What this is
- () is a severe condition characterized by elevated pressure in the pulmonary arteries due to low oxygen levels.
- Osteopontin (OPN) has been identified as a key gene linked to and cardiovascular diseases, particularly in .
- This study investigates the role of OPN in regulating through the in pulmonary artery smooth muscle cells (PASMCs) under hypoxic conditions.
Essence
- OPN silencing reduces by enhancing through the PI3K-AKT pathway, leading to decreased pulmonary arterial pressure and right ventricular hypertrophy.
Key takeaways
- OPN knockdown in hypoxic PASMCs resulted in increased markers, suggesting a protective role against . This indicates that targeting OPN may enhance and mitigate pulmonary vascular remodeling.
- Inhibition of OPN in a mouse model of led to a decrease in mean pulmonary arterial pressure (mPAP) and right ventricular hypertrophy index (RVHI), demonstrating a potential therapeutic strategy for .
- The study identifies the as a crucial mediator of OPN's effects on , linking OPN regulation to cellular proliferation and in PASMCs.
Caveats
- The study's reliance on a single database for gene screening may limit the comprehensiveness of the findings. Further validation across multiple datasets is necessary.
- The specific functions of OPN in require additional investigation, as the current study primarily focuses on its regulatory role in .
Definitions
- Hypoxic pulmonary hypertension (HPH): A subtype of pulmonary arterial hypertension characterized by elevated pulmonary artery pressure due to low oxygen levels.
- Autophagy: A cellular process that degrades and recycles internal components, crucial for maintaining cellular homeostasis.
- PI3K-AKT signaling pathway: A critical signaling pathway involved in regulating cell growth, survival, and metabolism, often implicated in cancer and cardiovascular diseases.
AI simplified
Introduction
Hypoxic pulmonary hypertension (HPH) represents a distinct subtype within the broader category subtype of pulmonary arterial hypertension (PAH) and poses a significant burden on patients' quality of life. Characterized by persistent elevation of pressure in the pulmonary arteries, HPH stems from pathological alterations in lung vasculature1. These changes lung vasculature irreversible damage to the pulmonary vasculature triggered by oxygen deprivation2. In a study conducted in Spiti Valley, India, the prevalence of primary HPH in the local population was 3.23%3. HPH is a prevalent and life-threatening condition in highland regions4. Current therapeutic approaches for HPH, primarily consisting of long-term oxygen therapy and systemic vasodilators, offer only temporary relief from hypoxic injury to pulmonary vasculature5. However, targeted therapeutic strategies specifically addressing pulmonary vasculature lesions in HPH are lacking. Therefore, it is imperative to elucidate the underlying mechanistic pathways to improve survival rates among affected individuals.
Autophagy, a fundamental biological process involving the degradation of internal components within lysosomes such as proteins and mitochondria, has garnered attention for its potential relevance to HPH pathogenesis6. Previous studies have identified several aspects of autophagy, including macroautophagy, microautophagy, and molecular chaperone-mediated autophagy, each characterized by distinct cargo delivery mechanisms to lysosomes for degradation7. Macroautophagy (hereinafter referred to as autophagy) involves the recognition of cargoes by autophagic vesicles characterized by a double membrane structure. These vesicles encapsulate cargoes and facilitate their binding to lysosomes, where subsequent digestion of their contents occurs8. In contrast, microautophagy directly involves the invagination of cargoes by lysosomes for phagocytosis and decomposition9. Another variant, molecular chaperone-mediated autophagy relies on the receptor protein LAMP2A expressed on lysosome membranes to selectively recognize cargoes bearing the KFERQ motif. Subsequently, these cargoes traverse specialized channels within the lysosomal membrane, facilitating their entry into the lysosome for degradation10. Studies have established a correlation between autophagy and HPH, wherein increased autophagic activity was observed in PASMCs within a rat model aimed at alleviating systolic pressure and attenuating remodeling, thereby impeding the progression of HPH in the pulmonary arteries11. This finding suggests that upregulation of autophagy may hold promise in preventing HPH progression. Furthermore, treatment with tanshinone II sodium sulfonate A has been shown to stimulate autophagy in rat lung tissue under hypoxic conditions, mitigating pathogenic alterations in lung tissue12. Thus, modulating autophagy presents a potential therapeutic approach for managing HPH.
