A transcriptional network underlying migratory cellular states and reduced 5‑ALA‑based photodynamic detectability in glioblastoma 

Introduction

Glioblastoma (GBM) is an aggressive primary brain tumor characterized by diffuse infiltration and inevitable recurrence, despite multimodal therapy comprising surgical resection, radiotherapy, and temozolomide chemotherapy (1,2). The extent of resection is among the strongest prognostic factors for GBM. However, achieving maximal and safe resection is technically challenging because tumor cells often extend beyond radiographically apparent margins and intermingle with eloquent brain tissue (3-7).

To enhance intraoperative visualization of tumor tissue, photodynamic detection (PDD) with 5-aminolevulinic acid (5-ALA) has been widely adopted (8-10). Following systemic administration, 5-ALA is metabolized to protoporphyrin IX (PpIX), which preferentially accumulates in many GBM cells and emits red fluorescence under violet-blue excitation, thus enabling real-time guidance for resection (8,11,12). Randomized and observational studies have demonstrated that 5-ALA-guided surgery increases the rate of complete resection and improves short-term outcomes compared to white-light resection alone (11,13). Nevertheless, fluorescence-negative tumor foci do occur, and residual disease is frequently found in peritumoral and infiltrative regions, even after PDD-assisted resections, underscoring the biological heterogeneity in PpIX accumulation and diagnostic evasion during surgery (14-17).

Among the potential determinants of PDD visibility, two biological features may be relevant to surgical failure: i) cellular motility or migration, which drives dissemination along white matter tracts and vascular niches, leading to non-contiguous microscopic disease; and ii) metabolic programs controlling PpIX biosynthesis, export, and degradation, which modulate the fluorescence yield upon 5-ALA exposure (18-21). Previous studies suggested that subpopulations with stem-like or stress-adapted traits exhibit altered porphyrin metabolism and reduced PpIX fluorescence, potentially facilitating escape from intraoperative detection and subsequent persistence after resection (12,14,22). However, whether the migratory capacity and PDD visibility are coupled at the level of shared molecular programs has not yet been systematically evaluated using patient-derived GBM models.

Glioblastoma progression and spatial dissemination are critically shaped by the tumor microenvironment, which provides structural, metabolic, and paracrine support for tumor cell migration and survival (23-26). Hypoxic gradients, perivascular niches, extracellular matrix remodeling, and cytokine-mediated signaling have been shown to promote mesenchymal-like transcriptional programs associated with enhanced motility, metabolic plasticity, and therapeutic resistance (23-25,27). Although GBM arises from non-epithelial tissue, tumor cells frequently acquire migration-associated cellular states that share features with epithelial-mesenchymal transition, including cytoskeletal reorganization and altered adhesion dynamics, without undergoing classical epithelial marker conversion (27,28). These findings indicate that the migratory capacity reflects the integration of microenvironmental signals into coordinated transcriptional programs that support tumor progression and dissemination.

Here, using six patient-derived GBM cell lines (KBT#12137, KBT#10135, KBT#10170, PDM19, PDM22, and PDM123), we quantitatively assessed cellular migratory capacity and 5-ALA-induced PpIX accumulation and tested their relationship. We performed transcriptomic profiling to identify the gene expression signatures associated with the combined phenotype. Our analyses revealed a positive correlation, indicating that cells with higher migratory potential displayed lower PpIX accumulation and, therefore, reduced PDD visibility. Transcriptome-wide comparisons highlighted the enrichment of pathways related to cytoskeletal regulation, heme/porphyrin metabolism, and transporter activity associated with this phenotype.

Collectively, these findings support a functional link between migratory capacity and intraoperative diagnostic evasion of GBM. From a translational perspective, the results identify candidate molecular markers that may predict incomplete resection and recurrence risk and suggest testable strategies to enhance PDD visibility, such as modulation of heme biosynthesis and transport, or to combine PDD-guided resection with adjunctive photodynamic therapy in molecularly defined settings (29,30). This study provides a compact and mechanistically informed foundation for future validation and intervention studies.

