Abstract

Background

   Lung cancer is the leading cause of cancer-related deaths worldwide, so
   research and development of potential therapeutic targets is urgent.

Methods

   The target gene, AKR1C2, was screened using the TCGA and FerrDb
   databases. The expression of AKR1C2 in lung cancer, its correlation
   with the clinical characteristics of patients, and the biological roles
   and molecular mechanisms involved were assessed by bioinformatics. The
   expression levels of AKR1C2 in normal lung epithelial cells and lung
   cancer cells were compared by qRT-PCR and Western blot. The effects of
   AKR1C2 knockdown on the malignant phenotype of lung cancer cells were
   evaluated using Transwell, wound healing, and CCK8 assays. Finally, the
   impact of silencing AKR1C2 on malondialdehyde, reactive oxygen species,
   Fe^2+ levels, and ferroptosis-related genes in lung cancer cells were
   experimentally investigated.

Results

   AKR1C2 is highly expressed in lung adenocarcinoma tissues, and the
   expression level correlates with patient gender, tumor stage, lymph
   node metastasis, and prognosis. AKR1C2 is associated with substance
   metabolism, steroid hormone biosynthesis, cellular lipid metabolism,
   and oxidoreductase activity. AKR1C2 had high expression levels in A549
   cells. AKR1C2 silencing inhibited cell viability, invasion, and
   migration. In A549 cells, AKR1C2 knockdown markedly raised the levels
   of reactive oxygen species, malondialdehyde, and Fe²⁺. The knockdown of
   AKR1C2 regulated the expression of ferroptosis-related genes.

Conclusion

   Our study demonstrates that AKR1C2 knockdown promotes ferroptosis and
   inhibits malignant biological behaviors in lung cancer cells.

1. Introduction

   Globally, lung cancer stands as a prominent cause of cancer-associated
   mortality [[26]1]. Of these, lung adenocarcinoma (LUAD) is the most
   common histological type of lung cancer [[27]2]. Over the past decade,
   significant advancements have been achieved in the treatment of lung
   cancer, particularly through the application of molecularly targeted
   therapies and immunotherapies. Despite these progressions, the 5-year
   survival rate for patients remains below 30%, with metastasis and
   drug-resistant recurrence persisting as two major unresolved challenges
   [[28]3]. Studying the underlying molecular mechanisms and creating more
   potent, molecularly targeted treatment approaches are therefore
   imperative.

   Ferroptosis is a new programmed cell death pathway first discovered and
   proposed by Dixon et al [[29]4] in 2012, which is uniquely
   biochemically characterised by aberrant lipid peroxidation, reactive
   oxygen species (ROS) accumulation, and substantial elevation of iron
   levels [[30]5]. In recent years, Ferroptosis has had a significant
   regulatory role in lung cancer, according to an increasing number of
   research findings [[31]6]. MAX’s Next Tango promotes the proliferation
   of LUAD cells and reduces their sensitivity to chemotherapy by
   inhibiting the spermine/spermine N1-acetyltransferase 1-associated
   ferroptosis pathway [[32]7]. Knockdown of myeloma overexpressed genes
   promotes ferroptosis and inhibits the growth and proliferation of LUAD
   [[33]8].

   A member of the human Aldo-keto reductases (AKRs) family, Aldo-keto
   reductase family 1 member C2 (AKR1C2), regulates steroid hormones and
   is aberrantly expressed in many cancers [[34]9]. According to certain
   research, AKR1C2 expression in lung cancer is strongly associated with
   resistance to cisplatin and adriamycin [[35]10–[36]12]. However, it has
   not yet been investigated or documented whether it has a role in
   controlling LUAD cell migration, invasion, proliferation, and
   ferroptosis.

   Therefore, the aim of this study was to characterize AKR1C2 expression
   levels based on the LUAD dataset in TCGA database and to identify the
   functional roles of AKR1C2 and its relationship with ferroptosis by
   bioinformatics and cell experiments.

