Gene Expression Profile Algorithm for Calculating a Recurrence Score for a Patient with Kidney Cancer

A method of predicting a likelihood of a clinical outcome for a patient with kidney cancer, comprising:

• determining a level of one or more RNA transcripts, or an expression product thereof, in a tumor sample obtained from the patient, wherein the one or more RNA transcripts, or an expression product thereof, is selected from APOLD1, EDNRB, NOS3, PPA2B, EIF4EBP1, LMNB1, TUBB2A, CCL5, CEACAM1, CX3CL1, and IL-6;
• assigning the one or more RNA transcripts, or an expression product thereof, to one or more gene subsets;
• calculating a quantitative score for the patient by weighting the level of one or more RNA transcripts, or an expression product thereof, by their contribution to a clinical outcome;
• and
• predicting a likelihood of a clinical outcome for the patient based on the quantitative score.

A method for obtaining a recurrence score (RS) for a patient with kidney cancer, comprising:

• extracting RNA from a tumor sample obtained from the patient;
• reverse transcribing an RNA transcript of at least one prognostic gene selected from APOLD1, EDNRB, NOS3, PPA2B, EIF4EBP1, LMNB1, TUBB2A, CCL5, CEACAM1, CX3CL1, and IL-6 to produce a cDNA of the prognostic gene;
• amplifying the cDNA of the prognostic gene;
• producing an amplicon of the RNA transcript of the prognostic gene;
• assaying a level of the amplicon of the prognostic gene;
• normalizing the level against the level of an amplicon of at least one reference RNA transcript in the tumor sample to provide a normalized amplicon level of the prognostic gene;
• assigning the normalized amplicon level to a gene subset;
• weighting the gene subset according to its contribution to cancer recurrence;
• calculating a recurrence score (RS) for the patient using the weighted gene subset and the normalized amplicon level;
• and
• generating a report comprising the RS.