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. 2025 Jun 13:13:1575134.
doi: 10.3389/fcell.2025.1575134. eCollection 2025.

Hypoxia alters the response of ovarian cancer cells to the mitomycin C drug

Aleksandra Gawrylak  1   2 , Klaudia Brodaczewska  1 , Roksana Iwanicka-Nowicka  3   4 , Marta Koblowska  3   4 , Agnieszka Synowiec  1 , Lubomir Bodnar  5   6 , Cezary Szczylik  7 , Bogdan Lesyng  8 , Rafał Stec  9 , Claudine Kieda  1   10
Affiliations

Hypoxia alters the response of ovarian cancer cells to the mitomycin C drug

Aleksandra Gawrylak et al. Front Cell Dev Biol. .

Abstract

Introduction: Discrepancies between preclinical tests and clinical results raise serious concerns about the appropriateness of the current methodologies. In particular, cell biology approaches neglect fundamental physical parameters despite their relevance to in vivo conditions. Oxygen availability is critical for cell reactions; thus, the lack of consideration of hypoxia as the main regulator of the tumor microenvironment (TME) leads to misinterpreted data with consequences for translational applications. In this study, we show that mitomycin C (MMC), an antineoplastic antibiotic, is rarely used in ovarian cancer (OC) treatment despite its potential efficacy; we use MMC as an example of a treatment that warrants reevaluation under microenvironmental conditions, particularly during in vitro testing.

Methods: To evaluate the effects of MMC and oxygen tension (pO2) on OC cells (SKOV3), HTA 2.0 microarrays were used, which demonstrated that hypoxia and MMC induced transcriptomic changes in OC cells. Their combination particularly emphasized the effect of pO2 modification on MMC activity. The most significant findings were verified in three other OC cell lines, namely, TOV112D, ES-2, and A2780.

Results: Under normoxic conditions, MMC mostly affected several pathways associated with ribosome-related processes, whereas under hypoxic conditions, it induced modifications in the extracellular matrix (ECM). The most significantly upregulated gene in response to hypoxia-MMC treatment was MMP1, regulated by both MMC and hypoxia. Low pO2 levels during MMC treatment allowed the identification of important regulators, such as SPP1, and the corresponding processes, including cholesterol biosynthesis.

Conclusion: Hypoxia modulated the effects of MMC on OC cells and identified genes that may serve as promising targets to enhance the effectiveness of MMC treatment.

Keywords: differential gene expression; hypoxia; mitomycin c; ovarian cancer; pathway analysis; transcriptome.

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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. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

FIGURE 1
FIGURE 1
Influence of mitomycin C (MMC) on SKOV 3 cells under normoxic and hypoxic conditions. (A1) Cell size (FSC) and (A2) granularity (SSC) assessed by flow cytometry. (B) Quantification of number of SKOV3 cells. (C) Relative cytotoxicity of MMC assessed by the LDH assay. (D) Percentage of proliferative Ki67+ cells assessed by flow cytometry. (E) The cell cycle studied after propidium iodide (PI) incorporation and flow cytometry assessment: the percentages of cells among G0/G1, S, and G2/M phases of the cell cycle. (A) Detailed statistics description is provided in Supplementary Table S2.
FIGURE 2
FIGURE 2
Global gene expression in SKOV3 cells treated with mitomycin C (MMC) under normoxia and hypoxia conditions. (A) Principal component analysis (PCA). (B) Differentially expressed gene analysis in SKOV cells using TAC 4.0.2; fold change < -2 or >2; p < 0.05. (D) Venn diagram–representing the overlapping groups of transcripts identified in (B), red indicates different groups of genes mentioned in the article, black indicates the number of genes in a given group. N = 4. (D,E) The most significantly enriched Gene Ontologies (GO) in SKOV3 cells treated with MMC in hypoxia, based on molecular functions (MFs), biological processes (BPs), and cellular components (CCs). The enrichment score was calculated as −log (p-value). Fold change (FC) ≤ −2 and ≥2; p < 0.05; genes without Entrez Gene ID were excluded from the analysis. Analysis: (D) N-MMC vs N-C. (E) H-MMC vs. H-C.
FIGURE 3
FIGURE 3
Pathways altered in all DEGs identified in SKOV3 cells under the influence of hypoxia and mitomycin C (MMC) based on the KEGG database. (A) Effect of hypoxia (H-C vs N-C). (B) Effect of MMC in normoxia (N-MMC vs. N-C). (C) Effect of MMC in hypoxia (H-MMC vs. H-C). (D) Effect of pO2 on MMC treatment (H-MMC vs. N-MMC). Fold change (FC) ≥ 2; p < 0.05; genes without Entrez Gene ID were excluded from the analysis. (E) C-net plot of pathways/processes altered in SKOV3 cells treated with MMC in hypoxia (vs. N-MMC), based on the KEGG database. Fold change (FC) ≤ −2 and ≥2; p < 0.05; genes without Entrez Gene ID were excluded from the analysis.
FIGURE 4
FIGURE 4
Expression of VEGF on gene and protein levels in SKOV3 cells treated with mitomycin C (MMC) in normoxia and hypoxia. (A) The VEGF mRNA expression level was measured by RT-qPCR and normalized to PPIA and GUSB expressions and normoxia control as 1. (B) Level of VEGF secretion in the cell culture supernatant measured by ELISA; results were normalized to normoxia control set as 1. A detailed statistics description is provided in the Supplementary Table S2.
FIGURE 5
FIGURE 5
Expression of MMP1 on gene and protein levels upon treatment with mitomycin C (MMC) of SKOV3 cells in normoxia and hypoxia. MMP1 gene expression was measured using (A) HTA 2.0 microarrays and (B) RT-qPCR [normalized to PPIA and GUSB levels and normoxia control (NC) as 1]. (C) Immunoblot of MMP 1 protein (with vinculin as loading control). (D) Quantification of MMP1 protein levels by densitometry. (E) Secretion of pro-MMP1 protein levels measured by ELISA. (F) Secretion of total MMP1 protein levels measured by ELISA. (B,D) Results were normalized to normoxia control as 1. ****p < 0.0001, ***p < 0.001, **p < 0.01, and *p < 0.05; VIN, vinculin. A detailed statistics description is provided in the Supplementary Table S2.
FIGURE 6
FIGURE 6
Graphical summary of the influence of mitomycin C (MMC) and hypoxia on SKOV3 ovarian cancer cells, generated using IPA (Ingenuity Pathway) Core Analysis, which selects and connects significant entities based on their p < 0.05. The summary includes canonical pathways, upstream regulators, diseases, and biological functions. Orange indicates the activation of the entity, and blue indicates the inhibition of the entity. (A) Effect of hypoxia (H-C vs. N-C), (B) effect of MMC in normoxia (N-MMC vs. N-C), (C) effect of MMC in hypoxia (H-MMC vs. H-C), and (D) effect of pO2 on MMC treatment (H-MMC vs. N-MMC).
FIGURE 7
FIGURE 7
Ingenuity Pathway Analysis (IPA)-identified (A) key canonical enriched pathways. Y-axis represents the negative log of the p-value, indicating the significance of each canonical pathway. Bars are colored to indicate predicted pathway activity: orange for activation and blue for inhibition. (B) Upstream regulators that affected gene expression and effector pathways/processes when SKOV3 cells were treated with MMC in hypoxia (compared to N-MMC).
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