
==== Front
iScience
iScience
iScience
2589-0042
Elsevier

S2589-0042(24)01955-2
10.1016/j.isci.2024.110730
110730
Article
FNIP1 suppresses colorectal cancer progression through inhibiting STAT3 phosphorylation and nuclear translocation
Zhang Guixia 12
Chen Xintian 12
Yu Caiyuan 1
Cui Lijiao 1
Chen Ningning 1
Yi Guanrong 1
Wang Shan 1
Wei Haiyun 1
Liang Youxin 1
Ye Shicai yeshicai@gdmu.edu.cn
1∗
Zhou Yu ahdg2022@gdmu.edu.cn
13∗∗
1 Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong 524001, China
∗ Corresponding author yeshicai@gdmu.edu.cn
∗∗ Corresponding author ahdg2022@gdmu.edu.cn
2 These authors contributed equally

3 Lead contact

14 8 2024
20 9 2024
14 8 2024
27 9 1107309 12 2023
9 6 2024
12 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Summary

Folliculin interacting protein 1 (FNIP1) primarily participates in regulating cellular energy metabolism and is associated with Birt-Hogg-Dubé (BHD) syndrome. Although FNIP1 has been demonstrated to function as both a tumor suppressor and promoter, its role in colorectal cancer (CRC) remains unclear. Our study demonstrated a significant downregulation of FNIP1 in CRC, correlating with shorter overall and disease-specific survival. FNIP1 may potentially serve as an independent prognostic factor in CRC. Moreover, FNIP1 inhibited CRC progression in vitro and in vivo. Mechanistically, FNIP1 bound to phosphorylated signal transducer and activator of transcription-3 (p-STAT3) and downregulated its expression. FNIP1 deletion increased STAT3 phosphorylation and nuclear localization, thereby promoting CRC progression. The use of p-STAT3-specific chemical inhibitors successfully mitigated excessive tumorigenesis resulting from FNIP1 absence. Thus, our results suggest that FNIP1 hinders CRC progression by suppressing STAT3 phosphorylation and nuclear translocation. FNIP1 may be a candidate prognostic indicator and a therapeutic target for intervention in CRC.

Graphical abstract

Highlights

• FNIP1 is deregulated and acts as an independent prognostic marker in CRC

• FNIP1 restricts CRC tumorigenesis in vivo and in vitro

• FNIP1 binds to p-STAT3 and reduces its expression and nuclear localization

Biological sciences; Molecular biology; Cancer

Subject areas

Biological sciences
Molecular biology
Cancer
Published: August 14, 2024
==== Body
pmcIntroduction

Colorectal cancer (CRC) has emerged as one of the most common and deadly malignancies, posing a serious threat to patient health.1 Despite the development of numerous therapeutic approaches for CRC, the prognosis of CRC patients remains poor. Therefore, elucidating the pathogenesis of CRC and exploring more specific CRC biomarkers and therapeutic targets are necessary.

The signal transducer and activator of the transcription 3 (STAT3) signaling pathway is consistently abnormally activated in CRC. Stimuli such as insulin-like growth factor (IGF), epidermal growth factor (EGF), vascular endothelial growth factor (VEGF), interleukin 6 (IL-6), and interferon-gamma (IFN-γ) activate the upstream kinases of STAT3.2,3 Subsequently, kinases such as Janus kinase (JAK) and receptor tyrosine kinase (RTK) can phosphorylate STAT3 in the cytoplasm.4,5 Then the phosphorylated STAT3 translocates it to the nucleus, resulting in increased expression of c-Myc and cyclin D1 (CCND1), thereby contributing to tumorigenesis and development.6,7,8,9,10 Thus, deciphering the molecular basis of the aberrant activation of STAT3 signaling may enhance therapeutic options for CRC.

Folliculin interacting protein 1 (FNIP1) is a conserved protein widely expressed in human tissues and has been implicated in the pathogenesis of Birt-Hogg-Dubé (BHD) syndrome.11,12 Recently, FNIP1 has been found to be downregulated in breast cancer13 and implicated in pancreatic cancer progression.14 In human renal clear cell carcinoma, FNIP1 has been linked to antitumor drug sensitivity.15 FNIP1 may serve as a therapeutic target and a prognostic marker in tumors. However, the role and mechanism of FNIP1 in CRC remain unclear.

Our study aimed to understand the expression of FNIP1 in colorectal tissues and its relationship with the clinical prognosis of CRC. We also attempted to further elucidate the role of FNIP1 in the pathogenesis of CRC and the possible mechanisms involved. This may provide new strategies for the diagnosis and treatment of CRC.

Results

FNIP1 is an independent prognostic factor of CRC

To explore the potential role of FNIP1 in CRC, we analyzed the effect of FNIP1 on survival in CRC patients using The Cancer Genome Atlas (TCGA) data (TCGA : https://portal.gdc.cancer.gov/projects/TCGA-COAD and https://portal.gdc.cancer.gov/projects/TCGA-READ). The results indicated that patients with lower FNIP1 expression experienced poorer overall survival (OS) (Figure 1A) and disease-specific survival (DSS) (Figure 1B). The Human Protein Atlas (HPA) database (the HPA: https://www.proteinatlas.org/search/FNIP1) further validated that FNIP1 expression was decreased in CRC (Figures 1C and 1D, S1A and S1B). Moreover, our results of FNIP1 mRNA and protein levels in intestinal tissue samples of 233 healthy individuals or patients with adenoma or CRC verified the low expression of FNIP1 in CRC (Figures 1E–1G).Figure 1 FNIP1 is downregulated and correlated with poor prognosis in CRC patients

(A and B) The CRC data from TCGA database (TCGA: https://portal.gdc.cancer.gov/projects/TCGA-COAD and https://portal.gdc.cancer.gov/projects/TCGA-READ) were used to analyze the effects of FNIP1 on overall survival and disease-specific survival in patients with CRC.

(C) Representative IHC images of FNIP1 expression in normal colorectal tissues and CRC tissues were obtained from the HPA database (the HPA: https://www.proteinatlas.org/search/FNIP1). Scale bar: 200 μm. See also Figure S1A.

(D) The overall IHC score of FNIP1 in normal colorectal tissues and CRC tissues was analyzed based on the slide information acquired from the HPA database (the HPA: https://www.proteinatlas.org/search/FNIP1) (normal, n = 5; CRC, n = 11). See also Figure S1B.

