IFNγ Modulates the Immunopeptidome of Triple Negative Breast Cancer Cells by Enhancing and Diversifying Antigen Processing and Presentation

Peptide vaccination remains a viable approach to induce T-cell mediated killing of tumors. To identify potential T-cell targets for Triple-Negative Breast Cancer (TNBC) vaccination, we examined the effect of the pro-inflammatory cytokine interferon-γ (IFNγ) on the transcriptome, proteome, and immunopeptidome of the TNBC cell line MDA-MB-231. Using high resolution mass spectrometry, we identified a total of 84,131 peptides from 9,647 source proteins presented by human leukocyte antigen (HLA)-I and HLA-II alleles. Treatment with IFNγ resulted in a remarkable remolding of the immunopeptidome, with only a 34% overlap between untreated and treated cells across the HLA-I immunopeptidome, and expression of HLA-II only detected on treated cells. IFNγ increased the overall number, diversity, and abundance of peptides contained within the immunopeptidome, as well increasing the coverage of individual source antigens. The suite of peptides displayed under conditions of IFNγ treatment included many known tumor associated antigens, with the HLA-II repertoire sampling 17 breast cancer associated antigens absent from those sampled by HLA-I molecules. Quantitative analysis of the transcriptome (10,248 transcripts) and proteome (6,783 proteins) of these cells revealed 229 common proteins and transcripts that were differentially expressed. Most of these represented downstream targets of IFNγ signaling including components of the antigen processing machinery such as tapasin and HLA molecules. However, these changes in protein expression did not explain the dramatic modulation of the immunopeptidome following IFNγ treatment. These results demonstrate the high degree of plasticity in the immunopeptidome of TNBC cells following cytokine stimulation and provide evidence that under pro-inflammatory conditions a greater variety of potential HLA-I and HLA-II vaccine targets are unveiled to the immune system. This has important implications for the development of personalized cancer vaccination strategies.


INTRODUCTION
Breast cancer is the most commonly diagnosed cancer and contributes to the second largest mortality rate in women worldwide (1). Triple Negative Breast cancer (TNBC) is a highly heterogeneous disease characterized by malignant and aggressive tumor growth within the breast ducts (2). TNBC is characterized by the negative expression of three extracellular receptors: the estrogen receptor (ER), the progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2) (3). Consequentially, this has led to many therapeutic challenges in pursuing avenues for treatment, as TNBC is not subject to targeted therapies that are exploited in traditional hormonedependent breast cancer subtypes (4). As well-defined molecular targets for TNBC await identification, chemotherapy remains the primary means for treatment (5). As such, novel therapies are being explored, particularly those drawing upon the recent advancements in T cell immunotherapy.
Harnessing the power of the adaptive immune response is becoming an area of much interest and promise. Since the discovery of the first T cell-defined tumor antigen (6), a plethora of studies have led to the identification and direct assessment of the cell surface HLA-peptide repertoire (the field of immunopeptidomics) in different cancers, autoimmunity related conditions, and viral infections (7)(8)(9)(10)(11)(12)(13)(14). These HLApeptides can derive from the HLA-I pathway via cytosolic proteasomal degradation of proteins and transport of resultant peptides to the endoplasmic reticulum by the transporter associated with antigen processing (TAP) (15). These peptides (typically 8-12 amino acids in length) are loaded onto nascent HLA-I molecules based on their suitability to bind to the individual's HLA allotypes and transported to the cell surface for CD8+ T cell recognition. In contrast, the HLA-II pathway relies on lysosomal degradation of proteins by professional antigen presenting cells (APCs), with peptide loading occurring in the late endosome (with peptides 13-17 amino acids in length) (16) and transport of the HLA-II-peptide complexes to the cell surface for recognition by CD4+ T cells.
The molecular apparatus governing cell surface peptide display by HLA molecules is referred to as the antigen processing and presentation machinery (APPM), and both the HLA-I and HLA-II pathways have been shown to be strongly influenced by the tumor microenvironment including the presence of the pro-inflammatory cytokine interferon g (IFNg) (17,18). IFNg has the capacity to augment the presentation of HLA-I molecules (particularly the HLA class I B allomorphs) on the cell surface, as well as by altering the peptide repertoire through inducing the formation of the immunoproteasome (8,(19)(20)(21)(22)(23).
This specialized form of the proteasome possesses altered cleavage specificities, and has been proposed to remold the peptide repertoire allowing for presentation of a more diverse set of peptide antigens (8,19,20,24). Furthermore, cytokine driven changes have the ability to induce HLA-II expression on non-professional APC cells by activating the MHC class II transactivator (CIITA) (25). This phenotype can be mimicked in cell culture experiments following IFNg treatment allowing for the elucidation of HLA-II targets on cancerous cells that would otherwise be missed. Despite these known effects of IFNg, the mechanism of how cytokine derived alterations to the peptide repertoire occur has been a source of conjecture, with the individual roles of the transcriptome, source protein expression, and changes within the APPM yet to be conclusively determined. This is compounded by the poor correlations often observed between the proteome and the transcriptome of cells (26,27). Further, the general lack of immunopeptidomic studies with corresponding transcript and source protein measurements has led to difficulties elucidating the key determinants of HLA peptide presentation.
Here we have investigated the composition of the TNBC cell l i n e M D A -M B -2 3 1 t r a n s c r i p t o m e , p r o t e o m e , a n d immunopeptidome and quantified changes observed in each 'Omics data set under conditions of IFNg treatment. We achieved substantial depth at the transcript, protein, and HLApeptide level and show that IFNg not only increases antigen presentation but also unveils a suite of novel peptides to the immune system, many of which derive from known cancer antigens. This remolding of the peptidome was not strongly correlated with changes observed at transcript and protein level. These data highlight the importance of directly measuring the immunopeptidome of cancer cells since antigen processing and presentation cannot be inferred from the more readily measured transcriptome and proteome. Therefore, studies relying on these assumptions, risk excluding and misidentifying bona fide and potential therapeutic targets for cancer vaccination.

