TLX3 repressed SNAI1-induced epithelial-mesenchymal transition by directly constraining STAT3 phosphorylation and functionally sensitized 5-FU chemotherapy in hepatocellular carcinoma

A prognostic model built on amino acid metabolism patterns in HPV-associated head and neck squamous cell carcinoma

OBJECTIVES

To compare amino acid metabolism patterns between HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) patients and identify key genes for a prognostic model.

DESIGN

Utilizing the Cancer Genome Atlas dataset, we analyzed amino acid metabolism genes, differentiated genes between HPV statuses, and selected key genes via LASSO regression for the prognostic model. The model's gene expression was verified through immunohistochemistry in clinical samples. Functional enrichment and CIBERSORTx analyses explored biological functions, molecular mechanisms, and immune cell correlations. The model's prognostic capability was assessed using nomograms, calibration, and decision curve analysis.

RESULTS

We identified 1157 key genes associated with amino acid metabolism in HNSCC and HPV status. The prognostic model, featuring genes like IQCN, SLC22A1, SYT12, and TLX3, highlighted functions in development, metabolism, and pathways related to receptors and enzymes. It significantly correlated with immune cell infiltration and outperformed traditional staging in prognosis prediction, despite immunohistochemistry results showing limited clinical identification of HPV-related HNSCC.

CONCLUSIONS

Distinct amino acid metabolism patterns differentiate HPV-positive from negative HNSCC patients, underscoring the prognostic model's utility in predicting outcomes and guiding therapeutic strategies.

A contrast set mining based approach for cancer subtype analysis

The task of detecting common and unique characteristics among different cancer subtypes is an important focus of research that aims to improve personalized therapies. Unlike current approaches mainly based on predictive techniques, our study aims to improve the knowledge about the molecular mechanisms that descriptively led to cancer, thus not requiring previous knowledge to be validated. Here, we propose an approach based on contrast set mining to capture high-order relationships in cancer transcriptomic data. In this way, we were able to extract valuable insights from several cancer subtypes in the form of highly specific genetic relationships related to functional pathways affected by the disease. To this end, we have divided several cancer gene expression databases by the subtype associated with each sample to detect which gene groups are related to each cancer subtype. To demonstrate the potential and usefulness of the proposed approach we have extensively analysed RNA-Seq gene expression data from breast, kidney, and colon cancer subtypes. The possible role of the obtained genetic relationships was further evaluated through extensive literature research, while its prognosis was assessed via survival analysis, finding gene expression patterns related to survival in various cancer subtypes. Some gene associations were described in the literature as potential cancer biomarkers while other results have been not described yet and could be a starting point for future research.

Deciphering STAT3 signaling potential in hepatocellular carcinoma: tumorigenesis, treatment resistance, and pharmacological significance

Hepatocellular carcinoma (HCC) is considered one of the greatest challenges to human life and is the most common form of liver cancer. Treatment of HCC depends on chemotherapy, radiotherapy, surgery, and immunotherapy, all of which have their own drawbacks, and patients may develop resistance to these therapies due to the aggressive behavior of HCC cells. New and effective therapies for HCC can be developed by targeting molecular signaling pathways. The expression of signal transducer and activator of transcription 3 (STAT3) in human cancer cells changes, and during cancer progression, the expression tends to increase. After induction of STAT3 signaling by growth factors and cytokines, STAT3 is phosphorylated and translocated to the nucleus to regulate cancer progression. The concept of the current review revolves around the expression and phosphorylation status of STAT3 in HCC, and studies show that the expression of STAT3 is high during the progression of HCC. This review addresses the function of STAT3 as an oncogenic factor in HCC, as STAT3 is able to prevent apoptosis and thus promote the progression of HCC. Moreover, STAT3 regulates both survival- and death-inducing autophagy in HCC and promotes cancer metastasis by inducing the epithelial-mesenchymal transition (EMT). In addition, upregulation of STAT3 is associated with the occurrence of chemoresistance and radioresistance in HCC. Specifically, non-protein-coding transcripts regulate STAT3 signaling in HCC, and their inhibition by antitumor agents may affect tumor progression. In this review, all these topics are discussed in detail to provide further insight into the role of STAT3 in tumorigenesis, treatment resistance, and pharmacological regulation of HCC.

RNA Binding Motif Protein 3 Promotes Cell Metastasis and Epithelial–Mesenchymal Transition Through STAT3 Signaling Pathway in Hepatocellular Carcinoma

Purpose

RNA binding motif protein 3 (RBM3) has been reported to be dysregulated in various cancers and associated with tumor aggressiveness. Epithelial–mesenchymal transition (EMT) is an important biological process by which tumor cells acquire metastatic abilities. This study aimed to explore the regulatory and molecular mechanisms of RBM3 in EMT process.

Methods

Western blotting, IHC, and qRT-PCR were performed to evaluate the expression of target genes. Transwell assay was used to investigate the migration and invasion. RNA immunoprecipitation and luciferase reporter assay were performed to explore the correlation of RBM3 with STAT3 or microRNA-383. Animal HCC models were used to explore the role of RBM3 in metastasis in vivo.

