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. 2022 Jun 19;79(7):367. doi: 10.1007/s00018-022-04399-8

Reciprocal regulation of Daxx and PIK3CA promotes colorectal cancer cell growth

Yen-Sung Huang 1,2,✉, Chang-Chieh Wu 3, Che-Chang Chang 2,4,5,6, Shiu-Feng Huang 7, Hong-Yi Kuo 7, Hsiu-Ming Shih 1,2,7,✉
PMCID: PMC11072676  PMID: 35718818

Abstract

Upregulation of death-domain-associated protein (Daxx) is strongly associated with diverse cancer types. Among these, the clinicopathological significance and molecular mechanisms of Daxx overexpression in colorectal cancer (CRC) remain unknown. Here, we showed that Daxx expression was increased in both clinical CRC samples and CRC cell lines. Daxx knockdown significantly reduced proliferation activity in CRC cells and tumor growth in a xenograft model. Further studies revealed that Daxx expression could be attenuated by either treatment with the PIK3CA inhibitor PIK-75 or PIK3CA depletion in CRC cells. Conversely, expression of PIK3CA constitutively active mutants could increase Daxx expression. These data suggest that PIK3CA positively regulates Daxx expression. Consistently, the expression levels of PIK3CA and Daxx were positively correlated in sporadic CRC samples. Interestingly, Daxx knockdown or overexpression yielded decreased or increased levels of PIK3CA, respectively, in CRC cells. We further demonstrated that Daxx activates the promoter activity and expression of PIK3CA. Altogether, our results identify a mechanistic pathway of Daxx overexpression in CRC and suggest a reciprocal regulation between Daxx and PIK3CA for CRC cell growth.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00018-022-04399-8.

Keywords: CRC, PIK3CA, p110α, PI3K inhibitors, AKT

Introduction

CRC is the third most prevalent cancer among estimated new cancer cases and cancer related deaths in the United States in 2021 [1], underscoring the urgent need of understanding the molecular mechanisms that promote CRC progression and discovering new therapeutic targets for treatment and prevention. One important signaling pathway frequently dysregulated in CRC is the class I phosphatidylinositide-3-kinase (PI3K)/AKT pathway [2], which modulates cell survival, cellular proliferation, angiogenesis, metabolism and metastasis [3] and is often activated in the advanced stage of CRC [4]. Thus, the class I PI3K/AKT pathway represents an attractive target for therapeutic intervention.

PI3K catalytic subunit is responsible to phosphorylate the inositol ring of phosphatidylinositol(4,5)-bisphosphate (PIP2) at the D-3 position to form phosphatidylinositol(3,4,5)-trisphosphate (PIP3), a critical second messenger that recruits AKT for activation [5]. The catalytic subunit of class I PI3K consists of four isoforms (PIK3CA, PIK3CB, PIK3CD and PIK3CG) [3]. Among these isoforms, PIK3CA is often activated in CRC by gain-of-function hotspot mutations and gene amplification [6]. More than 75% of these mutations are clustered in the helical (E542K, E545K) and kinase (H1047R) domain of the PIK3CA gene [7], which leads to constitutively elevated lipid kinase activity, thereby resulting in increased AKT activation in CRC [8]. While inhibition of PIK3CA activity appears to be a good therapeutic strategy for CRC treatment, downregulation of the PIK3CA expression can be considered as another therapeutic intervention.

Previous studies reported that PIK3CA expression could be regulated by certain transcription factors. For instance, Y-box binding protein-1 can activate PIK3CA promoter activity, leading to elevated levels of basal-like breast carcinoma cell invasion [9]. Forkhead BoxO 3a induces PIK3CA expression by directly binding to PIK3CA promoter, rendering chronic myelogenous leukemia cells resistant to doxorubicin [10]. In addition, PIK3CA expression levels could be increased by nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) in ovarian cancer [11]. Given that little is known about the regulation of PIK3CA gene expression, identification of novel PIK3CA regulator(s) would provide additional candidates for targeted therapy of the PIK3CA-elicited cancer.

Daxx is a predominantly nuclear protein found in association with several different subnuclear structures, including the heterochromatin, PML nuclear body and nucleolus [12–14]. Daxx has several cellular functions, including the co-regulation of apoptosis and transcription via SUMO (small ubiquitin-like modifier) binding-dependent and -independent manners [15, 16]. Several Daxx-interacting proteins are involved in cancer-associated cellular pathways, such as p53, promyelocytic leukemia protein, Smad4 and transcription factor 7-like 2 (TCF4) [17–19]. Emerging evidence indicates an overexpression of Daxx in associated with various types of cancer. For instance, Daxx overexpression has been reported in prostate cancer [20–22], myelodysplastic syndrome [23], urothelial carcinoma [24], esophageal squamous cell carcinoma [25], and oral squamous cell carcinoma [26]. A positive correlation of Daxx and Ki-67 was found in prostate cancer and pancreatic neuroendocrine tumors [20, 27]. Furthermore, Daxx promotes prostate cancer tumorigenicity via suppression of autophagy modulator DAPK3 and ULK1 [21]. Daxx could enhance ovarian cancer ascites’ cell proliferation through ERK pathway activation [28]. However, the etiology of Daxx overexpression and its clinicopathological significance in CRC remain largely unclear.

