Abstract

   There is an urgent necessity to devise efficient tactics to tackle the
   inevitable development of resistance to osimertinib, which is a
   third‐generation epidermal growth factor receptor (EGFR) inhibitor used
   in treating EGFR‐mutant nonsmall cell lung cancer (NSCLC). This study
   demonstrates that combining itraconazole with osimertinib
   synergistically reduces the proliferation and migration, enhances the
   apoptosis of osimertinib‐resistant cells, and effectively inhibits the
   growth of osimertinib‐resistant tumors. Mechanistically, itraconazole
   combined with osimertinib promotes the proteasomal degradation of sonic
   hedgehog (SHH), resulting in inactivation of the SHH/Dual‐specificity
   phosphatase 13B (DUSP13B)/p‐STAT3 and Hedgehog pathways, suppressing
   Myc proto‐oncogene protein (c‐Myc). Additionally, DUSP13B interacts
   with signal transducer and activator of transcription 3 (STAT3) and
   modulates its phosphorylation. Interestingly, it is observed that SHH
   overexpression partially rescues the synergistic effects of this
   combination treatment strategy through the SHH/DUSP13B/p‐STAT3
   signaling axis. Moreover, it is found that SHH, (GLI1), p‐STAT3, and
   DUSP13B play significant predictive roles in osimertinib resistance. In
   lung adenocarcinoma, p‐STAT3 is positively correlated with SHH but
   negatively correlated with DUSP13B. Together, these results highlight
   the crucial role of itraconazole in reversing the acquired resistance
   to osimertinib and provide a scientific rationale for the therapeutic
   strategy of combining osimertinib with itraconazole.

   Keywords: DUSP13B, itraconazole, osimertinib resistance, p‐STAT3, SHH
     __________________________________________________________________

   Itraconazole directly binds to sonic hedgehog (SHH) and promotes its
   ubiquitin‐mediated degradation, which results in the upregulation of
   DUSP13B and dephosphorylation of STAT3. This inactivates the
   SHH/DUSP13B/p‐STAT3 axis and the Hedgehog pathway, leading to the
   suppression of c‐Myc and contributing to the reversal of osimertinib
   resistance.

   graphic file with name ADVS-12-2409416-g006.jpg

1. Introduction

   Lung cancer constitutes 11.4% of the total cancer incidence and 18.0%
   of global cancer‐related deaths.^[ [42]^1 ^] The increased application
   of low‐dose computed tomography screening has improved the early
   detection rates of lung cancer, leading to a decrease in mortality.
   However, most patients are diagnosed with distant metastases, and the
   efficacy of traditional treatment modalities remains unsatisfactory.^[
   [43]^2 , [44]^3 ^] Among Asian populations, EGFR gene mutations are the
   most prevalent driver mutations in lung cancer, with mutation rates
   ranging from 30% to 50%.^[ [45]^4 ^] EGFR‐TKIs are small‐molecule drugs
   that specifically target mutations in the EGFR gene. They competitively
   bind to the ATP‐binding site of EGFR, inhibiting EGFR
   autophosphorylation, thereby blocking signal transduction and exerting
   antitumor effects.^[ [46]^5 ^] Following treatment with first‐ and
   second‐generation EGFR‐TKIs, the majority of patients ultimately
   develop a T790M resistance mutation. Osimertinib, a third‐generation
   EGFR‐TKI, can overcome this resistance, significantly prolonging the
   survival of patients with EGFR‐mutant lung cancer. However, owing to
   tumor heterogeneity and the pressure of drug selection, patients
   treated with osimertinib ultimately develop resistance.^[ [47]^6 ,
   [48]^7 ^]

   The mechanisms leading to osimertinib resistance mainly fall into two
   categories: EGFR‐dependent and EGFR‐independent.^[ [49]^8 ^]
   EGFR‐independent mechanisms mainly involve the activation of
   alternative pathways (such as MET amplification, activation of the
   phosphatidylinositol 3‐kinase (PI3K) and RAS‐mitogen‐activated protein
   kinases (MAPK) pathway, and overexpression of AXL), and histological
   transformation.^[ [50]^8 ^] Although some progress has been made in
   understanding osimertinib resistance, owing to its heterogeneity and
   complexity, we are still far from fully elucidating its complete
   mechanisms, and solutions to overcome osimertinib resistance have not
   yet been found. Therefore, more research is needed to explore the
   mechanisms of acquired resistance to osimertinib and find solutions to
   overcome it, ultimately improving the prognosis of patients with lung
   cancer.

   Drug repurposing is an important strategy in drug development, as it
   significantly reduces the cost of drug research by identifying drugs
   from existing clinical therapies that can reverse resistance to
   osimertinib. Preliminary screening revealed that itraconazole inhibited
   the proliferation of osimertinib‐resistant cells. Itraconazole is a
   widely used antifungal drug in clinical practice. Recently, several
   studies have indicated that itraconazole not only exhibits antifungal
   activity but also exerts inhibitory effects on various malignancies,
   including hepatocellular carcinoma, basal cell carcinoma, prostate
   cancer, and melanoma.^[ [51]^9 ^] Itraconazole exerts antitumor effects
   via multiple pathways. Studies have demonstrated that itraconazole can
   inhibit the growth of liver cancer cells and promote apoptosis through
   the AKT/mTOR/S6K, reactive oxygen species (ROS), and Wnt/β‐catenin
   pathways, thereby exerting anticancer effects.^[ [52]^10 ^] In
   esophageal cancer, itraconazole acts by inhibiting the HER2/AKT
   signaling pathway.^[ [53]^11 ^] Although itraconazole exerts potent
   antitumor effects, its specific molecular mechanisms are not fully
   understood. To date, no studies have reported the potential application
   of itraconazole in overcoming acquired resistance to osimertinib.

   The Hh pathway is highly conserved and is primarily composed of
   ligands, receptors, transcription factors, and downstream target genes.
   Mammals have three types of ligands: Indian Hedgehog (IHH), Desert
   Hedgehog (DHH), and Sonic Hedgehog (SHH). Among them, SHH is the most
   important. When the SHH ligand is present, it binds to the receptor
   protein PTCH1, leading to the translocation of the transcription factor
   GLI into the nucleus and initiating the transcription of downstream
   target genes.^[ [54]^12 , [55]^13 ^] Recently, studies have found that
   dysregulated activation of the Hh signaling pathway correlates with
   drug resistance. Research has found that high SHH expression is related
   to a poor objective response rate to EGFR‐TKIs and shorter
   progression‐free survival.^[ [56]^14 ^] Furthermore, studies have found
   that using smoothened (SMO) inhibitors to block the hedgehog pathway
   restores the sensitivity of resistant cells to EGFR‐TKIs.^[ [57]^15 ^]

   Signal transducer and activator of transcription 3 (STAT3) belongs to
   the STAT family of proteins and is activated by the Janus kinase
   (JAK)/STAT pathway. JAK is a tyrosine kinase protein that is activated
   when cytokines bind to surface receptors, leading to the
   phosphorylation and activation of STAT3. Activated STAT3 enters the
   nucleus in the form of dimers and transcribes downstream target
   genes.^[ [58]^16 ^] Research has shown that STAT3 activation can also
   occur through JAK‐independent mechanisms, such as phosphorylation of
   the Tyr705 site by pyruvate kinase M2.^[ [59]^17 ^] In the past several
   years, studies have found that p‐STAT3 is associated with EGFR‐TKI
   resistance, and inhibition of the p‐STAT3 can enhance the sensitivity
   of lung cancer cells to EGFR‐TKIs.^[ [60]^18 ^]

   Dual‐specificity phosphatase 13B (DUSP13B) belongs to the DUSPs protein
   family and can dephosphorylate phosphorylated tyrosine and
   serine/threonine residues.^[ [61]^19 ^] Research has suggested that the
   coexpression of DUSP13B and DUSP4 weakens transforming growth factor
   β‐1 (TGFβ‐1)‐mediated invasion, migration, and chemotherapy resistance
   in lung cancer.^[ [62]^20 ^] However, there have been no investigations
   into the involvement of DUSP13B in osimertinib resistance.