(E and F) The expression of FNIP1 protein in human intestinal tissues was analyzed by western blotting (normal, n = 30; CRC, n = 30; CRC adjacent, n = 30; colorectal adenoma, n = 25). See also Figure S1C.

(G) The expression of FNIP1 mRNA in human colorectal tissues was detected by qRT-PCR (normal, n = 59; CRC, n = 88; CRC adjacent, n = 58; colorectal adenoma, n = 28). Data are represented as mean ± SD.∗p < 0.05, ∗∗p < 0.01, ∗∗∗∗p < 0.0001. Two-tailed Student’s t test for (C and D), one-way ANOVA with Tukey’s test for (E–G).

We conducted univariate and multivariate Cox regression analyses using CRC data from TCGA database to investigate whether low FNIP1 expression serves as an independent prognostic factor for CRC. Univariate Cox regression analysis showed that age, TNM stage, and FNIP1 expression were significant prognostic factors for OS and DSS in CRC patients (Table 1). In multivariate Cox regression, FNIP1 expression remained an independent prognostic biomarker for OS and DSS in CRC patients (Table 2). These results suggest that FNIP1 expression could be an independent prognostic factor in CRC patients.Table 1 Univariate Cox regression analysis of overall and DSS in CRC patients was analyzed using TCGA database

Variables	Total(N)a	Hazard Ratio (95% CIc)	pb	
 Overall Survival	
 Age (years old)	643			
 ≤ 65	276	1.000		
 >65	367	1.939 (1.320–2.849)	<0.001	
 Gender	643			
 Female	301	1.000		
 Male	342	1.054 (0.744–1.491)	0.769	
 T stage	640			
 T1 & T2	131	1.000		
 T3 & T4	509	2.468 (1.327–4.589)	0.004	
 N stage	639			
 N0	367	1.000		
 N1 & N2	272	2.627 (1.831–3.769)	<0.001	
 M stage	563			
 M0	474	1.000		
 M1	89	3.989 (2.684–5.929)	<0.001	
 FNIP1	643			
 Low	322	1.000		
 High	321	0.633 (0.443–0.903)	0.012	
 Disease-specific survival	
 Age (years old)	621			
 ≤ 65	273	1.000		
 >65	348	1.421 (0.894–2.257)	0.137	
 Gender	621			
 Female	290	1.000		
 Male	331	1.207 (0.769–1.895)	0.412	
 T stage	618			
 T1 & T2	129	1.000		
 T3 & T4	489	6.440 (2.029–20.441)	0.002	
 N stage	617			
 N0	358	1.000		
 N1 & N2	259	4.119 (2.496–6.797)	<0.001	
 M stage	542			
 M0	455	1.000		
 M1	87	7.471 (4.647–12.012)	<0.001	
 FNIP1	621			
 Low	307	1.000		
 High	314	0.521 (0.328–0.829)	0.006	
a Total(N): sample size. The total number of samples corresponding to the variables and the number of samples corresponding to the subgroups.

b p values are from the Log rank test.

c CI: confidence interval.

Table 2 Multivariate Cox regression analysis of overall survival and disease-specific survival in CRC patients were analyzed using TCGA database

Variablesa	Total(N)	Hazard ratio (95% CI)	p	
 Overall survival	
 Age (years old)	643			
 ≤ 65	276	1.000		
 >65	367	2.615 (1.687–4.056)	<0.001	
 T stage	640			
 T1 & T2	131	1.000		
 T3 & T4	509	2.193 (0.992–4.849)	0.053	
 N stage	639			
 N0	367	1.000		
 N1 & N2	272	1.752 (1.104–2.781)	0.017	
 M stage	563			
 M0	474	1.000		
 M1	89	3.040 (1.911–4.837)	<0.001	
 FNIP1	643			
 Low	322	1.000		
 High	321	0.612 (0.413–0.906)	0.014	
 Disease-specific survival	
 T stage	618			
 T1 & T2	129	1.000		
 T3 & T4	489	2.955 (0.887–9.848)	0.078	
 N stage	617			
 N0	358	1.000		
 N1 & N2	259	1.658 (0.883–3.113)	0.115	
 M stage	542			
 M0	455	1.000		
 M1	87	5.174 (2.963–9.033)	<0.001	
 FNIP1	621			
 Low	307	1.000		
 High	314	0.465 (0.283–0.764)	0.003	
a Variables satisfying p < 0.1 in the univariate Cox regression analysis are then included in the multivariate Cox regression.

FNIP1 inhibits CRC progression in vitro

Considering the correlation between low FNIP1 expression and poor CRC prognosis, we further studied the biological function of FNIP1 in CRC in vitro.

FNIP1 was knocked out and overexpressed in HCT116 and SW480 cells (Figures 2A and 2B), and cell proliferation was determined using CCK-8 assay. The knockout of FNIP1 significantly accelerated CRC cell proliferation compared with that in the control groups (Figures 2C and 2D), whereas FNIP1 overexpression significantly inhibited proliferation (Figures 2E and 2F). Moreover, FNIP1 knockout significantly reduced apoptosis (Figures 2G and 2H), whereas FNIP1 overexpression significantly promoted cell apoptosis (Figures 2I and 2J). FNIP1 knockout significantly promoted HCT116 and SW480 cell migration (Figures 2K–2N), whereas FNIP1 overexpression significantly inhibited the migration (Figures 2O–2R). These results demonstrate that FNIP1 inhibits the biological functions of the CRC cells in vitro.Figure 2 FNIP1 prevents proliferation, and migration and increases apoptosis of CRC cells in vitro

(A and B) The efficiency of FNIP1 knockout and overexpression in HCT116 and SW480 cells was analyzed by western blotting.

(C–F) CCK8 analysis was used to assess the proliferation of CRC cells when FNIP1 was knocked out or overexpressed (n = 5).

(G–J) Flow cytometry was used to detect apoptosis when FNIP1 was knocked out or overexpressed (n = 3).

(K–R) Representative images of cell migration when FNIP1 was knocked out or overexpressed (n = 3). Scale bar: 100 μm. Data are represented as mean ± SD. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Two-way ANOVA with Tukey’s test for (C–F). Two-tailed Student’s t test for (G–R).