OPN, also known as secreted phosphoprotein 1 (SSP1), is a member of the matricellular protein family and is classified as a non-structural extracellular matrix protein involved in diverse cellular processes13. Upregulation of OPN expression has been reported in hepatocellular carcinoma (HCC), where it promotes the proliferation and migration of HCC cells14. Inhibition of OPN leads to the suppression of cancer cell proliferation, as well as decreased regeneration and survival of primary hepatocytes, and cell cycle arrest15. Additionally, OPN has been implicated in the modulation of autophagy, where it attenuates fibrosis in atrial fibroblasts by inhibiting autophagy16. It also enhances autophagy capacity in human aortic smooth muscle cells, thereby reducing vascular calcification17. Despite these insights, the precise mechanism through which OPN regulates HPH remains elusive. Previous studies have demonstrated the efficacy of triptolide in inhibiting vascular remodeling in rats with HPH by targeting the PI3K-AKT signaling pathway18. Notably, differential expression of PI3K, rather than AKT, has been observed when comparing patients with PAH (mPAP ℠30) to control subjects (mPAP †20)19. Abnormal activation of PI3K has been implicated in the context of HPH/PAH. However, the involvement of OPN in autophagy in HPH remains insufficiently investigated.
In this study, we employed bioinformatics techniques to identify OPN as a common gene intersecting PAH and autophagy. Subsequently, we identified the top ten genes common among differentially expressed genes (DEGs), autophagy-related genes (ARGs), and differentially modular genes (DMGs), considering them as hub genes. KEGG analysis of these genes identified the PI3K-AKT pathway as one of the prominent pathways. To investigate the role of OPN in HPH, we generated OPNfl/fl-Cre CB57 mice. This study aimed to examine the impact of OPN on HPH progression and explore its potential regulatory effects on autophagy and the proliferation of PASMCs through the PI3K signaling pathway. The objective of this research was to elucidate the influence of OPN on autophagy and its involvement in pathological changes in pulmonary artery smooth muscle in the HPH model via the PI3K signaling pathway. These findings provide potential avenues for the development of therapeutic interventions for HPH.
Methods
Data collection and processing

Bioinformatics data analysis process.
Analysis of differentially expressed genes (DEGs)
The DEGs were analyzed using the "limma" package21 in the R software (version 4.2.2.) Specifically, this study used the Imfit function to find multiple linear regressions on the dataset. Then, we used the eBays function to compute the regulation t-statistic, the regulation F-statistic, and the log odds of differential expression by empirical Bayesian adjustment of the standard error to the common value. Finally, we obtained the significance of the difference for each gene. We set the fold change to log Fold Change > 1 and adjusted the p-value to set it to less than 0.01 to screen for target genes. Differential genes were then visualized using the "ggplot2" and "heatmap" R packages for volcano maps of all differential genes and heatmaps of the top 50 differentially up-and-down-regulated genes.
Weighted gene co-expression network analysis (WGCNA)
WGCNA is an algorithm that evaluates the relationships between measured transcripts, identifies clinically relevant co-expressed gene modules, and explores key genes in disease pathways from a systems biology perspective22. The âWGCNAâ R package was used to construct the PAH correlation module. To implement the scale-free network, the "pickSoftThreshold" function in the package was used to determine the optimal soft-threshold power ÎČ for increasing the expression similarity and calculating the neighboring relationships. Next, the gene correlation matrix was transformed into a neighboring matrix, which was further converted into an unsigned topological overlap matrix (TOM). According to the TOM, average chained hierarchical clustering was used to obtain gene clusters and construct a dendrogram. A minimum module size of 30 genes was used to identify gene modules using a dynamic tree-cutting algorithm (deep Split = 2); genes with similar expression patterns were assigned to the same module. Module-characterized genes (MEs) were calculated as the first principal component of the expression profile in each module. Modules were then clustered and merged based on ME differences (merge Cut Height = 0.25). The correlation between MEs and clinical characteristics of PAH patients was calculated using the Pearson correlation coefficient. Then, the two modules with the highest coefficients were targeted and the genes within the two modules were extracted for further analysis.
Functional enrichment analysis
Genes enriched in blue and turquoise modules with gene significance greater than 0.5 in WGCNA were analyzed by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis23â25 using the "cluster Profiler" R (version 4.2.2) package26, including biological process (BP), cellular component (CC), molecular function (MF) and KEGG pathway enrichment analysis visualized by the "ggplot2" R package. BP, CC, MF, and KEGG pathway enrichment analyses were included and visualized by the "ggplot2" R package. The P-value was set to 0.05 as the critical value.
