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Munnia A, Bollati V, Russo V, Ferrari L, Ceppi M, Bruzzone M, Dugheri S, Arcangeli G, Merlo F, Peluso M. Traffic-Related Air Pollution and Ground-Level Ozone Associated Global DNA Hypomethylation and Bulky DNA Adduct Formation. Int J Mol Sci 2023; 24:ijms24032041. [PMID: 36768368 PMCID: PMC9916664 DOI: 10.3390/ijms24032041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/09/2023] [Accepted: 01/17/2023] [Indexed: 01/22/2023] Open
Abstract
Studies have indicated that air pollution, including surface-level ozone (O3), can significantly influence the risk of chronic diseases. To better understand the carcinogenic mechanisms of air pollutants and identify predictive disease biomarkers, we examined the association between traffic-related pollutants with DNA methylation alterations and bulky DNA adducts, two biomarkers of carcinogen exposure and cancer risk, in the peripheral blood of 140 volunteers-95 traffic police officers, and 45 unexposed subjects. The DNA methylation and adduct measurements were performed by bisulfite-PCR and pyrosequencing and 32P-postlabeling assay. Airborne levels of benzo(a)pyrene [B(a)P], carbon monoxide, and tropospheric O3 were determined by personal exposure biomonitoring or by fixed monitoring stations. Overall, air pollution exposure was associated with a significant reduction (1.41 units) in global DNA methylation (95% C.I. -2.65-0.04, p = 0.026). The decrement in ALU repetitive elements was greatest in the policemen working downtown (95% C.I. -3.23--0.49, p = 0.008). The DNA adducts were found to be significantly increased (0.45 units) in the municipal officers with respect to unexposed subjects (95% C.I. 0.02-0.88, p = 0.039), mainly in those who were controlling traffic in downtown areas (95% C.I. 0.39-1.29, p < 0.001). Regression models indicated an increment of ALU methylation at higher B(a)P concentrations (95% C.I. 0.03-0.60, p = 0.032). Moreover, statistical models showed a decrement in ALU methylation and an increment of DNA damage only above the cut-off value of 30 µg/m3 O3. A significant increment of 0.73 units of IL-6 gene methylation was also found in smokers with respect to non-smokers. Our results highlighted the role of air pollution on epigenetic alterations and genotoxic effects, especially above the target value of 30 µg/m3 surface-level O3, supporting the necessity for developing public health strategies aimed to reduce traffic-related air pollution molecular alterations.
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Affiliation(s)
- Armelle Munnia
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Valentina Bollati
- EPIGET Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20122 Milan, Italy
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Valentina Russo
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Luca Ferrari
- EPIGET Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20122 Milan, Italy
- Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Marcello Ceppi
- Clinical Epidemiology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
| | - Marco Bruzzone
- Clinical Epidemiology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
| | - Stefano Dugheri
- Laboratorio di Igiene e Tossicologia Industriale, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Giulio Arcangeli
- Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50121 Florence, Italy
| | - Franco Merlo
- Research and Statistics Infrastructure, Azienda Unità Sanitaria Locale, IRCCS, 42121 Reggio Emilie, Italy
| | - Marco Peluso
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
- Correspondence:
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Russo V, Lallo E, Munnia A, Spedicato M, Messerini L, D’Aurizio R, Ceroni EG, Brunelli G, Galvano A, Russo A, Landini I, Nobili S, Ceppi M, Bruzzone M, Cianchi F, Staderini F, Roselli M, Riondino S, Ferroni P, Guadagni F, Mini E, Peluso M. Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis. Cancers (Basel) 2022; 14:4012. [PMID: 36011003 PMCID: PMC9406544 DOI: 10.3390/cancers14164012] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/26/2022] [Accepted: 08/12/2022] [Indexed: 12/24/2022] Open
Abstract
Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.