FNIP1 inhibits tumor growth and lung metastasis in vivo

We established a subcutaneous xenograft model in nude mice to further investigate the effects of FNIP1 on tumor growth in vivo. Briefly, HCT116 cells stably overexpressing FNIP1 (Figure S2A) were transplanted subcutaneously into nude mice. Tumors overexpressing FNIP1 exhibited smaller sizes, slower growth curves, and lower weights than the vector group (Figures 3A–3C). Conversely, cells with FNIP1 knockout (Figure S2B) formed larger tumors with faster growth rates and greater weights (Figures S2C–S2E). Immunohistochemistry (IHC) revealed that tumors in the OE-FNIP1 group expressed fewer Ki-67 than the control (Figures 3D and 3E). Correspondingly, Ki-67-positive cells were more abundant in the KO-FNIP1 group (Figures S2F and S2G). Our results validate that high expression levels of FNIP1 inhibit tumor growth in vivo.Figure 3 FNIP1 inhibits tumor growth and lung metastasis in vivo

BALB/c nude mice were injected subcutaneously with 3×106 FNIP1 vector or OE HCT116 cells in the right retro-axillary area. See also Figures S2A and S2B.

(A–C) The effect of FNIP1-overexpressing cells on the xenograft model was assessed by tumor sizes, growth curves, and tumor weights (n = 5). See also Figures S2C–S2E.

(D and E) IHC was performed to evaluate the FNIP1 and Ki-67 expression in xenografts, and Ki-67 positive cells were quantified (n = 5). Scale bar: 100 μm. See also Figures S2F and S2G.

(F and G) Representative images of lung specimens with CRC lung metastases in nude mice; the number of metastatic tumor nodules on the lung surface was counted (n = 5).

(H) Representative H&E staining images of lung metastasis from HCT116 cells. Scale bar: 200 μm. Data are represented as mean ± SD. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Two-way ANOVA with Tukey’s test for (B). Two-tailed Student’s t test for (C–G).

In addition, we further explored whether FNIP1 affects distant metastasis of CRC by constructing a nude mouse CRC lung metastasis model. Briefly, HCT116 cells were injected into the tail vein of nude mice. The results showed that FNIP1 knocked out HCT116 cells formed more metastatic tumor nodules in the lungs of nude mice compared to the control group (Figures 3F–3H). Our results suggest that FNIP1 deficiency promotes CRC lung metastasis.

FNIP1 regulates the activity of CRC-related signaling pathways

To investigate the possible mechanisms by which FNIP1 plays a role in CRC, we analyzed the relationship between FNIP1 and CRC-associated signaling pathway proteins on the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database (STRING: https://cn.string-db.org/). The results showed that FNIP1 may be related to AKT, STAT3, MAPK, and other signaling pathway proteins (Figure 4A).Figure 4 FNIP1 regulates the phosphorylation of AKT and STAT3 pathways in CRC cells

(A) The STRING database (STRING: https://cn.string-db.org/) was used to analyze the relationship between FNIP1 and CRC-associated signaling pathway proteins.

(B and C) Phosphorylation of STAT3, AKT, p38, and ERK in CRC cells was detected by western blotting when FNIP1 was knocked out or over-expressed (n = 3).

(D and E) Statistical analysis of the western blot bands showed significant changes of STAT3 and AKT phosphorylation levels both in HCT116 and SW480 cells (n = 3).

(F) Statistical analysis of the western blot bands showed significant changes of p38 phosphorylation levels in SW480 but not HCT116 cells (n = 3).

(G) Statistical analysis of the western blot bands showed no significant changes of ERK phosphorylation levels both in HCT116 and SW480 cells (n = 3).

(H–K) Western blotting was used to analyze the effects of MK2206 on AKT phosphorylation.

(L–M) CCK-8 was used to assay the proliferation of FNIP1 expressed or absent SW480 and HCT116 cells. The cells were treated with or without MK2206 (5μM) for 24, 48, 72, and 96 h ∗Indicates comparisons of the WT group with the KO-FNIP1 group, the vector group with the OE-FNIP1 group, and the WT + DMSO group with the KO-FNIP1+DMSO group. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. #Comparison between the KO-FNIP1+DMSO group and the KO-FNIP1+MK2206 group. ####p < 0.0001. Data are represented as mean ± SD. Two-tailed Student’s t test for (D–G). One-way ANOVA with Tukey’s test for (F–K). Two-way ANOVA with Tukey’s test for (L and M).

The AKT, STAT3, MAPKp38, and ERK signaling pathways are recognized as key contributors to CRC genesis and outcome.6,16,17,18,19,20 Considering the antitumor role of FNIP1 in CRC progression, we investigated whether FNIP1 participates in the regulation of these pathways.

Western blot analysis revealed that FNIP1 deficiency significantly elevated p-STAT3 and p-AKT levels in HCT116 and SW480 cells, whereas FNIP1 overexpression inhibited these levels (Figures 4B–4E). The expression of p-p38 and p-ERK was not significantly affected (Figures 4B, 4C, 4F, and 4G). The regulation of AKT by FNIP1 was consistent with previous reports.12

We next investigated the effect of the AKT phosphorylation inhibitor MK2206 on the proliferation of FNIP1-KO CRC cells. The results showed that MK2206 significantly inhibited AKT phosphorylation induced by FNIP1 knockout in HCT116 and SW480 cells (Figures 4H–4K), and reversed the increased proliferation caused by FNIP1 knockout in HCT116 cells (Figure 4L), but did not reverse the increased proliferation promoted by FNIP1 knockout in SW480 cells (Figure 4M). The results suggest that the AKT pathway plays different roles in how FNIP1 affects two types of CRC cells. However, the relationship between p-STAT3 and FNIP1 is currently unknown. Therefore, we next further explored the role of FNIP1 in the regulation of the STAT3 pathway.

Knockout of FNIP1 promotes STAT3 nuclear translocation

Based on our findings, we further investigate how FNIP1 relates to the STAT3 pathways. We analyzed the co-localization of FNIP1 with p-STAT3 by immunofluorescence and found that FNIP1 and p-STAT3 could co-localize in the cytoplasm, suggesting that FNIP1 and p-STAT3 may interact with each other (Figure 5A). Then we further verified that FNIP1 could bind to p-STAT3 in the cytoplasm by co-immunoprecipitation (coIP) in HCT116 cells (Figure 5B).Figure 5 Knockout of FNIP1 promotes STAT3 phosphorylation and nuclear translocation

(A) Representative immunofluorescence images of FNIP1 co-localized with p-STAT3 in the cytoplasm of HCT116 cells. Scale bar: 50 μm.

