Double-targeting CDCA8 and E2F1 inhibits the growth and migration of malignant glioma

CDCA8 and its multifaceted role in tumorigenesis

Human cell division cycle-associated 8 (CDCA8), also known as Borealin or Dasra-B, is a critical component of the vertebrate Chromosomal Passenger Complex (CPC). It plays a pivotal role in the segregation of sister chromatids during the cell cycle and is essential for preventing the formation of aneuploid chromosomes and ensuring successful cytokinesis. Numerous studies have demonstrated that CDCA8 is upregulated in various cancers, including hepatocellular carcinoma, lung cancer, glioma, and bladder cancer. By influencing key biological processes such as cell proliferation, apoptosis, invasion, and metastasis, CDCA8 drives tumor progression. Clinically, the expression of CDCA8 correlates closely with tumor staging and histological grading, providing significant prognostic value for patients with diverse cancers. Moreover, CDCA8 modulates tumor biology through multiple signaling pathways, including P53, PI3K/Akt, E2F/Rb, and mTOR. In summary, CDCA8 represents a promising diagnostic and therapeutic target across multiple cancer types and serves as a potential prognostic biomarker. This review highlights the critical roles of CDCA8 in cancer diagnosis, treatment, and prognosis, as well as the underlying mechanisms through which it exerts its effects. These insights offer a theoretical basis and research direction for early cancer diagnosis, targeted therapy, and prognostic evaluation.

Identification of exosome-related gene features in psoriasis and construction of a diagnostic model via integrated bioinformatics analysis

BACKGROUND

Psoriasis, a chronic inflammatory dermatosis, profoundly affects patients' well-being. Although exosomes are key in disease etiology, diagnostic potentials of associated genes are unclear. Our research targeted bioinformatics-based characterization of exosome-related genes and the development of a diagnostic model for psoriasis.

METHODS

Within GSE30999 dataset, an exosome-centric diagnostic model was formulated. Its diagnostic capability was appraised in GSE30999 and GSE14905 cohorts. Human keratinocytes (HaCaT) were used to construct psoriasis cell model. qRT-PCR was used to detect expression of diagnostic genes in the model. Construction of a protein-protein interaction network was undertaken, complemented by enrichment analyses. Comparative evaluation of immunological microenvironments between healthy controls and disease cohort was executed. Prospective miRNAs and transcription factors (TFs) were prognosticated using online prediction tools.

RESULTS

A distinctive diagnostic model with superior diagnostic performance, evidenced by an AUC value greater than 0.88, was unveiled. The model featured seven exosome-related biomarker genes (CCNA2, NDC80, CCNB1, CDCA8, KIF11, CENPF, and ASPM) interwoven in a complex network and chiefly linked in the regulation of Cell Cycle and Cellular Senescence. These genes were significantly overexpressed in psoriasis cell models. Immune infiltration analysis distinguished profound discrepancies (p < 0.05) in immunological microenvironment between disease and control groups with enrichment of T cells CD4 memory activated, Macrophages M1, and Neutrophils in the disease group. 11 miRNAs and 27 TFs were identified.

CONCLUSION

The study introduces a new and potent diagnostic model for psoriasis, with selection of credible exosome-associated biomarker genes. These discoveries aid in clinical diagnostics and research on exosome involvement in psoriasis.

LOCC: a novel visualization and scoring of cutoffs for continuous variables with hepatocellular carcinoma prognosis as an example

BACKGROUND

The interpretation of large datasets, such as The Cancer Genome Atlas (TCGA), for scientific and research purposes, remains challenging despite their public availability. In this study, we focused on identifying gene expression profiles most relevant to patient prognosis and aimed to develop a method and database to address this issue. To achieve this, we introduced Luo's Optimization Categorization Curve (LOCC), an innovative tool for visualizing and scoring continuous variables against dichotomous outcomes. To demonstrate the efficacy of LOCC using real-world data, we analyzed gene expression profiles and patient data from TCGA hepatocellular carcinoma samples.

RESULTS

To showcase LOCC, we demonstrate an optimal cutoff for E2F1 expression in hepatocellular carcinoma, which was subsequently validated in an independent cohort. Compared to ROC curves and their AUC, LOCC offered a superior description of the predictive value of E2F1 expression across various cancer types. The LOCC score, comprised of factors representing significance, range, and impact of the biomarker, facilitated the ranking of all gene expression profiles in hepatocellular carcinoma, aiding in the evaluation and understanding of previously published prognostic gene signatures. We also demonstrate that LOCC does not have the same assumptions required of Cox proportional hazards modeling for accurate analysis. Repeated sampling demonstrated that LOCC scores outperformed ROC's AUC in discriminating predictors from non-predictors. Additionally, gene set enrichment analysis revealed significant associations between certain genes and prognosis, such as E2F target genes and G2M checkpoint with poor prognosis, and bile acid metabolism and oxidative phosphorylation with good prognosis.

