Identification of metastasis and prognosis-associated genes for serous ovarian cancer

Transcriptome Analysis Suggests PKD3 Regulates Proliferative Glucose Metabolism, Calcium Homeostasis and Microtubule Dynamics After MEF Spontaneous Immortalization

Cell immortalization corresponds to a biologically relevant clinical feature that allows cells to acquire a high proliferative potential during carcinogenesis. In multiple cancer types, Protein Kinase D3 (PKD3) has often been reported as a dysregulated oncogenic kinase that promotes cell proliferation. Using mouse embryonic fibroblasts (MEFs), in a spontaneous immortalization model, PKD3 has been demonstrated as a critical regulator of cell proliferation after immortalization. However, the mechanisms by which PKD3 regulates proliferation in immortalized MEFs require further elucidation. Using a previously validated Prkd3-deficient MEF model, we performed a poly-A transcriptomic analysis to identify putative Prkd3-regulated biological processes and downstream targets in MEFs after spontaneous immortalization. To this end, differentially expressed genes (DEGs) were identified and further analyzed by gene ontology (GO) enrichment and protein-protein interaction (PPI) network analyses to identify potential hub genes. Our results suggest that Prkd3 modulates proliferation through the regulation of gene expression associated with glucose metabolism (Tnf, Ucp2, Pgam2, Angptl4), calcium homeostasis and transport (Calcr and P2rx7) and microtubule dynamics (Stmn2 and Map10). These candidate processes and associated genes represent potential mechanisms involved in Prkd3-induced proliferation in spontaneously immortalized cells as well as clinical targets in several cancer types.

DCAF13 promotes ovarian cancer progression by activating FRAS1-mediated FAK signaling pathway

Cullin-RING ubiquitin ligase 4 (CRL4) is closely correlated with the incidence and progression of ovarian cancer. DDB1- and CUL4-associated factor 13 (DCAF13), a substrate-recognition protein in the CRL4 E3 ubiquitin ligase complex, is involved in the occurrence and development of ovarian cancer. However, its precise function and the underlying molecular mechanism in this disease remain unclear. In this study, we confirmed that DCAF13 is highly expressed in human ovarian cancer and its expression is negatively correlated with the overall survival rate of patients with ovarian cancer. We then used CRISPR/Cas9 to knockout DCAF13 and found that its deletion significantly inhibited the proliferation, colony formation, and migration of human ovarian cancer cells. In addition, DCAF13 deficiency inhibited tumor proliferation in nude mice. Mechanistically, CRL4-DCAF13 targeted Fraser extracellular matrix complex subunit 1 (FRAS1) for polyubiquitination and proteasomal degradation. FRAS1 influenced the proliferation and migration of ovarian cancer cell through induction of the focal adhesion kinase (FAK) signaling pathway. These findings collectively show that DCAF13 is an important oncogene that promotes tumorigenesis in ovarian cancer cells by mediating FRAS1/FAK signaling. Our findings provide a foundation for the development of targeted therapeutics for ovarian cancer.

Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer

Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes-C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)-emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.

Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value

BACKGROUND

Ovarian cancer (OC) is a severe gynecological malignancy with significant diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be used to adjust diagnosis and improve patient care. However, serous OC lacks effective biomarkers. We aimed to identify novel biomarkers for OC and their pathogenic causes.

METHODS

The present study used the differentially expressed genes (DEGs) obtained from the "Limma" package and WGCNA modules for intersection analysis to obtain DEGs in OC. Three hub genes were identified-claudin 3 (CLDN3), interferon regulatory factor 6 (IRF6), and prostasin (PRSS8)-by searching for hub genes through the PPI network and verifying them in GSE14407, GSE18520, GSE66957, and TCGA + GTEx databases. The correlation between IRF6 and the prognosis of OC patients was further confirmed in Kaplan-Miller Plotter. RT-qPCR and IHC confirmed the RNA and protein levels of IRF6 in the OC samples. The effect of IRF6 on OC was explored using transwell invasion and scratch wound assays. Finally, we constructed a ceRNA network of hub genes and used bioinformatics tools to predict drug sensitivity.

RESULTS

The joint analysis results of TCGA, GTEx, and GEO databases indicated that IRF6 RNA and protein levels were significantly upregulated in serous OC and were associated with OS and PFS. Cell function experiments revealed that IRF6 knockdown inhibited SKOV3 cell proliferation, migration and invasion.

