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. 2022 Jun 7;17(6):e0269094. doi: 10.1371/journal.pone.0269094

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signaling pathway

Fei Lu 1, Shuran Chen 1, Weijun Shi 1, Xu Su 2, Huazhang Wu 2,*, Mulin Liu 1,*
Editor: Hamidreza Montazeri Aliabadi3
PMCID: PMC9173621  PMID: 35671267

Abstract

In this study, we analyzed GPC family genes in colorectal cancer (CRC) and the possible mechanism of action of GPC1 in CRC. CRC patient data were extracted from The Cancer Genome Atlas, and the prognostic significance of GPC1 expression and its association with clinicopathological features were identified by Kolmogorov–Smirnov test. CRC patients with high GPC1 expression had poor overall survival compared with patients with low GPC1 expression. In vitro experiments demonstrated that knockdown of GPC1 significantly inhibited the proliferation and migration and promoted cell apoptosis in CRC cell lines. Gene Ontology analysis of differential genes indicated that GPC1 may influence the TGF-β1 signaling pathway. Additional experiments revealed that silencing GPC1 suppressed the levels of TGF-β1 and p-SMAD2 but increased the expression of SMAD2. Taken together, these findings suggest that GPC1 may function as a tumor promoter in CRC cells through promoting TGF-β signaling pathway. Our results also indicate that GPC1 may serve as a critical effector in CRC progression and a new potential target for CRC therapy.

Introduction

Colorectal cancer (CRC) is one of the most common cancers in the United States, with an estimated 147,950 and 53,200 new cases and deaths each year, respectively [1]. In 2015, an estimated 376,300 cases and 150,000 deaths occurred in China [2]. Approximately 20% of patients with CRC have metastatic CRC [3], and 40% of CRC patients exhibit recurrence after treated localized disease [4]. The prognosis of metastatic CRC is poor, with a 5-year survival rate of less than 20% [3]. Therefore, the identification of new markers and novel treatment methods for CRC is critical.

Glypicans (GPCs) are a family of heparan sulfate proteoglycans (HSPGs) that interact with the plasma membrane through a glycosylphosphatidyl inositol anchor [5]. In humans, six GPC family members have been identified, including GPC1, GPC2, GPC3, GPC4, GPC5 and GPC6 [6]. Melo et al. studied GPC1 expression in the peripheral blood of 190 patients with pancreatic ductal adenocarcinoma and 100 healthy volunteers and found that GPC1 was highly expressed in patients with cancer compared with the healthy volunteers; furthermore, larger tumors showed a higher positive rate of GPC1. Li et al. found that GPC1 regulates the occurrence of esophageal cancer through the PTEN/Akt/β-catenin signaling pathway [7]. In addition, the authors found that GPC1 can be used as a biomarker for the recurrence of stage III CRC, and GPC1 may be involved in EMT activation, invasion and migration of CRC cells [8]. Further studies revealed the increased expression of GPC1 in prostate cancer, endometrial cancer, lung cancer and other cancers [9–11]. However, the mechanism by which GPC1 regulates the occurrence and progression of CRC is still unclear.

In this study, we analyzed the influence of GPC family proteins in CRC and the possible mechanism of action. Our findings indicate that GPC1 expression was associated with prognosis in CRC patients and reveal that GPC1 promotes the TGF-β signaling pathway in CRC cells.

Materials and methods

Patients and specimens

Between January and February 2022, we collected 4 pairs of cancer and paracarcinoma tissues from patients with CRC at the Gastrointestinal Surgery Department of the First Affiliated Hospital of Bengbu Medical College. Our study was approved by the ethics committee of Bengbu Medical College. We obtained informed consent from every patient. All specimens were stored at − 80°C.

Data source

The expression profiles and clinicopathological data of CRC and non-tumor tissues were obtained from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/) [12]. The inclusion criteria for clinical information were set as follows: (1) patients had complete clinical information; and (2) the follow-up time of samples exceeded 30 days.

Analysis of TCGA mRNA profiles

We used the “limma” package to identify differentially expressed mRNAs between 473 CRC tissues and 41 non-tumor tissues from TCGA (|FDR|>1, P<0.05) [13]. The Kaplan–Meier method was used for univariate analysis, followed by log-rank test for assessing the differences of overall survival (OS) among different groups (P<0.05). Next, we assessed the correlation between GPC1 and clinicopathological information using Kolmogorov–Smirnov test (P<0.05). Finally, we identified the GPC1-related genes using Pearson’s correlation test (P<0.05, |R|>0.5). The STRING database (https://string-db.org/), a publicly available comprehensive resource, was used to predict the relationships between target genes.

Functional enrichment analysis

Gene Ontology (GO) enrichment analysis was performed using “clusterProfiler” package in R (4.1.0), and the “org.Hs.eg.db” package was used as the reference data. The P value was corrected by the Benjamin–Hochberg method, with a P value <0.05 and a q value <0.05 being the cut-off criteria.

