Expression of ALKBH3 and its effects on proliferation, migration, and invasion of lung adenocarcinoma A549 cells: bioinformatics analysis and in vitro and in vivo experiments
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Abstract
Objective: To use bioinformatics analysis and in vitro and in vivo experiments to study the biological role of ALKBH3 in lung adenocarcinoma.
Methods: Bioinformatics analysis of ALKBH3 was performed using databases. ALKBH3 expression in lung adenocarcinoma and adjacent tissues was detected by qPCR (quantitative polymerase chain reaction), western blotting, and immunohistochemistry. Stable transformed A549 cells with low expression of ALKBH3 were constructed. The effects of knockdown of ALKBH3 on the proliferation, migration, and invasion of lung adenocarcinoma A549 cells were detected by CCK-8, cell scratch, and transwell invasion assays, respectively. The effects of ALKBH3 on the proliferation of A549 cells in vivo were detected using subcutaneous tumorigenesis in nude mice.
Results: Bioinformatics analysis showed that ALKBH3 has diagnostic value in tumors such as lung adenocarcinoma, the expression of ALKBH3 is related to immune cell infiltration, ALKBH3 interacts with ASCC family molecules, and ALKBH3 is involved in the demethylation of DNA and RNA. The expression of ALKBH3 in lung adenocarcinoma was higher than that in adjacent tissues (P < 0.05). CCK-8, wound healing and transwell assays showed that ALKBH3 knockdown significantly inhibited the proliferation, migration, and invasion of A549 cells in vitro (P < 0.01). ALKBH3 knockdown also significantly inhibited the growth of subcutaneous tumors in nude mice (P < 0.01).
Conclusions: ALKBH3 is a potential diagnostic marker for lung adenocarcinoma. Results in vivo and in vitro showed that knocking down ALKBH3 could inhibit the proliferation, migration, invasion, and subcutaneous tumorigenesis of lung adenocarcinoma A549 cells.
Keywords
INTRODUCTION
Among all malignant tumors, lung cancer, particularly lung adenocarcinoma, has the highest mortality and morbidity rates[1]. There are a variety of treatments available for lung cancer, including surgery, chemotherapy, radiotherapy, molecular targeted therapy, and immunotherapy. In patients with advanced lung cancer, the overall treatment effect is still unsatisfactory, resulting in a 5-year survival rate of less than 20% due to tumor proliferation and distant metastasis[2,3]. In this regard, there is a need to elucidate more fully the molecular mechanisms underlying lung cancer proliferation and metastasis in order to develop new treatment strategies.
Epigenetic dysregulation, a common feature of human cancers, promotes tumorigenesis and the maintenance of malignant phenotypes by regulating gene expression[4]. Epigenetic modification includes the chemical modification of DNA, proteins, and RNA. RNA epigenetic modification is the regulation mode at the post-transcriptional level[5,6]. As the most common and important pair of epigenetic modifications, methylation and demethylation regulate tumorigenesis, tumor development, migration, and invasion of tumor cells, which have attracted people’s attention[7-9]. Alpha-ketoglutarate-dependent dioxygenase homolog 3 (ALKBH3) is a recently discovered novel M6A demethylase belonging to the ALKB family. It has important roles in protecting cells from DNA damage and regulating gene expression and protein translation[10-13], as well as in maintaining genomic stability and regulating RNA transcription, and its abnormal expression and function have been implicated in the occurrence of many cancers[13,14]. Lu et al. found that enhancing the stability of ALKBH3 mRNA could promote proliferation and invasion of hepatocellular carcinoma cells[15]. In addition, Woo and Chambers found that overexpression of ALKBH3 increased the invasion of ovarian and breast cancer cells[16]. ALKBH3 has also been shown to accelerate the survival, angiogenesis, and invasion of urothelial carcinomas[17]. Tasaki et al. found that ALKBH3 significantly contributes to lung adenocarcinoma cancer cell survival through in vivo experiments[18]. Although previous studies have elucidated some functions and implications of ALKBH3 in cancer cells, the role and significance of ALKBH3 in lung adenocarcinoma cells in vitro remain largely unexplored. Furthermore, the function and significance of ALKBH3 in lung adenocarcinoma cells were further validated through the transplantation of tumor cells at various sites in nude mice.