2. Materials and methods

2.1. Target gene screening

   The dataset of LUAD was obtained from TCGA database, and significant
   differentially expressed genes between cancerous and normal tissues in
   this dataset were screened by DESeq2 package analysis of R software.
   The screening condition was set as |log2FoldChange| > 2, P adjust
   <0.05. The differential genes obtained were intersected with
   ferroptosis-related genes downloaded from the FerrDb database to obtain
   the differential genes related to ferroptosis in lung adenocarcinomas,
   and volcano diagrams were plotted using the ggplot2 package.
   Subsequently, the target gene of this study were identified after a
   literature search.

2.2. Correlation analysis between AKR1C2 and patients’ clinical
characteristics and prognosis

   Relevant clinical information was downloaded from the TCGA database and
   integrated with the AKR1C2 expression data to analyze the expression
   levels of the target gene in different patient ages, genders, tumor
   grades, and TNM stages to assess the relationship between AKR1C2 and
   the clinical characteristics of the patients.

   The relevant survival information was downloaded from the TCGA database
   and integrated with the AKR1C2 expression data, in which the patients
   were divided into two groups of high and low expression based on the
   expression level of the target gene. Subsequently, the survival curve
   was plotted by the survival package in R to determine the effect of
   high and low expression of AKR1C2 on the prognosis of the patients.

2.3. Functional and pathway analysis of AKR1C2

   GO, KEGG, GSEA enrichment analysis of target genes was performed by
   using R’s org.Hs.es.db package and clusterProfiler package, and the
   results were visualized by drawing the corresponding histograms using
   the ggplot2 package.

2.4. Cell culture

   The team of Academician Lin Lizhu from the Oncology Department at the
   First Affiliated Hospital of Guangzhou University of Chinese Medicine
   generously donated human normal lung epithelial cells (BEAS-2B).
   Meanwhile, LUAD cells (A549) were acquired from Zishan Biotech (Wuhan,
   China). Both cell lines were grown in RPMI 1640 medium (Gibco, USA)
   with 10 μL/ml of penicillin/streptomycin (Gibco, USA) and 10% fetal
   bovine serum (FBS) (Procell, China) added. The culturing was conducted
   at a temperature of 37°C with 5% CO[2].

2.5. Transfection

   Sangon Biotech (Shanghai, China) provided the small interfering RNA
   (siRNA), including negative control (si-NC) and si-AKR1C2. A 6-well
   plate was injected with 3.5 × 10^5 cells per well, and after 24 h of
   incubation, when the cell fusion efficiency reached 70–80%. Following
   the instructions, transfection complexes comprising si-NC or si-AKR1C2
   were made using RPMI 1640 medium and Lipo8000TM transfection reagent
   (Beyotime, China). The cells were then collected for additional
   research 48 h after transfection.

2.6. Quantitative real-time PCR (qRT-PCR)

   Trizol reagent (Thermo Fisher Scientific, USA) was used to extract RNA
   from each set of treated cells. Evo M-MLV RT Premix for qPCR (Accurate
   Biology, China) was then used to transform this RNA into cDNA.
   Subsequently, qRT-PCR was performed on the extracted cDNA using a
   QuantStudio 5 real-time PCR machine (Applied Biosystems, USA),
   employing the SYBR® Green Premix Pro Taq HS qPCR Kit (Accurate Biology,
   China). The 2^-ΔΔCT approach was used to determine the relative
   expression levels of the gene’s mRNA. [37]Table 1 lists the precise
   sequences of the primers used in this investigation, which were
   obtained from Sangon Biotech (Shanghai, China).

Table 1. Primers for qRT-PCR in this study.

   Gene      Sequence from 5’-3’
   AKR1C2-F  AAGTAAAGCTCTAGAGGCCGT
   AKR1C2-R  CTCTGGTCGATGGGAATTGCT
   β-actin-F CTACGTCGCCCTGGACTTCGAGC
   β-actin-R GATGGAGCCGCCGATCCACACGG
   SLC7A11-F GGTACTGCAATCACAATGCCAGA
   SLC7A11-R GCACATGCATCAAGAGTTTCCATAA
   GPX4-F    AATTCGCAGCCAAGGACATC
   GPX4-R    AGGCCAGGATTCGTAAACCA
   ACSL4-F   TGGAAGTCCATATCGCTCTGT
   ACSL4-R   TTGGATACAGCATGGTCAAA
   FTH1-F    CCCCCATTTGTGTGACTTCAT
   FTH1-R    GCCCGAGGCTTAGCTTTCATT
   [38]Open in a new tab

