Abstract CT011: Circulating tumor DNA (ctDNA) sequencing for <i>HER2</i> mutation (<i>HER2</i>mut) screening and response monitoring to neratinib in metastatic breast cancer (MBC)
Notice bibliographique
Résumé
Abstract Introduction: MutHER is a phase II trial that demonstrated the anti-tumor activity of the pan-HER inhibitor neratinib in HER2mut, non-amplified MBC. The major challenges to accrue to this trial were the large number of pts to screen for the 2-3% HER2mut population and the high rate (24%) of poor quality tumor DNA for sequencing. The goals of this ctDNA study were: 1) the concordance of HER2mut detected by ctDNA versus tumor testing; 2) the incidence of ctDNA HER2mut in HER2 non-amplified MBC; 3) changes in HER2mut variant allele frequency (VAF) on neratinib therapy. Methods: A sample size of 30 negative (neg) controls was needed to ensure 90% confidence if ctDNA testing has >90% specificity in detecting HER2mut. Thus, plasma from MBC pts obtained at screening for MutHER trial (Neg control: 40 pts without HER2mut on tumor testing; Positive (pos) control: 14 pts with known HER2mut who received neratinib) were subjected to Guardant360 ctDNA 70-gene panel sequencing (all exons of HER2 included). ctDNA from the 14 neratinib treated pts were also analyzed at week (wk) 4 and upon progression. ctDNA data from MBC pts clinically tested at Guardant Health were interrogated for HER2mut incidence. Results: Among the 14 pts with tumor pos for HER2mut, ctDNA sequencing identified the same HER2mut in 11, discrepant HER2mut in 1, and neg in 2. The 2 pts with ctDNA neg for HER2mut had progressive disease (PD) and stable disease (SD > 6 months) on neratinib, respectively. Among the 40 neg controls, 8 were not evaluable (no detectable ctDNA or assay unsuccessful) and all 32 successfully sequenced cases were neg for HER2mut. The sensitivity and specificity of ctDNA for HER2mut detection was 11/14 (79%, 90% CI: 53-94%) and 32/32 (100%, 90% CI: 91-100%), respectively. Among the 11 paired baseline and wk 4 samples, 9 (82%) had lower HER2mut VAFs at wk 4 than at baseline, with 1 complete response (CR), 1 partial response (PR), 5 SD, and 4 PD at wk 8 as best tumor response. Two pts had higher wk 4 ctDNA HER2mut VAFs and both had radiographic PD at wk 8. The absolute HER2mut VAF levels at wk 4 were significantly associated with TTP (Spearman rho=-0.69, p=0.02) and tumor size change (rho=0.67, p=0.05). The HER2mut VAFs were significantly higher at progression than wk 4 in all pts (p<0.01). One pt acquired a new HER2mut T798I, which is analogous to the gate-keeper mutation EGFR T790M. The incidence of HER2mut without amplification in unselected consecutive MBC clinically tested by Guardant360 was 3% (48/1,584), with mutation pattern similar to published tumor testing data. Conclusions: ctDNA sequencing is sensitive and highly specific in detecting HER2mut, offering a non-invasive method to identify pts for trials of HER2mut-targeted therapy. Decreased HER2mut VAFs at wk 4 was observed in 82% of cases, consistent with the on-target effect of neratinib. Increased HER2mut VAFs at wk 4 is a potential early marker of progression. Citation Format: Cynthia Ma, Ron Bose, Feng Gao, Rachel Freedman, Melinda Telli, Gretchen Kimmick, Eric Winer, Michael Naughton, Matthew Goetz, Christy Russell, Debu Tripathy, Melody Cobleigh, Andres Forero, Timothy Pluard, Carey Anders, Shana Thomas, Jill Anderson, Caroline Bumb, Kimberly Banks, Richard Lanman, Richard Bryce, Alshad Lalani, John Pfeifer, Daniel Hays, Mark Pegram, Kimberly Blackwell, Philippe Bedard, Hussam Al-Kateb, Matthew Ellis. Circulating tumor DNA (ctDNA) sequencing for HER2 mutation (HER2mut) screening and response monitoring to neratinib in metastatic breast cancer (MBC) [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 CT011. doi:10.1158/1538-7445.AM2017-CT011
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 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».