Combination of a MIP3α-antigen fusion therapeutic DNA vaccine with treatments of IFNα and 5-Aza-2’Deoxycytidine enhances activated effector CD8+ T cells expressing CD11c in the B16F10 melanoma model

doi:10.21203/rs.3.rs-3243336/v2

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Combination of a MIP3α-antigen fusion therapeutic DNA vaccine with treatments of IFNα and 5-Aza-2’Deoxycytidine enhances activated effector CD8+ T cells expressing CD11c in the B16F10 melanoma model

https://doi.org/10.21203/rs.3.rs-3243336/v2

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Previous studies in the B16F10 mouse melanoma model have demonstrated that combining a DNA vaccine comprised of regions of gp100 and tyrosinase-related protein 2 fused to Macrophage-inflammatory protein 3-alpha (MIP3α) with recombinant Interferon alpha (IFN) and 5-Aza-2’-Deoxycytidine (5Aza) treatments resulted in significantly greater anti-tumor activity and immunogenicity in the tumor microenvironment (TME). This brief report details that the combination of vaccine with treatments IFN and 5Aza results in both the upregulation of genes expressing CD11c-interacting proteins and an increase in the TME of a distinct CD11c+ CD8+ T cell population. This cell population correlates with tumor size, is primarily comprised of effector or effector memory T cells, and has a more robust response to ex vivo stimulation as compared to CD11c- CD8+ T cells as measured by surface activation markers 4-1BB (CD137) and KLRG1 (Killer cell lectin-like receptor G1) and intracellular IFNγ production. In conclusion, this combination therapy results in greater presence of highly active effector CD8+ T-cells expressing CD11c in the TME that correlate with and are likely primary contributors to treatment efficacy.

MIP3α/CCL20

IFNα/Interferon alpha/Type I interferon

5-Aza-2’-Deoxycytidine/Decitabine/Dacogen

CD11c

Tumor microenvironment

CD11c+ CD8+ T cell

DNA Therapeutic Cancer Vaccine

Cancer therapeutic vaccines combined with immunotherapies and chemotherapies have garnered interest due to their potential synergistic effects[1]. Previous preclinical studies have demonstrated that DNA vaccines comprising melanoma antigen(s) fused to MIP3α delayed tumor growth, prolonged survival, and enhanced T-cell immunity in the B16F10 melanoma model[2–4]. MIP3α vaccine fusions have been shown to target antigen(s) to immature dendritic cells (iDC), with presentation through MHC class I and II[5, 6]. Here, clinically-relevant antigens gp100_25-235 and tyrosinase-related protein 2 (Trp2_170-269)[7] are fused to MIP3α. When MIP3α-Gp100-Trp2 vaccine adjuvanted with CpG type C (henceforth referred to as “vaccine”) was combined with the drug treatments low-dose 5Aza-2’Deoxycytidine (5Aza) and a series of high and low doses of recombinant IFNα (IFN) (Fig. 1A), significantly greater anti-tumor activity was achieved, including increased dendritic cell (DC) and CD8+ T-cell infiltration into the tumor microenvironment (TME)[3, 8].

CD11c is a type I transmembrane protein forming part of the complement receptor 4 and has been shown to play a role in phagocytosis, cell migration, cytokine production, and T-cell proliferation. A subset of CD8+ T cells expressing CD11c+ have been described in various tissues, infections, and cancers[9–11] with the ability to become suppressor or effector cells[10, 12, 13]. The current study shows that levels of CD8+ T cells expressing CD11c are increased in the TME with combination treatment and are correlated with tumor size in vaccinated groups. To our knowledge, this study is the first to show the presence of CD8+CD11c+ T cells in a tumor-associated-antigen based therapeutic cancer vaccine system, and the data suggest that these cells are in higher numbers, are more robust, and are more potent with the combination treatments compared to vaccine alone or treatments alone. These cells are therefore likely to be critical components in the tumor suppression observed with the therapeutic regimen we have employed against the B16F10 melanoma.

Animals

6–12-week-old female C57BL/6 (Charles River, Wilmington, MA) mice were challenged with a lethal dose of B16F10 melanoma (5×10⁴ cells, >95% viability) administered intradermally on the mouse flank on day 0 of therapy[2, 3, 8]. Tumor size was recorded by calipers every 1–3 days as square mm (L × W). Mice were monitored in accordance with IACUC protocols and were removed from the study once tumo diameterr>1cm or if mice showed signs of distress.

