4b35dc6ad8831a1612196846da64e819 hlaimmres_a2026m2v107n2pe70563.pdf 48d7777ad0f8ad198dbcaa8efdee282dd5f0c914 hlaimmres_a2026m2v107n2pe70563.pdf fac2f2d12db2fdbabc8fc0e5b50d13da34421c53f3e143df4e6128830eee094d hlaimmres_a2026m2v107n2pe70563.pdf Title: HLA‐DRB1 Allelic Combinations Differentially Shape Dendritic Cell Antigen Presentation Enhanced by Tumour Cell Line Lysate‐Pulsing Subject: HLA 2026.107:e70563 Keywords: Keywords: antigen presentation; CD4+ T cells; dendritic cells; heterozygosity; HLA-DRB1 alleles; peptides Author: Gonzalo Lázaro,Juan A. Cedano, Maitane Faus, Carme Roura-Mir, Laia Garrigós, José Pérez-García, Javier Román-García, Javier Cortés, Andrea Aran, Mercè Martí Creator: Adobe InDesign 19.5 (Windows) Producer: Adobe PDF Library 17.0; modified using iTextSharp 5.5.13.4 ©2000-2024 iText Group NV (AGPL-version) CreationDate: Tue Jan 27 17:47:51 2026 CET ModDate: Thu Mar 12 18:31:27 2026 CET Custom Metadata: yes Metadata Stream: yes Tagged: yes UserProperties: no Suspects: no Form: none JavaScript: no Pages: 18 Encrypted: no Page size: 595.276 x 782.362 pts Page rot: 0 File size: 4830665 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- BERONW+STIXTwoText Type 1C Custom yes yes yes 63 0 QGDVPS+STIXTwoText-BoldItalic Type 1C WinAnsi yes yes yes 164 0 WHCKVG+STIXTwoText-Italic Type 1C WinAnsi yes yes yes 65 0 WFBAVG+ArialRoundedMTBold Type 1C WinAnsi yes yes no 2065 0 BHQJNW+STIXTwoText-Bold Type 1C Custom yes yes yes 64 0 Times-Roman Type 1 WinAnsi no no no 5 0 WFBAVG+STIX-Regular Type 1C Custom yes yes yes 99 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2026-03-13 04:27:30 CET RepresentationInformation: hlaimmres_a2026m2v107n2pe70563.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2026-03-12 18:32:27 CET Size: 4830665 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 0 FreeObjects: 2 IncrementalUpdates: 0 DocumentCatalog: ViewerPreferences: HideToolbar: false HideMenubar: false HideWindowUI: false FitWindow: false CenterWindow: false DisplayDocTitle: true NonFullScreenPageMode: UseNone Direction: L2R ViewArea: CropBox ViewClip: CropBox PrintArea: CropBox PageClip: CropBox PageLayout: SinglePage PageMode: UseNone Language: en-US Outlines: Item: Title: HLA-DRB1 Allelic Combinations Differentially Shape Dendritic Cell Antigen Presentation Enhanced by Tumour Cell Line Lysate-Pulsing Children: Item: Title: ABSTRACT Item: Title: 1   |   Introduction Item: Title: 2   |   Material and Methods Children: Item: Title: 2.1   |   Obtention of MCF-7 Cell Lysates Item: Title: 2.2   |   Protein Digestion for Proteome Analysis Item: Title: 2.3   |   Proteome Analysis: Tryptic Peptide Identification and Analysis by Mass Spectrometry (MS) Item: Title: 2.4   |   Blood Samples and Generation of Mature MoDCs Item: Title: 2.5   |   Phenotype Characterisation of MoDCs Item: Title: 2.6   |   Pulsing of MoDCs With MCF-7 Protein Extracts Item: Title: 2.7   |   HLA Typing of Modcs' Donors Item: Title: 2.8   |   Purification of HLA-DR Complexes Item: Title: 2.9   |   HLA-DR Repertoires From MoDCs. Peptide Identification by MS Item: Title: 2.10   |   HLA-DR Peptide Repertoire Analysis Item: Title: 2.11   |   Multidimensional Scaling (MDS) Item: Title: 3   |   Results Children: Item: Title: 3.1   |   Characterisation of the HLA-DRB1-Associated Peptide Repertoire in Heterozygous MoDCs Item: Title: 3.2   |   HLA-DRB1 Allele Dominance Is Shaped by Heterozygosity Item: Title: 3.3   |   Including Dual Binder Peptides Reveals Allelic Properties and Dominance Relationships Item: Title: 3.4   |   Patterns of Shared Peptide Distribution Are Influenced by Specific HLA-DR Allele Co-Expression and by Cell-Lysate Pulsing Item: Title: 3.5   |   Pulsing With MCF-7 Extract Enhances Presentation of Cytosolic Proteins Item: Title: 3.6   |   Pulse-Driven Immunopeptidome Analysis Enhances Allele-Specific Features and Reveals Distinct Binding Biases of the DRB1*03:01 and DRB1*13:02 Alleles in a Heterozygous Context Item: Title: 3.7   |   HLA-DRB1 Allelic Properties Impact the Presentation of MCF-7-Induced Peptides Item: Title: 4   |   Discussion Item: Title: Author Contributions Item: Title: Acknowledgements Item: Title: Funding Item: Title: Disclosure Item: Title: Ethics Statement Item: Title: Conflicts of Interest Item: Title: Data Availability Statement Item: Title: References Filters: FilterPipeline: