Discriminating Interpatient Variabilities of <i>RAS</i> Gene Variants for Precision Detection of Thyroid Cancer
Notice bibliographique
Résumé
Importance: Interpatient variabilities in genomic variants may reflect differences in tumor statuses among individuals. Objectives: To delineate interpatient variabilities in RAS variants in thyroid tumors based on the fifth World Health Organization classification of thyroid neoplasms and assess their diagnostic significance in cancer detection among patients with thyroid nodules. Design, Setting, and Participants: This prospective diagnostic study analyzed surgically resected thyroid tumors obtained from February 2016 to April 2022 and residual thyroid fine-needle aspiration (FNA) biopsies obtained from January 2020 to March 2021, at Mount Sinai Hospital, Toronto, Ontario, Canada. Data were analyzed from June 20, 2022, to October 15, 2023. Exposures: Quantitative detection of interpatient disparities of RAS variants (ie, NRAS, HRAS, and KRAS) was performed along with assessment of BRAF V600E and TERT promoter variants (C228T and C250T) by detecting their variant allele fractions (VAFs) using digital polymerase chain reaction assays. Main Outcomes and Measures: Interpatient differences in RAS, BRAF V600E, and TERT promoter variants were analyzed and compared with surgical histopathologic diagnoses. Malignancy rates, sensitivity, specificity, positive predictive values, and negative predictive values were calculated. Results: A total of 438 surgically resected thyroid tumor tissues and 249 thyroid nodule FNA biopsies were obtained from 620 patients (470 [75.8%] female; mean [SD] age, 50.7 [15.9] years). Median (IQR) follow-up for patients who underwent FNA biopsy analysis and subsequent resection was 88 (50-156) days. Of 438 tumors, 89 (20.3%) were identified with the presence of RAS variants, including 51 (11.6%) with NRAS, 29 (6.6%) with HRAS, and 9 (2.1%) with KRAS. The interpatient differences in these variants were discriminated at VAF levels ranging from 0.15% to 51.53%. The mean (SD) VAF of RAS variants exhibited no significant differences among benign nodules (39.2% [11.2%]), noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs) (25.4% [14.3%]), and malignant neoplasms (33.4% [13.8%]) (P = .28), although their distribution was found in 41.7% of NIFTPs and 50.7% of invasive encapsulated follicular variant papillary thyroid carcinomas (P < .001). RAS variants alone, regardless of a low or high VAF, were significantly associated with neoplasms at low risk of tumor recurrence (60.7% of RAS variants vs 26.9% of samples negative for RAS variants; P < .001). Compared with the sensitivity of 54.2% (95% CI, 48.8%-59.4%) and specificity of 100% (95% CI, 94.8%-100%) for BRAF V600E and TERT promoter variant assays, the inclusion of RAS variants into BRAF and TERT promoter variant assays improved sensitivity to 70.5% (95% CI, 65.4%-75.2%), albeit with a reduction in specificity to 88.8% (95% CI, 79.8%-94.1%) in distinguishing malignant neoplasms from benign and NIFTP tumors. Furthermore, interpatient differences in 5 gene variants (NRAS, HRAS, KRAS, BRAF, and TERT) were discriminated in 54 of 126 indeterminate FNAs (42.9%) and 18 of 76 nondiagnostic FNAs (23.7%), and all tumors with follow-up surgical pathology confirmed malignancy. Conclusions and Relevance: This diagnostic study delineated interpatient differences in RAS variants present in thyroid tumors with a variety of histopathological diagnoses. Discrimination of interpatient variabilities in RAS in combination with BRAF V600E and TERT promoter variants could facilitate cytology examinations in preoperative precision malignancy diagnosis among patients with thyroid nodules.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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) | 0,000 | 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 tête enseignante, 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 ».