Downregulation of IL16 Expression Induces Chemotherapeutic Drug Sensitivity via Increased Degradation of Mutant TP53 in Acute Myeloid Leukemia Cells

Abstract

Background

Interleukin 16 (IL16) is a pleiotropic cytokine that does not belong to any interleukin family and functions as a CD4⁺ T-cell chemokine, a regulator of T-cell activation, and an inhibitor of human immunodeficiency virus replication in acquired immunodeficiency syndrome. Studies in the hemato-oncological disease multiple myeloma have demonstrated that IL16 plays an important role in promoting tumor cell growth and is associated with tumor burden and prognosis. However, the role of IL16 in acute myeloid leukemia (AML) remains largely unexplored.

Aims

To investigate the potential role of IL16 in AML.

Study Design

In vitro experiments.

Methods

Bioinformatic analyses were conducted using online databases, including gene expression profiling interactive analysis 2, to evaluate IL16 expression and its prognostic significance in patients with AML. Transcriptome data from AML samples were used for gene function enrichment analysis, gene set enrichment analysis (GSEA), survival analysis, and other related bioinformatic assessments. In addition, a single-cell dataset was analyzed using the R programming language to identify specific IL16 expression subgroups in AML patients. The expression and secretion of IL16 in various AML cell lines were assessed using Western blot and ELISA. IL16 knockdown AML cell lines were generated and evaluated for proliferation, apoptosis, and multidrug resistance to chemotherapy using cell-based assays and protein immunoblotting to determine the effects of IL16 on AML biological behavior. Furthermore, transcriptome sequencing analysis was performed to elucidate the molecular mechanisms underlying the effects of IL16 on the biological functions of AML cells.

Results

IL16 expression levels were significantly elevated in patients with AML and were associated with poorer prognosis. IL16 was predominantly expressed in T cells, malignant hematopoietic stem cells, malignant progenitor cells, and malignant mononuclear precursor cells in AML patients. Knockdown of IL16 expression significantly inhibited proliferation and promoted chemotherapy-induced apoptosis in AML cells in vitro. Downregulation of IL16 also reduced cell viability and decreased the IC₅₀ of cytarabine (Ara-C) across different concentrations. Furthermore, reduced IL16 expression may induce degradation of mutated TP53 in AML cells, resulting in increased apoptosis and enhanced sensitivity to multiple chemotherapeutic agents.

Conclusion

High IL16 expression was observed in malignant cells from patients with AML. Downregulation of IL16 promotes degradation of mutant TP53 and induces apoptosis, thereby increasing the sensitivity of AML cells to various chemotherapeutic agents in vitro.

INTRODUCTION

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy with poor prognostic outcomes and significant treatment challenges.¹ Current therapeutic approaches primarily include chemotherapy, allogeneic hematopoietic stem cell (HSC) transplantation, and targeted small-molecule therapies. The National Cancer Institute estimates that around 20,000 individuals will be diagnosed with AML in 2023, and approximately 10,000 will die from AML-related complications.² Survival and prognosis for patients with AML are improving as existing treatment options continue to be optimized and with the advent of chimeric antigen receptor T-cell immunotherapy. However, some patients still have difficulty achieving a complete response (CR), and relapse after CR or develop chemotherapy resistance; therefore, there is an urgent need to discover effective targets for targeted therapy.

Interleukin 16 (IL16) is an independent proinflammatory cytokine.^{3, 4} It is synthesized as a precursor protein, pro-IL16, with an apparent molecular weight of 80 kDa. Following various cellular stimuli, pro-IL16 is cleaved by caspase 3 (CASP3) into a secreted carboxyl-terminal peptide with a molecular weight of 17 kDa and an amino-terminal 60 kDa prestructural domain.^{5, 6, 7} The former is the functional extracellular IL16, whereas the latter enters the nucleus and influences the cell cycle. It is primarily secreted by activated CD8⁺ T lymphocytes, mast cells, and macrophages.⁸IL16 is secreted into plasma as a ligand for CD4/CD9 and functions as a chemokine, growth factor, and differentiation factor for a variety of hematopoietic cell types involved in specific autoimmune and inflammatory responses.⁹ Its function is largely dependent on surface expression and signaling through CD4⁺ cells.^{10, 11, 12}