Materials and methods

Patient-derived GBM cell culture and reagents

Six patient-derived glioblastoma (GBM) cell lines (KBT#12137, KBT#10135, KBT#10170, PDM19, PDM22, and PDM123) were kindly provided by Dr. Takuichiro Hide (Department of Neurosurgery, Kitasato University School of Medicine, Kanagawa, Japan). All cell lines were established from primary GBM tissues using protocols approved by the Institutional Ethics Committee, and informed consent was obtained from all patients prior to tissue collection.

Primary GBM tissues obtained by surgical resection were mechanically minced and enzymatically dissociated into single-cell suspensions. The cell suspensions were filtered through a 70-µm cell strainer to remove debris and plated under serum-free conditions to promote sphere formation. Under these conditions, the cells formed free-floating neurospheres with a spherical morphology and well-defined borders, consistent with previously described patient-derived GBM neurosphere cultures.

Cells were maintained as neurospheres in serum-free Dulbecco's modified Eagle's medium/Nutrient Mixture F-12 (DMEM/F12; Gibco, Massachusetts, USA; Cat. No. 21331020) supplemented with 20 ng/ml human epidermal growth factor (EGF; PeproTech, USA; Cat. No. AF-100-15-500UG), 20 ng/ml human basic fibroblast growth factor (bFGF; Oriental Yeast Co., Ltd., Japan; Cat. No. 47079000), 20 ng/ml leukemia inhibitory factor (LIF; Oriental Yeast; Cat. No. 47076000), 0.5x N2 supplement (Thermo Fisher Scientific, USA; Cat. No. 17502048), 0.5x B27 supplement (Thermo Fisher Scientific; Cat. No. 17504044), 1x GlutaMAX (Thermo Fisher Scientific; Cat. No. 35050061), 1x penicillin-streptomycin (Thermo Fisher Scientific; Cat. No. 15140122), 5 µg/ml heparin (Sigma-Aldrich, Japan; Cat. No. H3149-10KU), and 10 ng/ml insulin (Sigma-Aldrich, Japan; Cat. No. I6634-50MG). Cultures were incubated in a humidified atmosphere with 5% CO2 at 37˚C and passaged every 7-10 days by gentle mechanical dissociation. The 5-aminolevulinic acid (5-ALA) hydrochloride was purchased from Cosmo Oil Co., Ltd. (Tokyo, Japan; Cat. No. AL-00-1).

Detection of PpIX fluorescence by flow cytometry and microscopy

To assess the cellular accumulation of PpIX following 5-ALA exposure, patient-derived cells were dissociated into single cells and seeded at a density of 5x104 cells/ml. The cells were then incubated with 1 mM of 5-ALA for 4 h at 37˚C under 5% CO2. After incubation, PpIX fluorescence was analyzed by flow cytometry (FACS Aria II, BD Biosciences, USA). Fluorescence was excited with a 488-nm laser and detected using a 660/20-nm band-pass filter. The data were processed using FlowJo software (v7.6.5; TOMY Digital Biology, Japan).

For microscopic observation, PpIX fluorescence was visualized using a fluorescence microscope (Bio-Revo BZ-9000, Keyence, Japan) equipped with a QD625 filter cube (Olympus, Japan). At least three independent experiments were performed for each condition, and representative results are shown.

Transwell migration assay for selection of migratory and non-migratory populations

Cell motility was evaluated using 24-well Transwell chambers with 8-µm pore polycarbonate membranes (Corning, #3422). Single-cell suspensions (2x105 cells/100 µl) in serum-free DMEM/F12 were placed into the upper chamber, and 600 µl of complete sphere medium was added to the lower chamber as a chemoattractant. After 72 h incubation at 37˚C, non-migratory cells remaining on the upper surface were collected by gentle trypsinization, while migratory cells that had traversed the membrane were recovered from the lower chamber.

