Compositions and methods relating to proliferative disorders

A method of identifying an agent effective to promote or inhibit G2 progression in vivo are provided according to aspects of the present invention which include providing a cell of a TR Class 4 cell line characterized by a TR Class 3 outlier SET response, wherein the cell comprises a TR nucleic acid expression cassette encoding a TR element and a reporter;

• wherein the expression cassette is stably integrated into the genome of the cells;
• administering the cell to a non-human animal, producing a xenograft tumor in the non-human animal;
• administering a test substance to the non-human animal;
• and measuring the effect of the test substance on the SET response, wherein an increase in a SET response identifies the agent as a SET agonist effective to promote G2 progression in vivo.

A method of identifying an agent effective as a component of a SET Combination drug for treatment a proliferative disease, comprising:

• providing a cell characterized by a TR Class 3 SET response or a TR Class 3 SET outlier response, wherein the cell comprises an expression construct encoding a TR element and a reporter stably integrated in the genome of the cell;
• contacting the cell with a test substance;
• and
• measuring the effect of the test substance on protein synthesis from a SET ribosome compared to a control, wherein inhibition of protein synthesis from a SET ribosome by the test substance identifies the substance as an agent effective as a component of a SET Combination drug for treatment a proliferative disease.

A method of generating a metastatic cancer cell line model, comprising:

• introducing an expression cassette encoding a TR element and a reporter into a cell, producing a parental population of cells wherein the expression cassette is stably integrated into the genome of the cells;
• isolating subclones of the parental population;
• administering a SET agonist to a population of cells of each subclone to induce a SET TR response in the population of cells of each subclone;
• assaying the TR SET response in the population of cells of each subclone by detecting expression of the reporter;
• ranking the TR SET response of each subclone compared to each other subclone, establishing a range of TR SET responses characterized by an average response;
• selecting the subclones characterized by detectable increases in expression of the reporter of at least two standard deviations greater than the mean response, thereby defining the selected subclones as TR Class 3 TR SET response subclones;
• administering a SET agonist to a population of cells of each TR Class 3 TR SET response subclone to induce a SET TR response in the population of cells of each TR Class 3 TR SET response subclone;
• assaying the TR SET response in the population of cells of each TR Class 3 SET response subclone by detecting expression of the reporter;
• ranking the TR SET response of each TR Class 3 SET response subclone compared to each other TR Class 3 SET response subclone, establishing a range of TR SET responses characterized by an average response;
• selecting the TR Class 3 SET response subclones characterized by detectable increases in expression of the reporter of at least two standard deviations greater than the mean response, thereby defining the selected TR Class 3 SET response subclones as TR Class 3 SET response outliers;
• administering one or more toxins to cells of one or more subclones characterized as a TR Class 3 SET response outliers;
• and
• detecting a response of the cells of the one or more subclones characterized as a TR Class 3 SET response outliers indicative of drug and stress resistance due to elevated SET ribosome activity in the cells of the subclone, thereby determining that the cells are TR Class 4 cells;
• and
• thereby generating a metastatic cancer cell line model.