A study by Tzeng et al. showed that Daxx reduced TCF4 transcriptional activity by impairing TCF4 DNA binding affinity [29]. However, our previous study indicated that Daxx functions as a positive co-regulator in modulating the TCF4-dependent transcriptional activity via direct protein–protein interaction [17]. Regardless of these contradictory observations, whether Daxx plays a tumor suppressive or oncogenic role in CRC remains to be clarified. Here, we demonstrated that Daxx has a tumor-promoting function in CRC by increasing the expression of PIK3CA. Moreover, we also showed that the PIK3CA pathway could activate Daxx promoter activity. Together, our findings provide evidence of previously undescribed reciprocal regulation of Daxx and PIK3CA expression in promoting CRC cell growth.

Materials and methods

Specimens

CRC samples were obtained from Tri-Service General Hospital following Institutional Review Board approved protocols (098-05-292). The CRC tissue array was purchased from SUPER BIO CHIPS (Seoul, Korea) with Institute Review Board approval.

Immunohistochemistry (IHC)

IHC was performed as previously described [30]. Briefly, paraffin-embedded slides were incubated with antibodies against Daxx (D7810, Sigma, St. Louis, USA) or PIK3CA (4249, Cell Signaling Technology, Danvers, USA) 1 h at room temperature, stained with the Vectastain Elite ABC kit (Vector Lab, Burlingame, CA), developed using DAB (brown precipitate, Vector Lab), and visualized by light microscopy (Olympus, Tokyo, Japan). Images of histological samples were digitalized using Mirax Scan. Staining intensity was grouped into four categories based on signal density: none (0), weak (+1), medium (+2) and strong (+3); samples with negative (signal density 0 and + 1) or positive (signal density + 2 and + 3) were analyzed accordingly.

Cells and reagents

All cell lines were cultured in respective medium with 10% fetal bovine serum. HEK-293 T, HT29 and HT29-Luc were cultured in DMEM medium; HCT116 and Cas9-HCT116 were culture in McCoy’s 5a. CCD18-co cells were culture in MEM with 1 mM sodium pyruvate as mention previously [31]. Whole cell lysates of Colo 205, HCC-2998, SW620, KM12, and HCT15 cell lines were purchased from Origene (Rockville, USA). Lentiviral transduction of the MSCV Luciferase PGK-hygro plasmid was performed to generate the luciferase stably expressing HT29 cells (HT29-Luc) for xenograft experiments. PI3K inhibitor PIK-75 was purchased from Selleckchem (Houston, USA).

Plasmids

The pcDNA3-HA-Daxx constructs expressing full length, 1–625 and 570–740 proteins were described previously [32, 33]. MSCV Luciferase PGK-hygro, PIK3CA-Exon20 H1047R, PIK3CA-Exon 9 E545K and pX330-U6-Chimeric_BB-CBh-hSpCas9 plasmids were a gift from Dr. Scott Lowe (Addgene plasmid 18,782), Dr. Bert Vogelstein (Addgene plasmid # 16639 and 16642) and Dr. Feng Zhang (Addgene plasmid # 42230), respectively [34, 35]. The PIK3CA promoter construct containing the PIK3CA promoter sequence from − 2122 to + 482 was supported by Dr. Noriyuki Tsumaki [36]. The lentivirus plasmid expressing Luc, GFP, Daxx#1 or #2 shRNA were purchased from the National RNAi Core Facility located at the Academia Sinica. The shRNA sequences are listed as follows: shLuc: CTTCGAAATGTCCGTTCGGTT, shGFP: CAACAGCCACAACGTCTATAT, shDaxx#1: TCACCATCGTTACTGTCAGAA, shDaxx#2: GGAGTTGGATCTCTCAGAA and mouse shDaxx: CCTGGATCTCATCTACAACTT. pcDNA3-HA-DaxxRFL was created by introducing silent mutation within shDaxx#2 corresponding sequence, which generated a shDaxx#2-resistant Daxx full length clone. All construct transfections were performed using Lipofectamine 2000 reagent (Life Technologies) according to the manufacturer’s instructions.