To ensure reproducibility, migration assays were performed in triplicate using independent cell preparations. Both fractions were treated with 5-ALA, as described above, to assess the relationship between migratory capacity and PpIX accumulation. The combination of migration status (migratory vs. non-migratory) and fluorescence phenotype (PpIX+ vs. PpIX-) yielded four distinct subpopulations, which were used for downstream transcriptomic analysis.

RNA extraction and cDNA microarray analysis

Total RNA was extracted from the four subpopulations described above (migratory PpIX+, migratory PpIX-, non-migratory PpIX+, and non-migratory PpIX-) using the RNeasy Plus Micro Kit (Qiagen, #74034) according to the manufacturer's protocol. RNA integrity was assessed using a Bioanalyzer (Agilent Technologies), and only samples with an RNA integrity number (RIN) >9.0 were used. For transcriptome profiling, genome-wide cDNA microarray analysis was outsourced to the Chemicals Evaluation and Research Institute (CERI, Tokyo, Japan) and performed using the Agilent Human Whole Genome Oligo Microarray platform (4x44 K, G4112F). Differentially expressed genes (DEGs) were defined as those showing a fold-change greater than 2 and a false discovery rate (FDR) <0.05. Data normalization and statistical analyses were conducted using the GeneSpring GX software (Agilent Technologies).

Gene set enrichment analysis (GSEA)

To elucidate biological pathways associated with PpIX detection resistance and cell motility, DEGs identified in microarray data were subjected to GSEA (31). Analyses were performed using the fgsea R package (v1.26.0; Bioconductor) with Molecular Signatures Database Hallmark and Gene Ontology gene sets (32,33). Genes were ranked according to the log2 fold change between groups, and enrichment scores were calculated using 10,000 permutations. Significantly enriched pathways were defined by a FDR<0.05. Functional categories related to cytoskeleton regulation, heme metabolism, and membrane transport are highlighted.

The Cancer Genome Atlas (TCGA) data analysis

Public transcriptomic data of patients with GBM (n=525) were obtained from TCGA (TCGA_GBM; HG-U133A platform) using the GlioVis portal (https://gliovis.bioinfo.cnio.es/) (34).

Statistical analysis

All data are expressed as the mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student's t-test, and correlations were analyzed using Pearson's correlation coefficient. Survival differences in TCGA data were evaluated using Kaplan-Meier survival analysis with log-rank and Gehan-Breslow-Wilcoxon tests. A P-value <0.05 was considered to indicate a statistically significant difference.

Results

Migratory capacity inversely correlates with 5-ALA-induced PpIX accumulation in patient-derived GBM cells

To assess whether migratory potential influences intraoperative detectability in GBM, we examined the relationship between cell motility and 5-ALA-induced PpIX fluorescence in six patient-derived GBM cell lines (KBT#10135, KBT#12137, KBT#10170, PDM19, PDM22, and PDM123). Flow cytometric analysis of the recurrent GBM cell line PDM123 revealed heterogeneous PpIX fluorescence with a distinct population lacking detectable signals (Fig. 1A). Across the six lines, the proportion of PpIX-negative cells varied substantially, with the primary line KBT#12137 showing the highest PpIX accumulation and the recurrent line PDM123 showing the lowest (approximately 70% PpIX-negative cells) (Fig. 1A and B). Although the recurrent lines tended to exhibit weaker fluorescence than the primary lines, the difference between the two groups was statistically significant (P<0.05; two-tailed t-test, n=3 lines per group). Transwell migration assays demonstrated that recurrent GBM cell lines exhibited significantly higher migratory activity than primary cell lines (P<0.05; two-tailed t-test, n=3 lines per group) (Fig. 1C). When the proportion of PpIX-negative cells was plotted against the migratory index [defined as the migration rate (%)=(lower-/upper-chamber cell counts) x100], positive correlations were observed within both the primary and recurrent groups (Pearson's r=0.8578 and 0.9849, respectively; Fig. 1D). The overall correlation across all six lines was positive (Pearson's r=0.7852). These findings demonstrate that highly motile GBM cells accumulate lower levels of PpIX upon 5-ALA exposure and are thus less detectable during fluorescence-guided surgery. Collectively, these data support functional coupling between intrinsic motility and diagnostic invisibility, which may contribute to incomplete tumor removal and postsurgical recurrence.

