Abstract B022: Precision medicine for the fusion protein driven cancer, fibrolamellar carcinoma (FLC): Beyond sequencing
Notice bibliographique
Résumé
Abstract Fibrolamellar carcinoma (FLC) is a rare, usually lethal primary liver tumor that affects children, adolescents and young adults. Sequencing of FLC tumors in hepatocytes reveals that in 99% of the patients there is one recurrent genomic alteration: A deletion of 400 kB. This produces DNAJB1::PRKACA, a fusion of the first exon of DNAJB1 with the 2nd – 10th exons of PRKACA, the catalytic subunit of protein kinase A (PKA). PKA exists as a holoenzyme of two catalytic subunits and two regulatory subunits. The regulatory subunit both inhibits the catalytic and localizes it in the cell. Calibrated mass spectrometry shows that in normal liver there is always an excess of regulatory>catalytic subunits, but in the adjacent FLC tumor tissue there is an excess of catalytic>regulatory subunits. Different biochemistry assays and proximity ligation reveal both free catalytic, unbound to regulatory subunits, and an increase of kinase activity in the tumor cells. Much of the increase of catalytic subunit is in the nucleus. Transducing primary human hepatocytes (PHH) with DNAJB1::PRKACA is sufficient to recapitulate the transcriptome of FLC tumors. Transduction of PHH with just the wt PRKACA is also sufficient to recapitulate the transcriptome of FLC tumors. Thus, just increasing the level of kinase is sufficient, there is nothing special about the fusion domain. From our tissue repository we have four patients who have a tumor that looks like FLC but does not have a fusion to the catalytic subunit. The only alteration in these patients is loss of regulatory subunit. The transcriptome of these patient tumors is indistinguishable from that of classic DNAJB1::PRKACA FLC in hepatocytes. Additionally, we have a few dozen patients who have either DNAJB1::PRKACA or another fusion, ATP1B1::PRKACA in the ductal cells of their liver (producing cholangiocarcinomas) or ductal cells of their pancreas (producing IOPN, Intraductal Oncolytic Pancreatic Neoplasms). The transcriptome of these patients clusters with the transcriptome of the FLC patients with DNAJB1::PRKACA in the hepatocytes. A functional precision medicine drug repurposing screen found that the EC50 of the response of freshly resected tumors from patients to a wide panel of drugs is the same as that of FLC patients with DNAJB1::PRKACA in their hepatocytes. Based on sequencing one could conclude that patients with deletion of regulatory subunit in the hepatocytes, or expression of DNAJB1::PRKACA in the hepatocytes, or expression of DNAJB1::PRKACA or ATP1B1::PRKACA in the cholangiocytes or pancreatic ductal cells are at least three distinct diseases. An analysis of the cell biological changes reveals that they all of an increase of the ratio of catalytic:regulatory subunit, they have an increase of catalytic subunit in the nucleus, and these all result in the same changes of transcriptome and the same drug-response profile. Thus, looking beyond sequencing to the cellular changes leads to a different conclusion, that maybe they should be considered the same disease. Citation Format: Sanford Simon, Mahsa Shirani, David Requena, Denise Ng, Gadi Lalazar, Solomon Levin, Michael S. Torbenson, Aatur D. Singhi, Henrik Molina, Charles M. Rice, Philip Coffino, Barbara A. Lyons. Precision medicine for the fusion protein driven cancer, fibrolamellar carcinoma (FLC): Beyond sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B022.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,014 |
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 ».