A system for developing a radiation therapy treatment plan for a subject having a tumor, characterized by: a processor; and a memory operably coupled to the processor, the memory having computer-executable instructions stored thereon that, when executed by the processor, cause the processor to: determine a radiosensitivity index of the tumor, the radiosensitivity index being assigned from expression levels of one or more signature genes, wherein the radiosensitivity index is assigned using a linear regression model of the expression levels of the one or more signature genes; derive a subject-specific variable based on the radiosensitivity index, wherein the subject-specific variable is derived using a linear quadratic model for cell survival, the radiosensitivity index being approximately equal to cell survival; obtain a genomic adjusted radiation dose effect value for the tumor, the genomic adjusted radiation dose effect value being predictive of tumor recurrence in the subject after treatment; and determine a radiation dose based on the subject-specific variable and the genomic adjusted radiation dose effect value, wherein: the radiosensitivity index is equal to e -αd-βd^2, where α is the subject-specific variable, β is a standard fractionation constant, and d is the radiation dose, and the genomic adjusted radiation dose effect value is equal to nd(α + βd), where α is the subject-specific variable, β is the standard fractionation constant, d is the radiation dose, and n is a number of radiation treatments. a processor; and a memory operably coupled to the processor, the memory having computer-executable instructions stored thereon that, when executed by the processor, cause the processor to: determine a radiosensitivity index of the tumor, the radiosensitivity index being assigned from expression levels of one or more signature genes, wherein the radiosensitivity index is assigned using a linear regression model of the expression levels of the one or more signature genes; derive a subject-specific variable based on the radiosensitivity index, wherein the subject-specific variable is derived using a linear quadratic model for cell survival, the radiosensitivity index being approximately equal to cell survival; obtain a genomic adjusted radiation dose effect value for the tumor, the genomic adjusted radiation dose effect value being predictive of tumor recurrence in the subject after treatment; and determine a radiosensitivity index of the tumor, the radiosensitivity index being assigned from expression levels of one or more signature genes, wherein the radiosensitivity index is assigned using a linear regression model of the expression levels of the one or more signature genes; derive a subject-specific variable based on the radiosensitivity index, wherein the subject-specific variable is derived using a linear quadratic model for cell survival, the radiosensitivity index being approximately equal to cell survival; obtain a genomic adjusted radiation dose effect value for the tumor, the genomic adjusted radiation dose effect value being predictive of tumor recurrence in the subject after treatment; and determine a radiation dose based on the subject-specific variable and the genomic adjusted radiation dose effect value, wherein: the radiosensitivity index is equal to e -αd-βd^2, where α is the subject-specific variable, β is a standard fractionation constant, and d is the radiation dose, and the genomic adjusted radiation dose effect value is equal to nd(α + βd), where α is the subject-specific variable, β is the standard fractionation constant, d is the radiation dose, and n is a number of radiation treatments. the radiosensitivity index is equal to e -αd-βd^2, where α is the subject-specific variable, β is a standard fractionation constant, and d is the radiation dose, and the genomic adjusted radiation dose effect value is equal to nd(α + βd), where α is the subject-specific variable, β is the standard fractionation constant, d is the radiation dose, and n is a number of radiation treatments.