Results

RBM3 was highly expressed in HCC tissues compared to healthy tissues, and its level was negatively correlated with the prognosis of HCC patients. RBM3 overexpression accelerated migration and invasion, promoted EMT process, and activated STAT3 signaling. EMT induced by RBM3 was not only attenuated by inhibiting pSTAT3 via S3I-201 but also abolished by suppressing STAT3 expression via siRNAs. Mechanistically, RBM3 increased STAT3 expression by stabilizing STAT3 mRNA via binding to its mRNA. As an upstream target of RBM3, microRNA-383 inhibited RBM3 expression by binding to its 3ʹUTR and resulted in the inhibition of the EMT process. Inhibition of RBM3 in HCC animal models prolonged survival and ameliorated malignant phenotypes in mice.

Conclusion

Our findings support that RBM3 promotes HCC metastasis by activating STAT3 signaling.

The Transcription Factors Zeb1 and Snail Induce Cell Malignancy and Cancer Stem Cell Phenotype in Prostate Cells, Increasing Androgen Synthesis Capacity and Therapy Resistance

Prostate cancer (PCa) incidence has increased during the last decades, becoming one of the leading causes of death by cancer in men worldwide. During an extended period of prostate cancer, malignant cells are androgen-sensitive being testosterone the main responsible for tumor growth. Accordingly, treatments blocking production and action of testosterone are mostly used. However, during disease progression, PCa cells become androgen insensitive producing a castration-resistant stage with a worse prognosis. Overcoming castration-resistant prostate cancer (CRPC) has become a great challenge in the management of this disease. In the search for molecular pathways leading to therapy resistance, the epithelial-mesenchymal transition (EMT), and particularly the transcription factors zinc finger E-box-binding homeobox 1 (Zeb1) and zinc finger protein SNAI1 (Snail), master genes of the EMT, have shown to have pivotal roles. Also, the discovery that cancer stem cells (CSCs) can be generated de novo from their non-CSCs counterpart has led to the question whereas these EMT transcription factors could be implicated in this dynamic conversion between non-CSC and CSC. In this review, we analyze evidence supporting the idea that Zeb1 and Snail induce cell malignancy and cancer stem cell phenotype in prostate cells, increasing androgen synthesis capacity and therapy resistance.

Sulfatase 2-Induced Cancer-Associated Fibroblasts Promote Hepatocellular Carcinoma Progression via Inhibition of Apoptosis and Induction of Epithelial-to-Mesenchymal Transition

Background

Sulfatase 2 (SULF2) removes the 6-O-sulfate groups from heparan sulfate proteoglycans (HSPG) and consequently alters the binding sites for various signaling molecules. Here, we elucidated the role of SULF2 in the differentiation of hepatic stellate cells (HSCs) into carcinoma-associated fibroblasts (CAFs) in the hepatocellular carcinoma (HCC) microenvironment and the mechanism underlying CAF-mediated HCC growth.

Methods

The clinical relevance of SULF2 and CAFs was examined using in silico and immunohistochemical (IHC) analyses. Functional studies were performed to evaluate the role of SULF2 in the differentiation of HSCs into CAFs and elucidate the mechanism underlying CAF-mediated HCC growth. Mechanistic studies were performed using the chromatin immunoprecipitation, luciferase reporter, and RNA immunoprecipitation assays. The in vitro findings were verified using the nude HCC xenograft mouse model.

Results

The Cancer Genome Atlas (TCGA) database and IHC analyses revealed that the expression of CAF markers, which was positively correlated with that of SULF2 in the HCC tissues, predicted unfavorable postsurgical outcomes. Co-culturing HSCs with HCC cells expressing SULF2 promoted CAF differentiation. Additionally, CAFs repressed HCC cell apoptosis by activating the SDF-1/CXCR4/PI3K/AKT signaling pathway. Meanwhile, SULF2-induced CAFs promoted epithelial-to-mesenchymal transition (EMT) of HCC cells by modulating the SDF-1/CXCR4/OIP5-AS1/miR-153-3p/SNAI1 axis. Studies using HCC xenograft mouse models demonstrated that OIP5-AS1 induced EMT by upregulating SNAI1 and promoted HCC growth in vivo.

Conclusion

These data indicated that SULF2 secreted by the HCC cells induced the differentiation of HSCs into CAFs through the TGFβ1/SMAD3 signaling pathway. SULF2-induced CAFs attenuated HCC apoptosis by activating the SDF-1/CXCR4/PI3K/AKT signaling pathway and induced EMT through the SDF-1/CXCR4/OIP5-AS1/miR-153-3p/SNAI1 axis. This study revealed a novel mechanism involved in the crosstalk between HCC cells and CAFs in the tumor microenvironment, which can aid in the development of novel and efficient therapeutic strategies for primary liver cancer.