Last Updated on 2026-02-11

• Supplementary Materials
  • Supplementary Data S1: NSCLC Patient Information
  • Supplementary Data S2: NSCLC Protein-Affecting Variants
  • Supplementary Data S3: NSCLC Missense Variants
  • Supplementary Data S4: NSCLC HLA Loss of Heterozygosity
  • Supplementary Data S5: NSCLC Shared Protein Lists
  • Supplementary Data S6: NSCLC pVACseq Class I Predictions
  • Supplementary Data S7: NSCLC pVACseq Class II Predictions
  • Supplementary Data S8: NSCLC pVACseq Peptidome Combined Predictions
  • Supplementary Data S9: NSCLC Tested Neoantigens
  • References

Supplementary Materials

This repository contains the supplementary data files for: Immunopeptidomics-guided identification of functional neoantigens in non-small cell lung cancer [1]. This repository is associated with

For Supplementary Figures S1-S11 and Supplementary Tables S1-S2, please refer to supplement-2026-02-11.pdf.

Supplementary Data S1 to S9 are csv files. The column names and contents of these files are described below.

Supplementary Data S1: NSCLC Patient Information

Supplementary Data S1, a csv file containing patient information with 24 rows and 21 column variables. Each row in Supplementary Data S1 represents observations for a single patient.

Column Variable	Description
accel_id	CRUK Accelerator patient identifier
target_lung_id	Targeted Lung Health Check patient identifier
tissue	NSCLC type: Adenocarcinoma or Squamous cell carcinoma
n_somatic_variants	Total number of somatic variants identified by whole exome sequencing
mut_burden_per_mb	Mutational burden: mutations per million bases of DNA. Exome target size was 35.7 Mb
obs_class_I	Number of observed HLA I peptides by mass spec. immunopeptidomics
obs_class_II	Number of observed HLA II peptides by mass spec. immunopeptidomics
HLA	Class I and II HLA allotypes identified by genomic sequencing
wet_weight	Wet weight of tumour tissue
tumour_purity	Tumour purity as calculated from WES by ASCAT
tumour_ploidy	Tumour ploidy as calculated from WES by ASCAT
til_status	Tumour infiltrating T-cell status by immunohistochemistry: Low, Moderate, High or NA
weeks_post_surgery	Number of weeks since surgery
status_as_of_2021_01_19	Status since 2021-01-19: Alive, Deceased or NA
date_of_diagnosis	Date of diagnosis
smoking_status	Smoking status
notes_2	Notes about smoking history

Supplementary Data S2: NSCLC Protein-Affecting Variants

Column Variable	Description
accel_id	CRUK Accelerator patient identifier
vid	Unique variant identifier
chrom	Chromosome
pos	Genomic coordinate
ref	Reference base
alt	Variant base
type	Variant type: snv, ins, del or complex. Single nucleotide variant, insertion, deletion and complex variant respectively
gene_name	HGNC gene name
ensg	Ensembl gene identifier
ensp	Ensembl protein identifier
consequence	Variant consequence annotation
biotype	Gene biotype filter: protein_coding
canonical	Canonical transcript flag
vaf	Variant allele frequency
depth	Sequencing depth
filter	Variant filter status
info	Information field from VCF file
format	Format of VCF variable columns
sample_1	Reference sample VCF variable values corresponding with format
sample_2	Tumour sample VCF variable values corresponding with format
tissue	Lung tumour tissue type: Squamous or Adenocarcinoma

Supplementary Data S3: NSCLC Missense Variants

Column Variable	Description
accel_id	CRUK Accelerator patient identifier
vid	Unique variant identifier
chrom	Chromosome
pos	Genomic coordinate
ref	Reference base
alt	Variant base
type	Variant type: snv, ins, del or complex. Single nucleotide variant, insertion, deletion and complex variant respectively
gene_name	HGNC gene name
ensg	Ensembl gene identifier
ensp	Ensembl protein identifier
vaf	Variant allele frequency
depth	Sequencing depth
filter	Variant filter status
info	Information field from VCF file
format	Format of VCF variable columns
sample_1	Reference sample VCF variable values corresponding with format
sample_2	Tumour sample VCF variable values corresponding with format
tissue	Lung tumour tissue type: Squamous or Adenocarcinoma

Supplementary Data S4: NSCLC HLA Loss of Heterozygosity

Column Variable	Description
accel_id	CRUK Accelerator patient identifier
message	HLA LOH detection message
HLA_A_type1	HLA allele type 1: A, B or C
HLA_A_type2	HLA allele type 2: A, B or C
LossAllele	HLA allele that was lost
KeptAllele	HLA allele that was retained