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Affiliation(s)
- Valentina Russo
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Eleonora Lallo
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Armelle Munnia
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Miriana Spedicato
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Luca Messerini
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Romina D’Aurizio
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Elia Giuseppe Ceroni
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Giulia Brunelli
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Antonio Galvano
- Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Antonio Russo
- Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Ida Landini
- Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Stefania Nobili
- Department of Neurosciences, Imaging and Clinical Sciences, “G. D’Annunzio” Chieti-Pescara, 66100 Chieti, Italy
| | - Marcello Ceppi
- Clinical Epidemiology Unit, IRCCS-Ospedale Policlinico San Martino, 16131 Genova, Italy
| | - Marco Bruzzone
- Clinical Epidemiology Unit, IRCCS-Ospedale Policlinico San Martino, 16131 Genova, Italy
| | - Fabio Cianchi
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Fabio Staderini
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Mario Roselli
- Medical Oncology Unit, Department of Systems Medicine, Tor Vergata University, 00133 Rome, Italy
| | - Silvia Riondino
- Medical Oncology Unit, Department of Systems Medicine, Tor Vergata University, 00133 Rome, Italy
| | - Patrizia Ferroni
- BioBIM (InterInstitutional Multidisciplinary Biobank), IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Human Sciences & Quality of Life Promotion, San Raffaele Roma Open University, 00166 Rome, Italy
| | - Fiorella Guadagni
- BioBIM (InterInstitutional Multidisciplinary Biobank), IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Human Sciences & Quality of Life Promotion, San Raffaele Roma Open University, 00166 Rome, Italy
| | - Enrico Mini
- Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Marco Peluso
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
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Peluso M, Munnia A, Russo V, Galli A, Pala V, van der Schouw YT, Schulze MB, Weiderpass E, Tumino R, Saieva C, Exezarreta Pilar A, Aune D, Heath AK, Aglago E, Agudo A, Panico S, Petersen KEN, Tjønneland A, Cirera L, Rodriguez-Barranco M, Katzke V, Kaaks R, Ricceri F, Milani L, Vineis P, Sacerdote C. Cruciferous Vegetable Intake and Bulky DNA Damage within Non-Smokers and Former Smokers in the Gen-Air Study (EPIC Cohort). Nutrients 2022; 14:2477. [PMID: 35745207 PMCID: PMC9231287 DOI: 10.3390/nu14122477] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/09/2022] [Accepted: 06/13/2022] [Indexed: 02/06/2023] Open
Abstract
Epidemiologic studies have indicated that cruciferous vegetables can influence the cancer risk; therefore, we examined with a cross-sectional approach the correlation between the frequent consumption of the total cruciferous vegetables and the formation of bulky DNA damage, a biomarker of carcinogen exposure and cancer risk, in the Gen-Air study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. DNA damage measurements were performed in the peripheral blood of 696 of those apparently healthy without cancer controls, including 379 never-smokers and 317 former smokers from seven European countries by the 32P-postlabeling assay. In the Gen-Air controls, the median intake of cruciferous vegetables was 6.16 (IQR 1.16−13.66) g/day, ranging from 0.37 (IQR 0−6.00) g/day in Spain to 11.34 (IQR 6.02−16.07) g/day in the UK. Based on this information, participants were grouped into: (a) high consumers (>20 g/day), (b) medium consumers (3−20 g/day) and (c) low consumers (<3.0 g/day). Overall, low cruciferous vegetable intake was correlated with a greater frequency of bulky DNA lesions, including benzo(a)pyrene, lactone and quinone-adducts and bulky oxidative lesions, in the adjusted models. Conversely, a high versus low intake of cruciferous vegetables was associated with a reduction in DNA damage (up to a 23% change, p = 0.032); this was particularly evident in former smokers (up to a 40% change, p = 0.008). The Generalized Linear Regression models indicated an overall Mean Ratio between the high and the low consumers of 0.78 (95% confidence interval, 0.64−0.97). The current study suggests that a higher intake of cruciferous vegetables is associated with a lower level of bulky DNA adducts and supports the potential for cancer prevention strategies through dietary habit changes aimed at increasing the consumption of cruciferous vegetables.