FlateDecode FilterPipeline: CCITTFaxDecode Images: Image: NisoImageMetadata: FormatName: image/png ImageWidth: 228 ImageHeight: 45 ColorSpace: RGB BitsPerSample: 8 BitsPerSampleUnit: integer Filter: FlateDecode Image: NisoImageMetadata: FormatName: image/tiff CompressionScheme: CCITT Group 4 ImageWidth: 517 ImageHeight: 108 BitsPerSample: 1 BitsPerSampleUnit: integer Intent: RelativeColorimetric ImageMask: true Decode: 0, 1 Name: X Image: NisoImageMetadata: FormatName: image/png ImageWidth: 228 ImageHeight: 45 ColorSpace: black is zero BitsPerSample: 8 BitsPerSampleUnit: integer Filter: FlateDecode Image: NisoImageMetadata: FormatName: image/png ImageWidth: 2097 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Physiology and ImmunologyInstitut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB)BellaterraSpain Rect: 260, 565, 268, 552 ActionDest: 362 Annotation: Subtype: Link Contents: Immunology Unit, Department of Cell Biology, Physiology and ImmunologyInstitut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB)BellaterraSpain Rect: 348, 565, 352, 552 ActionDest: 362 Annotation: Subtype: Link Contents: International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud GroupBarcelonaSpain Rect: 416, 565, 419, 552 ActionDest: 362 Annotation: Subtype: Link Contents: International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud GroupBarcelonaSpain Rect: 498, 565, 506, 552 ActionDest: 362 Annotation: Subtype: Link Contents: Medical Oncology DepartmentIOB Institute of OncologyMadridMadridSpain Rect: 126, 554, 134, 541 ActionDest: 362 Annotation: Subtype: Link Contents: International Breast Cancer Center (IBCC), Pangaea Oncology, Quironsalud GroupBarcelonaSpain Rect: 195, 554, 208, 541 ActionDest: 362 Annotation: Subtype: Link Contents: Immunology Unit, Department of Cell Biology, Physiology and ImmunologyInstitut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB)BellaterraSpain Rect: 271, 554, 279, 541 ActionDest: 362 Annotation: Subtype: Link Contents: Please visit https://orcid.org/0000-0002-9036-2085 for your more information Rect: 279, 555, 291, 543 Annotation: Subtype: Link Contents: Immunology Unit, Department of Cell Biology, Physiology and ImmunologyInstitut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB)BellaterraSpain Rect: 350, 554, 358, 541 ActionDest: 362 Annotation: Subtype: Link Contents: Please visit https://orcid.org/0000-0002-1846-0043 for your more information Rect: 358, 555, 371, 543 Annotation: Subtype: Link Contents: Please visit mailto:aran@recerca.clinic.cat for your more information Rect: 154, 444, 230, 433 Annotation: Subtype: 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Rect: 536, 394, 544, 382 ActionDest: 264 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 386, 60, 395, 48 ActionDest: 354 Page: Sequence: 5 Annotations: Annotation: Subtype: Link Contents: TableS1: Summary table showing the number of total, filtered, binder, and dual peptides identified in each sample, along with the number of peptides associated with each HLADRB1 allele. The number of MoDCs obtained per sample ranged from 1.55 to 17.3 million. Peptide binding affinities for the different alleles were predicted using the NetMHCIIPan4.1 algorithm, revealing allelespecific binding imbalances. Rect: 187, 360, 196, 347 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 1" for your more reference Rect: 177, 348, 182, 335 ActionDest: 115 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 170, 268, 179, 255 ActionDest: 354 Annotation: Subtype: Link Contents: TableS1: Summary table showing the number of total, filtered, binder, and dual peptides identified in each sample, along with the number of peptides associated with each HLADRB1 allele. The number of MoDCs obtained per sample ranged from 1.55 to 17.3 million. Peptide binding affinities for the different alleles were predicted using the NetMHCIIPan4.1 algorithm, revealing allelespecific binding imbalances. Rect: 123, 210, 132, 197 ActionDest: 354 Annotation: Subtype: Link Contents: A.Suri, S. B.Lovitch, and E. R.Unanue, “The Wide Diversity and Complexity of Peptides Bound to Class II MHC Molecules,” Current Opinion in Immunology18, no. 1 (2006): 70 77, https://doi.org/10.1016/j.coi.2005.11.002. Rect: 218, 130, 240, 117 ActionDest: 264 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 200, 118, 216, 105 