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. 2026 Mar 1;34(2):391–400. doi: 10.4062/biomolther.2024.234

Exploratory Proteomic Profiling Reveals Potential Mediators of 5-FU Response under p53 Deficiency in Colon Cancer Cells

Seonyong Lee 1,2,†, Jiwon Lee 1,†, Ga Seul Lee 3, Jeong Hee Moon 3, Joohee Jung 1,2,*
PMCID: PMC12961981  PMID: 41755778

Abstract

Mutations in p53 have been implicated in poor prognosis and reduced sensitivity to 5-fluorouracil (5-FU) treatment in colon cancer. While p53-dependent mechanisms have been widely studies, less is known about how p53 deficiency reshapes cellular signaling and contributes to 5-FU resistance. In this study, we aimed to profile proteomic alterations associated with p53 loss by comparing colon cancer cells with and without p53 expression. Differentially expressed proteins (DEPs) related to cell cycle regulation were of particular interest, as 5-FU treatment induced G1 phase arrest in HCT116 p53 wild-type (WT) cells, whereas p53 knockout (KO) cells predominantly showed S phase arrest. We identified several DEPs in p53 deficient cells following 5-FU treatment. Notably, F3 expression was increased, while aldehyde dehydrogenase family 1 member A4 (ALDH1A3), histone deacetylase 2 (HDAC2), and protein S100-A4 (S100A4) were decreased. The expression levels of these genes were associated with overall survival in patients with colon cancer. These findings highlight proteomic alterations linked to p53 deficiency and support a proposed model in which differential regulation of specific proteins may be associated with reduced sensitivity to 5-FU, providing a basis for future mechanistic and functional studies.

Keywords: Proteomics, 5-FU, p53 knock-out, HDAC2, F3

INTRODUCTION

Colon cancer has the third highest global incidence, and its mortality rate is expected to be second globally in 2022 (Bray et al., 2024). Although the incidence and mortality rates of colon cancer have been decreasing over the past few decades, the need for the development of chemotherapeutic agents persists owing to the limitations of surgery and the occurrence of metastasis.

However, the characteristics of colon cancer must be understood in order to establish new chemotherapeutic strategies. Genomic analysis has shown that mutations in several genes, including adenomatous polyposis coli (APC), Kirsten rat sarcoma virus (KRAS), mothers against decapentaplegic homolog 4 (SMAD4), and tumor protein p53 (TP53, p53 gene) occur frequently in colon cancer (Zhuang et al., 2021). TP53 mutations are observed in approximately 55-60% of patients with colon cancer (Nakayama and Oshima, 2019). The TP53 gene is activated in response to various stress signals, such as DNA damage or oncogene activation, and plays a role in regulating responses such as DNA repair, cell cycle arrest, cell senescence, and cell death (Hafner et al., 2019). Thus, TP53 mutations are associated with poor prognosis in various cancers, including colon cancer, and decreased sensitivity to chemotherapeutic agents. Nonetheless, the various effects caused by mutations or deficiencies in TP53 in colon cancer cells have not yet been fully elucidated.

5-Fluorouracil (5-FU), an analog of uracil with fluorine at the 5th carbon position, is the main treatment for colon cancer. It rapidly enters cells using the same facilitated transport mechanism as that of uracil. Its metabolites, such as fluorodeoxyuridine monophosphate and triphosphate, and fluorouridine triphosphate, exert cytotoxic effects on cancer cells by interfering with RNA synthesis and the action of thymidylate synthase (Azwar et al., 2021; Longley et al., 2003; Zhang et al., 2008). However, 5-FU resistance often occurs because of changes in drug transport, cell cycle, DNA damage repair system, and apoptosis (Azwar et al., 2021). Thus, 5-FU resistance occurs due to a TP53-related response because TP53 plays a role in the cell cycle, DNA damage response, and apoptosis (Garcia et al., 2011; Alvarado-Ortiz et al., 2023). Although numerous studies have explored the role of p53 in mediating the response to 5-FU, most have focused on well-established transcriptional targets or apoptotic regulators.