HLA Typing of MDA-MB-231 Cells
Total DNA was extracted from 5 × 10 6 cells by the Qiagen DNA extraction for spin-column or 96-well purification of total DNA from animal blood and tissues and from cells, yeast, bacteria, or viruses (cat # 69504) kit as per manufacturer's protocol. Samples were sent to the Victorian Transplantation and Immunogenetic Service (VTIS) for high resolution HLA typing.

RNA Sequencing
Total RNA was extracted from 1 × 10 5 MDA-MB-231 cells in three biological replicates of IFNg treated (50 IU for 48 h) and untreated conditions using RNeasy mini kit (Qiagen) according to the manufacturer's instructions. Cells were cultured from an initial seed flask before being split into six flasks for comparative analysis of each replicate. Sequencing was performed by BGI Genomics (Hong Kong) with 100 base pair end reads to a depth of 30 million reads. The raw RNA-sequencing files were aligned using the Monash Bioinformatics Platform RNAsik pipeline (28). The RNA-seq files were aligned to the GRCh37 version of the genome and the corresponding annotation files (gtf).

Proteomics
The total proteome content of MDA-MB-231 cells was extracted in three biological replicates of IFNg treated (50 IU for 48 h) and untreated conditions. These cells were cultured from the identical seed flask used in transcriptome analysis before been split into an additional six flasks and harvested. Harvested cells were snap frozen using liquid nitrogen on the same day for proteomics and transcriptomics studies. These pelleted cells were lysed (5 × 10 6 cells) with 1% (w/v) sodium deoxycholate SDC lysis buffer in Tris pH 8.1. Lysate was then boiled at 95°C for 5 min and sonicated. Then 400 µg of protein was taken, and this was then denatured and alkylated with the addition of 10 mM Tris(2-carboxyethyl) phosphine (TCEP) and 40 mM chloroacetamide (CAA) at 95°C for 5 min. This was then allowed to cool to room temperature and the pH was adjusted to 8 before trypsin was added at a ratio of 1:30 [trypsin:protein (w/w)] and incubated at 37°C with shaking at 180 rpm overnight. The trypsin digested lysate was then fractionated into 18 fractions by C18 RP-HPLC. These fractions were then pooled into six fractions and analyzed on mass spectrometry for data dependent acquisition (35).