CONCLUSION

In summary, we present LOCC as a novel visualization tool for the analysis of gene expression in cancer, particularly for understanding and selecting cutoffs. Our findings suggest that LOCC scores, which effectively rank genes based on their prognostic potential, represent a more suitable approach than ROC curves and Cox proportional hazard for prognostic modeling and understanding in cancer gene expression analysis. LOCC holds promise as an invaluable tool for advancing precision medicine and furthering biomarker research. Further research regarding multivariable integration and validation will help LOCC reach its full potential and establish its utility across diverse cancer types and clinical settings.

CD133+/ABCC5+ cervical cancer cells exhibit cancer stem cell properties

Objective

This study explores the correlation between Forkhead box M1 (FOXM1) and ATP-binding cassette subfamily C member 5 (ABCC5) in relation to paclitaxel resistance in cervical cancer. It aims to identify potential cervical cancer stem cell markers, offering fresh perspectives for developing therapeutic strategies to overcome paclitaxel chemoresistance in cervical cancer.

Methods

Paclitaxel-resistant Hela cells (Hela/Taxol) were developed by intermittently exposing Hela cells to progressively increasing concentrations of paclitaxel. We assessed the biological properties of both Hela and Hela/Taxol cells using various assays: cell proliferation, clonogenic, cell cycle, apoptosis, scratch, and transwell. To determine which markers better represent tumor stem cells, we analyzed various known and potential stem cell markers in combination. Flow cytometry was employed to measure the proportion of positive markers in both parental and drug-resistant cell lines. Following statistical analysis to establish relative stability, CD133+ABCC5+ cells were sorted for further examination. Subsequent tests included sphere-forming assays and Western blot analysis to detect the presence of the stem cell-specific protein Sox2, aiding in the identification of viable cervical cancer stem cell markers.

Results

The Hela/Taxol cell line exhibited significantly enhanced proliferation, migration, and invasion capabilities compared to the Hela cell line, alongside a marked reduction in apoptosis rates (P < 0.01). Notably, proportions of CD44+, CD24+CD44+, ABCC5+, CD24+CD44+ABCC5+, CD44+ABCC5+, CD24+CD44+FOXM1+, CD44+FOXM1+, CD133+ABCC5+, and CD133+FOXM1+ were significantly higher (P < 0.05). Furthermore, the size and number of spheres formed byCD133+ABCC5+ cells were greater in the sorted Hela/Taxol line (P < 0.01), with increased expression of the stem cell marker Sox2 (P < 0.001).

Conclusion

The Hela/Taxol cells demonstrate increased tumoral stemness, suggesting that CD133+ABCC5+ may serve as a novel marker for cervical cancer stem cells.

Role of cell division cycle-associated proteins in regulating cell cycle and promoting tumor progression

The cell division cycle-associated protein (CDCA) family is important in regulating cell division. High CDCA expression is significantly linked to tumor development. This review summarizes clinical and basic studies on CDCAs conducted in recent decades. Furthermore, it systematically introduces the molecular expression and function, key mechanisms, cell cycle regulation, and roles of CDCAs in tumor development, cell proliferation, drug resistance, invasion, and metastasis. Additionally, it presents the latest research on tumor diagnosis, prognosis, and treatment targeting CDCAs. These findings are pivotal for further in-depth studies on the role of CDCAs in promoting tumor development and provide theoretical support for their application as new anti-tumor targets.

Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

CDCA8 Facilitates Tumor Proliferation and Predicts a Poor Prognosis in Hepatocellular Carcinoma

CDCA8 expression is abnormally high in a variety of cancers and involved in the biological process of tumor malignancy. In this study, we discovered that the expression of CDCA8 was up-regulated in hepatocellular carcinoma cancer (HCC) tissues and high levels of CDCA8 are associated with larger tumor size, higher AFP (α-fetoprotein) levels, and unfavorable prognosis. Cell functional experiments revealed that CDCA8 silencing remarkably inhibited proliferation and promoted apoptosis in SNU-387 and Hep-3B cells. The results of flow cytometry showed that CDCA8 regulated CDK1 and cyclin B1 expression to arrest at the S phase, inhibited proliferation, and promoted apoptosis. In addition, in vivo studies have confirmed that silencing CDCA8 could regulate CDK1/cyclin B1 signaling axis to inhibit the growth of HCC xenograft tumor. Our study demonstrated CDCA8 acts an oncogene to facilitate cell proliferation of HCC via regulating cell cycle, indicating the promising application value of CDCA8 for HCC diagnosis and clinical treatment.