However, the proteomic changes that occur in the absence of p53 under 5-FU treatment remain poorly characterized. In this study, we conducted a comparative proteomic analysis of colon cancer cells with and without p53 expression following 5-FU treatment. Through this approach, we aimed to profile protein-level alterations and to highlight candidate molecular signatures that could be associated with 5-FU response in the p53 deficient colon cancer cells.

MATERIALS AND METHODS

Cell culture

Human colon cancer HCT 116 cells, including wild-type (WT) and isogenic (p53 knock-out, KO) (Jung et al, 2019), were cultured in RPMI-1640 medium (GenDEPOT, TX, USA), while RKO and RKO-E6 cells were cultured in MEM medium (GenDEPOT) at 37°C in a 5% CO2 incubator. These medium contained 10% inactivated fetal bovine serum (GW Vitek, Seoul, Korea) and 1% penicillin/streptomycin (GenDEPOT).

Cell cycle assay

The cells were treated with 8 μM 5-FU and incubated for 0, 12, 24, or 36 h. Subsequently, the cells were washed with PBS, fixed in 70% ethanol, and stained with propidium iodide at room temperature (RT) for 30 min to assess the cell cycle. The cell cycle was analyzed using flow cytometry (Novocyte, Agilent Technologies, CA, USA).

Proteomic analysis

The cells were treated with 8 μM 5-FU and lysed. The lysate was placed in 10% SDS (final concentration, 2%) and subjected to ultrasonic processing (QSONICA) at an amplitude of 50 for 30 s (3 s on/off) to degrade DNA/RNA. The lysate was then heated at 95°C for 10 min and centrifuged at 13,000×g for 10 min at 25°C to extract proteins. The extracted proteins were digested into peptides. Peptides were labeled with tandem mass tags system following as a manual (Thermo Fisher Scientific). Labeled peptides were fractionated using UPLC (Waters, Miliford, MA, USA) with a BEH C18 column (PN186002352). Proteomic analysis was performed using Orbitrap Exploris 240 (Thermo Fisher Scientific). (Lim et al., 2022; Adelipour et al., 2024). The raw files were processed using MaxQuant and Perseus for protein identification and quantification and the Homo sapiens database from UniProt for protein identification. In total, 8,725 protein groups were identified, of which 7,389 protein groups were quantified. Proteins and their expression levels were compared and analyzed across four groups: the HCT116 control group, the HCT116-p53KO control group, the HCT116 5-FU treatment group, and the HCT116-p53KO 5-FU treatment group.

Tumor tissue obtained from xenograft models

The experiment was approved by the Institutional Animal Care and Use Committee of Duksung Women’s University (2024-002-027) in accordance with the regulations for the care and use of laboratory animals. Male Balb/c-nude mice (5-weeks old), purchased from JA BIO (Suwon, Korea), were acclimated in the animal laboratory center for 7 days. HCT116 WT or p53 KO cells (5×106 cells/mouse) were transplanted into hind legs of Balb/c-nude mice. When the tumor volume reached approximately 50 mm3, the mice were randomly devided into groups. 5-FU (50 mg/kg) was administered three times per week. Tumor tissues were collected after 2 weeks.