CONCLUSION

IRF6 is closely correlated with OC development and progression and could be considered a novel biomarker and therapeutic target for OC patients.

Metastasis-Related Signature for Clinically Predicting Prognosis and Tumor Immune Microenvironment of Osteosarcoma Patients

Osteosarcoma is the most prevalent clinical malignant bone tumor in adolescents. The prognosis of metastatic osteosarcoma is still very poor. The aim of our study was to investigate the clinical diagnosis and prognostic significance of metastasis related genes (MRGs) in patients with osteosarcoma. Clinical information and RNA sequencing data with osteosarcoma patients were obtained and set as the training set from UCSC databases. GSE21257 were downloaded and chosen as the verification cohort. An eight gene metastasis related risk signature including MYC, TAC4, ABCA4, GADD45GIP1, TNFRSF21, HERC5, MAGEA11, and PDE1B was built to predict the overall survival of osteosarcoma patients. Based on risk assessments, patients were classified into high- and low-risk groups. The high-risk patients had higher risk score and shorter survival time. ROC curves revealed that this risk signature can accurately predict survival times of osteosarcoma patients at the 1-, 2-, 3-, 4- and 5- year. GSEA revealed that MYC targets, E2F targets, mTORC1 signaling, Wnt /β-catenin signaling and cell cycle were upregulated, and cell adhesion molecules, and primary immunodeficiency were decreased in high-risk group. MRGs were highly linked with the tumor immune microenvironment and ICB response. These results identified that MRGs as a novel prognostic and diagnostic biomarker in osteosarcoma.

Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers worldwide. The molecular mechanisms of serous ovarian cancer (SOC) remain unclear and not well understood. SOC cases are primarily diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to obtain a better understanding of precise molecular mechanisms and to identify the chromosome instability region and key driver genes in the carcinogenesis and progression of SOC. Whole-exome sequencing was performed on the normal ovarian cell line IOSE80 and the EOC cell lines SKOV3 and A2780. The single-nucleotide variation burden, distribution, frequency and signature followed the known ovarian mutation profiles, without chromosomal bias. Recurrently mutated ovarian cancer driver genes, including LRP1B, KMT2A, ARID1A, KMT2C and ATRX were also found in two cell lines. The genome distribution of copy number alterations was found by copy number variation (CNV) analysis, including amplification of 17q12 and 4p16.1 and deletion of 10q23.33. The CNVs of MED1, GRB7 and MIEN1 located at 17q12 were found to be correlated with the overall survival of SOC patients (MED1: p = 0.028, GRB7: p = 0.0048, MIEN1: p = 0.0051), and the expression of the three driver genes in the ovarian cell line IOSE80 and EOC cell lines SKOV3 and A2780 was confirmed by western blot and cell immunohistochemistry.

Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis

Background. Bladder cancer (BLCA) is a highly malignant tumor that develops in the urinary system. Identification of biomarkers in progression and prognosis is crucial for the treatment of BLCA. BLCA-related differentially expressed genes (DEGs) were authenticated by screening the DEGs and weighted gene coexpression network analysis (WGCNA). LASSO and SVM-RFE algorithms were utilized to screen the feature genes in BLCA. Survival analysis was performed using the Kaplan–Meier curve provided by the ‘survival' R package. The BLCA samples were clustered by hclust based on the immune score matrix calculated by the single-sample GSEA (ssGSEA) algorithm. The immune, stromal, and ESTIMATE scores of each BLCA patient were calculated by applying the ESTIMATE algorithm. ssGSEA was conducted to explore the function of characteristic genes in BLCA. The expression of characteristic genes in clinical cancer tissue, and the pericancerous tissue of BLCA patients was verified using qRT-PCR assays. A total of 189 BLCA-related DEGs were identified. Fourteen feature genes were defined by LASSO and SVM-RFE algorithms. Five characteristic genes, including SMYD2, GAPDHP1, ATP1A2, CILP, and THSD4, were related to the OS of BLCA. The correlation analysis of five characteristic genes and clinicopathological factors showed that five genes played a role in the progression of BLCA. Additionally, the expression of five characteristic genes in clinical cancer tissues and pericarcinomatous tissues from BLCA patients was verified by qRT-PCR, which was consistent with the result from the public database. Finally, we discovered five prognostic genes linked to BLCA progression, which might serve as a theoretical basis for prognosis and treatment targets for BLCA patients.

Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma

Neuroblastoma (NB), which is the most common pediatric extracranial solid tumor, varies widely in its clinical presentation and outcome. NB has a unique ability to spontaneously differentiate and regress, suggesting a potential direction for therapeutic intervention. However, the underlying mechanisms of regression remain largely unknown, and more reliable prognostic biomarkers are needed for predicting trajectories for NB. We performed scRNA-seq analysis on 17 NB clinical samples and three peritumoral adrenal tissues. Primary NB displayed varied cell constitution, even among tumors of the same pathological subtype. Copy number variation patterns suggested that neuroendocrine cells represent the malignant cell type. Based on the differential expression of sets of related marker genes, a subgroup of neuroendocrine cells was identified and projected to differentiate into a subcluster of benign fibroblasts with highly expressed CCL2 and ZFP36, supporting a progressive pathway of spontaneous NB regression. We also identified prognostic markers (STMN2, TUBA1A, PAGE5, and ETV1) by evaluating intra-tumoral heterogeneity. Lastly, we determined that ITGB1 in M2-like macrophages was associated with favorable prognosis and may serve as a potential diagnostic marker and therapeutic target. In conclusion, our findings reveal novel mechanisms underlying regression and potential prognostic markers and therapeutic targets of NB.

CpG-binding protein CFP1 promotes ovarian cancer cell proliferation by regulating BST2 transcription

Epigenetic alterations have been functionally linked to ovarian cancer development and occurrence. The CXXC zinc finger protein 1 (CFP1) is an epigenetic regulator involved in DNA methylation and histone modification in mammalian cells. However, its role in ovarian cancer cells is unknown. Here, we show that CFP1 protein is highly expressed in human ovarian cancer tissues. Loss of CFP1 inhibited the growth of human ovarian cancer cells, promoted apoptosis, and increased senescence. CFP1 knockdown resulted in reduced levels of SETD1 (a CFP1 partner) and histone H3 trimethylation at the fourth lysine residue (H3K4me3). RNA-sequencing revealed that deletion of CFP1 resulted in mRNA reduction of bone marrow stromal cell antigen 2 (BST2). Bioinformatics analysis and chromatin immunoprecipitation showed that CFP1 binds to the promoter of BST2 and regulates its transcription directly. Overexpression of BST2 rescued the growth inhibitory effect of CFP1 loss. Furthermore, depletion of cullin-RING ubiquitin ligases 4 (CRL4) components ROC1 or CUL4A had significantly inhibited the expression of CFP1 and BST2 similar to MLN4924 treatment that blocked cullin neddylation and inactivated CRL4s. In conclusion, CFP1 promotes ovarian cancer cell proliferation and apoptosis by regulating the transcription of BST2, and the expression of CFP1 was affected by CRL4 ubiquitin ligase complex.

Network-based approach to identify prognosis-related genes in tamoxifen-treated patients with estrogen receptor-positive breast cancer

Tamoxifen is an estrogen receptor (ER) antagonist that is most commonly used for the treatment of ER-positive breast cancer. However, tamoxifen resistance remains a major cause of cancer recurrence and progression. Here, we aimed to identify hub genes implicated in the progression and prognosis of ER-positive breast cancer following tamoxifen treatment. Microarray data (GSE9893) for 155 tamoxifen-treated primary ER-positive breast cancer samples were obtained from the Gene Expression Omnibus database. In total, 1706 differentially expressed genes (DEGs), including 859 up-regulated and 847 down-regulated genes, were identified between relapse and relapse-free samples. Weighted correlation network analysis clustered genes into 13 modules, among which the tan and blue modules were the most significantly related to prognosis. From these two modules, we further identified and validated two prognosis-related hub genes (G-rich RNA sequence binding factor 1 (GRSF1) and microtubule-associated protein τ (MAPT)) via survival analysis based on several publicly available datasets. High expression of GRSF1 predicted poor prognosis, whereas MAPT indicated favorable outcomes in ER-positive breast cancer. Using breast cancer cell lines and tissue samples, we confirmed that GRSF1 was significantly up-regulated and MAPT was down-regulated in the tamoxifen-resistant group compared with the tamoxifen-sensitive group. The prognostic value of GRSF1 and MAPT was also verified in 48 tamoxifen-treated ER-positive breast cancer patients in our hospital. Gene set enrichment analysis (GSEA) suggested that GRSF1 was potentially involved in RNA degradation and cell cycle pathways, while MAPT was strongly linked to immune-related signaling pathways. Taken together, our findings established novel prognostic biomarkers to predict tamoxifen sensitivity, which may facilitate individualized management of breast cancer.

