Selection of cancer mutations for generation of a personalized cancer vaccine

A method for treating or limiting development of cancer comprising preparing a personalized vector vaccine encoding cancer neoantigens comprising the steps of:

• (a) determining neoantigens in a sample of cancerous cells, wherein each neoantigen
• is comprised within a coding sequence,
• comprises at least one mutations in the coding sequence resulting in a change of the encoded amino acid sequence that is not present in a sample of non-cancerous cells of said individual, and
• consists of 9 to 40 contiguous amino acids of the coding sequence in the sample of cancerous cells,
• (b) determining for each neoantigen the mutation allele frequency of each of said mutations of step (a) within the coding sequence,
• (c) determining the expression level of each coding sequence comprising at least one of said mutations,
• (i) in said sample of cancerous cells, or
• (ii) from an expression database of the same cancer type as the sample of cancerous cells,
• (d) predicting the MHC class I binding affinity of the neoantigens, wherein
• (I) the HLA class I alleles are determined from the sample of non-cancerous cells of said individual,
• (II) for each HLA class I allele determined in (I) the MHC class I binding affinity of each fragment consisting of 8 to 15 contiguous amino acids of the neoantigen is predicted, wherein each fragment is comprising at least one amino acid change caused by the mutation of step (a), and
• (III) the fragment with the highest MHC class I binding affinity determines the MHC class I binding affinity of the neoantigen, and in addition to or alternatively to step (d),
• (d′):
• determining the HLA class II alleles in the sample of non-cancerous cells of said individual,
• predicting the MHC class II binding affinity of the neoantigen, wherein
• for each HLA class II allele determined the MHC class II binding affinity for each fragment of 11 to 30 contiguous amino acids of the neoantigen is predicted, wherein each fragment is comprising at least one mutated amino acid generated by the mutation of step (a), and
• the fragment with the highest MHC class II binding affinity determines the MHC class II binding affinity of the neoantigen;
• (e) ranking the neoantigens according to the values of mutation allele frequency, expression level, and binding affinity of MHC class I and/or MHC class II determined in steps (b), (c), (d) and/or (d′), respectively, for each neoantigen from highest to lowest values, yielding, respectively, a first, a second, a third, and/or a fourth list of ranks,
• (f) calculating a rank sum from said first, second, third, and/or fourth list of ranks, wherein the rank sum is a weighted rank sum, wherein
• the number of neoantigens determined in step (a) is added to the rank value of each neoantigen:
• in the third list of ranks for which the prediction of MHC class I binding affinity of step (d) resulted in an IC50 value higher than 1000 nM and/or
• in the fourth list of ranks for which the prediction of MHC class II binding affinity of step (d′) resulted in an IC50 value higher than 1000 nM;
• and/or
• in case of step (c) (i) being performed by massively parallel transcriptome sequencing, the rank sum of step (f) is multiplied by a weighing factor (WF), wherein WF is
• 1, if the number of mapped transcriptome reads for the mutation is >0,
• 2, if the number of mapped transcriptome reads for the mutation is 0 and the number of mapped reads for the non-mutated sequence is 0 and the transcripts-per-million (TPM) value is at least 0.5,
• 3, if the number of mapped transcriptome reads for the mutation is 0 and the number of mapped reads for the non-mutated sequence is >0 and the transcripts-per-million (TPM) value is at least 0.5,
• 4, if the number of mapped transcriptome reads for the mutation is 0 and the number of mapped reads for the non-mutated sequence is 0 and the transcripts-per-million (TPM) value is <0.5, or
• 5, if the number of mapped transcriptome reads for the mutation is 0 and the number of mapped reads for the non-mutated sequence is >0 and the transcripts-per-million (TPM) value is <0.5;
• and
• ordering the neoantigens by increasing weighted rank sum, yielding a ranked list of neoantigens;
• (g) selecting 30-240 neoantigens from the ranked list of neoantigens obtained in (f) starting with the lowest rank;
• and
• (h) administering a vector encoding at least one of the 30-240 neoantigens selected in step (g) or a collection of vectors encoding each a portion of the 30-240 selected in step (g).