ActionDest: 354 Annotation: Subtype: Link Contents: TableS2: (A) List of all peptides eluted from HLADR molecules in MoDC samples. (B) List of peptides assigned to HLADRB1 alleles in each MoDC sample. (C) List of all source proteins identified in MoDC samples. (D) List of source proteins assigned to HLADRB1 alleles. Rect: 191, 107, 200, 94 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 337, 360, 351, 347 ActionDest: 354 Annotation: Subtype: Link Contents: TableS1: Summary table showing the number of total, filtered, binder, and dual peptides identified in each sample, along with the number of peptides associated with each HLADRB1 allele. The number of MoDCs obtained per sample ranged from 1.55 to 17.3 million. Peptide binding affinities for the different alleles were predicted using the NetMHCIIPan4.1 algorithm, revealing allelespecific binding imbalances. Rect: 334, 257, 343, 244 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 340, 188, 349, 175 ActionDest: 354 Annotation: Subtype: Link Contents: Please visit http://biorender.com for your more information Rect: 251, 478, 304, 466 Page: Sequence: 6 Annotations: Annotation: Subtype: Link Contents: TableS1: Summary table showing the number of total, filtered, binder, and dual peptides identified in each sample, along with the number of peptides associated with each HLADRB1 allele. The number of MoDCs obtained per sample ranged from 1.55 to 17.3 million. Peptide binding affinities for the different alleles were predicted using the NetMHCIIPan4.1 algorithm, revealing allelespecific binding imbalances. Rect: 174, 153, 183, 140 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 2A,B" for your more reference Rect: 207, 107, 226, 94 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2C,D" for your more reference Rect: 157, 61, 177, 48 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2A" for your more reference Rect: 458, 130, 469, 117 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2B" for your more reference Rect: 404, 107, 414, 94 ActionDest: 130 Page: Sequence: 7 Annotations: Annotation: Subtype: Link Contents: Please see "figure 2B" for your more reference Rect: 100, 613, 110, 601 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2C" for your more reference Rect: 78, 383, 89, 371 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2D" for your more reference Rect: 193, 383, 204, 371 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 2C,D" for your more reference Rect: 126, 337, 146, 325 ActionDest: 130 Annotation: Subtype: Link Contents: Please see "figure 3A" for your more reference Rect: 256, 211, 267, 198 ActionDest: 155 Annotation: Subtype: Link Contents: Please see "figure 3B" for your more reference Rect: 133, 199, 143, 187 ActionDest: 155 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 232, 176, 241, 164 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 3C" for your more reference Rect: 156, 130, 167, 118 ActionDest: 155 Annotation: Subtype: Link Contents: Please see "figure 4" for your more reference Rect: 337, 452, 341, 440 ActionDest: 163 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 447, 452, 456, 440 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 476, 372, 485, 359 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 4A" for your more reference Rect: 444, 291, 455, 279 ActionDest: 163 Annotation: Subtype: Link Contents: Please see "figure 4B" for your more reference Rect: 425, 268, 435, 256 ActionDest: 163 Page: Sequence: 8 Page: Sequence: 9 Page: Sequence: 10 Annotations: Annotation: Subtype: Link Contents: J. I.Griffiths, P. A.Cosgrove, E. F.Medina, etal., “Cellular Interactions Within the Immune Microenvironment Underpins Resistance to Cell Cycle Inhibition in Breast Cancers,” Nature Communications16, no. 1 (2025): 2132, https://doi.org/10.1038/s4146702556279x. Rect: 148, 647, 157, 634 ActionDest: 264 Annotation: Subtype: Link Contents: TableS3: List of proteins identified in the MCF7 lysates used for MoDC pulsing. Rect: 214, 590, 223, 577 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 5A" for your more reference Rect: 248, 555, 259, 542 ActionDest: 185 Annotation: Subtype: Link Contents: TableS4: Summary table showing the number of pulsederived peptides and proteins associated with each HLADRB1 allele in every sample. PDC1902 was excluded as no pulsederived proteins