Figure 1 Correlation between PpIX accumulation and migratory potential in patient-derived GBM cells. (A) Representative flow cytometry histograms showing 5-ALA-induced PpIX fluorescence in the recurrent GBM line PDM123. (B) Quantification of PpIX-negative cell fractions in three primary (KBT series) and three recurrent (PDM series) GBM lines. KBT#12137 showed the highest PpIX accumulation, whereas PDM123 exhibited the lowest, consistent with its recurrent origin. Significant differences were observed between the primary and recurrent groups. *P<0.05. (C) Quantitative analysis of migratory capacity assessed by Transwell assay across the six GBM lines. Recurrent lines displayed significantly higher motility than primary lines. ***P<0.001. (D) Correlation between the proportion (%) of PpIX-negative cells and the migratory index, defined as the migration rate (%)=(lower-/upper-chamber cell counts) x100. All data represent means ± SD from at least three independent experiments. GBM, glioblastoma; 5-ALA, 5-aminolevulinic acid; PpIX, protoporphyrin IX.

Highly migratory GBM cells exhibit reduced 5-ALA detectability

To further test whether the migration status directly affects 5-ALA detectability at the subpopulation level, each patient-derived GBM culture was fractionated into migratory and non-migratory populations using Transwell assays, followed by PpIX fluorescence analysis. In the recurrent line PDM123, the migratory (lower chamber) population contained a markedly higher proportion of PpIX-negative cells than the non-migratory (upper chamber) population (Fig. 2A). This trend was consistently observed across all six GBM cell lines, with five lines (all except PDM19) showing a significantly greater proportion of PpIX-negative cells in the migratory fraction (*P<0.05, **P<0.01) (Fig. 2B). The relative abundance of the migratory PpIX-negative population was positively correlated with the overall migratory index across cell lines (r=0.72, P<0.05). Thus, 5-ALA detectability is inversely linked to migratory behavior and a minor subpopulation that combines high motility with low fluorescence likely represents a surgically invisible fraction that contributes to tumor infiltration and recurrence.

Figure 2 Reduced PpIX accumulation in highly migratory GBM subpopulations. (A) Representative comparison of 5-ALA-induced PpIX fluorescence between migratory (lower-chamber) and non-migratory (upper-chamber) cells isolated from the recurrent GBM line PDM123. The migratory fraction contained a higher proportion of PpIX-negative cells. (B) Quantitative summary of PpIX-negative cell fractions in migratory and non-migratory subpopulations across six GBM lines (three primary and three recurrent). Except for PDM19, all lines exhibited a significantly higher frequency of PpIX-negative cells in the migratory fraction. *P<0.05 and **P<0.01. Data represent means ± SD from at least three independent experiments. GBM, glioblastoma; 5-ALA, 5-aminolevulinic acid; PpIX, protoporphyrin IX; n.s., not significant.

