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. 2024 Mar 1;14(1):5109.
doi: 10.1038/s41598-024-55593-6.

Reversing immunosuppression in the tumor microenvironment of fibrolamellar carcinoma via PD-1 and IL-10 blockade

Affiliations

Reversing immunosuppression in the tumor microenvironment of fibrolamellar carcinoma via PD-1 and IL-10 blockade

S K Daniel et al. Sci Rep. .

Abstract

Fibrolamellar carcinoma (FLC) is a rare liver tumor driven by the DNAJ-PKAc fusion protein that affects healthy young patients. Little is known about the immune response to FLC, limiting rational design of immunotherapy. Multiplex immunohistochemistry and gene expression profiling were performed to characterize the FLC tumor immune microenvironment and adjacent non-tumor liver (NTL). Flow cytometry and T cell receptor (TCR) sequencing were performed to determine the phenotype of tumor-infiltrating immune cells and the extent of T cell clonal expansion. Fresh human FLC tumor slice cultures (TSCs) were treated with antibodies blocking programmed cell death protein-1 (PD-1) and interleukin-10 (IL-10), with results measured by cleaved caspase-3 immunohistochemistry. Immune cells were concentrated in fibrous stromal bands, rather than in the carcinoma cell compartment. In FLC, T cells demonstrated decreased activation and regulatory T cells in FLC had more frequent expression of PD-1 and CTLA-4 than in NTL. Furthermore, T cells had relatively low levels of clonal expansion despite high TCR conservation across individuals. Combination PD-1 and IL-10 blockade signficantly increased cell death in human FLC TSCs. Immunosuppresion in the FLC tumor microenvironment is characterized by T cell exclusion and exhaustion, which may be reversible with combination immunotherapy.

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Conflict of interest statement

VGP is a member of the scientific advisory board for TriSalus Life Sciences. He served as a consultant for Merck & Company in 2018, GlaxoSmithKline in 2019, Imvax in 2019, Takeda in 2020, Umoja and Sensei in 2022. He has previously had research funding from AstraZeneca, Ipsen, Merck, NGM, and OncoResponse. No other disclosures. All other authors has no competing interest.

Figures

Figure 1
Figure 1
Using multiplex immunohistochemistry and RNA expression to define the immune landscape of FLC. (A) Representative mIHC 20 × field. (B) Overall average percentage of cell types in the FLC tumor compartment. (C) CD8 + T cell, CD4 + T cell, Regulatory T cell, and macrophage densities in adjacent NTL, interface, and tumor compartments in FLC, Mann–Whitney U test. (D) Ratio of CD8 + T cell: Regulatory T cell densities in adjacent NTL, interface, and tumor compartments in FLC, Mann–Whitney U test. (E) Paired CD8 + T cell, CD4 + T cell, Regulatory T cell, and macrophage densities in the stroma and carcinoma compartments of FLC tumor samples (5 patients, 9 slides), Wilcoxon matched-pairs signed rank test. (F) NanoString RNA expression CD8 T cell score comparing FLC NTL and tumor compartments to HCC NTL and tumor compartments, Mann–Whitney U test (G) NanoString RNA expression T cell function, chemokine, and cytokine scores of FLC NTL vs. tumor, Mann–Whitney U test.
Figure 2
Figure 2
Immune profiles in the tumor microenvironment of fibrolamellar carcinoma and NTL. (A) UMAP displaying myeloid-centered panel flow cytometry analysis of live CD45+ cells from NTL (left) and FLC (right) of patient 14. Each color represents a different immune population. (B) Frequency of CD45+ among live cells in tumor and NTL. (C) Frequency of myeloid populations among CD45+ cells in tumor and NTL. (D) Frequency of innate lymphocyte populations among CD45+ cells in tumor and NTL. (E) Frequency of lymphocyte populations among CD45+ cells in tumor and NTL. (F) Ratio of CD8+ cells to CD4+ and Treg cells in tumor and NTL; All paired T-test, parametric.
Figure 3
Figure 3
Characterization of T cell subsets and their PD-1 and CTLA-4 expression in FLC and NTL. (A) CD4 T cell subsets in NTL (left) and FLC (right). (Tnaive = CD45RA+CCR7+, Tcm = CD45RA-CCR7+, Teff = CD45RA+, CCR7-, Tem = CD45RA-CCR7-) (B) CD8 T cell subsets in NTL (left) and FLC (right). (C) and (D) PD-1 and CTLA-4 expression by conventional CD4 T cells, regulatory CD4 T cells and CD8 T cells in NTL and FLC; All paired T test, parametric.
Figure 4
Figure 4
T cell receptor (TCR) sequencing demonstrates low clonality but increased repertoire conservation. (A) Clone size distribution for FLC primary tumor and NTL samples down sampled to 20,000 unique CDR3ß amino acid sequence clonotypes. NTL appear to be more frequently expanded, with 3 NTL clones seen more than 100 times. (B) Clonality, with lower values corresponding to more polyclonal samples, demonstrates that FLC primary tumor samples are less expanded in 3 of 4 paired samples. While NTL samples tended towards higher clonality, this effect was not significant in our limited sample size (n/s- not significant by paired t test). (C) Morisita’s overlap index (MOI), a measure of repertoire overlap with higher values directly corresponding to a larger proportion of shared sequences between two samples, was calculated in a pairwise fashion for all NTL or FLC samples. FLC primary tumors samples more often shared TCR clonotypes across individuals than NTL samples (p < 0.03 by paired t-test). (D) and (E) FLC primary tumor samples had the lowest clonality but highest MOI when compared with melanoma (ML), pancreatic adenocarcinoma (PDA), colorectal adenocarcinoma (CRC), breast carcinoma (BRCA), and ovarian carcinoma (OV) samples downloaded from the immuneACCESS database27–33. A similar pattern of low clonality but high overlap between individuals was also seen for Merkel cell carcinoma (MC).
Figure 5
Figure 5
Tumor slice culture treatment with anti-PD-1 and anti-IL-10. (A) Representative 20 × fields of tumor slices from patient 10 stained for cleaved-Caspase-3 (cC3) after treatment with IgG mAb control, anti-PD-1 mAb, anti-IL-10 mAb, and anti-PD-1 mAb + anti-IL-10 mAb. (B) Average % cC3 raw positivity by treatment group for all patients combined. Each circle represents the difference compared to control in mean % cC3 + cells of three slice replicates per treatment group for a unique tumor (n = 5 for all except the aPD-1 and aIL-10 group where n = 4). The lines connect mean % cC3 + for each patient. Mann–Whitney U test.

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