Elevated MCL1 expression drives esophageal squamous cell carcinoma stemness and induces resistance to radiotherapy

Introduction

Esophageal cancer comprises two main histopathological types, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) (1), which are fundamentally different in terms of etiology and epidemiology (2,3). ESCC has an extremely strong invasive ability and is associated with a poor prognosis and a low survival rate, with its 5-year overall survival rate being approximately 17% (range, 5–34%) (4). Early ESCC is primarily treated with surgery, with surgical resection combined with perioperative radiotherapy and chemotherapy typically being applied for locally advanced ESCC (5-7). Several clinical studies on neoadjuvant chemoradiotherapy have found that patients with ESCC and pathological complete response have better long-term survival and disease-free survival rates, which are not significantly correlated with pathological type or clinical stage (8-10). Regardless of whether neoadjuvant therapy is conducted before surgery, the 5-year survival rate of patients with pathological complete response peaks at about 50%, which indicates that esophageal cancer itself varies in its sensitivity to radiotherapy and chemotherapy (11).

Radioresistance is highly common and complicates the treatment of ESCC, considerably worsening the quality of life and survival time of patients (12). Radioresistance involves cancer stem cells (CSCs), intrinsic radiation sensitivity, hypoxia-reoxygenation, cell cycle redistribution, reproliferation, repair of radiation damage, and the tumor microenvironment (13-15). Further investigation into the molecular genetics specific to ESCC is imperative, as this is crucial for gaining insights into the mechanisms underlying the onset and advancement of this disease and for devising personalized clinical treatment strategies tailored to the needs of afflicted individuals. By clarifying the genetic underpinnings of ESCC, we can enhance our understanding of the tumor’s biology and thus develop more effective and targeted therapies.

In clinical practice, it has been found that some patients with ESCC experience local recurrence at the site of radiotherapy even if they have received radical surgery and adjuvant radiotherapy (16). It is reasonable to speculate that there may be some specific genetic variants that confer radioresistance in these patients with progressive ESCC, especially in those with short-term recurrence. Therefore, for this particular group of patients, it is necessary to screen and identify the related gene variants so as to guide individualized precision treatment in clinic (17-19). Whole-exome sequencing (WES) is a second-generation high-throughput sequencing technology. In the field of cancer research, it has been applied widely in examining high-frequency exon mutations and low-frequency and rarer mutations and for identifying new mutation sites (20-23). Exploiting these advances in this sequencing technology, we clarified the characteristics of gene variants in ESCC at the genomic level, identifying amplification of 1q myeloid cell leukemia-1 (MCL1) as a significant factor associated with progression-free survival, overall survival, and radiosensitivity in ESCC (24).

The MCL1 gene is located on chromosome lq21 and encodes a protein with a molecular weight of 42 kD and 350 amino acids (25,26). MCL1 amplification is found to be present in a variety of human malignancies and is dependent on the survival of many hematopoietic and other cell lines (27,28). MCL1 protein is a member of the core antiapoptotic Bcl-2 family, and MCL1 plays a role in inhibiting apoptosis by antagonizing proapoptotic Bcl-2 family proteins in mitochondria (29). Studies on ESCC, lung cancer, and other malignant tumors have demonstrated that MCL1 contributes to drug resistance through various mechanisms, with the primary pathway being the inhibition of apoptosis (30-32). However, Lee et al. found that in addition to exerting an antiapoptotic effect, MCL1 can also increase mitochondrial oxidative phosphorylation (Mt-OXPHOS), leading to the expansion of CSCs and the promotion of reactive oxygen species (ROS), with hypoxia increasing the expression of HIF-1α factor to maintain the chemoresistance of CSCs (33). Thus far, few studies have examined the role of MCL1 in ESCC radioresistance. Only one study from Japan reported that the overexpression of SOCS1 could reverse ESCC radioresistance by inhibiting STAT3-MCL1 axis-mediated apoptosis (34).

We thus conducted this study to clarify the function of MCL1 in radioresistant ESCC and found that its high expression contributes to ESCC’s ability to tolerate radiotherapy. The related mechanism involves the enhancement of tumor stemness via mediation of the JAK-STAT pathway in causing G0/G1 phase arrest. We present this article in accordance with the MDAR reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2027/rc).