Integrated bioinformatics analysis and experimental validation identified CDCA families as prognostic biomarkers and sensitive indicators for rapamycin treatment of glioma

The cell division cycle associated (CDCA) genes regulate the cell cycle; however, their relationship with prognosis in glioma has been poorly reported in the literature. The Cancer Genome Atlas (TCGA) was utilized to probe the CDCA family in relation to the adverse clinical features of glioma. Glioma single-cell atlas reveals specific expression of CDCA3, 4, 5, 8 in malignant cells and CDCA7 in neural progenitor cells (NPC)-like malignant cells. Glioma data from TCGA, the China Glioma Genome Atlas Project (CGGA) and the gene expression omnibus (GEO) database all demonstrated that CDCA2, 3, 4, 5, 7 and 8 are prognostic markers for glioma. Further analysis identified CDCA2, 5 and 8 as independent prognostic factors for glioma. Lasso regression-based risk models for CDCA families demonstrated that high-risk patients were characterized by high tumor mutational burden (TMB), low levels of microsatellite instability (MSI), and low tumor immune dysfunction and rejection (TIDE) scores. These pointed to immunotherapy for glioma as a potentially viable treatment option Further CDCA clustering suggested that the high CDCA subtype exhibited a high macrophage phenotype and was associated with a higher antigen presentation capacity and high levels of immune escape. In addition, hsa-mir-15b-5p was predicted to be common regulator of CDCA3 and CDCA4, which was validated in U87 and U251 cells. Importantly, we found that CDCAs may indicate response to drug treatment, especially rapamycin, in glioma. In summary, our results suggest that CDCAs have potential applications in clinical diagnosis and as drug sensitivity markers in glioma.

CDCA8 promotes bladder cancer survival by stabilizing HIF1α expression under hypoxia

Hypoxia is an essential hallmark of solid tumors and HIF1α is a central regulator of tumor cell adaptation and survival in the hypoxic environment. In this study, we explored the biological functions of cell cycle division-related gene 8 (CDCA8) in bladder cancer (BCa) cells in the hypoxic settings. Specifically, we found that CDCA8 was significantly upregulated in BCa cell lines and clinical samples and its expression was positively correlated with advanced BCa stage, grade, and poor overall survival (OS). The expression of CDCA8 proteins was required for BCa cells to survive in the hypoxic condition. Mechanistically, CDCA8 stabilizes HIF1α by competing with PTEN for AKT binding, consequently leading to PTEN displacement and activation of the AKT/GSK3β signaling cascade that stimulates HIF1α protein stability. Significantly, HIF1α proteins bind to CDCA8 promoter for transcriptional activation, forming a positive-feedback loop to sustain BCa tumor cells under oxygen-deficient environment. Together, we defined CDCA8 as a key regulator for BCa cells to sense and prevail oxygen deprivation and as a novel BCa therapeutic target.

Cell division cycle-associated 8 is a prognostic biomarker related to immune invasion in hepatocellular carcinoma

BACKGROUND

Cell division cycle-associated 8 (CDCA8) is involved in numerous signaling networks, and it serves a crucial modulatory function in multiple malignant tumors. However, its significance in prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains unclear.

MATERIALS AND METHODS

Herein, we examined the CDCA8 levels in tumor tissues, as well as its associated signaling pathways and correlation with immune infiltration. Additionally, we further clarified the prognostic significance of CDCA8 among HCC patients. HCC patient information was recruited from The Cancer Genome Atlas (TCGA). Using bioinformatics, the following parameters were analyzed among HCC patients: CDCA8 expression, enrichment analysis, immune infiltration, and prognosis analysis. Moreover, we employed in vitro investigations, such as, qRT-PCR, immunohistochemistry (IHC), and cell functional experiments to validate our results.

