Abstract: This disclosure is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The disclosure also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma. More in particular, the disclosure provides a method for determining the disease outcome or the prognosis of a patient diagnosed with multiple myeloma by classifying the patient into a high risk or a low risk category, based on a 92-gene classifier.

Abstract: This disclosure is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The disclosure also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma. More in particular, the disclosure provides a method for determining the disease outcome or the prognosis of a patient diagnosed with multiple myeloma by classifying said patient into a high risk or a low risk category, based on a 92-gene classifier.

Abstract: The present disclosure relates to methods and kits for classifying an individual afflicted with multiple myeloma based on the likelihood of response to immunomodulatory drugs (IMiDs), such as thalidomide and lenalidomide. The disclosure further relates to methods of treating an individual afflicted with multiple myeloma with an IMiD and with methods for determining a therapy regime based on the likelihood of response to an IMiD as a result of genetic characteristic of the patient.

Abstract: This disclosure is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The disclosure also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma. More in particular, the disclosure provides a method for determining the disease outcome or the prognosis of a patient diagnosed with multiple myeloma by classifying said patient into a high risk or a low risk category, based on a 92-gene classifier.

Abstract: The present invention is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The invention also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma. More in particular, the invention provides a method for determining the disease outcome or the prognosis of a patient diagnosed with multiple myeloma by classifying said patient into a high risk or a low risk category, based on a 92 gene classifier.

Abstract: The disclosure is in the field of medical treatments and relates to the treatment of multiple myeloma (MM). In particular, it provides means and methods for the improved treatment of certain subgroups of MM patients, more in particular, patients with a poor prognosis. In a particular embodiment, the disclosure provides a method for determining whether a subject with multiple myeloma is likely to respond to a treatment with a proteasome inhibitor wherein the method comprises the step of performing, on a sample from the subject, a gene expression analysis of a number of N genes selected from the group consisting of the genes NUAK1, ITGB7, AGMAT, TFAP2C, CCDC85A, CLEC7A, TMEM37, RNF144A, and CMPK2, wherein N is at least 2 and wherein it is concluded that the subject is likely to respond to a treatment with a proteasome inhibitor in the case where at least two of the N genes are aberrantly expressed.

Abstract: The disclosure is in the field of medical treatments and relates to the treatment of cancer, in particular, multiple myeloma (MM). Even more in particular, it provides means and methods for the improved treatment of certain subgroups of MM patients, more in particular, subjects with a poor prognosis. In a particular embodiment, the disclosure provides a method of treatment wherein subjects with a poor prognosis are selected and treated with a proteasome inhibitor such as Bortezomib. The disclosure further provides means and methods for identifying subjects with a poor prognosis. More in particular, the disclosure provides a composition comprising a proteasome inhibitor for use in the treatment of a subject with multiple myeloma when the subject has been diagnosed with an amp1q chromosomal aberration.

Abstract: The present invention is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The invention also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma. More in particular, the invention provides a method for determining the disease outcome or the prognosis of a patient diagnosed with multiple myeloma by classifying said patient into a high risk or a low risk category, based on a 92 gene classifier.

Abstract: The present invention is in the field of molecular diagnostics and relates to a method for classifying samples obtained from patients diagnosed with multiple myeloma into three newly defined clusters. The invention also relates to a method for determining the prognosis of an individual diagnosed with multiple myeloma as well as a method for the prediction of the response to treatment of an individual diagnosed with multiple myeloma.