Abstract 67: Predicting colorectal patient prognoses by functional characterisation of heterogeneous cell types and their spatial interaction using a new technique: Whole slide imaging mass cytometry
Notice bibliographique
Résumé
Abstract Immunotherapies stimulate T cell function in the tumor microenvironment (TME). CD3+ and CD8+ T cell infiltration can predict disease recurrence in colorectal cancer (CRC) patients and has been validated as Immunoscore® (IS). The TME comprises multiple heterogeneous populations of immune cells, including T cells and cancer-associated fibroblasts (CAFs); CRC tumors are also morphologically diverse. Standard BioTools™ (SBI) has developed a novel whole slide Imaging Mass Cytometry™ technique that allows complete analysis of cell population heterogeneity in the TME using >40 markers. We hypothesised there are multiple heterogeneous subtypes of CAFs within CRC tumors and that they modulate T cell infiltration and patient outcome. In collaboration with SBI, we studied a cohort of CRC patients stratified based on T cell infiltrate and disease recurrence. We identified multiple CAF populations that interact with tumor-infiltrating T cell populations. Slides from 10 CRC patients with high or low CD3+CD8+ T cell infiltrate (IS) were stained with a panel encompassing markers for CAF and T cell heterogeneity, function, and metabolism. Slides were imaged using the Hyperion XTi™ Imaging System at SBI. Using a scan mode called Preview Mode, the whole slide was imaged in minutes to identify CAF and T cell phenotypic regions of interest. Next, the same slide was imaged at 1 μm resolution using Cell Mode (CM). Finally, for each sample, an additional serial section was imaged using a slightly lower resolution called Tissue Mode (TM). TM allowed us to image the samples in several hours instead of days while capturing the full heterogeneity of the entire tissue sample. We used clustering to identify phenotype clusters and neighbourhood analysis to study spatial enrichment. We also compared results between CM and TM. We report: Identification of heterogeneous CAF subtypes in CRC patients with high or low IS; determination of CAF populations that spatially interact with T cells in patients with high or low IS; and examination of consistent spatial interactions between CAF and T cells in CRC, and whether these interactions differ in patients with high or low IS. TM revealed several heterogeneous cellular populations that differed between patients with high or low IS; importantly, low IS tumors had more podoplanin+αSMA+ CAF populations and fewer podoplanin+αSMA- cell populations compared with high IS tumors. High IS tumors had more PD-1+CD8+ T cells compared with low IS tumors; these PD-1+CD8+ T cells spatially interacted with podoplanin+αSMA- CAF populations in high IS tumors. CAF-PD-1+CD8+ T cell interactions were absent from low IS tumors. Thus, CAF-PD-1+CD8+ T cell interactions are important in CRC patients with high IS, and these cellular interactions require further investigation. Citation Format: Rory M. Costello, Sonya Fenton, Helen McGuire, Liang Lim, David Howell, Qanber Raza, Jyh Yun Chwee, Roslyn Kemp. Predicting colorectal patient prognoses by functional characterisation of heterogeneous cell types and their spatial interaction using a new technique: Whole slide imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 67.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,004 | 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 ».