Cell viability assay

Cell viability was determined by trypan blue dye exclusion with cells harvested at 48 h post-DNA transfection or -lentiviral transduction. For PIK-75 treatment, cells were seeded into 6-cm plates at a density of 1 × 105 per well and treated with either vehicle control (DMSO) or PIK-75 (200 nM). The viability of these treated cells at indicated time points was monitored using 100 µL aliquot of complete growth medium with 10% alamarBlue reagent (88951, ThermoFisher Scientific, USA) into a 96-well plate for 3 h and followed by optical density of each plate measured at 540 and 630 nm with a standard spectrophotometer.

Colony formation assays

HT29 cells co-transfected with 10 μg lentivirus plasmid expressing shLuc or shDaxx#1 and 1 μg hygromycin B-resistance vector (Clontech) were selected for growth in media containing 250 μg/ml hygromycin B (10687010, Life Technologies). Colonies of the hygromycin-resistant cells after 14-day selection were visualized by crystal violet staining.

Lentivirus production and infection

Replication-deficient lentivirus was prepared by cotransfection of HEK-293 T cells with indicated plasmids using the PolyJet reagent (SignaGen Laboratories, Ijamsville, USA). Viral supernatants were collected at 72 h post-transfection, filtered, and stored at − 20 °C. For lentiviral infection, cells were incubated with lentivirus supernatants in the presence of 7.5 µg/ml of polybrene (Sigma) for 24 h.

Xenograft tumor model

Eight-week-old female nonobese diabetic/severe combined immunodeficiency (NOD/SCID) mice from the National Laboratory Animal Center were randomly allocated to one of three groups (3 or 5 mice per group) and injected subcutaneously with indicated HT29 cells. For in vivo bioluminescence imaging of xenograft tumors, xenograft mice were subcutaneously injected with 150 mg/kg D-Luciferin (122796, PerkinElmer) for approximately 30 min before imaging using the IVIS 200 system (PerkinElmer). The images were acquired at 1-min interval. Tumor volume was measured by a caliper and calculated using the formula width2 × length × 0.5. All animal procedures were performed under Academia Sinica IACUC-approved protocol#2009-018.

Protein extraction and western blot analysis

Cells transfected with indicated siRNA, plasmids or lentivirus were cultured for 48 h, then followed by extraction and immunoblotting procedure as described previously [32]. Sonicated tumor tissues or transfected cells were lysed directly in RIPA buffer containing protease inhibitor cocktail (4693132001, Sigma). Then, the lysates were subjected to SDS-PAGE gel electrophoresis (40 μg/lane), transferred onto Protran Transfer Membrane (NBA085C001EA, PerkinElmer, Boston, USA), probed with indicated antibodies, including Daxx (D7810, Sigma), PIK3CA (4249, Cell Signaling Technology), HA (H3663, Sigma), β-actin (A5441, Sigma), RNA polymerase II CTD phospho S2 (ab5095, Abcam), AKT (4691, Cell Signaling Technology) and phospho-AKT (4060, Cell Signaling Technology), and followed by enhanced chemiluminescence assays and analyzed with Las-4000 imaging system (Fujifilm, Valhalla, USA).

EdU-incorporation assay for cell proliferation

Cell proliferation was analyzed using the Click-iT EdU cell proliferation assay kit (C10419, ThermoFisher Scientific, USA). In brief, cells were grown at initial density of 8 × 105 cells onto 10 cm petri dishes. After 1-day incubation, the cells were pulsed with 10 μM EdU (5-ethynyl-2′-deoxyuridine) for 2 h and then fixed for labeling with Click-it EdU detection reagent conjugated with Alexa Fluor 647. The EdU-positive cells were analyzed on a FACSCanto flow cytometer (BD Biosciences, San Jose, USA).

Chromatin immunoprecipitation quantitative PCR (ChIP-qPCR) assay

2 × 106 cells were harvested at 48 h post-transfection for ChIP analysis as described [33]. ChIP product was analyzed by quantitative real-time PCR using the Applied Biosystem 7500 Real-Time PCR System as previously described [34]. Briefly, ChIP integrating DNA extraction was subjected to qPCR using specific primers for Daxx promoter: 5′-CGGAGTCCGGGCGTAG-3′ and 5′-CTTCCAGGTCGGAGT TTGTC-3′, GAPDH gene body: 5′-CACCGATCACCTCCCATCG-3′ and 5′-GTAGCCGGGCCCTACTTTC-3′, PIK3CA promoter segment 1: 5′-GCTTTTTCTGCTATGACACACAACTTC-3′, and 5′-GCACCTGGCCTATTT GTGATTTTTA-3′; PIK3CA promoter segment 2: 5′-GTGGATCACCTGAA GTCAGAA-3′ and 5′-CCAGAGTCTCACTCTGTAGC-3′; PIK3CA promoter segment 3: 5′-GTGAAACTACGACCACAAAGAGGA-3′ and 5′-AGCATCGGT TCCTCCTTGAA-3′; and PIK3CA promoter segment 4: 5′-GTCTCCAC GAAGTGAGTCAAA-3′ and 5′-CACCCATAGAGGAAACGAGATTA-3′.

