Increased expression of CELSR3 indicates a poor prognostic factor for Prostate Cancer

Emerging roles of EGFL family members in neoplastic diseases: Molecular mechanisms and targeted therapies

Epidermal growth factor-like proteins (EGFLs) contain more than a single EGF/EGF-like domain within their protein structure. To date, ten EGFL family members (EGFL1-10) have been characterized across diverse tissues and developmental stages under different conditions. In this review, we conclude that EGFLs are instrumental in regulating biological activities and pathological processes. Under physiological conditions, EGFLs participate in angiogenesis, neurogenesis, osteogenesis, and other processes. Under pathological conditions, EGFLs are linked with different diseases, particularly cancers. Furthermore, we highlight recent advancements in the study of EGFLs in biological conditions and cancers. In addition, the regulatory role and key underlying mechanism of EGFLs in mediating tumorigenesis are discussed. This paper also examines potential antagonists that target EGFL family members in cancer therapeutics. In summary, this comprehensive review elucidates the critical role of EGFLs in neoplastic diseases and highlights their potential as therapeutic targets.

mRNA vaccines for prostate cancer: A novel promising immunotherapy

The treatment of advanced prostate cancer (PCa) primarily based on androgen deprivation therapy (ADT); however, patients inevitably progress to the castration-resistant prostate cancer (CRPC) stage. Despite the recent advancements in CRPC treatment with novel endocrine drugs that further inhibit androgen receptor signaling, resistance ultimately develops, underscoring the urgent need for new effective therapeutic strategies. Therapeutic cancer vaccines, a form of immunotherapy, exert anti-cancer effects by activating the host's immune system. Over the past few decades, various conventional therapeutic PCa vaccines based on cells, microbes, proteins, peptides, or DNA have been developed and tested in patients with advanced PCa. These attempts have largely failed to improve survival, with the sole exception of sipuleucel-T, which extended the median overall survival of asymptomatic or minimally symptomatic metastatic CRPC (mCRPC) patients by four months. The rapid development and high efficacy of mRNA vaccines during the COVID-19 pandemic have garnered worldwide attention. Compared to conventional vaccines, mRNA vaccines offer several unique advantages, including high production efficiency, low cost, high safety, strong immune response induction, and high adaptability and precision. These attributes make mRNA vaccines a promising frontier in the treatment of advanced PCa.

Flamingo participates in multiple models of cell competition

The growth and survival of cells with different fitness, such as those with a proliferative advantage or a deleterious mutation, is controlled through cell competition. During development, cell competition enables healthy cells to eliminate less fit cells that could jeopardize tissue integrity, and facilitates the elimination of pre-malignant cells by healthy cells as a surveillance mechanism to prevent oncogenesis. Malignant cells also benefit from cell competition to promote their expansion. Despite its ubiquitous presence, the mechanisms governing cell competition, particularly those common to developmental competition and tumorigenesis, are poorly understood. Here, we show that in Drosophila, the planar cell polarity (PCP) protein Flamingo (Fmi) is required by winners to maintain their status during cell competition in malignant tumors to overtake healthy tissue, in early pre-malignant cells when they overproliferate among wildtype cells, in healthy cells when they later eliminate pre-malignant cells, and by supercompetitors as they compete to occupy excessive territory within wildtype tissues. 'Would-be' winners that lack Fmi are unable to overproliferate, and instead become losers. We demonstrate that the role of Fmi in cell competition is independent of PCP, and that it uses a distinct mechanism that may more closely resemble one used in other less well-defined functions of Fmi.