Immunohistochemistry

Colorectal cancer and paracarcinoma tissues were dewaxed in xylene and rehydrated through different gradients of alcohol. Then, we placed paraffin in 3% H2O2 for 15 min at 22°C. Next, the slide was heated in citrate buffer. After washing several times with PBS (pH   =  7.2), the slide was placed into the solution with a primary antibody against GPC1 (dilution 1:200, 16700-1-AP, Proteintech, China) at 4°C for more than 12 h. Then, we added secondary antibody at 22°C for 10 min. Finally, the slide was stained after the addition of 3,3′-diaminobenzidine (DAB) solution.

Cell culture and reagents

HCT116, SW480 cell lines were obtained from Cell Bank, Type Culture Collection, Chinese Academy of Sciences (Shanghai, China). All cells were cultured in DMEM (Gibco, USA) supplemented with 10% fetal bovine serum (Sigma-Aldrich, Australia) and penicillin-streptomycin (Invitrogen, USA) in a 90%–95% humidified atmosphere of 5% CO2 at 37°C.

siRNA-mediated gene silencing

SW480 and HCT116 cells were seeded in 6-well plates (2×105 cells/well) or 96-well plates (2×103 cells/well) 24 h before transfection. Two siRNAs designed to silence GPC1 and a control siRNA were obtained from Genepharma (Shanghai, China). The siRNA sequences are as follows: Control siRNA: 5′-UUCUCCGAACGUGUCACGUTT-3′; siGPC1#1: 5′-CCUGGAUAGUUAAGGGCUUTT-3′; and siGPC1#2: 5′-CCUUUCUGCCUUUUAAUUUTT-3′. siRNAs were transiently transfected into cells with Lipofectamine 8000 transfection reagent (Beyotime, Shanghai, China) according to the manufacturer’s instructions.

Cell proliferation assay

The CCK-8 Cell Counting Kit (Beyotime) was used to assess the proliferation of HCT116 and SW480 cells. Transfected cells were seeded in 96-well plates at a density of 2×104 cells/mL (100 μL/well) and incubated at 37°C with 5% CO2. On days 0 (at 48 h after transfection), 1, 2 and 3, CCK-8 reagent (10 μL) was added to cells and cells were incubated for 4–6 h. The optical density of the solution (OD450) in each well was measured by spectrophotometry (BioTek).

Apoptosis assay

The Annexin V-FITC Apoptosis Detection Kit (Beyotime, Shanghai, China) and a flow cytometer (Becton Dickinson, Franklin Lakes, NJ, USA) were used to evaluate the apoptosis of SW480 or HCT116 cells after transfection for 48 h. Briefly, cells were prepared into a 1×106 cells/mL cell suspension with 1 mL 1× Binding Buffer. Next, 200 μL of the cell suspension was mixed with 5 μL of Annexin V-FITC reagent in a centrifuge tube and the sample was mixed for 10 min in the dark at room temperature. PI reagent (5 μL) was then added to the centrifuge tube and samples were incubated in the dark at room temperature for 5 min. PBS was added to adjust the mixture to a final volume of 500 μL. After 30 min, the cells were evaluated by flow cytometry and the data were evaluated using CytoFLEX (Beckman Coulter) to calculate the number of apoptotic cells.

Cell cycle analysis

At 48 h after transfection, SW480 and HCT116 cells (2×106/ml) were collected, washed twice with PBS buffer and centrifuged at 1,000 × g for 5 min at 4°C. The supernatant was discarded and cells were fixed with ice-cold 70% ethanol for at 2 h at 4°C. The cells were centrifuged at 1,000 × g for 5 min at 4°C, washed twice with PBS and centrifuged again at 1,000 × g for 5 min at 4°C. The supernatant was discarded and cells were incubated with 50 μl RNase I (1 μg/ml; Beyotime, Shanghai, China) at 37°C for 1 h in the dark. Next, 200 μl propidium iodide (20 μg/ml) was added and the samples were held at room temperature for 20 min according to the manufacturer’s protocol.

Wound-healing assay

At 48 h after transfection, a sterilized 10-μL pipette tip was used to create a scratch in the monolayer of transfected CRC cells cultured in 6-well plates. After removing cell debris by washing with phosphate buffer saline (PBS), DMEM containing 2% FBS was added to each well and cells were cultured under 5% CO2 and 37°C for 48 h. The scratch width was measured at 0 h and 48 h using ImageJ software and an inverted optical microscope. The relative scratch width was calculated as the ratio of the scratch width at 48 h to the width at 0 h.

Transwell assay

At 24 h after transfection of CRC cells, 100 μL of cells (1×105 cells) were plated in serum-free DMEM medium in the top of a transwell chamber, and 600 μL of 20% DMEM medium was included in the bottom chamber. After 72 h of incubation under 37°C and 5% CO2, 99.99% methanol was used to fix the chamber, and 0.1% crystal violet was used for staining. A cotton swab was used to remove cells from the top chamber. Migrated cells were photographed and counted with an inverted optical microscope.

Real-time quantitative polymerase chain reaction (RT-qPCR)

Total RNA was isolated from CRC cells using TRizol reagent (Invitrogen, USA) according to the manufacturer’s instruction. Total RNAs were quantitatively analyzed and reverse-transcribed using a reverse transcription kit (PrimeScript RT Reagent Kit, RR047A, TaKaRa, Japan) to synthesize cDNAs. RT-qPCR was performed using a real-time quantitative PCR kit (A46113, Applied Biosystems, USA) on a QuantStudio 3 Real-Time PCR System (Thermo Fisher, USA). Each sample was run in triplicate. The sequences of primers used are listed in Table 1. The expression of target genes was calculated by the 2−ΔΔCt method [10]. GAPDH mRNA was used as a housekeeping gene for normalization of gene expression.

