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Table 1 Betti number analysis and its implication for single protein targeting. The Surveillance, Epidemiology and End Results Database (SEER) provide data for the 5-year survival, degree-entropy was calculated from the Protein-protein interaction network (PPI) using Python®, Cycle-Basis was calculated using networkX.cycle_basis (a Python function), the nominal Betti number was calculated using JPLEX, and represents the Betti number for the full cancer network, and the Best Betti represents the lowest Betti number achieved by removal of a protein from the specific cancer PPI network. Degree-entropy and cycle basis are provided only as alternative measures of network complexity. When the elimination of proteins generated the same reduction in Betti, they were considered “equivalent targets”. A node connecting two clusters of proteins would be considered a node with high betweeness. We used highest betweeneness-centrality to differentiate equivalency targets, and the shaded entries have lowest Betti numbers and high betweeness centrality in the specific cancer

From: Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks

  

AML

Bladder

CML

Colorectal

Endometrial

Glioma

NSCL

Pancreatic

Renal

SCL

Thyroid

5 years Survival [%]

23.6

78.1

55.2

63.6

68.6

33.4

18

5.5

69.5

6.2

97.2

Degree-Entropy

2.16

1.52

2.11

1.63

1.6

2.22

2.23

2

1.59

2.06

1.38

Cycle-Basis

108

20

115

58

45

128

75

72

52

150

24

Nominal Betti

107

20

114

51

45

128

50

38

51

149

24

Best Betti

95

15

101

41

35

109

37

29

34

131

17

Equivalent Targets

FLT3

        

ITGA3

 

HRAS

MAPK3

AKT1

AKT3

 

HRAS

   

ITGA6

HRAS

NRAS

MAPK1

AKT2

AKT2

PDPK1

NRAS

KRAS

KRAS

HIF1A

ITGA2B

NRAS

KRAS

 

AKT3

AKT1

ILK

KRAS

  

EPAS1

ITGB1

KRAS

         

ITGA2

 
         

ITGAV