(B) Representative immunoblot bands of FNIP1 binding to p-STAT3 in HCT116 cells verified by coIP.

(C and D) HCT116 cytoplasmic and nuclear proteins were extracted for p-STAT3 expression analysis using western blotting (n = 3).

(E) The distribution of p-STAT3 in HCT116 cells was shown in the representative immunofluorescence staining images. Scale bar: 50 μm. See also Figure S3A.

(F–H) Western blot analysis was used to analyze the expression levels of FNIP1, p-STAT3, c-Myc, and CCND1 when FNIP1 was knocked out and overexpressed (n = 3). See also Figures S3B–S3E.

(I–L) Cells were treated without or with C188-9 (10 μM) or HJC0152 (20 μM) for 12 h and the protein expressions of FNIP1, p-STAT3, STAT3, c-Myc, and CCND1 were detected by western blotting when FNIP1 was knocked out (n = 3). See also Figures S3F–S3I. Data are represented as mean ± SD. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Two-tailed Student’s t test for (C, D, and F–H). One-way ANOVA with Tukey’s test for (I–L).

STAT3 is a crucial transcription factor that promotes CRC progression by entering the nucleus after phosphorylation in the cytoplasm to regulate oncogenes expression.6 We further investigated whether FNIP1 regulates the nuclear localization of phosphorylated STAT3 in CRC. Western blotting was used to detect cytoplasmic and nuclear p-STAT3, revealing an elevation in both cytoplasmic and nuclear p-STAT3 expression when FNIP1 was knocked out (Figures 5C and 5D). Immunofluorescence staining, tracking the distribution of p-STAT3 in CRC cells, also yielded consistent results (Figures 5E and S3A). These results indicate that FNIP1 can affect the expression and distribution of p-STAT3 in the nucleus and cytoplasm.

Additionally, western blotting results showed significant upregulation and downregulation of c-Myc and CCND1, which are downstream proteins of p-STAT3, in the FNIP1 knockout and overexpressed cells, respectively (Figures 5F–5H, S3B, and S3C). Furthermore, consistent results were detected in FNIP1 knockout and overexpressed subcutaneous tumor tissues of nude mice (Figures S3D and S3E).

These results suggest that FNIP1 may down-regulate p-STAT3 expression in the cytoplasm by binding to p-STAT3 and promoting its dephosphorylation, which in turn leads to a decrease in p-STAT3 entering the nucleus. In contrast, FNIP1 deficiency can promote STAT3 phosphorylation and increase nuclear p-STAT3 levels, contributing to downstream gene expression and CRC progression.

To validate this potential mechanism, we treated CRC cells with C188-9 and HJC0152, both reported as small molecules inhibiting the phosphorylation of STAT3.21,22,23,24,25 The results showed that these two specific inhibitors of p-STAT3 markedly reversed the upregulation of p-STAT3 and its downstream proteins c-Myc and CCND1 caused by FNIP1 knockout (Figures 5I–5L and S3F–S3I).

FNIP1 deficiency accelerates CRC progression via the STAT3 pathway in vitro

To further clarify that FNIP1 inhibits CRC progression by reducing STAT3 pathway activation, we conducted additional verification using the p-STAT3-specific inhibitors C188-9 or HCJC0152 in FNIP1-absent HCT116 and SW480 cells.

The results showed that treatment with p-STAT3 inhibitors reversed the increased proliferation (Figures 6A and 6B, S4A, and S4B) and migration (Figures 6C–6F) in CRC cells induced by FNIP1 absence. Additionally, the p-STAT3 inhibitors reversed the reduced apoptosis caused by FNIP1 knockout (Figures 6G–6J). These findings demonstrate that FNIP1 inhibits CRC progression by mitigating the activation of p-STAT3.Figure 6 p-STAT3-specific inhibitors rescue FNIP1-deficiency induced CRC progression in vitro

(A and B) CCK-8 was used to assay the proliferation of FNIP1-expressed or -absent CRC cells. Cells were treated with or without C188-9 and HJC0152 (5μM and 10μM) for 24, 48, 72, and 96 h (n = 3). See also Figures S4A–S4B.

(C–F) Transwell chambers for migration assays were used to evaluate the migratory ability of CRC cells. Cells were treated with or without C188-9 (10 μM) or HJC0152 (20 μM) for 12 h (n = 3). Scale bar: 100 μm.

(G–J) Cells were treated with or without C188-9 (10 μM) or HJC0152 (20 μM) for 24 h. Then apoptosis was detected by flow cytometry (n = 3). Data are represented as mean ± SD. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Two-way ANOVA with Tukey’s test for (A and B). One-way ANOVA with Tukey’s test for (C–J).

FNIP1 knockout promotes CRC growth via the STAT3 pathway in vivo

To explore the effect of the STAT3 pathway on CRC progression caused by FNIP1 absence in vivo, we constructed a subcutaneous tumor model in nude mice and injected the STAT3 phosphorylation inhibitor HJC0152 intraperitoneally in nude mice. The results showed that the subcutaneous tumor growth rate and tumor weight were significantly higher in the FNIP1-KO group than in the wild-type (WT) group, and the STAT3 inhibitor HJC0152 reversed these effects (Figures 7A–7C). Meanwhile, IHC results showed that p-STAT3 expression was upregulated in tumor tissues knocked out of FNIP1, which was reversed by HJC0152 (Figure 7D). These results suggest that FNIP1 deficiency promotes CRC growth by promoting STAT3 pathway activity.Figure 7 p-STAT3 inhibitor rescues FNIP1 deficiency induced CRC growth in vivo

(A–C) BALB/c nude mice were injected subcutaneously with 3×106 FNIP1 WT or KO HCT116 cells. When the average tumor volume grew to about 50 mm3, mice were treated daily with 7.5 mg/kg of HJC0152 or an equal volume of DMSO solvent by intraperitoneal injection for 27 days. Subcutaneous tumor sizes, tumor weights, and tumor growth curves were measured in each group of nude mice (n = 5).

(D) After intraperitoneal injection with HJC0152 or DMSO in FNIP1 knock-out or control subcutaneous tumor models, IHC was used to detect the FNIP1 and p-STAT3 expression. Representative IHC images of FNIP1 and p-STAT3 expression in subcutaneous tumor tissues of nude mice are presented. Scale bar: 100 μm. Data are represented as mean ± SD. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. One-way ANOVA with Tukey’s test for (B). Two-way ANOVA with Tukey’s test for (C).

