Identification of hypoxia-related differentially expressed genes (DEGs) between ESCC and normal tissues

RNA sequencing (RNA-Seq) was employed to identify DEGs between six pairs of ESCC and adjacent normal tissues [14]. RNA-Seq tissues were collected from patients who received esophagectomy surgery in our cancer center in 2019. RNA-Seq were conducted and analyzed by Genminix-GCBI (Shanghai, China) with a screening criteria of an absolute log2-fold change (FC) > 1 and an adjusted P-value < 0.05. A hypoxia-related genes set was retrieved and downloaded from Gene Set Enrichment Analysis (GSEA) database [15]. The intersection of the two gene sets yielded the hypoxia-related DEGs.

Construction and validation of a prognostic signature

The mRNA expression profiles of ESCC patients and clinical data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Firstly, the univariate Cox regression analysis was conducted to identify the prognosis-related genes among the hypoxia-related DEGs using the “survival” R package on the GEO dataset. Subsequently, the Least absolute shrinkage and selection operator (LASSO) Cox regression was employed to narrow down the candidate genes via the “glmnet” R package [16]. The hypoxia-related prognostic gene signature was then determined based on the regression coefficient (β) and each gene's expression level, adhering to the proportional hazards assumption. The formula for risk score is articulated as: Risk score = β Gene1 × Expression level of gene1 + … + β Gene n × Expression level of gene n. This led to the categorization of patients into high-risk and low-risk groups, defined by the optimal cut-off value. The Kaplan–Meier survival analysis further assessed the predictive accuracy of this prognostic model in both the GEO and TCGA datasets.

Subsequently, we employed both univariate and multivariate Cox proportional hazard regression analyses to compare the prognostic gene signature's predictive capabilities against other clinical attributes. We analyzed the hazard ratio (HR) and 95% confidence intervals (CI) for ten primary clinical and prognostic variables, including age, sex, smoking habits, alcohol consumption, tumor location, grade, TNM stage, tumor stage, lymph node stage, and the hypoxia-related signature risk scores. Additionally, we visualized the risk using the “pheatmap” R package and evaluated the sensitivity and specificity of the gene signature with ROC curve analysis, facilitated by the “survival ROC” R package [17].

Functional enrichment analysis

To understand the biological functions and pathways related to the hypoxia signature, we conducted gene set enrichment analysis (GSEA) on the high- and low-risk groups using GSEA software [15].

Tumor specimens and cell culture

Tumor and adjacent normal tissues were collected from ESCC-diagnosed patients at our center. Patients were informed in alignment with the guidelines sanctioned by the Ethics Committee of Sun Yat-sen University Cancer Center. The corresponding clinical information includes age, gender, tumor grade, lymph node metastasis, AJCC TNM stages, and survival outcomes. Patients with insufficient clinical data were excluded. Propensity scores were estimated using age, gender (male versus female), TNM stage (I, II, III, IV), Tumor stage (T1, T2, T3, T4), Lymph Node stage (N0, N1, N2, N3), Metastasis stage (M0, M1) and treatment method (surgery, surgery + postoperative adjuvant chemotherapy). KYSE30 and KYSE150 were obtained from the Department of Experimental Research at the Sun Yat-sen University Cancer Center in Guangzhou, China. Cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) enriched with 10% FBS, and maintained at 37 °C in an atmosphere containing 5% CO2.

Chemical and hypoxia treatment

A 25 mM stock solution of cobalt chloride (CoCl2, Sigma-Aldrich, Germany) was prepared using sterile distilled water (dH2O) and subsequently diluted in the medium to achieve desired concentrations. To simulate an anoxic environment, KYSE30 and KYSE150 cells underwent treatment with varying concentrations (0, 100, 200, 300, 400 umol/L) of CoCl2 for 24 h [18].

Immunohistochemical assays

Immunohistochemical (IHC) analysis was performed according to the manufacturer’s instructions. Comprehensive details of antibodies and antigen retrieval techniques are available in Supplementary Table 1. For the survival analysis, ESCC patients from SYSUCC were grouped based on VBP1 expression levels, which was defined according to the following criteria: The intensity of VBP1 expression was scored as zero, negative; one point, weak staining; two points, mild staining; three points, strong staining. The positive stained area percentage (PSAP) of VBP1 expression was scored as 1, 0–25%; 2, 25%–50%; 3, 50%–75% and 4, 75%–100%. VBP1 IHC score = Intensity score × PSAP score. Patients were divided into high and low score groups by VBP1 IHC score and the Kaplan–Meier survival curves were analyzed using the log-rank test. The staining intensity was scored by two pathologists independently.

