Predictive biomarker for cancer therapy
The present invention relates generally to the identification of patients suffering from cancer whether they will respond to specific therapies. More particularly the invention relates to a method and means for identifying responder to a therapy TLR-9 agonists.
1. A method for treating a patient suffering from cancer or an autoimmune disease with TLR-9 agonist MGN1703, wherein said method comprises:
taking a blood sample from a patient suffering from cancer or an autoimmune disease;
determining the frequency of activated natural killer T (NKT) cells of the blood sample of the patient;
predicting or monitoring whether the patient will respond or responds to the treatment with the TLR-9 agonist MGN1703, by evaluating whether the patient has a frequency of at least 3% of activated NKT cells of the whole NKT cell population; and
administering, or continuing to administer, the TLR-9 agonist MGN1703 to a patient having a frequency of at least 3% of activated NKT cells of the whole NKT cell population.
2. The method of claim 1 , wherein previously an induction therapy with a non-DNA drug was performed on the patient.
3. The method of claim 1 , wherein said patient suffers from cancer.
4. The method of claim 3 , wherein the TLR-9 agonist MGN1703 is part of a pharmaceutical composition.
5. The method of claim 4 , wherein the pharmaceutical composition is a vaccine.
6. The method of claim 1 , wherein the step of determining the frequency of activated natural killer T (NKT) cells of a blood sample of the patient comprises the steps of:
staining the blood sample with fluorescence-labelled antibodies:
Anti CD3-FITC,
Anti CD56-PE,
Anti CD69-APC;
incubating the sample; and
performing fluorescence activated cell sorting (FACS), wherein the activated NKT cells are gated as CD3 positive, CD56 positive and CD69 positive cells.