Table 1. Neo-antigens identified from literature.

Peptide number	HLA	Parental peptide sequence	Parental binding affinity (nM)	Parental netchop score	Mutant peptide sequence	Mutant binding affinity (nM)	Mutant netchop score	PMBEC value	Coverage in cancer exome	Mutated in TCR exposed surface	Protein	Cancer type	Reference
1	A*02:01	FLDEFMEAV	2.24	0.734636	FLDEFMEGV	2.72	0.700886	0.0383	3 out of 3 exomes	YES	ME-1	NSCL cancer	Karanikas V et al.25
2	A*02:01	LLLDDSLVSI	6.89	0.954141	LLLDDLLVSI	5.39	0.94917	-0.0585	3 out of 3 exomes	YES	Prdx5	melanoma	Sensi M et al.26
3	A*02:01	SLADEAEVHL	38.56	0.969244	SLADEAEVYL	12.38	0.958266	0.0366	3 out of 3 exomes	YES	GAS7	melanoma	Zhou J et al.27
4	A*03:01	KIFSEVTPK	16.08	0.972275	KIFSEVTLK	14.09	0.971104	-0.051	3 out of 3 exomes	YES	SIRT2	melanoma	Lennerz V et al.12
5	A*68:02	ETVSEESNV	27.15	0.516073	ETVSEQSNV	19.44	0.671327	0.0281	3 out of 3 exomes	YES	Elongation Factor 2/EEF2	SCL cancer	Hogan KT et al.28
6	A*02:01	FIASKGVKLV	43.7	0.921914	FIASNGVKLV	29.49	0.938058	-0.034	3 out of 3 exomes	YES	a-Actinin-4/ACTN4	NSCL cancer	Echchakir H et al.29
7	A*24:02	SYLDSGIHS	18745.5	0.297074	SYLDSGIHF	41.4	0.973556	-0.0868	3 out of 3 exomes	YES	B-catenin/CTNNB1	melanoma	Robbins PF et al.30
8	A*03:01	KILDAVVAQE	14976.43	0.128682	KILDAVVAQK	48.23	0.969326	-0.0695	3 out of 3 exomes	YES	SNRP116/EFTUD2	melanoma	Lennerz V et al.12
9	A*03:01	EINKNPKYKK	6061.38	0.850773	KINKNPKYKK	157.05	0.850773	-0.0695	3 out of 3 exomes	YES	Myosin class I	melanoma	Zorn E et al.31
10	A*03:01	TLGWLLQTPK	178.74	0.675804	TLDWLLQTPK	282.03	0.714946	-0.0087	3 out of 3 exomes	YES	GPNMB	melanoma	Lennerz V et al.12
11	B*44:03	AEPIDIQTW	258.23	0.965739	AEPINIQTW	287.87	0.968687	0.0194	3 out of 3 exomes	YES	KIAA0205	bladder cancer	Guéguen M et al.32
12	B*44:02	SELFRSRLDSY	182.33	0.763436	SELFRSGLDSY	184.25	0.908365	-0.0232	2 out of 3 exomes	YES	MUM-2	melanoma	Chiari R et al.22
13	B*52:01	QQITQTEV	4077.72	0.962417	QQITKTEV	5030.87	0.944965	-0.0332	3 out of 3 exomes	YES	NFYC	NSCL cancer	Takenoyama M et al.33
14	C*06:02	FRSRLDSYV	3508.71	0.73499	FRSGLDSYV	5762.85	0.872751	-0.0232	2 out of 3 exomes	YES	MUM-2	melanoma	Chiari R et al.22
15	A*02:01	ARDPHSGHFV	25221.62	0.668099	ACDPHSGHFV	11191.79	0.475792	-0.0483	3 out of 3 exomes	NO	CDK4	melanoma	Wölfel T et al.11
16	A*02:01	SLFEGIDFYT	6.78	0.0445	SLFEGIDIYT	23.2	0.04132	0.0629	3 out of 3 exomes	YES	hsp70–2	renal cell carcinoma	Gaudin C et al.34
17	B*07:02	GPHVPESAF	68.08	0.96896	RPHVPESAF	9.67	0.96843	-0.0232	3 out of 3 exomes	NO	RBAF600/UBR4	melanoma	Lennerz V et al.12

Cancer neo-antigens (n = 17) that had been previously discovered by unbiased and non-computational strategies were analyzed to assess the sensitivity of our cancer exome-based neo-antigen prediction algorithm pipeline. Neo-antigens and their corresponding values as predicted by netMHCpan-2.4, netchop Cterm3.0 and the peptide:MHC binding energy covariance (PMBEC) matrix are shown. Presence of a non-synonymous mutation within the TCR exposed surface is indicated. Peptides 1–11 would have been identified by exome guided analysis, peptide 12 would have been identified in two out of three patients, peptides 13–17 would not have been identified.^25-34 Bold numbers indicate exlusion criteria.