In multiple hematological oncology studies, IL16 has been characterized as a proinflammatory cytokine involved in immune dysregulation in patients with hematologic malignancies. In patients with diffuse large B-cell lymphoma, IL16 has been shown to be a biological marker of treatment response.¹³ Single-cell transcriptomic profiling of mixed phenotype acute leukemia samples revealed notable activation of IL16 signaling pathways, along with cytokine–cytokine receptor interactions and interferon-alpha signaling via the Janus kinase-signal transducer and activator of transcription pathway axis in relapsed cases. These data implicate these pathways in leukemogenesis and are correlated with adverse clinical outcomes.^{14, 15, 16} These findings indicate that IL16 may influence the tumor immune microenvironment in hematologic malignancies by promoting the expression of inflammation-related pathways and may be associated with stress, drug resistance, and poor prognosis. While IL16 has been investigated in various hematologic malignancies, existing research has predominantly focused on lymphomas, which are tumors of lymphoid origin. In contrast, its functional significance in AML, a malignancy arising from the myeloid lineage, remains poorly defined. Given the distinct cellular origins and pathobiology of AML, we hypothesize that IL16 contributes to chemotherapy resistance in this disease. To test this hypothesis, we designed the present study to elucidate the role and mechanism of IL16 in AML drug resistance.

MATERIALS AND METHODS

Bioinformatics analysis

The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) RNA-seq data with AML were acquired from The University of California, Santa Cruz (UCSC) Xena database (Table 1). A preliminary analysis of the differential expression of the IL16 gene in the TCGA database was performed using the gene expression profiling interactive analysis 2 (GEPIA2) online platform.¹⁷ AML transcriptome datasets from TCGA and TARGET were downloaded from the UCSC Xena database, and the clinical features were plotted in R. Statistical mapping for survival analysis was performed using GraphPad Prism software, and correlation analysis in R (R > 0.4) was used to filter relevant genes.¹⁸ Gene function was then analyzed using the Metascape database, including enrichment and gene set enrichment analysis (GSEA) analysis.¹⁹ The GSE116256 single-cell transcriptome dataset was downloaded from the Gene Expression Omnibus (GEO) database.²⁰

TABLE 1. RNA-seq Data and Corresponding Clinical Information for AML were Obtained From the UCSC Xena Database, Including Datasets from TCGA and TARGET.

Dataset name	Database source	Data types	Number of samples
TARGET_LAML	UCSC Xena	Gene expression RNA-seq and clinical information	190
TCGA_LAML	UCSC Xena	Gene expression RNA-seq and clinical information	132
GSE116256	GEO	Single-cell RNA-seq	20

TCGA, The Cancer Genome Atlas; TARGET, Therapeutically Applicable Research to Generate Effective Treatments; USCS, University of Cingifornia Sisha Cruz; GEO, Gene Expression Omnibus; AML, acute myeloid leukemia.

Cell lines and culture conditions

AML cell lines (HL60, HEL, NB4, and THP1) were purchased from the Cell Bank of the Chinese Academy of Sciences. Cells were cultured in Roswell Park Memorial Institute 1640 medium with 10% FBS (HyClone; Cytiva) and maintained at 37 °C in a humidified incubator with 5% CO₂.

Construction of IL16 knockdown AML cell lines in vitro

AML cells were transduced using lentiviral infection. IL16 scramble, sh1, sh2, and sh3 lentiviruses were purchased from Cyagen (Cyagen US Inc., CA, USA). The target sequences were: sh1: GTTCTGGATGAAGCAACATTA; sh2: CCAGTGATGTTTCTGTAGAAT; sh3: CCAATGGCACTCCCAAAGTTT.

Western blot analysis

Cells were lysed in RIPA lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China), and protein concentration was determined using a bicinchoninic acid protein assay Kit. Proteins were separated on 10% and 12% sodium dodecyl sulfate-polyacrylamide gel electrophoresis gels and transferred to polyvinylidene fluoride membranes (EMD Millipore, USA) blocked with 5% skim milk. Membranes were incubated overnight with primary antibodies, followed by secondary antibodies for 1 hour at room temperature. Protein bands were visualized using ECL solution.

