerance is genetically determined in the pathogen. SIGNIFICANCE AND IMPACT OF THE STUDY This study suggests that selecting for high plant gossypol cultivars would have minimal effect on the overall Fov resistance of cotton. A new statistical model was developed to explore the statistical significance of plant-pathogen interactions.
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Affiliation(s)
- E Turco
- Dipartimento di Biotecnologie Agrarie, Sezione di Patologia vegetale, Università di Firenze, Florence, Italy.
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Abstract
MOTIVATION Molecular profiles (DNA fingerprints) may be used to allocate an individual of unknown membership to one among the known groups of a reference population. Time and costs of profile assessment may be reduced by identifying informative profile components (markers). RESULTS A genetic algorithm (GA) is proposed to identify promising candidate markers from a pilot experiment in which observations are supposed to be without measurement error. The analysis of simulated datasets suggests reasonable values for GA parameters and confirms that the GA finds components of the profile showing association with the considered groups. Our GA may be used to perform a first screening of candidate markers to be included in subsequent experiments. AVAILABILITY The 32-bit executable (Windows 95, 98 and NT) is available at http://www.ds.unifi.it/ approximately stefanin/bioinformatics.htm.
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Affiliation(s)
- F M Stefanini
- Department of Statistics G.Parenti, University of Florence, Viale Morgagni 59, 50134, Firenze, Italy.
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Abstract
Microsatellite loci have become important in population genetics because of their high level of polymorphism in natural populations, very frequent occurrence throughout the genome, and apparently high mutation rate. Observed repeat numbers (alleles size) in natural populations and expectations based on computer simulations suggest that the range of repeat numbers at a microsatellite locus is restricted. This range is a key parameter that should be properly estimated in order to proceed with calculations of divergence times in phylogenetic studies and to better investigate the within- and between-population variability. The 'plug-in' estimate of range based on the minimum and maximum value observed in a sample is not satisfactory because of the relatively large number of alleles in comparison with typical sample sizes. In this paper, a set of data from 30 dinucleotide microsatellite loci is analysed under the assumption of independence among loci. Bayesian inference on range for one locus is obtained by assuming that constraints on range values exist as sharp bounds. Closed-form calculations and robustness revealed by our analysis suggest that the proposed Bayesian approach might be routinely used by researchers to classify microsatellite loci according to the estimated value of their allelic range.
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Affiliation(s)
- F M Stefanini
- Department of Statistics G. Parenti, Università degli Studi di Firenze, Florence, Italy
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Stefanini FM, Camussi A. APLOGEN: an object-oriented genetic algorithm performing Monte Carlo optimization. Comput Appl Biosci 1993; 9:695-700. [PMID: 8143156 DOI: 10.1093/bioinformatics/9.6.695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Problem-solving and modelling within a biological context often need a level of descriptive accuracy that is unlikely to be capable of analytical treatment, especially if the mathematical background of the biologist is poor. Furthermore solver-model maintenance is often difficult without the availability of trained specialists. Better prospects are found in the genetic algorithm field. Genetic algorithms are a set of procedures formulated to solve complex problems without specifying rules for intermediate steps. This approach becomes feasible performing a Monte Carlo simulation of the natural evolution process, in which population improvement (search for solutions) in a considered environment (the specific problem domain) is achieved by following the genetic paradigm. Starting with a randomly constituted sample of individuals, drawn from the population of admissible values and expressed as binary strings, random mating brings about individuals of the next generation. Parents are chosen with a greater probability as the number of constraints violated by each individual becomes smaller. During the constitution of each generation the presence of some genetic operators causes the improvement of population diversity and its maintenance. Genetic operators are simple string transformation rules, generally independent of a specific context. We have developed the constant core of a minimal genetic algorithm, from which can be derived genetic problem-solvers in specific domains. An applicative example--a constrained matrix equation on signed integers--is also realized to show graphically the algorithm dynamics.
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Affiliation(s)
- F M Stefanini
- Istituto Agronomico per l'Oltremare, Ministero degli Affari Esteri, Florence, Italy
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