A FOXC2 inhibitor, MC-1-F2, as a therapeutic candidate for targeting EMT in castration-resistant prostate cancer.

Androgen deprivation therapy (ADT) is the major treatment option for advanced prostate cancer. However, prostate cancer can develop into androgen-independent castration-resistant prostate cancer (CRPC) which is resistant to ADT. An alternative treatment strategy for CRPC can be targeting the epithelial-mesenchymal transition (EMT). EMT is governed by a series of transcription factors of which forkhead box protein C2 (FOXC2) is a central mediator. Our previous research into the inhibition of FOXC2 in breast cancer cells lead to the discovery of MC-1-F2, the first direct inhibitor of FOXC2. In current study on CRPC, MC-1-F2 has shown a decrease in mesenchymal markers, inhibition of cancer stem cell (CSC) properties and decrease in invasive capabilities of CRPC cell lines. We have also demonstrated a synergistic effect between MC-1-F2 and docetaxel treatments, leading to a decrease in docetaxel dosage, suggesting the possible combination therapy of MC-1-F2 and docetaxel for the effective treatment of CRPC.

Homology modeling of Forkhead box protein C2: identification of potential inhibitors using ligand and structure-based virtual screening.

Overexpression of Forkhead box protein C2 (FOXC2) has been associated with different types of carcinomas. FOXC2 plays an important role in the initiation and maintenance of the epithelial-mesenchymal transition (EMT) process, which is essential for the development of higher-grade tumors with an enhanced ability for metastasis. Thus, FOXC2 has become a therapeutic target for the development of anticancer drugs. MC-1-F2, the only identified experimental inhibitor of FOXC2, interacts with the full length of FOXC2. However, only the DNA-binding domain (DBD) of FOXC2 has resolved crystal structure. In this work, a three-dimensional (3D) structure of the full-length FOXC2 using homology modeling was developed and used for structure-based drug design (SBDD). The quality of this 3D model of the full-length FOXC2 was evaluated using MolProbity, ERRAT, and ProSA modules. Molecular dynamics (MD) simulation was also carried out to verify its stability. Ligand-based drug design (LBDD) was carried out to identify similar analogues for MC-1-F2 against 15 million compounds from ChEMBL and ZINC databases. 792 molecules were retrieved from this similarity search. De novo SBDD was performed against the full-length 3D structure of FOXC2 through homology modeling to identify novel inhibitors. The combination of LBDD and SBDD helped in gaining a better insight into the binding of MC-1-F2 and its analogues against the full length of the FOXC2. The binding free energy of the top hits was further investigated using MD simulations and MM/GBSA calculations to result in eight promising hits as lead compounds targeting FOXC2.

FOXC2/ADAM12-dependent radiosensitivity of head and neck squamous cell carcinoma cells.

BACKGROUND: Radiotherapy greatly benefits patients with tumors, but not all patients show favorable treatment response. This study investigated the impact of forkhead box protein C2 (FOXC2)-mediated a disintegrin and metalloprotease 12 (ADAM12) on the radiosensitivity of head and neck squamous cell carcinoma (HNSCC). METHODS: After transfection and ionizing radiation, the biological activities of HNSCC cells were assessed. The relationship between ADAM12 and FOXC2 was verified. A xenograft model was used to evaluate the effect of FOXC2 knockdown on HNSCC growth in the context of radiation therapy. RESULTS: FOXC2 and ADAM12 were upregulated in irradiated CAL-27 and HN4 cells. Knockdown of FOXC2 suppressed the malignant behaviors of CAL-27 and HN4 cells and inhibited the growth of transplanted tumors in nude mice. FOXC2 could bind ADAM12 promoter. Overexpression of ADAM12 reversed the promotion of FOXC2 silencing on the radiosensitivity of HNSCC cells. CONCLUSIONS: FOXC2 regulates the radiosensitivity of HNSCC by targeting ADAM12.

Functional polymorphisms in FOXC2 gene and Epithelial ovarian Cancer susceptibility in Chinese population.

BACKGROUND: Epithelial ovarian cancer (EOC) is highly lethal gynecological cancer. Forkhead Box Protein C2 (FOXC2) promotes occurrence and development of various malignant tumors. The present study is aimed at exploring the correlation between the polymorphism of FOXC2 and epithelial ovarian cancer susceptibility in Chinese Han population. METHODS: A case-control design was used to verify the association between FOXC2 polymorphisms and epithelial ovarian cancer. The genotyping was performed using Taqman® SNP Genotyping kit by qRT-PCR. The genetic variants including rs3751794 C > T, rs1035550 A > G, rs4843163 C > G and rs4843396 C > T in FOXC2 gene were analyzed. The strength of the associations was detected using odds ratios and 95% confidence intervals. Stratification analyses showed the association between the FOXC2 gene polymorphisms rs3751794 C > T, rs4843163 C > G and rs4843396 C > T with epithelial ovarian cancer susceptibility in terms of age, metastasis status, clinical stage, pathological grade, pregnant times, pausimenia, and the expression of ER, PR, wild p53 and mutant p53. RESULTS: Rs3751794 C > T (P = 0.0016), rs4843163 C > G (P < 0.0001) and rs4843396 C > T (P < 0.0001) were significantly associated with increased epithelial ovarian cancer risk. In stratification analyses,rs3751794 C > T, was identified to be dominant in no metastasis patients, clinical stage 4 group, middle grade pathological stage, pregnant time over 3 patients, post-menopause women, strong wild type p53 expression; rs4843163 C > G was dominant in high grade clinical stage, high grade pathological stage, post-menopause women, strong ER expression group and no mutant p53 expression group; rs4843396 C > T was dominant in high grade clinical stage, high grade pathological stage, strong ER expression group. The rs1035550 A > G was not related to epithelial ovarian cancer susceptibility. CONCLUSIONS: The results of the current study verified that FOXC2 gene polymorphisms were associated with increased epithelial ovarian cancer risk and suggested that FOXC2 gene polymorphisms might be a potential biomarker for epithelial ovarian cancer susceptibility.