RT-qPCR

RNA was extracted using TRIzol® reagent, and cDNA was synthesized from each RNA sample using the PrimeScript™ RT reagent Kit. Quantitative polymerase chain reaction (PCR) was performed using iQ™ SYBR® Green Supermix on the CFX384 Real-Time System (both from Bio-Rad Laboratories, Inc., Shanghai, China). The mRNA expression levels of IL16 and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were quantified using the following primers: IL16 forward: CAAGGAAGGGGCATCTCCAA, reverse: AGCTCTGAAAGGTTGAGCGA; GAPDH forward: AGGGGCCATCCACAGTCTT, reverse: AGCCAAAAGGGTCATCATCTCT. The relative expression ratio was calculated using the 2^–ΔΔCq method.

Cell proliferation assay

Cell proliferation was measured using the Cell Counting Kit-8 (CCK-8; TransGen Biotech Co., Ltd., Beijing, China) according to the manufacturer’s instructions. Cells were seeded at 1,000 cells per well in 96-well plates. 10 μL of CCK-8 solution was added every 24 hours, followed by a 2-hour incubation. Absorbance was measured at 450 nm.

Mitochondrial membrane potential assay

To assess early apoptosis, mitochondrial membrane potential was measured in IL16-knockdown AML cells using JC-1 staining after azacitidine (AZA) treatment. The depolarization ratio was calculated as the green/red fluorescence intensity ratio using confocal microscopy.

Cell cytotoxicity assay

Cytotoxicity was assessed using a CCK-8 assay. Cells seeded in 96-well plates were treated with various drugs for 48 hours. After adding CCK-8 and incubating for 2 hours, absorbance at 450 nm was measured to determine cell viability. Data from three independent experiments were analyzed using GraphPad Prism 8.

Nested PCR

Amplification of HL60 and THP1 cDNA for TP53 mutations was performed using nested PCR. The first round of PCR was conducted with forward primer CCCCTCTGAGTCAGGAAACA and reverse primer TTATGGCGGGGAGGTAGACTG. The second round of PCR used forward primers GTCCCAAGCAATGGGATGATT and TGGCCATCTACAAGCAGTCA, and reverse primers CATAGGGCACCACCACACTA and TGAGTTCCAAGGCCTCATTC. PCR products were analyzed by agarose gel electrophoresis to confirm the expected band size, and correctly sized bands were sent to Sangon Biotech for sequencing and sequence analysis.

Cycloheximide (CHX) pulse-chase assay

The half-life of mutant TP53 proteins was investigated using a cycloheximide (CHX) pulse-chase assay.²¹ Cells were transfected with scramble shRNAs or shIL16. Seventy-two hours after transfection, cells were treated with CHX (100 μg/mL) for 0, 6, 12, 24, 40, and 48 hours. Mutant TP53 protein levels were analyzed by Western blot using an anti-TP53 antibody.

Statistical analysis

All statistical analyses were conducted using R version 4.5.2 (with the Seurat, tidyverse, multtest, dplyr, ggplot2, and patchwork packages) and GraphPad Prism. Data are presented as mean ± standard deviation, unless otherwise indicated. A two-sided p value < 0.05 was considered statistically significant. Kaplan–Meier survival curves were generated based on overall survival data. Differences between survival curves (high vs. low IL16 expression groups) were assessed using the log-rank test. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated from univariate Cox proportional hazards models. Associations between continuous variables were evaluated using Pearson’s correlation coefficient. Cell viability data from CCK-8 assays across a range of drug concentrations were fitted to a non-linear regression model in GraphPad Prism. IC₅₀ values and their 95% CI were interpolated from the fitted curves. Statistical comparisons of IC₅₀ values between groups were performed using an extra sum-of-squares F test. Transcriptome sequencing and primary bioinformatic analyses were performed by Sangon Biotech Co. (Service Contract No. MRNA236020GZ). GSEA was performed using GSEA software v4.3.2. RNA-seq and GSEA results were evaluated using the normalized enrichment score and false discovery rate (FDR) q value, with FDR q < 0.05 used to identify significantly enriched biological pathways. For hypothesis-driven validation experiments (western blot, RT-qPCR, and cell cytotoxicity assays) that tested a limited set of predefined targets, nominal p values were used without adjustment for multiple comparisons. Comparisons between two groups were preceded by normality assessment using the Shapiro–Wilk test. However, we acknowledge that, with very small sample sizes, the power of normality tests is limited, and results should be interpreted with caution. Sample sizes were determined based on standard criteria routinely used to detect reproducible biological effects.

