Abstract 4550: Correlations between tumor mutation burden, inflammatory profile and histological characteristics of tumor microenvironment in early-stage squamous cell lung carcinoma
Notice bibliographique
Résumé
Abstract Background: Anti-PD1/PD-L1 immunotherapy has demonstrated success in the treatment of advanced non-small cell lung cancer (NSCLC). Clinical data have shown that both the expression of PD-L1 in patient tumors and high tumor mutation burden (TMB) predicts the likelihood of a positive response to anti-PD-1/PD-L1 immunotherapy. Also, tumor microenvironment (TME) is the constitutive element in cancer immunity, in which analysis of characteristics reflects the potential existing immune reaction. Method: Histologic sections from 150 squamous cell lung carcinoma (SqCLC) were evaluated by two pathologists independently for percentage and character of intratumoral inflammatory cells and percentage and character of para-tumoral infiltrate. The ratios of infiltrating inflammatory cells to tumor cells were estimated in 10% increments by microscopic inspection. The proportions of immune cell populations were deconvulated using the CIBERSORT method based on Affymetrix gene expression profiles. PD-L1 protein expression by IHC was evaluated using the Dako PD-L1 22C3 pharmDx kit and scoring was determined according to the Dako tumor proportion score (TPS). Tumor Mutation Burden (TMB) was calculated based on data from targeted genome sequencing. CD4 and CD8 mRNA levels were determined from Affymetrix gene expression data from frozen specimens. Results: The infiltrates could be divided into intratumoral and paratumoral patterns according to their location in relation to microscopic tumor cell nests. Using the CIBERSORT assay, we confirmed our histological findings by microscopic examination that the SqCLC cohort can be subtyped into plasma cell dominant (74.8%) or other immune infiltrates dominant (such as macrophages), based on the proportions of immune cell populations. We found by regression analysis that TMB had a negative correlation with the percentage of intratumoral inflammatory cells (P=0.014), but did not significantly correlate with paratumoral infiltrates. The TMB demonstrated a significant negative correlation with CD4 mRNA level (P=0.017), but not with CD8 mRNA level. No correlation was determined for TMB and the immune cells dominant subgroup. Interestingly, we didn’t find any association for PD-L1 protein expression with the percentage of intra- or para-tumoral infiltrates, plasma cells dominant group and CD4 and CD8 mRNA levels. Conclusions: TMB was negatively correlated with the percentage of intratumoral inflammatory cells and CD4 mRNA level, which indicate that high TMB may promote an immune suppression environment. In addition, we did not find any association of PD-L1 expression with characteristics of TME in this early-stage SqCLC cohort. Further studies are needed to verify these interesting results. Citation Format: Hui Yu, Daniel T. Merrick, Ming-Sound Tsao, William G. Richards, Lucian R. Chirieac, Mark A. Watson, Christopher J. Rivard, David H. Harpole, Raphael Bueno, Adrie van Bokhoven, Aik-Choon Tan, Fred R. Hirsch, Wilbur A. Franklin. Correlations between tumor mutation burden, inflammatory profile and histological characteristics of tumor microenvironment in early-stage squamous cell lung carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4550.
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 | 0,001 |
| 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 | 0,000 | 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) | 0,003 | 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 ».