Analysis of public data sets

The processed RNA-sequencing data of colon adenocarcinoma data set, prostate cancer and ovarian cancer were obtained from The Cancer Genome Atlas (TCGA) Data Portal (https://tcga-data.nci.nih.gov/tcga/) [4]. The expression intensities of both Daxx and PIK3CA were compared using the standard linear correlation in SigmaPlot software.

Establishment of Cas9-HCT116 cells generated by CRISPR (clustered regularly interspaced short palindromic repeat)/Cas9

sgRNAs targeting Daxx were designed using tools from http://crispr.mit.edu provided by Zhang laboratory [35]. The sgRNA oligonucleotides (5′-CACCGAGTTTGGCCATGA GTCGGC-3′ and 5′-AAACGCCGACTCATGGCCAAACTC-3′) were annealed and cloned into BbsI-digested vector pX330-U6-Chimeric_BB-CBh-hSpCas9 to generate a construct pX330-Daxx. pX330-Daxx construct was transfected into HCT116 using Lipofectamine 2000 reagent (Life Technologies). After 48 h, transfected cells were cloned using FACS and colonies were expanded for genotyping and Western analysis. The oligonucleotides to generate the genomic PCR for DNA sequencing of the Daxx targeting region were Daxx exon 4 target F1 (5′-ATGACCCAGACTCCGCATAC-3′) and Daxx exon 4 target R1 (5′-CTGTACCCCATCCACACCTC-3′).

Statistical analysis

Regression analyses were performed using SigmaPlot software (Systat Software). Significance (P < 0.05) was ascertained using an unpaired Student’s t-Test or one-way ANOVA with GraphPad Prism software (GraphPad, San Diego, USA).

Results

Daxx expression is increased in clinical CRC specimens and CRC cell lines

We first analyzed Daxx expression in CRC using TCGA data sets [4]. The results indicated that Daxx was increased in 19 of the 28 CRC specimens, compared with the adjacent normal tissues (Fig. 1a). Next, we collected clinical specimens of paired normal colon tissue and CRC tissue for quantitative RT-PCR analysis. Among the 15 paired specimens, 12 of which showed higher expression of Daxx RNA in the tumor than in the adjacent normal tissues (Fig. 1b). Furthermore, we used IHC analysis to determine the expression level and expression site of Daxx protein in the CRC tissues. Elevated levels of Daxx protein were found in the nuclei of the adenocarcinoma cells, as compared to that of the adjacent normal intestinal epithelium (Fig. 1c). Daxx expression was also assessed in non-tumorigenic colon cells and a panel of CRC cell lines by Western blotting. All CRC cell lines showed higher Daxx levels, especially HCT116 and HT29, compared to a human non-tumorigenic colon cell line CCD-18co (Fig. 1d). These results suggest that Daxx expression is significantly upregulated in sporadic CRC samples and CRC cell lines.

Fig. 1.

Fig. 1

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Suppression of Daxx expression reduces CRC neoplastic transformation. a Analysis of Daxx expression by RNA-seq from 28 pairs of matched normal colon tissue and sporadic CRC tissues using the TCGA data sets. b RT-qPCR analysis of Daxx and GAPDH expression from 15 pairs of matched normal colon and sporadic CRC tissues. c IHC analysis of Daxx expression in sporadic CRC samples. The right panel shows the magnification rectangle area. t: represents tumor part. n: represents normal part. d Western blotting of Daxx expression in a non-tumorigenic CCD18-co cell line and a panel of CRC cell lines. e, f Western and viability analyses of HCT116 and HT29 cells infected with indicated shDaxx. g Colony formation analysis of HT29 cells transfected with the indicated plasmids for 14-day selection and then stained with crystal violet. h Western and cell viability analyses of Daxx in Cas9-HCT116 and parental HCT116 cells. i Cell proliferation analysis of Cas9-HCT116 and HCT116 cells with EdU incorporation. j Xenograft studies of HT29 cells infected with indicated lentivirus and then injected subcutaneously into NOD/SCID mice. Left panel: Western blotting of the infected cells before injection. Middle panel: histogram showing the size of the tumors on 28 day after tumor cell injection. Right panel: representative photograph of the mice bearing tumors. The results are expressed as mean ± SD (n = 3–5; unpaired Student’s t test)

Suppression of Daxx expression reduces CRC cell growth

To test whether elevated Daxx expression contributes to CRC cell growth, we employed two Daxx-specific shRNAs to knockdown endogenous Daxx expression in HCT116 and HT29 cells for cell growth analysis (Fig. 1e). These two Daxx shRNAs have been extensively used to target Daxx mRNA in several studies [32, 33, 37]. Suppression of Daxx expression led to a significant decrease in cell viability and foci-forming activity of both cell lines (Fig. 1f and g). In addition, we also used CRISPR/Cas9 system to generate an isogenic HCT116 cell line with hemizygous loss of Daxx (Fig. S1). Similar to Daxx shRNA knockdown cells, this Cas9-HCT116 cell line with significant reduction in Daxx expression exhibited decreased levels of cell viability (Fig. 1h). In addition, this cell line yielded less EdU incorporation during cell proliferation (Fig. 1i). These results suggest a positive role of Daxx in cell growth control.