RESULTS

IL16 expression is upregulated and associated with poor prognosis in AML

GEPIA2 pan-cancer bioinformatics analysis revealed that the IL16 gene is highly expressed in AML (Figure 1a, b). Further analysis of transcriptomic data from AML patients in the TCGA and TARGET datasets, obtained via the UCSC Xena database, showed that biological functions positively correlated with IL16 expression (R > 0.4) were primarily enriched in the regulation of T-cell activity, immune responses, and cytokine-chemokine signaling. Functional enrichment analyses based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) further indicated that IL16 expression is positively associated with immune modulation as well as cytokine and chemokine regulatory pathways (Figure 1c, d). Based on IL16 expression levels and the survival outcomes and clinical characteristics of patients in the TCGA and TARGET AML transcriptomic datasets, we classified AML patients into high-expression and low-expression groups. Analysis of the TCGA and TARGET databases confirmed that age at diagnosis was a universal and stable independent adverse prognostic factor (TCGA: HR = 1.03, 95% CI: 1.02–1.05, p < 0.001; TARGET: HR = 1.06, 95% CI: 1.02–1.10, p = 0.004). The established disease risk stratification systems also demonstrated strong prognostic predictive ability in this study. For example, compared with the low-risk group, the death risk of the high-risk group was significantly increased (TARGET: HR = 4.56, 95% CI: 1.44–14.47, p = 0.01). In cytogenetic analysis, compared with the good-risk group, the unclassified (not otherwise specified) risk group had an extremely high-risk (HR = 27.73, 95% CI: 5.37–143.27, p < 0.001), although this result should be interpreted cautiously due to its wide CI. Notably, high IL16 expression showed a hazard ratio associated with an adverse survival trend in both cohorts (TCGA HR = 1.17, 95% CI: 0.71–1.94, p = 0.533; TARGET HR = 1.41, 95% CI: 0.92–2.17, p = 0.115), but none reached statistical significance (p > 0.05). This suggests that IL16 may be a potential biomarker, warranting further investigation with a larger sample size (Supplementary Table 1). IL16 expression in TCGA and TARGET AML transcriptome data was divided into high- and low-expression groups and further analyzed using GSEA software. Our study revealed significant enrichment of immunosuppressive, cytokine, and chemokine pathways in the high-expression group (p < 0.01, FDR q value < 0.01, NES > 2), indicating that these pathways are activated with increased IL16 expression (Supplementary Figure 1a).

Figure 1.

IL16 gene is highly expressed in AML patients, with higher expression levels correlating with poorer prognosis. (a, b) GEPIA2 online bioinformatic analysis demonstrates elevated IL16 gene expression across various malignant tumors. (c, d) Correlation analysis was conducted using the R programming language to identify related genes (R > 0.4), followed by gene function enrichment analysis using the Metascape database. (e) Kaplan–Meier curves showing outcomes of AML patients from the TCGA and TARGET. Scatterplots were used to reflect the survival of AML patients. Heat maps were used to reflect clinical information about AML patients in the TCGA (n = 132) and TARGET (n = 190) datasets. (TCGA HR = 1.17, 95% CI: 0.71 - 1.94, p = 0.533; TARGET HR = 1.41, 95% CI: 0.92 - 2.17, p = 0.115).

IL16, interleukin 16; AML, acute myeloid leukemia; GEPIA2, gene expression profiling interactive analysis 2; HR, hazard ratio; CI, confidence interval; TCGA, The Cancer Genome Atlas; TARGET, Therapeutically Applicable Research to Generate Effective Treatments.

The IL16 gene is predominantly expressed in malignant tumor cells of AML patients

