Abstract 3149: Enumeration and mutational profiling of CTCs and comparison to ctDNA and colorectal cancer liver metastases
Notice bibliographique
Résumé
Abstract Background Colorectal cancer (CRC) is the 3rd most common cancer diagnosed worldwide in both men and women. Only 39% of cancers are diagnosed at a localized stage, and 5-year survival rates decrease rapidly for patients with advanced and metastasized disease (stage III 61%, stage IV 8%). Better markers for detection of disease progression, therapeutic resistance and minimal residual disease are still needed. Liquid biopsies, such as CTCs and ctDNA, are emerging biomarkers shed by the tumor into the blood stream. Both markers currently are attracting growing interest for their use in disease prognosis, early detection of recurrence and are promising candidates for guiding cancer therapy in real-time. Method For rapid label-free isolation of CTCs from peripheral blood we used the Vortex technology, a microfluidic device using inertia and laminar microvortices. From 15 patients with metastatic CRC to the liver that underwent liver metastatectomy with curative intent, we collected CTCs preoperatively, at the 5th postoperative day and during follow-up visits. Cells collected were immunostained for EpCAM, CD45 and DAPI, enumerated using standardized classification criteria, and subjected to Sanger sequencing. CTC enumeration and mutational patterns were compared to the primary tumor, liver metastases and ctDNA (detected by a multiplexed PCR and enrichment technology; Kidess E et al., 2015) as well as CEA levels when available. Results 41 blood samples from 15 patients were collected at different time points prior to and after surgical resection of liver metastases. More CTCs were found in preoperatively collected CRC patient samples (2.4 CTCs/mL, 0.1 - 5.5/mL) than in age-matched healthy controls (0.1 CTCs/mL, 0 - 0.4/mL). 80% of all CRC samples were identified as positive for CTCs (based on a calculated threshold from healthy controls), with varying levels of EpCAM expression (81.4% of CTCs being EpCAM+). The number of CTCs for each patient, showed a close correlation to clinical parameters and ctDNA levels: detection of CTCs, CTC mutational profiles as well as ctDNA revealed minimal residual disease and anticipated tumor recurrence earlier than carcinoembryonic antigen (CEA) value or imaging. For example, for P006, postoperative imaging surveillance revealed progressive disease, which was accompanied by rising levels of CTCs (up to 29 CTCs/mL at the last time point) and PIK3CA mutant DNA in both plasma ctDNA and CTC DNA, while CEA remained in the normal range. Conclusion Our data illustrate that CTCs as well as ctDNA can efficiently reveal disease recurrence as well as disease progression earlier than imaging and far more reliable compared to CEA, the currently standard biomarker for CRC. Beyond enumeration, CTC molecular analysis gives additional information and will potentially help to promote the development of tailored therapies for every individual patient. Citation Format: Evelyn Kidess-Sigal, Haiyan E. Liu, Melanie Triboulet, James Che, Georges A. Poultsides, Brendan C. Visser, Andre Marziali, Marc Lee, Valentina Vysotskaia, Matthew Wiggin, Vishnu C. Ramani, Ulrich Keilholz, Ingeborg Tinhofer, Amin Zia, John Coller, Jeffrey A. Norton, Elodie Sollier, Stefanie S. Jeffrey. Enumeration and mutational profiling of CTCs and comparison to ctDNA and colorectal cancer liver metastases. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3149.
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 | 0,000 | 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) | 0,001 | 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 ».