ROGER CHAMMAS
Projetos de Pesquisa
Unidades Organizacionais
Departamento de Radiologia, Faculdade de Medicina - Docente
LIM/05 - Laboratório de Poluição Atmosférica Experimental, Hospital das Clínicas, Faculdade de Medicina
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/05 - Laboratório de Poluição Atmosférica Experimental, Hospital das Clínicas, Faculdade de Medicina
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina - Líder
3 resultados
Resultados de Busca
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- Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk(2024) UENAL, Pelin; LU, Ye; BUENO-DE-MESQUITA, Bas; EIJCK, Casper H. J. van; TALAR-WOJNAROWSKA, Renata; SZENTESI, Andrea; GAZOULI, Maria; KREIVENAITE, Edita; TAVANO, Francesca; MALECKA-WOJCIESKO, Ewa; EROSS, Balint; OLIVERIUS, Martin; BUNDUC, Stefania; AOKI, Mateus Nobrega; VODICKOVA, Ludmila; BOGGI, Ugo; GIACCHERINI, Matteo; KONDRACKIENE, Jurate; CHAMMAS, Roger; PALMIERI, Orazio; THEODOROPOULOS, George E.; BIJLSMA, Maarten F.; BASSO, Daniela; MOHELNIKOVA-DUCHONOVA, Beatrice; SOUCEK, Pavel; IZBICKI, Jakob R.; KIUDELIS, Vytautas; VANELLA, Giuseppe; ARCIDIACONO, Paolo Giorgio; WLODARCZYK, Barbara; HACKERT, Thilo; SCHOETTKER, Ben; UZUNOGLU, Faik G.; BAMBI, Franco; GOETZ, Mara; HLAVAC, Viktor; BRENNER, Hermann; PERRI, Francesco; CARRARA, Silvia; LANDI, Stefano; HEGYI, Peter; DIJK, Frederike; MAIELLO, Evaristo; CAPRETTI, Giovanni; TESTONI, Sabrina Gloria Giulia; PETRONE, Maria Chiara; STOCKER, Hannah; ERMINI, Stefano; ARCHIBUGI, Livia; GENTILUOMO, Manuel; CAVESTRO, Giulia Martina; PEZZILLI, Raffaele; FRANCO, Gregorio Di; MILANETTO, Anna Caterina; SPERTI, Cosimo; NEOPTOLEMOS, John P.; MORELLI, Luca; VOKACOVA, Klara; PASQUALI, Claudio; LAWLOR, Rita T.; BAZZOCCHI, Francesca; KUPCINSKAS, Juozas; CAPURSO, Gabriele; CAMPA, Daniele; CANZIAN, FedericoGenome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 x 10-8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 x 10-7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 x 10-6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 x 10-5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.
- Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic(2024) RITTO, Ana Paula; ARAUJO, Adriana Ladeira de; CARVALHO, Carlos Roberto Ribeiro de; SOUZA, Heraldo Possolo De; FAVARETTO, Patricia Manga e Silva; SABOYA, Vivian Renata Boldrim; GARCIA, Michelle Louvaes; KULIKOWSKI, Leslie Domenici; KALLAS, Esper Georges; PEREIRA, Antonio Jose Rodrigues; COBELLO JUNIOR, Vilson; SILVA, Katia Regina; ABDALLA, Eidi Raquel Franco; SEGURADO, Aluisio Augusto Cotrim; SABINO, Ester Cerdeira; RIBEIRO JUNIOR, Ulysses; FRANCISCO, Rossana Pulcineli Vieira; MIETHKE-MORAIS, Anna; LEVIN, Anna Sara Shafferman; SAWAMURA, Marcio Valente Yamada; FERREIRA, Juliana Carvalho; SILVA, Clovis Artur; MAUAD, Thais; GOUVEIA, Nelson da Cruz; LETAIF, Leila Suemi Harima; BEGO, Marco Antonio; BATTISTELLA, Linamara Rizzo; DUARTE, Alberto Jose da Silva; SEELAENDER, Marilia Cerqueira Leite; MARCHINI, Julio; FORLENZA, Orestes Vicente; ROCHA, Vanderson Geraldo; MENDES-CORREA, Maria Cassia; COSTA, Silvia Figueiredo; CERRI, Giovanni Guido; BONFA, Eloisa Silva Dutra de Oliveira; CHAMMAS, Roger; BARROS FILHO, Tarcisio Eloy Pessoa de; BUSATTO FILHO, GeraldoIntroduction The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency.Methods At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output.Results Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19.Discussion Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.
- Expression data of FOS and JUN genes and FTIR spectra provide diagnosis of thyroid carcinoma(2024) QUEIROZ, Joao Paulo da Silva; PUPIN, Breno; BHATTACHARJEE, Tanmoy Tapobrata; UNO, Miyuki; CHAMMAS, Roger; KULCSAR, Marco Aurelio Vamondes; CANEVARI, Renata de AzevedoWe explore the feasibility of using FOS and JUN gene expression and ATR-FTIR for diagnosis of thyroid cancer. For the study, 38 samples (6 non-neoplastic (NN), 10 papillary thyroid carcinoma (PTC), 7 follicular thyroid carcinoma (FTC), and 15 benign tumors (BT) were subjected to RNA extraction followed by quantitative real time PCR (qRT-PCR) and 30 samples (5 NN, 9 PTC, 5 FTC, and 11 BT) were used for Attenuated Total Reflectance - Fourier Transform Infrared (ATR-FTIR) followed by multivariate analysis. Of the above, 20 samples were used for both gene expression and ATR-FTIR studies. We found FOS and JUN expression in malignant tumor samples to be significantly lower than NN and benign. ATR-FIR after multivariate analysis could identify the difficult to diagnose FTC with 93 % efficiency. Overall, results suggest the diagnostic potential of molecular biology techniques combined with ATR-FTIR spectroscopy in differentiated thyroid carcinomas (PTC and FTC) and BT.