Vaccines and Therapies

Vaccine antigen is the MIP-3α-Gp100-Trp2 (tyrosinase-related protein 2) DNA construct in the pCMVe mammalian expression plasmid[8]. Therapy including vaccine, recombinant mouse interferon alpha-A (IFNα, R&D Systems, Inc. Minneapolis, MN), and InSolution™ 5 Aza 2′-deoxycytidine (5Aza, CalBiochem®, MilliporeSigma, Burlington, MA) has been detailed in prior publications[8] and is outlined in Figure 1A.

Flow Cytometry

Tumor cell and splenic suspensions were prepared as previously described [2, 3]. The Attune™ NxT (Thermo Fisher Scientific, Waltham, MA) flow cytometer was utilized. Data were analyzed by FlowJo Software (FlowJo, LLC Ashland, OR) or Attune NxT Software v3.2.1. Tumors smaller than 25mm² were not analyzed. Supplemental Figure 1 outlines gating structure and stimulation procedures[3]. Gates were formulated using full-minus-one (FMO) staining controls.

Immunofluorescence Staining

Tumor tissues were collected at the time of harvest and were immediately fixed in 10% neutral-buffered formalin for 48 hours and were then processed, embedded into paraffin (FFPE), and cut onto slides. The slides were blocked, stained with αCD3 antibody, washed, stained with AF488 secondary antibody, washed, and repeated for αCD11c antibody and AF647 secondary. The nuclei were counterstained with DAPI and mounted. Three slides were blindly selected from each group for analysis. Images were acquired across ten random fields per slide under the 40x objective using a Leica THUNDER computational clearing widefield microscope through LAS X software (Leica Microsystems, Wetzlar, Germany).

Database Collection and Statistics

The correlations between CD11c (ITGAX) expression and infiltrating immune cell subsets in the tumor microenvironment were assessed through TIMER 2.0 web server (http://timer.cistrome.org/) and the xCell algorithm. Purity-adjusted Spearman's rho and statistical significance were used to evaluate correlations. Datasets were tested for normality by D'Agostino & Pearson test and followed by by one-way ANOVA with Tukey’s or Dunn’s multiple comparison test for multiple groups, or by unpaired Student’s T test or Mann-Whitney tests for two groups, Scatter plots were analyzed by linear regression with Pearson correlation coefficient test. Grouped experiments were analyzed by 2-way ANOVA with Sidak’s multiple comparison test. Sample sizes are defined in the figure legends. GraphPad Prism™ 10 (GraphPad Software, Inc. San Diego, CA) was utilized for statistical analyses and figure creation. Error bars represent the estimation of the standard error of the mean and midlines the group mean. α≤0.05

CD8+11c+ T cells in the TME

In our model combining vaccine with IFN and 5Aza (Fig. 1A), the CD8+CD11c+ T-cell population was significantly higher following combination therapy vs. vaccine alone (p=0.0271) or IFN+5Aza (p=0.0007) (Fig. 1B). Of note, when stratified across groups, the presence of the CD11c+ CD8+ T-cell subpopulation was also correlated with tumor size in vaccinated groups, whereas CD11c- CD8+ T cell numbers were not correlated (Fig. 1C-D). Complementing the flow cytometry data, the presence and distribution of T cells in the intratumoral areas were determined by immunofluorescence microscopy (Fig. 1E). A significantly higher number of CD11c+ T cells were observed in the group that received combination therapy as compared with IFN+5Aza (P=0.0118) or vaccine alone (P=0.0234) (Fig. 1F). The relationship between CD11c (ITGAX) expression and CD8+ T cell infiltration was further explored by analyzing publicly available datasets of melanoma patients (Fig. 1G). The results suggest a significant positive correlation between CD11c expression and the overall infiltration level of CD8+ T cells (rho= 0.23, P= 4.03e-08).

