Molecular signatures associated with tumor-specific immune response in melanoma patients treated with dendritic cell-based immunotherapy

Tamara García-Salum, Andrea Villablanca, Franziska Matthäus, Andrés Tittarelli, Mauricio Baeza, Cristián Pereda, M Alejandra Gleisner, Fermín E González, Mercedes N López, Jörg D Hoheisel, Johannes Norgauer, Peter J Gebicke-Haerter, Flavio Salazar-Onfray, Tamara García-Salum, Andrea Villablanca, Franziska Matthäus, Andrés Tittarelli, Mauricio Baeza, Cristián Pereda, M Alejandra Gleisner, Fermín E González, Mercedes N López, Jörg D Hoheisel, Johannes Norgauer, Peter J Gebicke-Haerter, Flavio Salazar-Onfray

Abstract

Purpose: We previously showed that autologous dendritic cells (DCs) loaded with an allogeneic heat shock (HS)-conditioned melanoma cell-derived lysate, called TRIMEL, induce T-cell-mediated immune responses in stage IV melanoma patients. Importantly, a positive delayed-type hypersensitivity (DTH) reaction against TRIMEL after vaccination, correlated with patients prolonged survival. Furthermore, we observed that DTH reaction was associated with a differential response pattern reflected in the presence of distinct cell subpopulations in peripheral blood. Detected variations in patient responses encouraged molecular studies aimed to identify gene expression profiles induced after vaccination in treated patients, allowing the identification of new molecular predictive markers.

Methods: Gene expression patterns were analyzed by microarrays during vaccination, and some of them confirmed by quantitative real-time reverse transcriptase PCR (qRT-PCR) in the total leukocyte population of a representative group of responder and non-responder patients. New candidates for biomarkers with predictive value were identified using bioinformatics, molecular analysis, and flow cytometry.

Results: Seventeen genes overexpressed in responder patients after vaccination respect to non-responders were identified after a mathematical analysis, from which ten were linked to immune responses and five related to cell cycle control and signal transduction. In immunological responder patients, increased protein levels of the chemokine receptor CXCR4 and the Fc-receptor CD32 were observed on cell membranes of CD8+ T and B cells and the monocyte population, respectively, confirming gene expression results.

Conclusions: Our study contributes to finding new molecular markers associated with clinical outcome and better understanding of clinically relevant immunological responses induced by anti-tumor DC-vaccines.

Keywords: CD32; CXCR4; immunotherapy; melanoma; molecular signatures.

Conflict of interest statement

CONFLICTS OF INTEREST The authors declare that they have no conflicts of interest.

Figures

Figure 1. TRIMEL-loaded DCs-treated immunological responder patients…
Figure 1. TRIMEL-loaded DCs-treated immunological responder patients have a higher median survival than non-immunological responder patients
Post-TRIMEL-loaded DCs immunotherapy overall survival curves for immunological responder (DTH+: full line) and immunological non-responder (DTH-/NT: dash line) patients. *p < 0.05 **p < 0.01. NT: Not tested.
Figure 2. Differences in temporal gene expression…
Figure 2. Differences in temporal gene expression of potential molecular markers between clinical responder and non-responder patients
Vaccinated patients were reclassified according DTH reaction and overall survival as described in Material and methods. (A) Relative gene expression of genes CLEC2D, CXCR4, FCGR2A, GIT2, MS4A7, PRDM1, PRDX3, SDCBP, SPG21 and VNN2 were determined by microarrays. Black dots: Clinical responders (DTH+/long survivor patients); samples from 1st-4th vaccination (n = 5), samples from DTH evaluation (n = 6); red triangles: Non-responder patients (DTH− patients), samples from 1st vaccination (n = 3), 2nd vaccination (n = 4), 3rd vaccination (n = 1), 4th vaccination (n = 2) and DTH evaluation (n = 1). (B) Relative expression of genes CREB5, CSNK1A1, EIF4G2, LOC648210, STRN3, TROVE2 and unknown (probe ID 2120450) were determined by microarrays. Black dots: Clinical responder patients, samples from 1st to 4th vaccination (n = 5), DTH evaluation (n = 6); red triangles: Non-responder patients, samples from 1st vaccination (n = 3), 2nd vaccination (n = 4), 3rd vaccination (n = 1). 4th vaccination (n = 2) and DTH evaluation (n = 1). (C) Relative gene expression determined by qRT-PCR of genes CLEC2D, CXCR4, FCGR2A, MS4A7 and CSNK1A1. Black dots: Clinical responder patients, samples from 1st vaccination (n = 4–6), 2nd vaccination (n = 3–4), 3rd vaccination (n = 6), 4th vaccination (n = 5–7), and DTH evaluation (n = 7); red triangles: non-responder patients, samples from 1st vaccination (n = 2–3), 2nd vaccination (n = 4); 3rd vaccination (n = 1), 4th vaccination (n = 2) and DTH evaluation (n = 1). Fold changes relative to the respective reference sample are given. Each data dot represents one patient's sample, each line represents the mean of the data dots. Vaccination (vac.); evaluation (eval.); ID, identification number.
Figure 3. Theoretical network of genetic interactions…
Figure 3. Theoretical network of genetic interactions associated to DC vaccine-induced immune response
Fifteen genes significantly regulated during the vaccination period (large, blue circles) were subjected to analyses of direct genetic interactions using STRING and BioGrid platforms. Most interactions were unique for each gene, but a few appeared in two or more lists of the 15 genes attributing to them a connector function (yellow circles; the more of the 15 genes are connected by a connector gene, the larger its diameter) and hence giving rise to a molecular network. For instance, ubiquitin C (UBC) (the connector gene with the most connections) connects 9 out of the 15 genes. The combined STRING and BioGrid genes were entered into “genes.R” available in “R”, and further processed in “igraph”.
Figure 4. Increased CXCR4 surface expression on…
Figure 4. Increased CXCR4 surface expression on CD8+ T-cells and B-cells, and CD32 surface expression on monocyte populations in immunological responder compared to non-responder patients
(A, C) Cryopreserved PBMCs, obtained from healthy donors (HD; n = 4–5), immunological responder (n = 4–9) and non-responder patients (n = 7–10), at the beginning (pre-tx) and at the end (post-tx) of TRIMEL-loaded DCs immunization protocol, were analyzed for the CXCR4 (A) and CD32 (C) surface expression by flow cytometry. Each data point represents one patient sample. MFI: mean of fluorescence intensity. Mann-Whitney test; *p < 0.05 **p < 0.01. (B, D) Representative histograms compare the analysis of one healthy donor (HD), one responder and one non-responder patient to TRIMEL-loaded DCs immunotherapy. CD4+ T-cells: CD45+/CD3+/CD4+; CD8+ T-cells: CD3+/CD8+; B-cells: CD3–/CD19+; NK-cells: CD45+/CD16+/CD56+ and monocyte population: CD45+/CD14+. Black lines: immunological responder patients; red lines: non-responder patients; continuous lines: pre-tx; dashed lines: post-tx; fill curve: HD; tx, treatment.

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