Quantitative real-time PCR (qRT-PCR)

To assess the mRNA expression difference of VBP1 between ESCC and normal tissues, real-time RT-PCR was conducted according to the manufacturer’s guidelines. We extracted the total RNA from cells and tissues using the TRIzol reagent method. The cDNA was synthesized from 1 μg of cellular RNA. The RT-qPCR process was then executed on a Light-Cycler480II (Roche) using SYBR Green Master Mix and specific primers (details in Supplementary Table 2).

Western blot

Following the manufacturer’s protocol, western blotting was carried out. In brief, cell lysates were prepared with RIPA Lysis Buffer (Beyotime, China) and protein quantification was done using the BCA Protein Kit (Beyotime, China). The cell lysates and immunocomplexes were then processed on SDS-PAGE and transferred to a PVDF membrane. These membranes, post-transfer, were blocked using QuickBlock™ Blocking Buffer (Beyotime, China), followed by an overnight incubation at 4 °C with specific antibodies. In the subsequent day, after incubation with secondary antibodies, immunoblots were visualized. The list of antibodies is provided in Supplementary Table 1.

Small interfering RNAs (siRNAs) and gene knockdown

VBP1 and control siRNA were purchased from GenePharma (Suzhou, China). The VBP1 siRNA mediated gene knockdown in KYSE30 and KYSE150 cells was achieved with Lipofectamine®3000 (Invitrogen, USA), as described in Supplementary Table 3.

Retroviruses and stable cell line

To establish KYSE30 cell lines that consistently overexpress VBP1, we utilized VBP1 recombinant retroviruses sourced from GenePharma (Suzhou, China). KYSE30 cells were infected with these retroviruses in the presence of polybrene. Following a 48-h infection period, we selected cells using 2 μg/mL puromycin to derive stable VBP1 over-expressing cell lines.

Cell proliferation assays

The proliferation of KYSE30 and KYSE150 cells was measured using a Cell Counting Kit-8 kit (CCK-8, Yeasen, Shanghai, China). In the first day, 1000 cells per well were cultured in a 96-well plate with 100 μL DMEM medium. On subsequent days, we prepared a working solution by adding the CCK-8 reagent to the medium as instructed by the manufacturer. This solution was added to each well and incubated for 1.5 h, after which it was measured at 450 nm absorbance. CCK-8 assays were performed in three biological replicates.

EdU assay

KYSE30 and KYSE150 cells were cultivated in 6-well plates and exposed to 2000 μL of medium containing 10 μM EdU, in line with the manufacturer’s instructions (BeyoClick™ EdU Cell Proliferation Kit with Alexa Fluor 594, Beyotime, China). After a 2-h incubation, cells were fixed and processed using Immunol Staining Fix Solution and Immunostaining Permeabilization Buffer, both from Beyotime, China. Cell nuclei were stained with Hoechst dye 33,342. Images were captured from three randomly chosen areas for each group, and the proliferation rate was calculated. EdU assays were performed in three biological replicates.

Colony formation

KYSE30 and KYSE150 cells were cultured in 6-well plates. Following 14 days of the specified treatment, colonies were visualized using hematoxylin staining. This procedure was replicate in triplicate.

Xenograft mouse model

For in vivo assessment, 4-week-old male nude mice (BALB/c-nu, Vital River Laboratory Animal Technology, Zhejiang, China) were utilized. KYSE30 cells (5 × 106 cells per mouse) were injected subcutaneously in the right rear back region. Mice were then grouped into two categories: 8 for the control (NC) group and 8 for the VBP1 overexpression (OE) group. Both body weight and tumor sizes were observed every four days, with tumor volume calculated using the given formula, volume = 1/2 × length × (width)2. On the 18th day, tumors were extracted for further analysis using hematoxylin and eosin (HE) staining and immunohistochemistry.

Statistical analysis

The SPSS 23.0 software program (IBM SPSS) and Graphpad Prism 7 (GraphPad Software Inc., CA, USA) were used for data analysis. Data are expressed as means ± standard deviation and P < 0.05 was considered statistically significant. Chi-squared or Fisher's exact tests were used to compare the categorical variables, and Student's t test was chosen to compare the difference in measurement data between two groups. The survival analyses were estimated by the Kaplan–Meier method, and the comparison was evaluated by the log-rank test. The univariate and multivariate analyses were conducted using a model of Cox's proportional hazards regression.