FOXC2 Promotes Oxaliplatin Resistance by Inducing Epithelial-Mesenchymal Transition via MAPK/ERK Signaling in Colorectal Cancer.

BACKGROUND: Chemoresistance is a major obstacle to improving the survival rate of colorectal cancer (CRC) patients. Forkhead box protein C2 (FOXC2), a member of the forkhead box (Fox) transcription factor family, is reported to be an important regulator of epithelial-to-mesenchymal transition (EMT) and plays a key role in tumor progression. However, little is known about the effects of FOXC2 on oxaliplatin (OXA) resistance in CRC. METHODS: OXA-resistant cells were generated from HCT116 cells. CCK-8, colony formation, flow cytometry and Transwell assays were used to compare the characteristics of OXA-resistant HCT116/OXA cells and the corresponding parental HCT116 cells. The expression of FOXC2 was confirmed by qRT-PCR and Western blotting in HCT116/OXA and HCT116 cells. Gain- and loss-of-function assays were performed to evaluate the effects of FOXC2 on OXA sensitivity and EMT in HCT116/OXA and HCT116 cells both in vitro and in vivo, and the possible molecular mechanisms were investigated. RESULTS: The relative expression of FOXC2 was significantly increased in HCT116/OXA cells compared with the parental HCT116 cells. Upregulation of FOXC2 in HCT116 cells reduced OXA sensitivity and promoted EMT. However, knockdown of FOXC2 in HCT116/OXA cells markedly increased the in vitro and in vivo sensitivity of HCT116/OXA cells to OXA by regulating EMT progression. Furthermore, FOXC2 activated MAPK/ERK signaling, and blockade of ERK attenuated FOXC2-induced EMT and FOXC2-enhanced OXA resistance. CONCLUSION: FOXC2 induced EMT to promote oxaliplatin resistance by activating the MAPK/ERK signaling pathway. FOXC2 may be a potential therapeutic target for overcoming OXA resistance in human CRC.

Meta-analysis of the prognostic significance of FOXC2 in various tumors.

OBJECTIVE: Many studies have focused on correlations between forkhead box protein C2 (FOXC2) and various tumors but discrepant results have been reported. Thus, we conducted this meta-analysis to assess the prognostic role of FOXC2 in tumors. METHODS: Four electronic databases (PubMed, Embase, Web of Science, and SinoMed) were screened through September 2019. RESULTS: The final analysis included 15 reports and 2115 patients; results suggested that cancer patients with FOXC2 had worse overall survival (hazard ratio 2.14, 95% confidence interval (CI) 1.74-2.64), cancer-specific survival (hazard ratio 2.65, 95% CI 1.44-4.89), and disease-free survival (hazard ratio 1.93, 95% CI 1.49-2.50) than patients lacking FOXC2. CONCLUSIONS: The presence of FOXC2 was associated with poor survival in cancer patients. FOXC2 could be a promising prognostic marker in the future.

Risk Prediction Tool for Aggressive Tumors in Clinical T1 Stage Clear Cell Renal Cell Carcinoma Using Molecular Biomarkers.

Some early-stage clear cell renal cell carcinomas (ccRCCs) of ≤7 cm are associated with a poor clinical outcome. In this study, we investigated molecular biomarkers associated with aggressive clinical T1 stage ccRCCs of ≤7 cm, which were used to develop a risk prediction tool toward guiding the decision of treatment. Among 1069 nephrectomies performed for ccRCC of ≤7 cm conducted between January 2008 and December 2014, 177 cases with available formalin-fixed paraffin-embedded tissue were evaluated. An aggressive tumor was defined as a tumor exhibiting synchronous metastasis, recurrence, or leading to cancer-specific death. Expression levels of six genes (FOXC2, CLIP4, PBRM1, BAP1, SETD2, and KDM5C) were measured by reverse-transcription polymerase chain reaction (qRT-PCR) and their relation to clinical outcomes was investigated. Immunohistochemistry was performed to validate the expression profiles of selected genes significantly associated with clinical outcomes in multivariate analysis. Using these genes, we developed a prediction model of aggressive ccRCC based on logistic regression and deep-learning methods. FOXC2, PBRM1, and BAP1 expression levels were significantly lower in aggressive ccRCC than non-aggressive ccRCC both in univariate and multivariate analysis. The immunohistochemistry result demonstrated the significant downregulation of FOXC2, PBRM1, and BAP1 expression in aggressive ccRCC. Adding immunohistochemical staining results to qRT-PCR, the aggressive ccRCC prediction models had the area under the curve (AUC) of 0.760 and 0.796 and accuracy of 0.759 and 0.852 using the logistic regression method and deep-learning method, respectively. Use of these biomarkers and the developed prediction model can help stratify patients with clinical T1 stage ccRCC.