Western blotting analysis

Cells (1×106 cells/dish) were treated with 8 μM 5-FU for 48 h and lysed in RIPA buffer (GenDEPOT) containing protease and phosphatase inhibitors (GenDEPOT). Protein concentration in cell lysates was quantified using the BCA assay. Proteins were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to a PVDF membrane (Millipore, MA, USA). Membranes were blocked with 5% blotting-grade blocker (Bio-Rad Laboratories, Hercules, CA, USA) at RT for 1 h and incubated with primary antibodies at 4°C overnight. The primary antibodies used were: p53 (BP53-12, monoclonal, 1:1,000, P5813, Sigma-Aldrich), p21 (CP74, monoclunal, 1:2,000, P38936, Sigma-Aldrich), phospho-p53 (p-p53, F-11, monoclonal, sc-377561), cyclin E (E-4, monoclonal, sc-377100), cyclin A (B-8, monoclonal, sc-271682), histone deacetylase 2 (HDAC2, C-8, monoclonal, sc-9959), and tissue factor (TF, F3, H-9, monoclonal, sc-374441) (1:1,000, Santa Cruz Biotechnology, TX, USA), cyclin B1 (V152, monoclonal, #4135), cyclin D1 (monoclonal, #2922), cyclin-dependent kinase (CDK)1 (POH1, monoclonal, #9116), CDK2 (78B2, monoclonal, #2546), CDK4 (D9G3E, monoclonal, #12790), CDK 6 (D4S8S, monoclonal, #13331)(1:1,000, Cell signaling, MA, USA), and aldehyde dehydrogenase family 1 member A4 (ALDH1A3, GT926, monoclonal, #MA5-27727) (1:1,000, Thermo Fisher Scientific) (Lee et al., 2022). The membranes were washed and incubated with goat anti-mouse IgG-HRP conjugate and goat anti-rabbit IgG-HRP conjugate (1:3,000, Bio-Rad Laboratories) secondary antibodies at RT for 3 h. Specific protein expression was visualized using an enhanced chemiluminescence solution and detected using ImageQuant LAS 500 (Cytiva Sweden AB, Uppsala, Sweden). The intensities of specific protein bands were calculated using ImageJ (NIH). β-actin (1:5,000, Abcam Cambridge, UK) and GAPDH (1:5,000, Sigma-Aldrich) were used as the loading control.

Statistical analysis

All data are expressed as the mean ± standard deviation (SD). The significance of the data was analyzed by analysis of variance (ANOVA) (GraphPad Prism 7 Software, CA, USA). Statistical significance was set at p<0.05.

Kaplan–Meier plot analysis

Relapse-free survival (RFS) was analyzed using the Kaplan–Meier plotter for colon cancer (kmplot.com) (LGyőrffy, 2024). The RFS of DEPs was analyzed as follows: auto-select the best cut-off and all restrictive factors, including cancer stage, location, site, TNM classification of the tumor, grade, microsatellite instability, BRAF mutation, KRAS mutation, sex, and adjuvant chemotherapy. Data from patients with colon cancer were compared with those from TP53 WT and mutant cells.

Protein-protein interaction network analysis

Protein-protein interaction network analysis was performed using the a search tool for retrieving interacting gene (STRING) database (version 12.0, https://string-db.org). DEPs were input, and interactions were visualized.

RESULTS

Differential cell cycle response to 5-FU in p53 wild-type and deficient colon cancer cells

P53-deficient colon cancer cells exhibited reduced sensitivity to 5-FU compared with p53 wild-type cells (Supplementary Fig. 1). In coincidence of other research, the role of p53-mediated apoptosis could be related to 5-FU resistance. At the low concentration of 5-FU without cell death, the cell cycle were compared between HCT116 WT and p53KO cells. 5-FU arrested HCT116 WT cells in the G0-G1 phases, but HCT116 p53 KO cells in the S phase (Fig. 1A). In other to elucidate the difference of cell cyle arrest, we investigated the levels of cell cycle-related proteins. In HCT116 WT cells, 5-FU significantly activated p53-p21 signaling pathway. In contrast, cyclin E was significantly induced in HCT116 p53KO cells with 5-FU treatment (Fig. 1B).

Fig. 1.

Fig. 1

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Differences in cell cycle arrest between HCT116 wild-type (WT) and p53 knock-out (KO) cells treated with 5-FU. (A) Profiles of cell cycle phases and quantification of cell cycle phases. (B) Expression levels of cell cycle-related proteins. Each protein level is one in control of HCT116 WT cells and compares to 5-FU treated HCT116 WT cells and HCT116 p53 KO cells. Fold induction (n=3) was calculated using ImageJ and analyzed using ANOVA test (Sidak’s multiple test). *p<0.01; **p<0.05; ****p<0.0001.

