Data and metadata supporting the article: Co-dependency for MET and FGFR1 in basal triple negative breast cancers
Notice bibliographique
Résumé
Triple-negative breast cancer (TNBC) is a heterogeneous disease that lacks both effective patient stratification strategies and therapeutic targets. Whilst elevated levels of the MET receptor tyrosine kinase are associated with TNBCs and predict poor clinical outcome, the functional role of MET in TNBC is still poorly understood. In this study, the authors utilized an established Met-dependent transgenic mouse model of TNBC, human cell lines, and patient-derived xenografts to investigate the role of MET in TNBC tumourigenesis.<br> <b>Data access</b>: Processed RNA sequencing datasets generated during the study, are available in Gene expression Omnibus: https://identifiers.org/geo:GSE162272. The raw RNA sequencing data are available in Sequence Read Archive: https://identifiers.org/ncbi/insdc.sra:SRP294504. All other datasets generated and analysed during the study (including tumoursphere formation assays, tumoursphere proliferation assays, immunohistochemistry data, quantitative RT-PCR, <i>in vivo</i> inhibitor treatments (including tumour volume calculations), flow cytometry data and immunofluorescence data) are publicly available in the figshare repository as part of this data record. The publicly available TCGA data analysed during the study are available in cBioPortal for Cancer Genomics: https://identifiers.org/cbioportal:brca_tcga_pub. Microarray data from the MMTV-Metmt;Trp53fl/+;Cre tumours analysed during the study, are available in Gene Expression Omnibus: https://identifiers.org/geo:GSE41601. RNA sequencing data from breast cancer pairs of primary tumors and PDXs, analysed during the study, are also available in Gene Expression Omnibus: https://identifiers.org/geo:GSE142767. Uncropped Western blots are part of the supplementary files that accompany the article.<br> <b>Study approval and patient consent: </b>All human participants provided informed consent for this study and tissue was collected at McGill University Health Center in accordance with the protocols approved by the research ethics board (SUR-99-780). All animal studies linked to this protocol were approved by the McGill University Animal Care Committee (2014-7514). The Biobank protocol (05-006) and the protocol to generate PDX from biobank tissues (14-168) were both approved by Jewish General Hospital ethics committee.<br> <b>Study aims and methodology: </b>In the present study, the authors assayed tumour-initiating cells (TIC) properties to directly investigate the role of Met in tumour initiation and identify FGFR1 signaling as a key convergent pathway with Met for the maintenance of TICs. Primary mouse cell lines were established by dissociation of MMTV-<i>Metmt</i>, <i>Trp53fl/+;Cre</i>, and MMTV-<i>Metmt;Trp53fl/+;Cre </i>mammary tumours as previously described. Additionally, the following cell lines were used during the study: BT-20, HCC70, HCC1937, HCC1954, HCC1395, MDA-MB-468, MDA-MB-436, MDA-MB-157, MDA-MB-231, BT-549, and Hs578T. The following are described in more detail in the published article: cell culture, patient-derived xenografts, antibodies and reagents, lentiviral infection, tumoursphere formation assays, tumoursphere proliferation assays, Western blot analysis, quantitative RT-PCR, immunohistochemistry, RNA sequencing, in vivo limiting dilution assay, <i>in vivo</i> inhibitor treatments, flow cytometry, immunofluorescence, tumour dissociation, analysis of gene expression data, and statistical analysis.<br> <b>Data supporting the figures, supplementary figures and supplementary tables in the article: </b> This data record consists of a total of 38 data files in the following file formats: .xlsx, .pdf, .csv, .txt, .png and tiff. A list of all the datasets generated during the study, are included in the file <b>Sung, V. et al.xlsx.</b>
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 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 | 0,003 |
| 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 | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».