   Autophagy is a process of self‐degradation and recycling of cellular
   components, and is essential for maintaining cellular homeostasis and
   survival. It is typically classified into macroautophagy,
   chaperone‐mediated autophagy, and microautophagy.^[ [63]^21 , [64]^22
   ^] Autophagy plays a crucial role in cancer progression, metastasis,
   and drug resistance. First, it can serve as a protective mechanism
   leading to resistance to chemotherapy. It has been shown that autophagy
   is involved in cisplatin resistance in lung cancer cells, and autophagy
   inhibitors can enhance sensitivity to cisplatin.^[ [65]^23 ^] In
   addition, chemotherapeutic drugs can also induce autophagic cell death.
   It has been found that esomeprazole inhibits the proliferation of
   paclitaxel‐resistant cells by inducing autophagy.^[ [66]^24 ^]
   Additionally, autophagy has been implicated in the resistance to
   EGFR‐TKIs. Research has revealed that an HIF‐1α inhibitor enhances
   gefitinib‐induced apoptosis by inhibiting autophagy.^[ [67]^25 ^] Due
   to the dual nature of autophagy, it is essential to explore whether
   autophagy is induced and its role in the therapeutic process of
   anticancer drugs to fully enhance anticancer efficacy.

   This study aimed to explore the role of itraconazole in overcoming
   acquired resistance to osimertinib and its specific molecular
   mechanisms, thereby providing new perspectives and ideas for overcoming
   osimertinib resistance.

2. Experimental Section

2.1. Reagents and Cell Lines

   Osimertinib was purchased from Selleck (Houston, TX). Itraconazole,
   chloroquine, MG132, and CHX were obtained from MedChemExpress (Monmouth
   Junction, NJ). All drugs were dissolved in Dimethyl sulfoxide (DMSO).
   The complete list of antibodies is provided in Table [68]S1 (Supporting
   Information). SHH protein was purchased from SinoBiological (Beijing,
   China). Immunoprecipitation Assay Kit was purchased from Beyotime
   (Shanghai, China). The Annexin V‐FITC/7AAD Apoptosis Detection Kit was
   procured from MultiSciences (Hangzhou, China). The PC‐9/AR
   (osimertinib‐resistant cell line) was generously gifted by Prof.
   Shi‐Yong Sun (Emory University, USA). HCC827/AR cells were constructed
   using a concentration gradient dependency. PC‐9 and HCC827 are
   osimertinib‐sensitive cell lines.

2.2. Cell Counting Kit‐8 (CCK‐8)

   Cells were plated at an appropriate density in a 96 well plate, and
   drug treatment (either alone or in combination) was commenced the
   following day. Cell viability was evaluated employing the Cell Counting
   Kit‐8 (CCK‐8). The combination index (CI) for drug interactions was
   estimated using the CompuSyn software. A CI value greater than 1 is
   indicative of an antagonistic relationship. A CI value less than 1
   signifies a synergistic effect and a CI value equal to 1 represents an
   additive effect.

2.3. Colony Formation Assays

   Cells were plated at an appropriate density in a 6 well plate, and drug
   treatment (either alone or in combination) was commenced the following
   day for 9–12 days. The drug‐containing medium was refreshed at regular
   intervals of 2–3 days. Subsequently, the colonies underwent a fixation
   process utilizing 4% paraformaldehyde, followed by a staining procedure
   with crystal violet for a duration of 20 min. Finally, colonies were
   photographed and counted.

2.4. Apoptosis Assay and Cell Cycle Analysis

   Cells were collected, washed with PBS, and detected using the Apoptosis
   Detection Kit. The apoptosis rate was examined using the FlowJo V10
   software. Cell cycle analysis was performed using a reagent kit and
   analyzed by Modifit software.

2.5. Western Blotting

   After treating the cells with various methods, they were lysed, and the
   protein supernatant was collected. Protein samples underwent
   electrophoretic separation via Sodium Dodecyl Sulfate Polyacrylamide
   Gel Electrophoresis (SDS‐PAGE) and were subsequently transferred onto a
   Polyvinylidene Fluoride (PVDF) membrane for further analysis. After
   blocking with a 5% skim milk solution at ambient temperature for a
   duration of 2 h, the membrane underwent incubation with the primary
   antibody at 4 °C for an overnight period. Following the primary
   antibody incubation, the membrane was subjected to a secondary antibody
   incubation step at 37 °C for a period of 1 h and detected using an
   enhancedchemiluminescence (ECL) system.

2.6. Animal Experiments

   Female BALB/c nude mice were housed in a pathogen‐free facility.
   PC‐9/AR cells were injected subcutaneously into nude mice. Once the
   tumor volume reached between 50 and 100 mm^3, female BALB/c nude mice
   were randomly assigned to four distinct experimental groups, each
   consisting of six mice: a vehicle group, an itraconazole alone group
   (75 mg kg^−1 day^−1), an osimertinib alone group (5 mg kg^−1 day^−1),
   and a combination therapy group. Tumor volume and body mass were
   measured at a frequency of every 3 days. The tumor volume was
   determined as follows: V = length × (width^2)/2. After excision, the
   tumors were weighed and subsequently immersed in 10% neutral buffered
   formalin for fixation. The experimental procedures involving animals
   were authorized by the Animal Welfare and Ethics Review Committee of
   Hunan Yuantai Biotechnology (YT‐T‐20211209‐1) and complied with the
   ethical regulations.

2.7. Immunohistochemistry (IHC) Staining

   IHC staining of human NSCLC tissue specimens and nude mouse tumor
   tissue specimens was conducted following a previously described
   protocol.^[ [69]^26 , [70]^27 ^] The semiquantitative evaluation method
   was as follows: total score = intensity score×percentage score. The
   intensity scores encompassed four levels: 0 (negative), 1 (weak), 2
   (moderate), and 3 (strong), while the extent of staining was
   categorized based on the proportion of stained cells: 0 (no staining),
   1 (1%–25%), 2 (26%–50%), 3 (51%–75%), and 4 (76%–100%).