Table 1. Sequences of primers for qRT-PCR.

ID Forward sequence(5′-3′) Reverse sequence(5′-3′)
GPC1 TGAAGCTGGTCTACTGTGCTC CCCAGAACTTGTCGGTGATGA
GAPDH AGATCCCTCCAAAATCAAGTGG GGCAGAGATGATGACCCTTTT
TGF-β1 CTAATGGTGGAAACCCACAACG TATCGCCAGGAATTGTTGCTG
SMAD2 TCATAGCTTGGATTTACAGCCAG TTCTACCGTGGCATTTCGGTT
SMAD3 TGGACGCAGGTTCTCCAAAC CCGGCTCGCAGTAGGTAAC
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Western blotting

SW480, and HCT116 cells were lysed using RIPA buffer (Beyotime, Shanghai, China). Equal amounts of protein were separated by 10% SDS–PAGE and electrophoretically transferred to a PVDF membrane (Millipore, Billerica, MA, USA). The membrane was blocked with 5% non-fat milk for 2 h of blocking and then incubated with primary antibodies for 12 h at 4°C. After three washes, the membranes were incubated with secondary antibodies (1:5000) for 4 h followed by washing with TBST washing buffer. The protein bands were visualized using BeyoECL Star (Beyotime) and BIO-RAD Gel Doc XR+ (USA) and Image J software were used to analyze protein bands. The primary antibodies used are as follows: primary antibodies against GPC1 (1:1000, 16700-1-AP, Proteintech); TGF-β1 (1:1000, 21898-1-AP, Proteintech); SMAD2 (1:1000, 12570-1-AP, Proteintech); and p-SMAD2 (1:1000, ABP50459, abbkine).

Statistical analysis

Log-rank test was used to compare the Kaplan–Meier survival curves between high and low expression of GPC1, and the median was used as cutoff. P<0.05 indicated statistical significance.

Results

Elevated expression of GPC1 is positively associated with the survival, disease stage and TNM stage of CRC patients

We analyzed the mRNA expression of GPCs in CRC and non-tumor tissues from TCGA database using the “limma” and “survival” program packages of R software. The results showed that the expressions of GPC1 and GPC2 were higher (P<0.001) in CRC tissues than non-tumor tissues (Fig 1A). Furthermore, Kaplan–Meier analysis revealed that high expression of GPC1 and GPC2 were associated with shorter (P<0.01) overall survival in CRC patients (log-rank test) (Fig 1B). We also found that GPC1 expression was lower (P<0.01) in early stage tumors (stage I or II, T1–2, N0 or N1, M0) than in late stage tumors (stage III or IV, T3–4, N2, M1) (Fig 2A–2E) (S1 Table). GPC2 expression was lower (P<0.05) in early stage tumors (stage I or II, T1–2, N0 or N1) than in late stage tumors (stage III or IV, T3–4, N2). There were significant differences of GPC2 expression in M0 and M1 stage (P>0.05) (Fig 2F–2J and S1 Table). In addition, compared with that in paracarcinoma tissues, the protein expression of GPC1 in tumour tissues was elevated (Fig 2K). These results indicate that CRC patients with a high expression of GPC1 had a poor prognosis. Furthermore, GPC1 may function as an oncogene in the tumorigenesis and development of CRC and may also serve as a potential molecular marker for diagnosis and prognosis prediction for CRC.

Fig 1. Differential expression of GPC family genes in colorectal cancer (CRC) patients.

Fig 1

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(A). Gene expression of six GPC family members in cancer tissues (473 samples) and non-tumor tissues (41 samples) in CRC patients (TCGA) using Student’s t test. Blue indicates non-tumor tissues, and red indicates CRC tissues. (B). Kaplan–Meier analysis revealed that CRC patients (453 samples, TCGA) with high GPC1 expression (225 samples, TCGA) and high GPC2 expression (225 samples, TCGA) had a poor prognosis compared with patients with low GPC1 and GPC2 expression.

Fig 2. Elevated expression of GPC1 is associated with clinicopathological features of CRC.

Fig 2

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(A–J). GPC1 and GPC2 mRNA expression analysis in TCGA CRC samples (453 samples) by age, stage, T, N and M using Kolmogorov–Smirnov test. (K). Immunohistochemical staining for GPC1 in CRC tissues and normal tissues.

SiRNA-mediated GPC1 gene silencing significantly inhibits cell growth, induces cell cycle arrest, and promotes apoptosis of CRC cells

To explore the role of GPC1 in CRC cells, we performed siRNA-mediated gene silencing of GPC1 (si-GPC1-1 and si-GPC1-2). qRT-PCR and western blot analysis were conducted to measure GPC1 mRNA and protein expression in HCT116 and SW480 cell lines at 48 and 72 h after transfection. GPC1 mRNA expression levels were knocked down by up to 60% with si-GPC-1-1 and si-GPC1-2. We then evaluated the effects of GPC1 silencing on cell proliferation using the CCK-8 assay. The results showed that silencing GPC1 significantly (P<0.05) inhibited the proliferation of HCT116 and SW480 CRC cells compared with cells transfected with control siRNA (Fig 3A–3D).