We further tested the effect of Daxx on cell growth by the mouse xenograft model. HT29 cells with Daxx knockdown were subcutaneously injected into NOD/SCID mice for tumor growth analysis. Notably, tumor formation of shDaxx#1-treated HT29 cells in the xenografted mice was significantly reduced, compared to mice xenografted with shLuc-treated cells (Fig. 1j). Collectively, these results suggest a role of Daxx in upregulation of CRC cell growth.

Daxx expression is positively regulated by PI3KCA

We next explored the molecular basis of Daxx expression increasing in CRC. The upregulation of Daxx expression in CRC could result from genomic amplification and/or tumorigenic pathway activation. To test these possibilities, we first analyzed Daxx genomic alteration in CRC using Cancer GEnome Mine and Catalogue of Somatic Mutations in Cancer database. However, we did not find any copy number gains in Daxx gene (data not shown). These data excluded the possibility of Daxx locus amplification in CRC.

We then investigated the association of Daxx expression with known hallmarks of CRC cellular pathways such as Wnt, TGF-β, PI3K, Ras/BRAF and p53. Previous reports showed that Wnt, TGF-β and p53 pathways did not activate Daxx expression [17, 18, 38]. We further tested whether PI3K or Ras/BRAF cellular pathways could alter Daxx expression. Interestingly, PI3KCA inhibitor PIK-75, but not BRAF inhibitor GDC-0879, significantly decreased Daxx mRNA expression in both HCT116 and HT29 cells (Fig. 2a, b, and S2, black line with open square), while both inhibitors effectively reduced cell viability of these two cell lines (red line with open square). We further confirmed the reduction of Daxx levels in PIK-75-treated cells by Western blot analysis (Fig. 2c). These results suggest that PIK3CA pathway positively regulates Daxx expression.

Fig. 2.

Fig. 2

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The PIK3CA/AKT pathway upregulates Daxx expression. a, b Cell viability and RT-qPCR analyses of HCT116 and HT29 cells treated with or without 200 nM PIK-75 at indicated the time points. c Western blotting of HCT116 and HT29 cells treated with or without 200 nM PIK-75 with Daxx and β-actin antibodies at the indicated time points. d, e RT-qPCR and immunoblotting analyses of HCT116 and HT29 cells transfected with 10 nM specific siRNA oligonucleotides against PIK3CA using RNAMAX. f RT-qPCR and immunoblotting analyses of CCD18-co cells transfected with indicated PIK3CA-Exon20 H1047R or PIK3CA-Exon9 E545K construct. g ChIP-qPCR analysis of HCT116 and HT29 cells transfected with control or PIK3CA siRNA. ChIP assays were performed with indicated antibodies, and qPCR was carried out with primers specific for a region encompassing the Daxx promoter. h, i ChIP-qPCR analysis of HCT116 and HT29 cells treated with PIK-75 for the indicated period of time and then subjected to ChIP assays with indicated antibodies and qPCR analysis using primers specific for the promoter region of Daxx or GAPDH. Input represents 1% of the chromatin used for immunoprecipitation. Error bars: mean ± SD (n = 3; one-way ANOVA)

To further demonstrate the function of PI3KCA in regulation of Daxx expression, we knocked down PIK3CA by siRNA and revealed that Daxx mRNA and protein levels were also decreased (Fig. 2d and e). As a control, PIK3CA knockdown reduced AKT phosphorylation (Fig. 2e, second panel). Since PIK3CA H1047R and E545K mutations could constitutively induce AKT hyperactivation, we then tested whether Daxx expression can be upregulated by these PIK3CA mutants. As expected, both PIK3CA mutants enhanced Daxx mRNA and protein levels in CCD18-co cells (Fig. 2f). These results further support the notion that PIK3CA pathway positively controls Daxx expression.

It is possible that PIK3CA-elicited Daxx expression in part via transcriptional activation. To this end, we performed ChIP analysis in both HCT116 and HT29 cells with or without siPIK3CA treatment. PIK3CA knockdown decreased the recruitment of active RNA polymerase II to Daxx promoter region in both HCT116 and HT29 cell lines (Fig. 2g). Similar observation was made with PIK-75-treated cells (Fig. 2h and i), while the PIK-75 treatment did not significantly alter the recruitment of active RNA polymerase II to the GAPDH promoter as a negative control. These results suggest that PIK3CA pathway-induced Daxx expression is at least mediated via Daxx transcriptional activation.

