Abstract Osteosarcoma is a kind of primary malignant bone tumor with the highest incidence and an extraordinarily poor prognosis and early pulmonary metastasis formation as a frequent occurrence. Transcriptional positive coactivator 4 (PC4) has multiple functions in DNA replication, transcription, repair and chromatin organization, even in tumorigenesis. However, the precise function of PC4 in osteosarcoma is still unclear and controversial. In this paper we found PC4 was upregulated in patient-derived osteosarcoma tissues compared to normal. Moreover, higher expression of PC4 was correlated with poorer overall survival and advanced clinicopathological tumor staging. Down regulation of PC4 in the highly metastatic osteosarcoma cells reduced the malignant behaviors in vitro and in vivo. Analyzing the downstream genes affected obviously by shPC4 with RNA sequencing, we found knocking down PC4 will inhibit the propensity for lung metastasis through transcriptional suppression of MMPs pathways. Taken together, PC4 may be an attractive therapeutic strategy for osteosarcoma, especially in preventing lung metastasis formation. Keywords: PC4, SP1, MMP, pulmonary metastasis INTRODUCTION Approximately 20% of osteosarcoma patients exhibit lung metastasis when diagnosed, while an additional 40% develop lung metastasis in advanced stages, which correlates with poor 5-year survival rates [[46]1]. Despite intense efforts to characterize the genomic patterns of osteosarcoma, effective therapeutic targets and diagnostic markers are still in urgent need [[47]2]. The purpose of this paper is to find a possible therapeutic target for osteosarcoma. Positive coactivator 4 (PC4) is a highly conserved DNA-binding nuclear protein and is involved in distinct DNA-dependent processes, such as DNA repair, replication, and transcription [[48]3–[49]6]. Previously, we reported that PC4 was a novel oncogenic gene whose overexpression accompanied with the malignant transformation of dermis-derived mesenchymal stem cells [[50]7, [51]8]. PC4 was found to highly expressed in human prostate stromal cells at the embryonic stage and declined to significantly lower levels by adulthood, while elevated in prostate cancer associated stroma [[52]7]. As osteosarcoma is believed to originate from mesenchymal cells, we sought to evaluate the potential function of PC4 in osteosarcoma tumorigenesis and pulmonary metastasis. In this context, it has been demonstrated that high PC4 expression in osteosarcoma correlates with poor prognosis, and suppression of PC4 blocked the pulmonary metastasis by reducing malignancy phenotype through transcriptional level depression of MMP9. Our findings imply that PC4 may be an effective potential therapeutic gene to inhibit osteosarcoma tumorigenesis and prevent lung metastasis. RESULTS High PC4 expression in osteosarcoma correlates with poor patient prognosis We analyzed 5 osteosarcoma tissues and adjacent normal counterparts by western-blot, PC4 was differentially overexpressed in osteosarcoma (Figure [53]1C). To confirm this, immunohistochemistry staining was performed in additional patient-derived paraffin-embedded osteosarcoma samples (n=82) and tissue microarray sections (n=116) and compared to normal bone tissues of healthy controls (n=44). The average staining score in osteosarcoma was significantly higher than normal tissues (7.2±0.26 vs 2.8±0.39, p<0.01, Figure [54]1B), and PC4 staining localized primarily to the nucleus (Figure [55]1A). The data gathered in this part implied that PC4 was increased in osteosarcoma. Figure 1. Increased expression of PC4 protein in osteosarcoma tissues. Figure 1 [56]Open in a new tab (A) Immunohistochemical staining of PC4 expression in osteosarcoma. PC4 was mainly located in cell nucleus. (B) Average immnohistochemical staining scores of PC4 expression from 198 osteosarcoma tissues and 44 adjacent normal tissues. PC4 was highly expressed in osteosarcoma. (*p < 0.01). (C) Western blotting analysis of PC4 expression of 5 osteosarcoma patients (A1-A5) and the adjacent normal tissues (T1-T5). (D) Immnohistochemical staining analysis of PC4 expression in different pathological stages. IIA group was higher than IB group (*p < 0.05), III group was higher than IIA group (**p < 0.05). (E) Statistical analysis of correlation between PC4 expression level and the survival of osteosarcoma patients (PC4^+, n=43; PC4^−, n=16; p < 0.01) (Kaplan-Meier survival curves). Then we compared immunohistochemical staining across tumors of different clinical staging. Greater PC4 expression in advanced stage tumors was found (Figure [57]1D). High PC4 expression was detected in 160 of 198 cases and it was correlated with staging and tumor size (Table [58]1). Interestingly, the prevalence of PC4 positivity was higher in patients with pulmonary metastasis (Enneking stage III, 85%) compared to total (80%), suggesting PC4 might be involved in osteosarcoma metastatic potential. Table 1. Relationship between PC4 expression and clinicopathological characteristics of osteosarcoma patients. PC4 p Low or none High Total osteosarcoma patients 38 160 Sex >0.05  Male 15 71  Female 23 89 Age >0.05  < 40 25 125  ≥ 40 13 35 Enneking stages <0.01  IA 4 5  IB 11 15  IIA 5 22  IIB 15 101  III 3 17 Tumor size <0.01  ≤ 8 cm 21 51  > 8 cm 17 109 [59]Open in a new tab Follow-up data were available from 59 patients. Statistically difference in survival was found between the PC4 positive group (n=43) and the PC4 low or negative group (n=16) (p<0.05) (Figure [60]1F). Association of PC4 with clonogenicity and tumorigenicity of osteosarcoma cell lines To characterize the functional relevance of increased PC4 expression in osteosarcoma, we performed further experiments in vitro in seven osteosarcoma cell lines. Immunofluorescent staining for PC4 demonstrated prominent nuclear localization and exhibited greatest intensity in 143B and MNNG-HOS cells (Figure [61]2A). Western-blotting and real-time PCR confirmed these findings, demonstrating highest PC4 expression in 143B and MNNG-HOS cells, moderate PC4 levels in MG63 and U2OS cells, and lowest PC4 expression in HOS, SAOS2, and 9901 cells (Figure [62]2B). Clonogenicity assays demonstrated greatest sphere formation in 143B cells, followed by moderate formation in MNNG-HOS, MG63, and 9901 cells, and lowest formation in HOS, U2OS, and SAOS2 cells (Figure [63]2C). Likewise, 143B and MNNG-HOS cells exhibited greatest tumorigenicity in xenografted mouse models, while MG63 and 9901 cells had lower tumorigenicity; HOS xenografts did not develop visible tumors in our experiment (Figure [64]2D). Based on these results, 143B cells were selected for further research, based on the elevated PC4 levels and high potential for lung metastases [[65]9, [66]10]. These results indicated that PC4 expression was possibly related to clonogenicity in vitro and tumorigenicity in vivo. We also found that 143B cells had the highest