Methods

Induction of radioresistant ESCC cell lines

Human esophageal endothelial cells (HEECs), and KYSE150 and ECA109 cells were purchased from Xiamen Yimo Biotechnology Co., Ltd (Xiamen, China). To develop chemotherapy-resistant variants, ECA109 and KYSE150 were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin at 37 ℃ in a humidified incubator with 5% CO₂. Cells were harvested during the logarithmic growth phase and resuspended to a final concentration of 2×10⁵ cells/mL. Aliquots of 100 µL were then plated into each well of a 6-well plate. After incubation for 24 hours to allow cell attachment, 2 mL of fresh RPMI-1640 medium was added to each well. The cells were then exposed to radiation therapy using a linear accelerator delivering a total dose of 36 Gy (3 fractions of 2, 4, and 6 Gy each, administered once a week). After the completion of irradiation, the cells were cultured for an additional 3 months to allow for the outgrowth of potential radioresistant clones. Cell survival was assessed using a clonogenic assay to compare the radiosensitivity of the parental cell lines with that of the irradiated cells. Surviving clones exhibiting increased radioresistance were isolated and designated as “KYSE150RR” and “ECA109RR”.

Clinical samples

This study included 33 ESCC tissue samples collected from the Affiliated Hospital of Nantong University. All patients with ESCC were pathologically confirmed independently by two pathologists, and none had received any neoadjuvant radiotherapy, chemotherapy, or immunotherapy before surgery. All patients were those who received surgical operations and postoperative adjuvant radiotherapy, namely postoperative radiotherapy (PORT) patients. Patients were included and excluded based on the completeness of data, and those with complete clinical and pathological information were enrolled. All patients were followed up for at least 2 years after treatment to confirm whether local recurrence occurred. According to the local recurrence status of patients, they were divided into the recurrence group (radiotherapy-resistant group) and the stable group (radiotherapy-sensitive group). The criterion for local recurrence was that the recurrence site of the patient was the irradiated area of postoperative adjuvant radiotherapy. If a new lesion was confirmed in the relevant anatomical location by biopsy pathology, positron emission tomography/computed tomography (PET/CT) or CT, it was determined as local recurrence and classified into the radiotherapy-resistant group. If no new lesion was observed in the patient at least 2 years after treatment, they were classified into the radiotherapy-sensitive group. Finally, 23 samples were collected, including 11 cases in the radiotherapy-sensitive group and 12 cases in the radiotherapy-resistant group. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Ethics Committee of the Affiliated Hospital of Nantong University (No. 2019-K078), and written informed consent was obtained from each patient.

Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR)

RNA was isolated using TRIzol (Thermo Fisher Scientific, Waltham, MA, USA) and quantified using a NanoDrop 2000 device (Thermo Fisher Scientific). RT-qPCR was conducted as follows. The reaction system was configured with the RT-qPCR SYBR Green Kit according to the manufacturer’s protocol (Vazyme Biotech Co., Ltd., Nanjing, China). The reagents in the PCR system were added to an eight-well plate, and three replicate samples were set for each sample. The plate was placed in the 7500 RT-qPCR instrument, and a total of 40 cycles were completed under the following reaction conditions: 95 ℃ for 10 minutes, 95 ℃ for 30 seconds, 59 ℃ for 32 seconds, and 72 ℃ for 31 seconds. Finally, the results were analyzed using 7500 Software v2.0 (Applied Biosystems, Thermo Fisher Scientific). PCR results were obtained after analysis of the data. The primer sequences are listed in Table S1.

Immunohistochemical (IHC) staining

For IHC staining, the tissue chip was placed in a 60 ℃ constant temperature box for baking for 2 hours. After baking, the tissue chip was placed in in xylene solution for 10 minutes, anhydrous ethanol for 5 minutes, and 95% ethanol for 5 minutes and then in 90%, 85%, and 80% ethanol for 2 minutes, respectively. Finally, the chip was rinsed with water and distilled water in a glass dish three times and finally removed. The rehydrated tissue slice was placed in citrate buffer solution and boiled at 100 ℃ for high-temperature cooking and then cooled naturally, as slicing abruptly can cause the slice to fall off, affecting the final staining effect. This process was repeated twice. After cooling, 3% hydrogen peroxide (H₂O₂) was added for 15-minute incubation, which was followed by a wash with phosphate-buffered saline (PBS) three times and a sealing with 5% bovine albumin serum (BAS) for 20 minutes; the remaining liquid was then discarded. Diluted MCL1 antibody (1:1,000) was added, and the solution was placed in a wet box at 4 ℃ overnight. Subsequently, three gentle washes with PBS buffer were performed, with each lasting 5 minutes. Secondary antibody was added, the mixture was incubated at room temperature for 30 minutes, and washed with PBS three times, after which the remaining solution was discarded. DAB chromogenic reagent was then added for color development for 5 minutes, counterstained with hematoxylin for 3 minutes, and rinsed with PBS. The slides were then mounted with gum arabic. The dyeing score was based on the number and intensity of cells with color (0–12 points). Immunological scoring was independently performed by two pathologists, and a final score was provided after discussion if there was any discrepancy.