Supplementary Data S5: NSCLC Shared Protein Lists

Column Variable	Description
hla_class	HLA class (I or II)
intersection	Set intersection identifier
n_proteins	Number of patients observations of protein in set intersection
uniprot_id	UniProt protein identifier
gene_name	HGNC gene name

Supplementary Data S6: NSCLC pVACseq Class I Predictions

Column Variable	Description
sample	CRUK Accelerator patient identifier
chromosome	The chromosome of this variant
start	The start position of this variant in the zero-based, half-open coordinate system
stop	The stop position of this variant in the zero-based, half-open coordinate system
reference	The reference allele
variant	The alt allele
transcript	The Ensembl ID of the affected transcript
transcript_support_level	The transcript support level (TSL) of the affected transcript. NA if the VCF entry doesn't contain TSL information
ensembl_gene_id	The Ensembl ID of the affected gene
variant_type	The type of variant. missense for missense mutations, inframe_ins for inframe insertions, inframe_del for inframe deletions, and FS for frameshift variants
mutation	The amino acid change of this mutation
protein_position	The protein position of the mutation
gene_name	The Ensembl gene name of the affected gene
hgv_sc	The HGVS coding sequence variant name
hgv_sp	The HGVS protein sequence variant name
hla_allele	The HLA allele for this prediction
peptide_length	The peptide length of the epitope
sub_peptide_position	The one-based position of the epitope within the protein sequence used to make the prediction
mutation_position	The one-based position of the start of the mutation within the epitope sequence. 0 if the start of the mutation is before the epitope
mt_epitope_seq	The mutant epitope sequence
wt_epitope_seq	The wildtype (reference) epitope sequence at the same position in the full protein sequence. NA if there is no wildtype sequence at this position or if more than half of the amino acids of the mutant epitope are mutated
best_mt_score_method	Prediction algorithm with the lowest mutant ic50 binding affinity for this epitope
best_mt_score	Lowest ic50 binding affinity of all prediction algorithms used
corresponding_wt_score	ic50 binding affinity of the wildtype epitope. NA if there is no WT Epitope Seq
corresponding_fold_change	Corresponding WT Score / Best MT Score. NA if there is no WT Epitope Seq
tumor_dna_depth	Tumor DNA depth at this position. NA if VCF entry does not contain tumor DNA readcount annotation
tumor_dna_vaf	Tumor DNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain tumor DNA readcount annotation
tumor_rna_depth	Tumor RNA depth at this position. NA if VCF entry does not contain tumor RNA readcount annotation
tumor_rna_vaf	Tumor RNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain tumor RNA readcount annotation
normal_depth	Normal DNA depth at this position. NA if VCF entry does not contain normal DNA readcount annotation
normal_vaf	Normal DNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain normal DNA readcount annotation
gene_expression	Gene expression value for the annotated gene containing the variant. NA if VCF entry does not contain gene expression annotation
transcript_expression	Transcript expression value for the annotated transcript containing the variant. NA if VCF entry does not contain transcript expression annotation
median_mt_score	Median ic50 binding affinity of the mutant epitope across all prediction algorithms used
median_wt_score	Median ic50 binding affinity of the wildtype epitope across all prediction algorithms used. NA if there is no WT Epitope Seq
median_fold_change	Median WT Score / Median MT Score. NA if there is no WT Epitope Seq
mh_cflurry_wt_score	MHCflurry ic50 binding affinity for the wildtype epitope
mh_cflurry_mt_score	MHCflurry ic50 binding affinity for the mutant epitope
mh_cnuggets_i_wt_score	MHCnuggets-I ic50 binding affinity for the wildtype epitope
mh_cnuggets_i_mt_score	MHCnuggets-I ic50 binding affinity for the mutant epitope
net_mhc_wt_score	NetMHC ic50 binding affinity for the wildtype epitope
net_mhc_mt_score	NetMHC ic50 binding affinity for the mutant epitope
pick_pocket_wt_score	PickPocket ic50 binding affinity for the wildtype epitope
pick_pocket_mt_score	PickPocket ic50 binding affinity for the mutant epitope
cterm_7mer_gravy_score	Mean hydropathy of last 7 residues on the C-terminus of the peptide
max_7mer_gravy_score	Max GRAVY score of any kmer in the amino acid sequence. Used to determine if there are any extremely hydrophobic regions within a longer amino acid sequence
difficult_n_terminal_residue	Is N-terminal amino acid a Glutamine, Glutamic acid, or Cysteine? (T/F)
c_terminal_cysteine	Is the C-terminal amino acid a Cysteine? (T/F)
c_terminal_proline	Is the C-terminal amino acid a Proline? (T/F)
cysteine_count	Number of Cysteines in the amino acid sequence. Problematic because they can form disulfide bonds across distant parts of the peptide
n_terminal_asparagine	Is the N-terminal amino acid an Asparagine? (T/F)
asparagine_proline_bond_count	Number of Asparagine-Proline bonds. Problematic because they can spontaneously cleave the peptide
b_rank	Rank of binding score: 1/median neoantigen binding affinity. Lower is better
f_rank	Rank of fold change: the difference in median binding affinity between neoantigen and wildtype peptide (agretopicity). Higher is better
m_rank	Ranks of mutant allele expression: the product of gene_expression and tumor_rna_vaf. Higher is better
d_rank	Rank of the tumor_dna_vaf. Higher is better
score	A score is calculated from the above ranks with the following formula: b_rank + f_rank + (m_rank * 2) + (d_rank/2). Higher is better
rank_score	The score converted to a rank, with the best being 1, splitting ties by first. Lower is better
rank_percent	The percentage rank score. Lower is better