expression of MMP-9, which may have been related to the propensity for lung metastases, observed in 143B cells. Compared to other osteosarcoma cell lines, mRNA levels of P53 were extraordinary low in 143B cells (Figure [67]2G-2J). Figure 2. Expression of PC4 in osteosarcoma cells and malignant phenotype of different osteosarcoma cell lines. Figure 2 [68]Open in a new tab (A) Immunofluorescent staining of PC4. PC4 (red), DAPI (blue). (B) Western blotting analysis of PC4 expression level in seven osteosarcoma cell lines. GAPDH served as control. (C, D) Spheroid development in semisolid soft agar medium after 7 days, which cells were grown in six-well plates with triple replications. (E, F) Tumorigenicity of five osteosarcoma cell lines. Grow for 5 weeks in nude mice (n=3 mice in each group). Mice were injected with 5*10^6 cells. All the cells developed a visible tumor except HOS group. (G-J) Quantitative RT-PCR test of PC4 and malignant phenotype related genes in different osteosarcoma cell lines (*comparing with 143B p<0.05). Knockdown of PC4 further decreases the malignancy of 143B cells To further investigate the role of PC4 in the malignancy of 143B cells, PC4 was silenced in 143B utilizing lentivirus shRNA. Stably transfected 143B^PC4− cells were obtained, which PC4 expression level was maintained at 30% comparing with the parental cells (Figure [69]3A). Figure 3. Stable knockdown of PC4 and the accompanied malignant phenotype change. Figure 3 [70]Open in a new tab (A) Western blotting analysis of PC4 knockdown efficiency in 143B cells. (B) Cell proliferation assays show slight inhibition by lv-shRNA-PC4 (*p<0.01). (C) Cell cycle distribution of 143B cells with lv-shRNA transfection (*p<0.05). (D) Cell attachment assay. 2*10^4 cells were seeded into 96-well culture plates, and incubated at 37°C for 30 min or 60 min or 120min or 24 hours. After incubation, unattached cells were washed with PBS, and adherent cells were counted with CCK-8 kits, (*p<0.01). (E, F) Spheroid development in semisolid soft agar medium after 7 days. 143B showed decreased efficiency of sphere-forming in 143B^PC4−group. Spheres were counted in five random fields of vision. (G) Invasion assay. 143B cells seeded on the upper chamber with pre-coated matrigel for 24 hours. Cells on the underside of the membrane were fixed, stained with crystal violet. (H, I) Effect of lv-shRNA-PC4 on 143B cell migration by wound-healing assay. The 143B cells were seeded in 6-well plates for 24h, after cell reached 100% density wounds were created. Cell migration was observed at 0h, 24h, 48h, and 72h after wounding. The migration distance was calculated as the width at indicated time (*p<0.05 versus control). Cell proliferation was decreased after PC4 knockdown (Figure [71]3B). In 143B^PC4− group, the percentage of cells in G1 phase increased (p<0.05) while those in S phase decreased but there was no significant difference, the data suggested down regulation of PC4 in 143B cells induces G1-phase arrest (Figure [72]3C). The 143B^PC4− group showed slower adherent speeds at 30min, 60min and 120min (Figure [73]3D). Likewise, 143B^PC4− cells showed decreased colony formation ability (Figure [74]3E, 3F). Transwells suggested that shPC4 may reduce the invasion of 143B (Figure [75]3G). Scarification test results demonstrated that migration potential was inhibited in 143B^PC4− cells (Figure [76]3H, 3I). Down regulation of PC4 in 143B cells suppresses tumor growth in vivo