Table 1 The effect of E2F1 and receptor molecules in relevant combinations on the EMT phenotype in bladder and breast cancer model

From: Unraveling a tumor type-specific regulatory core underlying E2F1-mediated epithelial-mesenchymal transition to predict receptor protein signatures

(a) Bladder cancer

E2F1

TGFBR1

FGFR1

EGFR

CXCR1

RARA

EMT

 0

0

0

0/1

0/1

0/1

0

 0

0

1

0/1

0/1

0/1

1

 0

1

0

0/1

0/1

0/1

1

 0

1

1

0/1

0/1

0/1

2

 1

0

0

0/1

0/1

0/1

1

 1

0

1

0/1

0/1

0/1

2

 1

1

0

0/1

0/1

0/1

2

 1

1

1

0/1

0/1

0/1

3

(b) Breast cancer

E2F1

TGFBR2

EGFR

HMMR

THRB

IL1R1

RARA

EMT

 0

0

0

0/1

0/1

0/1

0/1

0

 0

0

1

0/1

0/1

0/1

0/1

1

 0

1

0

0/1

0/1

0/1

0/1

1

 0

1

1

0/1

0/1

0/1

0/1

2

 1

0

0

0/1

0/1

0/1

0/1

1

 1

0

1

0/1

0/1

0/1

0/1

2

 1

1

0

0/1

0/1

0/1

0/1

2

 1

1

1

0/1

0/1

0/1

0/1

3

  1. Active state of the molecule is represented by ‘1’ and the inactive state as ‘0’. The phenotype output (EMT) can take four ordinal levels ranging from ‘0’ (non- invasive) to ‘3’ (highly invasive). Table (a) is the summary of 64 in silico simulations of bladder cancer. Each row represents the result of eight simulations where for the given Boolean state of E2F1, TGFBR1, and FGFR1, all eight combinations of EGFR, CXCR1, and RARA results in the same phenotypical output. Table (b) is the summary of 128 in silico simulations of breast cancer. Each row represents the result of 16 simulations where for the given Boolean state of E2F1, TGFBR2, and EGFR, all 16 combinations of HMMR, THRB, IL1R1, and RARA results in the same phenotypical output
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