Immunopeptidomics Sample Preparation
HLA-I and -II peptides were eluted from three biological replicates of 5 × 10 8 MDA-MB-231 cells prior to or after treatment with IFNg (i.e. n = 6) as described (36). Briefly, cells were lysed in 0.5% IGEPAL, 50 mM Tris-HCl pH 8.0, 150 mM NaCl supplemented with protease inhibitors (Complete Protease Inhibitor Cocktail Tablet; Roche Molecular Biochemicals) for 45 min at 4°C. Lysates underwent ultracentrifugation at 40,000 g and HLA-I and -II complexes were purified using a pan HLA-I antibody (w6/32) whilst HLA-II complexes were purified with the allele-specific antibodies of LB3.1 (HLA-DR), B721 (HLA-DP), and SPV-L3 (HLA DQ). The HLA peptide bound molecules were then eluted from the affinity column with five column volumes of 10% acetic acid. The eluted HLA-I or HLA-II peptide complexes were loaded onto a 4.6 mm internal diameter × 50 mm monolithic C18 RP-HPLC column (Chromolith Speed Rod; Merck) at a flow rate of 1 ml/min using an EttanLC HPLC system (GE Healthcare) with buffer A [0.1% trifluoroacetic acid (TFA)] and peptides separated by increasing concentrations of buffer B (80% ACN/0.1% TFA) as described in (36). Fractionated peptides were then concatenated into 10 pools and analyzed with an Orbitrap Fusion ™ Tribrid ™ mass spectrometer (ThermoFisher Scientific).
For quantitative proteomics we used data independent acquisition (DIA) approach the identical LC-MS/MS instrument setup above was used. Twenty-five sequential DIA windows with an isolation width of 24 m/z between 375 and 975 m/z were acquired. A 158-min gradient of increasing concentrations of 80% ACN/0.1% FA was used to separate the peptides for DIA acquisition.

Proteomics Identification and Quantification
The Acquired DDA.raw files were searched against the human proteome (Uniprot v_05102017) using Spectronaut Pulsar software to obtain peptide sequence information and generate a spectral library for DIA analysis. The following search parameters and settings have been used: (i) trypsin (full specificity after Arginine and Lysine) was selected as protease and up to one missed cleavage was permitted (37); mass tolerances were set to 10 ppm for precursor and 0.02 Da for fragment masses; (iii) carbamidomethylation of C was selected as fixed and oxidation of methionine residues was selected as variable modification. Only peptides identified at a false discovery rate (FDR) of 1% based on the added decoy database were considered for spectral library generation. Spectronaut 10 (Orion; Biognosys) was used to create the corresponding spectral library and search all DIA raw files. For data analysis, we used Spectronaut 10 default protein-centric parameters (BGS Factory Settings). Data matrices containing the quantitative values were obtained from "QValue Sparse" scores.

HLA Peptide Identification
MS/MS spectra were analyzed via PEAKS studio X software. MS files were imported into PEAKS X with the following settings: parent mass error tolerance was set at 10 parts per million with a fragmentation mass error of 0.02 Da. An initial de novo search of all MS/MS spectra against peptide sequences was performed followed by a specific search against the human proteome database with oxidation of methionine selected as a variable PTM. A false discovery rate (FDR) of 1% was implemented and all resulting peptides were exported.

Clustering and Binding Prediction of HLA Peptides
The peptide data was extracted and underwent further data analysis using Gibbs clustering to validate the biochemical properties of these peptides (38). Furthermore, peptides were allocated as binders or non-binders using NetMHCpan. This software predicts HLApeptide binding using artificial neural networks, here we implemented the default cut-off of 2 as a binder peptide (39).