RESULTS

Elevated CDCA8 expression in HCC patients was markedly associated with T stage, pathological status (PS), tumor status (TS), histologic grade (HG), and AFP. Elevated CDCA8 expression HCC patients exhibited reduced overall survival (OS) (p < 0.001), disease-specific survival (DSS) (p < 0.001), and progress free interval (PFI) H(p < 0.001). According to the ROC analysis, the area under the curve (AUC) was 0.997. Multivariate analysis revealed that CDCA8 was a stand-alone prognostic indicator of patient OS (p = 0.009) and DSS (p = 0.006). A nomogram was then generated based on the multivariate analysis, and the C-indexes and calibration chart revealed excellent predictive performance in determining HCC patient outcome. Based on the GSEA analysis, CDCA8 modulated the P53, Notch, PPAR, E2F networks. We observed a direct link between CDCA8 levels and Th2 and T helper cells, and a negative link between CDCA8 levels and dendritic cells (DC), neutrophils, cytotoxic cells, and CD8 T cells. Furthermore, CDCA8 deficiency inhibited liver cancer cell proliferation and invasion.

CONCLUSION

In conclusion, these findings indicate that CDCA8 is a new molecular bioindicator of HCC patient prognosis, and it is an excellent candidate for therapeutic target against HCC.

CDCA8 induced by NF-YA promotes hepatocellular carcinoma progression by regulating the MEK/ERK pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors. Cell division cycle associated 8 (CDCA8) is an important multifactorial regulator in cancers. However, its up and downstream targets and effects in HCC are still unclear.

METHODS

A comprehensive bioinformatics analysis was performed using The Cancer Genome Atlas dataset (TCGA) to explore novel core oncogenes. We quantified CDCA8 levels in HCC tumors using qRT-PCR. HCC cell's proliferative, migratory, and invasive abilities were detected using a Cell Counting Kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, clone formation, and a Transwell assay. An orthotopic tumor model and tail vein model were constructed to determine the effects of CDCA8 inhibition in vivo. The mechanism underlying CDCA8 was investigated using RNA sequencing. The prognostic value of CDCA8 was assessed with immunohistochemical staining of the tissue microarrays.

RESULTS

CDCA8 was identified as a novel oncogene during HCC development. The high expression of CDCA8 was an independent predictor for worse HCC outcomes both in publicly available datasets and in our cohort. We found that CDCA8 knockdown inhibited HCC cell proliferation, colony formation, and migration by suppressing the MEK/ERK pathway in vitro. Moreover, CDCA8 deficiency significantly inhibited tumorigenesis and metastasis. Next-generation sequencing and laboratory validation showed that CDCA8 silencing inhibited the expression of TPM3, NECAP2, and USP13. Furthermore, NA-YA overexpression upregulated the expression of CDCA8. CDCA8 knockdown could attenuate NF-YA-mediated cell invasion in vitro. The expression of NF-YA alone or in combined with CDCA8 were validated as significant independent risk factors for patient survival.

CONCLUSION

Our findings revealed that the expression of CDCA8 alone or in combined with NF-YA contributed to cancer progression, and could serve as novel potential therapeutic targets for HCC patients.

A necroptosis-related lncRNA signature was identified to predict the prognosis and immune microenvironment of IDH-wild-type GBM

Introduction

Necroptosis-related genes are essential for the advancement of IDH-wild-type GBM. However, the putative effects of necroptosis-related lncRNAs (nrlncRNAs) in IDH-wild-type GBM remain unknown.

Methods

By using the TCGA and GTEx databases, a nrlncRNA prognostic signature was created using LASSO Cox regression. The median risk score was used to categorize the patients into low and high-risk groups. To confirm the validity, univariate, multivariate Cox regression and ROC curves were used. Furthermore, by enrichment analysis, immune correlation analysis, and drug sensitivity analysis, the targeted lncRNAs were selected for further verification. As the highest upregulated expression in tumor than peritumor specimens, RP11-131L12.4 was selected for phenotype and functional experiments in primary GBM cells.

Results

Six lncRNAs were proved to be closely related to necroptosis in IDH-1-wild-type GBM, which were used to create a new signature. For 1-, 2-, and 3-year OS, the AUCs were 0.709, 0.645 and 0.694, respectively. Patients in the low-risk group had a better prognosis, stronger immune function activity, and more immune cell infiltration. In contrast, enrichment analysis revealed that the malignant phenotype was more prevalent in the high-risk group. In vitro experiments indicated that RP11-131L12.4 increased the tumor proliferation, migration and invasion, but decreased the necroptosis. Moreover, this nrlncRNA was also proved to be negatively associated with patient prognosis.