Fig 3. Silencing GPC1 inhibits CRC cell proliferation.

Fig 3

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(A, C). CRC cell lines were transfected with siRNA targeting GPC1, and silencing efficiency at the mRNA and protein levels was determined. (B, D). Cell proliferation was inhibited in SW480 and HCT116 cells by silencing GPC1. * p<0.05, ** p<0.01.

To further study the biological function of GPC1 in the development of CRC, we evaluated the effect of GPC1 silencing on the cell cycle and apoptosis of CRC cells by flow cytometry assay. Knockdown of GPC1 significantly (P<0.05) induced apoptosis and cell cycle arrest at the S phase in SW480 and HCT116 cells (Fig 4A–4D). These results indicated that silencing GPC1 inhibits cell growth, induces S phase arrest and promotes apoptosis of CRC cells.

Fig 4. Knockdown of GPC1 induces apoptosis and S phase cell cycle arrest in CRC cells.

Fig 4

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(A, B). GPC1 silencing promoted SW480 and HCT116 cell apoptosis. (C, D). Knockdown of GPC1 induced S cell cycle arrest in SW480 and HCT116 cells. * p<0.05.

Silencing GPC1 significantly reduces cell migration ability in CRC cells in vitro

To further investigate the role of GPC1 in CRC, cell motility was assessed by wound healing and transwell migration assays. In wound healing assays, cells with GPC1 knockdown showed reduced migration compared with control cells in SW480 and HCT116 cell lines (Fig 5A and 5B). Similarly, transwell migration assay indicated that GPC1 knockdown significantly (P<0.01) impaired cell migration ability in SW480 and HCT116 cells (Fig 5C and 5D). These results showed that silencing GPC1 impairs cell migration activity in CRC cells, further implying an important role for GPC1 in the progression of CRC.

Fig 5. Silencing GPC1 significantly reduces cell migration ability in CRC cells.

Fig 5

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(A, B). Knockdown of GPC1 significantly inhibited wound healing in SW480 and HCT116 cell lines. (C, D). Silencing GPC1 significantly impaired the cell migration in SW480 and HCT116 cell lines. ** p<0.01.

GPC1 regulates the TGF-β1/SMAD2 signaling pathway

To explore the mechanism underlying the involvement of GPC1 in CRC, we first analyzed the possible signaling pathways mediated by GPC1 by bioinformatics assay using “limma” bioconductor to identify the RNAs related to GPC1. The GPC1-related RNAs are shown in a heatmap in Fig 6A. Next, we used GO enrichment analysis on the target genes that were screened (Fig 6B). We then predicted the relationships between GPC1-related target genes (Fig 6C). Two different bioinformatics analyses indicated that GPC1 may regulate the TGF-β1 signaling pathway in CRC cells (Fig 6B and 6C), which is consistent with our previous findings [14]. Notably, previous studies showed that the TGF-β signaling pathway is involved in the occurrence and development of CRC [15].

Fig 6. Pathway enrichment analysis and TGF-β signaling pathway identification in CRC.

Fig 6

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(A). Correlations between GPC1 and target genes in CRC. (B). GO analysis showed that the TGF-β signaling pathway was enriched in CRC. (C). The correlation-target network for GPC1. (D–G). GPC1-associated mRNAs and proteins were examined by qRT-PCR and western blot analysis in SW480 and HCT116 cell lines after silencing GPC1.

To confirm the results of the bioinformatics analysis, we explored the effect of GPC1 silencing on the expression of TGF-β1 signaling pathway–related molecules such as SMAD1 and SMAD2 by qRT-PCR. TGF-β1 and SMAD2 mRNAs were significantly down-regulated and up-regulated, respectively, in HCT116 and SW480 cells after the silencing of GPC1 expression (Fig 6D and 6F). We then evaluated the effects of GPC1 silencing on the protein levels of TGF-β1, SMAD2 and p-SMAD2 by western blot assay. The results showed that the levels of TGF-β1 and p-SMAD2 proteins were significantly down-regulated, and the expression of SMAD2 protein was significantly up-regulated in HCT116 and SW480 cells following the silencing of GPC1 expression (Fig 6E and 6G). Together these results suggest that GPC1 may be involved in the proliferation, apoptosis and migration of CRC cells through regulating the TGF-β1/SMAD2 signaling pathway.

Discussion

With the development of bioinformatics, several key genes that play an important role in the occurrence and development of CRC have been identified [16]. In this study, we analyzed the gene expression of the GPC family in CRC. GPCs belong to the HSPG family and interact with a variety of protein ligands, proteases, cytokines, chemokines, adhesion molecules and ECM proteins, thereby producing a variety of structures and signal transduction functions [17]. HSPG proteins exhibit functions in a wide range of biological processes, such as development, hemostasis control, and inflammation, and are associated with cell survival [18]. In addition, HSPG proteins are involved in cell adhesion, movement, proliferation, differentiation and apoptosis [14] and thus have been linked to the enhancement of malignant diseases.