We began by analyzing ALKBH3 expression in lung adenocarcinoma and pan-cancer tissues to determine its effects on biological behaviors. Furthermore, we investigated the relationship between ALKBH3 expression and immune infiltration, as well as genetic changes and epigenetic status. The study utilized lung adenocarcinoma tissue, normal lung tissue, a lung adenocarcinoma tissue microarray, the lung adenocarcinoma A549 cell line, and nude mice. First, ALKBH3 expression was assessed using western blotting, real-time quantitative polymerase chain reaction (RT-qPCR), and immunohistochemistry (IHC). Next, a stable transformed cell line consisting of lung adenocarcinoma A549 cells with low ALKBH3 expression was constructed. Through CCK-8 assays in vitro, transwell and cell scratch assays, and subcutaneous tumorigenesis experiments in nude mice, we found ALKBH3 could inhibit lung adenocarcinoma A549 cell proliferation, migration, and invasion.
MATERIALS AND METHODS
Bioinformatics analysis
ALKBH3 expression levels
Differences in gene expression were analyzed using the Assistant for Clinical Bioinformatics website
ALKBH3 expression and immune cell infiltration
TIMER2.0 (http://timer.cistrome.org/) is an online database that provides comprehensive data on the immune cells that are infiltrating tumors. In this study, we used the “Immune” and “Exploration” modules in TIMER2.0 to analyze the correlations between ALKBH3 expression levels and immune cell infiltration levels, EGFR expression levels, and mutation status in lung adenocarcinoma.
Based on expression data, the European Prospective Investigation into Cancer and Nutrition (EPIC)[19]
Protein-protein interaction network analysis
GeneMANIA, an online database for protein-protein interaction networks developed by the University of Toronto[20-22], was used to explore the protein molecules that interact and are co-expressed with ALKBH3 in lung adenocarcinoma and to predict the functions of target genes.
Mutations and epigenetic alterations
The cBioPortal enables the analysis and interpretation of cancer genetic data and facilitates the interpretation of molecular data obtained from cancer histological and cytological studies[23]
ALKBH3 promoter DNA methylation levels in normal and pan-cancer tissues were examined using UALCAN (http://ualcan.path.uab.edu/analysis.html)[24]. DNA methylation levels are represented by beta values, indicating hypomethylation (beta: 0.3-0.25) or hypermethylation (beta: 0.7-0.5)[25].
Tissue experiments in lung adenocarcinoma
Clinical sample
Patients at Suining Central Hospital in 2023 who had not received any antineoplastic therapy (including radiotherapy, chemotherapy, targeted therapy, and immunotherapy) were enrolled, and 16 pairs of fresh lung adenocarcinoma tissues and adjacent tissues (further than 3 cm from the tumor margin) were collected. ALKBH3 protein and mRNA expression levels were measured by western blotting and RT-qPCR. The Ethics Committee of Suining Central Hospital approved this study (approval number: KYLLKS20230109). A lung adenocarcinoma tissue chip (array number: HLugA180Su11; chip batch number: XT21-011) was used for IHC.
Real-time quantitative PCR
To isolate total RNA from tissues, TRIzol reagent was used. We used a reverse transcription kit to reverse transcribe RNA into cDNA and performed RT-qPCR according to the instructions provided with the RT-qPCR kit (Shenzhen Apuno Biomedical Technology Co., Ltd.). To calculate relative mRNA expression levels, GAPDH was used as a control gene. The primers used were as follows: GAPDH, GAAAGCCTGCCGGTGACTAA (positive) and TCACGTCAACAAAGCCAGGA (reverse); ALKBH3, AGCCACGAGTGATTGACAGA (positive) and TCACGTCAACAAAGCCAGGA (reverse).
Western blotting analysis
Frozen tissue samples were cracked with a strong PIPA cleavage solution and crushed with a homogenizer. Using the BCA method, the protein concentration was determined after low-temperature ultracentrifugation. In this study, proteins were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes (PVDF). After sealing with 5% skimmed milk powder, according to the instructions provided with the antibodies against ALKBH3 and
IHC analysis
The IHC staining experiments were carried out by RocheVentanaBenchMark at the Department of Pathology, Suining Central Hospital. The degree of positivity was determined based on the extent of color development: colorless, 0; light yellow, 1; light brown, 2; dark brown, 3. The scoring system was as follows: 5%, 0 points; 6%-25%, 1 point; 26%-50%, 2 points; 51%-75%, 3 points; > 75%, 4 points. For the product of the two fractions, 0-6 was considered to indicate low expression and > 6 to denote high expression.