and development of pulmonary metastases Mean tumor sizes in the parental 143B group, mock-transfected 143B group, and 143B^PC4− group were 1 519±620 mm^3, 1 390±504 mm^3, and 525±333 mm^3, respectively (means±SD, P<0.05; Figure [77]4A, 4B). The respective weights of the tumors were 1.52±0.77 g, 1.30±0.73 g, and 0.40±0.23 g (means±SD, P<0.05; Figure [78]4D). These data suggested that the growth might be suppressed in 143B^PC4− in vivo without affecting body weight. Figure 4. Tumorigenicity of osteosarcoma cells with stable knockdown of PC4. Figure 4 [79]Open in a new tab (A) Excised all tumors in nude mice at day 27 when the biggest tumor volume reach 2000 mm^3. (B) Tumor volume of 143B xenografts. 143B^PC4− group had a regression compared with control (*P<0.05). (C) Body weight of nude mice. (D) Excised Tumor weight (*P<0.05). (E) Excised lung in nude mice when tumor volume reach 2000 mm^3. Photographs of lungs of each group. Arrow shows the metastasis. Representative lungs H&E staining of each group. (F) Visible lung metastasis number of each group (*P<0.05). To determine the role of PC4 in pulmonary metastasis in osteosarcoma, and to avoid the effect on proliferation, another 15 nude mice were used. Lungs were excised when tumors reached 2 000mm^3. Both the rate of pulmonary metastasis and the number of visible metastases in the 143B^PC4− group were dramatically reduced (Figure [80]4E, 4F). Diagnoses of metastatic nodules were confirmed by H&E stains. RNA-seq analysis reveals diminished MMP expression after PC4 knockdown We utilized RNA-seq to explore the molecular alterations after PC4 interference in 143B cells. In total, 12562108 reads were obtained in 143B cells and 129963468 reads were obtained in 143B^PC4− cells. We mapped 87.63% of the reads to the human reference genome (hg18) in 143B cells and 88.06% in 143B^PC4−cells. In comparison with 143B cells, 572 genes were increased and 513 genes were decreased in 143B^PC4− cells. Top 10 up and down represented genes were shown (Table [81]2). CXCL1, MMP9, IL1B, WNT7A, and CCL2 were associated with cancer malignant characteristics which were remarkably decreased in Top 10 list. MMP9 (log[2]Ratio=-8.19), MMP2 (log[2]Ratio=-1.02) and FN (log[2]Ratio=-3.99) were downregulated in 143B^PC4− cells, which were strongly associated with metastasis and had reciprocal actions. KEGG pathway of enrichment analysis of differentially expressed genes was performed, and the top 20 pathway enrichments for 143B^PC4− cells were shown, comparing with all genes with pathway annotation, pathways which P<0.05 were listed (Table [82]3). Gene ontology functional classification of differentially expressed genes was analyzed, cluster frequency comparing with genome frequency, corrected P<0.05 were listed (Table [83]4). Table 2. Top 10 up- and down- represented genes after PC4 knocking down in 143B cell. Gene GeneID Description log2 Ratio Gene_length P-value FDR DRD5 1816 Dopamine receptor D5 7.80382017 2398 2.67E-13 2.84E-12 INHBE 83729 Inhibin, beta E 6.757445414 2453 1.22E-61 6.70E-60 CTH 1491 Cystathionase (cystathionine gamma-lyase) 6.182881406 2140 0 0 FAM90A1 55138 Family with sequence similarity 90, member A1 6.07740762 2516 0.000102221 0.000435026 MEIS1-AS3 730198 An RNA Gene, and is affiliated with the non-coding RNA class. 