In this study, we found that high expression of GPC1 was significantly related to the poor prognosis of patients with CRC. This finding is consistent with previous reports [19]. Several studies demonstrated that GPC1 is involved in the formation and development of different types of tumors [20, 21]. Experimental studies revealed that the expression of GPC1 was significantly increased in the extracellular vesicles released by the mouse MC38 CRC cell line [22]. In addition, TMT-MS methods to study crEV in patients with CRC found that GPC1 can be used as a biomarker for the detection of early CRC [23].

A previous study using bioinformatics analysis showed that GPC1 may participate in the occurrence and development of CRC through the glycolytic pathway [23]. Other analyses found that GPC1 may be involved in CRC development through influencing intestinal tumor hypoxia on immune cells in the tumor microenvironment [24]. However, these findings have not been verified by experiments and the precise mechanism by which GPC1 participates in the regulation of CRC is still unclear. In this study, our in vitro experiments revealed that GPC1 gene silencing in the HCT116 and SW480 CRC cell lines resulted in inhibition of cell proliferation, S phase cycle arrest, induction of apoptosis and reduced migration of CRC cells. We further showed that GPC1 may be involved in the occurrence and development of CRC by activating the TGF-β/SMAD2 signaling pathway. Decreased GPC1 expression suppresses pancreatic cancer cell growth by modifying TGF-β signaling [25]. GPC1 has been shown to interact with TGF-β and its receptors to stabilize their assembly for enhanced Smad signaling. Downregulation of GPC1 expression resulted in a slightly altered response toward TGF-β1, activin-A, and BMP2 in terms of growth, p21 induction, and Smad2 phosphorylation, ultimately leading to decreased anchorage-independent growth of T3M4 and PANC-1 cells.

GPC3 also promotes the growth of liver cancer cells and may regulate the TGF-β signaling pathway [26]. The human TGF-β family includes 33 genes that encode for homodimeric or heterodimeric secreted cytokines [27, 28]. These proteins are involved in a variety of biological processes, including proliferation, differentiation, migration, apoptosis and adhesion [29]. Dysregulation of TGF-β signaling frequently occurs in CRC [30]. TGF-β signaling is initiated through binding of the TGF-β ligand to the receptor, which in turn phosphorylates the downstream target SMAD2/3 [31, 32]. Phosphorylated SMAD2/3 enters the nucleus with the help of SMAD4 and cofactors and acts as a transcription factor to induce gene expression, including the expression of EMT-related genes [33, 34]. EMT has been shown to affect cancer cell migration [31]. The TGF-β/SMAD2/3 signaling pathway has been shown to affect the cell proliferation, survival, differentiation, apoptosis and migration of CRC [35–37]. The mechanism of S phase arrest and apoptosis induced by GPC1 silencing requires further investigation.

Future studies should verify our results using larger numbers of clinical specimen and more in-depth research is required into the mechanism by which GPC1 functions in CRC. In addition, animal models will be required to elucidate how GPC1 affects the occurrence and development of CRC in vivo. Our results suggest that GPC1 may be a prognostic marker and a new therapeutic target for CRC.

Supporting information

S1 Fig. GPC1 mRNA expression in different cancers and cancer cell lines.

(A) Significantly high expression of GPC1 mRNA in colon adenocarcinoma (COAD), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), lung squamous cell carcinoma (LUSC), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD). (B) GPC1 mRNA expression levels in different cancer cell lines.

(TIF)

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S2 Fig. Enrichment analysis of GPC1 in major cancer-related signaling pathways.

GPC1 is significantly enriched in the TGF-β signaling pathway.

(TIF)

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S1 Table. GPC1 is significantly related to M stage in colorectal cancer patients from TCGA.

(DOCX)

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S2 Table. Results of 3 independent replicate experiments of cell apoptosis.

Note: Survival analysis was performed by Kaplan–Meier test, and correlation analysis of clinicopathological characteristics was performed by Kolmogorov-Smirnov test; the numbers in the table represent the P value of the correlation analysis.

(DOCX)

Click here for additional data file. (13.1KB, docx)
S3 Table. Results of 3 independent replicate experiments of cell cycle.

(DOCX)

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S1 File

(DOCX)

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Acknowledgments

We thank Gabrielle White Wolf, PhD, from Liwen Bianji (Edanz) (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

LF and LM both are funded by the following: Anhui Natural Science Foundation under Grand (No. 2108085MH291), and the 512 Talent Cultivation Plan for subject leader of Bengbu Medical College (by51201107). LF and WH both are funded by the following: Anhui Natural Science Foundation under Grand (1908085MH257). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Hamidreza Montazeri Aliabadi

8 Mar 2022

PONE-D-21-26390

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signaling pathway

PLOS ONE

Dear Dr. Liu,

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PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

********** 

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: There are several questions needed to be discussed.

1. The manuscript has to be polished by professional language polishing companies because there are a lot of typographical or grammatical errors.

2. TGF-β signaling is initiated through binding of the TGF-β ligand to the receptor, which in turn phosphorylates the downstream target SMAD2/3. In this study, authors reported that GPC1 knockdown decreased the expression of TGF-β and p-SMAD2. However, why total SMAD2 expression also be affected?