Conclusion

The signature of nrlncRNAs may aid in the formulation of tailored and precise treatment for individuals with IDH-wild-type GBM. RP11-131L12.4 may play indispensable role in necroptosis suppression.

CLSPN is a potential biomarker associated with poor prognosis in low-grade gliomas based on a multi-database analysis

BACKGROUND

The oncogene CLSPN, also known as claspin, has regulatory effects in a variety of tumours; however, it is not clear whether CLSPN is a therapeutic target in low-grade gliomas (LGG). In this study, the prognostic value of CLSPN in LGG and its role as an immunotherapeutic target were evaluated.

METHODS

Transcriptome and methylation data for thousands of patients with glioma were collected from various databases, including The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gene Expression Omnibus. Subsequently, a series of bioinformatics methods were used to evaluate the relationships between CLSPN and prognosis, clinical features, methylation status, immune cells, and molecular signaling pathways in LGG.

RESULTS

CLSPN expression levels were positively correlated with major malignant characteristics of LGG, and low expression of CLSPN was associated with a better prognosis. The methylation sites cg04263115 and cg06100291 negatively regulated the expression of CLSPN, and increased methylation levels at these sites were related to a longer survival time in patients with LGG. CLSPN was positively correlated with tumour-infiltrating immune cells and showed high copy number variation in these cells. There was a positive regulatory relationship between CLSPN expression and programmed death-1 (PD-1) and programmed cell death ligand 1 (PD-L1). A gene set enrichment analysis revealed that CLSPN activates a variety of cancer signaling pathways.

CONCLUSION

CLSPN was identified as an independent risk factor for LGG with excellent prognostic value.

Decorin inhibits proliferation and metastasis in human bladder cancer cells by upregulating P21

Migration of bladder cancer (BC) cells poses a substantial threat to human health. It is critical to elucidate the mechanism of BC invasion and progression for surgical treatment and the prognosis of patients. Decorin is of interest as an anticancer treatment that can play a vital role in regulating tumorigenesis. The effect of decorin expression on survival in clinical patients was screened and analyzed using bladder urothelial carcinoma data from the Cancer Genome Atlas (TCGA) database. The differential expression of transforming growth factor-β1 (TGF-β1) in tumors was compared against that of normal samples to analyze the correlation between them. MTT, flow cytometry, and Wound/Transwell assays were used to detect cell proliferation, cycle arrest, apoptosis, migration, and invasion. Analysis of TCGA data showed that decorin expression was significantly lower in bladder urothelial carcinoma samples than in normal tissues, while TGF-β1 expression did not change significantly. We found that decorin was correlated with TGF-β1 expression in bladder urothelial cancer. In addition, decorin blocked the G1/S phase by upregulating p21 protein and inhibiting the expression of TGF-β1 and MMP2, promoting the occurrence of apoptosis and inhibiting the proliferation of human BC T24 cells. Moreover, decorin increased the adhesion of tumor cells in vitro, and effectively inhibited cell metastasis. Decorin regulated the expression of TGF-β1 and MMP2 through p21 protein, promoted apoptosis and adhesion, and inhibited the proliferation and metastasis of BC cells.

Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer

Purpose

Glioma is the most common primary cranial brain tumor that arises from the cancelation of glial cells (which can be in the brain or spinal cord). It is due to innate genetic risk factors or induced by a carcinogenic environment. If left untreated, the disease has a poor prognosis.

Methods

In this study, we downloaded glioma data from TCGA database and GEO (GSE4412). The GSEA database was used to screen tumor microenvironment-related gene sets. Cancer subtypes were classified by GSVA enrichment method.

Results

By GSVA enrichment analysis, we obtain three Gliomas cancer subtypes. After further survival prognosis analysis and biological function analysis, we obtained 13 tumor microenvironment gene sets and 14 core genes that affect patients' survival prognosis, and these genes have the potential to become targets for targeted therapies and disease detection.

Conclusion

We screened a total of 13 gene sets through a series of enrichment analyses, statistical and prognostic analyses, etc. Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.

Developing an Immune-Related Signature for Predicting Survival Rate and the Response to Immune Checkpoint Inhibitors in Patients With Glioma

Background: Glioma is one of the most aggressive cancer types affecting the central nerve system, with poor overall survival (OS) rates. The present study aimed to construct a novel immune-related signature to predict prognosis and the efficiency of immunotherapy in patients with glioma.