Supplementary Data S7: NSCLC pVACseq Class II Predictions

Column Variable	Description
sample	CRUK Accelerator patient identifier
chromosome	The chromosome of this variant
start	The start position of this variant in the zero-based, half-open coordinate system
stop	The stop position of this variant in the zero-based, half-open coordinate system
reference	The reference allele
variant	The alt allele
transcript	The Ensembl ID of the affected transcript
transcript_support_level	The transcript support level (TSL) of the affected transcript. NA if the VCF entry doesn't contain TSL information
ensembl_gene_id	The Ensembl ID of the affected gene
variant_type	The type of variant. missense for missense mutations, inframe_ins for inframe insertions, inframe_del for inframe deletions, and FS for frameshift variants
mutation	The amino acid change of this mutation
protein_position	The protein position of the mutation
gene_name	The Ensembl gene name of the affected gene
hgv_sc	The HGVS coding sequence variant name
hgv_sp	The HGVS protein sequence variant name
hla_allele	The HLA allele for this prediction
peptide_length	The peptide length of the epitope
sub_peptide_position	The one-based position of the epitope within the protein sequence used to make the prediction
mutation_position	The one-based position of the start of the mutation within the epitope sequence. 0 if the start of the mutation is before the epitope
mt_epitope_seq	The mutant epitope sequence
wt_epitope_seq	The wildtype (reference) epitope sequence at the same position in the full protein sequence. NA if there is no wildtype sequence at this position or if more than half of the amino acids of the mutant epitope are mutated
best_mt_score_method	Prediction algorithm with the lowest mutant ic50 binding affinity for this epitope
best_mt_score	Lowest ic50 binding affinity of all prediction algorithms used
corresponding_wt_score	ic50 binding affinity of the wildtype epitope. NA if there is no WT Epitope Seq
corresponding_fold_change	Corresponding WT Score / Best MT Score. NA if there is no WT Epitope Seq
tumor_dna_depth	Tumor DNA depth at this position. NA if VCF entry does not contain tumor DNA readcount annotation
tumor_dna_vaf	Tumor DNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain tumor DNA readcount annotation
tumor_rna_depth	Tumor RNA depth at this position. NA if VCF entry does not contain tumor RNA readcount annotation
tumor_rna_vaf	Tumor RNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain tumor RNA readcount annotation
normal_depth	Normal DNA depth at this position. NA if VCF entry does not contain normal DNA readcount annotation
normal_vaf	Normal DNA variant allele frequency (VAF) at this position. NA if VCF entry does not contain normal DNA readcount annotation
gene_expression	Gene expression value for the annotated gene containing the variant. NA if VCF entry does not contain gene expression annotation
transcript_expression	Transcript expression value for the annotated transcript containing the variant. NA if VCF entry does not contain transcript expression annotation
median_mt_score	Median ic50 binding affinity of the mutant epitope across all prediction algorithms used
median_wt_score	Median ic50 binding affinity of the wildtype epitope across all prediction algorithms used. NA if there is no WT Epitope Seq
median_fold_change	Median WT Score / Median MT Score. NA if there is no WT Epitope Seq
mh_cnuggets_ii_wt_score	MHCnuggets-II ic50 binding affinity for the wildtype epitope
mh_cnuggets_ii_mt_score	MHCnuggets-II ic50 binding affinity for the mutant epitope
cterm_7mer_gravy_score	Mean hydropathy of last 7 residues on the C-terminus of the peptide
max_7mer_gravy_score	Max GRAVY score of any kmer in the amino acid sequence. Used to determine if there are any extremely hydrophobic regions within a longer amino acid sequence
difficult_n_terminal_residue	Is N-terminal amino acid a Glutamine, Glutamic acid, or Cysteine? (T/F)
c_terminal_cysteine	Is the C-terminal amino acid a Cysteine? (T/F)
c_terminal_proline	Is the C-terminal amino acid a Proline? (T/F)
cysteine_count	Number of Cysteines in the amino acid sequence. Problematic because they can form disulfide bonds across distant parts of the peptide
n_terminal_asparagine	Is the N-terminal amino acid an Asparagine? (T/F)
asparagine_proline_bond_count	Number of Asparagine-Proline bonds. Problematic because they can spontaneously cleave the peptide
net_mhci_ipan_wt_score	NetMHCIIpan ic50 binding affinity for the wildtype epitope
net_mhci_ipan_mt_score	NetMHCIIpan ic50 binding affinity for the mutant epitope
n_nalign_wt_score	NNalign ic50 binding affinity for the wildtype epitope
n_nalign_mt_score	NNalign ic50 binding affinity for the mutant epitope
sm_malign_wt_score	SMMalign ic50 binding affinity for the wildtype epitope
sm_malign_mt_score	SMMalign ic50 binding affinity for the mutant epitope
b_rank	Rank of binding score: 1/median neoantigen binding affinity. Lower is better
f_rank	Rank of fold change: the difference in median binding affinity between neoantigen and wildtype peptide (agretopicity). Higher is better
m_rank	Ranks of mutant allele expression: the product of gene_expression and tumor_rna_vaf. Higher is better
d_rank	Rank of the tumor_dna_vaf. Higher is better
score	A score is calculated from the above ranks with the following formula: b_rank + f_rank + (m_rank * 2) + (d_rank/2). Higher is better
rank_score	The score converted to a rank, with the best being 1, splitting ties by first. Lower is better
rank_percent	The percentage rank score. Lower is better