2.8. Lentivirus Infection

   Cells were seeded into 24 well plate at an appropriate density and then
   infected with the viruses LV‐SHH, LV‐DUSP13B, and the control virus
   LV‐NC. Following a 48‐h infection period, cells underwent puromycin
   screening (2–5 µg µL^−1) to establish stable cell lines.

2.9. Quantitative PCR Analysis

   Total RNA extraction was performed using the TRIzol reagent
   (Invitrogen). Reverse transcription and quantitative reverse
   transcription PCR were executed according to the Takara protocol.
   Primers used are listed in Table [71]S2 (Supporting Information).

2.10. Isothermal Titration Calorimetry (ITC) Measurement

   The ITC experiments were conducted at 25 °C. First, itraconazole and
   SHH protein were diluted in phosphate‐buffered saline (PBS) containing
   5% DMSO to final concentrations of 50 and 5 µm, respectively. The SHH
   protein was added to the cells and titrated with 50 µm itraconazole.
   Dispense 2.5 µL of itraconazole for each titration, with a total of 20
   titrations. Data analysis was used NanoAnalyze Software.

2.11. Coinmunoprecipitation (Co‐IP)

   The cellular lysate was subjected to an overnight incubation at 4 °C
   with 3 µg each of DUSP13B and STAT3 antibodies, along with a negative
   control IgG antibody. After adding Protein A/G beads, the resulting
   mixture was further incubated for 3 h at 4 °C. After washing the beads
   to remove nonspecific interactions, the tightly bound proteins were
   eluted and subsequently heated to 100 °C for 10 min.

2.12. Immunofluorescence (IF)

   The cells were subjected to a 30‐min fixation protocol at 37 °C using
   4% paraformaldehyde, followed by permeabilization with 0.25% Triton
   X‐100 for 30 min. Subsequently, they were blocked with 5% BSA for 1 h
   and then incubated with the primary antibody overnight at 4 °C. Next
   day, the cells were incubated with fluorescent secondary antibody at 37
   °C for 1 h and DAPI for 5 min.

2.13. Bioinformatics Databases and Clinical Samples

   The dataset [72]GSE193258 was sourced from the GEO database, focusing
   on osimertinib resistance and comprising four cell lines with EGFR
   mutations (PC9, HCC827, H1975, and HCC2935). R software was used for
   bioinformatic analyses. The relationship between the mRNA expression
   levels of different genes and EGFR gene mutation status was assessed
   using the TIMER2.0 website ([73]http://timer.cistrome.org/).
   Additionally, the association between the mRNA expression levels of
   various genes was investigated using the GEPIA2 website.

   Moreover, this study collected ten pairs of lung cancer tissue
   specimens before and after osimertinib resistance from the pathology
   department of the Second Xiangya Hospital of Central South University.
   Additionally, tumor tissue were obtained from 108 patients with lung
   adenocarcinoma who underwent surgical treatment, along with
   clinicopathological characteristics and prognosis data (Table [74]1 ).
   This study was approved by the Scientific Research Ethics Committee.

Table 1.

   Clinicopathological features of 108 cases of lung adenocarcinoma.
   Clinicopathological features         N [%]
   Gender
   Female                             61 (56.5)
   Male                               47 (43.5)
   Age (years)
   <60                                62 (57.4)
   ≥60                                46 (42.6)
   Pathological degree
   Well and moderated differentiation 72 (66.7)
   Poor differentiation               36 (33.3)
   EGFR mutation status
   Mutant‐Type                        80 (74.1)
   Wild‐Type                          28 (25.9)
   Clinical stages
   Stage I                            47 (43.5)
   Stage II and III                   61 (56.5)
   Lymph node metastasis
   Yes                                40 (37.0)
   No                                 68 (63.0)
   Smoking history
   Yes                                27 (25.0)
   No                                 81 (75.0)
   [75]Open in a new tab

2.14. Transmission Electron Microscope (TEM)

   The cells were harvested and then treated with a 2.5% glutaraldehyde
   solution for fixation at 4 °C for 4–6 h. Subsequently, the samples were
   sent to an electron microscopy room for further processing.
   Transmission electron microscopy was used to capture digital images.

2.15. Statistical Analysis

   Data processing and analysis were conducted using GraphPad Prism
   version 8.0, SPSS 24.0, and R 4.2.1. Statistical differences were
   accomplished using unpaired Student's t‐tests and ANOVA test. The
   Wilcoxon signed‐rank test was employed to analyze the expression levels
   of different proteins in lung cancer tissues before and after
   osimertinib resistance. To assess the correlation between various
   proteins, the Spearman's coefficient was applied. Data were presented
   as mean ± SD and obtained from at least three independent experiments.
   Statistical significance was defined as P < 0.05.

3. Results

3.1. Itraconazole Combined with Osimertinib had a Synergistic Effect on
Osimertinib‐Resistant NSCLC Cells In Vitro

   Drug repurposing is an important strategy in drug development, as it
   significantly reduces the cost of drug research by identifying drugs
   from existing clinical drugs that can reverse resistance to
   osimertinib. Preliminary screening revealed the ability of itraconazole
   to inhibit the proliferation of osimertinib‐resistant cells (Figure
   [76]S1, Supporting Information). To further elucidate whether the
   combination of itraconazole and osimertinib demonstrates a synergistic
   antitumor effect, we treated osimertinib‐resistant cells with varying
   concentrations of these two drugs in combination and assessed cell
   proliferation activity after 48 h. We then calculated the Combination
   Index (CI) and found that the CI values were <1 when itraconazole was
   combined with osimertinib in HCC827/AR and PC‐9/AR cells, signifying
   their synergistic antitumor effects (Figure [77] 1A). Moreover,
   itraconazole augmented the osimertinib's ability to suppress cell
   proliferation and colony formation (Figure [78]1B,C). We evaluated the
   levels of apoptosis and observed that itraconazole enhanced the
   apoptotic effect of osimertinib (Figure [79]1D). Additionally, we also
   investigated the expression of apoptosis‐associated proteins and
   observed that itraconazole in combination with osimertinib promoted the
   expression of Bax and cleaved PARP, while suppressing the expression of
   Bcl‐xL and Mcl‐1, both recognized as antiapoptotic proteins
   (Figure [80]1E). Furthermore, we assessed the effect of the combination
   therapy on the cell cycle and noted that the combination treatment
   synergistically induced G0/G1 phase arrest (Figure [81]S2, Supporting
   Information). Interestingly, we found that combination therapy
   synergistically inhibited the migration ability of
   osimertinib‐resistant cells, as evidenced by the decreased levels of
   MMP9, MMP2, and N‐cadherin proteins (Figure [82]1F–H).

Figure 1.