Identification of differential expressed module autophagy-related genes (DEMARGs) and construction of proteinâprotein interaction networks
We used the "Veen" R (version 4.2.2) package to identify DEGs, differential module genes, and ARGs co-expressed in DEMARGs. Subsequently, proteinâprotein interaction (PPI) between DEMARGs was analyzed and visualized by the CYTOSCAPE (version 3.9.1) software using the Searching for Gene Interactions Search Tool (STRING) database (https://cn.string-db.orgâ (accessed December 18, 2022)) to analyze PPI between DEMARGs and visualize them by CYTOSCAPE (version 3.9.1) software27. The DEMARGs were ranked using four algorithms, MCC, MNC, Degree, and EPC28 in the CytoHubba plugin to obtain the top ten Hub genes, and the Hub genes were analyzed for KEGG enrichment.
GeneMANIA: gene pathways and interactions of Hub genes
GeneMANIA (http://www.genemania.orgâ (accessed February 18, 2023)) provides a flexible, user-friendly analysis web interface for generating hypotheses based on gene function, analyzing gene lists, and prioritizing genes for functional analysis29. GeneMANIA was used to construct the geneâgene interaction network of Hub genes from physical interactions, co-expression, prediction, co-localization, and genetic interactions, and to evaluate their functions.
Animals
C57BL/6J (wide-type) mice were used as background. Transgelin protein encoded by the transgelin (TAGLN) gene is involved in regulating the formation and maintenance of the cytoskeleton, influencing cell contraction, morphology, and migration, and is an early marker of smooth muscle differentiation. To construct the targeting vector, BAC clone RP24-190A7 was used as a template to generate homologous Bo and cKO regions by PCR. Cas9 protein, sgRNA and targeting vector were co-injected into mouse fertilized eggs to generate F0 mice. F0-positive mice were mated with WT (TAGLN-Cre-containing) mice to obtain F1 generation OPNflox/+, TAGLN-Cre heterozygous mice that can be stably inherited. F1 generation OPNflox/â, TAGLN-Cre mice were self-crossed with mice of the same genotype to obtain pure and OPNflox/flox, TAGLN-Cre mice as vascular smooth muscle-specific knockout mice for experiments. Controls were littermate control OPNflox/flox mice (10â12 weeks) weighing 22 to 25 g for this study. All mice were purchased from Cyagen Biological Research Center (Taicang, China) (license SCXK (Su) 2018â0003). They were housed in a temperature-controlled environment at 22 ± 2 °C with a relative humidity of 45â55% and were fed ad libitum with a standard laboratory diet and tap water for 1 week before the experiment. The animals were randomly divided into 4 groups: (1) normoxic control using OPNflox/flox control mice (n = 7, hereafter referred to as normoxia group); (2) normoxic using OPNflox/flox, TAGLN-Cre mice (n = 7, hereafter referred to as normoxia + OPNfl/fl-TAGLN-Cre group); (3) hypoxic environment using OPNflox/flox control mice (n = 7, hereafter referred to as hypoxia group); (4) using OPNflox/flox, TAGLN-Cre mice in a hypoxic environment (n = 7, hereafter referred to as hypoxia + OPNfl/fl-TAGLN-Cre group). 3 and 4 groups were housed in a DYC3000 low-pressure hypoxic (10.6% oxygen content relative to sea level) chamber (Fenglei, Guizhou, China) at a simulated altitude of 5000 m for 28 days, and all animals were kept in a 12-h light-12-h dark cycle at 22 ± 2 °C, with food provided ad libitum, and bedding changed every 3 days.
Mean pulmonary artery pressure (mPAP) measurement in mice
A 2% sodium pentobarbital anesthetic was injected into the peritoneal cavity of mice according to their body weight. When the mice were in deep anesthesia, the mice were placed supine and fixed on the mouse platform, and a cut was made in the middle of the anterior neck to locate and separate the right measured external jugular vein, and a polyethylene microcatheter was heparinized and inserted from the right external jugular vein to the pulmonary artery. The other end was connected to a BL-420S biopressure transducer (Ed Instruments, Shanghai, China), and the pulmonary artery pressure profile was recorded for 5Â min.
Measurement of right ventricular hypertrophy index (RVHI) in mice
Immediately after the dislocation and execution of mice under anesthesia, heart, and lung tissues were removed, the surface was cleaned of blood with saline, and the whole heart was weighed, the right ventricle (RV) was cut out and the RV was weighed, followed by isolation of the left ventricle (LV) and the interventricular septum (S), and weighing the LV and the S. The right ventricle was then removed from the right ventricle and the septum was removed from the right ventricle. The result of calculating the Fulton index (RV/LVâ+âS) represented the right ventricular hypertrophy index (RVHI).
