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Your search keyword '"Bijlsma, M. F."' showing total 2 results
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2 results on '"Bijlsma, M. F."'

1. Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers.

Author

Mantini, G., Vallés, A. M., Le Large, T. Y. S., Capula, M., Funel, N., Pham, T. V., Piersma, S. R., Kazemier, G., Bijlsma, M. F., Giovannetti, E., and Jimenez, C. R.

Subjects
BIOMARKERS, PANCREATIC cancer, EPITHELIAL-mesenchymal transition, BIOLOGY, PROGNOSIS, GENES, HISTOCHEMISTRY, SYSTEMS biology
Abstract

Purpose: Despite extensive biological and clinical studies, including comprehensive genomic and transcriptomic profiling efforts, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with a poor survival and limited therapeutic options. The goal of this study was to assess co-expressed PDAC proteins and their associations with biological pathways and clinical parameters. Methods: Correlation network analysis is emerging as a powerful approach to infer tumor biology from omics data and to prioritize candidate genes as biomarkers or drug targets. In this study, we applied a weighted gene co-expression network analysis (WGCNA) to the proteome of 20 surgically resected PDAC specimens (PXD015744) and confirmed its clinical value in 82 independent primary cases. Results: Using WGCNA, we obtained twelve co-expressed clusters with a distinct biology. Notably, we found that one module enriched for metabolic processes and epithelial-mesenchymal-transition (EMT) was significantly associated with overall survival (p = 0.01) and disease-free survival (p = 0.03). The prognostic value of three proteins (SPTBN1, KHSRP and PYGL) belonging to this module was confirmed using immunohistochemistry in a cohort of 82 independent resected patients. Risk score evaluation of the prognostic signature confirmed its association with overall survival in multivariate analyses. Finally, immunofluorescence analysis confirmed co-expression of SPTBN1 and KHSRP in Hs766t PDAC cells. Conclusions: Our WGCNA analysis revealed a PDAC module enriched for metabolic and EMT-associated processes. In addition, we found that three of the proteins involved were associated with PDAC survival. [ABSTRACT FROM AUTHOR]

Published
2020
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2. Genetic Polymorphisms Involved in Mitochondrial Metabolism and Pancreatic Cancer Risk

Author

Raffaele Pezzilli, Pavel Vodicka, Andrea Párniczky, George Theodoropoulos, Renata Talar-Wojnarowska, Paolo Giorgio Arcidiacono, Ugo Boggi, Bálint Erőss, Ewa Małecka-Panas, Martin Oliverius, Daniele Campa, Rita T. Lawlor, Faik G. Uzunoglu, Maria Chiara Petrone, Livia Archibugi, Stefania Bunduc, Edita Kreivenaite, Beatrice Mohelnikova-Duchonova, Manuel Gentiluomo, Maria Liliana Piredda, Giulia Peduzzi, Thilo Hackert, Francesco Perri, Giuseppe Vanella, Olivier R. Busch, Hermann Brenner, Pavel Soucek, John P. Neoptolemos, Martin Schneider, Sabrina Gloria Giulia Testoni, Luca Morelli, Krzysztof Jamroziak, Federico Canzian, Daniela Basso, Silvia Carrara, Maria Gazouli, Juozas Kupcinskas, Konstantinos Georgiou, Xīn Gào, Claudio Pasquali, Cosimo Sperti, Evaristo Maiello, Vytautas Kiudelis, Mara Götz, Martin Loos, Gabriele Capurso, Francesca Bazzocchi, Martin Lovecek, Bas Bueno-de-Mesquita, Viktor Hlavac, Niccola Funel, Roel Vermeulen, Maarten F. Bijlsma, Anna Caterina Milanetto, Ye Lu, Giulia Martina Cavestro, Stefano Ermini, Andrea Szentesi, Jakob R. Izbicki, William Greenhalf, Francesca Tavano, Feng Guo, Marta Puzzono, Domenica Gioffreda, Péter Hegyi, Eithne Costello, Casper H.J. van Eijck, Stefano Landi, Peduzzi, G., Gentiluomo, M., Tavano, F., Arcidiacono, P. G., Ermini, S., Vodicka, P., Boggi, U., Cavestro, G. M., Capurso, G., Morelli, L., Milanetto, A. C., Pezzilli, R., Lawlor, R. T., Carrara, S., Lovecek, M., Soucek, P., Guo, F., Hackert, T., Uzunoglu, F. G., Gazouli, M., Parniczky, A., Kupcinskas, J., Bijlsma, M. F., Bueno-De-Mesquita, B., Vermeulen, R., van Eijck, C. H. J., Jamroziak, K., Talar-Wojnarowska, R., Greenhalf, W., Gioffreda, D., Petrone, M. C., Landi, S., Archibugi, L., Puzzono, M., Funel, N., Sperti, C., Piredda, M. L., Mohelnikova-Duchonova, B., Lu, Y., Hlavac, V., Gao, X., Schneider, M., Izbicki, J. R., Theodoropoulos, G., Bunduc, S., Kreivenaite, E., Busch, O. R., Malecka-Panas, E., Costello, E., Perri, F., Giulia Testoni, S. G., Vanella, G., Pasquali, C., Oliverius, M., Brenner, H., Loos, M., Gotz, M., Georgiou, K., Eross, B., Maiello, E., Szentesi, A., Bazzocchi, F., Basso, D., Neoptolemos, J. P., Hegyi, P., Kiudelis, V., Canzian, F., Campa, D., Surgery, CCA - Cancer biology and immunology, CCA - Imaging and biomarkers, Center of Experimental and Molecular Medicine, and AGEM - Amsterdam Gastroenterology Endocrinology Metabolism