We obtained the single-cell RNA sequencing dataset GSE116256 from the GEO database. Cell clustering and annotation were performed using the Human Primary Cell Atlas as a reference. Columnar percentages of various cell types in normal HSCs and AML patient HSCs were compared, revealing a significant increase in myeloid cells in AML HSCs. Subsequent analysis of IL16-expressing HSCs revealed a predominance of malignant tumor cells (Figure 2a, b). Additionally, the expression of the known IL16 ligand, CD4, was mainly observed in monocytes within AML HSCs. Further analysis indicated that IL16-expressing cell subpopulations were primarily T cells, monocytes, monocyte precursors, and granular monocyte precursors (Figure 2c, d). Subpopulations of HSCs expressing IL16 showed significantly elevated expression in malignant HSCs, malignant progenitor cells (Prog), and malignant granulocyte-macrophage progenitor cells, with notable statistical differences (Figure 2b). We then assessed IL16 expression at both the mRNA and protein levels in four AML cell lines (NB4, HL60, THP1, and HEL). HEL exhibited the highest mRNA expression, whereas HL60 showed the lowest. At the protein level, NB4 had the highest IL16 expression, while HEL had the lowest. Only NB4 displayed a distinct band at 16 kDa, whereas no corresponding bands were observed in the other cell lines under normal culture conditions without external stimuli (Figure 2e). The inconsistent mRNA and protein expression levels observed among the four AML cell lines may be attributed to distinct post-transcriptional modifications regulated differently in each cell line.

Figure 2.

The IL16 gene is predominantly expressed in malignant tumor cells of AML patients. (a) Based on the HPCA database for clustering and annotation, the columnar occupancy of different cells was plotted for 4 normal donors and 16 AML patients. (b) Histogram of differences between presumed normal hematopoietic stem cells (PreHSC n = 783) and malignant hematopoietic stem cells (MHSC n = 880) expressing IL16 under different clusters. Mann-Whitney test *p < 0.05 **p < 0.01. (c) UMAP projection of BM cells from nine patients with sixteen AMLs and four HDs, showing the formation of 22 main clusters. (d) UMAP projection of IL16-BM cells from bone marrow cells expressing IL16, showing the formation of 17 main clusters. (e) RT-qPCR and western blot detection of IL16 in AML cell lines NB4 HL60 THP1 HEL. (f) mRNA and Protein expression levels were detected by RT-qPCR and Western blot after 0, 6, 12, 24 and 48 h co-incubation of AZA and AML cell lines HL60 and THP1. IL16, interleukin 16; AML, acute myeloid leukemia; BM, bone marrow; RT-qPCR, reverse transcription quantitative polymerase chain reaction; AZA, azacitidine.

Chemotherapeutic drugs induce IL16 mRNA expression and promote cleavage of the IL16 precursor in AML cells

Two AML cell lines, HL60 and THP1, were treated with the chemotherapeutic drug AZA at 10 μM, which induced apoptosis. Following treatment, IL16 mRNA expression was upregulated, and 16 kDa active IL16 was detected by Western blot at 24 and 48 h, suggesting that apoptosis in AML cells may trigger CASP3-mediated cleavage of precursor IL16. This process leads to the release of active IL16 along with apoptotic cells (Figure 2f). Previous studies have indicated that in CD8+ T lymphocytes, the IL16 precursor is cleaved by CASP3 into a C-terminal domain of approximately 17 kDa and an N-terminal domain of 60 kDa. The C-terminal domain forms a mature IL16 monomer of 130 amino acid residues, which is secreted extracellularly and covalently polymerized to form a biologically active homotetramer. These data suggest that a similar mechanism may exist in AML cells. In AML patients, malignant tumor cells predominantly accumulate in the myeloid lineage rather than the lymphoid lineage. Literature indicates that current research on IL16 primarily focuses on the lymphoid lineage. Our study further found that functional IL16 can be released from tumor cells along with apoptosis when stimulated by chemotherapeutic drugs. Based on these observations, we hypothesize that IL16 can serve as a biomarker of aggressive disease in AML and may be involved in chemotherapy resistance.

Downregulation of IL16 promotes chemotherapy-induced apoptosis in AML cell lines

We established stable IL16 knockdown cell lines, along with scramble controls, in HL60 and THP1 cells using lentiviral infection. The knockdown efficiency of IL16 was verified at both mRNA and protein levels, confirming the efficacy of the shRNA1 construct (Figure 3a, b). Functional assays were then conducted using the knockdown and scramble cell lines.

Figure 3.