   Figure 1
   [83]Open in a new tab

   Itraconazole and osimertinib had a synergistic effect in vitro. A) CI
   of itraconazole in combination with osimertinib in PC‐9/AR and
   HCC827/AR cells. The numbers represented the CI values, which were
   calculated using CompuSyn software. B,C) The effect of itraconazole in
   combination with osimertinib on the proliferation of PC‐9/AR and
   HCC827/AR cells was determined by CCK8 and colony formation. D)
   Itraconazole combined with osimertinib synergistically promoted
   apoptosis of PC‐9/AR and HCC827/AR cells examined by flow cytometry. E)
   The expression of apoptosis‐related proteins was detected by western
   blotting. F,G) Itraconazole in combination with osimertinib
   synergistically inhibited migration demonstrated by wound healing assay
   and transwell assay. H) The expression of migratory invasion‐associated
   proteins was detected by western blotting. Osim: osimertinib; Itrac:
   itraconazole; Comb: the combination of osimertinib and itraconazole.
   Data were presented as mean ± SD (n = 3), and the P value was
   calculated using unpaired student's t‐tests and two‐way ANOVA test. **P
   < 0.01; ***P < 0.001; ****P < 0.0001.

3.2. Itraconazole in Combination with Osimertinib Exerted its Effects Through
the SHH/DUSP13B/p‐STAT3 Axis

   To gain insights into the specific molecular mechanism by which
   itraconazole reverses the acquired resistance to osimertinib, we
   conducted RNA‐seq on PC‐9/AR cells treated with itraconazole or DMSO. A
   volcano plot of the differentially expressed genes was depicted in
   Figure [84] 2A. GSEA and KEGG pathway enrichment analysis suggested
   that itraconazole might target the Hedgehog and JAK‐STAT signaling
   pathways (Figure [85]2B,C). Therefore, we evaluated the expression of
   key proteins in these pathways, such as SHH, PTCH1, GLI1, STAT3,
   p‐STAT3, and its downstream target protein c‐Myc, using western
   blotting, both in the presence of itraconazole alone and in combination
   with osimertinib (Figure [86]S3 (Supporting Information) and
   Figure [87]2D). We also found that the mRNA expression of SHH was
   slightly reduced after treatment with itraconazole (Figure [88]S3,
   Supporting Information). In order to gain a thorough understanding of
   the potential interactions between the Hh and STAT3 pathways, we
   overexpressed the SHH plasmid in 293T cells and subsequently assessed
   the key proteins of these two signaling pathways. The results
   (Figure [89]2E) indicated a notable elevation in the expression of
   p‐STAT3 (Tyr705) and c‐Myc after SHH overexpression, suggesting a
   potential interaction between the Hh pathway and the STAT3 pathway via
   the SHH‐p‐STAT3 axis.

Figure 2.

   Figure 2
   [90]Open in a new tab

   Itraconazole combined with osimertinib exerted effects through the
   SHH/DUSP13B/p‐STAT3 axis. A) Volcano plot of differential gene
   expression before and after itraconazole treatment. B,C) Potential
   molecular mechanisms were identified through KEGG and GSEA analysis. D)
   Itraconazole combined with osimertinib modulated the key proteins of
   Hedgehog and STAT3 signaling pathway. E) SHH regulated the level of
   STAT3 phosphorylation. F) Regulation of JAKs proteins was detected by
   western blotting. G) The mRNA expression of DUSP13B after SHH
   overexpression was detected by qPCR. LV‐NC: the control group; LV‐SHH:
   stable overexpression of the SHH group. H–J) The mRNA and protein
   expression of DUSP13B after the combination of itraconazole with
   osimertinib. K) DUSP13B exhibited a dephosphorylation effect on STAT3,
   as confirmed by in vivo phosphorylation experiments. L) The result of
   molecular docking between STAT3 and DUSP13B. Blue represented STAT3 and
   green represented DUSP13B. M) Co‐IP demonstrated the binding of DUSP13B
   to STAT3. N) IF confirmed the colocalization between DUSP13B and STAT3
   in HCC827/AR cells. DUSP13B is labeled in green, STAT3 in red, and the
   nucleus in blue. Osim: osimertinib; Itrac: itraconazole; Comb: the
   combination of osimertinib and itraconazole. Data were presented as
   mean ± SD (n = 3), and the P value was calculated using unpaired
   student's t‐tests. **P < 0.01.

   Based on these findings, we initially confirmed the existence of the
   SHH‐p‐STAT3 signaling axis. As SHH has not been reported to have kinase
   or phosphatase activity, we speculated that the regulation of the
   SHH‐p‐STAT3 signaling axis by the combination of itraconazole and
   osimertinib might involve other kinases or phosphatases. First, we
   examined the expression levels of the most common kinases in the STAT3
   pathway and found no significant changes in the JAK1, JAK2, and TYK2
   proteins (Figure [91]2F). It has been shown that dual‐specificity
   phosphatases (DUSPs) play a crucial role in cellular physiology by
   dephosphorylating residues of phosphoserine, phosphothreonine, and
   phosphotyrosine.^[ [92]^28 ^] Since the Tyr705 site of p‐STAT3 is a
   phosphorylated tyrosine, we further focused our attention on DUSPs. As
   shown in Figure [93]2A, DUSP1, DUSP5, DUSP10, and DUSP13B levels were
   significantly increased after treatment with itraconazole. Thus, we
   conducted further analysis to examine the correlation between these
   DUSPs and SHH and found a significant negative correlation between
   DUSP13B and SHH (Figure [94]S4, Supporting Information). Furthermore,
   we noted a substantial reduction in the mRNA expression of DUSP13B
   after SHH overexpression (Figure [95]2G). Therefore, we hypothesized
   that the combination of itraconazole and osimertinib most likely
   induces dephosphorylation of p‐STAT3 by upregulating DUSP13B. Indeed,
   both the mRNA and protein levels of DUSP13B were markedly elevated
   after combination therapy (Figure [96]2H–J).

3.3. DUSP13B Interacted with STAT3 and Dephosphorylated STAT3

   To further validate whether DUSP13B can dephosphorylate p‐STAT3, we
   conducted in vivo phosphorylation experiments and found that DUSP13B
   had a dephosphorylation effect on p‐STAT3 (Figure [97]2K).
   Subsequently, we investigated whether DUSP13B achieves
   dephosphorylation by directly binding to STAT3. Initially, we performed
   molecular docking analysis of STAT3 and DUSP13B using the ZDOCK online
   website. The docking result revealed that the docking binding free
   energy ΔiG was <0, indicating that the docking was stable
   (Figure [98]2L). To further validate the physical interaction between
   DUSP13B and STAT3, we conducted co‐IP and immunofluorescence
   experiments. These experiments confirmed that DUSP13B interacted with
   STAT3 (Figure [99]2M,N).

3.4. Overexpression of DUSP13B Reversed Osimertinib Resistance in NSCLC

   As there have been no reports on the involvement of DUSP13B in acquired
   resistance to osimertinib, we investigated the role of DUSP13B in
   osimertinib‐acquired resistance. Remarkably, we observed a significant
   reduction in the mRNA and protein expression levels of DUSP13B in both
   PC‐9/AR and HCC827/AR cells (Figure [100]S5A,B, Supporting
   Information). Based on these findings, we proceeded to construct
   DUSP13B overexpressing stable cell lines. Intriguingly, we found that
   overexpressing DUSP13B resulted in a reduction of the IC50 value
   osimertinib‐resistant cells (Figure [101]S5C,D, Supporting
   Information). Furthermore, our investigations revealed that
   overexpression of DUSP13B not only inhibited the proliferation and
   migration of osimertinib‐resistant cells but also promoted apoptosis
   (Figure [102]S5E–G, Supporting Information). Taken together, these
   findings strongly indicate that overexpression of DUSP13B could be a
   promising approach to overcome osimertinib resistance in NSCLC.