IFNg Diversifies the Immunopeptidome of the TNBC MDA-MB-231 Cell Line
To study the effect of IFNg on the immunopeptidome of TNBC, we utilized MDA-MB-231, a metastatic breast adenocarcinoma cell line derived via pleural effusion (40). Testing IFNg concentrations at multiple timepoints, we determined that 50 IU for 48 h led to the greatest increase in HLA-I expression (average of 4.8-fold) as well as inducing HLA-II expression ( Figure 1A and Supplementary Figure 1) (P < 0.0001). These conditions were therefore used for all subsequent experiments.
Next, we interrogated the immunopeptidome of MDA-MB-231 cells in the presence or absence of IFNg, via immunoprecipitation of total HLA-I or HLA-II and identification of eluted peptides by mass spectrometry (36). Across three biological replicates of IFNg treated and untreated MDA-MB-231 cells, a total of 51,779 HLA-I and 34,641 HLA-II peptides were identified. An average of 15,785 HLA-I peptides were presented on untreated samples, increasing to 29,165 (1.85-fold p < 0.004) on IFNg treated samples, whilst an average of 22,316 HLA-II peptides were observed across the IFNg treated cells ( Figure 1B).
To attain a more detailed insight into this modulation, we listed and categorized all HLA-I peptides identified in untreated and IFNg treated samples and compared each of these against replicates from the opposing condition, allowing categorization of common peptides and those unique to each condition ( Supplementary Figures 2A-F). Overall, the HLA-I immunopeptidome reflects a total unique repertoire of 27,532 peptides (53.2%) present only following IFNg treatment. Conversely, 4,850 peptides (9%) were uniquely present on untreated samples whilst 19,397 (~37.5%) were shared across both HLA-I conditions (Supplementary Figure 2G). Analysis of the unique peptides showed that, as expected (and as observed in the common set), HLA-I peptides displayed a marked preference for 9 mers ( Figure 1C). However, IFNg stimulation led to a statistically significant increase (p < 0.0001 2way ANOVA for multiple comparisons) in the presentation of 10 and 11 mers ( Figure 1C). As anticipated HLA-II peptides only detected under conditions of IFNg treatment (Supplementary Figure 3A), and these peptides displayed characteristic length distributions predominantly (~65%) between 14 and 18 amino acids in length (Supplementary Figure 3B).
We next assessed the HLA allotype binding predictions of the peptides specific to treated or untreated cells. Filtering on 8-12 mer peptides unique to untreated or IFNg treated, we analyzed these peptides according to their HLA allotype predicted binding affinities using NetMHCpan 4.0 ( Figure 1D and Supplementary Figure 3C); 80.8% (1,756) of peptides unique to untreated cells and 90.2% (12,492) of peptides unique to IFNg treated cells were assigned as predicted binders to at least one of the alleles expressed by MDA-MB-231. However, IFNg treatment also resulted in a significant (p < 0.0001) increase (~32%) in the number of predicted binders to the HLA-B allomorphs expressed by these cells ( Figure 1D). Notably, the increased preference for 10 mers and 11 mers was more pronounced for peptides identified following IFNg treatment and particularly for HLA-B (Supplementary Figures 3D-G). Further evidence of HLA-B enrichment following IFNg treatment was observed by performing Gibbs cluster analysis. This software clusters peptides based on distinct sequence features (motifs), and this revealed a higher proportion of 9 mer peptides were clustered to the motif of HLA:B rather to the other alleles reported for this cell line (Supplementary Figures 4A, B).

IFNg Treatment Alters the Source Protein Landscape of MDA-MB-231 Cells
To assess how IFNg altered the presentation of different antigens in the HLA-I repertoire, we examined the source protein origin of identified peptides (Figures 2A, B). Comparison of source protein coverage between IFNg treated and untreated replicates revealed that the number of source proteins increased (1.3-fold) following treatment (Figure 2A). A comparative analysis revealed that across three biological replicates, 3,327 source proteins were shared across the two conditions. Whilst IFNg treatment led to 1,914 source proteins being uniquely represented at the immunopeptidome level ( Figure 2B). Conversely, 459 proteins were only represented by HLA-I peptides under the untreated conditions ( Figure 2B).
To furth er examin e th e effe ct of IFNg on the immunopeptidome of MDA-MB-231 cells at a source protein level, we examined the degree of peptide coverage and relative peptide abundance for all 3,327 shared HLA-I source proteins. Source proteins of peptides isolated from untreated cells contained a mean peptide coverage of 6.10%, whilst following IFNg this increased significantly by 1.44-fold to a mean of 8.82% (p < 0.0001) (Supplementary Figure 5A). A similar effect was observed when comparing total peptide number across these antigens with a 1.68-fold increase following IFNg treatment (mean of 4.074 for untreated vs 6.835 for IFNg treated, p < 0.0001) (Supplementary Figure 5B). Label-free quantitation (LFQ) of the MS1 intensity of these peptides also showed a significant shift (~2.8-fold, p < 0.0001) following IFNg treatment, whilst peptides derived from proteins unique to each condition had lower LFQ values for untreated, increasing~1.87-fold upon exposure to IFNg ( Figure 2C).
Following the changes observed within the intensities of the common source proteins, we also determined whether the number of peptides derived from each source protein was altered following IFNg treatment. As seen in Figure 2D, IFNg treatment caused a significant decrease in the number of proteins that are represented by only one or two HLA-I peptides (p = 0.0001 and p = 0.0018 respectively), whilst there was a significant