5.915134907 4115 1.48E-06 8.22E-06 LGR6 59352 Leucine-rich repeat containing G protein-coupled receptor 6 5.825052551 3458 2.49E-05 0.000117228 MKX 283078 Mohawk homeobox 5.736785943 3658 3.16E-15 3.88E-14 ESRP1 54845 Epithelial splicing regulatory protein 1 5.480263981 3806 0.000102221 0.000434922 ATF3 467 Activating transcription factor 3 4.908885316 2400 6.00E-127 7.54E-125 CHAC1 79094 ChaC, cation transport regulator homolog 1 (E. coli) 4.469583903 1578 1.31E-248 4.56E-246 CXCL1 2919 Chemokine (C-X-C motif) ligand 1 −10.12824838 1207 4.70E-32 1.28E-30 KRT75 9119 Keratin 75 −8.365650472 2125 5.59E-17 7.69E-16 SERPINA3 12 Serpin peptidase inhibitor, clade A −8.215694509 1629 5.93E-12 5.67E-11 MMP9 4318 Matrix metallopeptidase 9 −8.197914746 2387 5.59E-17 7.69E-16 IL1B 3553 Interleukin 1, beta −8.158410629 1498 2.60E-169 5.12E-167 WNT7A 7476 Wingless-type MMTV integration site family, member 7A −7.923708789 1732 1.78E-10 1.51E-09 STRA6 64220 Stimulated by retinoic acid gene 6 homolog (mouse) −7.923525266 3097 3.68E-18 5.42E-17 CCL2 6347 Chemokine (C-C motif) ligand 2 −7.664093493 760 3.47E-60 1.84E-58 BCHE 590 Butyrylcholinesterase −7.620436455 2461 5.93E-12 5.66E-11 NAP1L3 4675 Nucleosome assembly protein 1-like 3 −7.454490225 2761 5.93E-12 5.66E-11 [84]Open in a new tab Table 3. KEGG pathway enrichment analysis of different express genes. Pathway DEGs withpathwayannotation(906) All geneswith pathwayannotation(17252) P-value Q-value Pathway IDof KEGG p53 signaling pathway 23 (2.54%) 143 (0.83%) 1.52172E-06 0.000413907 ko04115 Axon guidance 34 (3.75%) 308 (1.79%) 3.53746E-05 0.004810942 ko04360 Isoquinoline alkaloid biosynthesis 6 (0.66%) 16 (0.09%) 0.000104847 0.009506101 ko00950 Glycine, serine and threonine metabolism 12 (1.32%) 71 (0.41%) 0.0002982 0.019414805 ko00260 Tropane, piperidine and pyridine alkaloid Biosynthesis 5 (0.55%) 13 (0.08%) 0.00035689 0.019414805 ko00960 Malaria 12 (1.32%) 76 (0.44%) 0.000568131 0.025755258 ko05144 Fatty acid biosynthesis 5 (0.55%) 15 (0.09%) 0.000762581 0.029631699 ko00061 Tyrosine metabolism 12 (1.32%) 81 (0.47%) 0.001018911 0.034642974 ko00350 Phenylalanine metabolism 7 (0.77%) 33 (0.19%) 0.001383711 0.041818821 ko00360 MAPK signaling pathway 36 (3.97%) 425 (2.46%) 0.003285155 0.083304921 ko04010 Legionellosis 13 (1.43%) 105 (0.61%) 0.003368949 0.083304921 ko05134 Alanine, aspartate and glutamate metabolism 8 (0.88%) 57 (0.33%) 0.009438303 0.213934868 ko00250 Neurotrophin signaling pathway 22 (2.43%) 248 (1.44%) 0.01151266 0.240880271 ko04722 Cytokine-cytokine receptor interaction 26 (2.87%) 317 (1.84%) 0.01654431 0.300741515 ko04060 Methane metabolism 7 (0.77%) 51 (0.3%) 0.01658501 0.300741515 ko00680 NOD-like receptor signaling pathway 14 (1.55%) 144 (0.83%) 0.01932437 0.315335493 ko04621 Measles 17 (1.88%) 188 (1.09%) 0.02056757 0.315335493 ko05162 Cocaine addiction 10 (1.1%) 91 (0.53%) 0.02086779 0.315335493 ko05030 Vitamin B6 metabolism 3 (0.33%) 12 (0.07%) 0.02223889 0.318367267 ko00750 Carbon fixation in photosynthetic organisms 5 (0.55%) 32 (0.19%) 0.02445567 0.332597112 ko00710 ECM-receptor interaction 22 (2.43%) 269 (1.56%) 0.02667029 0.345443756 ko04512 Rheumatoid arthritis 11 (1.21%) 115 (0.67%) 0.0392752 0.485584291 ko05323 [85]Open in a new tab Table 4. Gene ontology functional classification of differentially expressed genes. Gene Ontology term Cluster frequency Genome frequency of use Corrected P-value Molecular function Protein binding 299 out of 837 genes, 35.7% 4282 out of 15165 genes, 28.2% 0.00026 Binding 710 out of 837 genes, 84.8% 12079 out of 15165 genes, 79.7% 0.0168 Cellular component Cell junction 37 out