FNIP1 protein is negatively correlated with p-STAT3 expression in CRC

Finally, to assess the clinical significance of the findings, we examined the expression of FNIP1 and p-STAT3 in CRC tissues. IHC results showed that p-STAT3 was highly expressed in CRC patients with low FNIP1 expression, whereas p-STAT3 was low expressed in CRC tissues with high FNIP1 expression (Figure 8A). Correlation analysis revealed a negative correlation between FNIP1 and p-STAT3 (Figures 8B and 8C). Furthermore, western blot analysis also showed that FNIP1 and p-STAT3 were negatively correlated in CRC tissues (Figures 8D and 8E). We analyzed IHC staining for FNIP1 and p-STAT3 in xenografts formed by HCT116 cells and found that p-STAT3 protein levels were also lower in tumor tissues from the FNIP1 overexpression group than in the vector group (Figure 8F). Overall, these data demonstrate that FNIP1 was negatively correlated with p-STAT3 expression in CRC.Figure 8 FNIP1 is negatively correlated with p-STAT3 expression in CRC

(A) IHC assay of FNIP1 and p-STAT3 protein expression in CRC tissues was performed (n = 40). Representative images of FNIP1 and p-STAT3 expression in FNIP1 low expression cases and FNIP1 high expression cases are presented. Scale bar: 100 μm.

(B) Semi-quantitative scoring method (using a scale from 0 to 12) was used to quantify the scores of FNIP1 and p-STAT3 IHC staining and analyze the correlation between FNIP1 and p-STAT3 expression in CRC tissues by Fisher’s exact test (n = 40).

(C) Correlation between FNIP1 and p-STAT3 expression in CRC was examined by Pearson’s correlation analysis based on IHC scores (n = 40).

(D) Western blotting was used to determine FNIP1 and p-STAT3 protein expression in CRC tissues (n = 37). Representative western blot images of FNIP1 and p-STAT3 expression are presented.

(E) Pearson’s correlation analysis was used to analyze the correlation between FNIP1 and p-STAT3 expression in CRC tissues based on the results of western blot semi-quantitative analysis (n = 37).

(F) Representative IHC images of FNIP1 and p-STAT3 expression in mouse xenografts formed by HCT116 cells. Scale bar: 100 μm.

(G) A model diagram summarizing our findings. FNIP1 prevents STAT3 phosphorylation and reduces p-STAT3 nuclear translocation and oncogene expression, thereby inhibiting the development of CRC. Fisher’s exact test for (B). Pearson’s correlation analysis for (C–E).

Discussion

In the present study, we observed a substantial downregulation of FNIP1 in CRC tissues. Lower FNIP1 expression in CRC patients correlated with worse OS and DSS, suggesting its potential as an independent prognostic biomarker for CRC. FNIP1 deficiency was linked to CRC progression through enhanced STAT3 phosphorylation and increased p-STAT3 nuclear localization. Inhibition of STAT3 phosphorylation reversed the effects of FNIP1 deficiency. These findings underscore the potential of FNIP1 as a target for therapeutic intervention and prognostic biomarker for CRC.

FNIP1 is involved in various cellular physiopathological processes, including redox stress responses,26,27 energy sensing,28 and cell development and differentiation,29,30 rendering it a highly critical functional protein. FNIP1 has been implicated in several types of cancer. For example, FNIP1 and its homologous protein folliculin interacting protein 2 (FNIP2) play critical roles in suppressing kidney tumors in cooperation with folliculin (FLCN).31 In breast cancer, FNIP1 expression is downregulated and more pronounced in the most aggressive triple-negative breast cancers than in the less aggressive tubular luminal subtype.13 In pancreatic cancer, MEF2 maintains MTORC1 activation and tumor progression through direct regulation of FNIP1 and FNIP2.14 These studies suggest that FNIP1 plays an anti- or pro-cancer role in different types of tumors. Currently, there are limited studies of FNIP1 in CRC. It has been shown that 6% of MSI-H CRC and 5.9% of MSI-H gastric cancer patients carry a transcoding mutation in FNIP1, which may lead to the inactivation of its tumor suppressor function by premature termination of its translation.32 However, the specific roles of FNIP1 in CRC remain poorly understood.

Our findings indicate that FNIP1 expression is significantly lower in CRC than in the normal and adenomatous tissues, but not significantly different from CRC paracancerous tissues. Our data also imply that low FNIP1 expression adversely affects the prognosis of CRC patients. We also demonstrate the anti-cancer role of FNIP1 in CRC by in vitro and in vivo experiments. However, FNIP1 was not significantly different between normal, paracancerous, and adenomatous tissues. These results suggest that FNIP1 may primarily influence the progression of CRC. Nevertheless, the association of low FNIP1 expression with the initiation of CRC remains debatable, given the numerous CRC-associated precancerous lesions, including familial intestinal polyposis and ulcerative colitis, with FNIP1 expression in these tissues yet unknown.

The pathogenesis of CRC is unclear and may involve activating signaling pathways, such as those of STAT3, AKT, and MAPK.7,33,34 We found that FNIP1 may be associated with STAT3, AKT, and MAPK pathways by bioinformatics analysis. Consistent with previous study findings, our data indicated that FNIP1 inhibited the phosphorylation of AKT,12 with no significant effect on the phosphorylation of ERK in SW480 and HCT116 cells.12 The use of the AKT inhibitor MK2206 reversed the overproliferation in HCT116 cells due to FNIP1 deficiency but not in SW480 cells. This discrepancy in AKT function may be attributed to the distinct origins of these two cell lines, with HCT116 derived from colon carcinoma and SW480 derived from rectal carcinoma. The level of differentiation and the metabolic environment of the two types of CRC cells are different. Therefore, our results suggest that CRCs originating from different sites may necessitate different therapeutic options.

STAT3 is over-activated in many human cancers, including CRC.35 Inhibition of STAT3 activation reduces the intrinsic proliferation of tumor cells and improves the tumor immune microenvironment.24,36,37 However, there are still many challenges in treating cancer by directly targeting STAT3.38 Therefore, developing new therapies by targeting upstream or downstream components of STAT3 may be a promising approach.39 We observed that FNIP1 is bound to p-STAT3, which may induce p-STAT3 dephosphorylation in CRC cells. Moreover, FNIP1 knockout promoted STAT3 phosphorylation and translocation to the nucleus, ultimately leading to CRC progression. Application of STAT3-specific inhibitors could rescue CRC progression caused by FNIP1 deletion. We also demonstrated a negative correlation between FNIP1 and phosphorylated STAT3 in CRC tissues and mouse xenografts. Collectively, these findings may make the FNIP1-STAT3 pathway a potential target for CRC therapy.