IFNg Increases the Presentation of HLA-Peptides Derived From Tumor Associated Antigens
We next interrogated the HLA-I immunopeptidome from MDA-MB-231 cells for peptides derived from 641 breast cancerspecific or associated antigens compiled from multiple databases (CTantigen, T-Antigen, and breast cancer-specific antigens from UniProt). Using this refined list of 598 cancerous antigens (Supplemental File 1), a total of 2,680 peptides derived from 300 antigens were identified across our HLA-I immunopeptidome data in at least one replicate at 1% FDR. The IFNg-dependence for the presentation of these peptides is shown in Figure 3A. This highlights that although 1,180 peptides derived from cancer antigens are represented in the HLA-I immunopeptidome under both conditions, IFNg treatment leads to the presentation of an additional 1,268 peptides derived from cancer antigens ( Figure 3A). Furthermore, from the 245 HLA-I cancer-associated antigens common to both conditions, many were represented by more peptides following IFNg treatment ( Figure 3B) (A similar trend was observed across the total common source antigen pool, Supplementary Figure 5C). We next assessed the overall representation of these cancer associated antigens across the HLA-I and -II immunopeptidomes under both conditions ( Figure 3C). This analysis revealed that whilst many antigens had peptides presented by both HLA-I and HLA-II, 17 antigens were identified to be exclusive to the repertoire of HLA-II. Notable within these cancer antigens were the GTPase KRAS and the breast carcinoma associated antigen DF3. To perform a direct comparison between the repertoires and coverage of HLA-I and HLA-II in the context of these antigens and IFNg treatment, we examined the 115 shared ( Figure 3C) cancer associated antigens  Figure 3D).
The above dataset of 300 cancer-associated antigens presented by HLA-I was further refined to only include those described as associated or specific to breast cancer, resulting in 41 antigens in total. Figure 3E shows the number of HLA-I peptides derived from these proteins under each condition (classified as only detected in untreated, only detected in IFNg-treated or common to both conditions). This exemplifies different trends such as the four-breast cancer associated antigens (A-kinase anchor protein 13, Rho-related BTB domain-containing protein 2, Breast carcinoma-amplified sequence 4, and Protein SMG8) only present within IFNg treated cells. Furthermore, this analysis highlights the capacity of IFNg to enrich peptides associated with these cancer antigens, with a large proportion of these antigens only detected in IFNg dependent immunopeptidome (Supplementary Figure 6A denotes the total cancer antigen pool, which further exemplifies this trend). Examples of specific antigens of interest that highlight the capacity of IFNg to augment the presentation of potential breast cancer-associated candidates include NY-BR-16, which increased from 11 peptides to 30 following IFNg treatment, and breast cancer-associated antigen BRCAA1, which increased from three peptides to eight following IFNg treatment. Furthermore, from the 2,680 total HLA-I peptides derived from these cancer antigens a total of 636 were previously unreported in the literature, further highlighting the depth and coverage of this repertoire.