of 858 genes, 4.3% 351 out of 16090 genes, 2.2% 0.01023 Extracellular matrix 33 out of 858 genes, 3.8% 312 out of 16090 genes, 1.9% 0.0488 Biological process Locomotion 91 out of 811 genes, 11.2% 838 out of 14596 genes, 5.7% 6.13E-07 Anatomical structure development 232 out of 811 genes, 28.6% 2997 out of 14596 genes, 20.5% 1.73E-05 Response to chemical stimulus 163 out of 811 genes, 20.1% 1934 out of 14596 genes, 13.3% 2.28E-05 Developmental process 262 out of 811 genes, 32.3% 3517 out of 14596 genes, 24.1% 4.81E-05 Cell motility 62 out of 811 genes, 7.6% 538 out of 14596 genes, 3.7% 5.36E-05 Localization of cell 62 out of 811 genes, 7.6% 538 out of 14596 genes, 3.7% 5.36E-05 Response to external stimulus 81 out of 811 genes, 10.0% 787 out of 14596 genes, 5.4% 6.90E-05 Cellular component movement 62 out of 811 genes, 7.6% 568 out of 14596 genes, 3.9% 0.00038 Response to lipid 47 out of 811 genes, 5.8% 382 out of 14596 genes, 2.6% 0.00038 Multicellular organismal development 204 out of 811 genes, 25.2% 2681 out of 14596 genes, 18.4% 0.00075 Positive regulation of biological process 135 out of 811 genes, 16.6% 1642 out of 14596 genes, 11.2% 0.00215 Cell migration 49 out of 811 genes, 6.0% 431 out of 14596 genes, 3.0% 0.00226 System development 184 out of 811 genes, 22.7% 2407 out of 14596 genes, 16.5% 0.00252 Signaling 281 out of 811 genes, 34.6% 3999 out of 14596 genes, 27.4% 0.003 Response to stimulus 351 out of 811 genes, 43.3% 5195 out of 14596 genes, 35.6% 0.00318 Single-organism developmental process 153 out of 811 genes, 18.9% 1940 out of 14596 genes, 13.3% 0.00433 Anatomical structure morphogenesis 106 out of 811 genes, 13.1% 1236 out of 14596 genes, 8.5% 0.00554 Response to oxygen levels 9 out of 811 genes, 1.1% 25 out of 14596 genes, 0.2% 0.00701 Response to organic substance 99 out of 811 genes, 12.2% 1141 out of 14596 genes, 7.8% 0.00736 Positive regulation of cellular process 114 out of 811 genes, 14.1% 1364 out of 14596 genes, 9.3% 0.00772 Cell proliferation 77 out of 811 genes, 9.5% 836 out of 14596 genes, 5.7% 0.01147 Cellular developmental process 135 out of 811 genes, 16.6% 1706 out of 14596 genes, 11.7% 0.01616 Anatomical structure formation involved in morphogenesis 48 out of 811 genes, 5.9% 450 out of 14596 genes, 3.1% 0.01683 Biological regulation 421 out of 811 genes, 51.9% 6523 out of 14596 genes, 44.7% 0.0206 Intracellular signal transduction 96 out of 811 genes, 11.8% 1125 out of 14596 genes, 7.7% 0.02067 Regulation of metabolic process 198 out of 811 genes, 24.4% 2717 out of 14596 genes, 18.6% 0.0225 Enzyme linked receptor protein signaling pathway 66 out of 811 genes, 8.1% 698 out of 14596 genes, 4.8% 0.02319 Response to organic cyclic compound 44 out of 811 genes, 5.4% 405 out of 14596 genes, 2.8% 0.02487 Response to molecule of bacterial origin 23 out of 811 genes, 2.8% 157 out of 14596 genes, 1.1% 0.02983 Chemotaxis 44 out of 811 genes, 5.4% 408 out of 14596 genes, 2.8% 0.02987 [86]Open in a new tab Down regulation of PC4 inhibits the transcription of MMP9 through the synergy with SP1 In various osteosarcoma cells, PC4 knockdown reduced MMP9 and MMP2 mRNA levels, compared to each parental cell respectively (Figure [87]5A1-5A4). RNA-seq data showed fibronectin and MMP9 and MMP2 were reduced in 143B^PC4− cells. As both exogenously added fibronectin and endogenous up-regulation of fibronectin can result in an increase in MMPs according to the references [[88]11–[89]13], we infer PC4 might