3. In figure 2k, the GAPDH expression obviously differs in CRC cells and NCM460. therefore, please provide more accurate figures.

4. Please discuss how GPC1 influences the expression of TGF-β? It functions as a transcript factor?

Reviewer #2: PONE-D-21-26390.

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signalling pathway

The authors investigate the potential role of GPC-1 in colorectal cancer using in silico and in vitro techniques. While the role of GPC-1 has been well described in other cancers such as pancreatic and prostate, its role in colorectal cancer is poorly understood.

While there has been some published data on GPC-1 mRNA expression in colorectal vs normal tissues, and in GPC-1 exosomes in colorectal cancer, there has been limited investigation of the mechanisms by which GPC-1 may play a role in the biology of CRC.

The authors demonstrate that knockdown of GPC-1 in colon cancer cell lines reduces proliferation and migration, consistent with what has been observed in other cancer types. They have identified the TGF-b1/SMAD2 signalling axis as a potential mediator of GPC-1 function in CRC.

A major challenge in determining the expression of GPC-1 in different cancers is that expression of the mRNA should be correlated to the expression of the GPC-1 protein using immunohistochemistry. If tissue availability is an issue for this, the authors should comment on the likelihood that the relative expression identified by mRNA is reflected in the protein expression in tumours.

Similarly, the detection of GPC-1 via western blot in this paper is problematic. GPC-1 is known to be heparan sulphated. While the core protein of ~55kDa can be detected without lysate treatment, use of Heparanase can result in much higher levels of GPC-1 detectable via western blot. The western blots shown in the figures and in the supplementary material do not have a positive control (e.g. recombinant GPC-1) to ensure that the band detected is actually GPC-1 (it is not clear what the molecular weight of the reactive bands are).

Specific comments:

Line 77 – reference 9 (Quach) does not show the expression in endometrial, lung or other tumours. Suggest referring to individual papers for each indication or a review article.

Line 177 – Western blot. GPC-1 is generally highly glycosylated – in particular with heparan sulfate chains. Was Heparanase treatment of samples attempted? If so was there any additional GPC-1 that became visible after treatment?

Line 186 – all glypicans seem to be differentially expressed at a statistically significant level between normal and tumour tissue. It appears GPC-3 and GPC6 are decreased, while GPC-4 is increased in tumour vs normal. It is not possible to tell from Figure 1 what the expression levels of GPC-5 are like in tumour vs normal.

Lines 192-200. While the differences in GPC-1 expression for tumour stage are statistically significant, the relative fold changes are small.

Line 196 – referring to Figure 2 western blots. The western blot for GPC-1 is very dark and the signal quite weak. The fold change in expression between normal and cancer lines shows error bars but it is unclear how many times these blots were performed to generate the densitometry. There is also no control for GPC-1 (e.g. recombinant GPC-1 or a cell line known to overexpress GPC-1).

Under the Methods section line 169 it is unclear if NCM460, RKO, CACO2 cells were also lysed in RIPA buffer and their growth conditions are not described in the Methods section.

Line 219 – Figure 3. GPC1 mRNA expression levels were knocked down by up to 60% but not 100%. This should be commented on. It is also not clear from the text or the figure legends what si-GPC-1-1 and si-GPC1-2 refer to (although this is mentioned in the methods). For 3B and D, it is not clear when the transient transfection of the siRNAs occurred relative to the start of the proliferation assay.

There is insufficient detail in Apoptosis and Cell Cycle methods to describe Fig 4. Also no information about number of times the experiment was repeated to generate the error bars is provided.

Figure 4 shows relatively minor changes in Apoptosis and Cell Cycle effects, although they appear from the data to be statistically significant.

Line 233 – cell migration. Again it is unclear when the GPC-1 knockdown was performed relative to the assay being performed.

Line 253 seems to have missed completion of a sentence.

Line 260 – protein levels of TGFb1. Presumably these are cellular levels as secreted TGFb1 would not be collected and analysed via the western blot protein extraction method described?

Line 271 – “after treatment with” rather then “after treated with”

Reviewer #3: Summary

This paper introduces the promoting role of GPC1 in CRC, and provides evidence that GPC1 may be used as an early biological detection standard and therapeutic target for CRC in the future, which can help doctors better treat CRC patients and has very high clinical significance.

Advantages

1、With clear logic and extensive data, this paper provides sufficient evidence that GPC1 promotes the development of CRC

2、In this paper, the functional pathway of GPC1 has also been confirmed.

Disadvantages

1、The picture is not clear enough. For example, the legend in the survival analysis of B in figure1 is not clear.

2、The expression levels of GAPDH in Western blot were significantly different, such as K in figure2

3、Since there are many figures in this paper, each figure can be placed under the corresponding results for easy reading

4、The language needs to be more refined

********** 

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2022 Jun 7;17(6):e0269094. doi: 10.1371/journal.pone.0269094.r002

Author response to Decision Letter 0

30 Apr 2022

Reviewer Comments:

Reviewer 1

Question 1: The manuscript has to be polished by professional language polishing companies because there are a lot of typographical or grammatical errors.

Response: Thank you for your suggestions, our manuscript has been polished by Liwen Bianji (Edanz) (www.liwenbianji.cn/ac) for professional language polishing.

