Automated Author ProfileTakis, Panteleimon G
GiottoBiotech S.R.L., SestoFiorentino, Florence, Italy AND Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Faculty of Medicine, Imperial College London, London, United Kingdom
Takis, Panteleimon G
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.2 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This record contains data related to the article "Metabolome of Pancreatic Juice Delineates Distinct Clinical Profiles of Pancreatic Cancer and Reveals a Link between Glucose Metabolism and PD-1+ Cells". Better understanding of pancreatic diseases, including pancreatic ductal adenocarcinoma (PDAC), is an urgent medical need, with little advances in preoperative differential diagnosis, preventing rational selection of therapeutic strategies. The clinical management of pancreatic cancer patients would benefit from the identification of variables distinctively associated with the multiplicity of pancre- atic disorders. We investigated, by 1H nuclear magnetic resonance, the metabolomic fingerprint of pancreatic juice (the biofluid that collects pancreatic products) in 40 patients with different pancreatic diseases. Metabolic variables discriminated PDAC from other less aggressive pancreatic diseases and identified metabolic clusters of patients with distinct clinical behaviors. PDAC specimens were overtly glycolytic, with significant accumulation of lactate, which was probed as a disease-specific variable in pancreatic juice from a larger cohort of 106 patients. In human PDAC sections, high expression of the glucose transporter GLUT-1 correlated with tumor grade and a higher density of PD-1+ T cells, suggesting their accumulation in glycolytic tumors. In a preclinical model, PD-1+ CD8 tumor–infiltrating lymphocytes differentially infiltrat- ed PDAC tumors obtained from cell lines with different metabolic consumption, and tumors metabolically rewired by knocking down the phosphofructokinase (Pfkm) gene displayed a decrease in PD-1+ cell infiltration. Collectively, we introduced pancreatic juice as a valuable source of metabolic variables that could contri- bute to differential diagnosis. The correlation of metabolic markers with immune infiltration suggests that upfront evaluation of the metabolic profile of PDAC patients could foster the introduction of immunotherapeutic approaches for pancreatic cancer.
Authors
- Cortese, Nina ;
- Capretti, Giovanni ;
- Barbagallo, Marialuisa ;
- Rigamonti, Alessandra ;
- Takis, Panteleimon G ;
- Castino, Giovanni F ;
- Vignali, Debora ;
- Maggi, Giulia ;
- Gavazzi, Francesca ;
- Ridolfi, Cristina ;
- Nappo, Gennaro ;
- Donisi, Greta ;
- Erreni, Marco ;
- Avigni, Roberta ;
- Rahal, Daoud ;
- Spaggiari, Paola ;
- Roncalli, Massimo ;
- Cappello, Paola ;
- Novelli, Francesco ;
- Monti, Paolo ;
- Zerbi, Alessandro ;
- Allavena, Paola ;
- Mantovani, Alberto ;
- Marchesi, Federica
This record contains data related to the article "Metabolome of Pancreatic Juice Delineates Distinct Clinical Profiles of Pancreatic Cancer and Reveals a Link between Glucose Metabolism and PD-1+ Cells". Better understanding of pancreatic diseases, including pancreatic ductal adenocarcinoma (PDAC), is an urgent medical need, with little advances in preoperative differential diagnosis, preventing rational selection of therapeutic strategies. The clinical management of pancreatic cancer patients would benefit from the identification of variables distinctively associated with the multiplicity of pancre- atic disorders. We investigated, by 1H nuclear magnetic resonance, the metabolomic fingerprint of pancreatic juice (the biofluid that collects pancreatic products) in 40 patients with different pancreatic diseases. Metabolic variables discriminated PDAC from other less aggressive pancreatic diseases and identified metabolic clusters of patients with distinct clinical behaviors. PDAC specimens were overtly glycolytic, with significant accumulation of lactate, which was probed as a disease-specific variable in pancreatic juice from a larger cohort of 106 patients. In human PDAC sections, high expression of the glucose transporter GLUT-1 correlated with tumor grade and a higher density of PD-1+ T cells, suggesting their accumulation in glycolytic tumors. In a preclinical model, PD-1+ CD8 tumor–infiltrating lymphocytes differentially infiltrat- ed PDAC tumors obtained from cell lines with different metabolic consumption, and tumors metabolically rewired by knocking down the phosphofructokinase (Pfkm) gene displayed a decrease in PD-1+ cell infiltration. Collectively, we introduced pancreatic juice as a valuable source of metabolic variables that could contri- bute to differential diagnosis. The correlation of metabolic markers with immune infiltration suggests that upfront evaluation of the metabolic profile of PDAC patients could foster the introduction of immunotherapeutic approaches for pancreatic cancer.
Authors
- Cortese, Nina ;
- Capretti, Giovanni ;
- Barbagallo, Marialuisa ;
- Rigamonti, Alessandra ;
- Takis, Panteleimon G ;
- Castino, Giovanni F ;
- Vignali, Debora ;
- Maggi, Giulia ;
- Gavazzi, Francesca ;
- Ridolfi, Cristina ;
- Nappo, Gennaro ;
- Donisi, Greta ;
- Erreni, Marco ;
- Avigni, Roberta ;
- Rahal, Daoud ;
- Spaggiari, Paola ;
- Roncalli, Massimo ;
- Cappello, Paola ;
- Novelli, Francesco ;
- Monti, Paolo ;
- Zerbi, Alessandro ;
- Allavena, Paola ;
- Mantovani, Alberto ;
- Marchesi, Federica