Integrated Omics Reveal Increased APPM Modulation Following IFNg Treatment
To attain a further insight into the IFNg-induced changes within the immunopeptidome, we examined the cellular transcriptome and proteome of the MDA-MB-231 cells to ascertain whether these changes were mirrored in these compartments. As Total RNA and cellular proteins were extracted from the identical seed flask of MDA-MB-231 cells and grown under the same conditions used for the immunopeptidome studies, we justify this rationale to perform integrative omics. Following RNA isolation and sequencing, an average of 16,815 and 16,452 transcripts for untreated and IFNg treated conditions,  respectively, were identified across the biological replicates ( Figure 4A). From this analysis, 16,875 total transcripts were identified of which 1,094 were significantly up-regulated (FDR < 0.05) and 914 were significantly down-regulated (FDR < 0.05) after IFNg treatment (Supplementary Figure 7A). The significantly up-regulated transcripts displayed a strong molecular signature of IFNg inducible targets and highlight a profound effect on the APPM (Supplementary Figure 7B). At the protein level, initial mass spectrometric analysis led to the identification of a mean of 5,191 proteins detected under IFNg treated conditions compared to 6,004 proteins under untreated conditions ( Figure 4A) (p = 0.0112). A more indepth data-independent acquisition (DIA)-based quantitative mass spectrometry analysis revealed 463 proteins were found to be significantly up-regulated (Q-value <0.05) upon IFNg treatment, whereas 812 proteins were significantly downregulated (Q-value <0.05) (Supplementary Figure 7C). Similar to what was observed at the transcript level, a variety of downstream interferon mediated proteins and components of the APPM were enriched within the upregulated subset (Supplementary Figure 7B). The transcriptome and proteome overlap (Supplementary Figure 7D) allowed for comparative analysis of differential expression amongst shared genes and proteins, revealing a significant but weak correlation of 0.275 (p value <0.0001) ( Figure 4B).
Following a clear indication that components and associated proteins of the APPM were highly susceptible to IFNg treatment, we decided to further interrogate these changes ( Figure 4C). Interestingly, within the HLA-I allotypes, non-classical HLA-I contained the largest increase following IFNg treatment in the transcriptome (HLA-F was upregulated 37.5-fold) and the proteome (HLA-E was upregulated 5.96-fold). This was followed by HLA-B in both the transcriptome and the proteome, being up-regulated 15.74-fold and 5.64-fold, respectively. HLA-II allotypes were heavily modulated following IFNg treatment at both the protein and transcript  level. For example, HLA-DQ showed the highest increase within the transcriptome followed by HLA-DP and then HLA-DR. Although, this overall effect was maintained at the proteome level, the order was altered with HLA-DR showing the highest degree of modulation followed by HLA-DP. No HLA-F or HLA-DQ was detected via mass spectrometry ( Figure 4C).

Multi-omic Comparison of Proteome and Transcriptome Expression and Its Relation to the Immunopeptidome
The breadth and depth of this omics data allowed a systematic analysis between transcriptome and proteome abundance and resulting HLA-I derived peptides. To do this, we assessed the extent to which IFNg-mediated differential expression at the transcript and protein level affected modulation of the immunopeptidome (Figures 5A, B). Figure 5A shows a weak but significant correlation (Pearson correlation coefficient 0.2, p < 0.0001) of IFNg-induced changes at the transcript and HLA-I immunopeptidome level. A similar but weaker trend was observed at the protein level ( Figure 5B; Pearson correlation coefficient 0.08, p < 0.0001). To assess this further, we categorized the change in the IFNg-modulated immunopeptidome into three groups based on the fold change in the number of peptides per protein [decreased (fold change <0.5), unchanged (fold change 0.5-1.5), or increased (fold change >1.5)] and visualized the distribution of corresponding source transcript and protein expression across each category ( Figure 5C). These data further suggest that the IFNg induced modulation of the immunopeptidome is poorly reflected by corresponding changes across either the transcriptome or proteome. Protein half-life has been suggested by previous studies to be an important determinant of HLA presentation, as proteins with high turnover rates are more susceptible to be presented via HLA molecules. To examine this we used the protein half-life data from the Lamond group (41) to determine the effect of protein half-life on our HLA peptide data. We examined our IFNg treated and untreated datasets and could not find a significant correlation between proteins with shorter half-lives and an increased presentation on the immunopeptidome {Pearson correlation coefficient value of −0.004 [p-value of 0.8 (IFNg untreated)] and −0.02 [p-value of 0.15 (IFNg treated)]} (Supplementary Figures 8A, B). In order to further determine the impact of protein stability and its effect on HLA peptide presentation we filtered the Lamond dataset and used the top 100 most rapidly degrading proteins (RDP) and the top 100 most stable proteins to determine if a correlation could be observed between their respective protein half-life and the number of peptides presented on the immunopeptidome. Analysis between the top 100 half-lives of RDP and the number of HLA-I peptides by a Pearson correlation test, determined a correlation coefficient of 0.131 and 0.072 for untreated and IFNg treated with non-significant p-values of 0.19 and 0.47 respectively (Supplementary Figures 8C, D). Analysis of the top 100 most stable protein half-lives with a Pearson correlation test yielding a correlation coefficient of 0.025 and 0.019 with non-significant p values of 0.81 and 0.85 respectively for untreated and IFNg treated samples (Supplementary Figures 8E, F).

