Abstract P6-10-12: Texture heterogeneity of breast tumour in magnetic resonance imaging can be explained by differentially regulated genes
Notice bibliographique
Résumé
Abstract Background: Magnetic resonance imaging (MRI) and molecular profiling of tumour tissues have become standard techniques to study breast cancer in recent years. However, despite the myriad imaging and genetic subtypes that have been identified, the underlying biological mechanisms of MRI features are seldom explained, and differentially regulated genes are rarely linked to the phenotypic appearance of tumours. In this study, we propose to fill this gap in knowledge by investigating the unbiased correlations between MRI phenotypes and differential gene expressions in breast cancer. Methods: Patients diagnosed during 2002-15 with invasive breast cancer who went through surgery were retrospectively reviewed for magnetic resonance imaging (MRI) and genomics analysis. In total, we collected dynamic contrast-enhanced subtraction MRI and RNA sequencing results of surgical specimens from a cohort of 56 patients. Of these, 31 patients (aged 33 to 72 years) met our inclusion criteria. Tumour lesion segmentation was performed by a radiologist who has 10 years of experience. We extracted features that quantitatively describe tumour appearance from the segmented lesions using pyradiomics (v2.0.0). We then grouped the tumours into two imaging subtypes using an unsupervised clustering approach (SIMLR, v1.10.0). To probe the underlying biological mechanisms behind the difference in tumour appearance, we performed differential expression analysis (edgeR, v3.26.5) and pathway enrichment analysis (g:profiler) between the two imaging subtypes. Multiple testing correction was conducted with Benjamini-Hochberg correction using a false discovery rate of 0.05. Results: We classified the breast tumours from our cohort into two imaging subtypes that have distinct levels of heterogeneity in texture (p=0.004). We found a list of genes that were significantly differentially expressed between the heterogenous (n=20) and homogenous (n=11) subtypes (Table 1), and their associated biological pathways. We found that the pathways controlling cell growth (p=0.022), cell migration and invasion (p=0.023), estrogen regulation (p=0.022) and DNA damage repair (p=0.015) mechanisms may have contributed to increased heterogeneity in tumour presentation when imaged with MRI. Conclusion: The underlying biological mechanisms affecting breast MRI texture can be investigated by linking tumour appearance to gene expression profiling. Our results suggest that texture heterogeneity in breast MRI could be linked to a number of differentially expressed genes that may be further investigated as a biomarker of cancer risk assessment or recurrence. Further studies with a larger cohort will be conducted to validate and extend these results. Table 1. Differentially expressed genes between heterogenous and homogenous imaging subtypes.Genes upregulated in heterogeneous imaging subtypeLog fold changeAdjusted p valueABCC138.760.0022PROL17.760.0331TDRD127.100.0204SLC12A22.030.0204IGFBP3-1.500.0331UBASH3B-1.740.0331LYZ-2.120.0291CCL5-2.120.0204PDCD1LG2-2.180.0359SLC7A11-2.480.0363GNLY-3.090.0022GZMB-3.100.0204PTHLH-3.270.0246GSTM5-3.370.0325GNAO1-3.430.0363MYOZ1-3.580.0269CLEC4C-3.640.0246AJAP1-3.760.0325IL28B-3.930.0415CCL25-4.770.0325PI15-5.491.48e-7 Citation Format: Jianan Chen, Yutaka Amemiya, Gregory Kuling, Homa Fashandi, Yulia Yerofeyeva, Heba Hussein, Elzbieta Slodkowska, Fiona Ginty, Arun Seth, Martin Yaffe, Anne L. Martel. Texture heterogeneity of breast tumour in magnetic resonance imaging can be explained by differentially regulated genes [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 P6-10-12.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,004 | 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 ».