Data and metadata supporting the article: Co-dependency for MET and FGFR1 in basal triple negative breast cancers
Bibliographic record
Abstract
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>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".