Profilin 2 (PFN2) is an actin-binding protein important for cancer initiation and progression. However, the function and precise role of PFN2 in non-small cell lung cancer (NSCLC) remain unclear. Here, we assessed the expression levels of PFN2 in tissue from patients with NSCLC; identified binding partners using mass spectrometry, co-immunoprecipitations, and molecular modeling; and studied the angiogenic-promoting function of PFN2 using 3D droplet cultures and tube-formation assays. We found that upregulated PFN2 expression is associated with poor prognosis in patients with NSCLC. Knockdown of PFN2 significantly impaired the proliferation and angiogenesis of NSCLC cells, both in vivo and in vitro. Mechanistically, PFN2 physically interacts with pyruvate kinase M2 (PKM2) and modulates extracellular-signal regulated kinase 1/2 (ERK1/2)-mediated phosphorylation of PKM2 at S37, which substantially increases its nuclear translocation. PFN2 knockdown lead to reduced expression of PKM2, p65-NF-κB, and hypoxia-inducible factor (HIF)-1α and inhibited the nuclear translocation of PKM2. This resulted in impaired formation of the PKM2-HIF-1α-p65-NF-κB transcription complex, leading to decreased expression of its downstream target genes VEGFA, CCND1, and MAP2K5. Moreover, mutations in PFN2 at Y134 or S138 impaired its binding to PKM2, nuclear translocation of PKM2, and functionally inhibited angiogenesis in lung cancer cells. Overall, our data provide insights into the role of PFN2 in the regulation of lung cancer angiogenesis and indicate that PFN2 may serve as a therapeutic target against NSCLC.
Research Article
Profilin 2 regulates pyruvate kinase M2 nuclear translocation and potentiates tumor angiogenesis in non-small cell lung cancer
https://doi.org/10.21203/rs.3.rs-2834608/v1
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profilin 2
pyruvate kinase M2
NSCLC
actin-binding protein
angiogenesis
We characterize PFN2 as a signaling hub with potential therapeutic value for NSCLC due to its tumor progression and angiogenesis-inducing roles. PFN2 modulates the transcription complex PKM2-HIF-1α-p65-NF-κB, promoting transcription of angiogenesis-related factors.
Lung cancer is one of the most common malignant tumors and a leading cause of death worldwide [1]. Studies have shown that the occurrence, development, invasion, and metastasis of tumors depend on angiogenesis [2]. Newly generated blood vessels can supply oxygen and nutrients to growing tumor tissues and act as metastatic channels. Antiangiogenic therapy has attracted attention over the past few decades, with several drugs such as bevacizumab [3] and apatinib [4] having been approved for clinical applications and having achieved impressive results. However, antiangiogenic therapy is limited by its low response rates in some cancers, drug resistance and lack of more effective biomarkers. Therefore, more studies on the role and mechanism of lung cancer angiogenesis and development of additional targeted therapeutics are necessary.
Profilins (PFNs) are conserved small actin-binding proteins that are essential in all organisms examined to date, including animals, plants, and vaccinia viruses [5, 6]. The actin system of the archaea Asgardia was found to be regulated by eukaryotic PFNs, in a study on the origin of eukaryotes [7, 8]. PFNs contain actin-binding, phosphatidylinositol-binding, and proline-rich domains, which enable PFNs to interact with many proteins [9, 10]. These PFN protein interactors are highly heterogeneous, including nuclear export receptors, endocytosis regulators, Rac and Rho effector molecules, and putative transcription factors [5], indicating that PFNs have varied biological functions that are still unresolved.
PFN2, one of the main PFNs, was discovered serendipitously while sequencing cDNA library clones from the human brain and was originally considered to be expressed exclusively in the developing nervous system and in differentiated neurons. However, in recent years, researchers have found that PFN2 is abnormally expressed in a variety of tumors [11–13]. In addition, PFN2 is correlated with several clinicopathological factors and could be a biomarker for tumor treatment and prognosis. Nonetheless, our understanding of the molecular mechanisms and functional significance associated with PFN2 during the tumor progression is still limited, especially in the context of lung cancer.
PFN2 was highly expressed in lung cancer. It was upregulated by the circular RNA (circRNA) ataxin 7 (circATXN7) to accelerate the malignant progression of non-small cell lung cancer (NSCLC) [14]. It was also targeted by miR-30a-5p, which results in inhibition of epithelial-mesenchymal transition (EMT) in highly invasive NSCLC cell lines [15]. Tang et al. found that PFN2 promotes growth and metastasis of lung cancer by stimulating the EMT induced by TGF-β1 and the expression of VEGF and connective tissue growth factor (CTGF) through epigenetic mechanisms [16]. VEGF and CTGF are important vascular growth factors that can effectively promote vascular regeneration. Subsequently, PFN2 was proposed to promote the growth, metastasis, and angiogenesis of small-cell lung cancer through cancer-derived exosomes [17]. However, the mechanism and functional significance of PFN2 in NSCLC angiogenesis remains unclear, requiring further investigation.
