Abstract 779: A phase I study of BI 754111, an anti-LAG-3 monoclonal antibody (mAb), in combination with BI 754091, an anti-PD-1 mAb: Biomarker analyses from the microsatellite stable metastatic colorectal cancer (MSS mCRC) cohort
Notice bibliographique
Résumé
Abstract Introduction: LAG3 is an immune checkpoint receptor, often co-expressed with PD-1 on immune cell surfaces. PD-1 and LAG-3 signaling contribute to immune cell exhaustion in the tumor microenvironment. Dual blockade of PD-1 and LAG-3 is thus expected to improve response versus PD-1 blockade alone. A dose escalation/expansion trial (NCT03156114) is evaluating BI 754111, an anti-LAG-3 mAb, plus BI 754091, an anti-PD-1 mAb, in patients (pts) with advanced solid tumors. Here, we report data in pts with MSS mCRC, for whom checkpoint inhibitors (CPIs) have shown limited activity. We broadly evaluated biomarkers to provide information on mode of action and for their potential to predict responses. Methods: In this dose expansion cohort, pts with PD-(L)1-naïve, previously treated MSS mCRC tumors were enrolled. Pre- and on-treatment tumor biopsies and blood samples for biomarker analyses were collected. Cytokines, including interferon-gamma (IFN-γ), were quantified in plasma samples by multiplexed and high-sensitivity immunoassays. Activated effector memory T cell and other peripheral blood mononuclear cell counts were determined by flow cytometry. PD-L1, LAG-3 and CD8 expression was determined by immunohistochemistry (IHC). Exploratory gene expression analyses to determine immuno-oncology (IO)-related markers were conducted. Results: 40 pts with MSS mCRC received BI 754111 600 mg in combination with BI 754091 240 mg every 3 weeks. Pts had received a median (range) of 3.5 (1–10) prior treatments. To date (Sep 2019), 3 (7.5%) pts achieved a partial response (PR) and 11 (27.5%) had stable disease (SD) as best response. Peripheral blood analysis showed treatment led to coordinated upregulation of pro-inflammatory cytokines in some pts. Pts with greater cytokine induction were more likely to have SD. Also, upregulation of activated CD8 effector memory T cells in peripheral blood was observed in many pts. IHC analysis indicated that, in tumors that had CD8 T cells and PD-L1 expression at the tumor periphery at baseline, treatment led to infiltration of CD8 T cells into the tumor and an increase in PD-L1 expression. Analyses of pre-treatment tumors suggested that high PD-L1 gene expression was associated with clinical benefit. In addition, a treatment-associated increase of the IFN-γ gene signature scores was observed, supporting a treatment-induced activation of the immune system in the tumor; the effect was more pronounced in pts with PR/SD versus those with progressive disease. LAG-3 IHC levels at baseline were not predictive of outcome in this anti-PD-(L)1 naïve setting. Conclusion: BI 754111 plus BI 754091 showed encouraging results in this IO-refractory MSS mCRC population. Biomarker analyses showed activation of the immune system in peripheral blood and the tumor, consistent with other CPIs. Citation Format: Johanna Bendell, Susanna V. Ulahannan, Quincy Chu, Manish Patel, Ben George, Aurélie Auguste, Theresia Leo-Kress, Kai Bernd Stadermann, Nicole Kraemer, Mabrouk Elgadi, Melissa Johnson. A phase I study of BI 754111, an anti-LAG-3 monoclonal antibody (mAb), in combination with BI 754091, an anti-PD-1 mAb: Biomarker analyses from the microsatellite stable metastatic colorectal cancer (MSS mCRC) cohort [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 779.
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».