Transmission electron microscopy
Pulmonary arteries and PASMCs from all groups were fixed by adding 3% glutaraldehyde fixative at 4 °C for 24 h, and 1% osmium tetroxide was added and fixed for another 2 h. The fixed samples were dehydrated stepwise by immersing them in acetone and then embedded in epoxy resin after completion of dehydration. The samples were prepared into 50 nm sections, and the sections were stained with lead citrate and placed under a JEM-1400FLASH transmission electron microscope (JEOL, Tokyo, Japan) for observation and image acquisition.
Culturing of primary PASMCs
Ten 6-week-old SD rats (Certificate of Conformity No. 110322220100347884) purchased from Beijing Huafu Biotechnology Company were euthanized by cervical dislocation after being anesthetized by intraperitoneal injection of 2% sodium pentobarbital and were sterilized in 75% ethanol for 3 min. The heart and lung tissues were taken out by opening the thoracic cavity in an ultra-clean bench and placed in Petri dishes containing pre-cooled sterile 1% PBS at 4 °C (Solepol, Beijing, China)) in a Petri dish. The heart was removed, and the lung tissue was washed with PBS, and the lung tissue was fixed in a Petri dish containing floatation. Secondary and tertiary pulmonary arteries were isolated step by step down the main pulmonary artery trunk. They were transferred to a new petri dish for cleaning and then the small pulmonary arteries were cut longitudinally, the endothelial cells were gently scraped with a scalpel, and the outer and middle membranes were separated with ophthalmic forceps. The middle smooth muscle tissue was cut into 1 mm3-sized tissue blocks, which were then transferred to 15 mL centrifuge tubes containing 1â2 mL of 0.2% type II collagenase (Solebol, Beijing, China), and the centrifuge tubes were placed in a water bath at 37 °C for digestion for about 1 h. Digestion was terminated when the tissue blocks became flocculent. After digestion, the cells were resuspended in high glucose DMEM medium (Procell, Wuhan, China) containing 20% FBS (Gibco, California, USA), and the resuspension solution was added into the culture flasks and placed in a humidified incubator at 37 with 5% CO2 (Thermo HERAcell150i, Thermo Fisher Scientific, America) for culture. When the cells grew to about 70% confluence, the cells were purified by differential wall affixation. Generation 3â5 cells were used for subsequent experimental studies. In addition, the cells were classified into normoxia, hypoxia, hypoxia + OPN shRNA EV, hypoxia + OPN shRNA, and hypoxia + LY294002 (PI3K inhibitor) groups. Normoxic PASMCs were placed in an ambient incubator (Thermo HERAcell 150i, ThermoFisher, USA) with 5% CO2 and 20% O2 for 48 h, and hypoxic PASMCs were placed in an ambient incubator (CB53, BINDER, Germany) with 5% CO2 and 1% O2 for 48 h and then used for subsequent cell experiments.
Immunocytochemical assay
Logarithmic growth phase PASMCs were digested with 0.2% trypsin (Solebol, Beijing, China), and 1 Ă 104 cells were inoculated into 6-well cell culture plates. After cell attachment, the original medium was discarded, the cells were washed twice with PBS, and 4% paraformaldehyde was added to fix the cells at room temperature for 15 min. The cells were subsequently processed according to the steps of the two-step immunohistochemistry kit (Elabscience, Wuhan, China). Used to identify PASMCs, brown cells represent PASMCs.