2.7. Western blot

   RIPA buffer (Beyotime, China) was used to lyse cells, and an Enhanced
   BCA Protein Assay Kit (Beyotime, China) was used to measure the protein
   content. Following their separation using 10% SDS-PAGE (Beyotime,
   China), the proteins were transferred onto 0.45 μm PVDF membranes.
   These membranes were blocked with Western Blot Blocking Buffer
   (Beyotime, China) for 15 min at room temperature. Following this, they
   were incubated overnight at 4°C with primary antibodies against AKR1C2
   (1:800, DF3757, Affinity, China), glutathione peroxidase 4 (GPX4,
   1:7500, ET1706–45, HUABIO, China), SLC7A11 (1:1500, YP-Ab-17133,
   UpingBio, China), ACSL4 (1:1500, YP-Ab-12589, UpingBio, China),
   ferritin heavy chain 1 (FTH1, 1:750, WL05360, Wanleibio, China), and
   β-actin (1:7500, AF7018, Affinity, China). After that, the membrane was
   washed and incubated with the second antibody for an hour at room
   temperature. Lastly, an ultrasensitive ECL chemiluminescent substrate
   (Biosharp, China) was used to visualize the blot.

2.8. Cell counting kit‑8 (CCK‑8)

   A549 cells were plated into 96-well plates at a cellular density of
   5 × 10^3 cells per well and then pre-cultured for 24 hours in an
   incubator. Following this, the cells were transfected based on the
   experimental grouping. Post-transfection, after a duration of 48 h, 10
   μL of CCK-8 reagent (Beyotime, China) was dispensed into each well. The
   cells were then further incubated at 37°C for an extended period of
   1.5 h. The viability of the cell was assessed by using a microplate
   reader (Thermo Fisher Scientific, USA) at 450 nm and 600 nm.

2.9. Transwell assay

   Matrigel (Corning, Inc., USA) was first lined in 8 μmpore transwell
   chambers (LABSELECT, China). Medium containing 10% FBS was placed in
   the lower chamber, whereas 2 × 10^5 transfected cells and media devoid
   of FBS were placed in the top chamber. The cells were fixed for 40 min
   with 4% paraformaldehyde and stained for 20 min with 0.1% crystal
   violet solution following a 24-hour culture period. Then the invasive
   ability of the cells was measured by photographing and counting under
   an inverted microscope.

   The chambers were not coated with Matrigel and were seeded with
   1 × 10^5 transfected cells. The remaining steps were identical to those
   used in the invasion assay. The migratory capacity of the cells was
   assessed by photographing and counting the cells under an inverted
   microscope following fixation and staining.

2.10. Wound healing assay

   Cells transfected for 48 h in a six-well plate were scratched in
   parallel with a 200 μL pipette tip, rinsed with PBS, and replaced with
   the culture that contained 1% FBS. The cell migration at the 0h and 24h
   scratches were photographed under an inverted microscope.

2.11. Detection of intracellular ROS

   The treated and collected cells of each group were suspended in DCFH-DA
   fluorescent probe (Beyotime, China) working solution diluted in
   FBS-free medium, incubated at 37°C for 20 min without light (mixing
   upside down every 3–5 min), and washed in FBS-free medium 3 times. A
   flow cytometer was then used to measure the ROS levels in the cells (BD
   Biosciences, USA).

2.12. Measurement of malondialdehyde (MDA)

   The MDA level was evaluated by a lipid oxidation assay kit (Beyotime,
   China). Cells from individual groups underwent centrifugation for
   collection, followed by lysis through ultrasonic treatment in an
   ice-cold bath. After that, they underwent another centrifugation at
   12,000 rpm for 10 min at 4°C. After mixing the resulting supernatant
   with the MDA test reagent, it was heated for 60 min at 100°C in a metal
   bath. A microplate reader (Thermo Fisher Scientific, USA) set at 532 nm
   was used to measure the MDA content.

