Abstract PD14-07: Association between biomarkers and response to pembrolizumab in patients with metastatic triple-negative breast cancer (mTNBC): Exploratory analysis from KEYNOTE-086
Notice bibliographique
Résumé
Abstract Background: In the phase 2 KEYNOTE-086 study (NCT02447003), pembrolizumab monotherapy had durable antitumor activity in a subset of patients with previously treated mTNBC (cohort A; n = 170) and in patients with previously untreated PD-L1-positive mTNBC (cohort B; n = 84). In this exploratory analysis of KEYNOTE-086, we evaluated the association between several biomarkers and response to pembrolizumab. Methods: Cohort A enrolled patients regardless of PD-L1 expression who had documented disease progression following ≥1 systemic therapy for metastatic disease. Cohort B enrolled patients with PD-L1-positive (combined positive score [CPS] ≥1) tumors who had not received prior systemic therapy for metastatic disease. Immunohistochemistry was used to measure PD-L1 CPS and CD8 density; H&E staining for percentage of stromal tumor infiltrating lymphocytes (sTILs); RNA-sequencing for 18-gene T-cell-inflamed gene expression profile (GEP), angiogenesis, and glycolysis signatures; and whole exome sequencing (paired tumor and germline) for TMB (TMB-H defined as ≥175 mut/exome), HRD-LOH (DNA damage), Signature 3, and APOBEC. Biomarkers were analyzed as continuous variables in cohorts A and B combined and individually. Area under the receiver operating characteristic curve was estimated between each biomarker and overall response rate (ORR). Wald test P-values were calculated using logistic regression adjusted for cohort and Eastern Cooperative Oncology Group performance status. Germline and somatic BRCA1/2 mutations were pooled; one-sided P-value was calculated using Fisher’s exact test. Spearman’s correlation was used for correlations. Results: Biomarker data were available in the following number of patients: 253 (99.6%; PD-L1), 204 (80.3%; CD8), 187 (73.6%; GEP), 171 (67.3%; TMB/HRD), 228 (89.8%; sTILs), 163 (64.2%; Signature 3/APOBEC), and 132 (52.0%; angiogenesis/glycolysis). When data from cohorts A and B were combined, PD-L1 CPS (median 2; IQR 0-10), CD8 (median 159; IQR 62-319), GEP (median -0.34; IQR -0.57 to -0.11), TMB (median 82 mut/exome; IQR 50-139), and sTILs (median 5; IQR 2-20) were significantly associated with ORR (Table). There were moderate correlations between PD-L1 and GEP (r = 0.532), PD-L1 and sTILs (r = 0.451), and GEP and sTILs (r = 0.490). No correlation was observed between TMB and PD-L1 (r = 0.038), GEP (r = -0.035), and sTILs (r = -0.031). When cohorts were combined, TMB was significantly associated with ORR, PFS, and OS after adjustment for PD-L1, GEP, CD8, or sTILs. HRD-LOH score, Signature 3, and APOBEC were not significantly associated with ORR (Table); P for BRCA1/2 was 0.2385. The angiogenesis signature was associated with lack of response while the glycolysis signature was associated with response to pembrolizumab (Table). Conclusions: In this exploratory biomarker analysis from KEYNOTE-086, higher levels of PD-L1, GEP, TMB, CD8 IHC, sTILs, and the glycolysis signature were associated with increased response to pembrolizumab monotherapy. These findings may help identify patients with mTNBC who are most likely to respond to pembrolizumab. Table. Association of Biomarkers as Continuous Variables With Pembrolizumab Objective ResponseBiomarkerCombined Cohorts AUCCombined Cohorts P*Combined Cohorts Multitest corrected PCohort A AUCCohort B AUCPD-L10.6740.040-0.5440.654GEP0.7480.003-0.8370.561TMB0.6270.007-0.5480.710CD8 IHC0.760.000020.000120.850.68sTILs0.6710.012-0.6320.641HRD0.3940.874-0.5220.316Signature 30.6830.072-0.6970.736APOBEC0.5280.537-0.6740.623Angiogenesis0.6770.0090.0450.6610.731Glycolysis0.6120.0090.0360.8590.459AUC, area under the curve.*One-sided P-values are shown for all biomarkers except for Signature 3 and APOBEC, for which 2-sided P-values are shown. Citation Format: Sherene Loi, Peter Schmid, Javier Cortes, David W. Cescon, Eric P. Winer, Deborah L. Toppmeyer, Hope S. Rugo, Michelino De Laurentiis, Rita Nanda, Hiroji Iwata, Ahmad Awada, Antoinette R. Tan, Roberto Salgado, Vassiliki Karantza, Petar Jelinic, Anran Wang, Lingkang Huang, Razvan Cristescu, Lakshman Annamalai, Jennifer Yearley, Jennifer Yearley, Sylvia Adams. Association between biomarkers and response to pembrolizumab in patients with metastatic triple-negative breast cancer (mTNBC): Exploratory analysis from KEYNOTE-086 [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD14-07.
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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 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 | 0,001 |
| 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 ».