Experiments with lung adenocarcinoma cell line A549
Cell line, culture, and transfection
A549 cells are one of the types of human lung adenocarcinoma cells. Due to their easy culture, clear genetic background, and stability, A549 cells have been widely used in cancer biology, gene function and toxicology studies, especially those related to lung adenocarcinoma. Therefore, A549 cells were selected for experiments in this study. Lung adenocarcinoma A549 cells were purchased from Wuhan Irrette Biotechnology Co., Ltd., cultured in RPMI1640 medium supplemented with fetal bovine serum and 1% penicillin-streptomycin, and preserved at 37 °C under 5% carbon dioxide. The lentiviruses used in this experiment were constructed and packaged by Shanghai Jikai Basic Technology Co., Ltd. Three different lentiviruses were used: Lv-ALKBH3-RNAi-1, Lv-ALKBH3-RNAi-2, and Lv-ALKBH3-RNAi-3. The lentivirus negative control was LVCON303 (hu6-mts-cbh-gcgfp-ires-purromycin). The experimental group was divided into a blank control group (culture of normal A549 cells), an empty vector control group (A549 cells transfected with negative control), knockdown group 1 (LV-ALKBH3-RNAi-1 transfection), knockdown group 2 (LV-ALKBH3-RNAi-2 transfection), and knockdown group 3 (LV-ALKBH3-RNAi-3 transfection).
A 1 mL cell suspension and 1 mL of culture medium were added to a 6-well plate, designating one well as the blank control group, which received only culture medium. Another well served as the negative control group, receiving empty carrier lentivirus, while the remaining well was assigned to the infected virus group, treated with ALKBH3 knockdown lentivirus. Following 72 h of infection, the cell fusion rate under the microscope reached approximately 80%, prompting immediate screening of the infected cells. The cells were subsequently cultured in the puromycin-containing medium at a concentration of 2 μg/mL. After 24 h of culture, all cells in the blank control group perished, whereas the remaining cells in the negative control and infected groups survived, resulting in a stable A549 cell line with ALKBH3 knockdown. Western blotting and real-time quantitative PCR were employed to assess the TPM4 knockout efficiency.
Cell proliferation test (CCK-8 assay)
The stable transformants of ALKBH3 knockdown group 1 (LV-ALKBH3-RNAi-1) and knockdown group 2 (LV-ALKBH3-RNAi-1) were detected by CCK-8 assay. For each group, three accessory wells were set up, and 100 μL phosphate-buffered saline (PBS) solution was added to the remaining well. After the cells adhered to the walls of the wells, fresh medium (100 mL) and CCK-8 reagent (10 mL) were added, and the plate was incubated at 37 °C, 5% CO2. The absorbance values of each hole were measured and recorded at 450 nm using an enzyme labeling instrument. The experiment was repeated three times, and a proliferation curve was constructed based on the results.
Cell scratch assay
A cell suspension of A549 cells with low ALKBH3 expression was diluted to a concentration of
Transwell invasion assay
Cell invasion was investigated using a transwell assay. The matrigel matrix was diluted with serum-free medium at a 1:8 ratio at 4 °C. Then, 60 μL of the diluted Matrigel matrix was dropped onto the polycarbonate film of each transwell chamber, and the apparatus was placed in a Matrigel incubator at
Subcutaneous tumorigenesis in nude mice
Logarithmic-phase A549 cells and A549 cells exhibiting low-level ALKBH3 expression were harvested and adjusted to a concentration of 1 × 107 cells/mL. Male nude mice, aged 6 to 8 weeks and procured from Guangzhou Kexun Biotechnology Co., LTD., were selected, excluding those with physical frailty, underlying diseases, or behavioral abnormalities. The mice were randomly assigned into three groups: the control group (n = 10), knockout group 1 (n = 10), and knockout group 2 (n = 10). Prior to subcutaneous injection, the injection site of the nude mice was disinfected with 75% ethanol. The cell suspension was gently agitated to ensure homogeneity, preventing aggregation and optimizing cell viability. Each mouse received a subcutaneous injection of 200 μL of cell suspension, containing 2 × 106 cells, into the anterior axillary region, chosen for its abundant blood supply. The growth of the mice was monitored continuously. Once subcutaneous tumors formed, the body weight and tumor volume of each mouse were recorded daily. Mice were euthanized upon the tumor reaching a volume of 1.5 × 103 mm3. The tumors were excised, weighed, and photographed against a white background using vernier calipers, facilitating the construction of a statistical analysis of tumor weight.