were identified. Rect: 107, 509, 117, 496 ActionDest: 354 Annotation: Subtype: Link Contents: TableS5: (A) List of pulsederived peptides assigned to HLADRB1 alleles in each PDC sample. (B) List of pulsederived proteins assigned to HLADRB1 alleles in each PDC sample. Rect: 139, 509, 148, 496 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 149, 429, 165, 416 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 115, 371, 130, 358 ActionDest: 354 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 140, 348, 155, 335 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 5B" for your more reference Rect: 202, 199, 212, 186 ActionDest: 185 Annotation: Subtype: Link Contents: Figure S1: Computational analysis framework for studying the role of HLADR heterozygosity in antigen presentation. (1) The pipeline begins with the collection of peptide sequences presented by individuals with known HLA types. (2) A distance matrix is computed based on global sequence alignments using BLOSUM62 matrix to evaluate peptide similarity. (3) The optimal number of clusters is determined to group peptides that are homologous or belong to nested sets, reducing complexity. These peptide clusters are then associated with HLA alleles. Peptides capable of binding to both coexpressed alleles, that is, dual peptides, were identified in all samples. (4) The analysis proceeds in two parallel paths: in the filtered approach, each dual peptide in heterozygous individuals is assigned to the allele with the highest predicted binding affinity; in the nonfiltered approach, dual peptides are assumed to bind equally to both coexpressed alleles. Multidimensional scaling (MDS) is applied to both datasets to visualise the spatial relationships among HLADRB1 alleles based on the peptide clusters they present. (5) The distributions from the filtered and nonfiltered approaches are compared to evaluate how different assignment strategies affect the interpretation of allelespecific peptide presentation. MDS, multidimensional scaling.Figure S2: Phenotypic characterisation of mature MoDCs prior to HLADRpeptide immunoprecipitation. (A) Representative flow cytometry histograms from a single MoDC sample showing high fluorescence intensity for HLADR and additional DC maturation markers. The gating strategy was based on a negative control, resulting in nearly 100% positivity for all markers in the tested samples. (B) Bar plots representing the percentage of positive cells for each marker (HLAABC, HLADR, CD80, CD83 and CD86), shown as mean±standard deviation, separately for both control and pulsed samples. No statistical significance was observed between conditions, suggesting that pulsing did not influence the maturation status of MoDCs. Nearly all MoDCs express surface HLADR, ensuring the presence of DRbound peptides, along with high expression of other activation markers.Figure S3: General characterisation of HLADR eluted peptides in control (CDC) and pulsed (PDC) samples. (A) Peptide length showing a normal distribution with an average of 15mers in both groups of samples. (B) Subcellular distribution of the source proteins. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. A moderate increase in the percentage of nuclear and mitochondrial proteins was observed in pulsed samples, along with a decrease in proteins from the cell membrane and extracellular compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01.Figure S4: Percentage of strong binders (SB) and weak binders (WB) associated with each HLADRB1 allele in PDC (A) and CDC (B) samples, determined by the affinity prediction algorithm of NetMHCIIPan4.1. Certain alleles (e.g., DRB1*01:01, DRB1*01:02 and DRB1*04:04 in C2102, P1914 and P1903 respectively) displayed a stronger affinity for binding peptides compared to others (e.g., DRB1*11:01, DRB1*13:01, DRB1*13:02 and DRB1*13:05 in C2102, P1901/C1921, P1903 and P1902, respectively).Figure S5: Heatmap showing the frequency of protein overlap between DC control (A) and pulsed (B) samples and alleles. Diagonal cells display the fraction of proteins that are exclusive to an allele in a specific sample, whereas other cells indicate the frequency of proteins shared among different samples and alleles. Proteins observed in both control and pulsed samples tend to be frequently shared among different alleles and samples, with a lower