Transcriptomic and clinical characterization of the migratory PpIX-low phenotype

To define the molecular programs underlying this dual phenotype, we performed genome-wide transcriptomic profiling of four phenotypically defined subpopulations-migratory PpIX-high, migratory PpIX-low, non-migratory PpIX-high, and non-migratory PpIX-low-sorted from representative GBM lines. Genes specifically upregulated in the migratory PpIX-low subset were defined by combined criteria of selectivity and amplitude (log2FC_rest >1 and log2FC_CA, CB, CD >0.5). Under this definition, migratory PpIX-low cells exhibited a focused but distinct transcriptional signature comprising 10 upregulated and 42 downregulated genes, relative to the other three groups. The upregulated genes included SLCO4A1-AS1, HES5, LOC105374643, NMU, and NT5E (CD73), whereas the most strongly downregulated genes were MT1G, GPNMB.1, C1S.1, FOSB, and SPOCK2.1 (Fig. 3A and B). These gene expression patterns suggest a coordinated shift toward a proliferative, stress-resistant, and metabolically adaptive phenotype. For instance, HES5, a Notch-pathway effector, and NT5E, an ecto-5'-nucleotidase that generates adenosine and suppresses immune activation, both contribute to stem-like persistence and microenvironmental tolerance. NMU encodes neuromedin U, a neuropeptide known to enhance GBM motility and angiogenic signaling, whereas SLCO4A1-AS1 is an antisense RNA associated with hypoxia-driven drug transport regulation. Conversely, MT1G and FOSB are oxidative stress-responsive genes typically induced by differentiation or inflammatory cues, and SPOCK2 encodes an extracellular matrix proteoglycan involved in glial maturation; their suppression further indicates an undifferentiated, high-motility cell state. GSEA of the full expression dataset provided a broader functional overview (Fig. 3C) (31), with full Hallmark enrichment results listed in Table SI. Hallmark pathways enriched among the upregulated genes included E2F_TARGETS, MYC_TARGETS_V1, G2M_CHECKPOINT, and OXIDATIVE_PHOSPHORYLATION, reflecting enhanced proliferative and metabolic activation consistent with a cycling, self-renewing phenotype. In contrast, downregulated pathways included TNFA_SIGNALING_VIA_NFKB, INTERFERON_GAMMA_RESPONSE, INFLAMMATORY_RESPONSE, and CHOLESTEROL_HOMEOSTASIS, indicating the suppression of stress-responsive and immunomodulatory transcriptional programs. This pattern suggests that migratory PpIX-low cells adopt a metabolically efficient, yet immunologically quiescent state that may permit tissue dissemination and survival under oxidative or therapeutic stress. Together with the downregulation of heme and porphyrin biosynthetic genes, these data imply that the migratory PpIX-low phenotype is sustained by a coupled transcriptional network integrating cell cycle activation, metabolic adaptation, and reduced immunogenicity, which collectively diminish 5-ALA-derived fluorescence and promote tumor persistence beyond the surgical margin. Collectively, these findings define the migratory PpIX-low state as a transcriptionally integrated mode of high-motility, metabolically adaptive, and diagnostically invisible tumor persistence.

Figure 3 Transcriptomic and clinical significance of the migratory PpIX-low phenotype. (A) MA plot illustrating differential gene expression among the four subpopulations (non-migratory/PpIX-low, non-migratory/PpIX-high, migratory/PpIX-low, and migratory/PpIX-high) derived from the recurrent GBM line PDM123. Genes upregulated (>2-fold) in migratory PpIX-low cells are shown in red, downregulated (<0.5-fold) in blue. The top five genes by |log2FC| are annotated. (B) Heatmap of the top 200 differentially expressed genes ranked by |log2FC| across the four subpopulations (Group A: non-migratory/PpIX-low, B: non-migratory/PpIX-high, C: migratory/PpIX-low, and D: migratory/PpIX-high). Migratory/PpIX-low (Group C) cells showed a global downregulation pattern compared with the others. The colour scale represents z-score normalised expression. (C) Gene set enrichment analysis (GSEA) (31) dot plot summarizing the top 15 enriched pathways ranked by NES. Up- and down-regulated pathways are displayed in the lower and upper panels, respectively. Dot color indicates adjusted P-value (FDR), and dot size corresponds to gene count. Full results for the top 25 upregulated and downregulated pathways are provided in Table SI. (D) Kaplan-Meier survival analysis of 525 patients with GBM in The Cancer Genome Atlas cohort stratified by the migratory PpIX-low gene signature score. High-score patients (n=263) exhibited significantly shorter overall survival than low-score ones (n=262) (P<0.05, log-rank test). NES, normalized enrichment score; GBM, glioblastoma; 5-ALA, 5-aminolevulinic acid; PpIX, protoporphyrin IX.