Western blotting

For Western blotting, cell lysis solution was added after the cells were washed with PBS. The cells were lysed on a shaking table at 4 ℃ for 30 minutes. The cells were placed in a centrifuge at 4 ℃ and subjected to centrifugation at 12,000 ×g for 15 minutes for the collection of the supernatant, which was the total protein of the cells. Subsequently, 0.5 mg/mL of BSA was added in volumes of 0, 1, 2, 4, 8, 12, 16, and 20 µL to the standard protein wells, along with corresponding volumes of saline (20, 19, 18, 16, 12, 8, 4, and 0 µL), ensuring that the final volume in each well was maintained at a total of 20 µL. The protein samples were added according to the volumes of 19 µL of physiological saline and 1 µL of protein sample into protein sample wells. Based on the number of samples, bicinchoninic acid (BCA) working solution (Beyotime, Nantong, China) was prepared via the mixing of reagent A and reagent B at a ratio of 50:1, and 200 µL of this mixture was added to each well of a 96-well plate. The plate was gently shaken and incubated at 37 ℃ for 30 minutes. The absorbance (570 nm) was then measured, and a standard curve was drawn for calculating the protein concentration of each sample, with R²>0.99 indicating a standard curve. Proteins were boiled at 100 ℃ for 5 minutes, cooled down to room temperature, and stored at –20 ℃. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (PAGE) was conducted. Protein samples were added for loading, the sample comb was removed, electrophoresis liquid was added, and 15 µL of protein was added per lane. Subsequently, 5% skim milk was used for incubation, which was performed on a shaking table at room temperature for 1 hour. Incubation with primary antibody was performed overnight at 4 ℃ on a shaking table. Horseradish peroxidase (HRP)-labeled goat anti-mouse or anti-rabbit IgG (dilution ratio of 1:1,000) was selected according to the properties of the primary antibody, with incubation occurring at room temperature on a shaking table for 1 hour. The polyvinylidene fluoride (PVDF) membrane was then washed three times with Tris-buffered saline containing Tween 20 (TBST) for 10 minutes each. As per the manufacturer’s instructions for the enhanced chemiluminescence (ECL) chemiluminescence reagent kit (Sigma-Aldrich, St. Louis, MO, USA), the ECL reagent was applied evenly to the PVDF membrane. Pictures were taken using a gel imaging device to obtain immunoblotting bands. The antibodies are listed in the Table S2.

Colony formation assay

KYSE150, KYSE150RR, ECA109, and ECA109RR cells in the logarithmic growth phase were seeded into six-well plates and then treated with different doses of radiation (0, 1, 2, 4, 6, and 8 Gy). The cells were incubated at 37 ℃ for 14 days, with the medium being changed every other day. Subsequently, the cells were fixed with methanol at room temperature for 10 minutes. After being washed three times with PBS, the cells were stained with crystal violet solution for 30 minutes at room temperature. Excess crystal violet was removed, and the cells were rinsed three times with PBS.

Plasmid and small interfering RNA transfection

Cells in the logarithmic growth phase were collected by digestion and centrifugation into a 15-mL conical tube. The appropriate numbers of cells (60–70% confluence for plasmid transfection; 30–40% confluence for siRNA transfection) were then seeded into six-well plates. Two hours before transfection, the cells were placed in serum-free medium without antibiotics. Following this, 200 µL of Optimal-Minimal Essential Medium (Opti-MEM) medium and 5 µL of Lipofectamine 3000 were added to Eppendorf (EP) tube 1, and the solution was mixed gently and left to stand for 5 minutes. Subsequently, 200 µL of Opti-MEM medium and the specified amount of plasmid or siRNA were added to EP tube 2, and the solution was mixed gently and let stand for 5 minutes. The contents of EP tubes 1 and 2 were combined, incubated for 20 minutes, and then added to the corresponding wells of the six-well plate. Forty-eight hours later, RNA or proteins were collected for subsequent analysis.

Cell cycle analysis

For the analysis of the cell cycle, cells were seeded in six-well plates at a density of 1×10⁶ cells per well and incubated overnight. After a wash with PBS, they were fixed using 70% ice-cold ethanol and stored at 4 ℃ overnight. The cells were then washed again and resuspended in PBS before being treated with RNase A (20 µg/mL) and propidium iodide (PI) (50 µg/mL), which was followed by incubation at 37 ℃ for 30 minutes. Subsequently, flow cytometry analysis was performed using a flow cytometer (Beckman Coulter, Brea, CA, USA). CellQuest software was used to manually define regions corresponding to the G0/G1, S, and G2/M phases for cell cycle assessment. Each treatment group underwent three independent experiments. Flow cytometric data for DNA cell cycle analysis was processed using FlowJo software (FlowJo, Ashland, OR, USA).

Sphere formation assay

The cells in the logarithmic growth phase were digested, centrifuged, collected, and washed twice with PBS. After culture, the cells were resuspended at 1,000 cells/100 µL and inoculated in a U-shaped low-adsorption 96-well plate. After adherence, the cells were irradiated (9 Gy) and cultured in a 37 ℃, 5% CO₂ incubator. After 2 weeks of incubation, the sphere formation of the cells was photographed under the microscope and quantified.