Based on these findings, our study demonstrates that FNIP1 is downregulated in CRC and correlates with the survival prognosis of CRC patients. Downregulated FNIP1 promotes CRC tumor growth and migration through the activation of p-STAT3 and its nuclear localization. These functions can be effectively reversed by selective p-STAT3 inhibitors. These findings suggest that FNIP1 holds promise as a potential therapeutic target and prognostic biomarker for CRC.

Limitations of the study

A small sample of CRC tissues was collected for validation in this study, and a larger sample group may be needed for validation to reduce the effect of sampling error.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Yu Zhou (ahdg2022@gdmu.edu.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

This paper does not report the original code.

This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in the key resources table.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

The author(s) have reported that there is no funding for the work in this article.

Author contributions

Conceptualization, Y.Z. and S.Y.; methodology, G.Z., Y.Z., S.Y., and X.C.; formal analysis, G.Z., Y.Z., and X.C.; investigation, G.Z., X.C, C.Y., L.C., N.C., G.Y., S.W., H.W., and Y.L.; writing – original draft, G.Z. and X.C.; writing – review & editing, G.Z., X.C., Y.Z., and S.Y.; funding acquisition, Y.Z.; resources, C.Y., L.C., N.C., and G.Y.; supervision, Y.Z., S.Y., and C.Y.

Declaration of interests

The authors declare that they have no competing interests.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER	
Antibodies	
	
Rabbit monoclonal anti-FNIP1	abcam	Cat#ab134969; RRID: AB_3170229	
Rabbit monoclonal anti-FNIP1	LifeSpan BioSciences	Cat#LS-C677968; RRID: AB_3166176	
Rabbit monoclonal anti-FNIP1	antibodies-online	Cat#ABIN5066839; RRID: AB_3170227	
Rabbit anti-FNIP1	ImmuQuest	Cat#IQ351; RRID: AB_2278571	
Rabbit monoclonal anti-Phospho-STAT3 (Tyr705)	Cell Signaling Technology	Cat#9145S; RRID: AB_2491009	
Mouse monoclonal anti-Phospho-STAT3 (Tyr705)	Santa Cruz Biotechnolog	Cat#sc-81523; RRID: AB_1129708	
Rabbit monoclonal anti-STAT3	Cell Signaling Technology	Cat#4904S; RRID: AB_331269	
Rabbit monoclonal anti-AKT	Cell Signaling Technology	Cat#9272; RRID: AB_329827	
Rabbit monoclonal anti-Phospho-AKT (Ser473)	Cell Signaling Technology	Cat#4060S; RRID: AB_2315049	
Rabbit monoclonal anti-p44/42 MAPK (ERK1/2)	Cell Signaling Technology	Cat#4695S; RRID: AB_390779	
Rabbit monoclonal anti-Phospho-p44/42 MAPK (ERK1/2) (Thr202/Tyr204)	Cell Signaling Technology	Cat#4370S; RRID: AB_2315112	
Rabbit monoclonal anti-Phospho-p38 MAPK (Thr180/Tyr182)	Cell Signaling Technology	Cat#4511S; RRID: AB_2139682	
Rabbit monoclonal anti-p38 MAPK	Cell Signaling Technology	Cat#9212S; RRID: AB_330713	
Rabbit monoclonal anti-α-Tubulin	Affinity	Cat#AF7010; RRID: AB_2839418	
Rabbit monoclonal anti-GAPDH	Affinity	Cat#AF7021; RRID: AB_2839421	
Rabbit monoclonal anti-ACTIN	Affinity	Cat#AF7018; RRID: AB_2839420	
Rabbit monoclonal anti-Cyclin D1	Affinity	Cat#AF0931; RRID: AB_2835325	
Rabbit monoclonal anti-c-Myc	Cell Signaling Technology	Cat#5605S; RRID: AB_1903938	
Mouse monoclonal anti-Ki-67	Santa Cruz Biotechnolog	Cat#sc-23900; RRID: AB_627859	
Goat Anti-Rabbit IgG (H + L) HRP	Affinity	Cat#S0001; RRID: AB_2839429	
Goat Anti-Mouse IgG (H + L) HRP	Affinity	Cat#S0002; RRID: AB_2839430	
Alexa Fluor 647-labeled Goat Anti-Rabbit IgG(H + L)	Beyotime	Cat#A0468; RRID:AB_2936379	
Alexa Fluor 488-labeled Goat Anti-Mouse IgG(H + L)	Beyotime	Cat#A0428; RRID:AB_2893435	
	
Bacterial and virus strains	
	
FNIP1-overexpressing lentivirus (OE-FNIP1)	Genechem Co.	Cat#GOSL0268651	
Vector lentivirus	Genechem Co.	Cat#LVCON254	
Cas9 lentivirus	Genechem Co.	Cat#GPL2002A	
FNIP1-SgRNA lentivirus	Genechem Co.	Cat#GCEL0280824	
SgRNA negative control lentivirus	Genechem Co.	Cat#LVCON247	
	
Biological samples	
	
Adult colorectal tissue	Tissue Bank of Gastroenterology Laboratory of the Affiliated Hospital of Guangdong Medical University	N/A	
	
Chemicals, peptides, and recombinant proteins	
	
Lipofectamine™ 2000 Reagent	Invitrogen	Cat#1168019	
DAPI	Beyotime	Cat#C1006	
MK2206	MedCheExpress	Cat#HY-108232	
C-1889	Selleck	Cat#S8605	
HJC0152	Selleck	Cat#S8561	
HJC0152	MedCheExpress	Cat#HY-100602	
	
Critical commercial assays	
	
RNAiso Plus	Takara	Cat#9109	
PrimeScript™ RT Master Mix	Takara	Cat#RR036A	
TB Green® Premix Ex Taq™ (Tli RNaseH Plus)	Takara	Cat#RR420A	
Cell Counting Kit-8	Dojindo	Cat#CK04	
Annexin V, FITC Apoptosis Detection Kit	Dojindo	Cat#AD10	
Rabbit two-step detection kit (rabbit-enhanced polymer detection system)	ZSGB-Bio	Cat#PV-9001; RRID: AB_2868452	
DAB Kit	ZSGB-Bio	Cat#ZLI-9017	
	