Supplementary Data S8: NSCLC pVACseq Peptidome Combined Predictions

Column Variable	Description
sample_id	CRUK Accelerator patient identifier
hla_class	HLA class (I or II)
table_name	Identifier in the form accel_id/predicted_hla_allotype/peptide_length
length	Peptide length
hla_length_pref1	HLA allotype preferred peptide length 1
hla_length_pref2	HLA allotype preferred peptide length 2
gene_name	HGNC gene name
mt_epitope_seq	The mutant epitope sequence
median_mt_score	Median ic50 binding affinity of the mutant epitope across all prediction algorithms used
corresponding_fold_change	Corresponding WT Score / Best MT Score. NA if there is no WT Epitope Seq
gene_expression	Gene expression value for the annotated gene containing the variant
tumor_rna_vaf	Tumor RNA variant allele frequency (VAF) at this position
tumor_dna_vaf	Tumor DNA variant allele frequency (VAF) at this position
rank_percent	The percentage rank score. Lower is better
rank_score	The score converted to a rank, with the best being 1, splitting ties by first. Lower is better
Obs_I	The number of peptides from the source protein observed by mass spectrometry in HLA-I immunopeptidome
Obs_II	The number of peptides from the source protein observed by mass spectrometry in HLA-II immunopeptidome

Supplementary Data S9: NSCLC Tested Neoantigens

Column Variable	Description
accel_id	CRUK Accelerator patient identifier
gene_name	Gene
mt_epitope_seq	Mutated (neoantigen) peptide sequence
wt_epitope_seq	Wildtype peptide sequence
peptide_length	Peptide length
table_name	Identifier in the form accel_id/predicted_hla_allotype/peptide_length e.g. A119/DRB1*04:04/15
mutation	The mutation From/To
protein_position	Location of the mutation in the source protein, UNIPROT sequence number
Obs_I	The number of peptides from the source protein observed by mass spectrometry in HLA-I immunopeptidome
Obs_II	The number of peptides from the source protein observed by mass spectrometry in HLA-II immunopeptidome
median_mt_score	The median pVACseq predicted binding affinity of the neoantigen peptide
median_wt_score	The median pVACseq predicted binding affinity of the wildtype peptide
median_fold_change	The ratio between the median neoantigen affinity and wildtype peptide affinity
rank_percent	The overall rank percentage for the neoantigen from pVACseq for the peptide of that length and HLA allotype
mean_sfc_mt	Mean IFN-γ ELISPOT spot forming cells per million cells for the neoantigen peptide
mean_sfc_wt	Mean IFN-γ ELISPOT spot forming cells per million cells for the wildtype peptide
elispot_response	ELISPOT response category: Strong, Weak or None

References

1. Nicholas B, Bailey A, McCann KJ, Wood O, Currall E, Johnson P, et al. Proteogenomics guided identification of functional neoantigens in non-small cell lung cancer. 2024. Available: http://dx.doi.org/10.1101/2024.05.30.596609

2. Hundal J, Carreno BM, Petti AA, Linette GP, Griffith OL, Mardis ER, et al. pVAC-seq: A genome-guided in silico approach to identifying tumor neoantigens. Genome Medicine. 2016;8: 11. doi:10.1186/s13073-016-0264-5