Comparative proteomic analysis identifies DEPs associated with p53 deficiency

Proteomic analysis was performed to investigate the difference in the 5-FU-therapeutic effect between HCT116 WT and p53KO cells. Overall, 8,725 proteins were identified in HCT116 WT and p53 KO cells treated with 5-FU, and the expression levels of 7,389 proteins were quantitatively analyzed and compared between each group. As shown in Fig. 2, the differences in Student’s t-test were calculated based on the average expression level of each protein in the two groups and the log (p-value). The proteins were selected when the fold change (FC) of the protein expression levels was >1.5 or <0.5, and p<0.005 when comparing the two groups (Table 1 and Fig. 2 (orange spots and sky blue spots)). HCT116 p53KO cells showed increased expression levels of 12 proteins compared to HCT116 WT cells but decreased expression levels of five proteins (left panel). 5-FU increased the expression of 23 proteins in HCT116 WT cells (middle panel) and one protein in HCT116 p53KO cells (right panel).

Fig. 2.

Fig. 2

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Proteomic identification and validation of F3 as a p53-associated protein in colon cancer. (A) The volcano plots illustrate differences among HCT116 wild-type (WT) and p53 knockout (p53 KO) cells, as well as between HCT116 and HCT116 p53 KO cells treated with or without 5-fluorouracil (5-FU). Data are expressed as the relationship between Student t-test difference in protein levels and p-values. Blue dotted lines represent the cutoffs for fold change and p-value used for differential expression analysis. Proteins with fold change >1.5 are colored orange, and those with fold change <0.5 are colored sky blue. HDAC2 and F3 are highlighted in red. Diagrams present the number of differential expressed protein. (B) The expression differences of F3, identified from DEPs, were analyzed by Western blot in human colon cancer cell lines, HCT116WT cells, HCT116 p53KO cells, RKO cells and RKO-E6 cells. Fold induction (n=3) was calculated using ImageJ and analyzed using ANOVA test (Sidak’s multiple test). *p<0.05. (C) F3 expression was examined by Western blot using tumor tissues isolated from HCT116 WT cells or HCT116 p53KO cells- derived xenograft models. Fold induction (n=3) was calculated using ImageJ and analyzed using ANOVA test (Sidak’s multiple test). **p<0.01; ***p<0.001.

Table 1.

Differentially expressed proteins in HCT116 cells between WT and p53 KO by 5-FU treatment

Compare groups Fold change>1.5* Fold change<0.5*
KO vs. WT of Control TIMM17B, CRAT, RTN1, SLC2A1, CAMK2D, ICE2, ARL4C, RBBP9, IAH1, SARG, APEX2, PVRL3 FN3K, HDAC2, SYK, PROM1
ACSM3
5-FU vs. Control in WT CDKN1A, TP53I3, CPA4, FTH1, TP53, CCND1, SMOX, MGLL, FAS, FHL2, KLK6, RRM2B, CD82, SERPINB5, GDF15, AHNAK2, GPX1, SH3YL1, TIGAR, MDM2, PRKAG2, AHNAK, GALNT5 -
5-FU vs. Control in KO F3 -
KO vs. WT of 5-FU treatment TIMM17B, CRAT, RTN1, SLC2A1, CAMK2D, ICE2, ARL4C, RBBP9, IAH1, CKAP2, UBE2S, SLC1A4, SGOL2, PRR11, F3, TTC12, CDCA2, KIF2C, KIAA1524, FOXM1, CDCA8, SUPT4H1, TIMELESS, SPAG5, CENPL, CDK6, ANKIB1, CPSF7, STK17B, SUPT5H FN3K, HDAC2, SYK, PROM1, CDKN1A, TP53I3, MGLL, CCND1, ALDH1A3, FAS, S100A4, RFTN1
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WT, HCT116 WT cells; KO, HCT116 p53 KO cells.

*p<0.005.