Subjects
Mitochondrial DNA, Pancreatic ductal adenocarcinoma, Nuclear gene, endocrine system diseases, Epidemiology, Biology, SUSCEPTIBILITY, Polymorphism, Single Nucleotide, SDG 3 - Good Health and Well-being, Pancreatic cancer, medicine, Humans, 03.02. Klinikai orvostan, Genetic variability, Carcinoma, Pancreatic Ductal, Case-Control Studies, Genetic Variation, Genome, Mitochondrial, Mitochondria, Pancreatic Neoplasms, Polymorphism, GENOME-WIDE ASSOCIATION, Gene, Genetics, Genome, GENOME-WIDE ASSOCIATION, SUSCEPTIBILITY, Carcinoma, Single Nucleotide, Metabolism, medicine.disease, digestive system diseases, Mitochondrial, Oncology, Pancreatic Ductal
Abstract

Background: The mitochondrial metabolism has been associated with pancreatic ductal adenocarcinoma (PDAC) risk. Recent evidence also suggests the involvement of the genetic variability of the mitochondrial function in several traits involved in PDAC etiology. However, a systematic investigation of the genetic variability of mitochondrial genome (mtSNP) and of all the nuclear genes involved in its functioning (n-mtSNPs) has never been reported. Methods: We conducted a two-phase association study of mtSNPs and n-mtSNPs to assess their effect on PDAC risk. We analyzed 35,297 n-mtSNPs and 101 mtSNPs in up to 55,870 individuals (12,884 PDAC cases and 42,986 controls). In addition, we also conducted a gene-based analysis on 1,588 genes involved in mitochondrial metabolism using Multi-marker Analysis of GenoMic Annotation (MAGMA) software. Results: In the discovery phase, we identified 49 n-mtSNPs and no mtSNPs associated with PDAC risk (P < 0.05). In the second phase, none of the findings were replicated. In the gene-level analysis, we observed that three genes (TERT, SUGCT, and SURF1) involved in the mitochondrial metabolism showed an association below the Bonferroni-corrected threshold of statistical significance (P = 0.05/1588 = 3.1 × 10−5). Conclusions: Even though the mitochondrial metabolism might be involved in PDAC etiology, our results, obtained in a study with one of the largest sample sizes to date, show that neither n-mtSNPs nor mtSNPs are associated with PDAC risk. Impact: This large case–control study does not support a role of the genetic variability of the mitochondrial function in PDAC risk.

Published
2021

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