3.5. Overexpression of SHH Rescued the Synergistic Effect of Itraconazole and
Osimertinib

   We further elucidated the mechanism of action underlying the
   combination of itraconazole and osimertinib in reducing SHH protein
   expression levels. We initially used AutoDock software for molecular
   docking simulations of Itraconazole and SHH, and found that
   itraconazole had the capability to bind to SHH (Figure [103] 3A). So,
   we used ITC to further examine the interaction between SHH and
   itraconazole and found that there was a direct binding between
   itraconazole and SHH (Figure [104]3B). We then used MG132 to treat
   osimertinib‐resistant cells and observed that MG132 could restore the
   reducing effect of the combination therapy on SHH protein
   (Figure [105]3C). Furthermore, we conducted CHX assays and found that
   SHH degradation was faster in osimertinib‐resistant cells exposed to a
   combination of itraconazole and osimertinib than in the DMSO group,
   indicating that the combination therapy facilitated the degradation of
   SHH (Figure [106]3D). To further confirm that combination therapy
   promotes the ubiquitin‐mediated degradation of SHH protein, we measured
   the levels of polyubiquitinated SHH in osimertinib‐resistant cells. As
   shown in Figure [107]3E, combination therapy led to a significant
   increase in SHH polyubiquitination. In summary, these results indicated
   that combination therapy induced SHH ubiquitin‐mediated degradation.

Figure 3.

   Figure 3
   [108]Open in a new tab

   Overexpression of SHH rescued the synergistic effect of itraconazole
   and osimertinib. A) The molecular docking schematic of itraconazole and
   SHH. B) Isothermal titration calorimetry was used to measure the
   binding between itraconazole and STAT3. C) MG132 abolished the ability
   of itraconazole combined with osimertinib to decrease SHH level. D)
   Itraconazole combined with osimertinib shortened the half‐life of SHH
   protein. E) The HCC827/AR cells were treated with combination therapy
   for 36 h, followed by treatment with MG132 for 6 h before harvesting.
   Ubiquitination levels were then assessed after immunoprecipitation with
   SHH antibody. F) Successful establishment of stable cell lines
   overexpressing SHH was validated by western blotting. G,H)
   Overexpression of SHH partially rescued the synergistic
   antiproliferative effect of itraconazole combined with osimertinib by
   CCK8 and colony formation assay. I) Overexpression of SHH partially
   rescued the synergistic proapoptotic ability of itraconazole combined
   with osimertinib. J) The expression of apoptosis‐related proteins was
   detected by western blotting. K) Overexpression of SHH partially
   rescued the synergistic antimigratory capacity of itraconazole combined
   with osimertinib. L) The expression of migratory invasion‐associated
   proteins was detected by western blotting. M) Overexpression of SHH
   could partly reverse the regulation of itraconazole combined with
   osimertinib on SHH/DUSP13B/p‐STAT3 signaling axis. Osim: osimertinib;
   Itrac: itraconazole; Comb: the combination of osimertinib and
   itraconazole; CHX: Cycloheximide. Data were presented as mean ± SD (n =
   3), and the P value was calculated using unpaired student's t‐tests. *P
   < 0.05; **P < 0.01; ****P < 0.0001.

   Previous findings have suggested that itraconazole in combination with
   osimertinib exerts its effects through the SHH/DUSP13B/p‐STAT3
   signaling axis. To verify whether the overexpression of SHH could
   rescue the synergistic effect of itraconazole and osimertinib, we
   constructed stable cell lines overexpressing SHH, which were validated
   by western blotting (Figure [109]3F). As expected, overexpression of
   SHH partially rescued the synergistic effects of itraconazole and
   osimertinib, including proliferation, apoptosis, and migration
   (Figure [110]3G–L). In addition, we observed that overexpression of SHH
   could partly reverse the regulation of itraconazole combined with
   osimertinib on the SHH/DUSP13B/p‐STAT3 signaling axis (Figure [111]3M).

3.6. The Combination of Itraconazole and Osimertinib Induced Autophagy in
Osimertinib‐Resistant Cells

   When analyzing the RNA‐seq results, GSEA enrichment analysis suggested
   that itraconazole can induce autophagy in PC‐9/AR cells (Figure [112]
   4A). Therefore, we explored the effect of itraconazole combined with
   osimertinib on autophagy. As depicted in Figure [113]4B, we observed a
   substantial increase in granular LC3, indicating an increase in
   autophagosomes in the combination therapy group. Additionally, the
   ratio of LC3II/LC3I and P62 were also significantly increased
   (Figure [114]4C). mRFP‐GFP‐LC3 was used for real‐time detection of
   autophagy flux, with GFP (green) and RFP (red) tagged to LC3. The green
   fluorescence of GFP on autolysosomes was denatured in an acidic
   environment, resulting in only red fluorescence inside the cells,
   whereas the autophagosomes displayed yellow fluorescence. We noticed a
   substantial rise in the number of yellow dots (autophagosomes) and red
   dots (autolysosomes) in the combination therapy group, suggesting an
   increase in autophagic flux (Figure [115]4D–E). TEM showed that
   itraconazole combined with osimertinib significantly increased the
   count of autophagosomes in osimertinib‐resistant cells
   (Figure [116]4F).

Figure 4.

   Figure 4
   [117]Open in a new tab

   The combination of itraconazole and osimertinib induced autophagy in
   osimertinib‐resistant cells. A) GSEA analysis showed that autophagy was
   enriched in the itraconazole‐treated group. B) IF demonstrated the
   impact of itraconazole combined with osimertinib on LC3. C) The
   expression of autophagy‐related proteins was detected by western
   blotting. D,E) Autophagic flux was analyzed by mRFP‐GFP‐LC3. Red dots
   represented autolysosomes, and yellow dots represented autophagosomes.
   F) Observation of intracellular autophagosomes by TEM. G) CQ further
   inhibited proliferation detected by CCK8 assay. H) CQ further increased
   apoptosis as detected by flow cytometry I) CQ further suppressed the
   migratory capacity. J) The indicated proteins were detected using
   western blotting. Osim: osimertinib; Itrac: itraconazole; Comb: the
   combination of osimertinib and itraconazole; CQ: chloroquine. Data were
   presented as mean ± SD (n = 3), and the P value was calculated using
   unpaired student's t‐tests. **P < 0.01; ***P < 0.001; ****P < 0.0001.

