FoxQ1 is a Novel Molecular Target for Pancreatic Cancer and is Associated with Poor Prognosis

The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients

Contemporary analyses focused on a limited number of clinical and molecular biomarkers have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma. Here we describe a precision medicine platform known as the Molecular Twin consisting of advanced machine-learning models and use it to analyze a dataset of 6,363 clinical and multi-omic molecular features from patients with resected pancreatic ductal adenocarcinoma to accurately predict disease survival (DS). We show that a full multi-omic model predicts DS with the highest accuracy and that plasma protein is the top single-omic predictor of DS. A parsimonious model learning only 589 multi-omic features demonstrated similar predictive performance as the full multi-omic model. Our platform enables discovery of parsimonious biomarker panels and performance assessment of outcome prediction models learning from resource-intensive panels. This approach has considerable potential to impact clinical care and democratize precision cancer medicine worldwide.

Hsa_circRNA_0088036 acts as a ceRNA to promote bladder cancer progression by sponging miR-140-3p

Circular RNAs (circRNAs) are a class of non-coding RNAs that play vital roles in cancer biology. However, the potential role of hsa_circRNA_0088036 in bladder cancer (BCa) remains unknown. Hsa_circRNA_0088036 was identified by microarray analysis and validated by quantitative real-time polymerase chain reaction. Functional assays were conducted to confirm the effects of hsa_circRNA_0088036 on the growth, migration, invasion, tumorigenesis, and metastasis of BCa cells. The luciferase reporter assay and RNA pull down assay were performed to investigate the interactions between hsa_circRNA_0088036, miR-140-3p, and forkhead box protein Q1 (FOXQ1). Upregulated expression of hsa_circRNA_0088036 in BCa tissues and cell lines was positively correlated with overall survival and clinicopathologic characteristics. Knockdown of hsa_circRNA_0088036 inhibited the growth, migration, and invasion of BCa cells both in vivo and in vitro. Mechanistically, hsa_circRNA_0088036 could directly interact with miR-140-3p and act as a miRNA sponge to modulate FOXQ1 expression. Knockdown of hsa_circRNA_0088036 inhibited the proliferation, migration, and metastasis of BCa cells via miR-140-3p/FOXQ1 signaling, suggesting that hsa_circRNA_0088036 is a potential biomarker and therapeutic target for BCa.

vFLIP-regulated competing endogenous RNA (ceRNA) networks targeting lytic induction for KSHV-associated malignancies

Kaposi's sarcoma-associated herpesvirus (KSHV) causes life-long latent infection and malignancies, including Kaposi sarcoma (KS) commonly found in AIDS patients. Lytic replication can be induced to kill tumor cells harboring latent KSHV, through viral cytopathic effects and the subsequent antiviral immune responses. Viral FLICE-inhibitory protein (vFLIP), encoded by KSHV ORF K13, inhibits KSHV lytic reactivation, implying that the competing endogenous RNA (ceRNA) networks regulated by vFLIP can be modulated to induce the lytic reactivation of latent KSHV, a promising strategy for KSHV-associated malignancies. Here, we performed whole-transcriptome sequencing to reveal the global landscape of non-coding RNAs and mRNAs in iSLK-RGB-BAC16 cells and iSLK-RGB-K13 mutant cells. It showed that vFLIP regulated 227 differently expressed (DE) lncRNAs, 57 DE circRNAs, 20 DE miRNAs and 1371 DE mRNAs. Enrichment analysis verified that riboflavin metabolism was simultaneously enriched in DE genes related to miRNAs, lncRNAs, and circRNAs. The upregulated hsa-miR-378i and hsa-miR-3654, and downregulated miR-4467, miR-3163, miR-4451 and miR-4257 were significantly enriched in the ceRNA complex network, which contained 9 upregulated and 7 downregulated circRNAs, 5 upregulated and 85 downregulated lncRNAs, 5 upregulated and 35 downregulated mRNAs. Finally, we constructed and validated two vFLIP-regulated ceRNA networks: circRNA hsa_circ_0070049/hsa-miR-378i/SPEG/FOXQ1 and lncRNA AL031123.1/hsa-miR-378i/SPEG/FOXQ1. Taken together, the two ceRNA networks may mediate KSHV reactivation. These novel findings refreshed the present understanding of ceRNA network in KSHV lytic induction and provided potential therapeutic targets for KSHV-associated malignancies. This article is protected by copyright. All rights reserved.