Question 2: TGF-β signaling is initiated through binding of the TGF-β ligand to the receptor, which in turn phosphorylates the downstream target SMAD2/3. In this study, authors reported that GPC1 knockdown decreased the expression of TGF-β and p-SMAD2. However, why total SMAD2 expression also be affected?

Response: Thanks for this comment. In the case of our study, we used RIPA Lysis Buffer (50mM Tris(pH 7.4), 150mM NaCl, 1% NP-40，0.5% sodium deoxycholate,

0.1% SDS, sodium orthovanadate, sodium fluoride, EDTA, leupeptin) to extract proteins, in which the nucleoproteins are difficult to extract. Our speculation is that SMAD2 nuclear translation affects total SMAD2. (M. Kretzschmar, et al. A mechanism of repression of TGFbeta/ Smad signaling by oncogenic Ras Genes Dev., 13 (7) (1999), pp. 804-816; M. Kretzschmar, et al. The TGF-beta family mediator Smad1 is phosphorylated directly and activated functionally by the BMP receptor kinase Genes Dev., 11 (8) (1997), pp. 984-995).

Question 3: In figure 2k, the GAPDH expression obviously differs in CRC cells and NCM460. therefore, please provide more accurate figures.

Response: Thanks for this comment. Because NCM460 cells and Caco-2 cells are difficult to grow, the total GPC-1 expression is low. Due to experimental techniques, the GAPDH expression obviously differs in CRC cells and NCM460. For the accuracy of the conclusion, we used IHC technique for clinical tissue samples to investigate the protein expression levels of GPC1 in colorectal cancer.

Question 4: Please discuss how GPC1 influences the expression of TGF-β? It functions as a transcript factor?

Response: Thank you. Decreased GPC1 expression suppresses pancreatic cancer cell growth by modifying TGF-β signaling. GPC1 has been shown to interact with TGF-β and its receptors to stabilize their assembly for enhanced Smad signaling. Downregulation of GPC1 expression resulted in a slightly altered response toward TGF-β1, activin-A, and BMP2 in terms of growth, p21 induction, and Smad2 phosphorylation, ultimately leading to decreased anchorage-independent growth of T3M4 and PANC-1 cells.

Reviewer 2

Question 1: Line 77 – reference 9 (Quach) does not show the expression in endometrial, lung or other tumours. Suggest referring to individual papers for each indication or a review article.

Response: Thanks for this comment.We have referred to individual papers for each indication or a review article (line 68).

Question 2: Line 177 – Western blot. GPC-1 is generally highly glycosylated – in particular with heparan sulfate chains. Was Heparanase treatment of samples attempted? If so was there any additional GPC-1 that became visible after treatment?

Response: Thanks for this comment. Your suggestion is very correct. But we did not treat protein samples with Heparinase. (Yu Mu, Dezhi Wang, Liangyu Bie,et al. Glypican-1-targeted and gemcitabine-loaded liposomes enhance tumor-suppressing effect on pancreatic cancer. Aging (Albany NY). 2020 Oct 15; 12(19): 19585–19596. )

Question 3: Line 186 – all glypicans seem to be differentially expressed at a statistically significant level between normal and tumour tissue. It appears GPC-3 and GPC6 are decreased, while GPC-4 is increased in tumour vs normal. It is not possible to tell from Figure 1 what the expression levels of GPC-5 are like in tumour vs normal.

Response: Thanks for your comment. We have produced a new Figure showing the significant differential expression of GPC5 between tumor and normal tissues.

Question 4: Lines 192-200. While the differences in GPC-1 expression for tumour stage are statistically significant, the relative fold changes are small.

Response: Thanks for this comment. Our data and scientific conclusion from them (FC>1 or FC <-1, P<0.05) are to be credible. (Shi, L., Jones, W. D., Jensen, R. V., Harris, S. C., Perkins, R. G., Goodsaid, F. M., … Tong, W. (2008). The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies. BMC Bioinformatics, 9(Suppl 9), S10.)

Question 5: Line 196 – referring to Figure 2 western blots. The western blot for GPC-1 is very dark and the signal quite weak. The fold change in expression between normal and cancer lines shows error bars but it is unclear how many times these blots were performed to generate the densitometry. There is also no control for GPC-1 (e.g. recombinant GPC-1 or a cell line known to overexpress GPC-1).

Response: Thanks for this comment. Because Caco-2 cells are difficult to grow, the total GPC-1 expression is low. For the accuracy of the conclusion, we used IHC technique for clinical tissue samples to investigate the protein expression levels of GPC1 in colorectal cancer.

Question 6: Under the Methods section line 169 it is unclear if NCM460, RKO, CACO2 cells were also lysed in RIPA buffer and their growth conditions are not described in the Methods section.

Response: Thanks for this comment. SW480, NCM460, RKO, CACO2 and HCT116 cells were lysed using RIPA buffer (Beyotime, Shanghai, China).

Question 7: Line 219 – Figure 3. GPC1 mRNA expression levels were knocked down by up to 60% but not 100%. This should be commented on. It is also not clear from the text or the figure legends what si-GPC1-1 and si-GPC1-2 refer to (although this is mentioned in the methods). For 3B and D, it is not clear when the transient transfection of the siRNAs occurred relative to the start of the proliferation assay.