Memory subtyping of CD8+11c+ T cells in the TME

The overall phenotype of CD3+CD8+CD11c+ cells infiltrating into the TME was explored, independent of treatment group. CD3+CD8+CD11c+ cells were categorized into three groups based on CD44 and CD62L expression: CD62L+CD44+ central memory (Tcm); CD62L-CD44+ effector and effector memory (Teff/em); and CD62L+CD44- naive (Tnaive). CD8+CD11c+ cells had a significantly greater proportion of Teff/em cells compared to their CD11c- counterparts (p=0.01) and significantly smaller proportions of Tnaive (p<0.001) and Tcm (p=0.001) cells (Fig. 2A). Infiltration scores from publicly available human datasets also show that CD11c is positively correlated with the infiltration levels of CD8+ T effector memory cell subtypes (rho= 0.178, P= 1.34e-04), but not CD8+ naïve T cells (rho= 0.017, P= 0.723) (Fig. 2B). Surprisingly, a positive correlation is also observed between CD11c and infiltrating CD8+ central memory T cells (rho= 0.337, P= 1.26e-13) (Fig. 2B), which differs from our mouse model data (Fig. 2A).

Activation Markers of CD8+11c+ T cells in the Spleen

Cryopreserved splenocytes were analyzed to further assess the subset of CD11c+ CD8+ T cells for markers of effector function and activation: 4-1BB, Killer cell lectin-like receptor G1 (KLRG1), and IFNγ. Following ex-vivo stimulation with vaccine peptides, we show that co-expression of KLRG1 and 4-1BB was significantly higher in CD8+CD11c+ T cells (p<0.001) compared to CD11c– cells (Fig.2C). Further, when stratified by treatment group, expression of 41BB and KLRG1 on the surface of CD8+CD11c+ T cells was increased significantly following combination therapy relative to treatment with IFN+5Aza (p=0.0020) or vaccine alone (p=0.0250) (Fig. 2D). Using intracellular staining methods, IFNγ expression was greater in the combination group compared to the IFN+5Aza group (p= 0.0393) and the vaccine group (p= 0.0426) (Fig. 2E). Additionally, after stratifying the CD8+ T cells by CD11c expression, the CD11c+ population carries the phenotype of higher cytokine production in the combination group compared to IFNα+5Aza (p=0.0110) and vaccine (p= 0.0319) (Fig. 2F). Moreover, the CD11c+ cells had a significantly greater proportion of cells expressing IFNγ in the combination group compared to their CD11c- counterparts (p=0.0019) (Fig. 2F).

The current study provides evidence that CD8+CD11c+ T cells are increased with combination therapy, are correlated with tumor size (Fig. 1), and express more markers associated with activation and effector function (Fig. 2). 4-1BB is hypothesized to be a necessary costimulatory marker for CD8+CD11c+ T cells and is known to promote T-cell survival and enhance expression of cytokines such as IFNγ[14]. KLRG1 is induced on highly cytolytic, short-lived effector CD8+ T cells and is hypothesized to play a role in CD8+CD11c+ T-cell activity [15]. Interestingly, the majority of the IFNγ production induced by our vaccination protocol is attributable to the CD8+CD11c+ and not the CD8+CD11c- T-cell population (Fig. 2F). Some studies have pointed to stronger regulatory activity of this cell poopulation [10], but others have shown, similar to results here, that CD8+CD11c+ T cells aid in successful antitumoral responses via enhanced effector functions [9], including direct anti-tumor cytotoxicity[13]. Our studies have identified an immunization protocol that is particularly effective in activating this T cell population.

Analysis of human melanoma trials from publicly available databases show that intratumoral CD11c expression correlates with increased CD8+ T-cell infiltration (Fig. 1F), especially effector/memory subtypes (Fig. 2B), and that patients with more expression have improved survival outcomes (Supp Fig. 3) and better responses to immune checkpoint inhibitor therapy (Supp Fig. 4). We hypothesize that the stronger Tcm correlation in patients compared to our results in the mouse model may be attributable to the more prolonged time frame of melanoma persistence in the clinical setting. Importantly, clinical data supports the interaction of CD11c with CD8+ T-cells and with improved outcomes in melanoma.

Our results show that vaccine-induced, activated, IFNγ-secreting, effector/memory CD8+CD11c+ T cells significantly correlate to the antitumoral effect elicited by our combination therapy and are dependent on the combination of vaccine and drug treatments, as removing either arm limits the induction of these cells. These results combined with the literature [9, 13–15] suggest that the vaccine-induced CD8+CD11c+ T cells are primary effectors of the anti-tumor immune response. Future studies will further delineate whether these T-cells 1) are relevant to other tumor models; 2) traffic into the tumor or develop at the site 3) vary in number and potency over time; 4) interact with other cells in the tumor; and 5) have direct anti-tumor cytotoxicity.