DISCUSSION
The tumor microenvironment (TME) is a pivotal component of tumor development and progression and is a key variable often overlooked when comparing cell culture experiments to patient derived cancerous material (8). The pro inflammatory cytokine IFNg is secreted by both the tumor and infiltrating immune cells into the extracellular space acting synergistically to increase HLA expression and enhance antigen presentation (18,20). Although the effects of IFNg within the TME have been extensively studied, its effect on the immunopeptidome has only received recent interest (8,9,19,20,23,42). HLA silencing is a common tumor mechanism to evade cellular immunity, with tumors containing IFNg or "inflamed" tumors conferring an improved prognosis and higher overall susceptibility to immunotherapy approaches such as immune checkpoint inhibitors (43). Therefore, it can be speculated that the immunopeptidome of IFNg exposed tumors confer a higher level of anti-tumor immunity due to the presence of IFNg-dependent peptide antigens. This is an important consideration for future studies wishing to examine the immunopeptidome of cancer cells.
In this study the TNBC model cell line MDA-MB-231 was comprehensively characterized, with in-depth analysis of the transcriptome, proteome, and immunopeptidome of these cells cultured in the presence or absence of IFNg. Following qualitative assessment of the immunopeptidome we have identified >51,000 unique peptides in HLA-I and >34,000 unique peptides in HLA-II peptidomes. More importantly we have identified 54,440 previously unreported HLA-I and HLA-II-restricted peptides of which 23,386 were 8-12 mers, adding a valuable source of peptide antigens to the literature. IFNg treatment caused considerable remolding of the immunopeptidome with typically less than 50% overlap observed between the induced and basal immunopeptidomes. Moreover, an increase in longer peptides (towards 10-and 11-mers) and decreased representation of HLA-A and HLA-C binding peptides was also observed. This change was mirrored at the HLA-B transcript and protein level with allotypes from these loci dominating the immunopeptidome following IFNg treatment. Consistent with this observation, HLA-B modulation following IFNg treatment has been highlighted in previous studies (8,20). However, here we show that these HLA-B binding peptides include a higher proportion of 10-and 11-mer peptides. We speculate that the appearance of these longer peptides within the immunopeptidome are either or a combination of the effects of IFNg induction at the APPM favoring the generation of longer peptides, or that the increased and abundant expression of nascent HLA-I allotypes facilitates the binding of longer peptide precursors under less competitive binding conditions. The mechanistic basis of these observations will be the subject of future studies.
A key observation made in this study addresses the mechanism of the IFNg mediated remolding of the immunopeptidome. Here we show a large overlap in the expression of protein antigens between both treatment conditions (93%). However, there is a considerable increase in source protein representation in the HLA-I immunopeptidome (2,343 new source proteins) following cytokine treatment. Moreover, IFNg-treatment increased the number of distinct peptides derived from a given antigen thereby increasing the coverage of the source protein and enhancing the chances of T cell recognition. One of the reasons this shift occurred may be due to IFNg increasing the overall expression level HLA-peptide complexes, circumventing some of the challenges in peptide identification and allowing them to be more readily identified via mass spectrometry. Furthermore, the shift observed within the peptide repertoire was not proportional to changes within source protein abundance. This highlights that IFNg induction leads to an enhancement of antigen processing and presentation independent of source protein abundance.
We next examined if previously determined protein degradation rates for some of the source antigens lead to enhanced processing and presentation of these antigens. This analysis also did not provide an explanation for the observed changes in the immunopeptidome following IFNg stimulation. This is in accordance with a previous study that has suggested HLA peptide presentation is determined by HLA availability rather than peptide supply (20). Consistent with this observation a higher number of potential HLA-B binders entered the immunopeptidome in association with increases in the evidence for these HLA allotypes in the transcriptome and proteome following IFNg treatment. Furthermore, this trend was not correlated with protein or transcript abundance, supporting the notion that peptide pools exist within the endoplasmic reticulum and these peptides are then bound to available HLA molecules based on their affinities (20).
A higher availability of HLA molecules in the ER promotes increased peptide presentation and this becomes clinically significant as it unveils a suite of antigens which would have been previously missed. This was supported when examining cancer associated antigens, highlighting the increased coverage and the increased diversity of peptides presented with therapeutic relevance. Overall, examining the immunopeptidome in the context of inflammation not only mimics the physiological environment of a tumor more accurately, it also increases the scope and potential to identify more antigens that can be exploited through vaccine approaches. This was particularly evident when comparing tumor associated showing an overall increase in the number and label free intensities of these antigens of interest. Although these peptides have not been tested for their immunogenicity, they are potential sources to be examined in future research. This dataset also encompassed previously reported immunogenic epitopes that were considered to be HLA-A*02:01 restricted and immunogenic based on their annotations in the IEDB (44): with 28 peptides in IFNg untreated and 32 peptides in IFNg treated samples. It is important to consider that IFNg treatment mimics the phenotype of a "hot" tumor, a phenotype associated with improved immunotherapy success (45). Our data also suggest that the enhanced presentation of HLA:B resident peptides could be one of the factors that provide a higher degree of anti-tumor immunity in such "hot" tumors (8).
Taken together these results highlight the plasticity of the TNBC immunopeptidome following IFNg treatment. Importantly, we show that these changes are not mirrored by intracellular changes in protein and transcript abundance but rather the enhancement of the APPM following cytokine stimulation. The combined dataset from basal and cytokine stimulated MD-MBA-231 TNBC cells represents one of the most comprehensive HLA peptide dataset from a single cell line with over 84,000 linear peptides identified with high confidence. This study provides a comprehensive understanding of the role of cytokine derived changes to the immunopeptidome of TNBC, which will act as a critical consideration for the development of personalized vaccine therapy.