Positive correlation between PIK3CA and Daxx levels in sporadic CRC

The findings that Daxx expression was upregulated by PI3KCA in CRC cell lines led us to further test the correlation between Daxx and PIK3CA expression in clinical CRC samples. Analysis of TCGA data set revealed that Daxx expression is positively associated with PIK3CA expression in CRC tissues (Fig. 3a). Furthermore, IHC analysis revealed that PIK3CA-positive CRC tissues displayed increased Daxx levels, while PIK3CA-negative tissues showed decreased Daxx levels (Fig. 3b). These results suggest a positive correlation between Daxx and PIK3CA expression in CRC, which was further supported by the analysis of additional clinical samples (Fig. 3c).

Fig. 3.

Fig. 3

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A positive correlation of both Daxx and PIK3CA expression in clinical CRC samples. a Coexpression analysis of Daxx and PIK3CA in clinical CRC samples using TCGA data sets. b IHC analysis of CRC samples with serial sections with Daxx and PIK3CA antibodies. Intensity was quantified from the IHC image and scored for negative (low) or positive (high) expression (see “Materials and methods”). Scale bar, 200 um. c Regression analysis of a correlation between Daxx and PIK3CA levels in sporadic CRC specimens

Daxx promotes PIK3CA expression in CRC cells

The results of the positive correlation between Daxx and PIK3CA expression led us to further speculate that Daxx could upregulate PIK3CA expression in CRC cells. To this end, we knocked down Daxx expression and examined PIK3CA expression. Interestingly, shDaxx#1 treatment rendered a reduction of PIK3CA expression in HT29 cells, as evidenced by RT-qPCR and Western analyses, which was correlated with decreased phospho-AKT levels (Fig. 4a). We further validated these observations in the cellular context of mouse xenograft. HT29 cells stably expressing luciferase were first infected with lentivirus expressing shDaxx#1 or shGFP (a negative control) and then injected subcutaneously into NOD/SCID mice. To ensure the initial input of both xenograft cells were comparable, bioluminescence imaging based on the expression of luciferase was detected at 30 min after inoculation (Fig. 4a, left panel). In addition to the downregulation of PIK3CA and phospho-AKT (Fig. 4a, right panel), tumor growth activity was also decreased in the xenograft mice of the HT29 cells with Daxx knockdown (Fig. 4b, middle panel). Likewise, Daxx knockdown by CRISPR/Cas9 in HCT116 cells showed decreased levels of both PIK3CA and phospho-AKT (Fig. 4c). Conversely, Daxx overexpression in Cas9-HCT116 and CCD18-co cells increased PIK3CA expression and AKT phosphorylation (Fig. 4d and e). These results suggest that Daxx upregulates PIK3CA expression in CRC cells.

Fig. 4.

Fig. 4

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Daxx augments PIK3CA expression in CRC cells. a RT-qPCR and Western analyses of HT29 cells infected with lentivirus expressing indicated shRNAs. b Xenograft studies of luciferase-expressing HT29 cells infected with lentivirus expressing shDaxx#1 or shGFP (negative control). One million of these cells were injected subcutaneously into NOD/SCID mice and bioluminescence imaging based on the expression of luciferase was detected at 30 min after inoculation (left panel). This is to demonstrate the initial input of both xenograft cells were comparable. Histograms show tumor weight from individual tumor at day 36 post-subcutaneous injection (middle panel). Immunoblots show the expression of indicated proteins from xenograft tumors (right panel). c RT-qPCR and immunoblotting analyses of HCT116 cells and Cas9-HCT116 cells. d, e RT-qPCR and immunoblotting analyses of Cas9-HCT116 and CCD18-co cells transfected with indicated plasmids. f Relative cell viability of HCT116 and Cas9-HCT116 cells treated with different concentration of PIK-75. Error bars: mean ± SD (n = 3; unpaired Student’s t test)

If PIK3CA expression was upregulated by Daxx, Daxx knockdown should demand lower dose of the PIK3CA pathway inhibitor in blocking CRC cell growth. As expected, Cas9-HCT116 cells showed more sensitivity to PIK-75 treatment (IC50 = 19.79 nM), compared to the parental HCT116 cells (IC50 = 79.37 nM) (Fig. 4f). These results further validate that Daxx upregulates PIK3CA expression in CRC cells.

