Abstract 2495: The metabolic secretome of cachexia inducing pancreatic ductal adenocarcinoma
Notice bibliographique
Résumé
Abstract Cachexia is an underexplored and yet devastating consequence of cancer that is the cause of 20% of all cancer related deaths1. Cachexia inducing tumors cause a ‘wasting away’ of the body. The condition is associated with poor treatment outcome2, fatigue, and extremely poor quality of life2,3. Because of the multi-factorial characteristics of this condition, it has been difficult to understand the mechanisms driving the impact of the tumor on body organs and the sequence of events that leads to this lethal condition. Here we have used 1H MRS to characterize the metabolic profile of tumor interstitial fluid (TIF) obtained from noncachexia (Panc1) and cachexia inducing (Pa04C) tumors to further understand the impact of the deranged metabolism of cachexia-inducing tumors on the tumor metabolic secretome. The human pancreatic cancer cell line, Panc1, was obtained from ATCC. The human pancreatic cancer cell line, Pa04C, was provided by Dr. Maitra4. Six to 8 week old male SCID mice were inoculated in both the right and left flank with cancer cells (5×106, Panc1 N=2, Pa04C N=2). We created a collection chamber to collect TIF. The chamber was implanted together with small tumor pieces harvested from the subcutaneous flank tumors, into the subcutaneous flank space of SCID mice (Panc1 N=8 and Pa04C N=6) until the tumor encompassed the chamber (4-5 weeks). The tumor was then removed and the tumor tissue and TIF were collected. To obtain control TIF, an empty chamber was implanted in the subcutaneous flank space of healthy mice. Dual phase solvent extraction was performed on tumor tissue. The water phase was separated, freeze dried, reconstituted in D2O PBS for spectral acquisition. All 1H MR spectra were acquired on an Avance III 750 MHz (17.6T) Bruker NMR spectrometer equipped with a 5 mm broad band inverse (BBI) probe. Spectral acquisition, processing and quantification were performed using TOPSPIN 2.1 software. Notable differences between Pa04C compared to Panc1 TIF or normal interstitial fluid were a significant decrease of polyunsaturated fatty acids (PUFA) and lipids, and formate, pyruvate, glutamine, and glucose. Lactate, glutamate, succinate, glycine and acetone significantly increased in Pa04C TIF compared to Panc1 TIF or normal interstitial fluid. These differences in TIF cannot be explained solely by the differences in the tumor metabolic profile. Our data provide new insights into changes in the metabolic secretome with induction of cachexia that may shed new light on the cachexia cascade, and identify metabolic strategies to reverse the syndrome. References: (1) Argiles, J. M., et al. Nature reviews. Cancer 2014, 14, 754-762. (2) Ozola Zalite, I., et al. Pancreatology 2015, 15, 19-24. (3) Fearon, K. C., et al. HPB (Oxford) 2010, 12, 323-324. (4) Penet, M. F., et al. Clinical Cancer Research 2015, 21, 386-395. Acknowledgment: This work was supported by NIH R01 CA193365, NIH P50CA013175 and NIH P30CA06973. Citation Format: Santosh K. Bharti, Paul T. Winnard, Louis Dore-Savard, Yelena Mironchik, Marie-France Penet, Zaver M. Bhujwalla. The metabolic secretome of cachexia inducing pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2495. doi:10.1158/1538-7445.AM2017-2495
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».