Additional file 1 of The ELF3 transcription factor is associated with an epithelial phenotype and represses epithelial-mesenchymal transition
Creators: name: Subbalakshmi, Ayalur Raghu
name: Sahoo, Sarthak
name: Manjunatha, Prakruthi
name: Goyal, Shaurya
name: Kasiviswanathan, Vignesh A
name: Mahesh, Yeshwanth
name: Ramu, Soundharya
name: McMullen, Isabelle
name: Somarelli, Jason A.
name: Jolly, Mohit Kumar
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified
subject: Developmental Biology
subject: Cancer
subject: Hematology

description: Additional file 1: Mathematical model formulation. Fig S1. ELF3 levels in TCGA. A) ELF3 expression levels in TCGA cancer samples ordered by low KS score to high KS score. B) Scatter plot for ELF3 expression and its methylation status in TCGA cancer types. Each dot (cancer type) colored by KS score. The higher the KS score, the more mesenchymal a sample is. Colorbar is given to the right; higher scores are denoted by red. Fig S2. ELF3 delays onset of EMT. (A) Phase diagrams for the ELF3 network driven by an external signal (l_ext) for varying strength of interactions along the ELF3-ZEB axis (B) Phase diagrams for the ELF3 network driven by an external signal (l_ext) for varying strength of ELF3 self-activation. (C) Phase diagrams for the ELF3 network driven by an external signal (l_ext) for varying strength of interactions along the Slug-ELF3 axis (D) Sensitivity analysis of parameters for the ELF3 coupled EMT circuit (Fig 2E) indicating percent change in the I_ext interval for which the hybrid E/M state exists. The red dotted line indicates the percent change in the stable hybrid region in the absence of ELF3 (core network) when compared to the coupled network. Figure S3. ELF3 is an inducer of MET. (A) Gene regulatory network showing the regulation between epithelial and mesenchymal genes. Green arrows indicate activatory links and Red hammers indicate inhibitory links. (B) Kernel density estimate plots of EMT score (ZEB – miR200) (top panel) and ELF3 z-normalized expression (bottom panel). The red vertical line shows the approximate position of the minima of the largely bimodal distributions. PCA scatter plot of all steady states of RACIPE colored by (i) the EMT score defined as ZEB – miR200, (ii) SLUG expression (iii) ELF3 expression and (iv) KLF4 expression. (C) PCA scatter plot of all steady states of RACIPE colored by GRHL2 Expression (leftmost panel), miR200 expression (center panel) and ZEB expression (rightmost panel). (D) Scatterplot of EMT scores and ELF3 levels across steady state solutions obtained from RACIPE. Red lines indicate the position of minima in the bimodal distributions of EMT scores and ELF3 levels. Spearman correlation. coefficient and p-value are mentioned. (E) Scatterplot of Epithelial scores (GRHL2 + miR200) and Mesenchymal scores (ZEB + SNAIL +SLUG) with ELF3 levels of steady state solutions from RACIPE. The spearman correlation coefficient and the corresponding p-values have been mentioned. (F) Scatterplot of Epithelial scores (GRHL2 + miR200) and Mesenchymal scores (ZEB + SNAIL +SLUG) with KLF4 levels of steady state solutions from RACIPE. The spearman correlation coefficient and the corresponding p-values have been mentioned. (G) Fraction of steady state solutions resulting in Epithelial phenotype in control, 20-fold and 100-fold over expression of ELF3. * represents a statistically significant difference in the fraction of cases in the epithelial phenotype (Students’ t-test; p &lt; 0.05). (H) Fraction of steady state solutions resulting in the Epithelial (left panel) and Mesenchymal (right panel) phenotypes in control, 20-fold over expression of ELF3, GRHL2 and KLF4. *represents a statistically significant difference (Students’ t-test; p &lt; 0.05). Fig S4. ELF3 shows stronger trends as compared to KLF4 with an epithelial behavior. Scatter plots showing correlations of imputed ELF3 and KLF4 expression with 76GS EMT score (the higher the 76GS score, the more epithelial the sample) in two cancer cell lines A) A549 (lung cancer) and B) DU145 (prostate cancer) when treated with TGFβ (GSE147405). Spearman correlation coefficient and the corresponding p-values have been mentioned. Imputed gene expression values were calculated using the MAGIC algorithm for different cell lines separately. C) Volcano plots showing correlation of GRHL2 expression levels with ssGSEA epithelial and mesenchymal scores in a meta-analysis of breast cancer datasets. Each dot represents a dataset. R &lt; - 0.3, p&lt; 0.05 or R &gt; 0.3, p &lt; 0.05 are counted as statistically significant cases. Nneg denotes number of datasets for which a negative correlation (blue dots) is observed, Npos denotes number of datasets for which a positive correlation (red dots) is observed between the two corresponding expression levels or ssGSEA scores. D) Same as C) but for bladder cancer. E) Same as C) but for prostate cancer. Panels D and E show results for KLF4, ELF3 and GRHL2. Fig S5. ELF3 correlates with patient survival in a cancer-specific manner. Trends in breast cancer samples. (A) overall survival (GSE9893) (B) relapse-free survival (GSE4922) (C) metastasis-free survival (GSE6532). Trends in colorectal cancer samples. (D) overall survival (GSE39582) (E) relapse-free survival (GSE395824) (F) metastasis-free survival (GSE28722). Fig S6. WT1 correlates with patient survival in a cancer-specific manner. (A) Overall survival in Breast cancer sample (GSE9893). (B) Relapse free survival in breast cancer sample (GSE9893). (C) (D) Relapse free survival in colorectal cancer samples (GSE17536, GSE14333) (E) (F) Overall survival in lung cancer samples (GSE50081, GSE314) (G) Relapse free survival in lung cancer sample (GSE31210) (H) Overall survival in ovarian cancer sample (GSE73614) (I) Overall survival in pancreatic cancer sample (TCGA-PAAD)