Abstract PS6-02: Spatially defined immune-related proteins and outcome in triple negative breast cancer in the FinXX trial and Mayo Clinic cohort
Notice bibliographique
Résumé
Abstract Background: Growing data established the pivotal role of preexisting immune response in triple negative breast cancer (TNBC). Conventionally, preexisting immune response can be evaluated by quantifying tumor infiltrating lymphocytes mainly in the stroma or gene expression analysis from the whole tumor section. Due to technical challenges with these conventional methods, limited data regarding specific subtypes and spatial distribution of these immune infiltrates are currently available. Methods: NanoString IO360 gene expression analysis and Digital Spatial Profiling (DSP) were used. DSP was used to quantify 29 immune-related proteins in stromal and tumor-enriched segments from 44 TNBC samples from the FinXX trial (NCT00114816) and 335 samples from the Mayo Clinic (MC) cohort of centrally reviewed TNBC (Leon-Ferre BCRT 2018). In FinXX trial, 22 patients with recurrence and 22 patients without recurrence were included. In MC cohort, 217/335 patients received adjuvant chemotherapy while 118 patients had surgery only without adjuvant chemotherapy. Regions were segmented based on pancytokeratin staining. The general linear model was used for statistical analysis of differential expression with recurrence free survival (RFS) as a categorical variable (recur yes or no). Kaplan-Meier (KM) estimates and Cox regression models were also used for analysis. Results: In the FinXX trial, there were 12 out of 29 proteins in tumor epithelial segments (intraepithelial) which were significantly expressed at higher levels among patients who were free of recurrence. These proteins include Beta-2 microglobulin, CD11c, CD20, CD40, CD56, CD8, Granzyme B, HLA-DR, ICOS, PD-L1, PD-L2, and TGFB1. In contrast, merely 5 out of 29 proteins in stromal segments were significantly differentially expressed in these 2 groups of patients. Granzyme B, IDO1, PD-L1, and PD-L2 in stroma were significantly higher and SMA was significantly lower in patients without recurrence. Using Cox regression models, intraepithelial CD56, CD40, and HLA-DR were significantly associated with outcome. When comparing between highest and lowest intraepithelial protein expression by tertile, intraepithelial CD56 (HR 0.12, 95%CI 0.03-0.39, p < 0.001), CD40 (HR 0.13, 95%CI 0.04-0.46, p = 0.002), and HLA-DR (HR 0.24, 95%CI 0.06-0.89, p = 0.032) were significantly associated with improved outcome. However, expression of these same proteins in stroma was not associated with outcome. Using KM estimates, intraepithelial CD56 (p < 0.0001), CD40 (p = 0.0006), and HLA-DR (p = 0.013) were also significantly associated with improved outcome. Nonetheless, RNA expression of these proteins by IO360 from whole tumor sections were not significantly associated with outcome (CD56 p = 0.27, CD40 p = 0.21, HLA-DR p = 0.48). Similar findings with DSP were observed in MC TNBC cohort. Comparing between the highest and lowest quartiles, there were significantly fewer patients who developed recurrence with high protein expression of intraepithelial CD56 (p < 0.001), CD40 (p = 0.002), and HLA-DR (p = 0.006). Conclusions: Using an in-depth analysis with spatially defined context, we identify that there were numerically more intraepithelial immune-related proteins associated with outcome compared to proteins in stroma. Specifically, intraepithelial CD56, CD40, and HLA-DR were significantly associated with improved outcome in both FinXX and MC TNBC cohorts. However, neither expression of these proteins in stroma nor RNA expression from whole tumor were associated with outcome. Our study highlights the impact of spatial biology and the importance of evaluating each potential biomarker in a spatially defined manner. Support: W81XWH-15-1-0292, BCRF 19-161, P50CA116201-9, P50CA015083 Citation Format: Saranya Chumsri, Jodi M. Carter, Yaohua Ma, Douglas Hinerfeld, Heather Ann Brauer, Sarah Warren, Torsten O. Nielsen, Karama Asleh, Heikki Joensuu, Edith A. Perez, Roberto A. Leon-Ferre, David W. Hillman, Judy C. Boughey, Minetta C. Liu, James N. Ingle, Krishna R. Kalari, Fergus J. Couch, Keith L. Knutson, Matthew P. Goetz, E. A. Thompson. Spatially defined immune-related proteins and outcome in triple negative breast cancer in the FinXX trial and Mayo Clinic cohort [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 PS6-02.
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 | 0,000 |
| 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 ».