   As mentioned above, the combination of itraconazole and osimertinib
   promotes autophagy in osimertinib‐resistant cells. To clarify the
   specific role of autophagy, we used chloroquine (CQ) to inhibit
   autophagy by suppressing the fusion and degradation of autolysosomes.^[
   [118]^29 ^] Compared with the combination drug group, CQ combined with
   itraconazole and osimertinib further inhibited the growth of
   osimertinib‐resistant cells, as shown by the CCK8 assay
   (Figure [119]4G). Analysis of apoptosis (Figure [120]4H) revealed that
   the synergistic proapoptotic effect of itraconazole in combination with
   osimertinib was further enhanced after inhibiting autophagy using CQ.
   Moreover, the results indicated that CQ further enhanced the
   synergistic antimigratory effect of the combination of itraconazole and
   osimertinib (Figure [121]4I). We performed western blotting experiments
   and found that after inhibiting autophagy, the regulatory effects of
   itraconazole combined with osimertinib on apoptosis‐ and
   migration‐related proteins were further enhanced. Unexpectedly, we
   found that the levels of p‐STAT3 and SHH were further reduced after
   inhibiting autophagy (Figure [122]4J).

3.7. Itraconazole and Osimertinib had a Synergistic Effect In Vivo

   Furthermore, to clarify whether the combination of itraconazole and
   osimertinib exhibits synergistic effects in vivo and to establish a
   robust theoretical basis for its clinical application, we conducted
   preliminary validation of the therapeutic efficacy and dosing safety of
   the combination therapy in vivo. The results (Figure [123] 5A,B)
   revealed a significant decrease in tumor volume within the combination
   group compared to the other groups. Additionally, the combination of
   itraconazole and osimertinib markedly reduced the tumor weight
   (Figure [124]5C). The growth curves of the nude mice were shown in
   Figure [125]5D. Moreover, we conducted H&E staining of the liver,
   heart, kidney, and spleen of nude mice and observed no damage to these
   organs across the four groups, indicating that the combination of
   itraconazole and osimertinib did not result in significant toxic side
   effects (Figure [126]5E). We further conducted H&E and Ki‐67 staining
   of the subcutaneous tumor tissues of mice. As shown in Figure [127]5F,
   the Ki‐67 expression level was the lowest in the combination group,
   indicating that the combination significantly reduced the proliferative
   capacity of tumor tissues. To investigate whether itraconazole combined
   with osimertinib can suppress the expression of the SHH/DUSP13B/p‐STAT3
   signaling axis in vivo, IHC staining was performed. As expected, the
   expression of SHH, p‐STAT3, and GLI1 was markedly decreased in the
   combination group, whereas DUSP13B expression was significantly
   increased, which was consistent with our in vitro findings
   (Figure [128]5G). In addition, we also validated the effect of combined
   treatment on the autophagy protein LC3 in vivo, and found that the
   combined treatment group had the highest expression of LC3 protein
   (Figure [129]S6, Supporting Information).

Figure 5.

   Figure 5
   [130]Open in a new tab

   The combination of itraconazole and osimertinib effectively inhibited
   the growth of osimertinib‐resistant tumors in vivo. A) Subcutaneous
   tumors were excised from nude mice, and the tumor size was observed and
   photographed. B) Tumor size was measured and calculated as, V = length
   × (width^2)/2. C) Differences in tumor weight of subcutaneously
   transplanted tumors. D) Changes in body weight among four groups of
   nude mice. E) H&E staining of the heart, liver, kidney, and spleen of
   nude mice. F) Representative images of H&E and Ki‐67 staining. G)
   Representative images of IHC staining of SHH/DUSP13B/p‐STAT3 axis.
   Osim: osimertinib; Itrac: itraconazole; Comb: the combination of
   osimertinib and itraconazole. Data were presented as mean ± SD (n = 6),
   and the P value was calculated using unpaired Student's t‐tests and
   two‐way ANOVA test. **P < 0.01; ***P < 0.001.

3.8. The Expression of SHH/DUSP13B/p‐STAT3 in Lung Adenocarcinoma Tissues and
their Correlation with Osimertinib Resistance

   We first investigated the correlation between SHH, GLI1, DUSP13B, and
   STAT3, and the mutation status of the EGFR gene using the TIMER2.0
   database (Figure [131] 6A). Surprisingly, the mRNA levels of SHH and
   GLI1 were markedly upregulated in lung adenocarcinoma tissues with EGFR
   mutations (P < 0.0001 and P = 0.048, respectively). Conversely, the
   mRNA level of DUSP13B was downregulated in lung adenocarcinoma tissues
   with EGFR mutations (P = 0.025). We then utilized the GEPIA2 online
   platform to examine the correlation among the mRNA levels of SHH, GLI1,
   DUSP13B, and STAT3 in lung adenocarcinoma tissues from the TCGA
   dataset. The results revealed significant positive correlations between
   SHH with GLI1, and STAT3 (r = 0.34, P < 0.0001; r = 0.16, P = 0.00 032)
   but a notable negative correlation with DUSP13B (r = −0.19, P <
   0.0001). Additionally, a positive correlation between GLI1 and STAT3 (r
   = 0.15, P = 0.00 093) and a negative correlation between DUSP13B (r =
   −0.16, P = 0.00 054) were observed. Additionally, our findings revealed
   a pronounced negative association between the levels of STAT3 and
   DUSP13B (r = −0.11, P = 0.016; Figure [132]S7, Supporting Information).

Figure 6.

   Figure 6
   [133]Open in a new tab

   The expression of the SHH/DUSP13B/p‐STAT3 signaling axis. A) The
   correlation between SHH, GLI1, PTCH1, and DUSP13B with the mutation
   status of the EGFR gene. B) The relationship between SHH, DUSP13B, and
   p‐STAT3 proteins and the EGFR gene mutation status. C) The localization
   and expression of SHH, DUSP13B, and p‐STAT3 proteins in lung
   adenocarcinoma tissues. D) GEO database validated the involvement of
   Hedgehog pathway in osimertinib resistance. E) GEO database validated
   the involvement of JAK/STAT3 pathway in osimertinib resistance. F) The
   protein expression of SHH, GLI1, DUSP13B, and p‐STAT3 in lung cancer
   tissues before and after osimertinib resistance were examined with IHC
   staining. Data were presented as mean ± SD, and the P value was
   calculated using the wilcoxon signed‐rank test and chi‐squared test. *P
   < 0.05; **P < 0.01.

   In addition, we conducted IHC staining on 108 lung adenocarcinoma
   tissues and assessed the association between the protein levels of SHH,
   DUSP13B, p‐STAT3, and EGFR gene mutation status. The results
   (Figure [134]6B) revealed that the expression rate of SHH protein
   exhibited a substantial increase in lung adenocarcinoma tissues with
   EGFR gene mutations (P = 0.012; 83.8%). Moreover, a higher expression
   rate of p‐STAT3 protein was observed in EGFR mutated‐type lung
   adenocarcinoma tissues (P = 0.029). Nevertheless, no significant
   correlation was observed between DUSP13B protein levels and the
   presence of EGFR mutations (P > 0.05). Subsequently, we analyzed the
   correlation between SHH, DUSP13B, and p‐STAT3 proteins. As shown in
   Table [135]2 and Figure [136]6C, we found a notable positive
   correlation between p‐STAT3 and SHH (r = 0.235, P = 0.014) but no
   significant correlation between p‐STAT3 and DUSP13B (r = 0.038, P =
   0.700). Besides, we found a negative correlation between p‐STAT3 and
   DUSP3B (r = −0.234, P = 0.015).