Progress on the study of the anticancer effects of artesunate

Artesunate (ART) is a derivative of artemisinin that is extracted from the wormwood plant Artemisia annua. ART is an antimalarial drug that has been shown to be safe and effective for clinical use. In addition to its antimalarial properties, ART has been attracting attention over recent years due to its reported inhibitory effects on cancer cell proliferation, invasion and migration. Therefore, ART has a wider range of potential clinical applications than first hypothesized. The aim of the present review was to summarize the latest research progress on the possible anticancer effects of ART, in order to lay a theoretical foundation for the further development of ART as a therapeutic option for cancer.

A Comprehensive Analysis of the Downregulation of miRNA-1827 and Its Prognostic Significance by Targeting SPTBN2 and BCL2L1 in Ovarian Cancer

Background: Previous studies demonstrated that miRNA-1827 could repress various cancers on proliferation, angiogenesis, and metastasis. However, little attention has been paid to its role in ovarian cancer as a novel biomarker or intervention target, especially its clinical significance and underlying regulatory network.

Methods: A meta-analysis of six microarrays was adopted here to determine the expression trend of miRNA-1827, and was further validated by gene expression profile data and cellular experiments. We explored the functional annotations through enrichment analysis for the differentially expressed genes targeted by miRNA-1827. Subsequently, we identified two hub genes, SPTBN2 and BCL2L1, based on interaction analysis using two online archive tools, miRWALK (it consolidates the resources of 12 miRNA-focused servers) and Gene Expression Profiling Interactive Analysis (GEPIA). Finally, we validated their characteristics and clinical significance in ovarian cancer.

Results: The comprehensive meta-analysis revealed that miRNA-1827 was markedly downregulated in clinical and cellular specimens. Transfection of the miRNA-1827 mimic could significantly inhibit cellular proliferation. Concerning its target genes, they were involved in diverse biological processes related to tumorigenesis, such as cell proliferation, migration, and the apoptosis signaling pathway. Moreover, interaction analysis proved that two hub genes, SPTBN2 and BCL2L1, were highly associated with poor prognosis in ovarian cancer.

Conclusion: These integrated bioinformatic analyses indicated that miRNA-1827 was dramatically downregulated in ovarian cancer as a tumor suppressor. The upregulation of its downstream modulators, SPTBN2 and BCL2L1, was associated with an unfavorable prognosis. Thus, the present study has identified miRNA-1827 as a potential intervention target for ovarian cancer based on our bioinformatic analysis processes.

STMN2 mediates nuclear translocation of Smad2/3 and enhances TGFβ signaling by destabilizing microtubules to promote epithelial-mesenchymal transition in hepatocellular carcinoma

Metastasis remains the major obstacle of improving the survival of patients with hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) is critical to cancer metastasis. Successful induction of EMT requires dramatic cytoskeleton rearrangement. However, the significance of microtubule (MT), one of the core components of cell cytoskeleton, in this process remains largely unknown. Here we revealed that STMN2, an important MT dynamics regulator, is barely expressed in normal live tissues but markedly up-regulated in HCCs, especially in those with early recurrence. High STMN2 expression correlates with aggressive clinicopathological features and predicts poor prognosis of HCC patients. STMN2 overexpression in HCC cells promotes EMT, invasion and metastasis in vitro and in vivo, whereas STMN2 knockdown has opposite results. Mechanistically, STMN2 modulates MTs disassembly, disrupts MT-Smad complex, and facilitates release from MT network, phosphorylation and nuclear translocation of Smad2/3 even independent of TGFβ stimulation, thereby enhancing TGFβ signaling. Collectively, STMN2 orchestrates MT disassembly to facilitate EMT via TGF-β signaling, providing a novel insight into the mechanisms underlying cancer metastasis. STMN2 is a promising prognostic biomarker and potential therapeutic target for HCC.