PeptiCHIP: A Microfluidic Platform for Tumor Antigen Landscape Identification

Abstract

Identification of HLA class I ligands from the tumor surface (ligandome or immunopeptidome) is essential for designing T-cell mediated cancer therapeutic approaches. However, the sensitivity of the process for isolating MHC-I restricted tumor-specific peptides has been the major limiting factor for reliable tumor antigen characterization, making clear the need for technical improvement. Here, we describe our work from the fabrication and development of a microfluidic-based chip (PeptiCHIP) and its use to identify and characterize tumor-specific ligands on clinically relevant human samples. Specifically, we assessed the potential of immobilizing a pan-HLA antibody on solid surfaces via well-characterized streptavidin-biotin chemistry, overcoming the limitations of the cross-linking chemistry used to prepare the affinity matrix with the desired antibodies in the immunopeptidomics workflow. Furthermore, to address the restrictions related to the handling and the limited availability of tumor samples, we further developed the concept toward the implementation of a microfluidic through-flow system. Thus, the biotinylated pan-HLA antibody was immobilized on streptavidin-functionalized surfaces, and immune-affinity purification (IP) was carried out on customized microfluidic pillar arrays made of thiol-ene polymer. Compared to the standard methods reported in the field, our methodology reduces the amount of antibody and the time required for peptide isolation. In this work, we carefully examined the specificity and robustness of our customized technology for immunopeptidomics workflows. We tested this platform by immunopurifying HLA-I complexes from 1 × 10⁶ cells both in a widely studied B-cell line and in patients-derived ex vivo cell cultures, instead of 5 × 10⁸ cells as required in the current technology. After the final elution in mild acid, HLA-I-presented peptides were identified by tandem mass spectrometry and further investigated by in vitro methods. These results highlight the potential to exploit microfluidics-based strategies in immunopeptidomics platforms and in personalized immunopeptidome analysis from cells isolated from individual tumor biopsies to design tailored cancer therapeutic vaccines. Moreover, the possibility to integrate multiple identical units on a single chip further improves the throughput and multiplexing of these assays with a view to clinical needs.

Keywords: HLA peptides; affinity purification; ligandome; microfluidics; thiol−enes.

Figure 1

Microchip technology as an immunopurification platform for fast antigen discovery. A schematic overview describing the microchip methodology developed. Thiol–ene microchips incorporating free surface thiols are derivatized with biotin-PEG4-alkyne thiolene (stsStep 2) after which a biotinylated pan-HLA antibody is immobilized on the micropillar surface (step 3) and cell lysate is loaded into the microchip (step 4). After adequate incubation time and washing steps, the HLA molecules are eluted by adding 7% acetic acid (step 5).

Figure 2

Properties of the HLA-I peptidomes data set obtained from the JY cell line. (A) Number of nonredundant peptides (unique peptides) eluted from 50 × 10⁶, 10 × 10⁶, and 1 × 10⁶ JY cells. (B) Overall peptide length distribution of the HLA peptides in the three data sets derived from the JY cell line. (C–E) Length distribution of HLA peptides is depicted as number of nonredundant (unique peptides, left y axis) and percentage of occurrence (right y axis) for 50 × 10⁶ (C), 10 × 10⁶ (D), and 1 × 10⁶ (E) cells.

Figure 3

Accurate analysis of HLA ligands isolated from the JY cell line. (A) The eluted 9mers were analyzed in regards to their binding affinity to HLA-A*02:01 and HLA-B*07:02. The binders (green dots) and nonbinders (black dots) were defined in the NetMHCpan 4.0 Server (applied rank 2%). (B) HLA-I consensus binding motifs. Gibbs clustering analysis was performed to define the consensus binding motifs among the eluted 9mers peptides. The reference motif is depicted in the upper right corner. The clusters with the optimal fitness (higher KLD values, orange star) are shown, and the sequence logo is represented with the number of HLA-I for each cluster.