Pyruvate kinase M2 (PKM2) is a rate-limiting glycolytic enzyme that catalyzes the conversion of phosphoenolpyruvate (PEP) and ADP to pyruvate and ATP. PKM2 promotes tumorigenesis by facilitating the Warburg effect and enhancing oncoprotein activity. PKM2 can form active tetrameric and less active dimeric complexes [18] that relate to its subcellular localization: tetrameric PKM2 is localized in the cytoplasm where glycolysis occurs to produce ATP, whereas dimeric PKM2 can translocate to the nucleus where it serves as a transcriptional coactivator or phosphotransferase [19, 20], modulating the transcriptional program. PKM2 is function as a coactivator for NF-κB [21–23], Oct4 [24, 25], β-catenin [26, 27], Stat3 [28, 29], and hypoxia-inducible factor (HIF)-1α [30–32] transcription. Relative to the tetrameric form, dimeric PKM2 has a higher Km value for the substrate PEP and is inactive at physiological concentrations of this substrate [33, 34]. This leads to the accumulation of metabolites in the glycolytic pathway and facilitates biosynthesis of those required for cell proliferation, similar to what occurs in cancer cells [35, 36].
In this study, we describe a role of PFN2 as a major regulator of PKM2 function. We observed that PFN2 is upregulated in lung cancer tissues and contributes to hypoxia-induced cell proliferation and tumor-sprouting angiogenesis in vitro and in vivo, namely via its regulatory effects on PKM2 function. The molecular mechanisms associated with PFN2 contribute to increased cancer angiogenesis in response to low-oxygen challenges, indicating that this protein plays a determining role in NSCLC angiogenesis.
Immunohistochemistry (IHC)
For IHC analysis of PFN2 or CD34, formalin-fixed paraffin-embedded (FFPE) sections were blocked with 5% bovine serum albumin (BSA) and incubated with mouse anti-PFN2 antibody (Proteintech, Rosemont, IL, USA) or mouse anti-CD34 antibody (Abcam, Cambridge, UK) overnight at 4°C. The sections were then incubated with biotinylated secondary antibodies, and detected using the Streptavidin-Peroxidase IHC assay kit and DAB (ZSGB-bio, China). Staining was evaluated by two certified pathologists, blinded to the experimental conditions, and scored according to staining intensity (negative: 0 points; weak: 1 point; moderate: 2 points; and strong: 3 points) multiplied by the percentage of stained cells (percentage of positive cells: ≤25%: 1 point; 26–50%: 2 points; 51–75%: 3 points; ≥75%: 4 points). Scores of <6 were considered low-expression, and scores of ≥6 were considered high-expression. Written informative consent was received from all participating individuals.
Lentiviral infection and transfection
Cells were plated at a density of 4 ´ 105/60 mm dish, 18 h prior to transfection. Transient transfection was performed using the Lipofectamine 2000 reagent (Invitrogen, Waltham, MA, USA) according to the manufacturer’s instructions. For stable transfection, cells were infected with lentivirus and selected using puromycin (5 mg/mL) according to the manufacturer's instructions. Transfection efficiency was determined using western blotting.
Escherichia coli containing the plasmids HA-PFN2, HA-PFN2-Mus, and Flag-PKM2 were purchased from LongQian Biotech (Shanghai, China). Lentiviral and plasmid constructs for PFN2 knockdown (hU6-MCS-Ubiquitin-EGFP-IRES-puro) were purchased from GeneChem (Shanghai, China). The shRNA targets were as follows:
shRNA#1: CGCGAAGAAATGCTCAGTGAT
shRNA#2: CCGGGAAGGTTTCTTTACCAA
Cell viability assay
Cell viability was evaluated using the cell counting kit-8 (CCK-8) assay (MedChemExpress, Monmouth Junction, NJ, USA). The cell suspension was inoculated into 96-well plates (2 × 103 cells/well) and CCK-8 solution (10 μL) added to the wells after 24 h. Following a 1 h incubation, absorbance was measured at 450 nm using a microplate reader.