Bioinformatics analysis

The databases based on The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) project were used to analyze the expression of MCL1 in ESCC (https://xenabrowser.net/hub/). We used esophageal cancer samples from TCGA database and divided them into high- and low-expression groups based on the median MCL1 expression levels. We then performed differential gene analysis between the two groups, defining genes with |log fold change (FC)| >1 and an adjusted P value <0.05 as differentially expressed genes. Using the clusterProfiler package, we conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis on these differentially expressed genes, visualizing the top 15 significantly enriched pathways. Subsequently, we performed gene set enrichment analysis (GSEA) using the “clusterProfiler” package in R with the entire set of genes, sorting them by logFC. The JAK-STAT3 pathway genes identified by GSEA (http://www.gsea-msigdb.org/), stemness related genes reported in literature and MCL1 were uploaded to the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) website for network interaction analysis. The minimum required interaction score was set to 0.4, and nodes without connections were not removed. Using cytoHubba within the Cytoscape software, we identified the hub genes among the top 25 genes using the EcCentricity algorithm and selecting the top 10 nodes.

Statistical analysis

All experiments were performed in triplicate. The data analysis and data graphs were completed using GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, USA) and SPSS 23 software (IBM Corp., Armonk, NY, USA). The differences between groups were analyzed with the t test, and the differences between multiple groups were analyzed with one-way analysis of variance (ANOVA). The hypothesis test level was set at α=0.05, and P<0.05 was considered to indicate statistical significance.

Results

The messenger RNA (mRNA) and protein expressions of MCL1 were significantly higher in ESCC tumor tissues and cell lines compared than in normal tissue and cells

To investigate the relationship between MCL1 and ESCC, we initially used TCGA database and GTEx project to analyze MCL1 transcription. The results revealed that the transcriptional level of MCL1 was significantly higher in tumor tissues compared to normal tissue (Figure 1A,1B). Additionally, RT-qPCR analysis of 10 fresh surgical samples from patients with ESCC showed an obvious increase in MCL1 transcriptional expression levels in tumor tissue (Figure 1C). Furthermore, RT-qPCR analysis also demonstrated that the mRNA expression of MCL1 was significantly higher in ESCC cell lines than in human normal esophageal epithelial cells (Figure 1D).

Figure 1 The mRNA and protein expressions of MCL1 were higher in esophageal cancer tissues and cell lines than those in normal tissues and cells. (A) TCGA database was used to analyze the expression of MCL1 mRNA in unpaired samples of patients with esophageal cancer. (B) TCGA database and GTEx project were used to analyze the expression of MCL1 mRNA in tissues. (C) RT-qPCR was used to detect MCL1 mRNA expression in 10 pairs of fresh esophageal cancer tissues and adjacent tissues. (D) RT-qPCR was used to detect MCL1 mRNA expression in normal esophageal epithelial cells and esophageal cancer cell lines. (E) Immunohistochemistry was used to detect the expression of MCL1 in 10 paired esophageal cancer tissues. Representative images are shown. Scale bars: 500 µm (original image), 50 µm (enlarged image). (F) Immunohistochemical score of MCL1 expression level. (G) Western blotting of MCL1 protein expression in human normal esophageal epithelial cell lines and esophageal cancer cell lines. *, P<0.05; ***, P<0.001. MCL1, myeloid cell leukemia-1; TPM, transcripts per million; IHC, immunohistochemistry; TCGA, The Cancer Genome Atlas; GTEx, Genotype-Tissue Expression; RT-qPCR, real-time fluorescence quantitative polymerase chain reaction.

Next, to determine the protein expression of MCL1 in ESCC tissue samples, we initially collected 10 patient samples for IHC analysis. The findings revealed positive cytoplasmic and nuclear expression of MCL1 protein, indicated by brown particles (Figure 1E). Moreover, in 80% (8/10) of the ESCC tissues examined, MCL1 protein expression was higher compared to that of the corresponding normal tissue (Figure 1F). Western blotting results further indicated significantly elevated levels of MCL1 protein in ESCC cell lines KYSE150 and ECA109 as compared to normal HEECs (Figure 1G). These outcomes strongly suggest that MCL1 may play a crucial role in the development of ESCC.

