Abstract P1-08-09: High mid-treatment RNA disruption in patients with HER2-negative breast cancer predicts survival benefit after neoadjuvant chemotherapy
Notice bibliographique
Résumé
Abstract BACKGROUND: Ribosomal RNA fragmentation (RNA disruption) measured mid-therapy in breast cancer tumors has been shown to correlate with pCR and improved disease-free survival. Data from the NeoAva clinical trial was used to evaluate RNA disruption index values (RDI) for measurement of therapy efficacy. METHODS: The randomized phase II clinical trial NeoAva investigated the effects of neoadjuvant chemotherapy (FEC) in HER2-negative breast cancer patients with or without bevacizumab. Serial biopsies were taken prior to treatment and after 12 and 25 weeks of treatment. The majority of patients in this study were diagnosed with ER positive tumors (88% of the total 12-week samples). RNA isolation from frozen tumor tissue was carried out using the AllPrep DNA/RNA Mini kit with QIACube (Qiagen), and the quality of the RNA assessed (Agilent 2100 Bioanalyzer). Treatment response was measured using both pathological complete response (pCR) and residual cancer burden (RCB) at the time of surgery, and median follow-up time was 6.8 years. Using the RNA electropherogram data (Agilent Bioanalyzer) generated in this study, RDI values were assessed in pre-therapy samples (n=109), 12-week samples (n=98) and 25-week samples (n=106). RESULTS: RDI values were measured at three timepoints, however only the RDI values assessed from 12 week samples correlated with clinical outcomes. RDI values were higher in patients that achieved a RCB class of either 0 or 1 (n=28) (median RDI=2.6) compared with those patients that had an RCB class of 3 (n=17) (median RDI=1.3) (Mann-Whitney p=0.006). Out of the samples that were analyzed by the RNA disruption assay (RDA), 18 patients achieved a pCR and had a median RDI value of 2.6 compared with a median RDI of 1.8 for those who did not achieve a pCR (n=80); this finding did not reach statistical significance. RDI values measured in samples taken prior to therapy or at 25-weeks did not correlate with either RCB class or subsequent pCR. With 93% and 94% of patients having mid-therapy RDI values greater than 1.1 for RCB class of 0/1 or pCR, respectively, this was chosen as a cut point to generate Kaplan-Meier curves of recurrence free survival. These curves illustrated statistically significant improved survival (HR =2.6; 95% CI 0.8-8.1) for patients with a RDI > 1.1 (p=0.05). Similarly, Kaplan-Meier curves of breast cancer specific survival also demonstrated improved survival (HR = 3.1; 95% CI 0.8-11.7) for patients with a RDI > 1.1 (p=0.03). Kaplan-Meier curves based on pCR/no pCR were generated from the set of patients that had 12-week RDI values assessed and did not demonstrate improved survival in this small, predominantly ER+ group. No survival benefit was found based on RDI values measured prior to therapy or at 25 weeks. Patients that received bevacizumab (n=45) had significantly higher RDI values at 12 weeks (median RDI = 2.5) than patients that did not receive the drug (median RDI = 1.4) (n=53) (Mann-Whitney test p=0.0005). This overall increase in RDI values with bevacizumab resulted in improved survival for patients at a higher RDI cutoff values of 1.6 (p=0.03)(HR = 4.4; 95% CI 0.8-25.1). CONCLUSION: Taken together, our findings suggest that increased RNA disruption measured in tumor biopsies during neoadjuvant chemotherapy correlates with a survival benefit for patients and may be a more useful indicator of therapy efficacy than pCR, particularly for patients with ER positive tumors. Citation Format: Laura B Pritzker, Mads Haugland Haugen, Hedda von der Lippe Gythfeldt, Twinkle Masilamani, Gabriel Theriault, Renee St-Onge, Lavina D'costa, Ole Christian Lingjaerde, Amadeo Parissenti, Olav Engebraaten. High mid-treatment RNA disruption in patients with HER2-negative breast cancer predicts survival benefit after neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-09.
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 | 0,000 | 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) | 0,003 | 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 ».