Statistical analysis
The statistical methods employed in the bioinformatics analysis are comprehensively described in the “Experimental Methods” section of this study. Continuous variable data are presented as Mean ± Standard Error of the Mean (Mean ± SEM). Tests for normality and homogeneity of variance were conducted to compare the means of two independent samples. When both assumptions were satisfied, a two-sample t-test was applied. In cases where homogeneity of variance was not satisfied, an approximate t-test or Mann-Whitney U test was used. One-way Analysis of Variance (ANOVA) was conducted for pairwise comparisons among multiple groups. For comparisons of two sample proportions, the χ² test or Fisher’s exact test was applied. The significance threshold for all statistical analyses in this study was set at α = 0.05. Statistical significance was denoted as follows: * for P < 0.05, ** for P < 0.01, *** for P < 0.001, and **** for
RESULTS
Bioinformatics analysis
TPM4 expression levels
First, we used the Clinical Bioinformatics Assistant website to analyze the gene expression differences of ALKBH3 in cancers including lung adenocarcinoma. For differential gene expression analysis, 516 tumor samples and 637 normal samples were obtained (59 paracancerous tissue samples from TCGA and 578 normal tissue samples from GTEx). The expression levels of ALKBH3 in the two groups of samples were analyzed using the R software package ggplot2. In lung adenocarcinoma tissues, ALKBH3 expression was significantly higher than in adjacent tissues [Figure 1A]. ALKBH3 levels were significantly elevated in CHOL (cholangiocarcinoma), COAD (Colon adenocarcinoma), GBM (Glioblastoma multiforme), HNSC (Head and Neck squamous cell carcinoma), KIRC (Kidney renal clear cell carcinoma), LIHC (Liver hepatocellular carcinoma), LUSC (Lung squamous cell carcinoma), PCPG (Pheochromocytoma and Paraganglioma), and PRAD (Prostate adenocarcinoma) based on the TCGA and GTEx datasets. By contrast, ALKBH3 was downregulated in BRCA and UCEC [Figure 1B].
Figure 1. ALKBH3 expression and immune cell infiltration. (A) Expression levels of ALKBH3 in adjacent tissues and tumor tissues based on Assistant for Clinical Bioinformatics (n = 1,153). (B) The expression of ALKBH3 in pan-cancer tissues based on TCGA data
Protein-protein interaction network analysis
Online databases were used to explore protein molecules that interact and co-express with ALKBH3 in lung adenocarcinoma and predict the functions of target genes. As shown in Figure 1C, we observed interactions of ALKBH3 with ASCC3, ASCC2, and ASCC in lung adenocarcinoma, especially ASCC3. There was also a co-expression relationship between ALKBH3 and ALKBH2. Gene function prediction showed that the interaction between ALKBH3 and ASCC3 might be involved in the metabolism of DNA. ALKBH3 is involved in the demethylation of DNA and RNA, as well as in important biological processes such as iron-iron binding [Figure 1C].
ALKBH3 expression and immune cell infiltration
Secondly, the online database and statistical software were used to analyze the correlation between ALKBH3 expression level and immune cell infiltration level, EGFR expression level, and mutation status in lung adenocarcinoma tissue. CD4+ and regulatory T cells, bone marrow dendritic cells, neutrophils, natural killer cells, and macrophages were positively correlated with the expression of ALKBH3 in lung adenocarcinomas. Infiltration levels of M2 macrophages were positively correlated with those of CD8+ T cells [Figure 1D]. Moreover, we found a positive correlation between ALKBH3 and EGFR expression in lung adenocarcinomas. Compared with wild-type EGFR, mutant EGFR lung adenocarcinoma had higher expression levels of ALKBH3, and the difference was statistically significant [Figure 1E].
Our study used the EPIC online tool to determine if ALKBH3 expression is associated with immune cell infiltration within the tumor microenvironment. Eight types of cancer-associated immune cells were linked to ALKBH3 expression in various cancers, notably PAAD, PCPG, and THYM [Figure 1F].
Mutations and epigenetic alterations
Next, we used online databases to analyze mutations and epigenetic alterations in ALKBH3. Our investigation of pan-cancer genetic alterations within ALKBH3 was conducted using cBioPortal. ALKBH3 expression was altered in 2.0% of 51 samples collected from 2,565 cancer patients. ALKBH3 mutation was observed in 28 cancers, with bladder cancer showing the highest ALKBH3 mutation rate. Lung cancer is characterized by amplification-type copy number variations [Figure 2A and B].
Figure 2. Genetic alteration analysis and promoter methylation level in ALKBH3. (A) Genetic alteration in ALKBH3 in pan-cancer tissues, accounting for 5% of alterations. (B) The alteration frequency with the mutation type of ALKBH3 in different cancers. (C) Promoter methylation level in ALKBH3 between adjacent tissues and tumor tissues in 20 types of cancer from UALCAN.
In addition to assessing methylation levels in the promoter DNA of ALKBH3, we examined 20 types of cancer tissues. Hypermethylation was found in BRCA, CHOL, COAD, and other tumor types [Figure 2C].
