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This study introduces the prostate cancer linear energy transfer sensitivity index (PCLSI) as a novel method to predict relative biological effectiveness (RBE) in prostate cancer using linear energy transfer (LET) in proton therapy based on screening for DNA repair mutations.
Materials and Methods:
Five prostate cancer cell lines with DNA repair mutations known to cause sensitivity to LET and DNA repair inhibitors were examined using published data. Relative Du145 LET sensitivity data were leveraged to deduce the LET equivalent of olaparib doses. The PCLSI model was built using three of the prostate cancer cell lines (LNCaP, 22Rv1 and Du145) with DNA mutation frequency from patient cohorts. The PCLSI model was compared against two established RBE models, McNamara and McMahon, for LET-optimized prostate cancer treatment plans.
Results:
The PCLSI model relies on the presence of eight DNA repair mutations: AR, ATM, BRCA1, BRCA2, CDH1, ETV1, PTEN and TP53, which are most likely to predict increased LET sensitivity and RBE in proton therapy. In the LET-optimized plan, the PCLSI model indicates that prostate cancer cells with these DNA repair mutations are more sensitive to increased LET than the McNamara and McMahon RBE models, with expected RBE increases ranging from 11%–33% at 2keV/µm.
Conclusions:
The PCLSI model predicts increasing RBE as a function of LET in the presence of certain genetic mutations. The integration of LET-optimized proton therapy and genetic mutation profiling could be a significant step toward the use of individualized medicine to improve outcomes using RBE escalation without the potential toxicity of physical dose escalation.
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