Daxx upregulates PIK3CA gene expression via promoter activation

Since Daxx is a transcription co-regulator [15, 16], it is possible that Daxx upregulates PIK3CA expression via enhancing promoter activity. To explore this possibility, we analyzed the activity of a reporter construct containing PIK3CA promoter sequences (− 2122 to + 482) fused to the luciferase reporter gene in HCT116 cells with Daxx knockdown or overexpression. As expected, Daxx knockdown and overexpression resulted in a decrease and an increase of reporter gene activity, respectively (Fig. 5a). Furthermore, ChIP analysis revealed that Daxx bound to various PIK3CA promoter regions (Fig. 5b). Among them, Daxx robustly bound to segment 1 (− 2000 ~ − 1741) of PIK3CA promoter compared to other segments (Fig. 5b). Domain mapping study further showed that Daxx C-terminal 570–740 fragment, but not N-terminal 1–625 fragment, could be recruited to PIK3CA promoter region (Fig. 5c). In line with these results, Daxx C-terminal 570–740 fragment enhanced the reporter activity and expression level of PIK3CA, while its N-terminal 1–625 fragment failed to do so (Fig. 5d and e). These results provide a nice causal correlation between Daxx recruitment to PIK3CA promoter region and upregulation of PIK3CA promoter activity and gene expression. Taken together, our findings suggest that Daxx positively regulates PIK3CA gene expression in CRC cells.

Fig. 5.

Fig. 5

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Daxx could activate PIK3CA promoter activity. a Reporter gene analysis of HCT116 cells transfected with PIK3CA luciferase reporter along with indicated plasmids. Firefly and Renilla luciferase activities were determined 48 h post-transfection. Results are expressed as a relative ratio of Firefly to Renilla luciferase activity, relative to the ratio of control cells which was given a value of 1. Western blot shows the expression levels of indicated proteins in cell lysates. b, c ChIP and Western analyses of endogenous Daxx in HCT116 cells (b) or Cas9-HCT116 cells expressing indicated HA-Daxx proteins c with Daxx or HA antibody, respectively. qPCR analysis was carried out by primers specific for PIK3CA promoter. Input represents 1% of the chromatin used for IP. Western blots show the expression of immunoprecipitated proteins from HCT116 and Cas9-HCT116 cells with indicated antibodies. d Reporter activity and Western blotting of Cas9-HCT116 cells transfected with PIK3CA luciferase reporter along with indicated HA-Daxx wild-type or mutant plasmids. e RT-qPCR and immunoblotting analyses of Cas9-HCT116 cells expressing HA-Daxx wild-type or mutant proteins. The results are expressed as mean ± SD (n = 3; unpaired Student’s t test)

Discussion

In the present study, we reported that Daxx expression is increased in CRC clinical samples and cell lines. We further identified PI3K cellular pathway in regulating Daxx expression by the results that inhibition of PIK3CA activity or expression could attenuate Daxx expression in CRC cells. On the other hand, depletion of Daxx significantly reduced PIK3CA expression and AKT activation in CRC cells. Furthermore, Daxx could activate PIK3CA promoter activity through the recruitment of Daxx to the promoter region of the PIK3CA gene. Together, these results suggest a positive feedback regulatory loop between PIK3CA and Daxx in CRC cells. A positive correlation between PIK3CA and Daxx expression in sporadic CRC cancer tissues further supports this notion.

Several reports indicated that Daxx levels are elevated in various cancer types including prostate cancer, myelodysplastic syndrome, bladder cancer, esophageal squamous cell carcinoma, oral squamous cell carcinoma and ovarian cancer [21–26, 28, 39–41]. However, the molecular basis as to how Daxx expression is increased in these cancers remains unknown. Our findings that PIK3CA/AKT pathway promotes Daxx expression in CRC cells led to a possible scenario that Daxx levels are upregulated by PIK3CA in these cancers. Indeed, our analysis of TCGA data sets revealed that Daxx expression is correlated with PIK3CA expression in prostate cancer, bladder cancer, esophageal cancer and ovarian cancer (Fig. S3). Such coexpression patterns in various cancer types further support the reciprocal regulation of PIK3CA and Daxx expression.

Previous studies reported that PIK3CA gain-of-function mutations constitutively drive PI3K signaling in cancer progression [8]. In addition, several activators of PI3K signaling are mutated or overexpressed in cancer, such as mutations of EGFR, Ras and overexpression of ERBB2 [42]. Notably, some of these mutated genes or overexpressed proteins frequently coexist with PIK3CA mutations [42]. For instance, K-ras mutations and PIK3CA mutations occur concomitantly in some colorectal cancer [43]. ERBB2 overexpression associates with PIK3CA mutations in breast cancer [44]. Such co-occurring mutations or overexpression likely further augment cancer cell transformation [45]. Given that PIK3CA mutations occur in CRC at frequencies ranging from 13 to 28% [46] and that Daxx and PIK3CA reciprocally enhance each other’s expression, it is very likely that Daxx overexpression and PIK3CA mutations coexist in CRC. Indeed, three CRC cell lines with PIK3CA mutations (P449T in HT29 cells, H1047R in HCT116 cells, and E545K and D549N in HCT-15 cells) showed elevated Daxx levels, as compared to other four CRC cell lines harboring PIK3CA wild type (Colo205, HCC-2998, SW620 and KM12 cells) (Fig. 1d). In addition, expression of PIK3CA with E545K or H1047R mutation enhanced Daxx expression in CCD18-co cells (Fig. 2f). These findings suggest an association of PIK3CA mutations and Daxx overexpression in CRC cells. Further study is required to validate such an association in clinical CRC tissues.