ALKBH3 protein is highly expressed in lung adenocarcinoma
In this section, we used WB and immunohistochemistry to detect the expression level of ALKBH3 protein in lung adenocarcinoma tissues and adjacent tissues. Tissue microarray detection of 80 samples of lung adenocarcinoma and 88 samples of paracancerous tissues showed that positive expression of ALKBH3 was mainly located in the cytoplasm. Tissue microarray analysis showed that ALKBH3 expression was high in 38 of the 80 lung adenocarcinoma samples (IHC score > 6) and low in 42 samples (IHC score ≤ 6). In the 88 paraneoplastic tissue samples, the expression of ALKBH3 was high in one (1.14%) and low in 87 cases (98.86%). In lung adenocarcinoma, ALKBH3 expression was significantly higher than in adjacent tissues
Figure 3. Relative expression levels of ALKBH3 in lung adenocarcinoma and paracarcinoma tissues (IHC staining, with a scale bar included in the image).
Figure 4. Expression of ALKBH3. (A) Detection of ALKBH3 protein levels in 12 pairs of fresh LUAD and paracarcinomas using Western blot. (B) Statistical analyses and bar graphs of the relative expression of ALKBH3 protein in 12 pairs of LUAD and paracarcinomas.
ALKBH3 protein expression levels in LUAD and paracancerous tissues
| Group | High expression | Low expression | χ → P |
| CT [n (%)] | 38 (47.50) | 42 (52.50) | 47.97 < 0.001 |
| ANT [n (%)] | 1 (1.14) | 87 (98.86) |
ALKBH3 is highly expressed in lung adenocarcinoma
To further explore the expression of ALKBH3 in lung adenocarcinoma, we carried out RT-qPCR experiments. The relative expression of ALKBH3 mRNA in four pairs of fresh lung adenocarcinoma and matched paracancerous tissues was detected. In lung adenocarcinoma, ALKBH3mRNA expression was significantly higher compared to paracancerous tissue based on the results of cDNA amplification
Effects of ALKBH3 on proliferation, migration, and invasion of A549 cells
Effect of ALKBH3 expression on proliferation of A549 cells
First of all, we detected overexpression of ALKBH3 in lung adenocarcinoma by RT-qPCR and western blotting experiments. To further study the significance of ALKBH3 expression in lung adenocarcinoma, we constructed a stable mutant strain of A549 cells with low ALKBH3 expression via knockdown of ALKBH3. Western blotting and RT-qPCR showed that this stable transmutation had been successfully constructed
Effects of ALKBH3 expression on migration and invasion of A549 cells
Next, we tested the migration and invasion of A549 cells using a transwell assay and a scratch assay. The results of the cell scratch test showed that the healing ability of the ALKBH3-knockout A549 cell line was significantly weaker than that of the control group at 72 h (P < 0.01, Figure 5A and B). Moreover, the transwell assay showed that A549 cells with low ALKBH3 expression were significantly less invasive than the control group (P < 0.01, Figure 5C and D). In summary, our results indicate that knocking down ALKBH3 can reduce invasiveness.
Figure 5. Effects of ALKBH3 expression on migration and invasion of A549 cells. (A) the healing of four groups of cells. (B) Statistical diagram of cell migration rate of the four groups (** indicates P < 0.01). (C) Invasion ability of four groups of cells. (D) Statistical chart of the number of invasive cells in four groups of cells (** indicates P < 0.01). (E) Nude mice and subcutaneous tumors of nude mice. (F) Statistical graph of subcutaneous tumor weights of three groups (*** indicates P < 0.001).
Knockdown of ALKBH3 can inhibit the growth of subcutaneous tumors in nude mice
At last, we subcutaneously injected stable A549 cells and normal A549 cells with low ALKBH3 levels into nude mice to further verify the role of ALKBH3 in vivo. When subcutaneous tumors began to form, the mouse body weights and subcutaneous tumor volumes were recorded every day. When the subcutaneous tumors grew to more than 1.5 × 103 mm3, the nude mice were dissected, and the tumor growth was observed. As can be seen from Figure 5E, the subcutaneous tumor volumes of ALKBH3 knockdown group 1 and ALKBH3 knockdown group 2 were significantly smaller than those of the normal group (P < 0.001, Figure 5E and F). Overall, these results indicate that ALKBH3 knockdown prevents lung adenocarcinoma growth.
DISCUSSION
Adenocarcinoma accounts for about 40% of non-small-cell lung cancers, and lung cancer has the highest morbidity and mortality rates of all cancers worldwide[26,27]. Therefore, it is of great significance to explore new diagnosis and treatment targets for lung adenocarcinoma.
