Mutations in the SPOP Gene Diagnose Prostate Cancer

Prostate cancer is a clinically and molecularly heterogeneous disease, with marked variability in patient outcomes. Each year more than 200,000 men are diagnosed with prostate cancer.

Molecular classification holds the promise of improving risk stratification by defining distinct classes of prostate cancer associated with specific genetic alterations; however, until now, few driver mutations have been discovered that can allow for such classification.

Researchers at Weill Cornell Medical College have discovered recurrent mutations in the SPOP gene in human prostate cancer. These mutations occur in about 10% of all prostate cancers analyzed to date from multiple independent patient cohorts.

The mutations in SPOP designate a specific molecular subclass of prostate cancer and were found exclusively in the structurally-defined substrate-binding cleft of SPOP. Structural analysis suggests that these mutations will inactivate SPOP function by disrupting SPOP-substrate interaction, and loss of SPOP function in prostate cell lines resulted in increased invasiveness of the tumor cells and metastatic spread of prostate cancer. Importantly, all SPOP mutations occurred in tumors that were negative for ERG rearrangement and for PTEN deletion.

The identification of these recurring SPOP mutations can be used in the detection or diagnosis of prostate cancer. SPOP mutations may be useful to determine the prognosis of prostate cancer patients, or to help classify different types of prostate cancer. Determination of SPOP mutation status may be able to predict the response to certain therapies (surgery, radiation, chemotherapeutics, or targeted pharmacologic therapy) used in the treatment of prostate cancer. Furthermore, mutation of SPOP may alter the substrates to which SPOP binds, and small molecules may be developed to target this alteration of SPOP function. SPOP mutations are also likely to result in the dysregulation of downstream pathways leading to the initiation or progression of prostate cancers. These downstream pathways may represent excellent targets for pharmacologic intervention for the prevention or treatment of prostate cancer.

Potential Applications

• Prostate cancer diagnosis and prognosis
• Predict prostate cancer patients' response to certain therapy

Advantages

A new biomarker for diagnosing prostate cancer and predicting disease progression and response to therapy.