To evaluate the clinical relevance of this program, we constructed a migratory PpIX-low gene signature comprising the top 200 differentially expressed genes (70 upregulated and 130 downregulated; Table SII) and applied it to the TCGA GBM dataset (n=525) using the GlioVis data portal (34), with the clinical survival dataset provided in Table SIII. Kaplan-Meier analysis revealed that patients with high migratory PpIX-low signature scores (n=263) exhibited a significantly shorter overall survival than those with low scores (n=262; P=0.0404, log-rank test) (Fig. 3D). Taken together, these findings establish that the migratory PpIX-low state is defined by a transcriptional program that links motility and metabolic evasion, thereby conferring both high migratory capacity and diagnostic invisibility. Its association with poor patient outcomes underscores its translational significance and suggests that therapeutic modulation of this state, by restoring porphyrin biosynthesis or sensitizing migratory cells to 5-ALA, could improve intraoperative fluorescence detection and surgical efficacy in GBM.

Discussion

In this study, we identified a transcriptional connection between cellular migratory capacity and intraoperative detectability in GBM. Across six patient-derived GBM lines, highly migratory cells consistently exhibited reduced PpIX accumulation following exposure to 5-ALA, indicating that migratory behavior and fluorescence invisibility are functionally linked rather than independent phenomena. It should be noted that the cell behavior in this study was evaluated using a two-dimensional Transwell assay without extracellular matrix coating; therefore, our findings reflect chemotactic migration rather than true extracellular matrix invasion. Within this methodological scope, the observed association provides a molecular explanation for the incomplete resection often encountered during fluorescence-guided surgery and suggests that certain GBM subpopulations may remain undetectable during PDD.

Transcriptomic profiling of phenotypically defined subpopulations revealed that the migratory PpIX-low state represents a transcriptionally integrated mode of tumor persistence that combines high migratory capacity, metabolic adaptation, and diagnostic invisibility. Upregulated genes included HES5, a Notch effector maintaining stem-like identity (35,36); NT5E (CD73), an ecto-5'-nucleotidase that generates immunosuppressive adenosine (37); NMU, a neuropeptide that promotes GBM motility and angiogenesis (38); and SLCO4A1-AS1, a hypoxia-responsive long non-coding RNA involved in drug transport regulation (39). Conversely, downregulated genes such as MT1G and FOSB, which are oxidative stress-responsive and differentiation-associated (40), and SPOCK2, an extracellular matrix proteoglycan related to glial maturation (41), suggest the loss of differentiation and acquisition of a metabolically efficient migratory phenotype.

GSEA provided a broader view of these molecular shifts, with pathways associated with E2F targets, MYC targets, the G2M checkpoint, and oxidative phosphorylation being enriched, consistent with enhanced cell cycle and metabolic activation.

In contrast, pathways linked to TNFα-NFκB signaling, interferon-γ response, inflammatory response, and cholesterol homeostasis were suppressed, indicating a transcriptional landscape favoring proliferative efficiency and immune quiescence (42). Together with the downregulation of the heme and porphyrin biosynthesis pathways, these findings suggest that migratory PpIX-low cells adopt a metabolically streamlined yet stress-tolerant state that supports migration-associated dissemination and survival under therapeutic or oxidative pressure. This state may underlie their ability to escape intraoperative detection and contribute to tumor recurrence.

Clinically, the migratory PpIX-low gene signature was associated with significantly poorer overall survival in the TCGA GBM cohort, supporting its translational relevance (43). Concordance between in vitro fluorescence phenotypes and patient transcriptomic data implies that the molecular determinants of 5-ALA detectability reflect clinically meaningful tumor biology (44). Accordingly, the migratory PpIX-low signature may serve as a potential biomarker for predicting incomplete resection and recurrence risk (44), and therapeutic modulation of this state, by restoring porphyrin biosynthesis or sensitizing migratory cells to 5-ALA, could improve intraoperative tumor visualization and surgical efficacy in GBM.