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Affiliation(s)
- Marco Peluso
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy; (A.M.); (V.R.)
| | - Armelle Munnia
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy; (A.M.); (V.R.)
| | - Valentina Russo
- Research Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy; (A.M.); (V.R.)
| | - Andrea Galli
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50139 Florence, Italy;
| | - Valeria Pala
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, 20133 Milan, Italy;
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, 3508 GA Utrecht, The Netherlands;
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558 Nuthetal, Germany;
- Institute of Nutritional Science, University of Potsdam, 14558 Nuthetal, Germany
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, 69372 Lyon, France;
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research, AIRE ONLUS, 97100 Ragusa, Italy;
| | - Calogero Saieva
- Cancer Risk Factors and Life-Style Epidemiology Unit, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy;
| | - Amiano Exezarreta Pilar
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, 20014 San Sebastian, Spain;
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, 20014 San Sebastián, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Dagfinn Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; (D.A.); (A.K.H.); (E.A.)
| | - Alicia K. Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; (D.A.); (A.K.H.); (E.A.)
| | - Elom Aglago
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; (D.A.); (A.K.H.); (E.A.)
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Catalan Institute of Oncology-ICO, 08908 L’Hospitalet de Llobregat, Spain;
- Nutrition and Cancer Group, Epidemiology, Public Health, Cancer Prevention and Palliative Care Program, Bellvitge Biomedical Research Institute-IDIBELL, 08908 L’Hospitalet de Llobregat, Spain
| | - Salvatore Panico
- Department of Clinical Medicine and Surgery, Federico II University, 80138 Naples, Italy;
| | | | - Anne Tjønneland
- Danish Cancer Society Research Center, Diet, Cancer and Health, DK-2100 Copenhagen, Denmark; (K.E.N.P.); (A.T.)
- Department of Public Health, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Lluís Cirera
- Department of Epidemiology, Regional Health Council-IMIB–Arrixaca, 30120 Murcia, Spain;
- CIBER de Epidemiología y Salud Pública (CIBERESP), 28028 Madrid, Spain;
- Department of Social and Health Sciences, Murcia University, 30100 Murcia, Spain
| | - Miguel Rodriguez-Barranco
- CIBER de Epidemiología y Salud Pública (CIBERESP), 28028 Madrid, Spain;
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (V.K.); (R.K.)
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (V.K.); (R.K.)
| | - Fulvio Ricceri
- Department of Clinical and Biological Sciences, University of Turin, 10124 Turin, Italy; (F.R.); (L.M.)
- Unit of Cancer Epidemiology, Città Della Salute e Della Scienza University-Hospital and Center for Cancer Prevention (CPO), 10126 Turin, Italy;
| | - Lorenzo Milani
- Department of Clinical and Biological Sciences, University of Turin, 10124 Turin, Italy; (F.R.); (L.M.)
| | - Paolo Vineis
- MRC Centre for Environment and Health School of Public Health, Imperial College LondonSt Mary’s Campus, Norfolk Place, London W2 1PG, UK;
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città Della Salute e Della Scienza University-Hospital and Center for Cancer Prevention (CPO), 10126 Turin, Italy;
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A View on Polymerase Chain Reaction as an Outstanding Molecular Diagnostic Technique in Periodontology. BIOMED RESEARCH INTERNATIONAL 2021; 2021:9979948. [PMID: 34337068 PMCID: PMC8315861 DOI: 10.1155/2021/9979948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/11/2021] [Accepted: 07/13/2021] [Indexed: 12/12/2022]
Abstract
Objectives This study presents a discussion on the fundamentals of polymerase chain reaction (PCR) and its use as a diagnostic tool in periodontology. Materials and Methods A computer-aided as well as hand-made search in PubMed and Scopus indexed journals (relevant to the topic) was done by keywords of molecular technique in periodontology, PCR, applications of PCR, and PCR in periodontics. Only the papers in the English language and outlining PCR and its association with periodontology were collected and utilized to provide a succinct review. There was no limitation for publication time. Results The results of our search showed that PCR has turned into a standard in diagnosis in the field of periodontology. A variety of researches has demonstrated that its sensitive, and specific characteristics make it a quick and effective technique of recognition, identification, and quantification of microorganisms. Identification of various immunoinflammatory markers at the mRNA expression level as well as ascertaining gene-related polymorphisms can also be performed. Conclusions The mechanisms of periodontal disease can further become clarified using PCR. Clinical Relevance. PCR as a diagnostic method can play a main part in the validation of the clinical diagnosis of periodontal disease indicating the reason, pathogenesis, clinical steps, progress, and prognosis of the disease.
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