Additional file 1 of Identification of a Notch transcriptomic signature for breast cancer
Creators: name: Braune, Eike-Benjamin
name: Geist, Felix
name: Tang, Xiaojia
name: Kalari, Krishna
name: Boughey, Judy
name: Wang, Liewei
name: Leon-Ferre, Roberto A.
name: D’Assoro, Antonino B.
name: Ingle, James N.
name: Goetz, Matthew P.
name: Kreis, Julian
name: Wang, Kang
name: Foukakis, Theodoros
name: Seshire, Anita
name: Wienke, Dirk
name: Lendahl, Urban
Publisher: name: figshare
Year: 2024
Subjects: subject: Space Science
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Developmental Biology
subject: Cancer
subject: Mental Health
subject: Plant Biology

description: Additional file 1. Fig. S1. A schematic pipeline of data processing for the 20-gene transcriptomic Notch signature. The code for the pipeline is provided at GitHub at the link: https://github.com/KarolinskaMerck/NotchBRCASignature . Figure S2. A. Expression of the four NOTCH receptors (NOTCH1-4), the androgen receptor (AR), ERBB2 (HER2), ERBB3 (HER3), ESR1 and pGR1 in the six basal-like cell lines. B. Expression of HES1 and NRARP in the six basal-like cell lines under “Notch on” and “Notch off” conditions. C. Principal component analysis (P1-20) of the transcriptomic data from the six cell lines under “Notch on”, “Notch off” or “ground state”, as indicated for 8-h (upper) and 72-h (lower) treatment. (*p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 and ****p &lt; 0.0001). Data for PC6 versus PC7 and PC7 versus PC10 PCA combinations are also shown. D. Euclidian distances between the Notch-on, ground-state and Notch-off conditions for each of the six cell lines and biological replicates. Figure S3. A. Analysis of left skewed P value distribution of the 14 candidate signatures from Fig. 1B. The coherence scores for each signature length in the TCGA-BRCA patient cohort for the candidate signatures are also presented. B. Selection of optimal signatures based on both the largest coherence score as well as smallest empirical P value with the smallest gene set size in the range between 10 and 30 genes. C. Euclidian distances between the Notch-on, ground-state and Notch-off conditions for each of the six cell lines. D. Comparison of the transcriptomes from the 19 cell lines in ground-state conditions to previously established transcriptomes from the same cell lines. E. Expression of at least one of the four Notch receptor genes in the 19 cell lines. F. The performance of the candidate signatures to classify Notch activation status in the 19-cell line dataset was evaluated by ROC curves and their AUC (+/− 95% Confidence Interval). G. ROC analysis of the 19 breast cancer cell line dataset for signatures #5, #9 and #11; AUC with 95% confidence interval. Figure S4. A. Reactome graph-network analysis of the genes in the 20-gene signature to Notch-related pathway terms. B. String.db interaction enrichment analysis for the 20-gene signature to Notch-related pathway terms. Figure S5: A. Calculation of mean overlap between signatures and assessment of mean similarity using Jaccard coefficient. B. Overlap dendrogram of the signatures from A. C. Jaccard dendrogram of the signatures from A. D. Mean overlap coefficient of the signatures from A. E. Mean Jaccard similarities from the signatures from A. F. Mean centrality score from the signatures from A. Figure S6: A. ROC analysis of published Notch signatures analysed in the six cell line datasets. B. ROC analysis curves corresponding to the data in A. C. GSEA analysis of published Notch signatures analysed in the 19-cell line dataset for Notch on vs off for combined 8+72-h, 8-h and 72-h timepoints, as indicated. D. Corresponding ROC analysis for the published Notch signatures corresponding to data in C. E. ROC analysis curves for the published Notch signatures analysed in the 19-cell line dataset. Figure S7. A. Calculation of mean signature scores for the 20-gene signature and previously published signatures in the TCGA, METABRIC and Oslo2 patient cohorts, as indicated. B. Inferred immune and stromal content in the TCGA and Oslo2 datasets for the 20-gene signature and previously published Notch signatures, as indicated. Figure S8: A. Correlation of the Notch core signature (encompassing the Notch 1-4 receptors and the Jag1,2 and Dll13,4 ligands) to the 20-gene signature and previously published Notch signatures, as indicated. The correlation scores were calculated for six cell line (left) and the 19 cell line (right) datasets. B. Correlation of the Notch core signature to previously published Notch signatures for the TCGA, METABRIC and Oslo2 patient datasets, as indicated. C. ROC analysis for two binary comparisons of 57 published signatures indicating Notch alterations in the TCGA dataset (“Notch activation alteration” vs “Notch wild type” and “Notch inactivation alteration" vs “Notch wild type”) D. Signature score changes for the two binary comparisons in C in 16 previously published signatures, as indicated. Figure S9. Calculation of signature scores for the 20-gene signature and previously published signatures in the TCGA, METABRIC and Oslo2 patient cohorts, with basal, HER2, LumA, LumB and normal subtypes, as indicated. Figure S10. A. Comparison of signature scores (ssGSEA) for three breast cancer subtypes (21 Luminal A, 27 Luminal B and 21 TNBC patients) at the onset (orange) and after two rounds of epirubicin and docetaxel treatment (blue) for previously published Notch signatures, as indicated. B. Disease-free survival analysis (survival probability) of patients (n = 122 (28 TNBC; 42 LumA and 42 LumB)) at baseline according to signature scores from previously published Notch signatures, as indicated (high (red) and low (blue) groups) at baseline. C. Signature score changes in patients with and without lymph node metastasis from previously published signatures and the Notch core signature. D. Heatmap comparing the GSVA signature scores from non-responders and responders from the BEAUTY cohort for the 20-gene signature and previously published signatures, as indicated. E. Comparison GSVA scores in BEAUTY TNBC responder and non-responder patient cohorts for the 20-gene signature, the Notch core signature and previously published signatures, as indicated.