Colony formation assay
For colony formation assays, cells were plated in 6-well plates (400 cells/well). After culturing for two weeks, cells were fixed with 4% paraformaldehyde and stained with 1% crystal violet. The colonies (>50 cells) were counted manually.
Tube-formation assay
Matrigel with reduced growth factor (100 μL/well) was added into 48-microwell plates and placed at 37°C for 30 min to solidify. Next, 4 × 104 human pulmonary microvascular endothelial cells (HPMECs) were resuspended in conditioned media from different cell types and added to the microwells. Cells were incubated for 6 h.
A droplet-based tumor angiogenesis model was established as previously described [37]. Tumor cells (TCs) were 3D cultured in Matrigel, whereas HPMECs were cultured as a monolayer. Both TCs and HPMECs were cultured in serum-free medium. After 24 h, TCs were transferred into the endothelial cell (EC) well, and a coculture unit was formed by fusing the two cell droplets through a reciprocating horizontal movement of the capillary between the two droplets.
Rhodamine phalloidin immunofluorescence staining used to assess tube formation. Angiogenic tube formation was quantified by calculating vessels area and total vessels length, counting the total number of junctions per field.
Tumor xenograft model
All animal experiments were approved by the Animal Care Committee of the Dalian Medical University (NO.00122713). BALB/c nude mice (7-weeks-old) were obtained from Liaoning Changsheng Biotechnology Co. Ltd. (Shenyang, China). A mixture of A549/shNC or A549/shPFN2 cell suspension in Matrigel (3:1, v/v) was injected subcutaneously into the dorsal flanks of nu/nu mice (3 × 106 cells/200 μL per mouse). Tumor xenografts were allowed to grow for 3 weeks. Tumors were measured every 3 days with calipers and calculated using the following formula: a2 × b × 0.5, where a is the smallest diameter and b is the diameter perpendicular to a. At the end of the experiment, the mice were sacrificed, and the tumors excised and weighed. All tissue samples were prepared into FFPE (4 μm) for later analysis by IHC.
Western blotting analysis
Whole cell and nuclear extracts were prepared. Protein samples were electrophoresed on SDS-PAGE and transferred onto polyvinylidene fluoride membranes (Merck, USA). The membranes were blocked with 5% skim milk in TBS containing 0.1% Tween-20 (TBST) and subsequently incubated with primary antibody, overnight at 4°C. Next, membranes were washed with TBST three times at room temperature and incubated with a horseradish peroxidase (HRP)-conjugated secondary antibody for 1 h, followed by three 10 min washes. Protein bands were visualized using an enhanced chemiluminescence (ECL) solution. Band intensities were quantified using the ImageJ software (NIH, Bethesda, MD, USA) and normalized to those of each control lane.
Immunofluorescence (IF)
Cells were cultured on glass-bottom culture dishes for 24 h and then fixed with 4% paraformaldehyde for 30 min followed by permeabilization with 0.5% Triton X-100 for 15 min. Cells were gently washed with PBS, blocked with normal goat serum for 40 min, and incubated with anti-PKM2 (1:50) antibody diluted in blocking buffer overnight at 4°C. After three 10 min washes, the cells were incubated with the corresponding fluorescence-conjugated secondary antibodies for 2 h at room temperature. After three more washes, the nuclei were stained with DAPI for 5 min. Cells were imaged using a confocal laser scanning microscope (Leica Microsystems, Wetzlar, Germany).
qRT-PCR
Total RNA was extracted using RNAiso Plus reagent (Takara Bio, Shiga, Japan) and assessed using a NanoDrop 2000 system (Thermo Fisher Scientific, Waltham, MA, USA) to determine RNA concentration and purity. cDNA was synthesized from 0.5–1 μg of total RNA using TransScript First-Strand cDNA Synthesis SuperMix (TransGen Biotech, Beijing, China). qPCR was performed using the TB Green Premix Ex Taq II (Takara Bio) on a LightCycler96 Real-Time System (Roche, Basel, Switzerland). The data were analyzed using the ΔΔCt method. All reactions were performed in triplicate, and mRNA levels were normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA expression. The primers used were as follows:
VEGF：
5'-TCACAGGTACAGGGATGAGACAC-3' (Forward)
5'-CAAAGCACAGCAATGTCCTGAA-3' (Reverse)
PFN2：
5'-GGCGTCTTTCAGAGCATTACG-3' (Forward)
5'-TGTCCATTGTGCAGTCACCAT-3' (Reverse)
GAPDH ：
5'-ACCACAGTCCATGCCATCAC-3' (Forward)
5'-ATGACCTTGCCCACAGCCTT-3' (Reverse)
ELISA of human VEGF (hVEGF)
To compare the hVEGF secretion by A549 cells in 3D droplets and traditional Petri dishes, a 3D droplet array composed of A549 cells was generated. After culturing for 48 h, supernatants from 20 droplets were collected and diluted 50-fold with FBS-free medium in a 96-well plate. hVEGF was quantified using an ELISA kit specific for hVEGF (R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s protocol.