Reverse transcription-polymerase chain reaction (RT-PCR)
Total RNA from lung tissues was extracted using the Total RNA Extraction Kit (TIANGEN, Beijing, China) according to the manufacturer's instructions. cDNA was synthesized using the Reverse Transcription Reagent (TIANGEN, Beijing, China). cDNA was extracted from lung tissues using SuperReal PreMix Color (SYBR Green) (TIANGEN, Beijing, China) to determine the gene expression levels in an ABI PRISM 7500 sequence detection system (Applied Biosystems, Foster City, USA). Transcript expression levels were normalized to endogenous ÎČ-actin expression levels. All primer sequences were shown in Supplementary Table. 1
Cellular lentiviral transfection and culture
OPN interference sequences were designed, forward âGATGTCCCTFACGGCCGAGGTâ, reverse âACCTCGGCCGTCAGGGGACATCâ. Logarithmic growth phase PASMCs were inoculated in 25 mm2 culture flasks according to the instructions of the company from which they were purchased (Cyagen, California, America), and the cells were transfected with OPN interference sequences when the cells had grown to 30â40%. The virus was first lysed in a disease bath, polybrene was added to the virus-containing medium, and the viral solution was allowed to cover the surface of all cells overnight, and the virus-containing medium was removed the day after transfection to add fresh complete medium. After the virus-containing cells stably expressed specific green fluorescence, the cells were collected for subsequent experiments. The PASMCs were categorized into the hypoxia + OPN shRNA EV group plus containing OPN empty virus; and hypoxia + OPN shRNA group plus containing OPN interfering with lentivirus.
Western blotting (WB)
Lung tissues and cells of each group were collected, and the supernatant was collected after lysis on ice by adding the appropriate amount of RIPA lysate. Protein concentration was detected by the BCA (No. 23227, Thermo Fisher Scientific) method. Polyacrylamide gel electrophoresis (SDS-PAGE) was performed with 30 ”g of protein per well, and the target proteins were transfected onto a PVDF membrane, which was closed with 5% skimmed milk powder at room temperature for 1 h. To reduce the number of primary antibodies used, we cut the membranes to the appropriate size based on the marker corresponding to the molecular weight of the protein before incubating the membranes with the following primary antibody. The membranes were incubated with LC3B (1:1000, No. ab192890, Abcam), Beclin1 (1:2000, No. ab207612, Abcam), OPN (1:1000, No. ab63856, Abcam), PI3K (1:2000, No. ab191606, Abcam), AKT (1:1000, No. ab8805, Abcam), ÎČ-actin (1:5000, No. AC026, ABclonal) antibodies were incubated overnight at 4 °C in the refrigerator. The membrane was washed three times with TBST on the following day and then added with anti-mouse HRP secondary antibody (1:10,000, No. AS003, ABclonal) or anti-rabbit HRP secondary antibody (1:10,000, No. AS014, ABclonal) and incubated at room temperature for 1 h. After washing, the membrane was washed with ultrasensitive luminescent solution (No. 1856189, Thermo Fisher Scientific, America) in a gel imager to develop and save the images and analyze the gray value of the bands with ImageJ software (version 1.53t) to calculate the relative protein expression with ÎČ-actin as an internal reference.
5-ethynyl-2'-deoxyuridine (EdU) staining
EdU staining was performed using the BeyoClickâą EdU Cell Proliferation Detection Kit (BeyoClick, Nanjing, China). Cells were inoculated in 6-well plates and stained with 50Â ÎŒM EdU for 2Â h. Subsequently, cells were washed twice with PBS, fixed with 50Â ÎŒL of fixative (PBSâ+â4% polyoxymethylene), and incubated for 30Â min. Finally, cells were discolored with 100Â ÎŒL of permeabilization agent (PBSâ+â0.5% TritonX-100) for 2â3 times (each rinse for 10Â min). the nuclei were stained with DAPI staining of nuclei was performed for 10Â min. Cell staining results were observed with an inverted fluorescence microscope and EdU positively stained cells were counted using ImageJ software (version 1.53t).
Flow cytometry
PASMCs were inoculated in 6-well plates at 8 Ă 104 cells/well. PASMCs were grown in normoxia, hypoxia, hypoxia empty virus, hypoxia OPN shRNA, and hypoxia LY294002 culture environments. The normal untreated normoxia group served as a control. Cells were treated with a cell cycle assay kit (cell cycle assay kit, E-CK-A351, Wuhan, China). 48 h later, PASMCs were cultured in a conditioned medium collected in 1.5 mL centrifuge tubes, and the cells were washed with precooled PBS, and fixed in pre-cooled anhydrous ethanol at â 20 °C for 1 h. After washing again with PBS, 100 ÎŒL of RNase A Regent in a water bath at 37 °C for 0.5 h. After washing again with PBS, 25 ÎŒL of PI Regent was added, gently mixed, resuspended, and incubated for 30 min at 37 °C, protected from light, before being detected by flow cytometry to detect changes in the cell cycle. The data were further analyzed using FlowJo software (version 10.8.1).