Figure 4

In depth enrichment analysis of HLA-ligands source proteins and CD8+ T-cell based cytotoxic assay. (A) Gene ontology enrichment analysis of the HLA-ligands source proteins. The most overrepresented biological processes for 10 × 10⁶ cells are separately shown for HLA-A*02:01 and HLA-B*07:02 alleles (hypergeometric test padj <0.01). (B) Molecular Signature Database results are displayed. The source proteins analysis was performed against the hallmark data set and separately for HLA-A*02:01 and HLA-B*07:02 alleles.

Figure 5

(A) PBMCs from healthy donors were pulsed for 9 days with the indicated peptides, and at day 10, CD8+T cells were isolated and used in an in vitro killing assay at E/T 1:1. The time-response is showed after adding the effectors. (B) PBMCs from healthy donors were pulsed for 9 days with the candidate peptide and at day 10 CD8+T cells were isolated and used in an in vitro killing assay at E:T 1:1. The time-response is showed after adding the effectors. The data are shown as the mean ± SEM and the significance was assessed by 2-way ANOVA, ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. The results are plotted as bar graphs (n = 2–4).

Figure 6

Comparative analysis of the generated data sets from JY cell line. (A) The percentage of the shared 9mers has been calculated against a depository reference data set (pride ID PXD000394) derived from the JY cell line; the results are depicted as a bar plot, and the percentage of shared peptides is indicated in green. (B) The abundance of the source proteins is expressed in log₂ intensity, and the values are derived from a reference published proteomic analysis of the total JY cell lysate. The plot showed the comparison among the three data sets (50 × 10⁶ cells, 10 × 10⁶ cells, and 1 × 10⁶) generated through our microchip technology and the reference data set.

Figure 7

Comparative analysis between the standard method and PeptiCHIP technology. (A) Peptide length distribution is reported for the standard method (blue bars) and the microchip (green bars) for each number of cells (left, 1 × 10⁶ cells; right, 10 × 10⁶ cells). (B–E) The 9mers consensus binding motifs were deconvoluted by unsupervised Gibbs clustering analysis for both the standard method and the microchip and for each number of cells. The reference motif is shown in the upper right corner. The clusters with higher KLD values were chosen (orange star), and the sequence logo is reported. (F–I) The binding affinities to HLA-A*02:01 and HLA-B*07:02 were predicted for the eluted 9mers, and the percentages of binders and not binders are depicted as a part to the whole for both the standard method and the microchip and for both numbers of cells.

Figure 8

Microchip based platform reveals the immunopepetidomic profile in scarce tumor biopsies. (A) The weight of the samples before the processing, the total number, and the nonredundant (unique peptides) and the enrichment in 7–13mers specimens are summarized here. (B) The length distribution of the peptides in regards to their absolute number and the percentage are shown as bar plots.

Figure 9

Immunopeptidomic analysis of ccRCC and Bladder tumor patient derived organoids (PDO). (A) Number of nonredundant (unique peptides) detected in ccRCC and bladder PDOs. (B) The peptides length distribution is shown as the total number of nonredundant peptides (unique peptides, left y axis) and percentage of occurrence (right y axis) per each PDO (ccRCC, upper panel; bladder, lower panel).

Figure 10

Assessment of the immunopeptidomic profile in PDOs. (A) Gene ontology enrichment analysis. The most overrepresented biological processes for RCC (left panel) and bladder (right panel) PDOs are shown (hypergeometric test padj <0.01) (B) The source proteins expression is depicted as log₂ of the RNA level in healthy kidney tissue (black square) and in blood PBMCs (red circle). The 1st quartile is indicated as black and red dashed line, respectively, for the healthy kidney tissue and blood PBMCs. (C) PBMCs from healthy donors or (D) PBMCs from a patient were pulsed for 9 days with the indicated peptides, and at day 10 CD8+T cells were isolated and used in an in vitro killing assay at E/T 1:1. The time-response is shown after adding the effectors. The data are shown as the mean ± SEM, and the significance was assessed by 2-way ANOVA, ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. The results are plotted as bar graph (n = 2).