Co-immunoprecipitation (Co-IP)
Co-IP assays were performed using the Pierce Classic Magnetic IP/Co-IP Kit (Thermo Fisher Scientific) according to the manufacturer’s protocol. Cell lysates from each sample were incubated with 10 μg of conjugated antibody, overnight at 4°C, to form the immune complex.
Liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis of PFN2-interacting proteins
To identify PFN2-interacting proteins, co-IPed proteins were visualized after separation by electrophoresis using a Coomassie Blue Staining Kit (Beyotime, Shanghai, China). The co-IP gel and its corresponding negative gel bands were excised into five parts according to the heavy and light chains and sent to Novogene (Beijing, China) for LC-MS/MS analysis. See ESM Methods for further details.
Surface plasmon resonance (SPR) assay
The binding affinity of recombinant hPFN2 (rhPFN2) to rhPKM2 was determined using an OpenSPR biomolecular interaction analyzer with a COOH chip (SEN-AU-100-10-COOH, Nicoya, Kitchener, Ontario). The rhPKM2 protein was dissolved in 10 mM acetate buffer (pH 3.5) and immobilized onto the chip. The sensor surface was activated by injecting a mixture of 50 mM N-hydroxysuccinimide (NHS) and 200 mM 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC), and blocking with 1 M ethanolamine, pH 8.5. Different concentrations of rhPFN2 (800, 400, 200, 100, 50, and 0 nM) were prepared in the running buffer (PBS). The interactions were determined at a flow rate of 20 μL/min for 240 s during the association phase, followed by 180 s for the dissociation phase at 25°C. The data were analyzed using the TraceDrawer manager software (Uppsala, Sweden). The binding kinetic parameters were calculated by global fitting of the kinetic data from various concentrations of rhPFN2 using a one-to-one analysis model.
Computational docking and molecular simulation
The crystal structures of PFN2 and PKM2 were obtained from the Protein Data Bank (PDB; http://www.rcsb.org/pdb/). The Rosetta software was used for protein docking, which consisted of two steps. Aggressive sampling was performed in the first step, using the centroid model. In the second step, an all-atom model was used for small-scale optimization. Because the binding mode between proteins was not clear, the blind docking method was adopted for the first docking between any systems, that is, random placement and random docking of two proteins. Docking results for 100 phases were obtained. First, blind molecular docking was performed on PFN2 and PKM2, and the active binding regions of the two proteins were set. The lowest docking energy among the 100 docking results between PFN2 and PKM2 was selected for further analysis.
Statistical analysis
Significance was calculated using GraphPad Prism software (GraphPad Software, San Diego, CA, USA). All statistical analyses were performed using data from at least three independent experiments. More than three means were compared using two- or one-way ANOVA with Bonferroni correction, and two means were compared using the unpaired Student’s t-test of *P<0.05 was considered significant.
For IHC, the results were analyzed using a nonparametric alternative to ANOVA. The Kruskal–Wallis H test was used to assess differences between the four independent groups; if there was a significant difference, we tested the differences between every two groups using the Mann-–Whitney U test.
Increased PFN2 expression is associated with poor prognosis in patients with lung adenocarcinoma
Numerous studies have indicated that abnormal PFN2 expression may be important in cancer progression, metastasis, and prognosis. To determine the role of PFN2 in the development and progression of human lung adenocarcinoma, 94 cases of lung adenocarcinoma and 86 cases of adjacent non-tumor tissues were examined for PFN2 expression. PFN2 was mainly located in the cytoplasm of tumor cells, and 73.26% of lung adenocarcinoma tissues expressed high levels of PFN2 compared to adjacent non-tumor tissues (P<0.001; Fig. 1A, 1B and Table 1). Further analyses showed that higher PFN2 expression in lung adenocarcinoma was significantly correlated with higher grade and poor survival (P=0.000; Fig. 1C). Similar findings were observed in 483 patients with lung adenocarcinoma from the KM plotter database. It revealed that patients with high PFN2 expressing had a significantly shorter overall survival (P=0.026; Fig. 1D) and disease free survival (P=0.012; Fig.1E) than those with low PFN2 expression. Hence, high PFN2 expression is associated with a poor prognosis in patients with lung adenocarcinoma.