Firstly, we investigated the expression of ALKBH3 and its effects on lung adenocarcinoma's biological behavior and function. By analyzing publicly available data, we found that ALKBH3 was highly expressed in lung adenocarcinomas. The expression of ALKBH3 was also upregulated in some cancer tissues, according to pan-cancer analysis. These results suggest that ALKBH3 has potential applications as a marker for some tumor types. Human immunotherapy has led to the development of new treatment strategies for cancer patients and has greatly changed the pattern of oncology. As a result of the heterogeneity of the tumor microenvironment, not all patients benefit from immunotherapy or maintain a long-term clinical response. ALKBH3 expression levels were positively correlated with CD4+ T cells, regulatory T cells, myeloid dendritic cells, neutrophils, natural killer cells, and M2 macrophage infiltration levels in lung adenocarcinoma, but negatively correlated with CD4+ T cells. These results suggest that ALKBH3 could affect the sensitivity of patients to immunotherapy and could also be used as a therapeutic target. Notably, ALKBH5, another family member, has been shown to modulate anti-PD-1 therapy response by influencing lactate levels in the tumor microenvironment and altering immune cell infiltration, indicating a potential overlapping role in immune modulation[28]. Gene function prediction results showed that the interaction between ALKBH3 and ASCC3 may be involved in the metabolic process of DNA. ALKBH3 is involved in the demethylation of DNA and RNA and is also related to important biological processes such as iron-iron binding. In addition, mutations and epigenetic changes can lead to abnormal gene expression. We found that ALKBH3 had a high mutation frequency in lung cancer. Moreover, we assessed the levels of ALKBH3 promoter DNA methylation in 19 cancer tissues and found that ALKBH3 was hypermethylated in BRCA, CHOL, COAD, and other tumors. Previous studies have shown that the AlkB family can catalyze demethylation on a variety of substrates (such as RNA and DNA), thereby affecting tumor progression and prognosis[29-31]. In vitro, western blotting, RT-qPCR, and IHC techniques were used to further verify that the expression of ALKBH3 in lung adenocarcinoma was significantly upregulated. This is consistent with previous studies that found that ALKBH3 is differentially expressed in various cancer types, such as pancreatic cancer, prostate cancer, and renal cancer[32-34]. To further explore the effects of ALKBH3 on the biological behavior and function of lung adenocarcinoma, A549 cells and nude mice were used to construct a stable lung adenocarcinoma cell line with ALKBH3 knockout. CCK-8 assay in vitro, transwell assay, cell scratch assay, and subcutaneous tumor formation in nude mice were used to assess the effects of ALKBH3 on the proliferation, migration, and invasion of A549 cells. Compared to cells in the blank control group and empty vector group, A549 cells with low ALKBH3 expression exhibited significantly reduced proliferation, migration, and invasion. The oncogenic role of ALKBH3 in tumor growth is likely attributed to its regulation of mRNA stability and translation of genes that govern cell proliferation, which occurs through the activation of the PI3K/AKT and MAPK/ERK signaling pathways, thus facilitating tumor progression. Furthermore, its involvement in mitigating RNA damage and sustaining cancer cell survival under stress conditions further consolidates its pro-tumorigenic function. In vivo and in vitro experiments on subcutaneous tumor formation in nude mice showed that knockdown of ALKBH3 inhibited the growth of subcutaneous tumors. In addition, the role of ALKBH3 in cellular invasion and migration is likely attributed to its enhancement of the invasion and migratory capabilities of cancer cells, primarily through the modulation of epithelial-mesenchymal transition (EMT). This process involves the upregulation of EMT-related transcription factors and matrix metalloproteinases (MMPs), degradation of the extracellular matrix (ECM) barrier, and subsequent promotion of metastatic dissemination. The results of this study further confirmed the findings of Tasaki et al.[18]. In addition, these results are consistent with previous studies showing that ALKBH3 is involved in the progression of some cancers, such as prostate cancer, salivary gland tumors, and liver cancer, suggesting that inhibiting ALKBH3 may provide a viable therapeutic approach[32,35,36]. According to the above experimental results, ALKBH3 is a potential diagnostic biomarker and therapeutic target for lung adenocarcinoma.
Overall, our results support the role of ALKBH3 as an oncogene in the growth, invasion, and migration of lung adenocarcinoma cells. These findings will further our understanding of the tumor microenvironment in lung adenocarcinoma and provide valuable data for further exploration of its pathogenesis and potential therapeutic targets. However, this study has some limitations. Although A549 cells are of great value in the study of lung adenocarcinoma, they still have limitations. This study can be verified in other cell lines or patient-derived organoids to more fully reveal the biological mechanism and therapeutic potential of lung adenocarcinoma. Cell cycle and apoptosis assays can also be used to fully explore the role of ALKBH3 in lung adenocarcinoma cell function. Additionally, while we have established a link between ALKBH3 expression and immune cell infiltration, the exact mechanisms underlying this relationship require further exploration.