In HCT116 p53KO cells treated with 5-FU, only F3 protein levels were increased. Therefore, F3 expression was investigated in both HCT116 WT and p53KO cells following 5-FU treatment. F3 expression was higher in p53KO cell with 5-FU treatment compared to WT cells (Fig. 2B). Furthermore, similar patterns were observed in another colon cancer RKO and RKO-E6 cells. Consistent with the in vitro results, F3 expresseion levels were also elevated in xenograft models derived from WT and p53 KO cells (Fig. 2C).

Integrative analysis of DEPs through network and experimental validation

To further explore the relevance of the DEPs obtained from proteomic analysis in 5-FU treatment (Table 1), we investigated by combining protein-protein interaction (PPI) network mapping and western blotting analysis. In TP53 deficient cells, DEPs shown in the increase of FC had no relationship of PPI network, while DEPs shown in the decrease of FC decreased also under the condition of 5-FU treatment. Thus, DEPs decreased by 5-FU treatment were analyzed in p53 WT (Fig. 3A) and KO (Fig. 3B) cells. In HCT116 WT cells, TP53 interacted functionally enriched network with CDKN1A, HDAC2, CCND1, and FAS and was associated with p53 singaling pathway, DNA damage response, cell cycle regulation (clustering coefficient, 0.596; PPI enrichment p-value, 0.001). In contrast, the p53-deficient network showed reduced connectivity and loss of key regulatory interactions (clustering coefficient, 0.433; PPI enrichement p-value, 0.002). S100A4 were strongly interacted with TP53 (STRING score 0.99), but FN3K, MGLL, and RFTN1 showed no interaction with TP53 (Fig. 3A, 3B).

Fig. 3.

Fig. 3

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Protein-protein interaction network and expression of DEPs identified by proteomics. Protein-protein interaction network of DEPs in p53 WT cells (A) and KO cells (B). (C) Expression levels of DEPs. Each protein level is one in control of HCT116 WT cells and compares to 5-FU treated HCT116 WT cells and HCT116 p53 KO cells. Fold induction (n=3) was calculated using ImageJ and analyzed using ANOVA test (Sidak’s multiple test). ***p<0.001; ****p<0.0001.

Significant change of protein expression patterns were validated by Western blotting. 5-FU significantly showed the increase of F3 expression and the decrease of HDAC2 and ALDH1A3 expression in HCT116 p53KO cells compared to HCT116 WT cells (Fig. 3C).

Relapse-Free survival (RFS) of DEPs in patients with colon cancer

To assess the prognostic relevance of the identified DEPs, RFS in patients with colon cancer were analyzed using clinical datasets (Kaplan-Meier Plotter). Expression of F3 (TF, gene symbol 211203), which increased with 5-FU treatment in HCT116 p53KO cells compared to those in HCT116 WT cells (Table 1), was significantly associated with decreased RFS in patients with colon cancer. In particular, patients with TP53 mutation and high F3 expression showed significantly lower RFS (log-rank P=3.5e-6) (Fig. 4A). RFS was significantly different between high- and low-expression groups for ALDH1A3 (gene symbol 203180), HDAC2 (gene symbol 201833), and S100A4 (gene symbol 203186) (Fig. 4B). Notably, HDAC2, a gene functionally linked to TP53 signaling, showed a significant RFS difference in patients with TP53 mutant colon cancer (log-rank P=2.7e-6).

Fig. 4.

Fig. 4

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Difference in relapse free survival (RFS) between colon cancer patients with p53 wild type and mutation for differentially expressed proteins. RFS was analyzed using Kaplan–Meier Plots. The left graphs show RFS in all colon cancer patients, the middle graphs in patients with wild-type p53, and the right graphs in patients with mutant p53. All analyses were conducted without stratification based on 5-FU treatment. (A) Probability of RFS depending on F3 expression levels. (B) Probability of RFS depending on ALDH1A3, HDAC2, and S100A4 expression levels. Black line, low expression; red line, high expression; HR, hazard rate; p value, log-rank.

F3 and HDAC2 not only reflect altered proteomic responses to 5-FU but also correlate with poor prognosis in patients harboring TP53 mutations. Decreased HDAC2 expression had a more pronounced negative prognostic impact in TP53 mutant patients compared to the overall cohort.