The molecular basis as to how Daxx enhances PIK3CA expression in CRC cells is currently unknown. An increment of Daxx occupancy in PIK3CA -2000 to -1741 region (Fig. 5b) raised a possible scenario that Daxx binds to this region via interacting with certain transcription factor(s). We dissected the potential binding sites of transcription factors within this region by in silico analysis, and found that only NF-κB binding site was predicted in this region (data not shown). Since the interaction between Daxx and NF-κB has been reported [47], further studies are needed to clarify which transcription factor is required for Daxx in activating PIK3CA expression. Nevertheless, our current findings suggest that Daxx is a novel factor in regulating PIK3CA gene expression.

While the regulation of PIK3CA expression by Daxx could contribute to the oncogenic function of Daxx in CRC, it should be noted that Daxx could also enhance β-catenin/TCF4-mediated transcriptional activity and repress Smad4-mediated transactivation in various cancer cell lines [17, 38]. Furthermore, Daxx negatively regulates p53 levels via its interaction with USP7 to increase Mdm2 stability [18]. Given that these pathways (β-catenin, Smad4, p53 and PIK3CA) are associated with CRC progression [4], these findings suggest that Daxx exerts its oncogenic function in CRC via multiple cellular pathways (Fig. 6). Given that the PIK3CA-dependent AKT activation is a common feature in CRC, whether the upregulation of Daxx expression by PIK3CA could have an impact on these CRC-associated network pathways remains to be explored. In summary, our study elucidates a previously undescribed reciprocal regulation between PIK3CA and Daxx in CRC.

Fig. 6.

Fig. 6

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A hypothetical model of the PIK3CA/Daxx positive feedback regulatory loop with cellular pathways regulated by Daxx in CRC. a PIK3CA and Daxx form a positive feedback regulatory loop. b Daxx could activate β-catenin/TCF4 target gene expression via TCF4 interaction. c Daxx stabilizes MDM2 by interacting with USP7, which increases p53 degradation. d Daxx represses Smad4-mediated gene expression via its interaction with SUMO-modified Smad4. TF transcription factor, S SUMO modification, Ub ubiquitination

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 2963 KB) (2.9MB, doc)

Acknowledgements

We thank Dr. Chi-Jung Huang and Mrs. Hsiao-Ting Tseng for CCD18-co cells, Dr. Noriyuki Tsumaki for PIK3CA reporter construct, Dr. Scott Lowe for MSCV Luciferase PGK-hygro plasmid, Dr. Feng Zhang for pX330 construct and Dr. Bert Vogelstein for PIK3CA H1047R and E545K plasmids, respectively. We are grateful to Dr. Shun-Yuan Jiang, Dr. Po-Hsun Tu, Dr. Wei-Chih Yang, and Mr. Pei-Hsiang Hou for their excellent technical support.

Author contributions

Conceptualization: YSH, CCW, and HMS; performing experiments: YSH, CCC, and HYK; data analysis: CCW and SFH; drafting and editing YSH and HMS.

Funding

This work was supported by grants from the Ministry of Science and Technology (MOST 110-2327-B-001-001 and 108-2320-B-001-035-MY3), Taiwan.

Availability of data and material

The data presented in this study are available from the corresponding author on reasonable request.

Declarations

Conflict of interest

The authors have declared that they have no conflict of interests.

Ethical approval

The questionnaire and methodology for this study were approved by the Human Research Ethics committee of the Tri-Service General Hospital (Ethics approval number: 098-05-292). All animal handling was approved by the Ethical Committee on Animal Experiments, Academia Sinica, Taiwan (IACUC-approved ptotocol#2009-018).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

The participant has consented to the submission of these research findings to the journal.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Yen-Sung Huang, Email: yshuang@ibms.sinica.edu.tw.

Hsiu-Ming Shih, Email: hmshih@ibms.sinica.edu.tw.

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Associated Data

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Supplementary Materials

Supplementary file1 (DOC 2963 KB) (2.9MB, doc)

Data Availability Statement

The data presented in this study are available from the corresponding author on reasonable request.

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