MCL1 protein expression was significantly increased in patients with ESCC with radioresistance

To explore the multifaceted role of MCL1 in the progression of ESCC beyond its established association with esophageal malignancies, we conducted an exhaustive WES analysis on a cohort of 23 previously gathered ESCC specimens. Our previously findings revealed that gains in chromosome 1q copy number were significantly linked to an elevated risk of tumor recurrence following radiotherapy in patients with esophageal cancer. Notably, the MCL1 gene, located on chromosome 1q, exhibited amplification in these samples, suggesting a potential mechanistic link between MCL1 overexpression and radioresistance (24). To further substantiate this connection at the protein level, IHC was employed to assess MCL1 expression in the aforementioned ESCC tissues. Our results demonstrated a pronounced upregulation of MCL1 in the tissue samples from patients who experienced recurrence postradiotherapy. Specifically, within the recurrent group, a remarkable 83.3% (10 out of 12) of cases displayed heightened MCL1 protein expression, a stark contrast to the 27.3% (3 out of 11) observed in the stable disease group (Figure 2A,2B). These data collectively implicate MCL1 as a pivotal player in modulating the radiosensitivity of ESCC and thus potentially serving as a biomarker for predicting treatment outcomes and guiding therapeutic strategies.

Figure 2 MCL1 protein expression was significantly increased in patients with ESCC and radioresistance. (A) Immunohistochemical analysis of the MCL1 expression of 23 patients with esophageal carcinoma tissues. Representative images are shown. Scale bars: 200 µm (original image), 50 µm (enlarged image). (B) Quantification of MCL1 expression according to immunohistochemical score. (C,D) Survival curves, mean lethal dose (D0), and quasithreshold dose (Dq) of KYSE150 cells and their corresponding resistant cell lines after different doses of irradiation. (E,F) Survival curves, D0, and Dq of esophageal cancer cell line ECA109 and its corresponding resistant cell line after irradiation with different doses. (G) RT-qPCR was used to detect the transcriptional expression of MCL1 in esophageal cancer cell lines. (H) The expression of MCL1 protein in different esophageal cancer cell lines was detected by Western blotting. **, P<0.01. IHC, immunohistochemistry; MCL1, myeloid cell leukemia-1; IR, X-ray irradiation; RR, radiation resistance; ESCC, esophageal squamous cell carcinoma; RT-qPCR, real-time fluorescence quantitative polymerase chain reaction.

To confirm the involvement of MCL1 in ESCC radiation resistance, we engineered radiation-resistant ESCC cell lines. Through a series of cloning experiments, we validated the establishment of these resistant strains. A clonogenic survival assay was used to delineate cell survival curves, enabling us to quantify the average lethal dose (D0) and subthreshold dose (Dq) parameters. Our analyses revealed a notable elevation in the survival fraction, D0, and Dq values after radiation induction, indicative of an acquired resistance to radiotherapy (Figure 2C-2F). The resistant cells were named “KYSE150RR” and “ECA109RR”.

RT-qPCR assay was used to detect the transcription of MCL1 in the parental and radioresistant ESCC cells. The results showed that the transcription level of MCL1 in the resistant cell line was significantly higher than that in the parental cell line (Figure 2G). Western blotting analysis of MCL1 protein expression showed that the expression of MCL1 protein in the resistant cell line was significantly higher than that in the parental cell line (Figure 2H).

MCL1 overexpression enhanced radiotherapy resistance of ESCC in vitro

In the parental cell lines KYSE150 and ECA109, MCL1 overexpression promoted the proliferation of cells, as indicated by colony formation assay (Figure 3A-3D). In contrast, MCL1 was knocked down in the KYSE150RR and ECA109RR cell lines (Figure 3E). The results of colony formation assay showed that the proliferation ability of radio-resistant cell lines was significantly reduced by MCL1 knockdown (Figure 3F-3H).

Figure 3 In vitro MCL1 overexpression enhanced the radiotherapy resistance of ESCC. (A) NC and MCL1-overexpression (Flag-MCL1) plasmid were transfected into parental cell lines, and the transfection effect was detected via Western blotting. (B-D) Cells were exposed to X-ray irradiation and then subjected to a colony formation assay. After 14 days, the colonies were fixed with methanol, stained with crystal violet, and counted. (E) Control (Ctrl) and MCL1 siRNA (si-MCL1) was transfected into radioresistant cell lines, and the transfection effect was detected via Western blotting. (F-H) Cells were exposed to X-ray irradiation and then subjected to a colony formation assay. After 14 days, the colonies were fixed with methanol, stained with crystal violet, and counted. ***, P<0.001. MCL1, myeloid cell leukemia-1; NC, normal control; IR, X-ray irradiation; RR, radiation resistance; ESCC, esophageal squamous cell carcinoma.

MCL1 may regulate the stemness of ESCC through the JAK-STAT pathway

In order to further clarify the molecular mechanism underlying the involvement of MCL1 in the radiosensitivity of ESCC, we performed chemical and genetic perturbation based on the esophageal cancer data of TCGA database. Among the KEGG datasets analyzed, 15 signaling pathways emerged as significantly enriched based on stringent P value thresholds. Notably, MCL1 was prominently associated with the cell cycle and the JAK-STAT signaling pathway (Figure 4A), underscoring its potential role in these critical biological processes. The GSEA results showed that pathways related to tumor stemness were significantly enriched in the high-MCL1 expression group, including the STEM CELL UP and CELL_CYCLE terms (Figure 4B,4C).