Table 2.

   The association among expression of SHH, DUSP13B, and p‐STAT3 proteins
   in lung adenocarcinoma.
                                         SHH     DUSP13B    p‐STAT3
   SHH
   Spearman's correlation coefficient     1     r = 0.038  r = 0.235
   Sig. (2‐tailed)                              P = 0.700  P = 0.014
   DUSP13B
   Spearman's correlation coefficient r = 0.038     1      r = −0.234
   Sig. (2‐tailed)                    P = 0.700            P = 0.015
   p‐STAT3
   Spearman's correlation coefficient r = 0.235 r = −0.234     1
   Sig. (2‐tailed)                    P = 0.014 P = 0.015
   [137]Open in a new tab

   Furthermore, we downloaded the osimertinib resistance dataset
   [138]GSE193258 and conducted a GSEA enrichment analysis of the acquired
   data. This dataset contains transcriptome sequencing results before and
   after osimertinib resistance in four cell lines with EGFR mutations
   (PC9, HCC827, H1975, and HCC2935). GSEA enrichment analysis revealed an
   enrichment of the Hedgehog signaling pathway in osimertinib‐resistant
   HCC827 and HCC2935 cells (Figure [139]6D), as well as an enrichment of
   the JAK/STAT3 pathway in osimertinib‐resistant HCC827, H1975, and PC‐9
   cells (Figure [140]6E).

   To accurately determine the expression level of the SHH/DUSP13B/p‐STAT3
   axis in osimertinib‐resistant lung cancer tissues, we collected 10
   pairs of clinical lung cancer tissue specimens before and after
   osimertinib resistance and conducted IHC staining. As shown in
   Figure [141]6F, the SHH protein was predominantly expressed in the cell
   membrane and cytoplasm, with higher protein expression after
   osimertinib resistance than before. Both GLI1 and p‐STAT3 were
   primarily expressed in the nucleus and cytoplasm, with higher levels
   observed in postresistant tissues. Furthermore, DUSP13B protein was
   mainly expressed in the cytoplasm, with lower expression levels
   observed in postosimertinib‐resistant lung cancer tissues.

4. Discussion

   EGFR is a well‐known driver gene in lung cancer, with a significant
   percentage of patients carrying mutations in this gene.^[ [142]^30 ,
   [143]^31 ^] The third‐generation EGFR‐TKI osimertinib is an effective
   solution for overcoming resistance triggered by the T790M mutation, a
   common occurrence following treatment with first‐ and second‐generation
   TKIs. However, acquired resistance to osimertinib eventually develops,
   limiting its long‐term clinical utility.^[ [144]^32 , [145]^33 ^] Thus,
   there is a pressing need to investigate the mechanisms underlying
   osimertinib resistance, identify strategies to overcome it, and
   ultimately enhance the prognosis of patients with lung cancer.

   Currently, therapies have been developed to tackle osimertinib
   resistance in combination with other drugs.^[ [146]^34 , [147]^35 ,
   [148]^36 ^] We identified itraconazole as a significant inhibitor of
   osimertinib‐resistant cell proliferation in preliminary screening.
   Therefore, we investigated whether itraconazole can reverse osimertinib
   resistance and its specific molecular mechanisms. Initial assessment of
   the Combination Index indicated a potent synergistic effect of
   itraconazole combined with osimertinib, which was supported by
   subsequent in vitro experiments demonstrating synergistic effects on
   various malignant phenotypes of osimertinib‐resistant cells. Further
   validation in vivo confirmed the therapeutic efficacy of this
   combination in inhibiting the growth of osimertinib‐resistant tumors
   without significant toxic side effects. Ki‐67 staining (a proliferation
   marker^[ [149]^37 ^]) revealed a significant reduction in tumor cell
   proliferation, reinforcing the observed antiproliferative effects.

   To clarify the molecular mechanisms of the synergistic effects, we
   conducted RNA‐seq and revealed the modulation of the Hh and JAK/STAT
   signaling pathways. Subsequent western blot experiments confirmed the
   reduced activity of these pathways upon combination treatment. SHH is a
   crucial ligand of the Hh pathway, playing a pivotal role in cell
   differentiation, and proliferation.^[ [150]^38 ^] In lung cancer
   tissues, the expression level of the SHH protein was significantly and
   positively correlated with p‐STAT3.^[ [151]^39 ^] We then decided to
   further explore whether there is a specific regulatory relationship
   between them, thereby linking the Hh and STAT3 pathways. The results
   showed that upregulation of SHH led to the activation of p‐STAT3 and
   increased the expression of its target protein c‐Myc. For the first
   time, our investigation reveals the modulatory impact of SHH on the
   STAT3 pathway and provides initial insights into the existence of the
   SHH/p‐STAT3 signaling axis.

   As SHH has not been reported to possess kinase or phosphatase activity,
   we speculated that other kinases or phosphatases might be involved in
   regulating the SHH/p‐STAT3 signaling axis in response to itraconazole
   combined with osimertinib. Initially, we evaluated the expression
   levels of JAKs proteins, known for their association with STAT3, but
   found that the combination of itraconazole with osimertinib did not
   mediate its effects through the JAKs kinases. DUSPs play a pivotal role
   in cellular physiology by dephosphorylating phosphoserine,
   phosphothreonine, and phosphotyrosine residues in proteins.^[ [152]^28
   ^] We observed a substantial increase in several DUSPs after
   itraconazole treatment. We then conducted correlation analysis, qPCR,
   and western blotting, focusing on DUSP13B. The data demonstrated a
   pronounced upregulation of both mRNA and protein of DUSP13B following
   itraconazole combined with osimertinib treatment. To ascertain whether
   DUSP13B could dephosphorylate STAT3, we conducted in vivo
   phosphorylation experiments and illustrated dephosphorylation by
   DUSP13B. Molecular docking has been widely utilized to predict
   interactions between proteins.^[ [153]^40 ^] In this study, we
   conducted molecular docking of STAT3 and DUSP13B using the online
   website ZDOCK^[ [154]^41 ^] to predict their interactions. Employing
   molecular docking and subsequent co‐IP and immunofluorescence
   experiments, we confirmed the interaction between DUSP13B and STAT3.

   DUSPs play an important role in tumorigenesis and drug resistance.^[
   [155]^42 , [156]^43 , [157]^44 , [158]^45 , [159]^46 ^] Here, we
   investigated the involvement of DUSP13B in osimertinib resistance. Our
   findings revealed a significant reduction in DUSP13B expression after
   osimertinib resistance, and overexpression of DUSP13B reversed
   osimertinib resistance and enhanced the cell sensitivity to
   osimertinib. Moreover, we observed that combined treatment with
   itraconazole and osimertinib facilitated SHH protein degradation,
   leading to reduced SHH expression. Overexpression of SHH partially
   counteracted the synergistic effects of the drug combination, both in
   vitro and in regulating the SHH/DUSP13B/p‐STAT3 signaling axis. These
   findings collectively shed light on the molecular mechanisms underlying
   the synergistic effects of itraconazole and osimertinib, and provide
   compelling evidence for the therapeutic strategy of combining
   itraconazole with osimertinib to overcome osimertinib resistance in
   NSCLC.