frequency of protein exclusivity in most cases.Figure S6: Protein characterisation of MCF7 protein lysates. (A) Relationship between the most abundant proteins in the MCF7 proteome and their peptide representation in the PDC immunopeptidomes. No positive correlation was observed, indicating that highly prevalent proteins in the MCF7 proteome were not necessarily the most represented in the PDC samples, and vice versa, and suggesting that protein abundance alone does not dictate peptide presentation in PDCs. Complete names of the proteins are collected in TableS5. (B) Subcellular distribution of pulsederived proteins compared to the overall protein composition in PDC samples. Data are presented as mean±standard deviation (SD) for each subcellular compartment in both conditions. Multiple unpaired ttests were performed for comparisons between conditions without assuming equal variances. Statistical significance was determined using the HolmSidak method to correct for multiple comparisons, with a significance level of =0.05. Each compartment was analysed independently. Pulsederived proteins showed a significant increase in the proportion of cytosolic proteins, along with contributions from other cellular compartments (e.g., GA, Mit), while there was a notable decrease in proteins from the secreted or extracellular matrix compartments. CM, cell membrane; S/EM, secreted or extracellular matrix; C, cytosol; N, nucleus; Lys/End, lysosome or endosome; ER, endoplasmic reticulum; GA, Golgi apparatus; Mit, mitochondria. *p<0.05, **p<0.01. Rect: 274, 187, 283, 174 ActionDest: 354 Annotation: Subtype: Link Contents: Please see "figure 5C" for your more reference Rect: 171, 153, 182, 140 ActionDest: 185 Annotation: Subtype: Link Contents: Please see "figure 5D" for your more reference Rect: 76, 95, 87, 82 ActionDest: 185 Annotation: Subtype: Link Contents: Please see "figure 6A,C" for your more reference Rect: 484, 509, 503, 496 ActionDest: 194 Annotation: Subtype: Link Contents: Please see "figure 6B,D" for your more reference Rect: 440, 498, 458, 485 ActionDest: 194 Annotation: Subtype: Link Contents: Please see "figure 6A" for your more reference Rect: 385, 429, 396, 416 ActionDest: 194 Annotation: Subtype: Link Contents: Please see "figure 3C" for your more reference Rect: 379, 394, 389, 381 ActionDest: 155 Annotation: Subtype: Link Contents: Please see "figure 6C" for your more reference Rect: 493, 245, 503, 232 ActionDest: 194 Annotation: Subtype: Link Contents: Please see "figure 6B,D" for your more reference Rect: 370, 199, 389, 186 ActionDest: 194 Annotation: Subtype: Link Contents: Please see "figure 5B,C" for your more reference Rect: 382, 141, 400, 128 ActionDest: 185 Page: Sequence: 11 Annotations: Annotation: Subtype: Link Contents: S.Nie, S.McDermott, Y.Deol, Z.Tan, M.Wicha, and D.Lubman, “A Quantitative Proteomics Analysis of MCF7 Breast Cancer Stem and Progenitor Cell Populations,” Journal of Clinical Sleep Medicine15, no. 22 (2015): 3772 3783, https://doi.org/10.1002/pmic.201500002. 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Rect: 482, 84, 491, 71 ActionDest: 311 Annotation: Subtype: Link Contents: A.Amiri, F.Noei, S.Jeganathan, G.Kulkarni, D. E.Pinke, and J. M.Lee, “eEF1A2 Activates Akt and Stimulates AktDependent Actin Remodeling, Invasion and Migration,” Oncogene26, no. 21 (2007): 3027 3040, https://doi.org/10.1038/sj.onc.1210101. Rect: 491, 61, 514, 48 ActionDest: 311 Page: Sequence: 13 Annotations: Annotation: Subtype: Link Contents: G.Espinosacarrasco, A.Scrivo, P.Zumbo, etal., “Intratumoral Immune Triads Are Required for Adoptive T Cell TherapyMediated Elimination of Solid Tumors,” Cancer Cell42, no. 7 (2024): 1202 1216.e8, https://doi.org/10.1016/j.ccell.2024.05.025. Rect: 133, 705, 142, 692 ActionDest: 311 Annotation: Subtype: Link Contents: T.Cotner, H.Charbonneau, E.Mellins, and D.Pious, “mRNA Abundance, Rather Than Differences in Subunit Assembly, Determine Differential Expression of HLADR1 and DR3 Molecules,” Journal of Biological Chemistry264, no. 19 (1989): 11107 11111, https://doi.org/10.1016/s00219258(18)604351. Rect: 235, 463, 244, 450 ActionDest: 311 Annotation: Subtype: Link Contents: S.Kaabinejadian, C.Barra, B.Alvarez, H.Yari, W. H.Hildebrand, and M.Nielsen, “Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome,” Frontiers in Immunology13 (2022): 1 