Tumor Forkhead Box Q1 Is Elevated, Correlates with Increased Tumor Size, International Federation of Gynecology and Obstetrics Stage but Worse Overall Survival in Epithelial Ovarian Cancer Patients

Background: Forkhead box Q1 (FOXQ1) regulates epithelial ovarian cancer (EOC) cell proliferation, migration, and invasion, while its prognostic effect in EOC patients is unclear. This study aimed to assess FOXQ1 expression in EOC patients by immunohistochemical (IHC) staining and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and to analyze its correlation with EOC patients' clinical features and prognosis. Materials and Methods: FOXQ1 protein level in tumor and adjacent tissues from 173 EOC patients who underwent resection was detected by IHC staining and further scored by a semiquantitative scoring method; meanwhile, FOXQ1 mRNA level in tumor and adjacent tissues from 105 out of 173 EOC patients (whose fresh-frozen tissues were available) was detected by RT-qPCR. Besides, EOC patients' clinical features and survival data were collected. Results: Both FOXQ1 protein (n = 173) and mRNA (n = 105) levels were increased in tumor tissues compared with adjacent tissues (both p < 0.001) in EOC patients. Meanwhile, tumor FOXQ1 protein level was positively correlated with tumor size (p = 0.005) and International Federation of Gynecology and Obstetrics (FIGO) stage (p = 0.037), while FOXQ1 tumor mRNA level was only positively correlated with tumor size (p = 0.015) in EOC patients; however, they were not correlated with other clinical features such as histological subtypes, tumor differentiation, peritoneal cytology, and so on (all p > 0.05). Moreover, FOXQ1 protein (p = 0.030) and mRNA (p = 0.011) levels in tumors were both correlated with worse overall survival (OS) in EOC patients. Conclusion: FOXQ1 is elevated in tumor tissues, and its high tumor expression correlates with increased tumor size, elevated FIGO stage, and worse OS in EOC patients.

FOXQ1 is Differentially Expressed Across Breast Cancer Subtypes with Low Expression Associated with Poor Overall Survival

Purpose

Forkhead box Q1 (FOXQ1) has been shown to contribute to the development and progression of cancers, including ovarian and breast cancer (BC). However, research exploring FOXQ1 expression, copy number variation (CNV), and prognostic value across different BC subtypes is limited. Our purpose was to evaluate FOXQ1 mRNA expression, CNV, and prognostic value across BC subtypes.

Materials and Methods

We determined FOXQ1 expression and CNV in BC patient tumors using RT-qPCR and qPCR, respectively. We also analyzed FOXQ1 expression and CNV in BC cell lines in the CCLE database using K-means clustering. The prognostic value of FOXQ1 expression in the TCGA-BRCA database was assessed using univariate and multivariate Cox's regression analysis as well as using the online tools OncoLnc, GEPIA, and UALCAN.

Results

Our analyses reveal that FOXQ1 mRNA is differentially expressed between different subtypes of BC and is significantly decreased in luminal BC and HER2 patients when compared to normal breast tissue samples. Furthermore, analysis of BC cell lines showed that FOXQ1 mRNA expression was independent of CNV. Moreover, patients with low FOXQ1 mRNA expression had significantly poorer overall survival compared to those with high FOXQ1 mRNA expression. Finally, low FOXQ1 expression had a critical impact on the prognostic values of BC patients and was an independent predictor of overall survival when it was adjusted for BC subtypes and to two other FOX genes, FOXF2 and FOXM1.

Conclusion

Our study reveals for the first time that FOXQ1 is differentially expressed across BC subtypes and that low expression of FOXQ1 is indicative of poor prognosis in patients with BC.

miR-140-3p inhibits bladder cancer cell proliferation and invasion by targeting FOXQ1

Upregulation of the forkhead box protein Q1 (FOXQ1) promotes bladder cancer (BCa) cell growth and metastasis. Factors affecting FOXQ1 expression at the post-transcriptional level have not yet been identified. We performed cell proliferation, cell invasion, and tumorigenesis experiments to characterize the relationship between FOXQ1 and miR-140-3p. We found that FOXQ1 was significantly upregulated and miR-140-3p was significantly downregulated in BCa tissues. We also identified an inverse correlation between miR-140-3p and FOXQ1 expression in BCa tissues. Overexpression of miR-140-3p reduced FOXQ1 expression, suppressing BCa cell proliferation and invasion. A luciferase assay confirmed that miR-140-3p bound to the 3’-UTR of FOXQ1 mRNA and decreased its expression. In addition, we used a mouse xenograft model to demonstrate that miR-140-3p suppressed tumor cell growth in vivo. Our findings suggest that miR-140-3p suppresses BCa cell proliferation and invasion by directly decreasing FOXQ1 expression.