Table 1 Differential expression of PFN2 in cancerous and lung tissues.
PFN2 depletion inhibits tumor cell proliferation and tumor cell-induced angiogenesis
Based on previous reports, we speculated that PFN2 may be involved in angiogenesis in lung cancer, which is an important mechanism to support tumor growth [38]. To investigate the effects of PFN2 on tumor proliferation and angiogenesis, we transduced A549 cells with PFN2-specific shRNAs or a non-targeting shRNA (shNC). CCK8 and colony formation assays indicated that knockdown of PFN2 was closely correlated with a marked reduction in cell proliferation, whereas the shNC showed no effect (Fig. 2A-C). A tube formation assay subsequently demonstrated that PFN2 knockdown significantly inhibited HPMEC-mediated angiogenesis in vitro (Fig. 2D and E). To evaluate the effect of PFN2 knockdown on tumor formation in vivo, we performed subcutaneous injections of A549-shNC and A549-shPFN2#1 and #2 cells in BALB/c nude mice. The size and growth rate of the subcutaneous tumors were observed dynamically. As shown in Fig. 2F-H, PFN2 knockdown dramatically inhibited tumor growth in terms of volume (Fig. 2F) and weight (Fig. 2G, H). Moreover, IHC analysis of xenograft tissue slides (Fig. 2I) demonstrated that PFN2 knockdown markedly inhibited angiogenesis (CD34+) in vivo. These results suggest that PFN2 contributes to enhanced lung tumor growth and angiogenesis.
PFN2 depletion inhibits the NF-κB/HIF-1α signaling pathway
Fig. 3A depicts the model used to culture 3D tumor cells and 2D HUVECs in droplets, which are then fused to obtain cocultures, mimicking the interactions between TCs and ECs during the formation of capillary-like structures. Hypoxia triggers transcriptional programs that involve the upregulation of HIF-1α and downregulation of the proline hydroxylase family (PHD1-3) [39]. To verify the anoxic state of A549 cells during 3D droplet culture, cells were encapsulated in 10 μL 3D droplet. After 24 h of culture, cell precipitates were collected and total proteins extracted. We found that the expression of HIF-1α was upregulated, whereas the expression of PHD3 and its hydroxylation activity were downregulated (Fig. 3B). The expression of HIF-1α was then detected in by IF staining in frozen sections. We found that HIF-1α expression was enhanced in 3D droplets of lung cancer cells (Fig. 3C). These results indicate that droplet-based 3D cell culture can simulate the anoxic state of tumor tissues in vivo and can be used as a tumor-like platform for subsequent research on molecular mechanisms.
Next, we measured VEGF mRNA and protein levels after PFN2 knockdown, since this is a key factor contributing to tumor angiogenesis under hypoxia. We found that the levels of hVEGF, both at the mRNA and protein levels, were decreased (Fig. 3D, E). To determine how PFN2 knockdown affected lung cancer growth and angiogenesis, we compared the levels and activation status of key effectors in A549-shNC and A549-shPFN2#1 and #2 cells cultured in 10 μL 3D droplets. We found that when PFN2 was knocked down, the expression of p65-NF-κB and HIF-1α were downregulated (Fig. 3F). In addition, the expression of VEGF, cyclin D1, and mitogen-activated protein kinase kinase 5 (MEK5) was also downregulated. These results suggest that PFN2 enhances tumor growth and angiogenesis via a mechanism involving the activation of the NF-κB/HIF-1α signaling pathway and the expression of angiogenic factors.
PFN2 physically interacts with PKM2
To elucidate the mechanism by which PFN2 promotes lung cancer angiogenesis, we performed LC-MS/MS (Fig. S1) and identified 1449 proteins that co-IPed with PFN2 in lung cancer cells (Table S1). A band containing multiple peptides corresponding to PKM2 was also identified. We confirmed the MS/MS-based protein identification using IF to detect the association between PFN2 and PKM2. We observed that PFN2 co-localized with PKM2, mainly in the cytoplasm (Fig. 4A). HEK293T cells were transfected with pcDNA-Flag-PKM2 alone or pcDNA-HA-PFN2, followed by co-IP using anti-FLAG antibodies. Western blot analysis revealed that PFN2 was present in anti-Flag co-IPs from cells co-transfected with pcDNA-HA-PFN2 and pcDNA-Flag-PKM2, but not in cells co-transfected with Flag-PKM2 and the HA vector (Fig. 4B). Similarly, reciprocal co-IP analysis was conducted by transfecting cells with pcDNA-HA-PFN2 alone or pcDNA-Flag-PKM2, followed by co-IP using anti-HA antibodies (Fig. 4C). We further measured the binding affinity between PFN2 and PKM2 using SPR assays, in which PKM2 was immobilized on the sensor chip. A clear binding profile was observed, with a dissociation equilibrium constant of 5.06e-8 M (Fig. 4D).