17, https://doi.org/10.3389/fimmu.2022.835454. Rect: 140, 383, 149, 370 ActionDest: 264 Annotation: Subtype: Link Contents: G. P. M.Mommen, F.Marino, H. D.Meiring, etal., “Sampling From the Proteome to the Human Leukocyte AntigenDR (HLADR) Ligandome Proceeds via High Specificity,” Molecular & Cellular Proteomics15, no. 4 (2016): 1412 1423, https://doi.org/10.1074/mcp.M115.055780. Rect: 389, 613, 398, 601 ActionDest: 311 Annotation: Subtype: Link Contents: J. A.Collado, I.Alvarez, M. T.Ciudad, etal., “Composition of the HLADRAssociated Human Thymus Peptidome,” European Journal of Immunology43, no. 9 (2013): 2273 2282, https://doi.org/10.1002/eji.201243280. Rect: 536, 395, 544, 382 ActionDest: 311 Annotation: Subtype: Link Contents: M.Houtman, E.Hesselberg, L.Rönnblom, L.Klareskog, V.Malmström, and L.Padyukov, “HaplotypeSpecific Expression Analysis of MHC Class II Genes in Healthy Individuals and Rheumatoid Arthritis Patients,” Frontiers in Immunology12 (2021): 1 11, https://doi.org/10.3389/fimmu.2021.707217. Rect: 495, 268, 504, 256 ActionDest: 311 Annotation: Subtype: Link Contents: S.Southwood, J.Sidney, A.Kondo, etal., “Several Common HLADR Types Share Largely Overlapping Peptide Binding Repertoires,” Journal of Immunology160, no. 7 (1998): 3363 3373, https://doi.org/10.4049/jimmunol.160.7.3363. Rect: 370, 199, 392, 187 ActionDest: 311 Annotation: Subtype: Link Contents: L.Yin, P.Trenh, A.Guce, etal., “Susceptibility to HLADM Protein Is Determined by a Dynamic Conformation of Major Histocompatibility Complex Class II Molecule Bound With Peptide,” Journal of Biological Chemistry289, no. 34 (2014): 23449 23464, https://doi.org/10.1074/jbc.M114.585539. Rect: 416, 176, 425, 164 ActionDest: 311 Annotation: Subtype: Link Contents: E. T.Abualrous, S.Stolzenberg, J.Sticht, etal., “MHCII Dynamics Are Maintained in HLADR Allotypes to Ensure Catalyzed Peptide Exchange,” Nature Chemical Biology19, no. 10 (2023): 1196 1204, https://doi.org/10.1038/s41589023013163. Rect: 455, 130, 463, 118 ActionDest: 264 Annotation: Subtype: Link Contents: S.Southwood, J.Sidney, A.Kondo, etal., “Several Common HLADR Types Share Largely Overlapping Peptide Binding Repertoires,” Journal of Immunology160, no. 7 (1998): 3363 3373, https://doi.org/10.4049/jimmunol.160.7.3363. Rect: 308, 107, 317, 95 ActionDest: 311 Annotation: Subtype: Link Contents: E. T.Abualrous, S.Stolzenberg, J.Sticht, etal., “MHCII Dynamics Are Maintained in HLADR Allotypes to Ensure Catalyzed Peptide Exchange,” Nature Chemical Biology19, no. 10 (2023): 1196 1204, https://doi.org/10.1038/s41589023013163. Rect: 490, 73, 498, 60 ActionDest: 264 Page: Sequence: 14 Annotations: Annotation: Subtype: Link Contents: J.BandolaSimon, Y.Ito, K. W.Wucherpfennig, and P. A.Roche, “Defective Removal of Invariant Chain Peptides From MHC Class II Suppresses Tumor Antigen Presentation and Promotes Tumor Growth,” Cell Reports44, no. 1 (2025): 115150, https://doi.org/10.1016/j.celrep.2024.115150. Rect: 74, 705, 83, 693 ActionDest: 264 Annotation: Subtype: Link Contents: A. I.Guce, S. E.Mortimer, T.Yoon, etal., “HLADO Acts as a Substrate Mimic to Inhibit HLADM by a Competitive Mechanism,” Nature Structural & Molecular Biology20, no. 1 (2013): 90 98, https://doi.org/10.1038/nsmb.2460. Rect: 275, 682, 283, 670 ActionDest: 311 Annotation: Subtype: Link Contents: X.Chen, O.Laur, T.Kambayashi, etal., “Regulated Expression of Human Histocompatibility Leukocyte Antigen (HLA) DO During AntigenDependent and AntigenIndependent Phases of B Cell Development,” Journal of Experimental Medicine195, no. 8 (2002): 1053 1062, https://doi.org/10.1084/jem.20012066. Rect: 277, 648, 286, 635 ActionDest: 311 Annotation: Subtype: Link Contents: P. P.Nanaware, M. M.Jurewicz, J. D.Leszyk, S. A.Shaffer, and L. J.Stern, “HLADO Modulates the Diversity of the MHCII SelfPeptidome,” Molecular & Cellular Proteomics18, no. 3 (2019): 490 503, https://doi.org/10.1074/mcp.RA118.000956. Rect: 153, 636, 162, 624 ActionDest: 311 Annotation: Subtype: Link Contents: M.Houtman, E.Hesselberg, L.Rönnblom, L.Klareskog, V.Malmström, and L.Padyukov, “HaplotypeSpecific Expression Analysis of MHC Class II Genes in Healthy Individuals and Rheumatoid Arthritis Patients,” Frontiers in Immunology12 (2021): 1 11, https://doi.org/10.3389/fimmu.2021.707217. Rect: 221, 602, 229, 589 ActionDest: 311 Annotation: Subtype: Link Contents: M.Stražar, J.Park, J. G.Abelin, etal., “HLAII Immunopeptidome Profiling and Deep Learning Reveal Features of Antigenicity to Inform Antigen Discovery,” Immunity56, no. 7 (2023): 1681 1698.e13, https://doi.org/10.1016/j.immuni.2023.05.009. Rect: 239, 556, 263, 543 ActionDest: 264 Annotation: Subtype: Link Contents: M. T.Ciudad, N.Sorvillo, F. P.vanAlphen, etal., “Analysis of the HLADR Peptidome From Human Dendritic Cells Reveals High Affinity Repertoires and Nonconventional Pathways of Peptide Generation,” Journal of Leukocyte Biology101, no. 1 (2017): 15 27, https://doi.org/10.1189/jlb.6hi0216069r. Rect: 200, 429, 209, 417 ActionDest: 264 Annotation: Subtype: Link Contents: J. A.Collado, I.Alvarez, M. T.Ciudad, etal., “Composition of the HLADRAssociated Human Thymus Peptidome,” European Journal of Immunology43, no. 9 (2013): 2273 2282, https://doi.org/10.1002/eji.201243280. Rect: 147, 372, 156, 359 ActionDest: 311 Annotation: Subtype: Link Contents: J. A.Collado, I.Alvarez, M. T.Ciudad, etal., “Composition of the HLADRAssociated Human Thymus Peptidome,” European Journal of Immunology43, no. 9 (2013): 2273 2282, https://doi.org/10.1002/eji.201243280. Rect: 94, 291, 115, 279 ActionDest: 311 Annotation: Subtype: Link Contents: L.Karyampudi, C. J.Krco, K. R.Kalli, etal., “Identification of a Broad Coverage HLADR Degenerate Epitope Pool Derived From Carcinoembryonic Antigen,” Cancer Immunology, Immunotherapy59, no. 1 (2010): 161 171, https://doi.org/10.1007/s002620090738z. Rect: 109, 188, 133, 175 ActionDest: 311 Annotation: Subtype: Link Contents: M.Ayyoub, C. S.Hesdorffer, M.Montes, etal., “An Immunodominant SSX2Derived Epitope Recognized by CD4+ T Cells in Association With HLADR,” Journal of Clinical Investigation113, no. 8 (2004): 1225 1233, https://doi.org/10.1172/JCI200420667. Rect: 248, 142, 256, 129 ActionDest: 311 Annotation: Subtype: Link Contents: S.Kaabinejadian, C.Barra, B.Alvarez, H.Yari, W. H.Hildebrand, and M.Nielsen, “Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome,” Frontiers in Immunology13 (2022): 1 17, https://doi.org/10.3389/fimmu.2022.835454. Rect: 274, 96, 283, 83 ActionDest: 264 Annotation: Subtype: Link Contents: G. P. M.Mommen, F.Marino, H. D.Meiring, etal., “Sampling From the Proteome to the Human Leukocyte AntigenDR (HLADR) Ligandome Proceeds via High Specificity,” Molecular & Cellular Proteomics15, no. 4 (2016): 1412 1423, https://doi.org/10.1074/mcp.M115.055780. Rect: 394, 579, 403, 566 ActionDest: 311 Annotation: Subtype: Link Contents: B.Zhang, Z.Ren, J.Zhao, etal., “Global Analysis of HLAA2 Restricted MAGEA3 Tumor Antigen Epitopes and Corresponding TCRs in NonSmall Cell Lung Cancer,” Theranostics13, no. 13 (2023): 4449 4468, https://doi.org/10.7150/thno.84710. Rect: 308, 372, 317, 359 ActionDest: 311 Annotation: Subtype: Link Contents: M. T.Bethune, X. H.Li, J.Yu, etal., “Isolation and Characterization of NYESO1Specific T Cell Receptors Restricted on Various MHC Molecules,” Proceedings of the National Academy of Sciences of the United States of America115, no. 45 (2018): E10702 E10711, https://doi.org/10.1073/pnas.1810653115. Rect: 364, 372, 372, 359 ActionDest: 311 Annotation: Subtype: Link Contents: I.Bellantuono, L.Gao, S.Parry, etal., “Two Distinct HLAA0201Presented Epitopes of the Wilms Tumor Antigen 1 Can Function as Targets for LeukemiaReactive CTL,” Blood100, no. 10 (2002): 3835 3837, https://doi.org/10.1182/blood.V100.10.3835. Rect: 407, 372, 416, 359 ActionDest: 311 Annotation: Subtype: Link Contents: A. B. H.Barker, M. W. J.Schreurs, G.Tafazzul, etal., “Identification of a Novel Peptide Derived From the MelanocyteSpecific gp100 Antigen as the Dominant Epitope Recognized by an HLAA2.1Restricted AntiMelanoma CTL Line,” International Journal of Cancer62, no. 1 (1995): 97 102, https://doi.org/10.1002/ijc.2910620118. Rect: 455, 372, 463, 359 ActionDest: 311 Annotation: Subtype: Link Contents: P.Romero, D. E.Speiser, and N.Rufer, “Deciphering the Unusual HLAA2/MelanA/MART1 Specific TCR Repertoire in Humans,” European Journal of Immunology44, no. 9 (2014): 2567 2570, https://doi.org/10.1002/eji.201445004. Rect: 524, 372, 533, 359 ActionDest: 311 Annotation: Subtype: Link Contents: K.Fujiwara, Y.Shao, N.Niu, etal., “Direct Identification of HLA Class I and Class IIRestricted T Cell Epitopes in Pancreatic Cancer Tissues by Mass Spectrometry,” Journal