Flamingo participates in multiple models of cell competition

The growth and survival of cells with different fitness, such as those with a proliferative advantage or a deleterious mutation, is controlled through cell competition. During development, cell competition enables healthy cells to eliminate less fit cells that could jeopardize tissue integrity, and facilitates the elimination of pre-malignant cells by healthy cells as a surveillance mechanism to prevent oncogenesis. Malignant cells also benefit from cell competition to promote their expansion. Despite its ubiquitous presence, the mechanisms governing cell competition, particularly those common to developmental competition and tumorigenesis, are poorly understood. Here, we show that in Drosophila, the planar cell polarity (PCP) protein Flamingo (Fmi) is required by winners to maintain their status during cell competition in malignant tumors to overtake healthy tissue, in early pre-malignant cells when they overproliferate among wildtype cells, in healthy cells when they later eliminate pre-malignant cells, and by supercompetitors as they compete to occupy excessive territory within wildtype tissues. "Would-be" winners that lack Fmi are unable to over-proliferate, and instead become losers. We demonstrate that the role of Fmi in cell competition is independent of PCP, and that it uses a distinct mechanism that may more closely resemble one used in other less well-defined functions of Fmi.

Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States

Prostate cancer is a significant health concern and the most commonly diagnosed cancer in men worldwide. Understanding the complex process of prostate tumor evolution and progression is crucial for improved diagnosis, treatments, and patient outcomes. Previous studies have focused on unraveling the dynamics of prostate cancer evolution using phylogenetic or lineage analysis approaches. However, those approaches have limitations in capturing the complete disease process or incorporating genomic and transcriptomic variations comprehensively. In this study, we applied a novel computational approach to derive a prostate cancer progression model using multidimensional data from 497 prostate tumor samples and 52 tumor-adjacent normal samples obtained from The Cancer Genome Atlas study. The model was validated using data from an independent cohort of 545 primary tumor samples. By integrating transcriptomic and genomic data, our model provides a comprehensive view of prostate tumor progression, identifies crucial signaling pathways and genetic events, and uncovers distinct transcription signatures associated with disease progression. Our findings have significant implications for cancer research and hold promise for guiding personalized treatment strategies in prostate cancer.

SIGNIFICANCE

We developed and validated a progression model of prostate cancer using >1,000 tumor and normal tissue samples. The model provided a comprehensive view of prostate tumor evolution and progression.

CELSR3 is a prognostic marker in HNSCC and correlates with immune cell infiltration in the tumor microenvironment

PURPOSE

To look at the diagnostic value of the CELSR receptor 3 (CELSR3) gene in head and neck squamous cell carcinoma (HNSCC) and its effect on tumor immune invasion, which is important for enhancing HNSCC treatment.

METHODS

Several bioinformatics tools were employed to investigate CELSR3's putative oncogenic pathway in HNSCC, and datasets from The Tumor Genome Atlas (TCGA), Tumor Immune Estimation Resource (TIMER), Gene Expression Profile Interaction Analysis (GEPIA) and LinkedOmics were extracted and evaluated. CELSR3 has been linked to tumor immune cell infiltration, immunological checkpoints, and immune-related genes. CELSR3's putative roles were investigated using Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and pathway enrichment analysis. The expression level of CELSR3 in HNSCC tissues and cells was detected by RT-qPCR. The effects of CELSR3 on proliferation of HNSCC cells were detected by CCK-8 assay.

RESULTS

CELSR3 was shown to be expressed differently in different types of cancer and normal tissues. CELSR3 gene expression was linked to pN-stage and pM-stage. Patients with high CELSR3 expression also have a well prognosis. CELSR3 expression was found to be an independent predictive factor for HNSCC in both univariate and multivariate Cox regression analyses. We discovered the functional network of CELSR3 in HNSCC using GO and KEGG analysis. CELSR3 expression levels were found to be favorably associated with immune cell infiltration levels. Furthermore, CELSR3 expression levels were significantly correlated with the expression levels of many immune molecules, such as MHC genes, immune activation genes, chemokine receptors, and chemokines. CELSR3 is highly expressed in HNSCC tissues and cells. CELSR3 overexpression significantly inhibited the proliferation of HNSCC cells. CELSR3 expression may affect the immune microenvironment and, as a result, the prognosis of HNSCC.

CONCLUSION

CELSR3 expression is elevated in HNSCC tumor tissues, and high CELSR3 expression is associated with well prognosis, which inhibited the proliferation of NHSCC cells. CELSR3 has the potential to influence tumor formation by controlling tumor-infiltrating cells in the tumor microenvironment (TME). As a result, CELSR3 may have diagnostic significance in HNSCC.

