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Enregistrement W4317612789 · doi:10.1097/01.cot.0000918336.06435.b4

Genetic Profiling in Patients After Breast-Conserving Surgery

2023· article· en· W4317612789 sur OpenAlexaboutno aff
Mark McGraw

Notice bibliographique

RevueOncology Times · 2023
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBreast Cancer Treatment Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineBreast cancerRadiation therapyBreast-conserving surgeryOncologyAdjuvant radiotherapyInternal medicineAdjuvantMastectomyCancer

Résumé

récupéré en direct d'OpenAlex

imaging: imagingNew research finds that patients with invasive breast cancer who scored low on investigational gene molecular signatures had comparable rates of local recurrence regardless of whether they received adjuvant radiation therapy after breast-conserving surgery. Presenting their findings at the 2022 San Antonio Breast Cancer Symposium, researchers detailed how these results suggest that genetic profiling may help identify breast cancer patients who can safely omit radiation therapy after undergoing breast-conserving surgery (Abstract GS4-03). Patients who undergo breast-conserving surgery are typically recommended to receive adjuvant radiation therapy to reduce the risk of local recurrence. However, many of these patients will not experience a local recurrence even without radiation therapy, the authors noted, adding there are currently no reliable predictive classifiers to identify patients who might be able to skip radiation therapy. Also, the link between radiation therapy and problematic side effects in some patients underscores the importance of identifying those patients who can safely bypass radiation therapy. Study Details For this study, a team led by Per Karlsson, MD, Professor of Oncology at the Sahlgrenska Comprehensive Cancer Center and the University of Gothenburg, evaluated the predictive potential of POLAR (Profile for the Omission of Local Adjuvant Radiotherapy). It is an investigational 16-gene molecular signature that was developed based on gene expression differences between patients with and without local recurrence after breast-conserving surgery. Genes included in the signature have known roles in cellular proliferation and the immune response.Per Karlsson, MD: Per Karlsson, MDKarlsson and colleagues performed a meta-analysis of 623 patients with lymph node-negative, estrogen receptor-positive, HER2-negative breast cancer who were enrolled in one of three randomized clinical trials examining the efficacy of breast-conserving surgery with and without local breast radiation therapy. The clinical trials included in the meta-analysis were the Swedish SweBCG91RT trial, the Scottish Conservation Trial, and a trial from the Princess Margaret Hospital (PMH) in Canada. Among the 623 patients taking part in the meta-analysis, 354 were from SweBCG91RT and 132 came from the PMH trial. To evaluate the predictive capability of POLAR, the researchers analyzed gene expression in patient breast tumor samples to assign each patient a POLAR score. They then examined the impact of radiation therapy on patients with high and low POLAR scores. Among the 429 patients with high POLAR scores, those who received adjuvant radiation therapy after breast-conserving surgery had a 63 percent reduction of local recurrence compared with those who did not receive adjuvant radiation therapy, suggesting that adjuvant radiation therapy was beneficial for these patients. Among the 194 patients with low POLAR scores, there was no significant difference in local recurrence rate between those who received adjuvant radiation therapy and those who did not. After 10 years, 5 percent of patients who received radiation therapy experienced a local recurrence compared with 7 percent of those who did not receive radiation therapy. In this patient-level meta-analysis of three independent randomized clinical trials, the POLAR gene profile successfully predicted which patients would and would not benefit from local radiation therapy, thereby identifying a group of breast cancer patients for whom radiation therapy may be safely omitted after breast-conserving surgery, according to the authors. Noting that the POLAR gene profile may help mitigate toxicities and improve quality of life for many breast cancer patients, the researchers add that the POLAR gene profile will need further validation and additional streamlining before it could be used in a clinical setting. Karlsson and colleagues plan to undertake additional research to examine whether the POLAR gene profile can also identify patients who could safely avoid regional radiation therapy, which is associated with more severe toxicities than local radiation therapy. “Breast cancer is commonly classified by immunohistochemistry in different approximated sub-types. This classification is good,” Karlsson told Oncology Times. “However, gene expression information can give a more diverse information of the tumor. Out of the diverse information of all expressed genes we have identified a 16-gene profile (POLAR) with capacity to prognosticate locoregional recurrences and to predict radiotherapy benefit. The gene expression contains much more info than just immunohistochemistry, which we used in the development of the POLAR score.” In terms of what these findings signify for the role of radiation therapy in the treatment of breast cancer patients for whom adjuvant radiation therapy is recommended, “we need further streamlining of the POLAR assay and some further validation before it can be used in the clinic,” Karlsson noted. “Going forward, our results indicate that, in 25 percent of the patients in this population, radiotherapy can be safely omitted.” Mark McGraw is a contributing writer.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,521

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,253
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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