   Autophagy is a highly conserved degradation process that contributes
   significantly to the maintenance of cellular homeostasis. It plays a
   dual role in the cancer development, metastasis, and drug resistance.^[
   [160]^22 , [161]^47 ^] Therefore, investigating whether autophagy is
   induced during drug treatment and understanding its role are crucial
   for enhancing antitumor efficacy. Through analysis of the RNA‐seq
   results, we observed significant enrichment of the autophagy pathway in
   the itraconazole‐treated group. LC3 is involved in the development of
   autophagosomes, and the level of autophagy is reflected by the ratio of
   LC3II/LC3I.^[ [162]^48 , [163]^49 , [164]^50 ^] P62 protein, encoded by
   the SQSTM1 gene, is known to localize to autophagosomes and lysosomes,
   playing a crucial role as an autophagy adaptor protein that can also
   reflect autophagy activity.^[ [165]^51 ^] According to our examination,
   we found that granular LC3 was markedly increased in the combination
   therapy group, suggesting an increase in autophagosomes. Additionally,
   the ratio of LC3II/LC3I and P62 were also significantly increased. It
   is commonly assumed that increased P62 expression indicates the
   inhibition of autophagy. However, under toxic stimulation and oxidative
   stress, the expression level of P62 protein may align with autophagy
   activation. This is because P62 is also a stress protein that is
   significantly elevated under stressful conditions.^[ [166]^51 ,
   [167]^52 ^] Therefore, the activity of cellular autophagy cannot be
   determined based solely on a single experimental result. Observing the
   cellular ultrastructure through TEM is crucial for directly visualizing
   autophagosomes. Our observations revealed a notable rise in the count
   of autophagosomes in cells treated with the combination of itraconazole
   and osimertinib. Autophagy is a dynamic process that involves the
   formation of autophagosomes, their fusion with lysosomes, and the
   degradation of autolysosomes.^[ [168]^48 , [169]^53 ^] By monitoring
   intracellular fluorescence changes following infection with
   mRFP‐GFP‐LC3, we can observe the cellular autophagic flux more vividly
   and clearly, which serves as a reliable indicator to accurately assess
   autophagic activity.^[ [170]^54 ^] Lysosomes are an acidic environment.
   When the autophagosome fuses with the lysosome, the green fluorescence
   (GFP) on the autophagosome is quenched, resulting in only red
   fluorescence (mRFP), indicating unobstructed autophagic flow. If the
   acidic environment within the lysosome is disrupted or the
   autophagosome fails to fuse with the lysosome, the GFP green
   fluorescence will not be quenched. This leads to a large amount of
   yellow fluorescence within the cell, indicating blocked autophagic
   flow.^[ [171]^55 ^] Assessment of autophagy markers revealed increased
   autophagic activity following the combination therapy. The inhibitor
   chloroquine further improved the synergistic effects of itraconazole
   and osimertinib, indicating that induced autophagy serves as a
   protective mechanism, and inhibiting it could enhance the antitumor
   efficacy of the combination.

   EGFR is a transmembrane glycoprotein receptor belonging to the tyrosine
   kinase receptor family with a molecular weight of 170 kDa. EGFR gene
   mutations can lead to aberrant activation of a cascade of downstream
   pathways, such as JAK/STAT, PI3K/Akt, and MAPK, leading to tumor
   development.^[ [172]^56 ^] We investigated the correlation between key
   molecules, including SHH, GLI1, DUSP13B, and STAT3, and the mutation
   status of EGFR using the TIMER2.0 online website. Our findings revealed
   that the mRNA expression levels of SHH and GLI1 were markedly increased
   in the EGFR mutation group, whereas DUSP13B was greatly decreased.
   These results suggest that EGFR mutations may trigger the activation of
   the Hedgehog signaling pathway, potentially posing a latent risk for
   EGFR‐TKI resistance. To further explore the expression levels and
   correlation of SHH/DUSP13B/p‐STAT3 in lung adenocarcinoma tissues, we
   performed IHC staining and found that the high expression rate of SHH
   protein in EGFR‐mutant lung adenocarcinoma tissues was significantly
   higher than that in EGFR wild‐type tissues, which was consistent with
   the mRNA expression pattern. These results are consistent with the
   findings reported by Kim et al., who observed higher expression of SHH
   in lung adenocarcinoma patients with EGFR‐mutant, which was related to
   a poor prognosis.^[ [173]^57 ^] Furthermore, the high expression rate
   of p‐STAT3 protein was significantly increased in EGFR‐mutant lung
   adenocarcinoma tissues. However, DUSP13B protein expression was not
   related to EGFR mutation status, which may be attributed to the
   relatively small sample size. We also analyzed the association between
   SHH, DUSP13B, and p‐STAT3 proteins in lung adenocarcinoma tissues and
   found that p‐STAT3 was significantly positively correlated with SHH but
   negatively correlated with DUSP13B. This further suggests that DUSP13B
   may have a negative regulatory relationship with p‐STAT3, and further
   verification of this finding is needed in other types of cancer tissues
   in future studies.

   Furthermore, we verified that the Hh and JAK/STAT3 signaling pathways
   were implicated in osimertinib resistance using the GEO dataset.
   However, it is worth noting that variations may exist across different
   cell types. In addition, we observed a considerable increase in SHH
   protein expression in lung cancer tissues after osimertinib resistance
   compared with that in preresistant tissues. Given that the SHH protein
   is a secreted molecule detectable in serum, it could serve as a
   valuable marker for noninvasively predicting osimertinib resistance.
   Moreover, our study highlights the clinical relevance of these
   findings, demonstrating the increased expression of SHH, p‐STAT3, and
   GLI1 proteins in postosimertinib‐resistant lung cancer tissues, along
   with decreased DUSP13B expression. These proteins may serve as valuable
   molecular markers for predicting osimertinib resistance. And the
   working model was shown in Figure [174] 7 .

Figure 7.

   Figure 7
   [175]Open in a new tab

   Schematic diagram of molecular mechanism of synergistic effects of
   itraconazole in combination with osimertinib.

   Overall, our comprehensive investigations significantly contribute to
   the understanding of the molecular mechanisms underlying osimertinib
   resistance and shed light on potential therapeutic strategies for
   overcoming this resistance in NSCLC.

Conflict of Interest

   The authors declare no conflict of interest.

Author Contributions

   H.Z.: Resources, software, formal analysis, writing‐original draft,
   writing‐review and editing. Y.T.: Data curation, and validation. H.Z.:
   Funding acquisition, and methodology. J.L.: Software, and funding
   acquisition. H.Z.: Investigation, and methodology. Y.Z.: Software.
   Y.Z.: Formal analysis. Q.W.: Resources. J.M.: Supervision,
   investigation. S.F.: Conceptualization, data curation, supervision,
   funding acquisition, visualization, writing‐review, and editing.

Supporting information

   Supporting Information
   [176]ADVS-12-2409416-s001.docx^ (3.1MB, docx)

Acknowledgements