Abstract PR03: Molecular profiling of advanced solid tumors at Princess Margaret Cancer Centre and patient outcomes with genotype-matched clinical trials
Notice bibliographique
Résumé
Abstract Background: IMPACT and COMPACT are ongoing clinical trials at Princess Margaret (PM) to match advanced solid tumor patients with actionable somatic mutations to clinical trials with investigational therapies [NCT01505400]. We compared the outcome of patients profiled at PM treated on genotype-matched versus genotype-unmatched clinical trials. Methods: Patients with advanced solid tumors treated at PM or collaborating local institutions with available formalin fixed paraffin-embedded (FFPE) tumor tissue were prospectively consented for molecular profiling during standard treatment. Only patients with ECOG performance status ≤1 who were considered therapeutic trial candidates by their treating oncologist were eligible. Following pathology review, tumor DNA from FFPE blocks or unstained slides was extracted and genotyped using a customized Sequenom SNP genotyping panel (23 genes, 279 mutations) or a targeted next generation sequencing (NGS) panel, either the Illumina MiSeq TruSeq Amplicon Cancer Panel (48 genes, 212 amplicons) or the Ion Proton Ampliseq Cancer Hotspot Panel version 2 (50 genes, 207 amplicons) with ≤500x coverage in a Clinical Laboratory Improvement Amendments (CLIA) certified laboratory. An annotated molecular profiling report with somatic variants classified according to clinical actionability was included in the patient's electronic medical record. Oncologists were provided with regular summary tables of their patients' molecular profiling results and mutation-specific clinical trial listings to facilitate genotype-matched trial enrolment. Results: From March 2012 to July 2014, 1893 patients were enrolled with gynaecological (22%), breast (18%), lung (18%) colorectal (17%), pancreatobiliary (8%), upper aerodigestive (6%), genitourinary (5%), and other (5%) cancers. Patients had received a median of 4 prior systemic treatments (range 1-23). Of 253 (13%) screen failures, 10% were for insufficient tissue and 3% for clinical deterioration or other reasons. Patients were more likely to have one or more somatic mutations identified by NGS testing [597/813 (73%); average 1.23 mutations/patient; range 0-9 mutations/patient] compared with SNP genotyping [341/827 (41%); average 0.46 mutations/patient; range 0-2 mutations/patient; p<0.0001]. After a median follow-up of 18 months, a total of 244 patients (13%) were treated on 287 therapeutic clinical trials, including 84 patients (4%) on 92 genotype-matched trials. There was no difference in the proportion of trial enrolment onto genotype-matched therapies between patients profiled on Sequenom compared with targeted NGS [63/176 (36%) vs 29/101 (29%); p=0.23). Patients with pancreatobiliary and upper aerodigestive tract cancers were least likely to be treated on genotype-matched trials. A higher proportion of patients enrolled in genotype-matched trials were treated in phase I studies (80%) compared with genotype-unmatched trials (45%; p<0.001). The overall response rate by RECIST version 1.1 was higher in patients treated on genotype-matched trials (20%) compared with genotype-unmatched trials (11%; p<0.04). Patients treated on genotype-matched trials were more likely to achieve a best response of any shrinkage in the sum of their target lesions (61%) compared with patients treated on genotype-unmatched trials (32%; p<0.001). Conclusions: Few advanced solid tumor patients enrolled in a prospective institutional molecular profiling program were subsequently treated on genotype-matched therapeutic trials. Compared with SNP genotyping, profiling with a broader NGS panel did not increase the likelihood of receiving treatment on a genotype-matched trial. In this non-randomized comparison, genotype-enrichment of early phase clinical trials was associated with an increased objective tumor response rate. Greater efforts should be made to expand opportunities for genotype-trial matching and further studies are needed to evaluate the clinical utility of targeted NGS profiling. This abstract is also presented as Poster 18. Citation Format: Philippe L. Bedard, Amit Oza, Blaise Clarke, Ming-Sound Tsao, Natasha B. Leighl, Eric X. Chen, Albiruni Razak, Hal K. Berman, Stefano Serra, Michael Roehrl, Nadia Califaretti, Mateya Trinkaus, Tong Zhang, Mahadeo A. Sukhai, Anca Milea, Aaron R. Hansen, Trevor J. Pugh, Tracy Stockley, Suzanne Kamel-Reid, Lillian L. Siu. Molecular profiling of advanced solid tumors at Princess Margaret Cancer Centre and patient outcomes with genotype-matched clinical trials. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr PR03.
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 | 0,011 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».