Response: Thanks for this comment. On days 0 (at 48 h after transfection), 1, 2 and 3, CCK-8 reagent (10 µL) was added to cells and cells were incubated for 4–6 h.

Question 8: There is insufficient detail in Apoptosis and Cell Cycle methods to describe Fig 4. Also no information about number of times the experiment was repeated to generate the error bars is provided.Figure 4 shows relatively minor changes in Apoptosis and Cell Cycle effects, although they appear from the data to be statistically significant.

Response: Thanks for this comment. Concerning the under-description of Figure 4 in the Apoptosis and Cell Cycle Methods in this manuscript, we have described it exhaustively at the corresponding location in the manuscript, and the information about number of times the experiment was repeated to generate the error bars is provided in Supplementary Data. For the relatively small changes in apoptosis and cell cycle effects in Figure 4, because of their statistical differences and good statistical significance in other experimental stages, it does not affect the final conclusion of this study, so they are not further optimized.

Question 9: Line 233 – cell migration. Again it is unclear when the GPC-1 knockdown was performed relative to the assay being performed.

Response: Thanks for this comment. At 48 h after transfection, a sterilized 10-µL pipette tip was used to create a scratch in the monolayer of transfected CRC cells cultured in 6-well plates.

Question 10: Line 253 seems to have missed completion of a sentence.

Response: Thank you. Two different bioinformatics analyses indicated that GPC1 may regulate the TGF-β1 signaling pathway in CRC cells (Fig. 6B and 6C), which is consistent with our previous findings.

Question 11: Line 260 – protein levels of TGFb1. Presumably these are cellular levels as secreted TGFb1 would not be collected and analysed via the western blot protein extraction method described?

Response: We thank the reviewer for the very interesting comment. In fact, we used RIPA Lysis Buffer to extract proteins, in which secreted TGFb1 and the nucleoproteins are difficult to extract. So we described how to extract the protein in the protein extraction method.

Question 12: Line 271 – “after treatment with” rather then “after treated with”

Response: Thank you. GPC1-associated mRNAs and proteins were examined by qRT-PCR and western blot analysis in SW480 and HCT116 cell lines after silencing GPC1.

Reviewer 3

Question 1: The picture is not clear enough. For example, the legend in the survival analysis of B in figure1 is not clear.

Response: Thank you. We made a new figure1.

Question 2: The expression levels of GAPDH in Western blot were significantly different, such as K in figure2.

Response: Thanks for this comment. Because NCM460 cells and Caco-2 cells are difficult to grow, the total GPC-1 expression is low. Due to experimental techniques, the GAPDH expression obviously differs in CRC cells and NCM460. For the accuracy of the conclusion, we used IHC technique for clinical tissue samples to investigate the protein expression levels of GPC1 in colorectal cancer.

Question 3: Since there are many figures in this paper, each figure can be placed under the corresponding results for easy reading.

Response: Thank you. We will place figures as required by the journal.

Question 4: The language needs to be more refined.

Response: Thank you for your suggestions, our manuscript has been polished by Liwen Bianji (Edanz) (www.liwenbianji.cn/ac) for professional language polishing.

Attachment

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Click here for additional data file. (25.1KB, docx)

Decision Letter 1

Hamidreza Montazeri Aliabadi

16 May 2022

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signaling pathway

PONE-D-21-26390R1

Dear Dr. Liu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Hamidreza Montazeri Aliabadi

Academic Editor

PLOS ONE

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

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Acceptance letter

Hamidreza Montazeri Aliabadi

27 May 2022

PONE-D-21-26390R1

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signaling pathway

Dear Dr. Liu:

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. GPC1 mRNA expression in different cancers and cancer cell lines.

    (A) Significantly high expression of GPC1 mRNA in colon adenocarcinoma (COAD), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), lung squamous cell carcinoma (LUSC), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD). (B) GPC1 mRNA expression levels in different cancer cell lines.

    (TIF)

    Click here for additional data file. (6.1MB, tif)
    S2 Fig. Enrichment analysis of GPC1 in major cancer-related signaling pathways.

    GPC1 is significantly enriched in the TGF-β signaling pathway.

    (TIF)

    Click here for additional data file. (1.6MB, tif)
    S1 Table. GPC1 is significantly related to M stage in colorectal cancer patients from TCGA.

    (DOCX)

    Click here for additional data file. (13KB, docx)
    S2 Table. Results of 3 independent replicate experiments of cell apoptosis.

    Note: Survival analysis was performed by Kaplan–Meier test, and correlation analysis of clinicopathological characteristics was performed by Kolmogorov-Smirnov test; the numbers in the table represent the P value of the correlation analysis.

    (DOCX)

    Click here for additional data file. (13.1KB, docx)
    S3 Table. Results of 3 independent replicate experiments of cell cycle.

    (DOCX)

    Click here for additional data file. (19.7KB, docx)
    S1 File

    (DOCX)

    Click here for additional data file. (1.2MB, docx)
    Attachment

    Submitted filename: responds to the reviewer.docx

    Click here for additional data file. (25.1KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

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