Potential five-mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma

Although the mortality rate of papillary thyroid carcinoma (PTC) is relatively low, the recurrence rates of PTC remain high. The high recurrence rates are related to the difficulties in treatment. Gene expression profiles has provided novel insights into potential therapeutic targets and molecular biomarkers of PTC. The aim of the present study was to identify mRNA signatures which may categorize PTCs into high-and low-risk subgroups and aid with the predictions for prognoses. The mRNA expression profiles of PTC and normal thyroid tissue samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs were identified using the ‘EdgeR’ software package. Gene signatures associated with the overall survival of PTC were selected, and enrichment analysis was performed to explore the biological pathways and functions of the prognostic mRNAs using the Database for Visualization, Annotation and Integration Discovery. A signature model was established to investigate a specific and robust risk stratification for PTC. A total of 1,085 differentially expressed mRNAs were identified between the PTC and normal thyroid tissue samples. Among them, 361 mRNAs were associated with overall survival (P<0.05). A 5-mRNA prognostic signature for PTC (ADRA1B, RIPPLY3, PCOLCE, TEKT1 and SALL3) was identified to classify the patients into high-and low-risk subgroups. These prognostic mRNAs were enriched in Gene Ontology terms such as ‘calcium ion binding’, ‘enzyme inhibitor activity’, ‘carbohydrate binding’, ‘transcriptional activator activity’, ‘RNA polymerase II core promoter proximal region sequence-specific binding’ and ‘glutathione transferase activity’, and Kyoto Encyclopedia of Genes and Genomes signaling pathways such as ‘pertussis’, ‘ascorbate and aldarate metabolism’, ‘systemic lupus erythematosus’, ‘drug metabolism-cytochrome P450 and ‘complement and coagulation cascades’. The 5-mRNA signature model may be useful during consultations with patients with PTC to improve the prediction of their prognosis. In addition, the prognostic signature identified in the present study may reveal novel therapeutic targets for patients with PTC.

Microarray Analysis of Gene Expression Involved in Butyrate-Resistant Colorectal Carcinoma HCT116 Cells

BACKGROUND

Resistance to chemotherapeutic agents is usually found in cancer stem cells (CSCs) and cancer stem-like cells that are often regarded as the target for cancer monitoring. However, the different patterns of their transcriptomic profiling is still unclear.

OBJECTIVE

This study aims to illustrate the transcriptomic profile of CSCs and butyrate-resistant colorectal carcinoma cells (BR-CRCs), by comparing them with parental colorectal cancer (CRC) cells in order to identify distinguishing transcription patterns of the CSCs and BR-CRCs.

METHODS

Parental CRC cells HCT116 (HCT116-PT) were cultured and induced to establish the butyrate resistant cell model (HCT116-BR). Commercial enriching of the HCT116-CSCs were grown in a tumorsphere suspension culture, which was followed firstly by the assessment of butyrate tolerance using MTT and PrestoBlue. Then their gene expression profiling was analyzed by microarray.

RESULTS

The results showed that both butyrate-resistant HCT116 cells (HCT116-BR) and HCT116-CSCs were more tolerant a butyrate effects than HCT116-PT cells. Differentially expressed gene profiles exhibited that IFI27, FOXQ1, PRF1, and SLC2A3 genes were increasingly expressed in CSCs, and were dramatically overexpressed in HCT116-BR cells when compared with HCT116-PT cells. Moreover, PKIB and LOC399959 were downregulated both in HCT116-CSCs and HCT116-BR cells.

CONCLUSION

Our findings shed light on the transcriptomic profiles of chemoresistant CRC cells. This data should be useful for further study to provide guidelines for clinical prognosis to determine the guidelines for CRC treatment, especially in patients with chemoresistance and designing novel anti-neoplastic agents.

Potentiality of forkhead box Q1 as a biomarker for monitoring tumor features and predicting prognosis in non-small cell lung cancer

Background

This study aimed to explore the correlation of forkhead box Q1 (FOXQ1) with clinicopathological features and survival profiles in patients with non‐small cell lung cancer (NSCLC).

