The figure above depicts the complexity of genes with high network-smoothed mutation scores in a single subtype of ovarian cancer. Patients in this subtype exhibited the lowest survival and highest chemotherapy resistance rates in the cohort. Node size corresponds to smoothed mutation scores. Node color corresponds to the gene’s functional  category. Thickened node outlines indicate known cancer genes. An underlined gene symbol in the network indicates that somatic mutations were found for that gene in the examined subtype. Image courtesy of Trey Ideker, UC San Diego. 
“Wildly Heterogeneous Genes”New approach subtypes cancers by shared genetic effects; a step toward personalized medicine
Cancer tumors almost never share the exact same genetic mutations, a fact that has confounded scientific efforts to better categorize cancer types and develop more targeted, effective treatments.
In a paper published in the September 15 advanced online edition of Nature Methods, researchers at the University of California, San Diego propose a new approach called network-based stratification (NBS), which identifies cancer subtypes not by the singular mutations of individual patients, but by how those mutations affect shared genetic networks or systems.  
“Subtyping is the most basic step toward the goal of personalized medicine,” said principal investigator Trey Ideker, PhD, division chief of Genetics in the UC San Diego School of Medicine and a professor in the Departments of Medicine and Bioengineering at UC San Diego. “Based on patient data, patients are placed into subtypes with associated treatments. For example, one subtype of cancer is known to respond well to drug A, but not drug B. Without subtyping, every patient looks the same by definition, and you have no idea how to treat them differently.” 
Recent advances in knowledge and technology have made it easier (and less expensive) to sequence individual genomes, especially in the treatment of cancer, which is fundamentally a disease of genes. 
But genes are “wildly heterogeneous,” said Ideker. It is in combination, influenced by other factors, that mutated genes cause diseases like cancer. Every patient’s cancer is genetically unique, which can affect the efficacy and outcomes of clinical treatment.
More here

The figure above depicts the complexity of genes with high network-smoothed mutation scores in a single subtype of ovarian cancer. Patients in this subtype exhibited the lowest survival and highest chemotherapy resistance rates in the cohort. Node size corresponds to smoothed mutation scores. Node color corresponds to the gene’s functional  category. Thickened node outlines indicate known cancer genes. An underlined gene symbol in the network indicates that somatic mutations were found for that gene in the examined subtype. Image courtesy of Trey Ideker, UC San Diego.

“Wildly Heterogeneous Genes”
New approach subtypes cancers by shared genetic effects; a step toward personalized medicine

Cancer tumors almost never share the exact same genetic mutations, a fact that has confounded scientific efforts to better categorize cancer types and develop more targeted, effective treatments.

In a paper published in the September 15 advanced online edition of Nature Methods, researchers at the University of California, San Diego propose a new approach called network-based stratification (NBS), which identifies cancer subtypes not by the singular mutations of individual patients, but by how those mutations affect shared genetic networks or systems. 

“Subtyping is the most basic step toward the goal of personalized medicine,” said principal investigator Trey Ideker, PhD, division chief of Genetics in the UC San Diego School of Medicine and a professor in the Departments of Medicine and Bioengineering at UC San Diego. “Based on patient data, patients are placed into subtypes with associated treatments. For example, one subtype of cancer is known to respond well to drug A, but not drug B. Without subtyping, every patient looks the same by definition, and you have no idea how to treat them differently.”

Recent advances in knowledge and technology have made it easier (and less expensive) to sequence individual genomes, especially in the treatment of cancer, which is fundamentally a disease of genes.

But genes are “wildly heterogeneous,” said Ideker. It is in combination, influenced by other factors, that mutated genes cause diseases like cancer. Every patient’s cancer is genetically unique, which can affect the efficacy and outcomes of clinical treatment.

More here

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