Abstract TMEM-036: INTERFERON INDUCED STAT1 ASSOCIATES WITH DIFFERENTIAL CHEMOTHERAPY RESPONSE IN HIGH-GRADE SEROUS OVARIAN CANCER
Notice bibliographique
Résumé
Abstract PURPOSE: High-grade serous ovarian cancer (HGSC) is the most prevalent and fatal histological subtype of ovarian cancer. Unfortunately, 70% of HGSC patients show resistance to chemotherapeutic drugs, and clinical management is challenged by a lack of accurate prognostic and predictive biomarkers of chemotherapy response. It is now established that immune cells within the tumour microenvironment (TME) significantly contribute to tumor cell death or survival following exposure to chemotherapy. We previously reported the presence of a distinct, pre-existing T-helper Type I associated immune TME, mediated by Signal Transducer and Activator of Transcription Factor 1 (STAT1), that predicted chemotherapy response in HGSC. Current work builds on our previous findings and investigates the mechanisms linking STAT1 to a pre-existing inflammatory TME and differential response to chemotherapy. EXPERIMENTAL PROCEDURES: Tumour STAT1 expression and intra-epithelial CD8+ T-cells were confirmed as prognostic and predictive biomarkers in a second independent biomarker validation study. Immunohistochemistry and a custom NanoString platform, composed of 34-target genes of STAT1 and immune phenotypic markers, were used on fresh frozen chemo-naïve HGSC tumour samples. Based on the findings from these profiling studies, a subset of samples with high and low STAT1 expression levels were subjected to further gene profiling analysis to correlate the immune transcriptomic landscape and its association with chemotherapy response. Stable silencing of the STAT1 gene was performed by lentiviral transduction of murine ovarian cancer cells (ID8) with STAT1 short hairpin RNA (shRNA) to create STAT1-knockdown (KD) cells and STAT1-non targeting (NT) control cells. Ongoing in vivo experiments will define the contribution of STAT1 in modulating; the TME, tumor progression, the recruitment of tumor infiltrating lymphocytes, and response to chemotherapy in HGSC. RESULTS: Gene expression analysis revealed significant differential expression of genes involved in the cellular Type I Interferon pathway, notably STAT1 and its target genes (such as ISG15, DDX58, IFIT1, CXCL10, CXCL11), between chemosensitive and resistant groups. Preliminary in vitro analysis has revealed proliferative and migratory advantages to STAT1-KD cells compared to the STAT1-NT cells; indicating that STAT1 plays a role in the regulation of cell survival and proliferation in the absence of the immune TME. CONCLUSION: STAT1 expression significantly associates with progression free survival and response to chemotherapy in HGSC. High levels of STAT1 and its target genes potentially contribute to CD8+ T-cell recruitment and immune mediated chemosensitivity in HGSC. Ongoing in vitro and in vivo studies will confirm the mechanisms underlying variations in the interferon induced STAT1 pathways in the TME of HGSC. Elucidating the mechanisms underlying differential STAT1 expression in HGSC primary tumours will contribute to better patient stratification for informed biomarker guided immunotherapies. Citation Format: Gillian Reid-Schachter, Peter Truesdell, Nichole Peterson, Charles Graham, Julie-Ann Francis, Andrew Craig, Madhuri Koti. INTERFERON INDUCED STAT1 ASSOCIATES WITH DIFFERENTIAL CHEMOTHERAPY RESPONSE IN HIGH-GRADE SEROUS OVARIAN CANCER [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr TMEM-036.
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 | 0,000 | 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 ».