of Hematology & Oncology15, no. 1 (2022): 1 5, https://doi.org/10.1186/s13045022013736. Rect: 501, 349, 523, 336 ActionDest: 311 Annotation: Subtype: Link Contents: K. L.Knutson, K.Schiffman, and M. L.Disis, “Immunization With a HER2/Neu Helper Peptide Vaccine Generates HER2/Neu CD8 TCell Immunity in Cancer Patients,” Journal of Clinical Investigation107, no. 4 (2001): 477 484, https://doi.org/10.1172/JCI11752. Rect: 425, 326, 434, 313 ActionDest: 354 Annotation: Subtype: Link Contents: N.Ma, T.Zhou, C.Li, etal., “A PanCancer Analysis of the Prognosis and Immune Infiltration of eEF1A2 and Its Potential Function in Thyroid Carcinoma,” Heliyon10, no. 3 (2024): e24455, https://doi.org/10.1016/j.heliyon.2024.e24455. Rect: 519, 107, 527, 95 ActionDest: 354 Page: Sequence: 15 Annotations: Annotation: Subtype: Link Contents: Y.PerezRiverol, A.Csordas, J.Bai, etal., “The PRIDE Database and Related Tools and Resources in 2019: Improving Support for Quantification Data,” Nucleic Acids Research47, no. D1 (2019): D442 D450, https://doi.org/10.1093/nar/gky1106. 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Rect: 208, 650, 289, 639 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1038/jhg.2008.5 for your more information Rect: 45, 640, 81, 629 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1038/s41589-023-01316-3 for your more information Rect: 263, 605, 289, 593 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1038/s41589-023-01316-3 for your more information Rect: 45, 595, 168, 583 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.3389/fimmu.2013.00172 for your more information Rect: 61, 549, 205, 538 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.4049/jimmunol.169.8.4674-a for your more information Rect: 207, 504, 289, 492 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.4049/jimmunol.169.8.4674-a for your more information Rect: 45, 494, 124, 482 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.3389/fimmu.2022.835454 for your more information Rect: 45, 438, 195, 427 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1074/jbc.RA119.009437 for your more information Rect: 227, 393, 289, 382 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1074/jbc.RA119.009437 for your more information Rect: 45, 383, 125, 372 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1016/j.celrep.2024.115150 for your more information Rect: 182, 337, 289, 326 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1016/j.celrep.2024.115150 for your more information Rect: 45, 327, 88, 316 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1074/jbc.M110.148155 for your more information Rect: 96, 282, 233, 271 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1111/imm.12889 for your more information Rect: 169, 247, 284, 235 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1007/BF02918202 for your more information Rect: 148, 211, 267, 200 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1126/science.adi3808 for your more information Rect: 251, 186, 289, 174 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1126/science.adi3808 for your more information Rect: 45, 176, 142, 164 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1126/science.aao4572 for your more information Rect: 227, 140, 289, 129 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1126/science.aao4572 for your more information Rect: 45, 130, 119, 119 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.3389/fimmu.2023.1268117 for your more information Rect: 140, 95, 287, 84 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1016/j.immuni.2023.05.009 for your more information Rect: 524, 751, 549, 740 Annotation: Subtype: Link Contents: Please visit https://doi.org/10.1016/j.immuni.2023.05.009 for your more information Rect: 306, 741, 436, 730 Annotation: 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The number of MoDCs obtained per sample ranged from 1.55 to 17.3 million. Peptide binding affinities for the different alleles were predicted using the NetMHCIIPan4.1 algorithm, revealing allelespecific binding imbalances. Rect: 406, 591, 414, 580 ActionDest: 354 Checksum: 988e34d9 Type: CRC32 Checksum: 4b35dc6ad8831a1612196846da64e819 Type: MD5 Checksum: 48d7777ad0f8ad198dbcaa8efdee282dd5f0c914 Type: SHA-1 Checksum: fac2f2d12db2fdbabc8fc0e5b50d13da34421c53f3e143df4e6128830eee094d Type: SHA-256