The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer

Although recent efforts have led to the development of highly effective androgen receptor (AR)-directed therapies for the treatment of advanced prostate cancer, a significant subset of patients will progress with resistant disease including AR-negative tumors that display neuroendocrine features [neuroendocrine prostate cancer (NEPC)]. On the basis of RNA sequencing (RNA-seq) data from a clinical cohort of tissue from benign prostate, locally advanced prostate cancer, metastatic castration-resistant prostate cancer and NEPC, we developed a multi-step bioinformatics pipeline to identify NEPC-specific, overexpressed gene transcripts that encode cell surface proteins. This included the identification of known NEPC surface protein CEACAM5 as well as other potentially targetable proteins (e.g., HMMR and CESLR3). We further showed that cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) knockdown results in reduced NEPC tumor cell proliferation and migration in vitro. We provide in vivo data including laser capture microdissection followed by RNA-seq data supporting a causal role of CELSR3 in the development and/or maintenance of the phenotype associated with NEPC. Finally, we provide initial data that suggests CELSR3 is a target for T-cell redirection therapeutics. Further work is now needed to fully evaluate the utility of targeting CELSR3 with T-cell redirection or other similar therapeutics as a potential new strategy for patients with NEPC.

Significance

The development of effective treatment for patients with NEPC remains an unmet clinical need. We have identified specific surface proteins, including CELSR3, that may serve as novel biomarkers or therapeutic targets for NEPC.

Identification of an individualized therapy prognostic signature for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) are the most common cancers in the head and neck. Therapeutic response-related genes (TRRGs) are closely associated with carcinogenesis and prognosis in HNSCC. However, the clinical value and prognostic significance of TRRGs are still unclear. We aimed to construct a prognostic risk model to predict therapy response and prognosis in TRRGs-defined subgroups of HNSCC.

METHODS

The multiomics data and clinical information of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA). The profile data GSE65858 and GSE67614 chip was downloaded from public functional genomics data Gene Expression Omnibus (GEO). Based on TCGA-HNSC database, patients were divided into a remission group and a non-remission group according to therapy response, and differentially expressed TRRGs between those two groups were screened. Using Cox regression analysis and Least absolute shrinkage and selection operator (LASSO) analysis, candidate TRRGs that can predict the prognosis of HNSCC were identified and used to construct a TRRGs-based signature and a prognostic nomogram.

RESULT

A total of 1896 differentially expressed TRRGs were screened, including 1530 upregulated genes and 366 downregulated genes. Then, 206 differently expressed TRRGs that was significantly associated with the survival were chosen using univariate Cox regression analysis. Finally, a total of 20 candidate TRRGs genes were identified by LASSO analysis to establish a signature for risk prediction, and the risk score of each patient was calculated. Patients were divided into a high-risk group (Risk-H) and a low-risk group (Risk-L) based on the risk score. Results showed that the Risk-L patients had better overall survival (OS) than Risk-H patients. Receiver operating characteristic (ROC) curve analysis revealed great predictive performance for 1-, 3-, and 5-year OS in TCGA-HNSC and GEO databases. Moreover, for patients treated with post-operative radiotherapy, Risk-L patients had longer OS and lower recurrence than Risk-H patients. The nomogram involves risk score and other clinical factors had good performance in predicting survival probability.

CONCLUSIONS

The proposed risk prognostic signature and Nomogram based on TRRGs are novel promising tools for predicting therapy response and overall survival in HNSCC patients.