Methods

A total of 238 NSCLC patients with TNM stage I‐III who underwent surgical resection were reviewed, and the expression of FOXQ1 in tumor and paired adjacent tissue was detected using immunohistochemistry assays. The clinical data and survival data of patients with NSCLC were retrieved and calculated.

Results

FOXQ1 expression was increased in tumor tissue (61.3% high expression and 38.7% low expression) compared with paired adjacent tissue (37.8% high expression and 62.2% low expression) (P < .001). In addition, high FOXQ1 expression was associated with larger tumor size (P = .042), lymph node metastasis (P = .040), and advanced TNM stage (P = .002). Disease‐free survival (DFS) (P = .016) and overall survival (OS) (P = .008) were both reduced in patients with high FOXQ1 expression compared with patients with low FOXQ1 expression. Additionally, high FOXQ1 expression (P = .043), poor pathological differentiation (P = .003), and lymph node metastasis (P < .001) were independent risk factors for DFS, and high FOXQ1 expression (P = .021), tumor size (>5 cm) (P = .014), and lymph node metastasis (P < .001) were independent risk factors for OS.

Conclusion

High FOXQ1 expression is associated with advanced tumor features as well as undesirable survival profiles in patients with NSCLC, implying the potential prognostic value of FOXQ1 for NSCLC.

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

BACKGROUND

Transcriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.

MATERIALS AND METHODS

Gene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.

RESULTS

We identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.

CONCLUSION

The six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.

The Dominant Role of Forkhead Box Proteins in Cancer

Forkhead box (FOX) proteins are multifaceted transcription factors that are significantly implicated in cancer, with various critical roles in biological processes. Herein, we provide an overview of several key members of the FOXA, FOXC, FOXM1, FOXO and FOXP subfamilies. Important pathophysiological processes of FOX transcription factors at multiple levels in a context-dependent manner are discussed. We also specifically summarize some major aspects of FOX transcription factors in association with cancer research such as drug resistance, tumor growth, genomic alterations or drivers of initiation. Finally, we suggest that targeting FOX proteins may be a potential therapeutic strategy to combat cancer.

Genetic analysis of zebrafish homologs of human FOXQ1, foxq1a and foxq1b, in innate immune cell development and bacterial host response

FOXQ1 is a member of the forkhead-box transcription factor family that has important functions in development, cancer, aging, and many cellular processes. The role of FOXQ1 in cancer biology has raised intense interest, yet much remains poorly understood. We investigated the possible function of the two zebrafish orthologs (foxq1a and foxq1b) of human FOXQ1 in innate immune cell development and function. We employed CRISPR-Cas9 targeted mutagenesis to create null mutations of foxq1a and foxq1b in zebrafish. Using a combination of molecular, cellular, and embryological approaches, we characterized single and double foxq1a bcz11 and foxq1b bcz18 mutants. This study provides the first genetic mutant analyses of zebrafish foxq1a and foxq1b. Interestingly, we found that foxq1a, but not foxq1b, was transcriptionally regulated during a bacterial response, while the expression of foxq1a was detected in sorted macrophages and upregulated in foxq1a-deficient mutants. However, the transcriptional response to E. coli challenge of foxq1a and foxq1b mutants was not significantly different from that of their wildtype control siblings. Our data shows that foxq1a may have a role in modulating bacterial response, while both foxq1a and foxq1b are not required for the development of macrophages, neutrophils, and microglia. Considering the implicated role of FOXQ1 in a vast number of cancers and biological processes, the foxq1a and foxq1b null mutants from this study provide useful genetic models to further investigate FOXQ1 functions.

FOXC1 promotes melanoma by activating MST1R/PI3K/AKT

FOXC1 is a member of Forkhead box family transcription factors. We showed that FOXC1 level was increased in melanoma cells and tissues and correlated with hypomethylation of the FOXC1 gene. Overexpression of FOXC1 promoted proliferation, migration, invasion, colony formation and growth in 3D Matrigel of melanoma cells. FOXC1 increased MST1R and activated the PI3K/AKT pathway. Also, FOXC1 expression was associated with disease progression and poor prognosis of melanoma. We suggest that FOXC1 is a potential prognostic biomarker for treating melanoma and predicting outcome of patients.