DATA AVAILABILITY STATEMENT
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: PRIDE repository, accession numbers: PXD023038 and PXD023044.

AUTHOR CONTRIBUTIONS
GG, NC, PF, and AP conceived and planned all experiments. GG, DD, and RA carried out the experiments. NC, PF, and GG contributed to mass spectrometry analyses. KM, NC, PF, and GG contributed to bioinformatics analyses. GG, NC, PF, and AP wrote the manuscript. All authors contributed to the article and approved the submitted version.  following IFNg treatment comparing overall coverage (A), total peptides (B), and overall peptide fold change following treatment (C). Statistical analysis was performed by using a two-way ANOVA and significance is highlighted by **** (P < 0.001). All data are from three biological replicates per condition.
Supplementary Figure 6 | Three hundred cancer specific or associated antigens are then plotted to show the overall distribution of HLA peptides originating from both IFNg treated and untreated or peptides unique to each condition. Figure 7 | A volcano plot denoting the transcriptome (A) distribution following IFNg treatment, a line at y = 1.3 is shown to depict differentially expressed transcripts (FDR < 0.05). A comparative analysis between the common identified significant transcripts (FDR < 0.05) and proteins (Q < 0.05) are shown in (B) (n = 220). The corresponding log 2 fold change of these genes and proteins were plotted with a selection of antigen presentation pathway associated genes shown in blue. Correlative analysis following a Pearson correlation test between 220 transcripts and proteins revealed a 95% CI of 0.66 and 0.78 with a correlation of 0.73. The p value reported was 3.37e-37. A volcano plot denoting the proteome changes following IFNg treatment is shown in (C) with a line at y = 1.  A and B respectively). The top 100 half-lives considered to be the Rapidly degrading proteins (RDP) were analyzed with the number of HLA-I peptides from untreated (C) and IFNg treated (D). Following a Pearson correlation test an insignificant p value was determined (0.19 untreated and 0.47 for IFNg treated) with a correlation coefficient of 0.131 and 0.072 respectively. Furthermore, the top 100 most stable half-lives were also analyzed with the number of HLA-I peptides from untreated (E) and IFNg treated (F). Following a Pearson correlation test an insignificant p value was determined (0.81 untreated and 0.85 for IFNg treated) with a correlation coefficient of 0.025 and 0.019 respectively. Table of cancer antigens.