Abstract LB-173: Genome analysis informs chemotherapy decision-making in patients with advanced malignancies.
Notice bibliographique
Résumé
Abstract Background: Tumor heterogeneity poses a significant challenge to the success of treatment; tumors with similar histological features may have substantially different underlying biological drivers. Applying personal genomic information prospectively to assist in chemotherapy decision-making could result in more effective and efficient cancer treatment. Methods: Eligible subjects with incurable cancers for whom there are limited or no standard chemotherapy options, have a tumor biopsy and when possible a tissue matched normal sample plus “normal” blood samples taken specifically for genomic analysis. Archival specimens are concurrently analyzed to look for changes over time and with chemo and/or radiation. Samples are subject to both an Ampliseq amplicon cancer panel analysis and whole genome DNA and RNA sequencing. State-of-the-art bioinformatics approaches are used to identity genes with somatic variants, copy number variants, and expression changes. All variants are integrated into a pathway analysis to identify tumor specific biological processes that may be driving the tumor. These pathways are matched to the known drug databases and to manual literature reviews to identify drugs that may be useful or drugs that may be counter-indicated and a report is generated and discussed. Results: Between July 2012 and January 2013, 10 subjects (of 30 planned) have been enrolled; 3 cases of colorectal and 2 of breast, 1 each of squamous skin, squamous ethmoid sinus cancer, nasopharynx, lung, and one CLL-peripheral mantle cell cancer. The Ampliseq panel results have generally correlated well with whole genome and RNA sequencing results, although the panel, providing less comprehensive information albeit more rapidly, has not been as informative a modality for identifying candidate druggable driver events. And the case of ethmoid cancer was discovered to be a rare pediatric tumor, this was not identified by the panel. Each case had extensive pathway mapping and uncovered potential drug targets that would not have necessarily been considered without this analyses. To date, 3 subjects have initiated treatment based on the reports generated; the analyses are in process for the remaining cases. We also note that we observe significant genomic differences between the archival and fresh tumor materials. Conclusions: Initial results suggest that the information garnered from detailed genomic analysis can inform chemotherapy decision-making. The panel is adept at profiling the common abnormalities that are the target of many of the current generation of molecular targeted drugs; however the whole genome approach provides a comprehensive view of the genomic landscape providing more information on particular aberrant pathways affected and ideas for drug repositioning. For now we have elected to employ whole genome and transcriptome analysis in addition to an “oncogene panel” to both compare the relative utility of these two approaches and provide as comprehensive a view of candidate druggable driver events across patients to inform on the next generation of rapid panel designs. Citation Format: Janessa J. Laskin, Karen Gelmon, Howard Lim, Daniel Renouf, Stephen Yip, David Huntsman, Anna Tinker, Cheryl Ho, Erin D. Pleasance, Yvonne Li, Yaoqing Shen, Katayoon Kasaian, Richard Corbett, Karen Mungall, Yongjun Zhao, Andy Mungall, Jacquie Schein, Robyn Roscoe, Steven Jones, Marco Marra. Genome analysis informs chemotherapy decision-making in patients with advanced malignancies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-173. doi:10.1158/1538-7445.AM2013-LB-173
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».