A six-mRNA signature model for the prognosis of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), one of the most common cancers with high morbidity and mortality rates worldwide, has a poor prognosis. The transcriptome sequencing data of 500 patients with HNSCC in the TCGA dataset were assessed to find biomarkers associated with HNSCC prognosis so as to improve the prognosis of patients with HNSCC. The patients were divided into the training and testing sets. A model of six mRNAs (FRMD5, PCMT1, PDGFA, TMC8, YIPF4, ZNF324B) that could predict patient prognosis was identified in the training set using the Cox regression analysis. According to this model, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier analysis showed that the high-risk group showed significantly shorter overall survival time compared with the low-risk group in both training and testing sets. The receiver operating characteristic analysis further confirmed high sensitivity and specificity for the model, which was more accurate compared with some known biomarkers in predicting HNSCC prognosis. Moreover, the model was applicable to patients of different ages, genders, clinical stages, tumor locations, smoking history, and human papillomavirus (HPV) status, as well as to microarray dataset. This model could be used as a novel biomarker for the prognosis of HNSCC and a significant tool for guiding the clinical treatment of HNSCC. The risk score acquired from the model might contribute to improving outcome prediction and management for patients with HNSCC, indicating its clinical significance.

Prognostic value of FOXQ1 in patients with malignant solid tumors: a meta-analysis

Background

Forkhead box Q1 (FOXQ1, also known as HFH1), a member of the forkhead transcription factor family, has been demonstrated to be overexpressed in multiple tumors and is thought to be an indicator of poor clinical outcomes.

Methods

A meta-analysis using qualified relevant literature was performed to evaluate the prognostic significance of FOXQ1 in various malignant solid tumors. A search of electronic databases was conducted in MEDLINE, Embase, and the Cochrane Library to identify relevant studies published from 1966 to July 30, 2016, and the studies were identified by further evaluation. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for analyses were assessed to investigate the association between FOXQ1 expression and overall survival (OS) of patients with malignant solid tumors.

Results

A total of 1,520 patients from six studies (seven cohorts) with multiple malignant solid tumors were included. For OS, high FOXQ1 expression could significantly predict worse outcome with the pooled HR of 1.38 (95% CI: 1.17–1.59; P<0.001). The subgroup analysis suggested that the elevated levels of FOXQ1 appear to be associated with worse OS in hepatocellular carcinoma (HR =1.34; 95% CI: 1.11–1.57; P<0.001) and other cancers (HR =1.62; 95% CI: 1.09–2.14; P<0.001).

Conclusion

This meta-analysis indicated that the high expression of FOXQ1 is associated with an adverse OS in malignant solid tumors, suggesting that FOXQ1 may be a predictor of poor prognosis for the development of malignant solid tumors.

Prognostic Impact of Cell Division Cycle Associated 2 Expression on Pancreatic Ductal Adenocarcinoma

<strong>Objective</strong> To examine the expression of cell division cycle associated 2 (CDCA 2) in pancreatic ductal adenocarcinoma (PDAC) and investigate its role in prognosis of PDAC patients. <strong>Methods</strong> This retrospective study included 155 PDAC patients who underwent surgical treatment and complete post-operative follow-up. Clinicopathologic data were collected through clinical database. Tissue microarray was constructed and immunohistochemistry was performed to detect CDCA2 expression in the PDAC tumor tissues and adjacent non-tumor tissues. Clinicopathological characteristics between high and low CDCA2 expression were compared. Correlation of CDCA2 expressions with patients' survival was analyzed using Kaplan-Meier method and Cox regression analysis. <strong>Results</strong> Expression of CDCA2 in PDAC cells was significantly higher than that in adjacent non-tumor tissues (U=4056.5, P<0.001). Univariate analysis showed that CDCA2 expression [hazard ratio (HR)=1.574, 95% confidence interval (CI)=1.014-2.443, P=0.043] and node metastasis (HR=1.704, 95%CI=1.183-2.454, P=0.004) were significantly associated with prognosis. Cox regression analysis showed CDCA2 expression was not an independent prognostic risk factor (HR=1.418, 95%CI=0.897-2.242, P=0.135) for PDCA patients. Stratification survival analysis demonstrated CDCA2 expression as an independent prognostic risk factor in male patients (HR=2.554, 95%CI=1.446-4.511, P=0.003) or in non-perineural invasion patients (HR=2.290, 95%CI=1.146-4.577, P=0.012). <strong>Conclusions</strong> CDCA2 is highly expressed in PDAC tumor tissue. Although CDCA2 is not an independent prognostic risk factor for PDAC patients, it might be used to help predict prognosis of male or non-perineural invasion patients of PDAC.