摘要:
Gene expression profiling is a powerful tool that has varied utility. It enables classification of multiple myeloma into subtypes and identifing genes directly involved in disease pathogensis and clinical manifestation. The present invention used gene expression profiling in large uniformly treated population of patients with myeloma to identify genes associated with poor prognosis. It also demonstrated that over-expression of CKS1B gene, mainly due to gene amplification that was determined by Fluorescent in-situ hybridization to impart a poor prognosis in multiple myleoma. It is further contemplated that therapeutic strategies that directly target CKS1B or related pathways may represent novel, and more specific means of treating high risk myeloma and may prevent its secondary evolution.
摘要:
Gene expression profiling in multiple myeloma patients identifies genes that distinguish between patients with subsequent early death or long survival after treatment. Poor survival is linked to over-expression of genes such as ASPM, OPN3 and CKS1B which are located in chromosome 1q. Given the frequent amplification of 1q in many cancers, it is possible that these genes can be used as powerful prognostic markers and therapeutic targets for multiple myeloma and other cancer.
摘要:
Gene expression profiling in multiple myeloma patients identifies genes that distinguish between patients with subsequent early death or long survival after treatment. Poor survival is linked to over-expression of genes such as ASPM, OPN3 and CKS1B which are located in chromosome 1q. Given the frequent amplification of 1q in many cancers, it is possible that these genes can be used as powerful prognostic markers and therapeutic targets for multiple myeloma and other cancer.
摘要:
Gene expression profiling reveals four distinct subgroups of multiple myeloma that have significant correlation with various clinical characteristics. Diagnosis for multiple myeloma (and possibly monoclonal gammopathy of undetermined significance) based on differential expression of 14 genes, as well as prognosis for the four subgroups of multiple myeloma based on the expression of 24 genes are established. A 15-gene model that classifies myeloma into 7 groups is also reported. Gene expression profiling also allows placing multiple myeloma into a developmental schema parallel to that of normal plasma cell differentiation. Development of a gene expression- or developmental stage-based classification system for multiple myeloma would lead to rational design of more accurate and sensitive diagnostics, prognostics and tumor-specific therapies for multiple myeloma.
摘要:
Gene expression profiling in multiple myeloma patients identifies genes that distinguish between patients with subsequent early death or long survival after treatment. Poor survival is linked to over-expression of genes such as ASPM, OPN3 and CKS1B which are located in chromosome 1q. Given the frequent amplification of 1q in many cancers, it is possible that these genes can be used as powerful prognostic markers and therapeutic targets for multiple myeloma and other cancer.
摘要:
Provided herein is a method for gene expression profiling multiple myeloma patients into distinct subgroups via DNA hybridization and hierarchical clustering analysis of the hybridization data where the results may further be used to identify therapeutic gene targets. Also provided is a method for controlling bone loss in an individual via pharmacological inhibitors of DKK1 protein. In addition provided herein is a method for diagnosing multiple myeloma using a 15-gene model that classifies myeloma into groups 1-7.
摘要:
Provided herein is a method for gene expression profiling multiple myeloma patients into distinct subgroups via DNA hybridization and hierarchical clustering analysis of the hybridization data where the results may further be used to identify therapeutic gene targets. Also provided is a method for controlling bone loss in an individual via pharmacological inhibitors of DKK1 protein. In addition provided herein is a method for diagnosing multiple myeloma using a 15-gene model that classifies myeloma into groups 1-7.
摘要:
Gene expression profiling in multiple myeloma patients identifies genes that distinguish between patients with subsequent early death or long survival after treatment. Poor survival is linked to over-expression of genes such as ASPM, OPN3 and CKS1B which are located in chromosome 1q. Given the frequent amplification of 1q in many cancers, it is possible that these genes can be used as powerful prognostic markers and therapeutic targets for multiple myeloma and other cancer.
摘要:
Gene expression profiling is a powerful tool that has varied utility. It enables classification of multiple myeloma into subtypes and identifying genes directly involved in disease pathogensis and clinical manifestation. The present invention used gene expression profiling in large uniformly treated population of patients with myeloma to identify genes associated with poor prognosis. It also demonstrated that over-expression of CKS1B gene, mainly due to gene amplification that was determined by Fluorescent in-situ hybridization to impart a poor prognosis in multiple myleoma. It is further contemplated that therapeutic strategies that directly target CKS1B or related pathways may represent novel, and more specific means of treating high risk myeloma and may prevent its secondary evolution.
摘要:
Gene expression profiling reveals four distinct subgroups of multiple myeloma that have significant correlation with various clinical characteristics. Diagnosis for multiple myeloma (and possibly monoclonal gammopathy of undetermined significance) based on differential expression of 14 genes, as well as prognosis for the four subgroups of multiple myeloma based on the expression of 24 genes are established. A 15-gene model that classifies myeloma into 7 groups is also reported. Gene expression profiling also allows placing multiple myeloma into a developmental schema parallel to that of normal plasma cell differentiation. Development of a gene expression- or developmental stage-based classification system for multiple myeloma would lead to rational design of more accurate and sensitive diagnostics, prognostics and tumor-specific therapies for multiple myeloma.