Statistical analysis
Statistical analyses were performed using R software (version 4.2.2) or GraphPad Prism (version 9). All data are expressed as mean ± standard deviation (SD) and all experiments were repeated at least 3 times. Significant differences were determined using Bonferroniâs multiple comparison test with a one-way analysis of variance (ANOVA) between the control and other groups. p < 0.05 was considered statistically significant.
Delaration of ethis
This study conformed to the stipulations set forth in the ARRIVE guidelines for experimental animals research. The protocols governing animal care and experimental utilization were rigorously aligned with the Chinese Guidelines for the Care and Use of Laboratory Animals. The animal experiments obtained approval from the Ethics Committee of Qinghai University School of Medicine.
ResuIts
DEGs analysis in PAH patients and normal individuals

An analysis of the differentially expressed genes. () Volcano diagram of PAH () data, where green scatters indicated down-regulated genes and red scatters indicated up-regulated genes. () A heat map of PAH () data, with red showing high expression and blue indicating low expression. () Violin diagram of the top 10 differentially expressed genes indata. Asterisks indicate statistically significant differences. ***<â0.001. A B C GSE113439 GSE113439 GSE113439 p
WGCNA and identification of key modules

WGCNA ofdata. () Scale-free fit index (on the left) and average connectivity (on the right) for evaluating various soft threshold powers. () The map of differentially expressed genes based on the topological overlap matrix. () Heatmap displaying the relationship between modules and sample attributes. (,) Scatter diagrams of module genes in modules colored blue and turquoise. GSE113439 A B C D E
KEGG and GO enrichment analysis of DMGs

Functional enrichment analysis of blue and green pine module genes using GO and KEGG. (,) Top 10 GO terms in the blue module and turquoise module genes in cellular components, molecular functions, and biological processes, respectively. (,) Blue module and turquoise module genes enriched in the KEGG pathway with<â0.05. Warmer colors indicated higher statistical significance. A C B D P
Identification of hub genes

Hub gene PPI construction. () Genes where ARGs, DEGs, and DMGs intersect. () STRING-based PPI analysis of DEMARGs. () Visualization of the PPI of DEMARG using Cytoscape. () Identification of 10 Hub genes in DEMARGs through MCC, MNC, Degree, and EPC algorithms in CytoHubbs. A B C D
GenMANIA and KEGG enrichment analysis of the Hub genes

Functional analysis of Hub genes. () Geneâgene interaction network identification of Hub genes. () The top 10 Hub genes were enriched in the KEGG pathway analysis with<â0.05. Warmer colors indicated higher statistical significance. A B P
OPN-TAGLN-Cre alleviation of HPH under hypoxia fl/fl

The effect of OPN knockdown in a hypoxic environment on RVHI, mPAP, and pathologic changes in the pulmonary arteries in HPH. () The intersecting gene between the top 10 DEGs and the hub genes was SPP1. () mPAP measurement. () RVHI measurement. () Sections of an electron microscope (scale bar: 1 ”m) revealed altered pulmonary artery vascular cells. Mi (mitochondrion), N (nucleus), RER (rough endoplasmic reticulum). Pulmonary artery endothelial cells (red up arrow), pulmonary artery smooth muscle cells (yellow up arrow), autophagy (green up arrow). Results are representative of 7 independent experiments. Asterisks indicate statistically significant differences. *<â0.05, **<â0.01, ***<â0.001. A B C D p p p
OPN activation of PI3K inhibits the autophagy genes LC3B and Beclin1

Inhibition of OPN in mouse lung tissue affected the expression of PI3K, LC3B, and Beclin1. () Relative OPN mRNA expression in lung tissues. () Relative PI3K mRNA expression in lung tissues. () Relative LC3B mRNA expression in lung tissues. () Relative Beclin1 mRNA expression in lung tissues. () OPN, PI3K, LC3B, and Beclin1 were analyzed by WB in the normoxia, normoxiaâ+âOPN-TAGLN-Cre, hypoxia, and hypoxiaâ+âOPN-TAGLN-Cre groups. (â) OPN, PI3K, LC3B, and Beclin1 proteins relative expression in the indicated groups. Results are representative of 3 independent experiments. Asterisks indicated statistically significant differences. **<â0.01, ***<â0.001. A B C D E F I fl/fl fl/fl p p
Involvement of OPN in PI3K-AKT signaling pathway affects autophagy in hypoxic PASMCs

