Abstract 4819: Gene-expression profiles predict sorafenib efficacy in wild-type EGFR non-small cell lung cancer (NSCLC)
Notice bibliographique
Résumé
Abstract Background: Results from our Biomarkers-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) program suggest that patients with chemorefractory wild-type (wt) EGFR NSCLC including those with mutant KRAS may benefit from sorafenib. Using 3 different approaches, we tested the hypothesis that gene expression profiles from wild-type (wt) EGFR tumors may predict sorafenib efficacy by capturing effects on multiple targets. Material and Methods: Baseline tumor biopsies from 37 BATTLE patients (pts) with EGFR wt tumors and treated with sorafenib were profiled (Affymetrix Human Gene 1.ST), as well as 68 EGFR wt NSCLC cell lines with available IC50 to sorafenib (Illumina HumanWG-6 v3.0 expression beadchip). (i) We first developed an In vitro Sorafenib Signature (ISS). Correlation of IC50 with each individual probe expression level was computed. Most significant probes were summarized by the first principal component (PC), and correlated with IC50 of sorafenib. To validate the signature, the first PC was computed in BATTLE samples, and progression-free survival (PFS) of pts with high- vs. low-sensitivity signature was compared based on the median of the first PC. (ii) Alternatively, we developed a Clinical Sorafenib Signature (CSS) using BATTLE samples. We compared 23 (62%) pts who achieved 8-week disease control with 14 (38%) who did not (t-test). Most significant probesets were summarized by the first PC and PFS of pts with a high- vs. low-sensitivity signature were compared. To validate the signature, the first PC was computed in cell lines and correlated with IC50 of sorafenib. (iii) Finally, we tested a previously reported KRAS mutation gene expression signature derived by comparing genes differentially expressed in mutant vs. wt KRAS early stage resected lung adenocarcinomas, in 124 BATTLE samples including 24 mutant KRAS. Results: (i) The ISS included 50 probes. The first PC was correlated with the IC50 of sorafenib (rho = –0.71, P < 0.0001). The ISS was then tested in BATTLE and PFS was significantly different in pts with the high- (median PFS 3.61 months) vs. the low-sensitivity signature (median PFS 1.84 months, log-rank P = 0.0263). (ii) The CSS developed in BATTLE included 80 probesets summarized using the first PC. PFS was significantly different in pts with the high- vs. the low-sensitivity signature (log-rank P < 0.0001). The CSS was then tested in cell lines and the first PC was signicantly correlated with IC50 of sorafenib (rho = 0.24, P = 0.0483). (iii) Finally, the KRAS signature was significantly associated with KRAS mutation, but no association was observed with outcome in pts treated with sorafenib in BATTLE. Conclusion: We report 2 gene expression signatures, ISS and CSS, that predicted benefit from sorafenib in patients with chemorefractory NSCLC and in vitro sensitivity to sorafenib respectively. Further validation is planned in our ongoing BATTLE-2 program. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4819. doi:1538-7445.AM2012-4819
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 | 0,000 |
| 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) | 0,002 | 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 ».