Downregulation of IL16 expression promotes chemotherapy-induced apoptosis in AML cell lines. (a, b) mRNA and protein levels of IL16 in AML cells (THP1 and HL60) transfected with vector scramble or IL16 shRNA were quantified by RT-qPCR and western blot analysis, respectively. Bar chart shows mRNA expression of scramble and IL16 shRNA expressing. (c) Proliferation curves of THP1 scramble and IL16 shRNA cell lines. At 24 h (p = 0.00086), 48 h (p = 0.000034), 72 h (p = 0.000034), and 96 h (p = 0.000007). (d) HL60 and THP1 IL16 shRNA and scramble groups cells were separately treated with AZA for 24 h then mitochondrial membrane potential (JC‐1) was measured by confocal microscopy (×100 uM). Red fluorescence means normal cells. Green fluorescence cells indicate loss of mitochondrial membrane potential. (e) Bar charts show expression levels as JC‐1 Green/Red intensity with mean ± SD, n = 5, 5 randomly selected fields of view. Mann-Whitney U test *p < 0.05 **p < 0.01, ***p < 0.001.

IL16, interleukin 16; AML, acute myeloid leukemia; AZA, azacitidine; SD, standard deviation; RT-qPCR, reverse transcription quantitative polymerase chain reaction.

The CCK8 proliferation assay revealed a significant decrease in cell viability at 24, 48, 72, and 96 h in the knockdown group compared with the scramble control in THP1 cells, whereas no significant differences were observed in HL60 cells (Figure 3c). After 24 h of coincubation with AZA, mitochondrial membrane potential was assessed in HL60 and THP1 cells. A significant decrease in mitochondrial membrane potential was observed in IL16 knockdown cells compared with scramble controls. This reduction, indicative of early apoptosis, suggests that IL16 downregulation may enhance early apoptosis in AZA-treated cells (Figure 3d, e). Given these findings, it is valuable to investigate whether IL16 knockdown can also enhance apoptosis in response to other commonly used clinical chemotherapeutic agents, potentially overcoming resistance in AML cells.

Knockdown of IL16 overcome chemotherapy resistance in AML cells

To assess the role of IL16 in chemotherapy-induced apoptosis, scramble control and IL16-shRNA HL60 and THP1 cells were treated with a range of concentrations of four chemotherapeutic agents: Ara-C, Ida, AZA, and Ven. IL16 knockdown significantly reduced cell viability across multiple drug concentrations in both cell lines compared with controls. Furthermore, the IC₅₀ for cell viability was markedly lower in IL16-deficient cells, indicating enhanced chemosensitivity (Figure 4a, Supplementary Table 2). Ara-C, Ida, AZA, and Ven are commonly used in the clinical treatment of AML and play critical roles in patient management. Our experimental data indicate that IL16 may contribute to AML tumor cell resistance to various chemotherapeutic drugs. Subsequently, HL60 and THP1 cells in both the scramble and knockdown groups were treated with AZA at 10 μM for 0, 12, 24, and 48 h to assess the expression of apoptosis-related molecules via Western blot. Compared with controls, cleaved CASP3 (cCASP3) expression in HL60 cells significantly increased at different time points after treatment, with similar results observed in THP1 cells (Figure 4b). HL60 and THP1 cells were also treated with the targeted drug Ven. Compared with controls, cCASP3 levels significantly increased at different time points. Additionally, PARP cleavage, a marker of apoptosis, was significantly enhanced after Ven treatment. Notably, the degree of PARP cleavage in IL16-deficient cells was significantly higher than in controls at 6 and 12 h, further confirming the enhanced induction of apoptosis following IL16 knockout (Figure 4c). Chemotherapy-induced apoptosis was evaluated using multiple complementary assays, including mitochondrial membrane potential measurement, CCK-8 cytotoxicity testing, and Western blot analysis of apoptosis-related proteins. All methods consistently demonstrated an enhanced apoptotic trend following IL16 knockdown in both cell lines. These results suggest that IL16 downregulation potentiates chemotherapy-induced apoptosis in vitro.

Figure 4.