Figure 4 GSEA of esophageal cancer using TCGA data indicated that MCL1 may regulate the stemness of esophageal cancer through the JAK-STAT pathway. (A) TCGA database was used to perform GSEA pathway enrichment analysis with the KEGG pathway database as the background, and the 15 pathways with the most significant P values were visualized. (B) Pathway GSEA of the correlation between MCL1 and cell stemness. (C) The correlation between MCL1 and cell cycle was analyzed via GSEA pathway enrichment. (D) The STRING database was used to analyze the protein interaction between MCL1 and the JAK-STAT pathway and stemness-related genes. (E) TCGA database was used to analyze the correlation between MCL1 and the JAK-STAT pathway and stemness-related gene transcription levels. (F,G) Normal control (NC) and MCL1-overexpression (Flag-MCL1) plasmid were transfected into ECA109 and KYSE150 cells, and the transcriptional expression of STAT3, SNAI1, CD44 and MYC was detected. ***, P<0.001. TPM, transcripts per million; MCL1, myeloid cell leukemia-1; JAK, janus kinase; STAT, signal transducer and activator of transcription; KEGG, Kyoto Encyclopedia of Genes and Genomes; SNAI1, snail family transcriptional repressor 1; MYC, MYC proto-oncogene, BHLH, transcription factor; GSEA, gene set enrichment analysis; TCGA, The Cancer Genome Atlas.

Using cytoHubba within the Cytoscape software and the STRING database (https://cn.string-db.org/), we identified MCL1 as a hub gene within this network (Figure 4D). TCGA database was used to analyze the correlation between these genes and MCL1, and the results showed that MCL1 was significantly positively correlated with JAK1-3, STAT1/3/5B, MYC, and SNAI1 (Figure 4E). In ESCC cell lines, overexpression of MCL1 led to a significant upregulation in the expression of STAT3, SNAI1, CD44 and MYC (Figure 4F,4G). These findings collectively suggest a mechanistic link between MCL1 and the modulation of CSC properties and cell cycle regulation in ESCC.

MCL1 promoted G0/G1 phase arrest by regulating the expression of cyclin D3 and p21

Studies have confirmed that there is a close relationship between cell G0/G1 phase arrest and tumor cell stemness, and MCL1 has been confirmed to be an antiapoptotic protein (14,29). To determine the effect of MCL1 on cell cycle, flow cytometry analysis was performed. The results showed that overexpression of MCL1 induced significant G0/G1 phase arrest in KYSE150 and ECA109 cells (Figure 5A,5B). Furthermore, Western blotting showed that overexpression of MCL1 increased the expression of the inhibitory cyclin p21 and decreased the expression of cyclin D3, a key protein in the regulation of G1-to-S phase transition (Figure 5C). MCL1 could regulate cell cycle arrest in the G0/G1 phase via cyclin D3 and p21.

Figure 5 MCL1 regulated cell G0/G1 phase arrest by regulating cyclin D3 and p21 expression. (A,B) After NC and MCL1-overexpression (Flag-MCL1) plasmid was transfected into in KYSE150 and ECA109 cells, cell cycle changes were detected via flow cytometry. (C) MCL1 was overexpressed in the cells, and cyclin D3 and p21 protein expression was detected by Western blotting. (D,E) Stemness sphere formation assay was performed with transfected cells or with inhibitors, and the cells were observed under microscopy after 14 days. (F,G) Cell clonogenic assays were performed on cell lines treated with transfection or combined inhibitors, and 14 days later, the cells were fixed with methanol for 30 minutes, stained with crystal violet for 30 minutes, and then counted. ***, P<0.001; 1, NC; 2, Flag-MCL1; 3, Flag-MCL1 + AZD-1480; NC, normal control; MCL1, myeloid cell leukemia-1; IR, X-ray irradiation.

To elucidate the role of the JAK-STAT pathway in the MCL1-mediated radiotherapy resistance of esophageal cancer, we employed the well-characterized JAK inhibitor, AZD-1480, in our cellular models. This intervention was designed to evaluate the impact of MCL1 impact on JAK signaling dynamics and its downstream effects on tumor biology. Our findings revealed that enforced MCL1 expression significantly augmented the tumorigenic potential of esophageal cancer cells, which manifested as an enhanced sphere-forming capacity and radioresistance. Intriguingly, treatment with AZD-1480 effectively abrogated the radioprotective effect conferred by MCL1 overexpression, reestablishing cellular sensitivity to radiotherapy (Figure 5D-5G). These data collectively support the notion that MCL1 operates as a critical regulator of tumor stem cell traits and radioresistance, exerting its influence, at least in part, through the modulation of the JAK-STAT signaling cascade. This study underscores the potential of targeting MCL1 and its associated pathways as a viable strategy for overcoming radiotherapy resistance in esophageal cancer, offering new avenues for therapeutic intervention.