Deposited data	
	
TCGA-COAD	National Institutes of Health (NIH)	https://portal.gdc.cancer.gov/projects/TCGA-COAD	
TCGA-READ	National Institutes of Health (NIH)	https://portal.gdc.cancer.gov/projects/TCGA-READ	
FNIP1 IHC information	The Human Protein Atlas (HPA)	https://www.proteinatlas.org/search/FNIP1	
	
Experimental models: Cell lines	
	
Human: HCT116 cells	Cell Bank of the Chinese Academy of Sciences	RRID: CVCL_C97566	
Human: SW480 cells	Cell Bank of the Chinese Academy of Sciences	RRID: CVCL_C97567	
	
Experimental models: Organisms/strains	
	
Mouse: BALB/cNj-Foxn1nu/Gpt	GemPharmatech Co., Ltd	Strain NO. D000521	
	
Oligonucleotides	
	
siRNA targeting sequence: Si-FNIP1_001: GAACCAC
CTTTGCTATCGT	RiboBio	Cat#stB0005794A	
siRNA targeting sequence: Si-FNIP1_002: GCAGGAC
CAAAGAGATACA	RiboBio	Cat#stB0005794B	
negative control siRNA sequences	RiboBio	Cat#siN0000001-1-5	
sgRNA targeting sequence: GATATACAATCAGTCGAATC	Genechem Co.	N/A	
Primer: FNIP1 Forward: TGCATTGTCAGAGTCAGGCT	This paper	N/A	
Primer: FNIP1 Reverse: TGGGCAGCCTCACAAGAAAA	This paper	N/A	
Primer: GAPDH Forward: CGAGA
TCCCTCCAAAATCAA	This paper	N/A	
Primer: GAPDH Reverse: TTCAC
ACCCATGACGAACAT	This paper	N/A	
	
Software and algorithms	
	
ImageJ	National Institutes of Health (NIH)	https://imagej.net/ij/	
GraphPad Prism 8	GraphPad Software	https://www.graphpad.com	
	
Other	
	
Laser scanning confocal focus microscope	Olympus	FV3000	
Xiantao academic tools	www.helixlife.cn	https://www.xiantaozi.com/products	

Experimental model and study participant details

Human participants

We collected colorectal tissues from 233 subjects who underwent colonoscopy at the Affiliated Hospital of Guangdong Medical University (Guangdong, China) between 2022 and 2023. Although all participants were of Chinese nationality, specific data on ancestry, race and ethnicity were not collected, as these were not part of the inclusion and exclusion criteria. This may lead to limitations in generalizing the findings of the study. The gender and age characteristics of the participants are shown in Table S1. The study was approved by the Clinical Research Ethics Committee of the Affiliated Hospital of Guangdong Medical University (No. KT2023-141-03), and informed consent was obtained from the participants.

Animals

All animal experiments were approved by the Animal Ethics Committee of the Affiliated Hospital of Guangdong Medical University (No. AHGDMU-LAC-B-202207-0004. Four-week-old female BALB/c nude mice (BALB/cNj-Foxn1nu/Gp) were purchased from GemPharmatech Co., Ltd (Guangdong, China) and maintained in the Affiliated Hospital of Guangdong Medical University.

Cells

Human CRC cell lines (HCT116 and SW480) were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). Cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum and placed in a humidified incubator at 37°C with 5% CO2.

Method details

Collection and processing of data from public databases

RNA-seq data from TCGA gene expression database (https://portal.gdc.cancer.gov) were analyzed using Xiantao academic tools (https://www.xiantaozi.com/products) to analyze the survival curves and prognostic potential of FNIP1 in CRC patients. The protein expression of FNIP1 in human normal and CRC tissues was analyzed using the HPA (https://www.proteinatlas.org/) database. STRING (https://cn.string-db.org/) database was used to predict proteins that may interact with FNIP1.

RNA extract and qRT-PCR

Total RNA was extracted using RNAiso Plus (Takara, Dalian, China). cDNA was then synthesized using PrimeScript RT Master Mix (Takara, Dalian, China). Real-time fluorescence quantitative PCR analysis was conducted on a LightCycler 480 II system (Roche Diagnostics, Switzerland) utilizing TB Green Premix Ex Taq II (Takara, Dalian, China).

Cell treatment

FNIP1-overexpressing lentivirus (OE-FNIP1) and C9-Easy lentivirus (knockout, double vector, FNIP1) and their respective negative control vector lentivirus were purchased from Genechem Co. (Shanghai, China). According to the manufacturer’s protocols, CRC cell lines were infected with the above lentiviral vectors and cultured in a medium containing puromycin (2 μg/mL) or G418 (700 μg/mL) for 2 weeks to screen for cell lines stably overexpressing or depleting FNIP1 for subsequent cellular experiments.

Human FNIP1 small interfering RNA (si-FNIP1) and negative control siRNA (si-NC, cat. no. siN0000001-1-5) were purchased from RiboBio (Guangzhou, China). The siRNAs (50nM) were transfected into CRC cells using Lipofectamine 2000 reagent (Thermo Fisher Scientific Inc, USA).

Western Blot analysis

Western blotting was conducted as previously mentioned.40 All the Western blot experiments were repeated at least three times. Specific primary antibodies against FNIP1 (ab134969, abcam, UK), p-STAT3 (9145S, Cell Signaling Technology, USA), STAT3 (4904S, Cell Signaling Technology, USA), AKT (9272, Cell Signaling Technology, USA), p-AKT (4060S, Cell Signaling Technology, USA), ERK (4695S, Cell Signaling Technology, USA), p-ERK (4370S, Cell Signaling Technology, USA), p38 (9212S, Cell Signaling Technology, USA), p-p38 (4511S, Cell Signaling Technology, USA), α-Tubulin (AF7010, Affinity, USA), GAPDH (AF7021, Affinity, USA), Cyclin D1 (AF0931, Affinity, USA), c-Myc (5605S, Cell Signaling Technology, USA), and ACTIN (AF7018, Affinity, USA) were used for Western blotting.

Cell proliferation, migration, and apoptosis assay

Cell proliferation ability was detected using the Cell Counting Kit-8 (CCK-8) assay (Dojindo, Japan). 4×103 CRC cells were seeded in 96-well plates. Cells were treated with or without C188-9 (5μM) (Selleck, USA) and HJC0152 (10μM) (Selleck, USA) and cultured for 24, 48, 72 and 96 h, respectively. After incubation with CCK-8 reagent for 1h at 37°C, the 450nm OD values were measured by spectrophotometry to analyze the proliferation capacity of the cells.