To elucidate the binding interactions between PFN2 and PKM2, we performed molecular docking studies. The binding modes of PFN2 and PKM2 in the molecular dynamics simulation of 70–100 ns are shown in Fig. 4E. The enlarged diagrams of the binding interface are shown in Fig. 4E (up and right, Part A and Part B). We found that PFN2 displayed a high binding affinity to PKM2 with an estimated binding free energy of −91.53 kcal/mol. The amino acids at the interface between the two proteins form a relatively dense binding network. For example, PKM2 forms four hydrogen bonds with residues A2, N10, Y30, and S138 of PFN2 and two salt bridges with residues R108 and D137 at the interaction interface. Moreover, MM/GBSA free energy decomposition analysis showed that the residues Y7, N10, Y30, R108, S134, D137 and S138 of PFN2 significantly contributed (<−1 kcal/mol) to the binding of PFN2 to PKM2 (Fig. 4F).
To validate the PFN2 binding sites to PKM2, we mutated residues Y7, N10, Y30, R108, S134, D137, and S138 in the PFN2 binding interface. Co-IP analyses were performed using lysates from HEK293T cells transfected with plasmids harboring these mutations. We found that, compared to the wild-type group, replacement of R108, S134, D137, and S138 with alanine significantly weakened the binding between PFN2 and PKM2, particularly S134A and S138A. However, the single point mutation Y30A did not affect the interaction between PFN2 and PKM2. Mutations Y7A and N10A appeared to block the breakdown of the complex (Fig. 4G). Taken together, these results confirm that PFN2 is physically associated with PKM2 and that the most critical interaction region in PFN2 resides in the C-terminal region (residues 108–138).
PFN2 regulates the expression and nuclear translocation of PKM2
Next, we investigated whether PFN2 impacts lung cancer growth and angiogenesis by regulating PKM2. We first determined the expression levels of PKM2 in shPFN2 cells and found that PKM2 expression was downregulated (Fig. 5A). To investigate whether PFN2 affects the nuclear localization of PKM2, we assessed the nuclear and cytosolic distributions of PKM2 in shNC- and shPFN2-transfected cells, using confocal microscopy (Fig. 5B). We detected nuclear PKM2 in shNC cells but very little in shPFN2 cells. Western blot analysis of nuclear and cytosolic fractions from shPFN2-expressing cells revealed a significant decrease in the nuclear PKM2 signal in shPFN2 cells compared to that in shNC cells, in accordance with the confocal microscopic findings (Fig. 3C). Phosphorylation of PKM2 at S37 mediated by ERK1/2, which is stimulated by EGF treatment, is known to induce translocation of PKM2 to the nucleus [26, 40]. Thus, we investigated whether expression of ERK1/2 and PKM2 S37 phosphorylation were affected by PFN2 knockdown. We found that PFN2 knockdown led to reduced expression of ERK1/2 and impaired phosphorylation of PKM2 S37 (Fig. 5D). In addition, western blotting of the cytoplasmic and nuclear fractions and IF analysis revealed that EGF treatment promoted PKM2 nuclear translocation in lung cancer cells, which was impaired in shPFN2 cells. However, in these cells, EGF treatment induced increased PKM2 expression and S37 phosphorylation and restored ERK1/2 expression. Taken together, these results indicate that PFN2 is necessary for PKM2 nuclear translocation at least in part via the regulation of PKM2 S37 phosphorylation mediated by ERK1/2.
PKM2 is known to form a transcriptional complex, in the nucleus, with HIF-1α and p65-NF-κB, resulting in the transcription of downstream target genes. To explore whether PFN2 downregulation interfered with the formation of NF-κB/HIF-1α/PKM2 transcriptional complex, we performed co-IP assays and found that HIF-1α and p65-NF-κB binding to PKM2 were decreased in cells expressing shPFN2 (Fig. 5G). This suggests that PFN2 knockdown also interferes with the formation of PKM2/HIF-1α/p65-NF-κB transcription complex, thus affecting the expression of downstream target genes.