Lentiviral intervention utilizing OPN and the application of PI3K inhibitor augmented the expression of autophagy proteins by PASMCs under hypoxic conditions. () Immunohistochemistry results showed the identification of PASMCs; brown cells were PASMCs expressing α-SMA (scale bar: 200 Όm/100 Όm). () The green fluorescence indicated lentivirus that had entered PASMCs (scale bar: 200 Όm/100 Όm). () OPN expression under normoxia, hypoxia, normoxiaâ+âOPN shRNA conditions. () OPN, PI3K, AKT, LC3B, and Beclin1 were analyzed by WB in the normoxia, hypoxia, hypoxia OPN shRNA empty virus, and hypoxia OPN shRNA groups. (â) Protein expression levels for OPN, PI3K, AKT, LC3B, and Beclin1 were shown. () OPN, PI3K, AKT, LC3B, and Beclin1 were analyzed by WB in normoxia, hypoxia, and hypoxiaâ+âPI3K inhibitor (LY294002) groups. (â) OPN, PI3K, AKT, LC3B, and Beclin1 proteins relative expression in the indicated groups. PASMCs in all groups were incubated in normoxic (5% COand 20% O) or hypoxic (5% COand 1% O) environments for 48 h. Results are representative of 3 independent experiments. Asterisks indicated statistically significant differences. *<â0.05, **<â0.01, ***<â0.001. A B C D E I J K O 2 2 2 2 p p p
Localization of autophagy proteins and formation of autophagosomes in PASMCs

Quantitative expression of autophagosomes and autophagy-related proteins in PASMCs. () Electron microscopic analysis (scale bar: 2Â ÎŒm) of the number of autophagosomes (yellow uparrow) in the indicated groups. (,) Immunofluorescence (scale bar: 50Â ÎŒm) showed the fluorescence expression intensity of LC3B and Beclin1 in PASMCs. (â) Quantification of LC3B and Beclin1 immunofluorescence. PASMCs in all groups were incubated in normoxic (5% COand 20% O) or hypoxic (5% COand 1% O) environments for 48Â h. Results are representative of 3 independent experiments. Asterisks indicated statistically significant differences. ***<â0.001. A B C D E 2 2 2 2 p
Inhibition of OPN and PI3K expression suppresses PASMCs proliferation under hypoxia

Under hypoxia, OPN and PI3K inhibition prevented PASMCs growth. () EdU staining of PASMCs showed alterations in cell proliferation (scale bar: 50Â ÎŒm). () Flow cytometry analysis of the cell cycle. To calculate the percentage of cells in each phase, each set of cells was grown in the appropriate environment for 48Â h before staining with PI. () Statistical chart showing the proportion of cells that were EdU-positive. () A plot of cell cycle dispersion distribution based on flow cytometry analysis. PASMCs in all groups were incubated in normoxic (5% COand 20% O) or hypoxic (5% COand 1% O) environments for 48Â h. Results are representative of 3 independent experiments. Asterisks indicated statistically significant differences. ***<â0.001. A B C D 2 2 2 2 p
Discussion
HPH involves various biological mechanisms, including proliferation, autophagy, and cell cycle alterations in PASMCs35,36. In this study, we observed that the suppression of OPN in vascular smooth muscle cells within a hypoxic mice model resulted in decreased mean mPAP and RVHI, ultimately ameliorating HPH. Furthermore, we discovered that OPN-regulated autophagy played a crucial role in modulating the proliferation of hypoxic PASMCs with the PI3K-AKT potentially serving as a key downstream signaling factor of OPN.
HPH, characterized by hypoxic pulmonary vasoconstriction leading to increased pulmonary vascular resistance and pulmonary artery pressure, is a key factor in the hypoxic proliferation of PASMCs. Previous studies have highlighted the occurrence of autophagy in PASMCs37. Therefore, elucidating the role of autophagy-related genes is important for developing interventions targeting HPH. By employing bioinformatics approaches, we identified candidate biomarkers of autophagy in PAH. DEGs in PAH were identified using the limma parameter method, followed by the analysis of DEGs, ARGs, and DMGs using WGCNA to select DEMARGs. Notably, among the top 10 DEMARGs identified as hub genes through CytoHubba, OPN emerged as a prominent gene, being not only upregulated but also serving as a hub gene. Moreover, KEGG analysis of hub genes revealed the PI3K-AKT signaling pathway as a key pathway implicated in HPH. However, the specific functions of OPN in HPH need to be further investigated. Elevated levels of PI3K have been associated with the development of various cardiovascular diseases, including PAH, atherosclerosis, and myocardial fibrosis38â41. and the inhibition of PI3K could inhibit the proliferation of blood vessels42 and promote apoptosis and autophagy43,44. Therefore, in this study, we focused on elucidating the link between OPN and PI3K in HPH.