DISCUSSION

This study provides an exploratory proteomic profiling intended to identify early candidate proteins and trends, rather than definitive mechanisms, associated with differential 5-FU responses under p53 deficiency. We identified several DEPs, including F3 and HDAC2, that may represent potential molecular features associated with p53 deficiency and altered 5-FU responsiveness (Fig. 5). Although these observations provide preliminary clues, the biological implications of the identivied DEPs remain tentative and require further mechanistic validation.

Fig. 5.

Fig. 5

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Proposed model illustrating the association between p53 loss and 5-FU resistance. In p53 WT cells treated with 5-FU, p53 activation is induced, leading to G1 cell cycle arrest and subsequent apoptosis. In contrast, in p53 KO cells, 5-FU treatment is associated with altered regulation of HDAC2 (downregulation) and F3 (upregulation), which is proposed to contribute to 5-FU resistance. Dotted arrows indicate hypothetical regulatory relationships proposed in this study based on integrated proteomic, cellular, and clinical analyses and have not yet been fully validated by direct functional experiments. These molecular alterations were further associated with RFS in patients harboring TP53 mutations.

5-FU is known to induce cell cycle arrest via increasing p21 levels and accumulation of reactive oxygen species (Li et al., 2023). TP53 plays a critical role in cell cycle checkpoints and apoptosis regulation (Mihara et al., 2003), and its expression significantly influences the chemotherapeutic efficacy of 5-FU (Giovannetti et al., 2007; Yoshikawa et al., 2001). In our results, although 5-FU induced S-phase arrest in HCT116 p53 KO cells, its chemotherapeutic effect was attenuated, supporting prior findings that 5-FU primarily induces cell death via regulation of the p53-pathway (Yang et al., 2021). Moreover, previous studies using an assay for transposase-accessible chromatin sequencing have shown that 5-FU activates the AP-1 complex, which is associated with cell proliferation, differentiation, and apoptosis, in p53 WT but not p53 KO colon cancer cells (Yang et al., 2021).

Therefore, we compared the proteomic profiles of HCT116 WT and p53 KO cells treated with 5-FU. Several DEPs were identified that were potential candidates associated with p53 status and 5-FU response (Table 1). Some of DEPs were investigated by western blotting analysis, PPI, and RFS.

Nevertheless, our study has several limitations. First, we could not extend the full proteomic profiling to multiple cell lines, but performed protein-level assesments of selected DEP, F3, in another colon cancer RKO and RKO-E6 cells (Fig. 2B). Second, direct functional validation of DEPs should be addressed in further studies. We plan to investigate whether suppressing F3 expression can restore 5-FU sensitivity in p53 KO cells. To compensate this limitation, F3 protein levels were validated in xenograft models derived from WT and p53KO cells (Fig. 2C).

Subsequent analysis of clinical datasets revealed that some of these proteins, including F3 and HDAC2, were significantly associated with patient prognosis (Fig. 4). The results provide preliminary evidence for prognostic biomarkers or potential therapeutic targets in p53-deficient colon cancer. When comparing RFS between all patients and those with p53 mutation (Fig. 4), the discrepancy between the proteomic analysis and the RFS of ALDH1A3 and S100A4 may reflect broader consequences of p53 deficiency rather than direct modulation by 5-FU.

Among the DEPs, F3, also known as tissue factor, was the only protein upregulated in HCT116 p53 KO cells treated with 5-FU (Table 1). Furthermore, F3 expression level increased in RKO and RKO-E6 cells, and in xenograft models. High TF expression levels induced by NF-κB and early growth response protein-1 are also linked to cancer progression (Hisada and Mackman, 2019). The F3-protease activated receptor 1 signaling pathway promotes cancer progression, whereas endotheral cell protein C receptor counteracts this effect by inducing apoptosis (Keshava et al., 2013). Our result is consistent with a previous study reporting increased F3 expression in colorectal cancer cells with p53 mutations (Rao et al., 2011). However, its functional involvement in 5-FU resistance remains hypothetical at this stage. The induction of F3 in p53 deficient cells and xenograft samples suggests a consistent pattern, but the mechanistic relevance of this protein should be interpreted with caution. Future experiments are required to determine whether F3 contributes causally to attenuated apoptotic responses or reflects a broader shift in stress-response pathways associated with p53 loss.