Cell migration was assessed using the 8 μm pore size transwell insert modified culture system (Corning Incorporated, USA). The CRC cells were treated with or without C188-9 (10μM) (Selleck, USA) and HJC0152 (20μM) (Selleck, USA) and cultured for 12h. Then 1×105 cells were seeded in the upper chambers with serum-free 1640 medium. After incubating for 24 h at 37°C with 5% CO2, the cells were then fixed with methanol and stained with crystal violet. The cells that stayed in the upper chamber were carefully removed. The microscope was used to take images of cells traversing the pores. ImageJ software was used to calculate the cell number that had entered the pores.

Apoptosis was detected using the Annexin V-FITC/propidium iodide (PI) Apoptosis Detection Kit (Dojindo, Japan). Cells were collected after treated with or without the p-STAT3 inhibitors C188-9 (10μM) (Selleck, USA) and HJC0152 (20μM) (Selleck, USA) for 24h. According to the manufacturer’s protocols, all cells were collected and resuspended by Annexin V binding solution. Then cells were stained with Annexin V-FITC and PI at room temperature for 15 min and then analyzed by flow cytometry (BD, FACSCantoTM II). The total apoptosis rate was used to measure the level of apoptosis. Specifically, we calculated the total apoptosis rate by summing the proportions of cells in the Q2 (representing late apoptosis) and Q3 (representing early apoptosis) regions.

Animal work

For the subcutaneous xenograft tumor model, the mice were randomly divided into the control group (vector or WT group), FNIP1 overexpression group (OE-FNIP1), and FNIP1 knockout group (KO-FNIP1). For the subcutaneous xenograft tumor model treated by p-STAT3 inhibitor, the mice were randomly divided into the WT + DMSO group, KO-FNIP1+DMSO group, WT + HJC0152 group, and KO-FNIP1+HJC0152 group. When the average tumor volume was approximately 50 mm3, HJC0152 (7.5 mg/kg) was injected intraperitoneally daily in the treatment group of mice, and solvent containing an equal volume of DMSO was injected intraperitoneally in the control group of mice. The stable HCT116 cells were suspended in PBS (3 × 107 cells/mL). The cell suspension (3 × 106 cells/100 μL) was then injected subcutaneously into the right retro-axillary region of the mice. The longest(a) and shortest(b) diameters of the subcutaneous tumors in mice were measured every three days starting on the sixth day after injection. The tumor volume was calculated every 3 days using the formula V = a × (b × b)/2.

For the CRC lung metastasis model, mice were randomly divided into the WT group and the KO-FNIP1 group. Mice were injected with 1 × 106 WT or FNIP1-KO HCT116 cells in the tail vein. mice were euthanized after 40 days. Lung tissues were collected and fixed in phosphate-buffered formalin for further hematoxylin and eosin (H&E) staining. The number of metastatic cancer nodules on the lung surface was counted.

Immunohistochemistry

IHC staining was carried out as previously described.41 Heat-induced epitope retrieval was achieved using citrate buffer (pH 6.0). Anti-FNIP1 antibody (LS-C677968, LifeSpan BioSciences, USA), anti-p-STAT3 antibody (9145S, Cell Signaling Technology, USA), and anti-Ki-67 antibody (sc-23900, Santa Cruz Biotechnology) were used as the primary antibodies, diluted at 1:400, 1:50 and 1:200, respectively. Tissue sections not incubated with primary antibodies were used as negative controls.

The IHC staining scores of FNIP1 and p-STAT3 were evaluated by combining the percentage of cells with the staining intensity and being dependent on the IRS (immunoreactivity score, IRS). The intensity of FNIP1 and p-STAT3 immunostaining were scored as 0–3 (0, negative; 1, weak; 2, moderate; 3, strong); the percentage of immunoreactivity cells was graded as 1 (0–25%), 2 (26–50%), 3 (51–75%), and 4 (76–100%). Relied on the IRS, the levels of FNIP1 and p-STAT3 expression were categorized as low (IRS: 0–4) and high (IRS: 5–12) expression.

Immunofluorescence staining

CRC cells were fixed with immunostaining fixative (Beyotime, Shanghai, China). Cells were permeabilized with 0.1% Triton X-100 (Beyotime, Shanghai, China) before BSA blocking. Anti-p-STAT3 (9145S, Cell Signaling Technology, USA) (1:200), anti-p-STAT3 (sc-81523, Santa Cruz Biotechnology, USA) (1:50), and anti-FNIP1(ABIN5066839, antibodies-online, Germany) (1:400) were used as the primary antibody and incubated with cells overnight at 4°C. The next day, the cells were incubated with goat anti-rabbit Alexa Fluor 647-conjugated secondary antibody (A0468, Beyotime, Shanghai, China) (1:200) or goat anti-mouse Alexa Fluor 488-conjugated secondary antibody (A0428, Beyotime, China) (1:200) for 1 h at room temperature. The cells were stained with DAPI (Beyotime, Shanghai, China) for 5 min and then fixed with an anti-fluorescence quencher (Beyotime, Shanghai, China). The cells were then photographed using a 60x fluorescence microscope (Olympus Corp.).

Immunoprecipitation (IP) assay

Total protein from untreated HCT116 cells was harvested and incubated overnight with anti-FNIP1(IQ351, ImmuQuest, UK) or anti-p-STAT3 (9145S, Cell Signaling Technology, USA). Protein A + G Agarose Beads (P2012, Beyotime, China) were then added and incubated for 2h. The immune complexes were then centrifuged and washed. FNIP1 or p-STAT3 protein was detected by Western blotting.

Quantification and statistical analysis

Xiantao academic tools (https://www.xiantaozi.com/products) was used to analyze the TCGA data. GraphPad Prism 8 software (GraphPad Software, Inc.) was used for statistical analysis. The unpaired t-test was used to compare two groups, and ANOVA (with Tukey’s multiple comparison test) was used to compare multiple groups. Correlation analysis was performed by Fisher’s exact test and Pearson’s correlation analysis. Data are expressed as mean ± standard deviation (SD) and are considered statistically significant when p < 0.05.

Supplemental information

Document S1. Figures S1–S4 and Table S1

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2024.110730.
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