Methods: The mRNA expression data and other clinical information of patients with glioblastoma multiforme (GBM) and low grade glioma (LGG) were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The immune-related genes were obtained from the Immunology Database and Analysis Portal database. Subsequently, an immune-related signature was created following the results obtained from the Least Absolute Shrinkage and Selection Operator regression model. To validate the predictability of the signature, Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves were created. Moreover, both univariate and multivariate analyses were carried out using the OS between this signature and other clinicopathologic factors, and a nomogram was constructed. In addition, the association between signature, immune cell infiltration, tumor mutation burden and immunophenoscore were determined.

Results: Results of the present study using 118 GBM and LGG samples uncovered 15 immune-related genes that were also differently expressed in glioma samples. These were subsequently used to construct the immune-related signature. This signature exhibits the ability to predict prognosis, the infiltration of immune cells in the tumor microenvironment and the response of patients with glioma to immunotherapy.

Conclusion: Results of the present study demonstrated that the aforementioned novel immune-related signature may accurately predict prognosis and the response of patients with glioma to immunotherapy.

Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis

Improved insight into the molecular mechanisms of triple negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify key genes which may affect the prognosis of TNBC patients by bioinformatic analysis. In our study, the RNA sequencing (RNA-seq) expression data of 116 breast cancer lacking ER, PR, and HER2 expression and 113 normal tissues were downloaded from The Cancer Genome Atlas (TCGA). We screened out 147 differentially co-expressed genes in TNBC compared to non-cancerous tissue samples by using weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were constructed, revealing that 147 genes were mainly enriched in nuclear division, chromosomal region, ATPase activity, and cell cycle signaling. After using Cytoscape software for protein-protein interaction (PPI) network analysis and LASSO feature selection, a total of fifteen key genes were identified. Among them, BUB1 and CENPF were significantly correlated with the overall survival rate (OS) difference of TNBC patients (p value < 0.05). In addition, BUB1, CCNA2, and PACC1 showed significant poor disease-free survival (DFS) in TNBC patients (p value < 0.05), and may serve as candidate biomarkers in TNBC diagnosis. Thus, our results collectively suggest that BUB1, CCNA2, and PACC1 genes could play important roles in the progression of TNBC and provide attractive therapeutic targets.

Bioinformatic Analyses and Experimental Verification Reveal that High FSTL3 Expression Promotes EMT via Fibronectin-1/α5β1 Interaction in Colorectal Cancer

Background: Colorectal cancer (CRC) is a typical cancer prevalent worldwide. Despite the conventional treatments, CRC has a poor prognosis due to relapse and metastasis. Moreover, there is a dearth of sensitive biomarkers for predicting prognosis in CRC.

Methods: This study used a bioinformatics approach combining validation experiments to examine the value of follistatin-like 3 (FSTL3) as a prognostic predictor and therapeutic target in CRC.

Results:FSTL3 was remarkably upregulated in the CRC samples. FSTL3 overexpression was significantly associated with a poor prognosis. FSTL3 was found to activate the epithelial-mesenchymal transition by promoting the binding of FN1 to α5β1. FSTL3 expression was also positively correlated with the abundance of the potent immunosuppressors, M2 macrophages.

Conclusion:FSTL3 overexpression affects CRC prognosis and thus, FSTL3 can be a prognostic biomarker and therapeutic target with potential applications in CRC.

FGF14-AS2 accelerates tumorigenesis in glioma by forming a feedback loop with miR-320a/E2F1 axis

Glioma is the most common primary tumour in the central nervous system in adults, and at present, there is no effective treatment to cure this malignancy. Long noncoding RNAs (lncRNAs) are closely related to tumour progression and have attracted increasing attention in tumour research. However, the role of lncRNA FGF14-AS2 in glioma tumorigenesis has not been determined. In the present study, we found that FGF14-AS2 expression was significantly elevated in glioma tissues and was associated with poor survival in glioma patients. Silencing FGF14-AS2 inhibited the proliferation, migration and invasion ability of glioma cells. In vivo assay showed that silencing FGF14-AS2 led to inhibition of tumour growth. In addition, FGF14-AS2 was observed to promote glioma progression via the miR-320a/E2F1 axis. Moreover, E2F1 could bind to the promoter region of FGF14-AS2, thereby enhancing FGF14-AS2 expression. In conclusion, FGF14-AS2 could accelerate tumorigenesis of glioma by forming a feedback loop with the miR-320a/E2F1 axis which suggested that FGF14-AS2 could serve as a therapeutic target for glioma.