Methods for Classifying Samples Based on Network Modularity

A computer-readable medium, comprising computer-readable code that if executed is configured to:

• (a) compare the relative expression of a hub protein and an interacting partner detected in a subject's sample to a standard or model characteristic of a biological state, disease or disease stage;
• and
• (b) provide an indication of a biological state, disease or disease stage in said subject based upon the comparison,
• wherein said computer-readable code is configured to repeat (a) for additional interacting partners with said hub protein, and for additional hub proteins and their interacting partners.

A method of categorizing drug responsiveness in a population comprising:

• (a) determining the expression levels of hub proteins and interacting partners for each subject in the population;
• (b) identifying a group of subjects in the population that have a substantially similar response to the drug;
• and
• (c) clustering the hub protein and its interacting partners by the drug response of the group to generate a reference network signature indicating drug responses for the group of subjects.

A method for diagnosing a mammalian subject for breast cancer comprising:

• (a) providing a network signature characteristic of a breast cancer state generated by a method comprising:
• i. obtaining gene expression levels for multiple proteins from a reference mammalian population having two different biological states selected from a healthy state and breast cancer state;
• ii. for each different biological state identifying multiple sets of proteins formed by a hub protein that interacts with multiple interacting partner proteins and at least one interacting partner protein of the hub protein, wherein the hub protein is one or more of MAP3K1, GRB2, SHC, SRC, ESR1, BRCA1, RAD51, MRE11, a protein of the BASC complex, and a proteasome component or a ribosomal component of any of these proteins;
• iii. generating co-expression values for each set of proteins for the healthy state and the breast cancer state, wherein the co-expression value for each hub protein and each interacting partner protein is the difference between the actual gene expression level of the hub and the actual gene expression level of the interacting partner;
• and forming the network signature for the breast cancer state by selecting those sets of proteins in which changes in the patterns of co-expression values of the hub protein and its interacting proteins distinguish the breast cancer state from the healthy state;
• (b) contacting a biological sample obtained from said subject with reagents active to detect and measure the gene expression levels of the same sets of genes encoding the proteins that form said network signatures;
• (c) generating the co-expression value for each protein set in said sample;
• and
• (d) diagnosing the subject as having breast cancer when the co-expression values of the sets of proteins in the subject's sample forms a network signature that demonstrates the same changes in patterns of co-expression values as present in the breast cancer network signature.