This study highlights ALKBH3 as a promising diagnostic biomarker for Lung adenocarcinoma, with its elevated expression serving as an indicator of aggressive disease. Therapeutically, targeting ALKBH3 could curb tumor proliferation and metastasis, either through small molecule inhibitors or RNA-based approaches. Additionally, its connection to immune cell infiltration suggests it could influence immune evasion, paving the way for combination therapies with immune checkpoint inhibitors. Building upon these findings, future investigations should focus on: elucidating the molecular mechanisms linking ALKBH3 to immune cell infiltration, with a particular focus on its role in shaping the tumor microenvironment; investigating the potential of ALKBH3 inhibitors in preclinical models, particularly their efficacy in halting the progression of lung adenocarcinoma and enhancing response to current therapeutic strategies; exploring ALKBH3’s role in other RNA modifications and their downstream effects, which could provide valuable insights into the broader implications of RNA epigenetics in the pathogenesis of lung adenocarcinoma; and conducting clinical studies to validate ALKBH3 as a biomarker for patient stratification and prognostic prediction, potentially improving personalized treatment approaches. Therefore, further studies and clinical trials are necessary to confirm the clinical value of ALKBH3 as a clinical diagnostic and prognostic indicator, paving the way for improved clinical outcomes in lung adenocarcinoma management.
DECLARATIONS
Acknowledgments
We acknowledge the use of TCGA, GTEx, TIMER2.0, EPIC, GeneMANIA, cBioPortal, and UALCAN free of cost.
Authors’ contribution
Conceptualization: Zhang S, Zhou H, Chen H, Liu T
Methodology, formal analysis, visualization, and writing original draft: Zhang S, Chen H, Liu T, Tang S
Software: Hu H, Liu T, Qin C, Dai T, Yan H, Tang S
Experiment validation: Zhang S, Qin C, Chen H, Yan H, Liu T
Data collection: Qin C, Yan H, Dai T, Yang L, Ji D
Project administration and funding acquisition: Zhou H, Yang L, Zhang S
All authors contributed to the article and approved the submitted version.
Availability of data and materials
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Financial support and sponsorship
This study was funded by the Sichuan Provincial Health Commission Project Fund (No. 21PJ188).
Conflicts of interest
All authors declared that there are no conflicts of interest.
Ethical approval and consent to participate
The study was conducted in accordance with the principles of the Declaration of Helsinki. It was approved by the Medical Research Ethics Review Committee of Suining Central Hospital. The ethical approval code is: KYLLKS20240054. All participants provided written informed consent prior to their inclusion in the study.
Consent for publication
Not applicable.
Copyright
© The Author(s) 2024
REFERENCES
1. Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. Nature 2018;553:446-54.
2. Allemani C, Matsuda T, Di Carlo V, et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet 2018;391:1023-75.
3. Oudkerk M, Liu S, Heuvelmans MA, Walter JE, Field JK. Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives. Nat Rev Clin Oncol 2021;18:135-51.
4. Zhu Z, Qian Q, Zhao X, Ma L, Chen P. N6-methyladenosine ALKBH5 promotes non-small cell lung cancer progress by regulating TIMP3 stability. Gene 2020;731:144348.
5. Yang P, Wang Q, Liu A, Zhu J, Feng J. ALKBH5 holds prognostic values and inhibits the metastasis of colon cancer. Pathol Oncol Res 2020;26:1615-23.
6. Zhang J, Guo S, Piao HY, et al. ALKBH5 promotes invasion and metastasis of gastric cancer by decreasing methylation of the lncRNA NEAT1. J Physiol Biochem 2019;75:379-89.
7. Roundtree IA, Evans ME, Pan T, He C. Dynamic RNA modifications in gene expression regulation. Cell 2017;169:1187-200.
8. Xu J, Liu Y, Liu J, et al. The identification of critical m6A RNA methylation regulators as malignant prognosis factors in prostate adenocarcinoma. Front Genet 2020;11:602485.
9. Fu Y, Dominissini D, Rechavi G, He C. Gene expression regulation mediated through reversible m6A RNA methylation. Nat Rev Genet 2014;15:293-306.
10. Tang C, Klukovich R, Peng H, et al. ALKBH5-dependent m6A demethylation controls splicing and stability of long 3'-UTR mRNAs in male germ cells. Proc Natl Acad Sci USA 2018;115:E325-33.
11. Zou S, Toh JDW, Wong KHO, Gao YG, Hong W, Woon ECY. N6-methyladenosine: a conformational marker that regulates the substrate specificity of human demethylases FTO and ALKBH5. Sci Rep 2016;6:25677.
12. Huang H, Weng H, Chen J. m6A modification in coding and non-coding RNAs: roles and therapeutic implications in cancer. Cancer Cell 2020;37:270-88.