This study had several limitations. Our analysis was based on six patient-derived lines and focused primarily on in vitro phenotypes; thus, the causal links between transcriptional programs and 5-ALA accumulation remain to be validated in vivo. Although we observed a consistent association between migratory capacity and reduced PpIX accumulation, alternative explanations should be considered. Although equal numbers of single cells were seeded into the upper chamber and migration was assessed within a defined time window under serum-free conditions, differences in proliferative activity could theoretically influence migration-based measurements. However, the positive correlation between migratory index and PpIX-negative fraction across independent cell lines suggests a stable phenotypic association rather than a transient growth-rate effect. Differences in cell-cycle distribution may influence porphyrin biosynthesis, because cycling cells exhibit altered metabolic demands that could affect PpIX synthesis. Furthermore, variability in 5-ALA uptake, intracellular transport, or efflux mechanisms, independent of migratory status, may contribute to the heterogeneous fluorescence intensity. Although our transcriptomic analyses support a coordinated molecular program linking motility and metabolic regulation, these alternative mechanisms cannot be excluded and warrant direct experimental validation. Future studies employing genetic manipulation and orthotopic xenograft models are necessary to determine whether altering this transcriptional network can modify tumor behavior or fluorescence responsiveness. In addition, while our Transwell system evaluated single-cell chemotactic migration, complementary models assessing collective migration dynamics (e.g., wound healing-type assays) may further refine the phenotypic characterization of GBM motility in future investigations. Despite these limitations, the present work provides a conceptual framework for understanding the molecular basis of the diagnostic invisibility associated with migratory GBM cell states and establishes a foundation for translational approaches to improve fluorescence-guided resection.

In summary, this study revealed a transcriptional network linking high migratory capacity with reduced 5-ALA-based fluorescence detectability in GBM.

Supplementary Material

Hallmark enrichment (PpIX-low).

Top 200 DEGs (PpIX-low signature).

The Cancer Genome Atlas glioblastoma survival data.

Acknowledgements

We thank Ms. Marika Nodera (Institute of Science Tokyo, Tokyo, Japan) for her technical assistance, Dr. Yoshitaka Murota (Institute of Science Tokyo, Tokyo, Japan) for his valuable discussions, and Professor Genki Kanda (Institute of Science Tokyo, Tokyo, Japan) for providing the research environment for this work.

Funding

Funding: This work was supported by the Japan Society for the Promotion of Science KAKENHI for Scientific Research (grant no. 24K10354) and JST CREST (grant no. JPMJCR2551). Additional support was provided by the Medical Research Center Initiative for High-Depth Omics, Nanken-Kyoten (grant nos. 2023-kokusai 01, 2024-kokunai 11, and 2025-kokunai 45), and Multilayered Stress Diseases (grant no. JPMXP1323015483), Science Tokyo.

Availability of data and materials

The data generated in the present study may be requested from the corresponding author. The microarray data generated in the present study have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE320501 and are available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE320501.

Authors' contributions

KT conceived and designed the study, curated and analyzed the data, and secured funding. TZ contributed to the investigation by performing the experiments. WL contributed to data analysis and interpretation. KT and TZ developed the methodology. IS, TH and TK contributed to acquisition of clinical samples and interpretation of data. SO contributed to experimental design and data interpretation. KT and TT supervised the study, and TT contributed to study design and data interpretation. KT validated the experiments, generated the figures, and wrote the original draft. All authors contributed to reviewing and editing the manuscript. All authors have read and approved the final manuscript. KT and TT confirm the authenticity of all the raw data.

Ethics approval and consent to participate

All procedures involving human specimens were approved by the Human Ethics Review Boards of the Kumamoto University School of Medicine (approval no. 231) and Kitasato University School of Medicine (approval no. B20-088) and conducted in accordance with the Declaration of Helsinki, with written informed consent obtained from all patients. All experiments involving recombinant DNA were approved by the Recombinant DNA Safety Committee of the Institute of Science Tokyo, Japan (approval nos. G2018-083C, G2023-051C, G2025-005A) and conducted in compliance with national regulations.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References