Androgen deprivation restores ARHGEF2 to promote neuroendocrine differentiation of prostate cancer

Androgen receptor (AR) plays an important role in the progression of prostate cancer and has been targeted by castration or AR-antagonists. The emergence of castration-resistant prostate cancer (CRPC) after androgen deprivation therapy (ADT) is inevitable. However, it is not entirely clear how ADT fails or how it causes resistance. Through analysis of RNA-seq data, we nominate ARHGEF2 as a pivotal androgen-repressed gene. We show that ARHGEF2 is directly suppressed by androgen/AR. AR occupies the enhancer and communicates with the promoter region of ARHGEF2. Functionally, ARHGEF2 is important for the growth, lethal phenotype, and survival of CRPC cells and tumor xenografts. Correspondingly, AR inhibition or AR antagonist treatment can restore ARHGEF2 expression, thereby allowing prostate cancer cells to induce treatment resistance and tolerance. Overall, our findings provide an explanation for the contradictory clinical results that ADT resistance may be caused by the up-regulation of ARHGEF2 and provide a novel target.

Identification and validation of a novel tumor driver gene signature for diagnosis and prognosis of head and neck squamous cell carcinoma

Objective: Head and neck squamous cell carcinoma (HNSCC) is a common heterogeneous cancer with complex carcinogenic factors. However, the current TNM staging criteria to judge its severity to formulate treatment plans and evaluate the prognosis are particularly weak. Therefore, a robust diagnostic model capable of accurately diagnosing and predicting HNSCC should be established. Methods: Gene expression and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Key prognostic genes associated with HNSCC were screened with the weighted gene co-expression network analysis and least absolute shrinkage and selection operator (LASSO) Cox regression model analysis. We used the timeROC and survival R packages to conduct time-dependent receiver operating characteristic curve analyses and calculated the area under the curve at different time points of model prediction. Patients in the training and validation groups were divided into high- and low-risk subgroups, and Kaplan-Meier (K-M) survival curves were plotted for all subgroups. Subsequently, LASSO and support vector machine algorithms were used to screen genes to construct diagnostic model. Furthermore, we used the Wilcoxon signed-rank test to compare the half-maximal inhibitory concentrations of common chemotherapy drugs among patients in different risk groups. Finally, the expression levels of eight genes were measured using quantitative real-time polymerase chain reaction and immunohistochemistry. Results: Ten genes (SSB, PFKP, NAT10, PCDH9, SHANK2, PAX8, CELSR3, DCLRE1C, MAP2K7, and ODF4) with prognostic potential were identified, and a risk score was derived accordingly. Patients were divided into high- and low-risk groups based on the median risk score. The K-M survival curves confirmed that patients with high scores had significantly worse overall survival. Receiver operating characteristic curves proved that the prognostic signature had good sensitivity and specificity for predicting the prognosis of patients with HNSCC. Univariate and multivariate Cox regression analyses confirmed that the gene signature was an independent prognostic risk factor for HNSCC. Diagnostic model was built by identifying eight genes (SSB, PFKP, NAT10, PCDH9, CELSR3, DCLRE1C, MAP2K7, and ODF4). The high-risk group showed higher sensitivity to various common chemotherapeutic drugs. DCLRE1C expression was higher in normal tissues than in HNSCC tissues. Conclusion: Our study identified the important role of tumor-driver genes in HNSCC and their potential clinical diagnostic and prognostic values to facilitate individualized management of patients with HNSCC.

CENPA acts as a prognostic factor that relates to immune infiltrates in gliomas

Background

Glioma is the most common primary tumor of the central nervous system (CNS). Centromere protein A (CENPA) plays an essential role in ensuring that mitosis proceeds normally. The effect of CENPA on glioma is rarely reported. However, the current study aims to explore whether aberrant CENPA expression promotes glioma progression and the potential mechanisms involved.

Methods

The GEPIA website, The Cancer Genome Atlas, and the Gene Expression Omnibus (GEO) were used to assess the expression of CENPA in glioma. The results were validated by real-time quantitative polymerase chain reaction and immunohistochemical staining of clinical samples. The relationship between the expression and prognostic value of the CENPA gene in glioma was investigated by Kaplan–Meier (KM) survival analysis with RNA-seq and clinical profiles downloaded from the Chinese Glioma Genome Atlas (CGGA) and UCSC Xena. The association between CENPA and clinical characteristics was also evaluated. Cell Counting Kit-8 (CCK8) assay, wound healing assay using two glioma cell lines, gene set enrichment analysis (GSEA), KEGG and gene ontology (GO) enrichment analysis, immune infiltration analysis, temozolomide (TMZ) sensitivity analysis, and single-cell sequence analysis were performed to explore the underlying mechanisms of high CENPA expression and its effect on glioma development. Finally, we performed a Cox analysis based on the expression of CENPA to predict patient prognosis.