Discussion

MCL1 was first discovered in 1993, being initially identified by Craig and colleagues as an up-regulated gene in the early differentiation of human myeloid leukemia cells (35). As a member of the antiapoptotic Bcl-2 family, MCL1 prevents the proapoptotic proteins Bcl-2 homologous antagonistic killer protein (Bak) and Bcl-2-associated protein X (Bax) from forming pores in the mitochondrial membrane such that cytochrome C is not released into the cytoplasm (36,37). MCL1 also inhibits the cysteine protease family, reducing subsequent caspase activation, which is primarily responsible for the degradation of most large molecules during apoptosis (38). MCL1 has a broad but specialized tissue distribution and has been shown to be involved in the survival and development of multiple cell types (39-42). In addition to its role in apoptosis and differentiation, MCL1 is also known to influence cell cycle progression (43,44). Beroukhim et al. and Wang et al. performed extensive somatic copy number amplification (SCNA) genomic analysis on more than 3,000 cancer specimens representing 26 histological types and found that MCL1 was enriched in focal SCNA regions; moreover, MCL1 amplification was found in cancers of a variety of tissue types, including breast cancer, lung adenocarcinoma, and melanoma (28,45). MCL1 expression often appears in a wide variety of tumor types and is closely associated with the poor prognosis of patients and the drug resistance of tumors (25,46-48). The second-generation MCL1 antagonists may be key targets for cancer treatment (49-51). In esophageal cancer, the MCL1 inhibitor obatoclax can significantly reduce the expression of multidrug resistance gene 1 (MDR1) and overcome the resistance of ESCC to cisplatin through the Src-MCL1-MDR1 pathway (31). However, thus far, few studies on MCL1 amplification and ESCC radiotherapy resistance have been conducted.

In the first part of this study, WES-sequencing technology was used to compare the genetic information of patients with ESCC with differing prognoses after postoperative radiotherapy, and several genetic variants including MCL1 amplification were found to be associated with radiotherapy resistance. We further aimed to investigate the role and mechanism of MCL1 in ESCC radioresistance. Initially, we established the relationship between MCL1 and ESCC through an analysis of TCGA database, followed by validation using 10 fresh surgical samples from patients with ESCC. The results showed that the transcriptional level of MCL1 in ESCC tissues was significantly higher than that in adjacent normal tissues. Subsequently, we investigated and analyzed the relationship between MCL1 expression and sensitivity to radiotherapy as well as radiation resistance. The results indicated that MCL1 expression was significantly elevated in patients exhibiting radiation resistance compared to those demonstrating radiation sensitivity, which aligns with the existing literature on MCL1 expression in ESCC (31,32,34). Among the Bcl-2 family members, the antiapoptotic protein MCL1 has a short half-life, which makes this protein highly sensitive to changes in synthesis or degradation; therefore, examining MCL1 regulators can help to uncover the mechanism of disease development and treatment (52). In the subsequent validation experiments, we also found that the expression of MCL1 was significantly higher in the radioresistant ESCC cell lines than in their parental cell lines. In the in vitro cell model experiment, overexpression of MCL1 in the KYSE150 and ECA109 cell lines significantly increased the radioresistance of ESCC cells, suggesting that MCL1 overexpression promotes the radioresistance of ESCC cells. The cloning experiment confirmed that the resistance of KYSE150RR and ECA109RR cells to radiation was significantly reduced after MCL1 was knocked down. The above results confirm that MCL1 participates in regulating the radiation resistance of ESCC, which is consistent with the research results of Sugase et al. (34). Taken together, the above results suggest that MCL1 may be involved in the radiosensitivity of ESCC.

