A prognostic method for determining risk of death, of a human subject with a neoplasia, which comprises identifying a population of neoplasia-specific mutations in a neoplasia specimen of a subject; assessing the neoplasia-specific mutations identified to classify Class I and Class II neoantigens encoded by said mutations; analyzing the neoantigens encoded by said mutations to identify and classify neoantigens that engage effector T cells and neo-epitopes that engage regulatory T cells, and computing a prognostic score from the immunogenicity of the population, wherein assessing neoplasia-specific mutations comprises: a) determining a binding score for a mutated peptide to one or more MHC molecules, wherein said mutated peptide is encoded by at least one of said neoplasia-specific mutations; b) determining a binding score for a non-mutated peptide to the one or more MHC molecules, wherein the non-mutated peptide is identical to the mutated peptide except for the encoded at least one of said neoplasia-specific mutations; c) determining the percentile rank of the binding scores of both the mutated peptide of step (a) and the non-mutated peptide of step (b) as compared to an expected distribution of binding scores for at least 10,000 randomly generated peptides using naturally observed amino acid frequencies; d) determining the TCR facing amino acid residues of said mutated peptide and said non-mutated peptide; and e) using it to calculate a prognostic score when: 1) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution and the non-mutated peptide has a determined binding score below the top 10 percentile of the expected distribution; or 2) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution, the non-mutated peptide has a determined binding score in the top 10 percentile of the expected distribution, and there is at least one mismatched TCR facing amino acid between the mutated peptide the non-mutated peptide. a) determining a binding score for a mutated peptide to one or more MHC molecules, wherein said mutated peptide is encoded by at least one of said neoplasia-specific mutations; b) determining a binding score for a non-mutated peptide to the one or more MHC molecules, wherein the non-mutated peptide is identical to the mutated peptide except for the encoded at least one of said neoplasia-specific mutations; c) determining the percentile rank of the binding scores of both the mutated peptide of step (a) and the non-mutated peptide of step (b) as compared to an expected distribution of binding scores for at least 10,000 randomly generated peptides using naturally observed amino acid frequencies; d) determining the TCR facing amino acid residues of said mutated peptide and said non-mutated peptide; and e) using it to calculate a prognostic score when: 1) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution and the non-mutated peptide has a determined binding score below the top 10 percentile of the expected distribution; or 2) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution, the non-mutated peptide has a determined binding score in the top 10 percentile of the expected distribution, and there is at least one mismatched TCR facing amino acid between the mutated peptide the non-mutated peptide. 1) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution and the non-mutated peptide has a determined binding score below the top 10 percentile of the expected distribution; or 2) the mutated peptide has a determined binding score in the top 5 percentile of the expected distribution, the non-mutated peptide has a determined binding score in the top 10 percentile of the expected distribution, and there is at least one mismatched TCR facing amino acid between the mutated peptide the non-mutated peptide.