Binding of PFN2 to PKM2 is required for nuclear translocation of PKM2 and affects lung cancer angiogenesis
These results led us to question whether binding of PFN2 to PKM2 was necessary for the nuclear translocation of PKM2. To answer this question, we co-transfected HEK293T cells with PKM2-FLAG and empty, PFN2-HA, PFN2 Y134A-HA, PFN2 S138A-HA or PFN2 Y134A+S138A plasmids and detected protein expression using western blot analysis (Fig. 6A). Analysis of nuclear and cytosolic fractions revealed that the nuclear translocation of PKM2 was decreased in cells expressing PFN2 Y134A or S138A, an effect that was exacerbated in PFN2 Y134A+S138A-expressing cells (Fig. 6B). Similarly, phosphorylation of PKM2 S37 was significantly reduced in cells expressing the double mutant of PFN2 (Fig. 6C). We also explored the effect of these PFN2 mutations on angiogenesis and found that expression of PFN2 Y134A+S138A inhibited tube formation in HPMEC cells (Fig. 6D). These results indicate that the interaction between PKM2 and PFN2 is necessary for the nuclear localization of PKM2, as demonstrated by impaired translocation of PKM2 elicited by PFN2 binding site mutations, which in turn affects angiogenesis.
PFN2 is an important member of the profilin family of actin-binding proteins. In this study, we report a connection between PFN2 and the angiogenesis-related molecule, PKM2. These proteins interact via multiple amino acid sites, including PFN2 residues Y134 and S138 that are located in the C-terminal helical region. PFN2 knockdown leads to reduced PKM2 nuclear translocation by impairing PKM2 S37 phosphorylation, which is mediated by ERK1/2, and inhibits the formation of the PKM2-HIF-1α-p65-NF-κB transcription complex, thus impacting lung cancer angiogenesis.
Hypoxia is an important feature of the microenvironment of all solid tumors and can activate a specific transcriptional program in cells that allows them to adapt to lower oxygen levels and induce tumor angiogenesis. However, at present, most studies on hypoxia-regulated gene expression have been conducted in vitro [41, 42], in which tumor cells are cultured with the same oxygen concentration as in normal air and then exposed to a low oxygen concentration (1% O2) for a short time or with chemical hypoxia simulators such as cobalt chloride. Thus, the hypoxia conditions in culture may not recapitulate what occurs in tumor cells that are oxygen-starved. Indeed, there are distinct gene expression patterns in cells experiencing intratumoral hypoxia in vivo and in cells exposed to hypoxia in vitro [43]. Post-hypoxic tumor cells have a ROS-resistant phenotype that provides a survival advantage in the bloodstream and promotes their ability to establish distant metastasis. Therefore, establishing a tumor angiogenesis model that can effectively simulate the anoxic tumor microenvironment in vivo is one of the key technical challenges in this field. In our previous studies [37], a 3D coculture system based on droplet arrays was developed, which can simulate the size and microenvironment of solid tumor tissue for tumor angiogenesis detection. We characterized the hypoxia state and found that lung cancer cells in 3D droplets can recreate an hypoxic microenvironment that is more similar to that in solid tumors, with increased HIF-1α and decreased PHD3 expression. This method provides a reference model for the simulation of anoxic microenvironments and the study of anoxic-related genes. Furthermore, immune cells can be integrated in the model, to study cellular interactions and their molecular mechanisms in an anoxic environment.
PFN2 consists of seven beta chains and four alpha helices and has three binding domains: the actin, poly-L-proline, and phosphatidylinositol 4,5-diphosphate-binding domains. Through its poly-L-proline domain, PFN2 interacts with many proteins, including ROCK and dynamin-1 [5]. Hundreds of potential PFN2 interactors were detected in our co-IP combined with LC-MS/MS assay, which were highly heterogeneous. Many of the identified proteins were binding proteins, including fatty acid-binding protein 5, polypyrimidine bundle-binding protein, polyadenylate-binding protein, S100 calcium-binding protein, and Hsp90. Several new PFN2-binding proteins have been reported in recent years, for example the N-terminal acetyltransferase NAA80 [44]. PFN2 was found to interact with NAA80 via its proline-rich loop and specifically increase the intrinsic catalytic activity of NAA80. This binding also promotes the interaction between the globular domains of actin and NAA80, and subsequent acetylation of actin. In this process, PFN2 acts as a chaperone by promoting N-terminal acetylation of actin, before filament formation. Another recently characterized interactor of PFN2 is the histone deacetylase HDAC1. PFN2 can bind HDAC1 and inhibit its activity, thus enhancing the transcriptional activation of SMAD2 and SMAD3 through epigenetic mechanisms, which promotes growth and metastasis in NSCLC [16]. Ectopic overexpression of formin like 1 (FMNL1) significantly enhanced the binding between HDAC1 and PFN2 in the cytoplasm and inhibited the enrichment of HDAC1 in the metastasis associated 1 (MTA1) promoter, leading to increased transcription and expression of MTA1 and promoting the development, invasion, and metastasis of nasopharyngeal carcinoma [45]. The retinoic acid receptor alpha subtype (RARα) has also been identified as a PFN2 binding partner. The N-terminal proline-rich motif (PRM) of RARα interacts with the SH3-like domain of PFN2 and promotes actin filament elongation [46]. Taken together, these findings point to a role of PFN2 as a chaperone or hub molecule that controls complex molecular interactions. This indicates that interfering with PFN2 expression could be an effective node for inhibiting this signaling network and prevent tumorigenesis.