13. Ueda Y, Ooshio I, Fusamae Y, et al. AlkB homolog 3-mediated tRNA demethylation promotes protein synthesis in cancer cells. Sci Rep 2017;7:42271.
14. Jiang X, Liu B, Nie Z, et al. The role of m6A modification in the biological functions and diseases. Signal Transduct Target Ther 2021;6:74.
15. Lu Q, Wang H, Lei X, et al. LncRNA ALKBH3-AS1 enhances ALKBH3 mRNA stability to promote hepatocellular carcinoma cell proliferation and invasion. J Cell Mol Med 2022;26:5292-302.
16. Woo HH, Chambers SK. Human ALKBH3-induced m1A demethylation increases the CSF-1 mRNA stability in breast and ovarian cancer cells. Biochim Biophys Acta Gene Regul Mech 2019;1862:35-46.
17. Shimada K, Fujii T, Tsujikawa K, Anai S, Fujimoto K, Konishi N. ALKBH3 contributes to survival and angiogenesis of human urothelial carcinoma cells through NADPH oxidase and tweak/Fn14/VEGF signals. Clin Cancer Res 2012;18:5247-55.
18. Tasaki M, Shimada K, Kimura H, Tsujikawa K, Konishi N. ALKBH3, a human AlkB homologue, contributes to cell survival in human non-small-cell lung cancer. Br J Cancer 2011;104:700-6.
19. Yeo JG, Wasser M, Kumar P, et al. The extended polydimensional immunome characterization (EPIC) web-based reference and discovery tool for cytometry data. Nat Biotechnol 2020;38:679-84.
20. Warde-Farley D, Donaldson SL, Comes O, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res 2010;38:W214-20.
21. Zuberi K, Franz M, Rodriguez H, et al. GeneMANIA prediction server 2013 update. Nucleic Acids Res 2013;41:W115-22.
23. Cerami E, Gao J, Dogrusoz U, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2012;2:401-4.
24. Chandrashekar DS, Bashel B, Balasubramanya SAH, et al. UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia 2017;19:649-58.
25. Men C, Chai H, Song X, Li Y, Du H, Ren Q. Identification of DNA methylation associated gene signatures in endometrial cancer via integrated analysis of DNA methylation and gene expression systematically. J Gynecol Oncol 2017;28:e83.
26. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209-49.
27. Xu JY, Zhang C, Wang X, et al. Integrative proteomic characterization of human lung adenocarcinoma. Cell 2020;182:245-61.e17.
28. Li N, Kang Y, Wang L, et al. ALKBH5 regulates anti-PD-1 therapy response by modulating lactate and suppressive immune cell accumulation in tumor microenvironment. Proc Natl Acad Sci USA 2020;117:20159-70.
29. Bian K, Lenz SAP, Tang Q, et al. DNA repair enzymes ALKBH2, ALKBH3, and AlkB oxidize 5-methylcytosine to 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine in vitro. Nucleic Acids Res 2019;47:5522-9.
30. Wu TP, Wang T, Seetin MG, et al. DNA methylation on N6-adenine in mammalian embryonic stem cells. Nature 2016;532:329-33.
31. Wu G, Yan Y, Cai Y, et al. ALKBH1-8 and FTO: potential therapeutic targets and prognostic biomarkers in lung adenocarcinoma pathogenesis. Front Cell Dev Biol 2021;9:633927.
32. Koike K, Ueda Y, Hase H, et al. Anti-tumor effect of AlkB homolog 3 knockdown in hormone- independent prostate cancer cells. Curr Cancer Drug Targets 2012;12:847-56.
33. Yamato I, Sho M, Shimada K, et al. PCA-1/ALKBH3 contributes to pancreatic cancer by supporting apoptotic resistance and angiogenesis. Cancer Res 2012;72:4829-39.
34. Hotta K, Sho M, Fujimoto K, et al. Clinical significance and therapeutic potential of prostate cancer antigen-1/ALKBH3 in human renal cell carcinoma. Oncol Rep 2015;34:648-54.
35. Marcinkowski M, Garbicz D, Pilžys T, Kukwa W, Grzesiuk E. Selected ALKBH dioxygenases are overexpressed in salivary gland tumours. Acta Biochim Pol 2022;69:889-94.
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Zhang, S.; Chen, H.; Liu, T.; Qin, C.; Yan, H.; Hu, H.; Tang, S.; Dai, T.; Ji, D.; Yang, L.; Zhou, H. Expression of ALKBH3 and its effects on proliferation, migration, and invasion of lung adenocarcinoma A549 cells: bioinformatics analysis and in vitro and in vivo experiments. J. Cancer. Metastasis. Treat. 2024, 10, 32. http://dx.doi.org/10.20517/2394-4722.2024.109
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