MIP3α: Macrophage inflammatory protein 3-alpha (aka CCL20)
IFN: Interferon Alpha
5Aza: 5’-Aza-2’-deoxycytidine
TME: Tumor Microenvironment
iDC: immature dendritic cell
Trp2: Tyrosinase-related protein 2
Tcm and Tem: T cell central and effector memory, respectively
KLRG1: Killer cell lectin-like receptor G1

Acknowledgments

We would like to acknowledge the staff at JHU Research Animal Resources for their assistance with animal care. The Attune Flow Cytometer was provided and supported by the Johns Hopkins Malaria Research Institute and the Department of Molecular Microbiology and Immunology (MMI). We thank Anne Jedlicka and Amanda Dziedzic in the JHSPH Genomic Analysis and Sequencing Core and Dr. Prakash Srinivasan (MMI) for core facility management, technological expertise, and instrument support. We also thank the scientists at the SKCCC Oncology Tissue Services core facility, with funding from grant number P30 CA006973. This work was supported by NIH grants R01AI148710 to PK and RM and K24AI143447 to PK as well as by discretionary funds available to RM.

Competing Interests: Authors RM and JG are inventors on patent 11419928 for the vaccine that has been issued to Johns Hopkins University. The remaining authors declare that the research was conducted in the absence of any further commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest.

Author Contributions: Authors KF and JZ equally contributed to the design and implementation of the studies as well as the writing of the manuscript and thus share first authorship. KF performed initial studies and wrote the initial draft. JZ performed studies included in the revision and revised the manuscript. AS performed some of the original studies that led to the initial observations. AS, YH, AK, SA, and SK assisted with assays, animal experiments, and tissue processing. PK contributed to the conception and design of the experiments. JG and RM contributed equally to the conception and design of the experiments as well as the writing of the manuscript and revision, and thus share last authorship. All authors contributed to the article and approved the submitted version.

Data Availability: Datasets utilized in the study are supplied in the Supplemental Data File. Further information is available by the corresponding authors upon reasonable request.

Ethical Approval: The animal protocols were reviewed and approved by the IACUC of the Johns Hopkins University under Protocols #MO16H147 and MO19H139.

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The authors declare potential competing interests as follows: Authors RM and JG are inventors on patent 11419928 for the vaccine that has been issued to Johns Hopkins University. The remaining authors declare that the research was conducted in the absence of any further commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest.

FesslerGordySupplementaryMethods.docx
Supplementary Methods: More experimental details and methodology, including methods of supplementary materials.
SupTable080724.tiff
Supplementary Table: Flow cytometry antibody information and panel constructions
S1080724.tiff
Supplementary Figure 1: Flow cytometry gating structure and stimulation protocols for the datasets. Cells were gated by FSCxSSC lymphocytes, single cells, and live cells followed by positivity for CD3, CD8, and CD11c. The population positive for all three were further analyzed by CD62L and CD44 in tumor suspensions and for activation markers (41BB, KLRG1, IFNγ) in splenocytes. Splenocytes were stimulated using a cocktail of gp100_25-33, Trp2_180-188, costimulatory antibodies, and cell transport inhibitor for 5 hours with or without cell transport inhibitor. Cell counts were normalized and represented as counts per 100,000 viable, single, lymphocytes.
S2080724.tiff
Supplementary Figure 2: Negative and autofluorescence controls for immunofluorescence staining of T cells and CD11c+ cells. Cells were stained by antibodies to CD3 (green) or CD11c (red) with both secondary antibodies and DAPI (cyan). x400 total magnification. NG: negative controls
S34080724.tiff
Supplementary Figure 3: Kaplan–Meier analysis of the relationship between CD11c (ITGAX) expression and OS in SKCM. Data from TCGA-SKCM database, with sample size and statistics on the graph. Dotted lines represent 95% CI of survival curves. Supplementary Figure 4: The difference in CD11c (ITGAX) expression levels between responders and non-responders of (A) anti-PD-1 and (B) anti-CTLA-4 therapy. Data were obtained from Kovács et al. (2023) (Supp. Ref [1]), including samples derived from 10 independent melanoma datasets (n=570, 345 non-responders and 225 responders). (**** P< 0.0001)

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Combination of a MIP3α-antigen fusion therapeutic DNA vaccine with treatments of IFNα and 5-Aza-2’Deoxycytidine enhances activated effector CD8+ T cells expressing CD11c in the B16F10 melanoma model

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Abstract

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Materials and Methods

Results

Discussion

Abbreviations

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References

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