2.13. Measurement of iron content

   The cells of each group were washed with PBS 3 times. After adding 1
   μmol/L of FerroOrange work solution (Dojindo, Japan), the mixture was
   incubated for 30 min at 37°C. Direct observation and photography of the
   cells were carried out under an inverted fluorescent microscope
   (Olympus Corporation, Japan) without washing.

2.14. Statistical analysis

   GraphPad Prism 9.5 and R 4.3.1 were used for data processing and
   statistical analysis. To guarantee the precision and dependability of
   the findings, every experiment was meticulously and independently
   conducted at least three times. The mean ± standard deviation
   (Mean ± SD) is used to display all data. We used the Student’s t-test
   method to demonstrate the difference between the two samples. For
   multi-group comparisons, one-way ANOVA was used. When P < 0.05, we
   considered the observed differences to be statistically significant.

3. Results

3.1. Identification of AKR1C2 as a target gene and its high expression in
LUAD

   589 lung cancer cases with RNA sequencing were downloaded from TCGA
   database, including 533 cancer cases and 56 normal tissue cases. After
   differential analysis and taking intersections with ferroptosis-related
   genes, 12 differential genes associated with ferroptosis in LUAD were
   screened out (11 of which were up-regulated in expression and 1
   down-regulated in expression) ([39]Fig 1A). The literature search
   revealed that no studies have confirmed the correlation between AKR1C2
   and ferroptosis in LUAD, whereas the other genes have been studied. So
   AKR1C2 was identified as the target gene. Meanwhile, the results of
   differential analysis showed that the expression level of the AKR1C2
   gene was significantly higher in tumor tissues compared with normal
   tissues ([40]Fig 1B).

Fig 1. LUAD differential genes associated with ferroptosis.

   [41]Fig 1
   [42]Open in a new tab

   (A) 12 LUAD differential genes were associated with ferroptosis. 11 of
   them were up-regulated, and 1 was down-regulated in expression. (B)
   Expression of AKR1C2 gene in tumor tissues versus normal tissues.
   AKR1C2 gene expression was significantly elevated in tumor tissues
   (P < 0.001). ***P < 0.001.

3.2. Relationship between AKR1C2 expression levels and patients’ clinical
characteristics and prognosis

   Relevant clinical and prognostic information was downloaded from the
   TCGA database and integrated with the target gene expression data. The
   correlation between AKR1C2 and clinical characteristics of lung
   adenocarcinoma patients was predicted, and the results showed that the
   expression level of AKR1C2 was closely related to gender, tumor stage,
   and lymph node metastasis of lung adenocarcinoma patients ([43]Fig 2B,
   [44]E, and [45]F), and was not related to the age of lung
   adenocarcinoma patients, tumor size, infiltration depth, and distant
   metastasis ([46]Fig 2A, [47]C, and [48]D). Kaplan-Meier survival curves
   were also drawn for AKR1C2 expression level and patients’ overall
   survival time ([49]Fig 2G), from which the survival curves showed that
   the expression level of AKR1C2 was correlated with patients’ overall
   survival, and that the overall survival of the group with high AKR1C2
   expression was lower than that of the group with low expression, which
   indicated that the prognosis of the patients with high AKR1C2
   expression was worse.

Fig 2. Relationship between AKR1C2 gene expression and clinical
characteristics and prognosis of LUAD patients.

   [50]Fig 2
   [51]Open in a new tab

   (A) The expression level of AKR1C2 was not related to the age of
   patients. (B) The expression level of AKR1C2 was related to the gender
   of patients. The expression level of AKR1C2 in male patients was
   slightly higher than that in females (P < 0.05). (C) The expression
   level of AKR1C2 was not related to the size and infiltration range of
   lung cancer. (D) The expression level of AKR1C2 was not related to the
   distant metastasis of lung cancer. (E) The expression level of AKR1C2
   was correlated with lymph node metastasis of lung cancer. The
   expression level of AKR1C2 in patients with lymph node metastasis was
   slightly higher than that in those without lymph node metastasis
   (P < 0.05). (F) The expression level of AKR1C2 was correlated with the
   pathological stage of lung cancer. The expression level of AKR1C2 in
   patients with pathological stage IV was slightly higher than that in
   grade I (P < 0.05), and the difference between the rest of the grades
   was not statistically significant. (G) The expression level of AKR1C2
   was correlated with the prognosis of the patients. Patients with high
   expression of AKR1C2 had a worse prognosis (P < 0.05). *P < 0.05.