Knockdown of IL16 may overcome resistance of AML cells to multiple chemotherapeutic drugs. THP1 and HL60 cells were transfected with IL16 shRNA constructs to knockdown IL16 expression. (a) Sigmoid curves showing IC₅₀ of different chemotherapeutic drugs after 48 h in scramble and IL16-shRNA transfected cells. Bar graphs showing the percentage of apoptotic and surviving cells at different drug concentrations with mean values ± SD, n = 3. (b) Western blot analysis of TP53, BAX, cleaved caspase 9 (C C9) and cleaved caspase 3 (C C3) was carried out on scramble and IL16-shRNA transfected THP1 and HL60 cells after AZA treatment. Bar charts show expressed as cleaved caspase/β-actin intensity with mean ± SD, n = 3. (c) Western blot analysis of TP53, PARP/cleaved PARP, BAX, C C9 and C C3 was carried out on scramble and IL16-shRNA transfected HL60 cells and THP1 cell after Ven treatment. Bar charts show expressed as cleaved caspase β-actin intensity with mean ± SD, n = 3. Mann-Whitney U test *p < 0.05, **p < 0.01, ***p < 0.001. (d) Volcano plot of differentially expressed genes between HL60-shScramble and HL60-shRNA1. (e, f) Annotation of KEGG pathway and KOG of the differentially expressed gene between HL60-shScramble and HL60-shRNA1. p value < 0.05, Q value < 0.05).

IL16, interleukin 16; AML, acute myeloid leukemia; AZA, azacitidine; SD, standard deviation; KEGG, Kyoto Encyclopedia of Genes and Genomes; KOG, Clusters of Orthologous Groups; AML, acute myeloid leukemia.

Downregulation of IL16 affects multiple biological processes in AML cells

To further elucidate the mechanisms underlying IL16 downregulation as a strategy to overcome chemoresistance, transcriptome sequencing was performed on HL60 cells transfected with scramble or IL16-shRNA, followed by bioinformatic analysis. Differential gene expression analysis revealed that IL16 knockdown resulted in 642 upregulated and 1,779 downregulated genes compared with the scramble control group (Figure 4d). KEGG pathway analysis showed that the affected functions were mainly enriched in the P53 pathway, apoptosis pathway, mitochondrial autophagy pathway, and MAPK pathway (Figure 4e). KOG analysis indicated that the differentially expressed genes were primarily associated with cell motility, signal transduction mechanisms, and cell cycle control, cell division, and chromosome partitioning (Figure 4f). Given the clinically observed association between TP53 mutations and poor therapeutic outcomes, including frequent chemotherapy resistance, we hypothesized that IL16 contributes to chemoresistance by modulating the stability of mutant TP53 protein. To explore this mechanistic correlation, we designed subsequent molecular experiments for verification.

Downregulation of IL16 expression reduces the half-life of mutant TP53 proteins

Due to the critical role of mutant TP53 accumulation in chemotherapy resistance, the interaction between IL16 and the P53 signaling pathway was further investigated. Nested PCR amplification was initially performed to confirm sequence alignment with predicted size ranges, followed by sequencing (Figure 5a). The wild-type TP53 reference sequence NM_000546 from National Center for Biotechnology Information was used, and SNAPGENE software was employed for sequence analysis. Multisite TP53 mutations were identified in HL60 and THP1 cells, with mutated amino acid positions at 72, 175, 218, 348, and 349. Specifically, a 46-base pair deletion at position 175 was observed in HL60 cells, whereas a 26-base pair deletion at the same position was detected in THP1 cells, potentially leading to frameshift mutations (Figure 5b). Sequence comparison indicated that the mutant TP53 in THP1 aligns with previous reports (GenBank: JN601516.1), whereas the mutant TP53 in HL60 is novel. THP1 cells were then coincubated with chemotherapeutic drugs, and Western blot analysis was performed to monitor mutant TP53 accumulation (Figure 5c). Protein samples from scramble and IL16 knockdown cells were collected at six time points and analyzed for mutant TP53 expression. The results showed that mutant TP53 expression began to decrease from 12 h onward. Gray-scale analysis of Western blots revealed a significant decrease in mutant TP53 in HL60-IL16-shRNA cells at multiple time points and in THP1-IL16-shRNA cells at specific time points compared with scramble controls. The half-life of mutant TP53 in IL16 knockdown cells was 40 h, whereas no significant reduction was observed in scramble controls (Figure 5d, e). These findings provide preliminary evidence that IL16 knockdown promotes mutant TP53 degradation in vitro. Nevertheless, the precise molecular mechanisms through which IL16 regulates mutant TP53 stability remain to be elucidated and warrant further investigation.

Figure 5.