In contrast, HDAC2 expression was decreased in HCT116 p53 KO cells. Modulation of HDAC is associated with oncogenesis, metastasis, and drug resistance (Qi et al., 2021), and HDAC overexpression has been observed in several cancers and is correlated with poor prognosis (Alzoubi et al., 2016). Thus, HDAC inhibitors have been researched as potential anti-cancer drugs (Jo et al., 2023), and combined treatment with anti-cancer drugs and HDAC inhibitors has been shown synergistic effects (Alzoubi et al., 2016). A previous report show that HDAC2 maintains the expression of p53 mutants, which frequently occurrs in pancreatic cancer cells (Stoganovic et al., 2017). Furthermore, the cancer/testis antigen CAGE was shown to induce HDAC2 and Snail, leading to decreased p53 expression and apoptosis resistance via drug resistance signaling (Kim et al., 2010). Conversely, p53 mutations has been reported to downregulate HDAC2, contributing to reduced drug sensitivity (Sun et al., 2019). The correlation between HDAC2 and p53 is crucial in cancer progression; however, no direct mechanistic relationship can be concluded based solely on the proteomic patterns. In general, previous studies have suggested that HDAC2 regulates p53 expression and signaling pathway, but few have addressed whether p53 mutation affect HDAC2 expression (Wagner et al., 2014). Especially, the role of p53 deficiency in reducing HDAC2 expression has not been reported. Nevertheless, our results support this possibility, as lower HDAC2 expression in HCT116 p53KO cells was associated with shorter RFS in patients with TP53 mutation colon cancer (Fig. 4B). These finding should be viewed as preliminary and not indicative of a causal role. In future studies, we plan to investigate whether reduced HDAC2 expression could activate alternative pro-survival signaling pathways that are advantageous to p53-deficient cells.

In addition, we observed that 5-FU treatment upregulated several p53-related proteins, including p21 (CDKN1A), TP53I3, TIGAR, and CCND1 (cyclin D1), in HCT116 WT cells, indicating activation of cell cycle-related signaling. Consistently, 5-FU induced G1-phase arrest in HCT116 WT cells. In contrast, these proteins were downregulated in p53 KO cells, suggesting the activation of compensatory or alternative pathways in the p53-deficiency. Notably, in p53 deficient cells, 5-FU induced S-phase arrest. The upregulation of F3 in 5-FU-treated p53KO cells may contribute to reinforcing the S-phase checkpoint, thereby allowing cells to evade apoptosis.

In summary, our study provide an initial proteomic framework for understanding how p53 deficiency modulates 5-FU responses in colon cancer cells. While further functional validation is needed, these findings may serve as preliminary biomarkers or hypothesis-generating targets for future studies aimed at overcoming chemoresistance in tumors lacking functional p53.

bt-34-2-391-supple.pdf (1.6MB, pdf)

ACKNOWLEDGMENTS

We would like to thank Editage (www.editage.co.kr) for English language editing.

This research was supported by an NRF grant from the MSIT (NRF-2021R1A2C2004535).

Footnotes

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

AUTHOR CONTRIBUTIONS

Conceptualization, J.J.; methodology, S.L., J.L., G.S.L.; software, S.L., G.S.L.; validation, S.L.; formal analysis, S.L, J.L., G.S.L., J.H.M.; investigation, S.L., G.S.L.; resources, J.J.; data curation, S.L.; writing-original draft preparation, S.L.; writing-review and editing, J.J.; visualization, J.J.; supervision, J.J.; project administration, J.J.; funding acquisition, J.J. All authors have read and agreed to the published version of the manuscript.

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