3.3. Functional and pathway analysis of AKR1C2

   GO/KEGG analysis showed that the differentially expressed molecular
   functions of AKR1C2 were mainly enriched in substance metabolism,
   steroid hormone biosynthesis, and the metabolic processes of
   doxorubicin and Zoerythromycin ([52]Fig 3A, [53]B). GSEA analysis
   showed that it was mainly enriched in cellular lipid metabolism,
   oxidoreductase activity, and other pathways ([54]Fig 3C).

Fig 3. Functional and pathway enrichment analysis of AKR1C2 gene.

   [55]Fig 3
   [56]Open in a new tab

   (A) GO analysis. (B) KEGG analysis. (C) GSEA enrichment analysis.

3.4. AKR1C2 is highly expressed in A549 cells

   We first used qRT-PCR and Western blot to compare the expression of
   AKR1C2 in normal lung epithelial cells with that in A549 cells in order
   to gain a better understanding of the function of AKR1C2 in tumor
   cells. The findings clearly showed that A549 cells’ AKR1C2 expression
   level was noticeably higher than BEAS-2B cells’ ([57]Fig 4). Next, we
   knocked down the expression of AKR1C2 to examine its possible impact on
   the biological behavior of A549 cells. A549 cells transfected with
   si-AKR1C2_1/2/3 exhibited significant downregulation of AKR1C2
   expression. Among these, the si-AKR1C2_1 group demonstrated the most
   effective knockdown compared to the other two groups ([58]Fig 5).
   Therefore, si-AKR1C2_1 was selected for subsequent experiments.

Fig 4. AKR1C2 expression was up-regulated in A549 cells.

   [59]Fig 4
   [60]Open in a new tab

   (A) qRT-PCR was performed to detect the mRNA expression level of AKR1C2
   compared to BEAS-2B (n = 6). (B) Western blot detection of the protein
   expression level of AKR1C2 compared to BEAS-2B (n = 6).
   ***P < 0.001,*P < 0.05.

Fig 5. Transfection of A549 cells with siRNA.

   [61]Fig 5
   [62]Open in a new tab

   (A) The knockdown efficiency of AKR1C2 mRNA expression level was
   detected by qRT-PCR (n = 4). (B) The knockdown effect of AKR1C2 protein
   levels was detected by Western blot (n = 8). ***P < 0.001. siRNA: short
   interfering RNA; si-NC: negative control.

3.5. Knockdown of AKR1C2 inhibits proliferation, migration, and invasion of
A549 cells

   To investigate the role of AKR1C2 in lung cancer cells A549, this study
   assessed whether AKR1C2 affected the invasion, migration, and
   proliferation of A549 cells. Firstly, we observed the viability and
   growth of AKR1C2 knockdown cells by CCK8 cell proliferation assay. The
   findings demonstrated that AKR1C2 knockdown dramatically decreased A549
   cell viability and inhibited cell growth ([63]Fig 6A). According to
   this, AKR1C2 could be crucial for preserving cell viability as well as
   encouraging the growth and development of tumors.

Fig 6. AKR1C2 silencing inhibited A549 cell proliferation, migration, and
invasion.

   [64]Fig 6
   [65]Open in a new tab

   (A) CCK8 assay was used to determine the proliferative capacity of
   transfected cells (n = 6). (B-C) Wound healing (n = 6) and transwell
   migration assay (n = 5) were used to determine the migratory capacity
   of transfected cells. (D) Transwell invasion assay was used to
   determine the invasive capacity of transfected cells (n = 5).
   *P < 0.05, ***P < 0.001.siRNA: short interfering RNA; si-NC: negative
   control.