Downregulation of IL16 reduces the half-life of mutant TP53 proteins. (a) Nested PCR showed p53 in HL60 and THP1. (b) Sequence comparison of P53 with wild-type P53 from HL60 and THP1 cell lines using SNAPGENE software. (c) Mut P53 Protein expression levels were detected by Western blot after 0, 8, 18, 24 and 48 h co-incubation of Ida in THP1, Mut TP53/β-actin intensity with mean ± SD, n = 3. (d, e) Western blot analysis of Mut P53 was carried out on scramble and IL16 construct transfected HL60 (d) and THP1 (e) cells after Cycloheximide, CHX (100ug/mL) treatment. Bar charts show expressed as Mut P53/β-actin intensity with mean ± SD, n = 3. Mann-Whitney U test *p < 0.05, **p < 0.01, ***p < 0.001.

IL16, interleukin 16; SD, standard deviation; PCR, polymerase chain reaction.

DISCUSSION

Cytokine therapy is a novel therapeutic approach that modulates the plasma concentration of cytokines, thereby enhancing the activity of relevant cell subpopulations and promoting the cytotoxic effect on AML tumor cells.^{22, 23, 24} IL16 has been reported to stimulate the migration of Tregs and T cells toward Foxp3-positive/negative cells.²⁵ T-cell differentiation toward Foxp3(+) Treg cells may contribute to the dysregulation of myeloid cell subset ratios and immune tolerance observed in chemotherapy-resistant patients with relapsed/refractory AML, a process potentially driven by the release of IL16 from apoptotic AML tumor cells.²⁶

Our bioinformatic analysis demonstrated widespread IL16 expression in malignant cells from AML patients. Correlation analysis revealed that genes positively associated with IL16 expression were predominantly enriched in B- and T-cell immunoregulation, cytokine signaling, and chemokine pathways. Elevated IL16 expression was linked to the activation of immunosuppressive pathways, including those involving cytokines and chemokines. Although IL16 expression was not significantly associated with overall survival in the analyzed datasets, a modest, non-significant increase in mortality risk was observed among patients with high IL16 expression levels. Detection of IL16 mRNA and protein expression in four AML cell lines in vitro revealed variable expression levels, with notable discrepancies between mRNA and protein. Given the pronounced heterogeneity of AML, this inconsistency may reflect differential post-transcriptional regulatory mechanisms operating in distinct cell populations. To further explore IL16’s functional role, stable IL16-knockdown cell lines were established using shRNA interference. Mitochondrial membrane potential assays demonstrated that IL16 knockdown in HL60 and THP1 cells caused a more pronounced decrease in mitochondrial membrane potential compared with controls. As a decline in mitochondrial membrane potential is an early marker of apoptosis, these findings suggest that IL16 downregulation enhances early apoptosis induced by AZA. Transcriptomic sequencing and bioinformatic analysis indicated that these effects are primarily mediated through modulation of the TP53 pathway. Mutant TP53 is a significant prognostic indicator in AML, with studies reporting a prevalence of TP53 mutations in hematological malignancies, particularly in AML patients, of approximately 76%.²⁷ The TP53 R248Q hotspot mutation is frequently observed in AML and is strongly associated with poor prognosis; most patients harboring this mutation succumb to the disease within months despite intensive anti-leukemic therapy.²⁸ Clinically employed chemotherapeutic agents have been observed to promote mutant TP53 accumulation in THP1 cells, enhancing tumor cell drug resistance. Additionally, our findings demonstrate a significantly reduced half-life of mutant TP53 protein in IL16 knockdown cells compared with controls, suggesting that IL16 downregulation facilitates mutant TP53 degradation and may overcome chemotherapy resistance in AML cells.^{29, 30}

Nevertheless, this study has several limitations. Functional data were derived from in vitro models, which cannot fully recapitulate the in vivo tumor environment. The precise molecular mechanism by which IL16 stabilizes mutant TP53 remains unclear. Future studies using primary patient samples, animal models, and clinical cohorts are essential to assess the therapeutic potential of targeting this pathway. Additionally, due to the modest sample size and lack of formal power analysis, the statistical power of the study is limited, and the findings should be interpreted as exploratory observations that warrant validation in larger cohorts. In summary, chemotherapy-induced apoptosis in AML cells is accompanied by upregulation and release of active IL16. Targeting IL16 enhances apoptosis via mechanisms involving the TP53 pathway and may overcome multiple forms of chemotherapy resistance.

Supplementary Materials

Supplementary Figure

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Supplementary Tables

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