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. 2023 Nov 8:13:1252700.
doi: 10.3389/fonc.2023.1252700. eCollection 2023.

Tumor cell cytoplasmic metallothionein expression associates with differential tumor immunogenicity and prognostic outcome in high-grade serous ovarian carcinoma

Elena Mairinger #  1 , Michael Wessolly #  2 , Paul Buderath  2 , Sabrina Borchert  1 , Larissa Henrich  1 , Pawel Mach  2 , Julia Steinborn  1 , Rainer Kimming  2 , Bharat Jasani  3 , Kurt Werner Schmid  1 , Agnes Bankfalvi  1 , Fabian Dominik Mairinger  1
Affiliations

Tumor cell cytoplasmic metallothionein expression associates with differential tumor immunogenicity and prognostic outcome in high-grade serous ovarian carcinoma

Elena Mairinger et al. Front Oncol. .

Abstract

Background: The underlying mechanism of high T-cell presence as a favorable prognostic factor in high-grade serous ovarian carcinoma (HGSOC) is not yet understood. In addition to immune cells, various cofactors are essential for immune processes. One of those are metallothioneins (MTs), metal-binding proteins comprising various isoforms. MTs play a role in tumor development and drug resistance. Moreover, MTs influence inflammatory processes by regulating zinc homeostasis. In particular, T-cell function and polarization are particularly susceptible to changes in zinc status. The aim of the present study was to investigate a possible role of MT-mediated immune response and its association with prognostic outcome in ovarian cancer.

Methods: A retrospective study was conducted on a clinically well-characterized cohort of 24 patients with HGSOC treated at the University Hospital of Essen. Gene expression patterns for anti-cancer immunogenicity-related targets were performed using the NanoString nCounter platform for digital gene expression analysis with the appurtenant PanCancer Immune Profiling panel, consisting of 770 targets and 30 reference genes. Tumor-associated immunohistochemical MT protein expression was evaluated using a semi-quantitative four-tier Immunohistochemistry (IHC) scoring.

Results: MT immunoexpression was detected in 43% (10/23) of all HGSOC samples. MT immunoexpression levels showed a significant association to survival, leading to prolonged progression-free and overall survival in positively stained tumors. Furthermore, T-cell receptor signaling gene signature showed a strong activation in MT-positive tumors. Activated downstream signaling cascades resulting in elevated interferon-gamma expression with a shift in the balance between T helper cells (TH1 and TH2) could be observed in the MT-positive subgroup. In addition, a higher expression pattern of perforin and several granzymes could be detected, overall suggestive of acute, targeted anti-cancer immune response in MT-positive samples.

Conclusion: This is the first study combining broad, digital mRNA screening of anti-tumor immune response-associated genes and their relation to MT-I/II in ovarian cancer. MT overexpression is associated with molecular characteristics of an anti-cancer immune response and is a strong prognostic marker in ovarian HGSOC. The observed immune cell activation associated with tumor MT expression comprises but is not limited to T cells and natural killer cells.

Keywords: high-grade serous ovarian carcinoma; immune response; metallothionein; overall survival; zinc signaling.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart encompassing the methodology of the entire project including study design, immunohistochemistry, digital gene expression analysis, and statistical analysis.
Figure 2
Figure 2
Distribution and clinical impact of MT expression in the overall cohort. (A) The figure shows a bar plot of samples with and without MT immunoexpression. Around 60% of all samples do not show a detectable immunoexpression of MTs, whereas 40% show at least one positive-stained tumor cell. (B) The figure depicts a combined histogram with density plot. The x-axis shows the percentage of stained cells for each sample, and the y-axis shows the sample count with the given percentage of stained cells. In the majority of the samples, only a few cells are positively stained (up to 10%). Only a minor amount of tumors present up to one-fifth positively stained cells. (C) Influence of subcellular localization on staining intensity. If only nuclear expression of MTs is found, then the overall amount of positively stained cells remains below 5%. For cases with cytoplasmic localization of MTs, overall, a higher number of positive cells can be seen; however, the individual values spread over a broad range between 1% and 20%. If both the nuclear and cytoplasmic staining occur, the highest number of stained cells can be found (8%–10%). (D) Kaplan–Meier curve for overall survival in dependency of MT expression. Positively stained tumors show a significantly prolonged overall survival (p = 0.0084). The median survival rate increases from 14 months to 42 months, and the 3-year survival rate rises from 12.5% to 80.0%. (E) Recurrence-free survival in MT-positive versus MT-negative tumors. Similar to OS, the recurrence-free survival (RFS) increases significantly, if an MT expression can be detected. Median RFS increases from 8.5 months to 39.5 months with an increase in 3-year RFS rate from 7.1% up to 50.0%.
Figure 3
Figure 3
Immunohistochemical MT-I and MT-II expression [(A), no expression (0); (B), moderate to intermediate expression (2+); (C), high expression (3+)] and MT subcellular localization [(D), nuclear; (E), cytoplasmic; (F), nuclear and cytoplasmatic].
Figure 4
Figure 4
(A) Gene set enrichment analysis displaying correlations between MT-I/II abundance and the amount of gene expression in certain signaling pathways. Pathways linked to MT-I/II–negative tumor samples are displayed in blue, whereas pathways linked to MT-I/II-positive tumors are shown in yellow. (B) List including the statistical metrics of the enrichment analysis displayed in (A). (C) Enrichment plot describing the representation of genes linked to T-cell receptor signaling. Similar to other immune pathways ( Supplementary Figure 1 ), a negative enrichment score is shown, indicating a high expression in MT-I/II-positive vs. MT-I/II–negative samples. (D) KEGG pathway map displaying genes involved in T-cell receptor signaling. Pathway members highlighted in green show induced gene expression levels in tumor samples with detectable MT overexpression.
Figure 5
Figure 5
(A) Examples for the automatic software-based analysis of immune cell infiltration in our whole cohort of 23 samples separated into MTI/II low (upper two lines) and high (lower two lines) HGSOCs. Each first row represents a staining for CD8-positive T cells, whereas the second row represents a staining for CD4-positive T cells. Cell separation and counting via QuPath leads to blue-shaded negatively and red-shaded positively counted cells. High infiltration levels of T cells could only be observed for MT-I/II rich tumors. (B) Basic statistical analysis for infiltration levels with CD3-, CD8-, and CD4-positive cells in MT-I/II–positive and MT-I/II–negative tumors. The p-value was calculated by Fisher’s exact test because both variables display a double-dichotomous correlation. (C–E) Correlation between MT-I/II expression (negative and positive) and infiltration (cells/mm2) of CD3-(C), CD8- (D), and CD4-positive immune cells (E).
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