   Next, we further explored the impact of AKR1C2 knockdown on A549 cell
   migration by wound healing and Transwell migration. In this experiment,
   we set up AKR1C2 knockdown and control groups to measure the efficiency
   of cell migration. The results showed that following AKR1C2 knockdown,
   the migratory efficiency of A549 cells was markedly decreased ([66]Fig
   6B, [67]C), indicating that AKR1C2 is the key to control A549 cell
   migration.

   In addition, Transwell invasion assay was a method to assess the
   invasive ability of cells. By observing the changes in invasiveness
   after cell transfection, we found that AKR1C2 knockdown could
   effectively inhibit the invasive ability of A549 cells ([68]Fig 6D).

   Taken together, these data consistently showed that A549 cell invasion,
   migration, and proliferation were all decreased by AKR1C2 knockdown.

3.6. Knockdown of AKR1C2 promotes ferroptosis

   The reduction of AKR1C2 significantly increased MDA and iron content
   levels ([69]Fig 7A, [70]B). DCFH-DA staining revealed that AKR1C2
   downregulation dramatically raised intracellular ROS levels in A549
   cells, comparable to the levels observed in cells treated with the
   ferroptosis inducer erastin. Moreover, AKR1C2 downregulation
   synergistically enhanced the increase in intracellular ROS levels when
   combined with erastin treatment in A549 cells ([71]Fig 7C). qRT-PCR
   ([72]Fig 8A) and Western blotting ([73]Fig 8B) both showed that in
   AKR1C2-silenced A549 cells, SLC7A11, GPX4, and FTH1 expression were
   reduced, and the ACSL4 protein level did not significantly change. In
   conclusion, AKR1C2 knockdown may lead to ferroptosis in A549 cells.

Fig 7. AKR1C2 silencing affects the levels of ferroptosis markers in A549
cells.

   [74]Fig 7
   [75]Open in a new tab

   (A) MDA levels were measured with a kit (n = 6). (B) Fe^2+ levels were
   measured with FerroOrange probe (n = 11). (C) DCFH-DA staining was used
   to estimate intracellular ROS levels by flow cytometry (n = 8).
   *P < 0.05, **P < 0.01, ***P < 0.001.siRNA: short interfering RNA;
   si-NC: negative control. erastin: ferroptosis inducer.

Fig 8. AKR1C2 silencing affected the expression of ferroptosis genes in A549
cells.

   [76]Fig 8
   [77]Open in a new tab

   (A) qRT-PCR to detect the expression of ferroptosis-related genes
   (n = 3). (B) Western blotting to detect the expression of
   ferroptosis-related proteins (n = 6). *P < 0.05, **P < 0.01,
   ***P < 0.001. siRNA: short interfering RNA; si-NC: negative control.

4. Discussion

   Oncogenes regulate cancer development and progression. With the rapid
   advancement of precision medicine, novel therapeutic strategies
   targeting oncogenic pathways have been proposed to improve the
   prognosis of patients with LUAD [[78]13]. Targeted therapy, either
   alone or in combination with other modalities, has emerged as a novel
   therapeutic approach with a potential preventive role in lung cancer
   [[79]14]. However, the identification of biomarkers for lung cancer
   remains limited, with only a small proportion of patients currently
   benefiting from these markers [[80]15]. Therefore, in order to enhance
   diagnosis and define therapeutic intervention targets, it is imperative
   to develop more accurate and efficient biomarkers [[81]16].Therefore,
   in this study, from the perspective of ferroptosis, we screened one
   gene, AKR1C2, which may be related to ferroptosis and is highly
   expressed in LUAD tissues through bioinformatics analysis and
   literature research.