The ultimate goal of gene sequencing analysis is to characterize gene expression patterns, facilitate a more in-depth interpretation of the results to clarify the biological mechanisms, and according to the differentially expressed genes between different categories, extract significant and meaningful results. With the widespread application of high-throughput sequencing technologies, increasingly larger datasets that are difficult to analyze and integrate have been generated, but traditional gene expression analysis strategies focus on identifying individual genes that exhibit differences between two states, which while useful, cannot clarify the related biological processes such as metabolic pathways, transcriptional programs, and stress responses (53). These biological processes are distributed in the whole gene network, but they are indiscernible when examined at the level of a single gene, so it is difficult for traditional gene analysis methods to generate meaningful conclusion from these data. GSEA, first proposed by the Broad Institute, is a powerful enrichment analysis tool. Compared with the single-gene methods, GSEA has three main advantages: First, it by identifying pathways and processes to simplify the interpretation of the large-scale experiments, researchers can focus on gene sets rather than on the genes with high scores, as gene sets tend to be easier to copy and thus more interpretable. Second, GSEA can help highlight true biological signals amid background noise. In a set of strongly correlated genes, even if the changes in individual genes are modest, GSEA can enhance the signal by integrating the overall changes, thus improving the effectiveness of the analysis. Third, this analysis can help define gene subgroups to elucidate the results (54). Therefore, GSEA has now become an integral part of high-throughput gene expression data analysis and is an algorithm widely used to identify statistically rich gene sets in transcriptome data. KEGG is a knowledge base that links genomic information with higher-order functional information and can be used for the systematic analysis of gene functions (55). Genomic information is stored in the gene database, which is a collection of gene catalogues of all fully sequenced genomes and partial genomes with up-to-date annotations of gene function. Higher-order functional information is stored in the KEGG PATHWAY database, which contains graphical representations of cellular processes such as metabolism, membrane transport, signal transduction, and cell cycle. Its purpose is to facilitate the use of computers to achieve a comprehensive display of the biological information contained in cells and organisms. With this genomic information, computing can calculate or predict complex pathways in cells or biologically complex behavior. In this study, MCL1 was found to be significantly correlated with KEGG terms “cell cycle” and “JAK-STAT signaling pathway”. In addition, GSEA showed that MCL1 had a positive correlation with tumor stemness but a negative correlation with cell cycle arrest. Overall, the GSEA findings suggest that the radioresistance of MCL1 in ESCC may be related to the JAK–STAT pathway, stemness-related genes, and cell cycle arrest.

The purpose of the STRING database is integrate all known and predicted associations between proteins, including physical interactions and functional associations (56). In this study, the STRING database was used to analyze the protein interaction between MCL1 and the JAK-STAT pathway and stemness-related genes, and it was found that MCL1 was closely related to JAK-STAT and stemness. TCGA database was used to analyze the correlation between MCL1 and the JAK-STAT pathway and stemness-related gene transcription levels. ECA109 and KYSE150 cells overexpressing MCL1 were used to detect the transcriptional expression of JAK1, STAT1, SNAI1 and MYC, and the results showed that MCL1 was positively correlated with JAK1-3, STAT1/3/5B, MYC, and SNAI1. In the subsequent cell experiments, JAK1, STAT1, OCT4, and SNAI1 were indeed significantly upregulated after the overexpression of MCL1 in esophageal cancer cell lines, which was consistent with the results of TCGA database analysis. In addition, a large number of studies have confirmed that cell cycle arrest is closely related to tumor cell stemness (57-59). We overexpressed MCL1 in KYSE150 cells and detected cell cycle changes via flow cytometry, and the results showed that overexpression of MCL1 could cause significant G0/G1 phase arrest in KYSE150 cells. Therefore, these results suggest that overexpression of MCL1 promotes stemness gene expression in ESCC.

Finally, to understand the importance of the JAK-STAT pathway in the MCL1-mediated radioresistance of esophageal cancer, we first used the previously documented JAK-STAT inhibitor AZD-1480 in immunoblotting analysis for experimental confirmation (60). After overexpression of MCL1, the protein levels of OCT-4 and SNAI1 were significantly upregulated, while the upregulation effect was significantly weakened after cotreatment with AZD-1480. Clonogenic assay showed that AZD-1480 reversed the effect of MCL1 overexpression on the radioresistance of tumor cells. Therefore, these results suggest that MCL1 promotes radioresistance by regulating tumor stemness through the JAK–STAT pathway.

Conclusions

In conclusion, the expression of MCL1 was detected at both the mRNA and protein level in 10 pairs of fresh surgical specimens from patients with ESCC and 23 pairs of ESCC tissues and adjacent normal tissues via RT-qPCR, Western blotting, and IHC. These experiments suggested that MCL1 was associated with the radiosensitivity of ESCC. The role of MCL1 in radioresistance of ESCC was further confirmed by knockdown or overexpression of MCL1 in the parental and radioresistant ESCC cell lines. Finally, TCGA database was used to perform GSEA and KEGG, STRING database analysis, and related verification experiments. MCL1 enhances the radioresistance of ESCC by promoting the expression of stem-related genes including JAK1, STAT1, OCT4, and SNAI1, as well as the tumor stemness mediated by the JAK-STAT pathway.

Acknowledgments

We would like to thank Qin Jin for helping with the analysis of pathological sections.

Funding: This work was supported by grants from the Research Project of Nantong Health Committee (No. MS2023008), the National Natural Science Foundation of China (No. 82203096), the Chinese Postdoctoral Science Foundation (No. 2022M711717), and the Jiangsu Provincial Research Hospital (No. YJXYY202204-YSB27).

Footnote

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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2024-2027/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Ethical approval was obtained from Ethics Committee of Affiliated Hospital of Nantong University (No. 2019-K078), and written informed consent was obtained from each patient.

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