Results

CENPA was significantly upregulated in glioma tissue samples and correlated with patient prognosis. Moreover, the downregulation of CENPA inhibited the migration and proliferation of glioma cells. In addition, the expression level of CENPA was significantly correlated with the grade, primary–recurrent–secondary (PRS) type, IDH mutation status, and 1p19q codeletion status. Furthermore, CENPA could serve as an independent prognostic factor for glioma that mainly interferes with the normal progression of mitosis and regulates the tumor immune microenvironment favoring glioma development.

Conclusion

CENPA may act as a prognostic factor in patients with glioma and provide a novel target for the treatment of gliomas.

Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Prostate adenocarcinoma (PRAD) is a leading cause of death among men. Messenger ribonucleic acid (mRNA) vaccine presents an attractive approach to achieve satisfactory outcomes; however, tumor antigen screening and vaccination candidates show a bottleneck in this field. We aimed to investigate the tumor antigens for mRNA vaccine development and immune subtypes for choosing appropriate patients for vaccination. We identified eight overexpressed and mutated tumor antigens with poor prognostic value of PRAD, including KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3. The correlation of those genes with antigen-presenting immune cells were assessed. We further identified three immune subtypes of PRAD (PRAD immune subtype [PIS] 1-3) with distinct clinical, molecular, and cellular characteristics. PIS1 showed better survival and immune cell infiltration, nevertheless, PIS2 and PIS3 showed cold tumor features with poorer prognosis and higher tumor genomic instability. Moreover, these immune subtypes presented distinguished association with immune checkpoints, immunogenic cell death modulators, and prognostic factors of PRAD. Furthermore, immune landscape characterization unraveled the immune heterogeneity among patients with PRAD. To summarize, our study suggests KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3 are potential antigens for PRAD mRNA vaccine development, and patients in the PIS2 and PIS3 groups are more suitable for vaccination.

Clinical Significance and Underlying Mechanisms of CELSR3 in Metastatic Prostate Cancer Based on Immunohistochemistry, Data Mining, and In Silico Analysis

Background: The treatment and survival rate of patients with metastatic prostate cancer (MPCa) remain unsatisfactory. Herein, the authors investigated the clinical value and potential mechanisms of cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) in MPCa to identify novel targets for clinical diagnosis and treatment. Materials and Methods: mRNA microarray and RNA-Seq (n = 1246 samples) data were utilized to estimate CELSR3 expression and to assess its differentiation ability in MPCa. Similar analyses were performed with miRNA-221-3p. Immunohistochemistry performed on clinical samples were used to evaluate the protein expression level of CELSR3 in MPCa. Based on CELSR3 differentially coexpressed genes (DCEGs), enrichment analysis was performed to investigate potential mechanisms of CELSR3 in MPCa. Results: The pooled standard mean difference (SMD) for CELSR3 was 0.80, demonstrating that CELSR3 expression was higher in MPCa than in localized prostate cancer (LPCa). CELSR3 showed moderate potential to distinguish MPCa from LPCa. CELSR3 protein expression was found to be markedly upregulated in MPCa than in LPCa tissues. The authors screened 894 CELSR3 DCEGs, which were notably enriched in the focal adhesion pathway. miRNA-221-3p showed a significantly negative correlation with CELSR3 in MPCa. Besides, miRNA-221-3p expression was downregulated in MPCa than in LPCa (SMD = -1.04), and miRNA-221-3p was moderately capable of distinguishing MPCa from LPCa. Conclusions: CELSR3 seems to play a pivotal role in MPCa by affecting the focal adhesion pathway and/or being targeted by miRNA-221-3p.