OPN is an acidic arginine-glycine-aspartate adhesion glycoprotein45. OPN is primarily secreted by osteoblasts, osteoclasts, and hematopoietic cells46. However, recent studies have identified OPN expression in cells from various tissues, including PASMCs and vascular endothelial cells47,48. Under acute hypoxia conditions, vascular smooth muscle cells exhibit increased OPN expression, with elevated OPN levels correlating with increased autophagy49. OPN upregulation has been observed in pancreatic lung cancer cells, and knockdown of OPN leads to increased autophagic activity50. Autophagy, a process pivotal in controlling cell proliferation, has demonstrated inhibitory effects on lung cancer development when induced by exogenous Beclin1 supplementation. This augmentation of autophagy not only suppresses cancer cell growth but also mitigates angiogenesis and attenuates OPN expression51. Autophagy serves as a crucial regulator of fundamental cellular processes and significantly influences disease progression. Increased OPN expression coupled with autophagy inhibition in atrial fibrosis promotes the proliferative potential of fibroblasts, consequently exacerbating fibrosis16. Conversely, augmenting autophagy in PASMCs through pharmacological interventions has been shown to have protective effects, reducing their proliferative potential and potentially alleviating hypoxia-induced PAH52. Autophagy regulated by OPN exhibits a protective role in disease pathogenesis, suggesting that enhancing this process may represent a promising therapeutic strategy for treating HPH.
The PI3K pathway, situated downstream of OPN53, plays a pivotal role in regulating autophagy. OPN triggers the activation of the PI3K-AKT pathway in response to oxidative stress signals, primarily through integrin αVÎČ354. The PI3K-AKT signaling pathway is crucial for fundamental cellular processes and exerts a significant impact on suppressing autophagy while stimulating proliferation55,56. Previous investigations have demonstrated the elevated concentration of PI3K in HPH compared to normal tissues, influencing cell division by modulating calcium levels within PASMCs57. Building upon this body of evidence, our hypothesis posits that the lack or inhibition of OPN in PASMCs could mitigate the progression of HPH by suppressing proliferation via PI3K-mediated autophagy.
To test the above hypotheses, we investigated differences in OPN expression between PAH and non-PAH. HPH is classified as a subtype of PAH, and to elucidate the role of OPN in HPH, mice with OPN deletion specifically in SMC were subjected to hypobaric oxygen chamber conditions to induce HPH. Our results demonstrated that OPN inhibition led to decreased RVHI and mPAP, accompanied by a significant enhancement in autophagy expression. This confirms the involvement of OPN in modulating autophagy expression. To validate the findings from pathway analysis, we conducted in vitro experiments. These experiments revealed that OPN knockdown reversed the effects of hypoxia on rat PASMCs proliferation and upregulated autophagy protein expression, providing further evidence of OPNâs influence on autophagy occurrence. Additionally, treatment with PI3K inhibitors on hypoxic PASMCs enhanced autophagy and inhibited cell proliferation, suggesting that OPN regulates autophagy via the PI3K-AKT pathway in PASMCs, with alterations in autophagy affecting proliferation. Based on these findings, we inferred that OPN regulates the PI3K-AKT pathway of autophagy, thereby influencing the thickening of the pulmonary artery smooth muscle layer in HPH.
This study has some limitations. Firstly, our approach for screening differential genes relied solely on one database, potentially limiting the comprehensiveness of our gene selection process. Additionally, during the screening phase, we did not prioritize the primary key pathway but instead opted for the PI3K-AKT pathway due to its relevance to autophagy. Furthermore, the validation of this pathway in vitro was compromised by the omission of a PI3K-AKT signaling pathway inhibitor in the normoxic PASMCs control group.
Conclusions
In summary, our study demonstrates that OPN regulates the autophagy pathway via the PI3K-AKT signaling axis in PASMCs under hypoxic conditions. This augmentation of the protective autophagic response effectively prevents the remodeling of the pulmonary artery smooth muscle layer. To our knowledge, this is the first study to investigate the relationship between PI3K-AKT signaling regulated by OPN and autophagy in HPH. These findings provide a new research direction regarding the mechanisms of HPH and offer potential avenues for improving clinical diagnosis and developing targeted therapy for HPH.
Supplementary Information
Supplementary Information.