Abstract: Disclosed herein are methods for personalized treatment of individual patient tumors. A computer software configured to integrate with a radiation therapy treatment planning system is presented. The computer software is configured to: assign a radiation sensitivity index (RSI) of a subject's tumor based at least in part on expression levels of one or more signature genes in the tumor; calculate a recommended personalized radiation dosage (RxRSI) for the subject based at least in part on a pre-determined genomic adjusted radiation dose (GARD) value and the RSI; and provide, to the radiation therapy treatment planning system, the recommended RxRSI as a radiation therapy dose for a radiation plan.

Abstract: Systems and methods for personalized dose and fractionation for radiation therapy are described herein. An example method can include predicting a patient-specific radiosensitivity parameter alpha (?) value for a tumor, where the patient-specific radiosensitivity parameter alpha (?) value is predicted based on a first set of signature genes. The method can also include predicting a patient-specific radiosensitivity parameter beta (?) value for the tumor, where the patient-specific radiosensitivity parameter beta (?) value is predicted based on a second set of signature genes. The method can further include calculating a patient-specific dose and fractionation using a radiation cytotoxicity score (RCS) function and the patient-specific radiosensitivity parameters alpha (?) and beta (?) values. RCS is predictive of clinical outcome.

Abstract: Disclosed herein are methods for personalized treatment of individual patient tumors. A computer software configured to integrate with a radiation therapy treatment planning system is presented. The computer software is configured to: assign a radiation sensitivity index (RSI) of a subject's tumor based at least in part on expression levels of one or more signature genes in the tumor; calculate a recommended personalized radiation dosage (RxRSI) for the subject based at least in part on a pre-determined genomic adjusted radiation dose (GARD) value and the RSI; and provide, to the radiation therapy treatment planning system, the recommended RxRSI as a radiation therapy dose for a radiation plan.

Abstract: Disclosed herein are methods for personalized treatment of individual patient tumors. A computer software configured to integrate with a radiation therapy treatment planning system is presented. The computer software is configured to: assign a radiation sensitivity index (RSI) of a subject’s tumor based at least in part on expression levels of one or more signature genes in the tumor; calculate a recommended personalized radiation dosage (RxRSI) for the subject based at least in part on a pre-determined genomic adjusted radiation dose (GARD) value and the RSI; and provide, to the radiation therapy treatment planning system, the recommended RxRSI as a radiation therapy dose for a radiation plan.

Abstract: Disclosed herein are methods for personalized treatment of individual patient tumors. In one embodiment, a method of calculating a personalized radiation therapy dosage for a subject comprises determining expression levels of one or more signature genes from a subject's tumor sample, applying a linear regression model to the gene expression levels and assigning a radiation sensitivity index (RSI) to the subject's tumor sample, calculating a genomic adjusted radiation dose (GARD) value based on RSI, radiation dose and fractionation schedule of the subject, and calculating a personalized radiation dosage (RxRSI) for the subject based on a pre-determined GARD value.

Abstract: Disclosed herein are methods for personalized treatment of individual patient tumors. In one embodiment, a method of calculating a personalized radiation therapy dosage for a subject comprises determining expression levels of one or more signature genes from a subject's tumor sample, applying a linear regression model to the gene expression levels and assigning a radiation sensitivity index (RSI) to the subject's tumor sample, calculating a genomic adjusted radiation dose (GARD) value based on RSI, radiation dose and fractionation schedule of the subject, and calculating a personalized radiation dosage (RxRSI) for the subject based on a pre-determined GARD value.

Abstract: A classifier to predict cellular radiation sensitivity based on gene expression profiles in thirty-five cell lines from the NCI panel of 60 cancer cell lines (NCI-60), using a novel approach to predictive gene analysis. Three novel genes are provided, retinoblastoma binding protein 4 (RbAp48), G-protein signaling regulator 19 (RGS19) and ribose-5-phosphate isomerase A (R5PIA) whose expression values were correlated with radiation sensitivity.