PKM2 is a pivotal protein involved in tumor glycolysis, oxidative stress, and angiogenesis in a variety of tumors. For example: 1) In pancreatic cancer, PKM2 promotes tumor angiogenesis by regulating HIF-1α through activation of NF-κB [47]. 2) In bladder cancer, PKM2 promotes angiogenesis and “metabolic addiction” to maintain tumor growth through the PKM2-STAT3-HIF-1α/VEGF signaling axis [48]. 3) In colorectal cancer, forkhead box M1 (FOXM1D) interacts with PKM2 and NF-κB and induces their nuclear translocation with the assistance of the nuclear transporter importin-4. Once in the nucleus, PKM2 and NF-κB complexes promote VEGFA transcription and tumor angiogenesis [49]. 4) In triple-negative breast cancer, destruction of the PKM2/NF-κB/miR-148a/152 feedback loop modulates cancer cell growth and angiogenesis [50]. Here, we report a regulatory effect mediated by PFN2 on lung cancer angiogenesis via its binding to PKM2.
We found that PFN2 binds to PKM2 via multiple residues as illustrated by the decreased interaction elicited by mutations in the Y134 and S138 residues of PFN2. Interfering with the interaction between PFN2 and PKM2 results in reduced nuclear translocation of PKM2, thereby affecting angiogenesis. The Y134 and S138 residues are located in the C-terminal helical region, which forms the polyproline binding pocket with the N-terminal helical region, thereby enabling PFN2 to interact with many proteins. Mutations in these two sites may result in a deficiency in poly-L-proline binding, thus affecting the binding of PKM2. In addition, mutation of PFN2 at Y134 or S138 abrogates the PFN2–dynamin interaction and inhibits endocytosis [51], which has been suggested as a new strategy for enhancing tumor immunotherapy [52]. If drug development targeting these two PFN2 sites simultaneously, unexpected effects may occur. This indicates that additional research is needed to uncover the complex regulatory effects of PFN2 in tumor cells, which may elicit the development of multi-effect antitumor drugs targeting PFN2.
In summary, our study shows that the downregulation of PFN2 causes abnormal vascular functions, which could significantly reduce vessel number and tumor growth both in PFN2 knockdown cells and mouse subcutaneous tumor transplantation models. Mechanistically, our results offer a novel framework in which PFN2 interacts with and promotes nuclear translocation of PKM2. Knockdown PFN2 interferes with PKM2 S37 phosphorylation and inhibits the formation of PKM2-HIF-1α-p65-NF-κB transcription complex, thereby affecting downstream gene transcription. These findings revealed that lung tumor growth requires proper angiogenesis that depends on an intact PFN2-PKM2-angiogenic factor signaling axis, warranting further research of this mechanism as a valuable target for lung cancer treatment.
Acknowledgements
This work was funded in part by the Natural Science Foundation of China (82027805, 81903185, 81972916 and 81703087), Liaoning Revitalization Talents Program (XLYC2002013), Project of Education Department of Liaoning Province (No.LJKZ0833), the Talent Innovation Support Plan of Dalian (2021RQ008).
The authors declare no potential conflicts of interest.
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No competing interests reported.
- FigureS1.tif
Fig. S1 Whole-cell extracts of A549 were collected, proteins that interacted with PFN2 were identified by combining Co-IP and mass spectrometry methods. A Validation of PFN2 accumulation in the immunoprecipitates by Coomassie staining. B-F Functions annotation after mass spectrometry analysis of the immunoprecipitates with IgG or the anti-PFN2 antibody. B Subcellular localization; C COG function classification; D GO annotation; E IPR annotation; F KEGG pathway annotation.
- TableS1.xlsx
Table S1. The proteins interacted with PFN2 were identified by combinding co IP and mass spectrometry.