   AKR1C2 protein is highly expressed in human liver, stomach, and bladder
   tissues [[82]9]. It is also aberrantly expressed in various cancers,
   where it regulates malignant phenotypes and contributes to
   chemoresistance in tumor cells. Silencing AKR1C2 inhibits
   triple-negative breast cancer cells’ ability to proliferate, migrate,
   invade, develop, and spread to the lungs [[83]17]. Inhibition of the
   AKR1C2 enzyme by ruthenium complexes in chemotherapy-resistant ovarian
   cancer cell lines has antiproliferative effects [[84]18]. Exosome
   lncAKR1C2 promotes lymph node metastasis in gastric cancer [[85]19].
   Reducing AKR1C2 expression in lung cancer cells increases sensitivity
   to cisplatin [[86]12]. Meanwhile, the correlation analysis and
   prognostic analysis in this study showed that the expression level of
   AKR1C2 was closely related to gender, tumor stage, and lymph node
   metastasis of LUAD patients and that the prognosis of patients with
   high AKR1C2 expression was worse. It suggests that AKR1C2 may be
   involved in regulating the malignant phenotype of LUAD. Consistent with
   previous studies and bioinformatics analysis, we found that AKR1C2 had
   a high expression level in A549 cells. Furthermore, we used CCK-8,
   scratch, and Transwell assays to show that AKR1C2 knockdown prevented
   A549 cells from growing, proliferating, and migrating.

   It has been suggested that AKR1C2 is involved in steroid hormone
   biosynthesis [[87]20] and ROS formation [[88]21], which can reduce the
   level of ROS in cancer cells [[89]22], make them resistant to oxidative
   stress and drug stimulation and ultimately mitigate death [[90]23].
   This contributes to the development and progression of malignant
   tumors. Ferroptosis is essential for controlling the proliferation of
   tumor cells, which is characterised by elevated iron levels and
   accumulation of intracellular lipid ROS [[91]5], and induction of
   ferroptosis has emerged as a possible cancer therapy [[92]24–[93]27].
   Furthermore, it has been demonstrated that in melanoma, BET inhibitors
   enhance GPX4 inhibition-induced ferroptosis through dual downregulation
   of AKR1C2 [[94]28]. The molecular function and pathway analysis in this
   study also showed that AKR1C2 is associated with processes such as
   substance metabolism, steroid hormone biosynthesis and pathways such as
   cellular lipid metabolism and oxidoreductase activity. Given these
   findings, AKR1C2 may regulate ferroptosis, making it a possible
   therapeutic target for LUAD. Investigating its function could aid in
   identifying potential markers of tumor progression. No study has
   confirmed the relationship between AKR1C2 and ferroptosis in LUAD
   cells. In this study, we looked at how AKR1C2 affected markers linked
   to ferroptosis, and the findings indicated that AKR1C2 knockdown not
   only downregulated ferroptosis-related genes’ expression levels (FTH1,
   GPX4, and SLC7A11) but also elevated ROS, MDA, and Fe^2+ levels. Taken
   together, we suggest that AKR1C2 may promote LUAD by inhibiting
   ferroptosis, and AKR1C2 knockdown helps to promote ferroptosis in lung
   cancer cells, thereby inhibiting lung cancer progression. These
   findings strongly imply that AKR1C2 targeting may be a viable approach
   to creating innovative treatment plans specifically designed to fight
   lung cancer. However, our current findings are limited to
   investigations in a single LUAD cell line (A549), and we have not yet
   fully elucidated the molecular mechanisms through which AKR1C2
   regulates ferroptosis. Therefore, it is necessary to conduct more
   experiments to further validate and explore.

5. Conclusions

   In conclusion, our study indicates that AKR1C2 knockdown promotes
   ferroptosis in LUAD cells and inhibits their proliferation, migration,
   invasion, and tumor growth. AKR1C2 may be a potential target for the
   treatment of lung cancer.

Supporting information

   S1 Raw images. All raw western blot images within this study.

   (PDF)
   [95]pone.0325995.s001.pdf^ (384.2KB, pdf)
   S1 File. Original data.

   (XLSX)
   [96]pone.0325995.s002.xlsx^ (17.4KB, xlsx)
   S2 File. RCode used in this study.

   (DOCX)
   [97]pone.0325995.s003.docx^ (21.2KB, docx)

Data Availability

   All relevant data are within the paper and its [98]Supporting
   information files.

Funding Statement

   The author(s) received no specific funding for this work.

References