Abstract P3-08-22: The mutational landscape of cancer driver genes in matched primary ductal carcinoma <i>in situ</i> and recurrent ductal carcinoma <i>in situ</i> or recurrent invasive cancers
Notice bibliographique
Résumé
Abstract Due to breast screening, ductal carcinoma in situ (DCIS) accounts for approximately 25% of all newly diagnosed breast neoplasms. Believed to be a precursor to invasive carcinoma, a significant number of patients diagnosed with DCIS are effectively managed by surgery alone or in conjunction with radiotherapy and endocrine therapy. In general, there is an 8-11% relative risk for a subsequent invasive carcinoma over a period of 10 year, with 98% breast cancer-specific survival after 10 years of follow up. Although mastectomy, breast conserving surgery, and radiotherapy can reduce the risk of recurrence, there are ongoing lifetime consequences of treatment. Thus, there is a clinical need to identify those patients who are at risk of an invasive recurrence from those who might not recur or experience a subsequent DCIS recurrence. In this study, 60 patients with pure primary DCIS, treated with only with breast conserving therapy, across three different clinical outcome groups were examined: patients who did not experience a recurrence within 5 years (n=20); patients who experienced a recurrent DCIS within 5 years (n=20); and patients that recurred with an invasive cancer within 5 years (n=20). Pure primary DCIS lesions, as well as the matched DCIS recurrence or invasive recurrence, were macrodissected from formalin fixed paraffin embedded tissues and subjected to nucleic acid extraction. All samples were profiled using Thermo Fisher Scientific’s validated targeted sequencing panel, the Oncomine Comprehensive Assay v3.0 (OCAv3.0). This assay is comprised of common cancer driver genes shown to be prognostic and predictive to targeted therapies in use or in late-phase clinical trials, and is currently being used in the NCI-MATCH trial (NCT02465060). While the OCA panel and accompanying Oncomine Knowledgebase Reporter provides information regarding the targeted treatments linked to known actionable mutations, this study utilized all somatic mutations and copy number changes to reveal the genomic landscape of DCIS and their matched recurrences across these pan-cancer driver genes Amongst all primary DCIS samples across the three different clinical outcome groups, PIK3CA, was frequently found to be affected by SNV and Indels (32.8%) in addition to TP53 (26.2%), NF1 (21.3%), CREBBP (16.4%), ATM (14.8%), PALB2 (14.8%). DNA repair genes, including CHEK1, RAD50, RAD51B, MRE11A, BRCA1 and BRCA2, were found to be frequently subject to mutation in these primary DCIS samples ranging from 5%-15%. Similarly, copy number gains were frequently detected in HER2 (26.2%), CDK12 (18%), FGFR1 (4.9%), GNAS (4.9%), MYC, CCNE1, AR, RAD51C and RNF43 (1.6% each), and loses at H3F3A and KNSTRN (each 1.6%). Matched primary DCIS and their recurrent DCIS or invasive lesions exhibited similar changes with invasive cancers suggesting that in some cases, the primary DCIS gives rise to the invasive cancer. We will present the preliminary findings mapping the mutational and copy-number landscape of primary DCIS and matched recurrences to identify putative genomic changes defining these clinical outcome groups and to investigate the genomic progression of DCIS to invasive carcinoma. Citation Format: Jane Bayani, Quang M Trinh, Mary Anne Quintayo, Cheryl Crozier, Ilinca Lungu, Dan Dion, Joema Felipe-Lima, Giancarlo Pruneri, Jonas Bergh, Fredrik Warnberg, Giuseppe Viale, Lincoln D Stein, John MS Bartlett. The mutational landscape of cancer driver genes in matched primary ductal carcinoma in situ and recurrent ductal carcinoma in situ or recurrent invasive cancers [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-22.
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 ».